Academic Appointments


Professional Education


  • PhD, Stanford University, Health Policy (2024)
  • ScB, Brown University, Biology (2014)

All Publications


  • Forecasting the effects of smoking prevalence scenarios on years of life lost and life expectancy from 2022 to 2050: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet. Public health 2024; 9 (10): e729-e744

    Abstract

    Smoking is the leading behavioural risk factor for mortality globally, accounting for more than 175 million deaths and nearly 4·30 billion years of life lost (YLLs) from 1990 to 2021. The pace of decline in smoking prevalence has slowed in recent years for many countries, and although strategies have recently been proposed to achieve tobacco-free generations, none have been implemented to date. Assessing what could happen if current trends in smoking prevalence persist, and what could happen if additional smoking prevalence reductions occur, is important for communicating the effect of potential smoking policies.In this analysis, we use the Institute for Health Metrics and Evaluation's Future Health Scenarios platform to forecast the effects of three smoking prevalence scenarios on all-cause and cause-specific YLLs and life expectancy at birth until 2050. YLLs were computed for each scenario using the Global Burden of Disease Study 2021 reference life table and forecasts of cause-specific mortality under each scenario. The reference scenario forecasts what could occur if past smoking prevalence and other risk factor trends continue, the Tobacco Smoking Elimination as of 2023 (Elimination-2023) scenario quantifies the maximum potential future health benefits from assuming zero percent smoking prevalence from 2023 onwards, whereas the Tobacco Smoking Elimination by 2050 (Elimination-2050) scenario provides estimates for countries considering policies to steadily reduce smoking prevalence to 5%. Together, these scenarios underscore the magnitude of health benefits that could be reached by 2050 if countries take decisive action to eliminate smoking. The 95% uncertainty interval (UI) of estimates is based on the 2·5th and 97·5th percentile of draws that were carried through the multistage computational framework.Global age-standardised smoking prevalence was estimated to be 28·5% (95% UI 27·9-29·1) among males and 5·96% (5·76-6·21) among females in 2022. In the reference scenario, smoking prevalence declined by 25·9% (25·2-26·6) among males, and 30·0% (26·1-32·1) among females from 2022 to 2050. Under this scenario, we forecast a cumulative 29·3 billion (95% UI 26·8-32·4) overall YLLs among males and 22·2 billion (20·1-24·6) YLLs among females over this period. Life expectancy at birth under this scenario would increase from 73·6 years (95% UI 72·8-74·4) in 2022 to 78·3 years (75·9-80·3) in 2050. Under our Elimination-2023 scenario, we forecast 2·04 billion (95% UI 1·90-2·21) fewer cumulative YLLs by 2050 compared with the reference scenario, and life expectancy at birth would increase to 77·6 years (95% UI 75·1-79·6) among males and 81·0 years (78·5-83·1) among females. Under our Elimination-2050 scenario, we forecast 735 million (675-808) and 141 million (131-154) cumulative YLLs would be avoided among males and females, respectively. Life expectancy in 2050 would increase to 77·1 years (95% UI 74·6-79·0) among males and 80·8 years (78·3-82·9) among females.Existing tobacco policies must be maintained if smoking prevalence is to continue to decline as forecast by the reference scenario. In addition, substantial smoking-attributable burden can be avoided by accelerating the pace of smoking elimination. Implementation of new tobacco control policies are crucial in avoiding additional smoking-attributable burden in the coming decades and to ensure that the gains won over the past three decades are not lost.Bloomberg Philanthropies and the Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S2468-2667(24)00166-X

    View details for PubMedID 39366729

    View details for PubMedCentralID PMC11447278

  • Bias-Adjusted Predictions of County-Level Vaccination Coverage from the COVID-19 Trends and Impact Survey. Medical decision making : an international journal of the Society for Medical Decision Making Reitsma, M. B., Rose, S., Reinhart, A., Goldhaber-Fiebert, J. D., Salomon, J. A. 2023: 272989X231218024

    Abstract

    BACKGROUND: The potential for selection bias in nonrepresentative, large-scale, low-cost survey data can limit their utility for population health measurement and public health decision making. We developed an approach to bias adjust county-level COVID-19 vaccination coverage predictions from the large-scale US COVID-19 Trends and Impact Survey.DESIGN: We developed a multistep regression framework to adjust for selection bias in predicted county-level vaccination coverage plateaus. Our approach included poststratification to the American Community Survey, adjusting for differences in observed covariates, and secondary normalization to an unbiased reference indicator. As a case study, we prospectively applied this framework to predict county-level long-run vaccination coverage among children ages 5 to 11y. We evaluated our approach against an interim observed measure of 3-mo coverage for children ages 5 to 11y and used long-term coverage estimates to monitor equity in the pace of vaccination scale up.RESULTS: Our predictions suggested a low ceiling on long-term national vaccination coverage (46%), detected substantial geographic heterogeneity (ranging from 11% to 91% across counties in the United States), and highlighted widespread disparities in the pace of scale up in the 3 mo following Emergency Use Authorization of COVID-19 vaccination for 5- to 11-y-olds.LIMITATIONS: We relied on historical relationships between vaccination hesitancy and observed coverage, which may not capture rapid changes in the COVID-19 policy and epidemiologic landscape.CONCLUSIONS: Our analysis demonstrates an approach to leverage differing strengths of multiple sources of information to produce estimates on the time scale and geographic scale necessary for proactive decision making.IMPLICATIONS: Designing integrated health measurement systems that combine sources with different advantages across the spectrum of timeliness, spatial resolution, and representativeness can maximize the benefits of data collection relative to costs.HIGHLIGHTS: The COVID-19 pandemic catalyzed massive survey data collection efforts that prioritized timeliness and sample size over population representativeness.The potential for selection bias in these large-scale, low-cost, nonrepresentative data has led to questions about their utility for population health measurement.We developed a multistep regression framework to bias adjust county-level vaccination coverage predictions from the largest public health survey conducted in the United States to date: the US COVID-19 Trends and Impact Survey.Our study demonstrates the value of leveraging differing strengths of multiple data sources to generate estimates on the time scale and geographic scale necessary for proactive public health decision making.

    View details for DOI 10.1177/0272989X231218024

    View details for PubMedID 38159263

  • Examining Opportunities to Increase Savings From Medicare Price Negotiations. JAMA internal medicine Reitsma, M. B., Dusetzina, S. B., Ballreich, J. M., Trujillo, A. J., Mello, M. M. 2023

    Abstract

    Allowing the US Centers for Medicare & Medicaid Services to negotiate prescription drug prices for Medicare may improve drug affordability.To estimate savings from Medicare price negotiation under the Inflation Reduction Act (IRA) and examine opportunities to increase savings.This cross-sectional, population-based study used data from 2020 Medicare prescription drug claims. The study was conducted and data were analyzed in 2022.Eligibility for Medicare price negotiation under the IRA and alternative criteria.Minimum savings under the IRA's eligibility criteria were estimated and compared with savings within alternative scenarios, including (1) selecting drugs for negotiation based on net spending after rebates rather than gross spending; (2) extending eligibility to drugs with biosimilar or generic competitors; (3) reducing the minimum years since US Food and Drug Administration approval for eligibility; and (4) changing 2 or 3 of these factors. Estimated savings were calculated at different levels of scale-up of price negotiation under the IRA, from 10 Part D drugs in 2026 to 60 Part B and D drugs in 2029. Gross spending was calculated using the US Centers for Medicare & Medicaid Services 2020 Medicare drug spending dashboard. Rebates were estimated using SSR Health data. Information on FDA approvals, generics, and biosimilars was obtained from FDA websites.Under IRA rules, estimated minimum savings from price negotiation in 2026 for 10 Part D drugs would be $3.2 billion. For 2029 for 60 Part D and B drugs, estimated savings were $16.0 billion. Selecting drugs for negotiation based on net rather than gross spending would be associated with estimated savings of $4.6 billion (a 45% increase) in 2026 and $18.9 billion (an 18% increase) in 2029. Including drugs with generic competitors or biosimilars would be associated with an estimated savings of $6.6 billion (a 109% increase) in 2026 and $24.9 billion (a 56% increase) in 2029. Making both changes would be associated with savings of $9.5 billion (a 200% increase) in 2026 and $28.3 billion (a 77% increase) in 2029. A sensitivity analysis suggested that reducing the required number of years since marketing approval by 2 years would be associated with increased estimated savings of 4% when 10 Part D drugs are negotiated and 12% when 60 Part D and B drugs are negotiated. Changing all 3 criteria would be associated with the greatest increase in estimated savings in 2029 (119% increase when 10 Part D drugs are negotiated and 93% increase for 60 Part D and B drugs).The results of this cross-sectional study suggest that adjusting the eligibility criteria for Medicare prescription drug price negotiation to permit inclusion of drugs with biosimilar or generic competitors and selecting drugs based on net rather than gross spending may be a promising approach to substantially increase estimated savings.

    View details for DOI 10.1001/jamainternmed.2023.0763

    View details for PubMedID 37067794

  • Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California. Health affairs (Project Hope) Reitsma, M. B., Claypool, A. L., Vargo, J. n., Shete, P. B., McCorvie, R. n., Wheeler, W. H., Rocha, D. A., Myers, J. F., Murray, E. L., Bregman, B. n., Dominguez, D. M., Nguyen, A. D., Porse, C. n., Fritz, C. L., Jain, S. n., Watt, J. P., Salomon, J. A., Goldhaber-Fiebert, J. D. 2021: 101377hlthaff202100098

    Abstract

    With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021-the most of any state. We analyzed California's racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through October 2020, combining data from 15.4 million SARS-CoV-2 tests with subcounty exposure risk estimates from the American Community Survey. We defined "high-exposure-risk" households as those with one or more essential workers and fewer rooms than inhabitants. Latino people in California are 8.1 times more likely to live in high-exposure-risk households than White people (23.6 percent versus 2.9 percent), are overrepresented in cumulative cases (3,784 versus 1,112 per 100,000 people), and are underrepresented in cumulative testing (35,635 versus 48,930 per 100,000 people). These risks and outcomes were worse for Latino people than for members of other racial/ethnic minority groups. Subcounty disparity analyses can inform targeting of interventions and resources, including community-based testing and vaccine access measures. Tracking COVID-19 disparities and developing equity-focused public health programming that mitigates the effects of systemic racism can help improve health outcomes among California's populations of color.

    View details for DOI 10.1377/hlthaff.2021.00098

    View details for PubMedID 33979192

  • Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet (London, England) 2021

    Abstract

    Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally.We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available.Globally in 2019, 1·14 billion (95% uncertainty interval 1·13-1·16) individuals were current smokers, who consumed 7·41 trillion (7·11-7·74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27·5% [26·5-28·5] reduction) and females (37·7% [35·4-39·9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0·99 billion (0·98-1·00) in 1990. Globally in 2019, smoking tobacco use accounted for 7·69 million (7·16-8·20) deaths and 200 million (185-214) disability-adjusted life-years, and was the leading risk factor for death among males (20·2% [19·3-21·1] of male deaths). 6·68 million [86·9%] of 7·69 million deaths attributable to smoking tobacco use were among current smokers.In the absence of intervention, the annual toll of 7·69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a clear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens.Bloomberg Philanthropies and the Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(21)01169-7

    View details for PubMedID 34051883

  • Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and initiation among young people in 204 countries and territories, 1990-2019. The Lancet. Public health Reitsma, M. B., Flor, L. S., Mullany, E. C., Gupta, V., Hay, S. I., Gakidou, E. 2021

    Abstract

    Universally, smoking cessation rates among established smokers are poor. Preventing young people from starting use of and becoming addicted to tobacco products remains a key strategy to end the tobacco epidemic. Previous country-specific studies have found that initiation of smoking tobacco use occurs predominantly among young people and have found mixed progress in reducing the prevalence of smoking tobacco use among young people. Current and comparable estimates for all countries are needed to inform targeted interventions and policies.We modelled two indicators: prevalence of current smoking tobacco use among young adults aged 15-24 years, and the age at which current smokers aged 20-54 years in 2019 began smoking regularly. We synthesised data from 3625 nationally representative surveys on prevalence of smoking and 254 on age at initiation. We used spatiotemporal Gaussian process regression to produce estimates of the prevalence of smoking and age of initiation by sex, for 204 countries and territories for each year between 1990 and 2019.Globally in 2019, an estimated 155 million (95% uncertainty interval 150-160) individuals aged 15-24 years were tobacco smokers, with a prevalence of 20·1% (19·4-20·8) among males and 4·95% (4·64-5·29) among females. We estimated that 82·6% (82·1-83·1) of current smokers initiated between ages 14 and 25 years, and that 18·5% (17·7-19·3) of smokers began smoking regularly by age 15 years. Although some countries have made substantial progress in reducing the prevalence of smoking tobacco use among young people, prevalence in 2019 still exceeds 20% among males aged 15-24 years in 120 countries and among females aged 15-24 years in 43 countries.The fact that most smokers start smoking regularly before age 20 years highlights the unique window of opportunity to target prevention efforts among young people and save millions of lives and avert health-care costs in the future. Countries can substantially improve the health of their populations by implementing and enforcing evidence-based tobacco control policies that prevent the next generation from initiating smoking.Bloomberg Philanthropies.

    View details for DOI 10.1016/S2468-2667(21)00102-X

    View details for PubMedID 34051921

  • Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021 LANCET Vollset, S., Ababneh, H. S., Abate, Y., Abbafati, C., Abbasgholizadeh, R., Abbasian, M., Abbastabar, H., Abd Al Magied, A. A., Abd ElHafeez, S., Abdelkader, A., Abdelmasseh, M., Abd-Elsalam, S., Abdi, P., Abdollahi, M., Abdoun, M., Abdullahi, A., Abebe, M., Abiodun, O., Aboagye, R., Abolhassani, H., Abouzid, M., Aboye, G., Abreu, L., Absalan, A., Abualruz, H., Abubakar, B., Abukhadijah, H., Addolorato, G., Adekanmbi, V., Adetunji, C., Adetunji, J., Adeyeoluwa, T., Adha, R., Adhikary, R., Adnani, Q., Adzigbli, L., Afrashteh, F., Afzal, M., Afzal, S., Agbozo, F., Agodi, A., Agrawal, A., Agyemang-Duah, W., Ahinkorah, B., Ahlstrom, A. J., Ahmad, A., Ahmad, F., Ahmad, M. M., Ahmad, S., Ahmad, S., Ahmed, A., Ahmed, A., Ahmed, H., Ahmed, S., Ahmed, S., Akinosoglou, K., Akkaif, M., Akrami, A. E., Akter, E., Al Awaidy, S., Al Hasan, S., Al Mosa, A. S., Al Ta'ani, O., Al Zaabi, O., Alahdab, F., Alajlani, M. M., Al-Ajlouni, Y., Alalalmeh, S. O., Al-Aly, Z., Alam, K., Alam, N., Alam, T., Alam, Z., Al-Amer, R., Alanezi, F., Alanzi, T. M., Albakri, A., Aldhaleei, W. A., Aldridge, R. W., Alemohammad, S., Alemu, Y., Al-Gheethi, A., Al-Hanawi, M., Ali, A., Ali, A., Ali, I., Ali, M., Ali, R., Ali, S., Ali, V., Ali, W., Al-Ibraheem, A., Alicandro, G., Alif, S., Aljunid, S., Alla, F., Almazan, J., Al-Mekhlafi, H. M., Alqutaibi, A., Alrawashdeh, A., Alrousan, S., Al-Sabah, S., Alsabri, M. A., Altaany, Z., Al-Tammemi, A. B., Al-Tawfiq, J. A., Altirkawi, K. A., Aluh, D., Alvis-Guzman, N., Al-Wardat, M., Al-Worafi, Y., Aly, H., Alyahya, M., Alzoubi, K. H., Al-Zyoud, W., Amani, R., Ameyaw, E., Amin, T., Amindarolzarbi, A., Amiri, S., Amirzade-Iranaq, M., Amu, H., Amugsi, D. A., Ancuceanu, R., Anderlini, D., Anderson, D. B., Andrade, P., Andrei, C., Andrei, T., Andrews, E., Anil, A., Anil, S., Anoushiravani, A., Antony, C. M., Antriyandarti, E., Anuoluwa, B., Anvari, S., Anyasodor, A., Appiah, F., Aquilano, M., Arab, J., Arabloo, J., Arafa, E. A., Arafat, M., Aravkin, A. Y., Ardekani, A., Areda, D., Aregawi, B., Aremu, A., Ariffin, H., Arkew, M., Armani, K., Artamonov, A. A., Arumugam, A., Asghari-Jafarabadi, M., Ashbaugh, C., Astell-Burt, T., Athari, S., Atorkey, P., Atout, M., Aujayeb, A., Ausloos, M., Awad, H., Awotidebe, A., Ayatollahi, H., Ayuso-Mateos, J. L., Azadnajafabad, S., Azeez, F., Azevedo, R. S., Badar, M., Baghdadi, S., Bagheri, M., Bagheri, N., Bai, R., Baker, J. L., Bako, A. T., Balakrishnan, S., Balcha, W., Baltatu, O., Barchitta, M., Bardideh, E., Barker-Collo, S., Barnighausen, T., Barqawi, H., Barteit, S., Basiru, A., Basso, J., Bastan, M., Basu, S., Bauckneht, M., Baune, B. T., Bayati, M., Bayileyegn, N., Behnoush, A., Behzadi, P., Beiranvand, M., Bello, O., Belo, L., Beloukas, A., Bemanalizadeh, M., Bensenor, I. M., Benzian, H., Beran, A., Berezvai, Z., Bernstein, R. S., Bettencourt, P. G., Beyene, K. A., Beyene, M., Bhagat, D. S., Bhagavathula, A., Bhala, N., Bhandari, D., Bharadwaj, R., Bhardwaj, N., Bhardwaj, P., Bhargava, A., Bhaskar, S., Bhat, V., Bhattacharjee, N. V., Bhatti, G., Bhatti, J., Bhatti, M. S., Bhuiyan, M., Bisignano, C., Biswas, B., Bjorge, T., Bodolica, V., Bodunrin, A., Hashemi, M., Basara, B., Borhany, H., Bosoka, S., Carvajal, A., Bouaoud, S., Boufous, S., Boxe, C., Boyko, E. J., Brady, O. J., Braithwaite, D., Brauer, M., Brazo-Sayavera, J., Brenner, H., Brown, C., Browne, A. J., Brugha, T., Bryazka, D., Bulamu, N. B., Buonsenso, D., Burkart, K., Burns, R. A., Busse, R., Bustanji, Y., Butt, Z. A., dos Santos, F., Barsbay, M., Calina, D., Campos, L., Cao, S., Capodici, A., Cardenas, R., Carreras, G., Carugno, A., Carvalho, M., Castaldelli-Maia, J., Castelpietra, G., Cattaruzza, M., Caye, A., Cegolon, L., Cembranel, F., Cenko, E., Cerin, E., Chadban, S. J., Chadwick, J., Chakraborty, C., Chakraborty, S., Chalek, J., Chan, J., Chandika, R., Chandy, S., Charan, J., Chaudhary, A., Chaurasia, A., Chen, A., Chen, H., Chen, M., Chen, S., Cherbuin, N., Chi, G., Chichagi, F., Chimed-Ochir, O., Chimoriya, R., Ching, P. R., Chirinos-Caceres, J., Chitheer, A., Cho, D., Cho, W. S., Choi, D., Chong, B., Chong, C., Chopra, H., Chu, D., Chung, E., Chutiyami, M., Clayton, J. T., Cogen, R. M., Cohen, A. J., Columbus, A., Comfort, H., Conde, J., Connolly, J. T., Cooper, E. K., Cortese, S., Cruz-Martins, N., da Silva, A., Dadras, O., Dai, X., Dai, Z., Dalton, B. E., Damiani, G., Dandona, L., Dandona, R., Das, J. K., Das, S., Das, S., Dash, N., Davletov, K., De la Hoz, F., De Leo, D., Debopadhaya, S., Delgado-Enciso, I., Denova-Gutierrez, E., Dervenis, N., Desai, H., Devanbu, V., Dewan, S., Dhama, K., Dhane, A. S., Dhingra, S., da Silva, D., Diaz, D., Diaz, L., Diaz, M. J., Dima, A., Ding, D. D., Do, T., Do Prado, C., Dodangeh, M., Dodangeh, M., Doegah, P., Dohare, S., Dong, W., D'Oria, M., Doshi, R., Dowou, R., Dsouza, H., Dsouza, V., Dube, J., Dumith, S. C., Duncan, B. B., Duraes, A., Duraisamy, S., Durojaiye, O., Dushpanova, A., Dutta, S., Dzianach, P., Dziedzic, A., Eboreime, E., Ebrahimi, A., Kalan, M., Edinur, H., Efendi, F., Eikemo, T., Eini, E., Ekundayo, T., El Arab, R., El Sayed, I., Elamin, O., Elemam, N., ElGohary, G., Elhadi, M., Elmeligy, O., Elmoselhi, A. B., Elshaer, M., Elsohaby, I., Eltahir, M., Emeto, T. I., Eshrati, B., Eslami, M., Esmaeili, Z., Fabin, N., Fagbamigbe, A., Fagbule, O., Falzone, L., Fareed, M., Farinha, C., Faris, M., Faro, A., Fasihi, K., Fatehizadeh, A., Fauk, N., Fazylov, T., Feigin, V. L., Fekadu, G., Feng, X., Fereshtehnejad, S., Ferrara, P., Ferreira, N., Firew, B., Fischer, F., Fitriana, I., Flavel, J., Flor, L. S., Folayan, M., Foley, K., Fonzo, M., Force, L. M., Foschi, M., Freitas, A., Fridayani, N., Fukutaki, K., Furtado, J. M., Fux, B., Gaal, P., Gadanya, M. A., Gallus, S., Ganesan, B., Ganiyani, M., Gautam, R. K., Gebi, T., Gebregergis, M. W., Gebrehiwot, M., Getacher, L., Getahun, G. A., Gething, P. W., Ghadimi, D. J., Ghadirian, F., Ghafarian, S., Ghailan, K., Ghasemi, M., Dabaghi, G., Ghazy, R., Ghoba, S., Gholami, E., Gholamrezanezhad, A., Gholizadeh, N., Ghorbani, M., Vajargah, P., Ghotbi, E., Gil, A., Gill, T. K., Girmay, A., Glasbey, J. C., Glushkova, E., Gnedovskaya, E. V., Gobolos, L., Goldust, M., Goleij, P., Golinelli, D., Gopalani, S., Goulart, A. C., Gouravani, M., Goyal, A., Grivna, M., Grosso, G., Guarducci, G., Gubari, M., Guicciardi, S., Guimaraes, R., Gulati, S., Gulisashvili, D., Gunawardane, D., Guo, C., Gupta, A., Gupta, R., Gupta, R., Gupta, R., Gupta, S., Gupta, V., Haakenstad, A., Hadi, N. R., Haep, N., Hafiz, A., Haghmorad, D., Haile, D., Ali, A., Ali, H., Haj-Mirzaian, A., Halboub, E. S., Haller, S., Halwani, R., Abdullah, K., Hamdy, N. M., Hamoudi, R., Hanifi, N., Hankey, G. J., Haq, Z., Haque, M., Harapan, H., Hargono, A., Haro, J., Hasaballah, A. I., Hasan, S., Hasanian, M., Hasnain, M., Hassan, A., Haubold, J., Hay, S. I., Hebert, J. J., Hegazi, O. E., Heidari, M., Hemmati, M., Henson, C. A., Herrera-Serna, B., Herteliu, C., Heydari, M., Hezam, K., Hidayana, I., Hiraike, Y., Hoan, N., Holla, R., Hoogar, P., Horita, N., Hossain, M., Hosseinzadeh, H., Hosseinzadeh, M., Hostiuc, M., Hostiuc, S., Hu, C., Huang, J., Hultstrom, M., Hundie, T., Hunt, A. J., Hushmandi, K., Hussain, J., Hussain, M., Hussein, N. R., Huynh, H., Hwang, B., Ibitoye, S., Iftikhar, P., Ikiroma, A. I., Ikwegbue, P., Ilic, I. M., Ilic, M. D., Immurana, M., Isa, M., Islam, M., Islam, S., Ismail, F., Ismail, N., Isola, G., Iwagami, M., Iyamu, I., Jacob, L., Jacobsen, K. H., Jafarinia, M., Jahankhani, K., Jahanmehr, N., Jain, N., Jairoun, A., Mani, D., Jamil, S., Jamora, R. G., Jatau, A., Javadov, S., Javaheri, T., Jayaram, S., Jee, S., Jeganathan, J., Jiang, H., Jokar, M., Jonas, J. B., Joseph, N., Joshua, C., Jurisson, M., Vaishali, K., Kabir, A., Kabir, Z., Kadashetti, V., Kalankesh, L. R., Kalra, S., Kamath, A., Kamath, R., Kamireddy, A., Kanaan, M., Kanchan, T., Kanmiki, E., Kanmodi, K., Kansal, S., Karim, A., Karkhah, S., Kashoo, F., Kasraei, H., Kassel, M. B., Katikireddi, S., Kauppila, J. H., Kaur, H., Kayode, G. A., Kazemi, F., Kazemian, S., Kebede, F., Kendal, E., Kesse-Guyot, E., Khademvatan, S., Khajuria, H., Khalaji, A., Khalid, A., Khalid, N., Khalilian, A., Khamesipour, F., Khan, F., Khan, M., Khan, M. B., Khanmohammadi, S., Khatab, K., Khatatbeh, H., Khatatbeh, M., Khatib, M., Kashani, H., Kheirallah, K. A., Khokhar, M., Khormali, M., Khorrami, Z., Khosla, A., Khosravi, M., Khosrowjerdi, M., Khubchandani, J., Kifle, Z., Kim, G., Kim, J., Kim, M., Kim, Y., Kimokoti, R. W., Kisa, A., Kisa, S., Knibbs, L. 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    Abstract

    Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]).Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 001271482100001

    View details for PubMedID 38762325

    View details for PubMedCentralID PMC11121021

  • Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 LANCET Brauer, M., Roth, G. A., Aravkin, A. Y., Zheng, P., Abate, K., Abate, Y., Abbafati, C., Abbasgholizadeh, R., Abbasi, M., Abbasian, M., Abbasifard, M., Abbasi-Kangevari, M., ElHafeez, S., Abd-Elsalam, S., Abdi, P., Abdollahi, M., Abdoun, M., Abdulah, D., Abdullahi, A., Abebe, M., Abedi, A., Abedi, A., Abegaz, T. 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A., Ribeiro, A. P., Rickard, J., Robinson-Oden, H., Rodrigues, C., Rodrigues, M., Rodriguez, J., Roever, L., Romadlon, D., Ronfani, L., Rosauer, J., Roshandel, G., Rostamian, M., Rotimi, K., Rout, H., Roy, B., Roy, N., Rubagotti, E., Ruela, G., Runghien, T., Russo, M., Ruzzante, S., Chandan, S. N., Saad, A. A., Saber, K., Saber-Ayad, M., Sabour, S., Sacco, S., Sachdev, P. S., Sachdeva, R., Saddik, B., Saddler, A., Sadee, B., Sadeghi, E., Sadeghi, M., Majd, E., Saeb, M., Saeed, U., Safi, M., Safi, S., Sagar, R., Sagoe, D., Sharif-Askari, F., Sharif-Askari, N., Sahebkar, A., Sahoo, S., Sahu, M., Saif, Z., Sajid, M., Sakshaug, J. W., Salam, N., Salamati, P., Salami, A., Salaroli, L. B., Salehi, L., Salehi, S., Salem, M., Salem, M. Y., Salihu, D., Salimi, S., Salum, G. A., Kafil, H., Samadzadeh, S., Samodra, Y., Samuel, V., Samy, A. M., Sanabria, J., Sanjeev, R., Sanna, F., Santomauro, D., Santric-Milicevic, M. 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H., Shiani, A., Shiferaw, D., Shigematsu, M., Shin, M., Shiri, R., Shittu, A., Shiue, I., Shivakumar, K. M., Shivarov, V., Shool, S., Shorofi, S., Shrestha, R., Shrestha, S., Shuja, K., Shuval, K., Si, Y., Siddig, E., Silva, D., Silva, L., Silva, S., Silva, T. R., Simpson, C. R., Singh, A., Singh, B., Singh, B., Singh, G., Singh, H., Singh, J. A., Singh, M., Singh, N., Singh, P., Singh, S., Sinto, R., Sivakumar, S., Siwal, S., Skhvitaridze, N., Skou, S. T., Sleet, D. A., Sobia, F., Soboka, M., Socea, B., Solaimanian, S., Solanki, R., Solanki, S., Soliman, S. M., Somayaji, R., Song, Y., Sorensen, R. D., Soriano, J. B., Soyiri, I. N., Spartalis, M., Spearman, S., Spencer, C. N., Sreeramareddy, C. T., Stachteas, P., Stafford, L. K., Stanaway, J. D., Stanikzai, M., Stein, C., Stein, D. J., Steinbeis, F., Steiner, C., Steinke, S., Steiropoulos, P., Stockfelt, L., Stokes, M. A., Straif, K., Stranges, S., Subedi, N., Subramaniyan, V., Suleman, M., Abdulkader, R., Sundstrom, J., Sunkersing, D., Sunnerhagen, K. S., Suresh, V., Swain, C., Szarpak, L., Szeto, M. D., Damavandi, P., Tabares-Seisdedos, R., Tabatabaei, S., Malazy, O., Tabatabaeizadeh, S., Tabatabai, S., Tabche, C., Tabish, M., Tadakamadla, S., Abkenar, Y., Soodejani, M., Taherkhani, A., Taiba, J., Takahashi, K., Talaat, I. M., Tamuzi, J., Tan, K., Tang, H., Tat, N. Y., Taveira, N., Tefera, Y., Tehrani-Banihashemi, A., Temesgen, W., Temsah, M., Teramoto, M., Terefa, D., Teye-Kwadjo, E., Thakur, R., Thangaraju, P., Thankappan, K., Thapar, R., Thayakaran, R., Thirunavukkarasu, S., Thomas, N., Thomas, N., Tian, J., Tichopad, A., Ticoalu, J., Tiruye, T., Tobe-Gai, R., Tolani, M., Tolossa, T., Tonelli, M., Topor-Madry, R., Topouzis, F., Touvier, M., Tovani-Palone, M., Trabelsi, K., Tran, J. T., Mai Thi Ngoc Tran, Nghia Minh Tran, Trico, D., Trihandini, I., Troeger, C. 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L., Gakidou, E., GBD 2021 Risk Factors Collaborators 2024; 403 (10440): 2162-2203

    Abstract

    Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021.The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws.Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP).Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 001270483200001

    View details for PubMedID 38762324

    View details for PubMedCentralID PMC11120204

  • Hypertension care cascades and reducing inequities in cardiovascular disease in low- and middle-income countries. Nature medicine Stein, D. T., Reitsma, M. B., Geldsetzer, P., Agoudavi, K., Aryal, K. K., Bahendeka, S., Brant, L. C., Farzadfar, F., Gurung, M. S., Guwatudde, D., Houehanou, Y. C., Malta, D. C., Martins, J. S., Saeedi Moghaddam, S., Mwangi, K. J., Norov, B., Sturua, L., Zhumadilov, Z., Bärnighausen, T., Davies, J. I., Flood, D., Marcus, M. E., Theilmann, M., Vollmer, S., Manne-Goehler, J., Atun, R., Sudharsanan, N., Verguet, S. 2024

    Abstract

    Improving hypertension control in low- and middle-income countries has uncertain implications across socioeconomic groups. In this study, we simulated improvements in the hypertension care cascade and evaluated the distributional benefits across wealth quintiles in 44 low- and middle-income countries using individual-level data from nationally representative, cross-sectional surveys. We raised diagnosis (diagnosis scenario) and treatment (treatment scenario) levels for all wealth quintiles to match the best-performing country quintile and estimated the change in 10-year cardiovascular disease (CVD) risk of individuals initiated on treatment. We observed greater health benefits among bottom wealth quintiles in middle-income countries and in countries with larger baseline disparities in hypertension management. Lower-middle-income countries would see the greatest absolute benefits among the bottom quintiles under the treatment scenario (29.1 CVD cases averted per 1,000 people living with hypertension in the bottom quintile (Q1) versus 17.2 in the top quintile (Q5)), and the proportion of total CVD cases averted would be largest among the lowest quintiles in upper-middle-income countries under both diagnosis (32.0% of averted cases in Q1 versus 11.9% in Q5) and treatment (29.7% of averted cases in Q1 versus 14.0% in Q5) scenarios. Targeted improvements in hypertension diagnosis and treatment could substantially reduce socioeconomic-based inequalities in CVD burden in low- and middle-income countries.

    View details for DOI 10.1038/s41591-023-02769-8

    View details for PubMedID 38278990

    View details for PubMedCentralID 7755038

  • Assessing the impact of community-based interventions on hypertension and diabetes management in three Minnesota communities: Findings from the prospective evaluation of US HealthRise programs. PloS one Fullman, N., Cowling, K., Flor, L. S., Wilson, S., Bhatt, P., Bryant, M. F., Camarda, J. N., Colombara, D. V., Daly, J., Gabert, R. K., Harris, K. P., Johanns, C. K., Mandile, C., Marshall, S., McNellan, C. R., Mulakaluri, V., Phillips, B. K., Reitsma, M. B., Sadighi, N., Tamene, T., Thomson, B., Wollum, A., Gakidou, E. 2023; 18 (2): e0279230

    Abstract

    BACKGROUND: Community-based health interventions are increasingly viewed as models of care that can bridge healthcare gaps experienced by underserved communities in the United States (US). With this study, we sought to assess the impact of such interventions, as implemented through the US HealthRise program, on hypertension and diabetes among underserved communities in Hennepin, Ramsey, and Rice Counties, Minnesota.METHODS AND FINDINGS: HealthRise patient data from June 2016 to October 2018 were assessed relative to comparison patients in a difference-in-difference analysis, quantifying program impact on reducing systolic blood pressure (SBP) and hemoglobin A1c, as well as meeting clinical targets (< 140 mmHg for hypertension, < 8% Al1c for diabetes), beyond routine care. For hypertension, HealthRise participation was associated with SBP reductions in Rice (6.9 mmHg [95% confidence interval: 0.9-12.9]) and higher clinical target achievement in Hennepin (27.3 percentage-points [9.8-44.9]) and Rice (17.1 percentage-points [0.9 to 33.3]). For diabetes, HealthRise was associated with A1c decreases in Ramsey (1.3 [0.4-2.2]). Qualitative data showed the value of home visits alongside clinic-based services; however, challenges remained, including community health worker retention and program sustainability.CONCLUSIONS: HealthRise participation had positive effects on improving hypertension and diabetes outcomes at some sites. While community-based health programs can help bridge healthcare gaps, they alone cannot fully address structural inequalities experienced by many underserved communities.

    View details for DOI 10.1371/journal.pone.0279230

    View details for PubMedID 36848352

  • Health effects associated with smoking: a Burden of Proof study. Nature medicine Dai, X., Gil, G. F., Reitsma, M. B., Ahmad, N. S., Anderson, J. A., Bisignano, C., Carr, S., Feldman, R., Hay, S. I., He, J., Iannucci, V., Lawlor, H. R., Malloy, M. J., Marczak, L. B., McLaughlin, S. A., Morikawa, L., Mullany, E. C., Nicholson, S. I., O'Connell, E. M., Okereke, C., Sorensen, R. J., Whisnant, J., Aravkin, A. Y., Zheng, P., Murray, C. J., Gakidou, E. 2022

    Abstract

    As a leading behavioral risk factor for numerous health outcomes, smoking is a major ongoing public health challenge. Although evidence on the health effects of smoking has been widely reported, few attempts have evaluated the dose-response relationship between smoking and a diverse range of health outcomes systematically and comprehensively. In the present study, we re-estimated the dose-response relationships between current smoking and 36 health outcomes by conducting systematic reviews up to 31 May 2022, employing a meta-analytic method that incorporates between-study heterogeneity into estimates of uncertainty. Among the 36 selected outcomes, 8 had strong-to-very-strong evidence of an association with smoking, 21 had weak-to-moderate evidence of association and 7 had no evidence of association. By overcoming many of the limitations of traditional meta-analyses, our approach provides comprehensive, up-to-date and easy-to-use estimates of the evidence on the health effects of smoking. These estimates provide important information for tobacco control advocates, policy makers, researchers, physicians, smokers and the public.

    View details for DOI 10.1038/s41591-022-01978-x

    View details for PubMedID 36216941

  • The Burden of Proof studies: assessing the evidence of risk. Nature medicine Zheng, P., Afshin, A., Biryukov, S., Bisignano, C., Brauer, M., Bryazka, D., Burkart, K., Cercy, K. M., Cornaby, L., Dai, X., Dirac, M. A., Estep, K., Fay, K. A., Feldman, R., Ferrari, A. J., Gakidou, E., Gil, G. F., Griswold, M., Hay, S. I., He, J., Irvine, C. M., Kassebaum, N. J., LeGrand, K. E., Lescinsky, H., Lim, S. S., Lo, J., Mullany, E. C., Ong, K. L., Rao, P. C., Razo, C., Reitsma, M. B., Roth, G. A., Santomauro, D. F., Sorensen, R. J., Srinivasan, V., Stanaway, J. D., Vollset, S. E., Vos, T., Wang, N., Welgan, C. A., Wozniak, S. S., Aravkin, A. Y., Murray, C. J. 2022

    Abstract

    Exposure to risks throughout life results in a wide variety of outcomes. Objectively judging the relative impact of these risks on personal and population health is fundamental to individual survival and societal prosperity. Existing mechanisms to quantify and rank the magnitude of these myriad effects and the uncertainty in their estimation are largely subjective, leaving room for interpretation that can fuel academic controversy and add to confusion when communicating risk. We present a new suite of meta-analyses-termed the Burden of Proof studies-designed specifically to help evaluate these methodological issues objectively and quantitatively. Through this data-driven approach that complements existing systems, including GRADE and Cochrane Reviews, we aim to aggregate evidence across multiple studies and enable a quantitative comparison of risk-outcome pairs. We introduce the burden of proof risk function (BPRF), which estimates the level of risk closest to the null hypothesis that is consistent with available data. Here we illustrate the BPRF methodology for the evaluation of four exemplar risk-outcome pairs: smoking and lung cancer, systolic blood pressure and ischemic heart disease, vegetable consumption and ischemic heart disease, and unprocessed red meat consumption and ischemic heart disease. The strength of evidence for each relationship is assessed by computing and summarizing the BPRF, and then translating the summary to a simple star rating. The Burden of Proof methodology provides a consistent way to understand, evaluate and summarize evidence of risk across different risk-outcome pairs, and informs risk analysis conducted as part of the Global Burden of Diseases, Injuries, and Risk Factors Study.

    View details for DOI 10.1038/s41591-022-01973-2

    View details for PubMedID 36216935

  • Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020 LANCET Bryazka, D., Reitsma, M. B., Griswold, M. G., Abate, K., Abbafati, C., Abbasi-Kangevari, M., Abbasi-Kangevari, Z., Abdoli, A., Abdollahi, M., Abdullah, A., Abhilash, E. S., Abu-Gharbieh, E., Acuna, J., Addolorato, G., Adebayo, O. M., Adekanmbi, V., Adhikari, K., Adhikari, S., Adnani, Q., Afzal, S., Agegnehu, W., Aggarwal, M., Ahinkorah, B., Ahmad, A., Ahmad, S., Ahmad, T., Ahmadi, A., Ahmadi, S., Ahmed, H., Rashid, T., Akunna, C., Al Hamad, H., Alam, M., Alem, D., Alene, K., Alimohamadi, Y., Alizadeh, A., Allel, K., Alonso, J., Alvand, S., Alvis-Guzman, N., Amare, F., Ameyaw, E., Amiri, S., Ancuceanu, R., Anderson, J. A., Andrei, C., Andrei, T., Arabloo, J., Arshad, M., Artamonov, A. A., Aryan, Z., Asaad, M., Asemahagn, M. A., Astell-Burt, T., Athari, S., Atnafu, D., Atorkey, P., Atreya, A., Ausloos, F., Ausloos, M., Ayano, G., Ayanore, M., Ayinde, O. O., Ayuso-Mateos, J. L., Azadnajafabad, S., Azanaw, M., Azangou-Khyavy, M., Jafari, A., Azzam, A. Y., Badiye, A. D., Bagheri, N., Bagherieh, S., Bairwa, M., Bakkannavar, S. M., Bakshi, R., Balchut-Bilchut, A., Barra, F., Barrow, A., Baskaran, P., Belo, L., Bennett, D. A., Bensenor, I. M., Bhagavathula, A., Bhala, N., Bhalla, A., Bhardwaj, N., Bhardwaj, P., Bhaskar, S., Bhattacharyya, K., Bhojaraja, V. S., Bintoro, B., Blokhina, E., Bodicha, B., Boloor, A., Bosetti, C., Braithwaite, D., Brenner, H., Briko, N., Brunoni, A. R., Butt, Z. A., Cao, C., Cao, Y., Cardenas, R., Carvalho, A. F., Carvalho, M., Castaldelli-Maia, J., Castelpietra, G., Castro-de-Araujo, L. S., Cattaruzza, M., Chakraborty, P., Charan, J., Chattu, V., Chaurasia, A., Cherbuin, N., Chu, D., Chudal, N., Chung, S., Churko, C., Ciobanu, L. G., Cirillo, M., Claro, R. M., Costanzo, S., Cowden, R. G., Criqui, M. H., Cruz-Martins, N., Culbreth, G. T., Dachew, B., Dadras, O., Dai, X., Damiani, G., Dandona, L., Dandona, R., Daniel, B., Danielewicz, A., Gela, J., Davletov, K., Paiva de Araujo, J., De Sa-Junior, A., Debela, S., Dehghan, A., Demetriades, A. K., Molla, M., Desai, R., Desta, A., da Silva, D., Diaz, D., Digesa, L., Diress, M., Dodangeh, M., Dongarwar, D., Dorostkar, F., Dsouza, H., Duko, B., Duncan, B. B., Edvardsson, K., Ekholuenetale, M., Elgar, F. J., Elhadi, M., Elmonem, M. A., Endries, A., Eskandarieh, S., Etemadimanesh, A., Fagbamigbe, A., Fakhradiyev, I., Farahmand, F., Farinha, C., Faro, A., Farzadfar, F., Fatehizadeh, A., Fauk, N., Feigin, V. L., Feldman, R., Feng, X., Fentaw, Z., Ferrero, S., Desideri, L., Filip, I., Fischer, F., Francis, J., Franklin, R., Gaal, P., Gad, M. M., Gallus, S., Galvano, F., Ganesan, B., Garg, T., Gebrehiwot, M., Gebremeskel, T., Gebremichael, M., Gemechu, T., Getacher, L., Getachew, M., Obsa, A., Getie, A., Ghaderi, A., Ghafourifard, M., Ghajar, A., Ghamari, S., Ghandour, L. A., Nour, M., Ghashghaee, A., Ghozy, S., Glozah, F. N., Glushkova, E., Godos, J., Goel, A., Goharinezhad, S., Golechha, M., Goleij, P., Golitaleb, M., Greaves, F., Grivna, M., Grosso, G., Gudayu, T., Gupta, B., Gupta, R., Gupta, S., Gupta, V., Gupta, V., Hafezi-Nejad, N., Haj-Mirzaian, A., Hall, B. J., Halwani, R., Handiso, T., Hankey, G. J., Hariri, S., Haro, J., Hasaballah, A. I., Hassanian-Moghaddam, H., Hay, S. I., Hayat, K., Heidari, G., Heidari, M., Hendrie, D., Herteliu, C., Heyi, D., Hezam, K., Hlongwa, M., Holla, R., Hossain, M., Hossain, S., Hosseini, S., Hosseinzadeh, M., Hostiuc, M., Hostiuc, S., Hu, G., Huang, J., Hussain, S., Ibitoye, S., Ilic, I. M., Ilic, M. D., Immurana, M., Irham, L., Islam, M., Islam, R. M., Islam, S., Iso, H., Itumalla, R., Iwagami, M., Jabbarinejad, R., Jacob, L., Jakovljevic, M., Jamalpoor, Z., Jamshidi, E., Jayapal, S., Jayarajah, U., Jayawardena, R., Jebai, R., Jeddi, S., Jema, A., Jha, R., Jindal, H., Jonas, J. B., Joo, T., Joseph, N., Joukar, F., Jozwiak, J., Jurisson, M., Kabir, A., Kabthymer, R., Kamble, B., Kandel, H., Kanno, G., Kapoor, N., Karaye, I. M., Karimi, S., Kassa, B., Kaur, R., Kayode, G. A., Keykhaei, M., Khajuria, H., Khalilov, R., Khan, I. A., Khan, M. B., Kim, H., Kim, J., Kim, M., Kimokoti, R. W., Kivimaki, M., Klymchuk, V., Knudsen, A., Kolahi, A., Korshunov, V., Koyanagi, A., Krishan, K., Krishnamoorthy, Y., Kumar, G., Kumar, N., Kumar, N., Ben Lacey, Lallukka, T., Lasrado, S., Lau, J., Lee, S., Lee, W., Lee, Y., Lim, L., Lim, S. S., Lobo, S. W., Lopukhov, P. D., Lorkowski, S., Lozano, R., Lucchetti, G., Madadizadeh, F., Madureira-Carvalho, A. M., Mahjoub, S., Mahmoodpoor, A., Mahumud, R., Makki, A., Malekpour, M., Manjunatha, N., Mansouri, B., Mansournia, M., Martinez-Raga, J., Martinez-Villa, F. A., Matzopoulos, R., Maulik, P. K., Mayeli, M., McGrath, J. J., Meena, J., Nasab, E., Menezes, R. G., Mensink, G. M., Mentis, A. A., Meretoja, A., Merga, B., Mestrovic, T., Jonasson, J., Miazgowski, B., de Sa, A., Miller, T. R., Mini, G. K., Mirica, A., Mirijello, A., Mirmoeeni, S., Mirrakhimov, E. M., Misra, S., Moazen, B., Mobarakabadi, M., Moccia, M., Mohammad, Y., Mohammadi, E., Mohammadian-Hafshejani, A., Mohammed, T., Moka, N., Mokdad, A. H., Momtazmanesh, S., Moradi, Y., Mostafavi, E., Mubarik, S., Mullany, E. C., Mulugeta, B., Murillo-Zamora, E., Murray, C. L., Mwita, J. C., Naghavi, M., Naimzada, M., Nangia, V., Nayak, B., Negoi, I., Negoi, R., Nejadghaderi, S., Nepal, S., Neupane, S., Kandel, S., Nigatu, Y. T., Nowroozi, A., Nuruzzaman, K. M., Nzoputam, C., Obamiro, K. O., Ogbo, F., Oguntade, A., Okati-Aliabad, H., Olakunde, B., Oliveira, G., Bali, A., Omer, E., Ortega-Altamirano, D. V., Otoiu, A., Otstavnov, S. S., Oumer, B., Mahesh, P. A., Padron-Monedero, A., Palladino, R., Pana, A., Panda-Jonas, S., Pandey, A., Pandey, A., Pardhan, S., Parekh, T., Park, E., Parry, C. H., Kan, F., Patel, J., Pati, S., Patton, G. C., Paudel, U., Pawar, S., Peden, A. E., Petcu, I., Phillips, M. R., Pinheiro, M., Plotnikov, E., Pradhan, P., Prashant, A., Quan, J., Radfar, A., Rafiei, A., Raghav, P., Rahimi-Movaghar, V., Rahman, A., Rahman, M., Rahman, M., Rahmani, A., Rahmani, S., Ranabhat, C., Ranasinghe, P., Rao, C. R., Rasali, D., Rashidi, M., Ratan, Z., Rawaf, D., Rawaf, S., Rawal, L., Renzaho, A. N., Rezaei, N., Rezaei, S., Rezaeian, M., Riahi, S., Romero-Rodriguez, E., Roth, G. A., Rwegerera, G. M., Saddik, B., Sadeghi, E., Sadeghian, R., Saeed, U., Saeedi, F., Sagar, R., Sahebkar, A., Sahoo, H., Sahraian, M., Saif-Ur-Rahman, K. M., Salahi, S., Salimzadeh, H., Samy, A. M., Sanmarchi, F., Santric-Milicevic, M. M., Sarikhani, Y., Sathian, B., Saya, G., Sayyah, M., Schmidt, M., Schutte, A., Schwarzinger, M., Schwebel, D. C., Seidu, A., Kumar, N., SeyedAlinaghi, S., Seylani, A., Sha, F., Shahin, S., Shahraki-Sanavi, F., Shahrokhi, S., Shaikh, M., Shaker, E., Shakhmardanov, M., Shams-Beyranvand, M., Sheikhbahaei, S., Sheikhi, R., Shetty, A., Shetty, J. K., Shiferaw, D., Shigematsu, M., Shiri, R., Shirkoohi, R., Shivakumar, K. M., Shivarov, V., Shobeiri, P., Shrestha, R., Sidemo, N., Sigfusdottir, I., Santos Silva, D., da Silva, N., Singh, J. A., Singh, S., Skryabin, V., Skryabina, A., Sleet, D. A., Solmi, M., Solomon, Y., Song, S., Song, Y., Sorensen, R. D., Soshnikov, S., Soyiri, I. N., Stein, D. J., Subba, S., Szocska, M., Tabares-Seisdedos, R., Tabuchi, T., Taheri, M., Tan, K., Tareke, M., Tarkang, E., Temesgen, G., Temesgen, W., Temsah, M., Thankappan, K., Thapar, R., Thomas, N., Tiruneh, C., Todorovic, J., Torrado, M., Touvier, M., Tovani-Palone, M., Mai Thi Ngoc Tran, Trias-Llimos, S., Tripathy, J., Vakilian, A., Valizadeh, R., Varmaghani, M., Varthya, S., Vasankari, T., Vos, T., Wagaye, B., Waheed, Y., Walde, M., Wang, C., Wang, Y., Wang, Y., Westerman, R., Wickramasinghe, N., Wubetu, A., Xu, S., Yamagishi, K., Yang, L., Yesera, G. E., Yigit, A., Yigit, V., Yimaw, A., Yon, D., Yonemoto, N., Yu, C., Zadey, S., Zahir, M., Zare, I., Zastrozhin, M., Zastrozhina, A., Zhang, Z., Zhong, C., Zmaili, M., Zuniga, Y. H., Gakidou, E., GBD 2020 Alcohol Collaborators 2022; 400 (10347): 185-235
  • Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990-2019: results from the Global Burden of Disease Study 2019 LANCET INFECTIOUS DISEASES Ledesma, J. R., Ma, J., Vongpradith, A., Maddison, E. R., Novotney, A., Biehl, M. H., LeGrand, K. E., Ross, J. M., Jahagirdar, D., Bryazka, D., Feldman, R., Abolhassani, H., Abosetugn, A., Abu-Gharbieh, E., Adebayo, O. M., Adnani, Q., Afzal, S., Ahinkorah, B., Ahmad, S., Ahmadi, S., Rashid, T., Salih, Y., Aklilu, A., Akunna, C., Al Hamad, H., Alahdab, F., Alemayehu, Y., Alene, K., Ali, B., Ali, L., Alipour, V., Alizade, H., Al-Raddadi, R. M., Alvis-Guzman, N., Amini, S., Amit, A. L., Anderson, J. A., Androudi, S., Antonio, C. T., Antony, C. M., Anwer, R., Arabloo, J., Arja, A., Asemahagn, M. A., Atre, S. R., Azhar, G., Darshan, B. B., Babar, Z., Baig, A., Banach, M., Barqawi, H., Barra, F., Barrow, A., Basu, S., Belgaumi, U., Bhagavathula, A., Bhardwaj, N., Bhardwaj, P., Bhattacharjee, N., Bhattacharyya, K., Bijani, A., Bikbov, B., Boloor, A., Briko, N., Buonsenso, D., Nagaraja, S., Butt, Z. A., Carter, A., Carvalho, F., Charan, J., Chatterjee, S., Chattu, S., Chattu, V., Christopher, D. J., Chu, D., Claassens, M. M., Dadras, O., Dagnew, A., Dai, X., Dandona, L., Dandona, R., Daneshpajouhnejad, P., Darwesh, A., Dhamnetiya, D., Dianatinasab, M., Diaz, D., Linh Phuong Doan, Eftekharzadeh, S., Elhadi, M., Emami, A., Enany, S., Faraon, E. A., Farzadfar, F., Fernandes, E., Desideri, L., Filip, I., Fischer, F., Foroutan, M., Frank, T. D., Garcia-Basteiro, A. L., Garcia-Calavaro, C., Garg, T., Geberemariyam, B., Ghadiri, K., Ghashghaee, A., Golechha, M., Goodridge, A., Gupta, B., Gupta, S., Gupta, V., Gupta, V., Haider, M., Hamidi, S., Hanif, A., Haque, S., Harapan, H., Hargono, A., Hasaballah, A., Hashi, A., Hassan, S., Hassankhani, H., Hayat, K., Hezam, K., Holla, R., Hosseinzadeh, M., Hostiuc, M., Househ, M., Hussain, R., Ibitoye, S., Ilic, I. M., Ilic, M. D., Irvani, S., Ismail, N., Itumalla, R., Jaafari, J., Jacobsen, K. H., Jain, V., Javanmardi, F., Jayapal, S., Jayaram, S., Jha, R., Jonas, J. B., Joseph, N., Joukar, F., Kabir, Z., Kamath, A., Kanchan, T., Kandel, H., Katoto, P., Kayode, G. A., Kendrick, P. J., Kerbo, A., Khajuria, H., Khalilov, R., Khatab, K., Khoja, A. T., Khubchandani, J., Kim, M., Kim, Y., Kisa, A., Kisa, S., Kosen, S., Koul, P. A., Laxminarayana, S., Koyanagi, A., Krishan, K., Bicer, B., Kumar, A., Kumar, G., Kumar, N., Kumar, N., Kwarteng, A., Lak, H., Lal, D., Landires, I., Lasrado, S., Lee, S., Lee, W., Lin, C., Liu, X., Lopukhov, P. D., Lozano, R., Machado, D., Kunjathur, S., Madi, D., Mahajan, P., Majeed, A., Malik, A., Martins-Melo, F., Mehta, S., Memish, Z. A., Mendoza, W., Menezes, R. G., Merie, H., Mersha, A., Mesregah, M., Mestrovic, T., Mheidly, N., Misra, S., Mithra, P., Moghadaszadeh, M., Mohammadi, M., Mohammadian-Hafshejani, A., Mohammed, S., Molokhia, M., Moni, M., Al Montasir, A., Moore, C. E., Nagarajan, A., Nair, S., Nair, S., Naqvi, A., Swamy, S., Nayak, B., Nazari, J., Kandel, S., Nguyen, T., Nixon, M. R., Nnaji, C. A., Ntsekhe, M., Nunez-Samudio, V., Oancea, B., Odukoya, O., Olagunju, A. T., Oren, E., Mahesh, P. A., Parthasarathi, R., Kan, F., Pattanshetty, S. M., Paudel, R., Paul, P., Pawar, S., Pepito, V., Yigit, Perico, N., Pirestani, M., Polibin, R., Postma, M. J., Pourshams, A., Prashant, A., Pribadi, D., Radfar, A., Rafiei, A., Rahim, F., Rahimi-Movaghar, V., Rahman, M., Rahman, M., Rahmani, A., Ranasinghe, P., Rao, C. R., Rawaf, D., Rawaf, S., Reitsma, M. B., Remuzzi, G., Renzaho, A. N., Reta, M., Rezaei, N., Rezahosseini, O., Rezai, M., Rezapour, A., Roshandel, G., Roshchin, D. O., Sabour, S., Saif-Ur-Rahman, K. M., Salam, N., Kafil, H., Samaei, M., Samy, A. M., Saroshe, S., Sartorius, B., Sathian, B., Sawyer, S. M., Senthilkumaran, S., Seylani, A., Shafaat, O., Shaikh, M., Sharafi, K., Shetty, R. S., Shigematsu, M., Shin, J., Silva, J., Singh, J., Sinha, S., Skryabin, V., Skryabina, A., Spurlock, E., Sreeramareddy, C. T., Steiropoulos, P., Sufiyan, M., Tabuchi, T., Tadesse, E., Tamir, Z., Tarkang, E., Tekalegn, Y., Tesfay, F., Tessema, B., Thapar, R., Tleyjeh, I. I., Tobe-Gai, R., Bach Xuan Tran, Tsegaye, B., Tsegaye, G., Ullah, A., Umeokonkwo, C., Tahbaz, S., Bay Vo, Giang Thu Vu, Waheed, Y., Walters, M. K., Whisnant, J. L., Woldekidan, M., Wubishet, B., Jabbari, S., Yazie, T., Yeshaw, Y., Yi, S., Yonemoto, N., Yu, C., Yunusa, I., Zastrozhin, M., Zastrozhina, A., Zhang, Z., Zumla, A., Mokdad, A. H., Salomon, J. A., Jr, R., Lim, S. S., Naghavi, M., Vos, T., Hay, S., Murray, C. L., Kyu, H., GBD 2019 Tb Collaborators 2022; 22 (2): 222-241

    Abstract

    Tuberculosis is a major contributor to the global burden of disease, causing more than a million deaths annually. Given an emphasis on equity in access to diagnosis and treatment of tuberculosis in global health targets, evaluations of differences in tuberculosis burden by sex are crucial. We aimed to assess the levels and trends of the global burden of tuberculosis, with an emphasis on investigating differences in sex by HIV status for 204 countries and territories from 1990 to 2019.We used a Bayesian hierarchical Cause of Death Ensemble model (CODEm) platform to analyse 21 505 site-years of vital registration data, 705 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, and 680 site-years of mortality surveillance data to estimate mortality due to tuberculosis among HIV-negative individuals. We used a population attributable fraction approach to estimate mortality related to HIV and tuberculosis coinfection. A compartmental meta-regression tool (DisMod-MR 2.1) was then used to synthesise all available data sources, including prevalence surveys, annual case notifications, population-based tuberculin surveys, and tuberculosis cause-specific mortality, to produce estimates of incidence, prevalence, and mortality that were internally consistent. We further estimated the fraction of tuberculosis mortality that is attributable to independent effects of risk factors, including smoking, alcohol use, and diabetes, for HIV-negative individuals. For individuals with HIV and tuberculosis coinfection, we assessed mortality attributable to HIV risk factors including unsafe sex, intimate partner violence (only estimated among females), and injection drug use. We present 95% uncertainty intervals for all estimates.Globally, in 2019, among HIV-negative individuals, there were 1·18 million (95% uncertainty interval 1·08-1·29) deaths due to tuberculosis and 8·50 million (7·45-9·73) incident cases of tuberculosis. Among HIV-positive individuals, there were 217 000 (153 000-279 000) deaths due to tuberculosis and 1·15 million (1·01-1·32) incident cases in 2019. More deaths and incident cases occurred in males than in females among HIV-negative individuals globally in 2019, with 342 000 (234 000-425 000) more deaths and 1·01 million (0·82-1·23) more incident cases in males than in females. Among HIV-positive individuals, 6250 (1820-11 400) more deaths and 81 100 (63 300-100 000) more incident cases occurred among females than among males in 2019. Age-standardised mortality rates among HIV-negative males were more than two times greater in 105 countries and age-standardised incidence rates were more than 1·5 times greater in 74 countries than among HIV-negative females in 2019. The fraction of global tuberculosis deaths among HIV-negative individuals attributable to alcohol use, smoking, and diabetes was 4·27 (3·69-5·02), 6·17 (5·48-7·02), and 1·17 (1·07-1·28) times higher, respectively, among males than among females in 2019. Among individuals with HIV and tuberculosis coinfection, the fraction of mortality attributable to injection drug use was 2·23 (2·03-2·44) times greater among males than females, whereas the fraction due to unsafe sex was 1·06 (1·05-1·08) times greater among females than males.As countries refine national tuberculosis programmes and strategies to end the tuberculosis epidemic, the excess burden experienced by males is important. Interventions are needed to actively communicate, especially to men, the importance of early diagnosis and treatment. These interventions should occur in parallel with efforts to minimise excess HIV burden among women in the highest HIV burden countries that are contributing to excess HIV and tuberculosis coinfection burden for females. Placing a focus on tuberculosis burden among HIV-negative males and HIV and tuberculosis coinfection among females might help to diminish the overall burden of tuberculosis. This strategy will be crucial in reaching both equity and burden targets outlined by global health milestones.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S1473-3099(21)00449-7

    View details for Web of Science ID 000762847000004

    View details for PubMedID 34563275

    View details for PubMedCentralID PMC8799634

  • The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019. Lancet (London, England) GBD 2019 Cancer Risk Factors Collaborators, Tran, K. B., Lang, J. J., Compton, K., Xu, R., Acheson, A. R., Henrikson, H. J., Kocarnik, J. M., Penberthy, L., Aali, A., Abbas, Q., Abbasi, B., Abbasi-Kangevari, M., Abbasi-Kangevari, Z., Abbastabar, H., Abdelmasseh, M., Abd-Elsalam, S., Abdelwahab, A. A., Abdoli, G., Abdulkadir, H. A., Abedi, A., Abegaz, K. H., Abidi, H., Aboagye, R. G., Abolhassani, H., Absalan, A., Abtew, Y. D., Abubaker Ali, H., Abu-Gharbieh, E., Achappa, B., Acuna, J. M., Addison, D., Addo, I. Y., Adegboye, O. A., Adesina, M. A., Adnan, M., Adnani, Q. E., Advani, S. M., Afrin, S., Afzal, M. S., Aggarwal, M., Ahinkorah, B. O., Ahmad, A. R., Ahmad, R., Ahmad, S., Ahmad, S., Ahmadi, S., Ahmed, H., Ahmed, L. A., Ahmed, M. B., Ahmed Rashid, T., Aiman, W., Ajami, M., Akalu, G. 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    Abstract

    BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally.METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented.FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01-4·94) deaths and 105 million (95·0-116) DALYs for both sexes combined, representing 44·4% (41·3-48·4) of all cancer deaths and 42·0% (39·1-45·6) of all DALYs. There were 2·88 million (2·60-3·18) risk-attributable cancer deaths in males (50·6% [47·8-54·1] of all male cancer deaths) and 1·58 million (1·36-1·84) risk-attributable cancer deaths in females (36·3% [32·5-41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6-28·4) and DALYs by 16·8% (8·8-25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9-42·8] and 33·3% [25·8-42·0]).INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden.FUNDING: Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(22)01438-6

    View details for PubMedID 35988567

  • The US COVID-19 Trends and Impact Survey: Continuous real-time measurement of COVID-19 symptoms, risks, protective behaviors, testing, and vaccination. Proceedings of the National Academy of Sciences of the United States of America Salomon, J. A., Reinhart, A., Bilinski, A., Chua, E. J., La Motte-Kerr, W., Ronn, M. M., Reitsma, M. B., Morris, K. A., LaRocca, S., Farag, T. H., Kreuter, F., Rosenfeld, R., Tibshirani, R. J. 1800; 118 (51)

    Abstract

    The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems.

    View details for DOI 10.1073/pnas.2111454118

    View details for PubMedID 34903656

  • Quantifying and Benchmarking Disparities in COVID-19 Vaccination Rates by Race and Ethnicity. JAMA network open Reitsma, M. B., Goldhaber-Fiebert, J. D., Salomon, J. A. 2021; 4 (10): e2130343

    View details for DOI 10.1001/jamanetworkopen.2021.30343

    View details for PubMedID 34668949

  • Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 LANCET NEUROLOGY Feigin, V. L., Stark, B. A., Johnson, C., Roth, G. A., Bisignano, C., Abady, G., Abbasifard, M., Abbasi-Kangevari, M., Abd-Allah, F., Abedi, V., Abualhasan, A., Abu-Rmeileh, N., Abushouk, A., Adebayo, O. M., Agarwal, G., Agasthi, P., Ahinkorah, B., Ahmad, S., Ahmadi, S., Salih, Y., Aji, B., Akbarpour, S., Akinyemi, R., Al Hamad, H., Alahdab, F., Alif, S., Alipour, V., Aljunid, S., Almustanyir, S., Al-Raddadi, R. M., Salman, R., Alvis-Guzman, N., Ancuceanu, R., Anderlini, D., Anderson, J. A., Ansar, A., Antonazzo, I., Arabloo, J., Arnlov, J., Artanti, K., Aryan, Z., Asgari, S., Ashraf, T., Athar, M., Atreya, A., Ausloos, M., Baig, A., Baltatu, O., Banach, M., Barboza, M. A., Barker-Collo, S., Barnighausen, T., Barone, M., Basu, S., Bazmandegan, G., Beghi, E., Beheshti, M., Bejot, Y., Bell, A., Bennett, D. A., Bensenor, I. M., Bezabhe, W., Bezabih, Y., Bhagavathula, A., Bhardwaj, P., Bhattacharyya, K., Bijani, A., Bikbov, B., Birhanu, M. M., Boloor, A., Bonny, A., Brauer, M., Brenner, H., Bryazka, D., Butt, Z. A., dos Santos, F., Campos-Nonato, I. R., Cantu-Brito, C., Carrero, J. J., Castaneda-Orjuela, C. A., Catapano, A. L., Chakraborty, P., Charan, J., Choudhari, S., Chowdhury, E., Chu, D., Chung, S., Colozza, D., Costa, V., Costanzo, S., Criqui, M. H., Dadras, O., Dagnew, B., Dai, X., Dalal, K., Damasceno, A., D'Amico, E., Dandona, L., Dandona, R., Gela, J., Davletov, K., De La Cruz-Gongora, V., Desai, R., Dhamnetiya, D., Dharmaratne, S., Dhimal, M., Dhimal, M., Diaz, D., Dichgans, M., Dokova, K., Doshi, R., Douiri, A., Duncan, B. B., Eftekharzadeh, S., Ekholuenetale, M., El Nahas, N., Elgendy, I. Y., Elhadi, M., El-Jaafary, S., Endres, M., Endries, A., Erku, D., Faraon, E. A., Farooque, U., Farzadfar, F., Feroze, A., Filip, I., Fischer, F., Flood, D., Gad, M. M., Gaidhane, S., Gheshlagh, R., Ghashghaee, A., Ghith, N., Ghozali, G., Ghozy, S., Gialluisi, A., Giampaoli, S., Gilani, S., Gill, P., Gnedovskaya, E., Golechha, M., Goulart, A. C., Guo, Y., Gupta, R., Gupta, V., Gupta, V., Gyanwali, P., Hafezi-Nejad, N., Hamidi, S., Hanif, A., Hankey, G. J., Hargono, A., Hashi, A., Hassan, T. S., Hassen, H., Havmoeller, R. J., Hay, S., Hayat, K., Hegazy, M., Herteliu, C., Holla, R., Hostiuc, S., Househ, M., Huang, J., Humayun, A., Hwang, B., Iacoviello, L., Iavicoli, I., Ibitoye, S., Ilesanmi, O., Ilic, I. M., Ilic, M. D., Iqbal, U., Irvani, S., Islam, S., Ismail, N., Iso, H., Isola, G., Iwagami, M., Jacob, L., Jain, V., Jang, S., Jayapal, S., Jayaram, S., Jayawardena, R., Jeemon, P., Jha, R., Johnson, W. D., Jonas, J. B., Joseph, N., Jozwiak, J., Jurisson, M., Kalani, R., Kalhor, R., Kalkonde, Y., Kamath, A., Kamiab, Z., Kanchan, T., Kandel, H., Karch, A., Katoto, P. C., Kayode, G. A., Keshavarz, P., Khader, Y., Khan, E., Khan, I. A., Khan, M., Khan, M. B., Khatib, M., Khubchandani, J., Kim, G., Kim, M., Kim, Y., Kisa, A., Kisa, S., Kivimaki, M., Kolte, D., Koolivand, A., Laxminarayana, S., Koyanagi, A., Krishan, K., Krishnamoorthy, V., Krishnamurthi, R., Kumar, G., Kusuma, D., La Vecchia, C., Lacey, B., Lak, H., Lallukka, T., Lasrado, S., Lavados, P. M., Leonardi, M., Li, B., Li, S., Lin, H., Lin, R., Liu, X., Lo, W., Lorkowski, S., Lucchetti, G., Saute, R., Razek, H., Magnani, F., Mahajan, P., Majeed, A., Makki, A., Malekzadeh, R., Malik, A., Manafi, N., Mansournia, M., Mantovani, L., Martini, S., Mazzaglia, G., Mehndiratta, M., Menezes, R. G., Meretoja, A., Mersha, A., Jonasson, J., Miazgowski, B., Miazgowski, T., Michalek, I., Mirrakhimov, E. M., Mohammad, Y., Mohammadian-Hafshejani, A., Mohammed, S., Mokdad, A. H., Mokhayeri, Y., Molokhia, M., Moni, M., Al Montasir, A., Moradzadeh, R., Morawska, L., Morze, J., Muruet, W., Musa, K., Nagarajan, A., Naghavi, M., Swamy, S., Nascimento, B., Negoi, R., Kandel, S., Trang Huyen Nguyen, Norrving, B., Noubiap, J., Nwatah, V., Oancea, B., Odukoya, O., Olagunju, A. T., Orru, H., Owolabi, M. O., Padubidri, J., Pana, A., Parekh, T., Park, E., Kan, F., Pathak, M., Peres, M. P., Perianayagam, A., Truong-Minh Pham, Piradov, M. A., Podder, V., Polinder, S., Postma, M. J., Pourshams, A., Radfar, A., Rafiei, A., Raggi, A., Rahim, F., Rahimi-Movaghar, V., Rahman, M., Rahman, M., Rahmani, A., Rajai, N., Ranasinghe, P., Rao, C. R., Rao, S. J., Rathi, P., Rawaf, D., Rawaf, S., Reitsma, M. B., Renjith, V., Renzaho, A. N., Rezapour, A., Rodriguez, J., Roever, L., Romoli, M., Rynkiewicz, A., Sacco, S., Sadeghi, M., Moghaddam, S., Sahebkar, A., Saif-Ur-Rahman, K., Salah, R., Samaei, M., Samy, A. M., Santos, I. S., Santric-Milicevic, M. M., Sarrafzadegan, N., Sathian, B., Sattin, D., Schiavolin, S., Schlaich, M. P., Schmidt, M., Schutte, A., Sepanlou, S. G., Seylani, A., Sha, F., Shahabi, S., Shaikh, M., Shannawaz, M., Shawon, M., Sheikh, A., Sheikhbahaei, S., Shibuya, K., Siabani, S., Silva, D., Singh, J. A., Singh, J., Skryabin, V., Skryabina, A., Sobaih, B., Stortecky, S., Stranges, S., Tadesse, E., Tarigan, I., Temsah, M., Teuschl, Y., Thrift, A. G., Tonelli, M., Tovani-Palone, M., Bach Xuan Tran, Tripathi, M., Tsegaye, G., Ullah, A., Unim, B., Unnikrishnan, B., Vakilian, A., Tahbaz, S., Vasankari, T., Venketasubramanian, N., Vervoort, D., Vo, B., Volovici, V., Vosoughi, K., Giang Thu Vu, Linh Gia Vu, Wafa, H. A., Waheed, Y., Wang, Y., Wijeratne, T., Winkler, A., Wolfe, C. A., Woodward, M., Wu, J. H., Hanson, S., Xu, X., Yadav, L., Yadollahpour, A., Jabbari, S., Yamagishi, K., Yatsuya, H., Yonemoto, N., Yu, C., Yunusa, I., Zaman, M., Bin Zaman, S., Zamanian, M., Zand, R., Zandifar, A., Zastrozhin, M., Zastrozhina, A., Zhang, Y., Zhang, Z., Zhong, C., Zuniga, Y. H., Murray, C. L. 2021; 20 (10): 795-820

    Abstract

    Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels.We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level.In 2019, there were 12·2 million (95% UI 11·0-13·6) incident cases of stroke, 101 million (93·2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6·55 million (6·00-7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8-12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1-6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0-73·0), prevalent strokes increased by 85·0% (83·0-88·0), deaths from stroke increased by 43·0% (31·0-55·0), and DALYs due to stroke increased by 32·0% (22·0-42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0-18·0), mortality decreased by 36·0% (31·0-42·0), prevalence decreased by 6·0% (5·0-7·0), and DALYs decreased by 36·0% (31·0-42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0-24·0) and incidence rates increased by 15·0% (12·0-18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5-3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5-3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57-8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97-3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01-1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7-90·8] DALYs or 55·5% [48·2-62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3-48·6] DALYs or 24·3% [15·7-33·2]), high fasting plasma glucose (28·9 million [19·8-41·5] DALYs or 20·2% [13·8-29·1]), ambient particulate matter pollution (28·7 million [23·4-33·4] DALYs or 20·1% [16·6-23·0]), and smoking (25·3 million [22·6-28·2] DALYs or 17·6% [16·4-19·0]).The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S1474-4422(21)00252-0

    View details for Web of Science ID 000701741000016

    View details for PubMedID 34487721

    View details for PubMedCentralID PMC8443449

  • The effects of tobacco control policies on global smoking prevalence. Nature medicine Flor, L. S., Reitsma, M. B., Gupta, V., Ng, M., Gakidou, E. 2021

    Abstract

    Substantial global effort has been devoted to curtailing the tobacco epidemic over the past two decades, especially after the adoption of the Framework Convention on Tobacco Control1 by the World Health Organization in 2003. In 2015, in recognition of the burden resulting from tobacco use, strengthened tobacco control was included as a global development target in the 2030 Agenda for Sustainable Development2. Here we show that comprehensive tobacco control policies-including smoking bans, health warnings, advertising bans and tobacco taxes-are effective in reducing smoking prevalence; amplified positive effects are seen when these policies are implemented simultaneously within a given country. We find that if all 155 countries included in our counterfactual analysis had adopted smoking bans, health warnings and advertising bans at the strictest level and raised cigarette prices to at least 7.73 international dollars in 2009, there would have been about 100 million fewer smokers in the world in 2017. These findings highlight the urgent need for countries to move toward an accelerated implementation of a set of strong tobacco control practices, thus curbing the burden of smoking-attributable diseases and deaths.

    View details for DOI 10.1038/s41591-020-01210-8

    View details for PubMedID 33479500

  • Mapping Inequality in SARS-CoV-2 Household Exposure and Transmission Risk in the USA. Journal of general internal medicine Reitsma, M. B., Salomon, J. A., Goldhaber-Fiebert, J. D. 2021

    View details for DOI 10.1007/s11606-021-06603-0

    View details for PubMedID 33604818

    View details for PubMedCentralID PMC7891469

  • Spatial, temporal, and demographic patterns in prevalence of chewing tobacco use in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019. The Lancet. Public health 2021

    Abstract

    Chewing tobacco and other types of smokeless tobacco use have had less attention from the global health community than smoked tobacco use. However, the practice is popular in many parts of the world and has been linked to several adverse health outcomes. Understanding trends in prevalence with age, over time, and by location and sex is important for policy setting and in relation to monitoring and assessing commitment to the WHO Framework Convention on Tobacco Control.We estimated prevalence of chewing tobacco use as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 using a modelling strategy that used information on multiple types of smokeless tobacco products. We generated a time series of prevalence of chewing tobacco use among individuals aged 15 years and older from 1990 to 2019 in 204 countries and territories, including age-sex specific estimates. We also compared these trends to those of smoked tobacco over the same time period.In 2019, 273·9 million (95% uncertainty interval 258·5 to 290·9) people aged 15 years and older used chewing tobacco, and the global age-standardised prevalence of chewing tobacco use was 4·72% (4·46 to 5·01). 228·2 million (213·6 to 244·7; 83·29% [82·15 to 84·42]) chewing tobacco users lived in the south Asia region. Prevalence among young people aged 15-19 years was over 10% in seven locations in 2019. Although global age-standardised prevalence of smoking tobacco use decreased significantly between 1990 and 2019 (annualised rate of change: -1·21% [-1·26 to -1·16]), similar progress was not observed for chewing tobacco (0·46% [0·13 to 0·79]). Among the 12 highest prevalence countries (Bangladesh, Bhutan, Cambodia, India, Madagascar, Marshall Islands, Myanmar, Nepal, Pakistan, Palau, Sri Lanka, and Yemen), only Yemen had a significant decrease in the prevalence of chewing tobacco use, which was among males between 1990 and 2019 (-0·94% [-1·72 to -0·14]), compared with nine of 12 countries that had significant decreases in the prevalence of smoking tobacco. Among females, none of these 12 countries had significant decreases in prevalence of chewing tobacco use, whereas seven of 12 countries had a significant decrease in the prevalence of tobacco smoking use for the period.Chewing tobacco remains a substantial public health problem in several regions of the world, and predominantly in south Asia. We found little change in the prevalence of chewing tobacco use between 1990 and 2019, and that control efforts have had much larger effects on the prevalence of smoking tobacco use than on chewing tobacco use in some countries. Mitigating the health effects of chewing tobacco requires stronger regulations and policies that specifically target use of chewing tobacco, especially in countries with high prevalence.Bloomberg Philanthropies and the Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S2468-2667(21)00065-7

    View details for PubMedID 34051920

  • Dependence of COVID-19 Policies on End-of-Year Holiday Contacts in Mexico City Metropolitan Area: A Modeling Study. MDM policy & practice Alarid-Escudero, F., Gracia, V., Luviano, A., Roa, J., Peralta, Y., Reitsma, M. B., Claypool, A. L., Salomon, J. A., Studdert, D. M., Andrews, J. R., Goldhaber-Fiebert, J. D. 2021; 6 (2): 23814683211049249

    Abstract

    Background. Mexico City Metropolitan Area (MCMA) has the largest number of COVID-19 (coronavirus disease 2019) cases in Mexico and is at risk of exceeding its hospital capacity in early 2021. Methods. We used the Stanford-CIDE Coronavirus Simulation Model (SC-COSMO), a dynamic transmission model of COVID-19, to evaluate the effect of policies considering increased contacts during the end-of-year holidays, intensification of physical distancing, and school reopening on projected confirmed cases and deaths, hospital demand, and hospital capacity exceedance. Model parameters were derived from primary data, literature, and calibrated. Results. Following high levels of holiday contacts even with no in-person schooling, MCMA will have 0.9 million (95% prediction interval 0.3-1.6) additional COVID-19 cases between December 7, 2020, and March 7, 2021, and hospitalizations will peak at 26,000 (8,300-54,500) on January 25, 2021, with a 97% chance of exceeding COVID-19-specific capacity (9,667 beds). If MCMA were to control holiday contacts, the city could reopen in-person schools, provided they increase physical distancing with 0.5 million (0.2-0.9) additional cases and hospitalizations peaking at 12,000 (3,700-27,000) on January 19, 2021 (60% chance of exceedance). Conclusion. MCMA must increase COVID-19 hospital capacity under all scenarios considered. MCMA's ability to reopen schools in early 2021 depends on sustaining physical distancing and on controlling contacts during the end-of-year holiday.

    View details for DOI 10.1177/23814683211049249

    View details for PubMedID 34660906

    View details for PubMedCentralID PMC8512280

  • Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. Journal of the American College of Cardiology Roth, G. A., Mensah, G. A., Johnson, C. O., Addolorato, G., Ammirati, E., Baddour, L. M., Barengo, N. C., Beaton, A. Z., Benjamin, E. J., Benziger, C. P., Bonny, A., Brauer, M., Brodmann, M., Cahill, T. J., Carapetis, J., Catapano, A. L., Chugh, S. S., Cooper, L. T., Coresh, J., Criqui, M., DeCleene, N., Eagle, K. A., Emmons-Bell, S., Feigin, V. L., Fernandez-Sola, J., Fowkes, G., Gakidou, E., Grundy, S. M., He, F. J., Howard, G., Hu, F., Inker, L., Karthikeyan, G., Kassebaum, N., Koroshetz, W., Lavie, C., Lloyd-Jones, D., Lu, H. S., Mirijello, A., Temesgen, A. M., Mokdad, A., Moran, A. E., Muntner, P., Narula, J., Neal, B., Ntsekhe, M., Moraes de Oliveira, G., Otto, C., Owolabi, M., Pratt, M., Rajagopalan, S., Reitsma, M., Ribeiro, A. L., Rigotti, N., Rodgers, A., Sable, C., Shakil, S., Sliwa-Hahnle, K., Stark, B., Sundstrom, J., Timpel, P., Tleyjeh, I. M., Valgimigli, M., Vos, T., Whelton, P. K., Yacoub, M., Zuhlke, L., Murray, C., Fuster, V., GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group, Roth, G. A., Mensah, G. A., Johnson, C. O., Addolorato, G., Ammirati, E., Baddour, L. M., Barengo, N. C., Beaton, A., Benjamin, E. J., Benziger, C. P., Bonny, A., Brauer, M., Brodmann, M., Cahill, T. J., Carapetis, J. R., Catapano, A. L., Chugh, S., Cooper, L. T., Coresh, J., Criqui, M. H., DeCleene, N. K., Eagle, K. A., Emmons-Bell, S., Feigin, V. L., Fernandez-Sola, J., Fowkes, F. G., Gakidou, E., Grundy, S. M., He, F. J., Howard, G., Hu, F., Inker, L., Karthikeyan, G., Kassebaum, N. J., Koroshetz, W. J., Lavie, C., Lloyd-Jones, D., Lu, H. S., Mirijello, A., Misganaw, A. T., Mokdad, A. H., Moran, A. E., Muntner, P., Narula, J., Neal, B., Ntsekhe, M., Oliveira, G. M., Otto, C. M., Owolabi, M. O., Pratt, M., Rajagopalan, S., Reitsma, M. B., Ribeiro, A. L., Rigotti, N. A., Rodgers, A., Sable, C. A., Shakil, S. S., Sliwa, K., Stark, B. A., Sundstrom, J., Timpel, P., Tleyjeh, I. I., Valgimigli, M., Vos, T., Whelton, P. K., Yacoub, M., Zuhlke, L. J., Abbasi-Kangevari, M., Abdi, A., Abedi, A., Aboyans, V., Abrha, W. A., Abu-Gharbieh, E., Abushouk, A. I., Acharya, D., Adair, T., Adebayo, O. M., Ademi, Z., Advani, S. M., Afshari, K., Afshin, A., Agarwal, G., Agasthi, P., Ahmad, S., Ahmadi, S., Ahmed, M. B., Aji, B., Akalu, Y., Akande-Sholabi, W., Aklilu, A., Akunna, C. J., Alahdab, F., Al-Eyadhy, A., Alhabib, K. F., Alif, S. M., Alipour, V., Aljunid, S. M., Alla, F., Almasi-Hashiani, A., Almustanyir, S., Al-Raddadi, R. M., Amegah, A. K., Amini, S., Aminorroaya, A., Amu, H., Amugsi, D. A., Ancuceanu, R., Anderlini, D., Andrei, T., Andrei, C. L., Ansari-Moghaddam, A., Anteneh, Z. A., Antonazzo, I. C., Antony, B., Anwer, R., Appiah, L. T., Arabloo, J., Arnlov, J., Artanti, K. D., Ataro, Z., Ausloos, M., Avila-Burgos, L., Awan, A. T., Awoke, M. A., Ayele, H. T., Ayza, M. A., Azari, S., B, D. B., Baheiraei, N., Baig, A. A., Bakhtiari, A., Banach, M., Banik, P. C., Baptista, E. A., Barboza, M. A., Barua, L., Basu, S., Bedi, N., Bejot, Y., Bennett, D. A., Bensenor, I. M., Berman, A. E., Bezabih, Y. M., Bhagavathula, A. S., Bhaskar, S., Bhattacharyya, K., Bijani, A., Bikbov, B., Birhanu, M. M., Boloor, A., Brant, L. C., Brenner, H., Briko, N. I., Butt, Z. A., Caetano Dos Santos, F. L., Cahill, L. E., Cahuana-Hurtado, L., Camera, L. A., Campos-Nonato, I. R., Cantu-Brito, C., Car, J., Carrero, J. J., Carvalho, F., Castaneda-Orjuela, C. A., Catala-Lopez, F., Cerin, E., Charan, J., Chattu, V. K., Chen, S., Chin, K. L., Choi, J. J., Chu, D., Chung, S., Cirillo, M., Coffey, S., Conti, S., Costa, V. M., Cundiff, D. K., Dadras, O., Dagnew, B., Dai, X., Damasceno, A. A., Dandona, L., Dandona, R., Davletov, K., De la Cruz-Gongora, V., De la Hoz, F. 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    Abstract

    Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285million)in1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.

    View details for DOI 10.1016/j.jacc.2020.11.010

    View details for PubMedID 33309175

  • Five insights from the Global Burden of Disease Study 2019 LANCET Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abedi, A., Abedi, P., Abegaz, K., Abolhassani, H., Abosetugn, A., Aboyans, V., Abrams, E. M., Abreu, L., Abrigo, M. M., Abu Haimed, A., Abualhasan, A., Abu-Gharbieh, E., Abu-Raddad, L., Abushouk, A. I., Acebedo, A., Ackerman, I. N., Adabi, M., Adair, T., Adamu, A. A., Adebayo, O. M., Adedeji, I., Adekanmbi, V., Adelson, J. D., Adeoye, A., Adetokunboh, O. O., Adham, D., Advani, S. M., Afarideh, M., Afshari, M., Afshin, A., Agardh, E. E., Agarwal, G., Agasthi, P., Agesa, K. M., Aghaali, M., Aghamir, S., Agrawal, A., Ahmad, T., Ahmadi, A., Ahmadi, K., Ahmadi, M., Ahmadieh, H., Ahmadpour, E., Ahmed, M., Aji, B., Akalu, T., Akinyemi, R., Akinyemiju, T., Akombi, B., Akunna, C., Alahdab, F., Al-Aly, Z., Alam, K., Alam, N., Alam, S., Alam, T., Alanezi, F., Alanzi, T. 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    Abstract

    The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.

    View details for Web of Science ID 000579154000005

    View details for PubMedID 33069324

  • Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 LANCET Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abolhassani, H., Aboyans, V., Abrams, E. M., Abreu, L., Abrigo, M. M., Abu-Raddad, L., Abushouk, A. I., Acebedo, A., Ackerman, I. N., Adabi, M., Adamu, A. A., Adebayo, O. M., Adekanmbi, V., Adelson, J. D., Adetokunboh, O. O., Adham, D., Afshari, M., Afshin, A., Agardh, E. E., Agarwal, G., Agesa, K. M., Aghaali, M., Aghamir, S., Agrawal, A., Ahmad, T., Ahmadi, A., Ahmadi, M., Ahmadieh, H., Ahmadpour, E., Akalu, T., Akinyemi, R., Akinyemiju, T., Akombi, B., Al-Aly, Z., Alam, K., Alam, N., Alam, S., Alam, T., Alanzi, T. M., Albertson, S. 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    Abstract

    In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries.GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution.Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990-2010 time period, with the greatest annualised rate of decline occurring in the 0-9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10-24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10-24 years were also in the top ten in the 25-49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50-74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI.As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000579154000007

    View details for PubMedID 33069326

    View details for PubMedCentralID PMC7567026

  • Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019 LANCET Murray, C. L., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abegaz, K., Abolhassani, H., Aboyans, V., Abreu, L., Abrigo, M. M., Abualhasan, A., Abu-Raddad, L., Abushouk, A. I., Adabi, M., Adekanmbi, V., Adeoye, A., Adetokunboh, O. O., Adham, D., Advani, S. M., Agarwal, G., Aghamir, S., Agrawal, A., Ahmad, T., Ahmadi, K., Ahmadi, M., Ahmadieh, H., Ahmed, M., Akalu, T., Akinyemi, R., Akinyemiju, T., Akombi, B., Akunna, C., Alahdab, F., Al-Aly, Z., Alam, K., Alam, S., Alam, T., Alanezi, F., Alanzi, T. M., Alemu, B., Alhabib, K. F., Ali, M., Ali, S., Alicandro, G., Alinia, C., Alipour, V., Alizade, H., Aljunid, S., Alla, F., Allebeck, P., Almasi-Hashiani, A., Al-Mekhlafi, H. M., Alonso, J., Altirkawi, K. A., Amini-Rarani, M., Amiri, F., Amugsi, D. A., Ancuceanu, R., Anderlini, D., Anderson, J. A., Andrei, C., Andrei, T., Angus, C., Anjomshoa, M., Ansari, F., Ansari-Moghaddam, A., Antonazzo, I., Antonio, C. T., Antony, C. M., Antriyandarti, E., Anvari, D., Anwer, R., Appiah, S., Arabloo, J., Arab-Zozani, M., Ariani, F., Armoon, B., Arnlov, J., Arzani, A., Asadi-Aliabadi, M., Asadi-Pooya, A. A., Ashbaugh, C., Assmus, M., Atafar, Z., Atnafu, D., Atout, M., Ausloos, F., Ausloos, M., Quintanilla, B., Ayano, G., Ayanore, M., Azari, S., Azarian, G., Azene, Z., Badawi, A., Badiye, A. D., Bahrami, M., Bakhshaei, M., Bakhtiari, A., Bakkannavar, S. M., Baldasseroni, A., Ball, K., Ballew, S. H., Balzi, D., Banach, M., Banerjee, S. K., Bante, A., Baraki, A., Barker-Collo, S., Barnighausen, T., Barrero, L. H., Barthelemy, C. M., Barua, L., Basu, S., Baune, B. T., Bayati, M., Becker, J. S., Bedi, N., Beghi, E., Bejot, Y., Bell, M. L., Bennitt, F. B., Bensenor, I. M., Berhe, K., Berman, A. E., Bhagavathula, A., Bhageerathy, R., Bhala, N., Bhandari, D., Bhattacharyya, K., Bhutta, Z. A., Bijani, A., Bikbov, B., Bin Sayeed, M., Biondi, A., Birihane, B., Bisignano, C., Biswas, R., Bitew, H., Bohlouli, S., Bohluli, M., Boon-Dooley, A. S., Borges, G., Borzi, A., Borzouei, S., Bosetti, C., Boufous, S., Braithwaite, D., Breitborde, N. K., Breitner, S., Brenner, H., Briant, P., Briko, A., Briko, N., Britton, G. B., Bryazka, D., Bumgarner, B. R., Burkart, K., Burnett, R., Nagaraja, S., Butt, Z. A., dos Santos, F., Cahill, L. E., Camera, L., Campos-Nonato, I. R., Cardenas, R., Carreras, G., Carrero, J. J., Carvalho, F., Castaldelli-Maia, J., Castaneda-Orjuela, C. A., Castelpietra, G., Castro, F., Causey, K., Cederroth, C. R., Cercy, K. M., Cerin, E., Chandan, J., Chang, K., Charlson, F. J., Chattu, V., Chaturvedi, S., Cherbuin, N., Chimed-Ochir, O., Cho, D., Choi, J., Christensen, H., Chu, D., Chung, M. T., Chung, S., Cicuttini, F. M., Ciobanu, L. G., Cirillo, M., Classen, T., Cohen, A. J., Compton, K., Cooper, O. R., Costa, V., Cousin, E., Cowden, R. G., Cross, D. H., Cruz, J. A., Dahlawi, S. A., Damasceno, A., Damiani, G., Dandona, L., Dandona, R., Dangel, W., Danielsson, A., Dargan, P. I., Darwesh, A., Daryani, A., Das, J. K., Das Gupta, R., das Neves, J., Davila-Cervantes, C., Davitoiu, D., De Leo, D., Degenhardt, L., DeLang, M., Dellavalle, R., Demeke, F., Demoz, G., Demsie, D., Denova-Gutierrez, E., Dervenis, N., Dhungana, G., Dianatinasab, M., da Silva, D., Diaz, D., Forooshani, Z., Djalalinia, S., Do, H., Dokova, K., Dorostkar, F., Doshmangir, L., Driscoll, T., Duncan, B. B., Duraes, A., Eagan, A., Edvardsson, D., El Nahas, N., El Sayed, I., El Tantawi, M., Elbarazi, I., Elgendy, I. Y., El-Jaafary, S. I., Elyazar, I. F., Emmons-Bell, S., Erskine, H. 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P., Kusuma, D., La Vecchia, C., Lacey, B., Lal, D., Lalloo, R., Lallukka, T., Lami, F., Landires, I., Lang, J. J., Langan, S. M., Larsson, A. O., Lasrado, S., Lauriola, P., Lazarus, J. V., Lee, P. H., Lee, S., LeGrand, K. E., Leigh, J., Leonardi, M., Lescinsky, H., Leung, J., Levi, M., Li, S., Lim, L., Linn, S., Liu, S., Liu, S., Liu, Y., Lo, J., Lopez, A. D., Lopez, J. F., Lopukhov, P. D., Lorkowski, S., Lotufo, P. A., Lu, A., Lugo, A., Maddison, E. R., Mahasha, P., Mahdavi, M., Mahmoudi, M., Majeed, A., Maleki, A., Maleki, S., Malekzadeh, R., Malta, D., Mamun, A. A., Manda, A., Manguerra, H., Mansour-Ghanaei, F., Mansouri, B., Mansournia, M., Herrera, A., Maravilla, J. C., Marks, A., Martin, R. V., Martini, S., Martins-Melo, F., Masaka, A., Masoumi, S., Mathur, M., Matsushita, K., Maulik, P. K., McAlinden, C., McGrath, J. J., McKee, M., Mehndiratta, M., Mehri, F., Mehta, K. M., Memish, Z. A., Mendoza, W., Menezes, R. G., Mengesha, E., Mereke, A., Mereta, S., Meretoja, A., Meretoja, T. J., Mestrovic, T., Miazgowski, B., Miazgowski, T., Michalek, I., Miller, T. R., Mills, E. J., Mini, G. K., Miri, M., Mirica, A., Mirrakhimov, E. M., Mirzaei, H., Mirzaei, M., Mirzaei, R., Mirzaei-Alavijeh, M., Misganaw, A., Mithra, P., Moazen, B., Mohammad, D. K., Mohammad, Y., Mezerji, N., Mohammadian-Hafshejani, A., Mohammadifard, N., Mohammadpourhodki, R., Mohammed, A., Mohammed, H., Mohammed, J., Mohammed, S., Mokdad, A. H., Molokhia, M., Monasta, L., Mooney, M. D., Moradi, G., Moradi, M., Moradi-Lakeh, M., Moradzadeh, R., Moraga, P., Morawska, L., Morgado-da-Costa, J., Morrison, S., Mosapour, A., Mosser, J. F., Mouodi, S., Mousavi, S., Khaneghah, A., Mueller, U., Mukhopadhyay, S., Mullany, E. C., Musa, K., Muthupandian, S., Nabhan, A. F., Naderi, M., Nagarajan, A., Nagel, G., Naghavi, M., Naghshtabrizi, B., Naimzada, M., Najafi, F., Nangia, V., Nansseu, J., Naserbakht, M., Nayak, V. C., Negoi, I., Ngunjiri, J. W., Nguyen, C., Nguyen, H., Nguyen, M., Nigatu, Y. T., Nikbakhsh, R., Nixon, M. R., Nnaji, C. A., Nomura, S., Norrving, B., Noubiap, J., Nowak, C., Nunez-Samudio, V., Otoiu, A., Oancea, B., Odell, C. M., Ogbo, F., Oh, I., Okunga, E., Oladnabi, M., Olagunju, A. T., Olusanya, B., Olusanya, J., Omer, M., Ong, K. L., Onwujekwe, O. E., Orpana, H. M., Ortiz, A., Osarenotor, O., Osei, F. B., Ostroff, S. M., Otstavnov, N., Otstavnov, S. S., Overland, S., Owolabi, M. O., Mahesh, P. A., Padubidri, J., Palladino, R., Panda-Jonas, S., Pandey, A., Parry, C. H., Pasovic, M., Pasupula, D., Patel, S., Pathak, M., Patten, S. B., Patton, G. C., Toroudi, H., Peden, A. E., Pennini, A., Pepito, V., Peprah, E. K., Pereira, D. M., Pesudovs, K., Pham, H., Phillips, M. R., Piccinelli, C., Pilz, T. M., Piradov, M. A., Pirsaheb, M., Plass, D., Polinder, S., Polkinghorne, K. R., Pond, C., Postma, M. J., Pourjafar, H., Pourmalek, F., Poznanska, A., Prada, S. I., Prakash, V., Pribadi, D., Pupillo, E., Syed, Z., Rabiee, M., Rabiee, N., Radfar, A., Rafiee, A., Raggi, A., Rahman, M., Rajabpour-Sanati, A., Rajati, F., Rakovac, I., Ram, P., Ramezanzadeh, K., Ranabhat, C., Rao, P. C., Rao, S. J., Rashedi, V., Rathi, P., Rawaf, D., Rawaf, S., Rawal, L., Rawassizadeh, R., Rawat, R., Razo, C., Redford, S., Reiner, R. C., Reitsma, M., Remuzzi, G., Renjith, V., Renzaho, A. N., Resnikoff, S., Rezaei, N., Rezaei, N., Rezapour, A., Rhinehart, P., Riahi, S., Ribeiro, D., Ribeiro, D., Rickard, J., Rivera, J. A., Roberts, N. S., Rodriguez-Ramirez, S., Roever, L., Ronfani, L., Room, R., Roshandel, G., Roth, G. A., Rothenbacher, D., Rubagotti, E., Rwegerera, G. M., Sabour, S., Sachdev, P. S., Saddik, B., Sadeghi, E., Sadeghi, M., Saeedi, R., Moghaddam, S., Safari, Y., Safi, S., Safiri, S., Sagar, R., Sahebkar, A., Sajadi, S., Salam, N., Salamati, P., Salem, H., Salem, M., Salimzadeh, H., Salman, O., Salomon, J. A., Samad, Z., Kafil, H., Sambala, E., Samy, A. 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    Abstract

    Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease.GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk-outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk-outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk-outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden.The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51-12·1) deaths (19·2% [16·9-21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12-9·31) deaths (15·4% [14·6-16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253-350) DALYs (11·6% [10·3-13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0-9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10-24 years, alcohol use for those aged 25-49 years, and high systolic blood pressure for those aged 50-74 years and 75 years and older.Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000579154000008

    View details for PubMedID 33069327

    View details for PubMedCentralID PMC7566194

  • Trends in prevalence and mortality burden attributable to smoking, Brazil and federated units, 1990 and 2017. Population health metrics Malta, D. C., Flor, L. S., Machado, I. E., Felisbino-Mendes, M. S., Brant, L. C., Ribeiro, A. L., Teixeira, R. A., Macario, E. M., Reitsma, M. B., Glenn, S., Naghavi, M., Gakidou, E. 2020; 18 (Suppl 1): 24

    Abstract

    BACKGROUND: The present study sought to analyze smoking prevalence and smoking-attributable mortality estimates produced by the 2017 Global Burden of Disease Study for Brazil, 26 states, and the Federal District.METHODS: Prevalence of current smokers from 1990 to 2017 by sex and age was estimated using spatiotemporal Gaussian process regression. Population-attributable fractions were calculated for different risk-outcome pairs to generate estimates of smoking-attributable mortality. A cohort analysis of smoking prevalence by birth-year cohort was performed to better understand temporal age patterns in smoking. Smoking-attributable mortality rates were described and analyzed by development at state levels, using the Socio-Demographic Index (SDI). Finally, a decomposition analysis was conducted to evaluate the contribution of different factors to the changes in the number of deaths attributable to smoking between 1990 and 2017.RESULTS: Between 1990 and 2017, prevalence of smoking in the population (≥ 20years old) decreased from 35.3 to 11.3% in Brazil. This downward trend was seen for both sexes and in all states, with a marked reduction in exposure to this risk factor in younger cohorts. Smoking-attributable mortality rates decreased by 57.8% (95% UI -61.2, -54.1) between 1990 and 2017. Overall, larger reductions were observed in states with higher SDI (Pearson correlation 0.637; p < 0.01). In Brazil, smoking remains responsible for a considerable amount of deaths, especially due to cardiovascular diseases and neoplasms.CONCLUSIONS: Brazil has adopted a set of regulatory measures and implemented anti-tobacco policies that, along with improvements in socioeconomic conditions, have contributed to the results presented in the present study. Other regulatory measures need to be implemented to boost a reduction in smoking in order to reach the goals established in the scope of the 2030 United Nations Agenda for Sustainable Development.

    View details for DOI 10.1186/s12963-020-00215-2

    View details for PubMedID 32993660

  • Community-based interventions for detection and management of diabetes and hypertension in underserved communities: a mixed-methods evaluation in Brazil, India, South Africa and the USA. BMJ global health Flor, L. S., Wilson, S., Bhatt, P., Bryant, M., Burnett, A., Camarda, J. N., Chakravarthy, V., Chandrashekhar, C., Chaudhury, N., Cimini, C., Colombara, D. V., Narayanan, H. C., Cortes, M. L., Cowling, K., Daly, J., Duber, H., Ellath Kavinkare, V., Endlich, P., Fullman, N., Gabert, R., Glucksman, T., Harris, K. P., Loguercio Bouskela, M. A., Maia, J., Mandile, C., Marcolino, M. S., Marshall, S., McNellan, C. R., Medeiros, D. S., Mistro, S., Mulakaluri, V., Murphree, J., Ng, M., Oliveira, J. A., Oliveira, M. G., Phillips, B., Pinto, V., Polzer Ngwato, T., Radant, T., Reitsma, M. B., Ribeiro, A. L., Roth, G., Rumel, D., Sethi, G., Soares, D. A., Tamene, T., Thomson, B., Tomar, H., Ugliara Barone, M. T., Valsangkar, S., Wollum, A., Gakidou, E. 2020; 5 (6)

    Abstract

    INTRODUCTION: As non-communicable disease (NCD) burden rises worldwide, community-based programmes are a promising strategy to bridge gaps in NCD care. The HealthRise programme sought to improve hypertension and diabetes management for underserved communities in nine sites across Brazil, India, South Africa and the USA between 2016 and 2018. This study presents findings from the programme's endline evaluation.METHODS: The evaluation utilises a mixed-methods quasi-experimental design. Process indicators assess programme implementation; quantitative data examine patients' biometric measures and qualitative data characterise programme successes and challenges. Programme impact was assessed using the percentage of patients meeting blood pressure and A1c treatment targets and tracking changes in these measures over time.RESULTS: Almost 60000 screenings, most of them in India, resulted in 1464 new hypertension and 295 new diabetes cases across sites. In Brazil, patients exhibited statistically significant reductions in blood pressure and A1c. In Shimla, India, and in South Africa, country with the shortest implementation period, there were no differences between patients served by facilities in HealthRise areas relative to comparison areas. Among participating patients with diabetes in Hennepin and Ramsey counties and hypertension patients in Hennepin County, the percentage of HealthRise patients meeting treatment targets at endline was significantly higher relative to comparison group patients. Qualitative analysis identified linking different providers, services, communities and information systems as positive HealthRise attributes. Gaps in health system capacities and sociodemographic factors, including poverty, low levels of health education and limited access to nutritious food, are remaining challenges.CONCLUSIONS: Findings from Brazil and the USA indicate that the HealthRise model has the potential to improve patient outcomes. Short implementation periods and strong emphasis on screening may have contributed to the lack of detectable differences in other sites. Community-based care cannot deliver its full potential if sociodemographic and health system barriers are not addressed in tandem.

    View details for DOI 10.1136/bmjgh-2019-001959

    View details for PubMedID 32503887

  • Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 LANCET RESPIRATORY MEDICINE Soriano, J. B., Kendrick, P. J., Paulson, K. R., Gupta, V., Vos, T., Abrams, E. M., Adedoyin, R., Adhikari, T., Advani, S. M., Agrawal, A., Ahmadian, E., Alahdab, F., Aljunid, S., Altirkawi, K. A., Alvis-Guzman, N., Anber, N., Andrei, C., Anjomshoa, M., Ansari, F., Anto, J. M., Arabloo, J., Athari, S., Athari, S., Awoke, N., Badawi, A., Banoub, J., Bennett, D. A., Bensenor, I. M., Berfield, K., Bernstein, R. S., Bhattacharyya, K., Bijani, A., Brauer, M., Bukhman, G., Butt, Z. A., Camera, L., Car, J., Carrero, J. J., Carvalho, F., Castaneda-Orjuela, C. A., Choi, J., Christopher, D. J., Cohen, A. J., Dandona, L., Dandona, R., Dang, A., Daryani, A., de Courten, B., Demeke, F., Demoz, G., De Neve, J., Desai, R., Dharmaratne, S., Diaz, D., Douiri, A., Driscoll, T., Duken, E., Eftekhari, A., Elkout, H., Endries, A., Fadhil, I., Faro, A., Farzadfar, F., Fernandes, E., Filip, I., Fischer, F., Foroutan, M., Garcia-Gordillo, M. A., Gebre, A., Gebremedhin, K., Gebremeskel, G., Gezae, K., Ghoshal, A., Gill, P., Gillum, R. F., Goudarzi, H., Guo, Y., Gupta, R., Hailu, G., Hasanzadeh, A., Hassen, H., Hay, S. I., Hoang, C., Hole, M. K., Horita, N., Hosgood, H., Hostiuc, M., Househ, M., Ilesanmi, O., Ilic, M. D., Irvani, S., Islam, S., Jakovljevic, M., Jamal, A. A., Jha, R., Jonas, J. B., Kabir, Z., Kasaeian, A., Kasahun, G., Kassa, G., Kefale, A., Kengne, A., Khader, Y., Khafaie, M., Khan, E., Khan, J., Khubchandani, J., Kim, Y., Kim, Y., Kisa, S., Kisa, A., Knibbs, L. D., Komaki, H., Koul, P. A., Koyanagi, A., Kumar, G., Lan, Q., Lasrado, S., Lauriola, P., La Vecchia, C., Tham Thi Le, Leigh, J., Levi, M., Li, S., Lopez, A. D., Lotufo, P. A., Madotto, F., Mahotra, N. B., Majdan, M., Majeed, A., Malekzadeh, R., Mamun, A. A., Manafi, N., Manafi, F., Mantovani, L., Meharie, B., Meles, H., Meles, G., Menezes, R. G., Mestrovic, T., Miller, T. R., Mini, G. K., Mirrakhimov, E. M., Moazen, B., Mohammad, K., Mohammed, S., Mohebi, F., Mokdad, A. H., Molokhia, M., Monasta, L., Moradi, M., Moradi, G., Morawska, L., Mousavi, S., Musa, K., Mustafa, G., Naderi, M., Naghavi, M., Naik, G., Nair, S., Nangia, V., Nansseu, J., Nazari, J., Ndwandwe, D., Negoi, R., Trang Huyen Nguyen, Cuong Tat Nguyen, Huong Lan Thi Nguyen, Nixon, M. R., Ofori-Asenso, R., Ogbo, F., Olagunju, A. T., Olagunju, T. O., Oren, E., Ortiz, J. R., Owolabi, M. O., Mahesh, P. A., Pakhale, S., Pana, A., Panda-Jonas, S., Park, E., Hai Quang Pham, Postma, M. J., Pourjafar, H., Poustchi, H., Radfar, A., Rafiei, A., Rahim, F., Rahman, M., Rahman, M., Rawaf, S., Rawaf, D., Rawal, L., Reiner, R. C., Reitsma, M., Roever, L., Ronfani, L., Roro, E., Roshandel, G., Rudd, K. E., Sabde, Y., Sabour, S., Saddik, B., Safari, S., Saleem, K., Samy, A. M., Santric-Milicevic, M. M., Jose, B., Sartorius, B., Satpathy, M., Savic, M., Sawhney, M., Sepanlou, S. G., Shaikh, M., Sheikh, A., Shigematsu, M., Shirkoohi, R., Si, S., Siabani, S., Singh, V., Singh, J. A., Soljak, M., Somayaji, R., Soofi, M., Soyiri, I. N., Tefera, Y., Temsah, M., Tesfay, B., Thakur, J., Toma, A., Tortajada-Girbes, M., Khanh Bao Tran, Bach Xuan Tran, Car, L., Ullah, I., Vacante, M., Valdez, P. R., van Boven, J. M., Vasankari, T., Veisani, Y., Violante, F. S., Wagner, G. R., Westerman, R., Wolfe, C. A., Wondafrash, D., Wondmieneh, A., Yonemoto, N., Yoon, S., Zaidi, Z., Zamani, M., Zar, H. J., Zhang, Y., GBD Chronic Resp Dis Collaborators 2020; 8 (6): 585-596

    Abstract

    Previous attempts to characterise the burden of chronic respiratory diseases have focused only on specific disease conditions, such as chronic obstructive pulmonary disease (COPD) or asthma. In this study, we aimed to characterise the burden of chronic respiratory diseases globally, providing a comprehensive and up-to-date analysis on geographical and time trends from 1990 to 2017.Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we estimated the prevalence, morbidity, and mortality attributable to chronic respiratory diseases through an analysis of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLL) by GBD super-region, from 1990 to 2017, stratified by age and sex. Specific diseases analysed included asthma, COPD, interstitial lung disease and pulmonary sarcoidosis, pneumoconiosis, and other chronic respiratory diseases. We also assessed the contribution of risk factors (smoking, second-hand smoke, ambient particulate matter and ozone pollution, household air pollution from solid fuels, and occupational risks) to chronic respiratory disease-attributable DALYs.In 2017, 544·9 million people (95% uncertainty interval [UI] 506·9-584·8) worldwide had a chronic respiratory disease, representing an increase of 39·8% compared with 1990. Chronic respiratory disease prevalence showed wide variability across GBD super-regions, with the highest prevalence among both males and females in high-income regions, and the lowest prevalence in sub-Saharan Africa and south Asia. The age-sex-specific prevalence of each chronic respiratory disease in 2017 was also highly variable geographically. Chronic respiratory diseases were the third leading cause of death in 2017 (7·0% [95% UI 6·8-7·2] of all deaths), behind cardiovascular diseases and neoplasms. Deaths due to chronic respiratory diseases numbered 3 914 196 (95% UI 3 790 578-4 044 819) in 2017, an increase of 18·0% since 1990, while total DALYs increased by 13·3%. However, when accounting for ageing and population growth, declines were observed in age-standardised prevalence (14·3% decrease), age-standardised death rates (42·6%), and age-standardised DALY rates (38·2%). In males and females, most chronic respiratory disease-attributable deaths and DALYs were due to COPD. In regional analyses, mortality rates from chronic respiratory diseases were greatest in south Asia and lowest in sub-Saharan Africa, also across both sexes. Notably, although absolute prevalence was lower in south Asia than in most other super-regions, YLLs due to chronic respiratory diseases across the subcontinent were the highest in the world. Death rates due to interstitial lung disease and pulmonary sarcoidosis were greater than those due to pneumoconiosis in all super-regions. Smoking was the leading risk factor for chronic respiratory disease-related disability across all regions for men. Among women, household air pollution from solid fuels was the predominant risk factor for chronic respiratory diseases in south Asia and sub-Saharan Africa, while ambient particulate matter represented the leading risk factor in southeast Asia, east Asia, and Oceania, and in the Middle East and north Africa super-region.Our study shows that chronic respiratory diseases remain a leading cause of death and disability worldwide, with growth in absolute numbers but sharp declines in several age-standardised estimators since 1990. Premature mortality from chronic respiratory diseases seems to be highest in regions with less-resourced health systems on a per-capita basis.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000540618400031

    View details for PubMedID 32526187

    View details for PubMedCentralID PMC7284317

  • Quantifying risks and interventions that have affected the burden of lower respiratory infections among children younger than 5 years: an analysis for the Global Burden of Disease Study 2017 LANCET INFECTIOUS DISEASES Troeger, C. E., Khalil, I. A., Blacker, B. F., Biehl, M. H., Albertson, S. B., Zimsen, S. M., Rao, P. C., Abate, D., Admasie, A., Ahmadi, A., Ahmed, M., Akal, C., Alahdab, F., Alam, N., Alene, K., Alipour, V., Aljunid, S., Al-Raddadi, R. M., Alvis-Guzman, N., Amini, S., Anjomshoa, M., Antonio, C. T., Arabloo, J., Aremu, O., Atalay, H., Atique, S., Avokpaho, E. A., Awad, S., Awasthi, A., Badawi, A., Balakrishnan, K., Banoub, J., Barac, A., Bassat, Q., Bedi, N., Bennett, D. A., Bhattacharyya, K., Bhutta, Z. A., Bijani, A., Bills, C. B., Car, J., Carvalho, F., Castaneda-Orjuela, C. A., Causey, K., Christopher, D. J., Cohen, A. J., Dandona, L., Dandona, R., Daryani, A., Demeke, F., Djalalinia, S., Dubey, M., Dubljanin, E., Duken, E., Zaki, M., Endries, A., Fernandes, E., Fischer, F., Frostad, J., Fullman, N., Gardner, W. M., Geta, B., Ghadiri, K., Gorini, G., Goulart, A. C., Guo, Y., Hailu, G., Haj-Mirzaian, A., Haj-Mirzaian, A., Hamidi, S., Hassen, H., Chi Linh Hoang, Horita, N., Hostiuc, M., Hussain, Z., Irvani, S., James, S. L., Jha, R., Jonas, J. B., Karch, A., Kasaeian, A., Kassa, T., Kassebaum, N. J., Kefale, A., Khader, Y., Khan, E., Khan, G., Khan, M., Khang, Y., Khoja, A. T., Kimokoti, R. W., Kisa, A., Kisa, S., Kissoon, N., Knibbs, L. D., Kochhar, S., Kosen, S., Koul, P. A., Koyanagi, A., Defo, B., Kumar, G., Lal, D., Leshargie, C., Lewycka, S., Li, S., Lodha, R., Macarayan, E., Majdan, M., Mamun, A. A., Manguerra, H., Mehta, V., Melese, A., Memish, Z. A., Mengistu, D., Meretoja, T. J., Mestrovic, T., Miazgowski, B., Mirrakhimov, E. M., Moazen, B., Mohammad, K., Mohammed, S., Monasta, L., Moore, C. E., Morawska, L., Mosser, J. F., Mousavi, S., Murthy, S., Mustafa, G., Nazari, J., Cuong Tat Nguyen, Huong Lan Thi Nguyen, Long Hoang Nguyen, Son Hoang Nguyen, Nielsen, K. R., Nisar, M., Nixon, M. R., Ogbo, F., Okoro, A., Olagunju, A. T., Olagunju, T. O., Oren, E., Ortiz, J. R., Mahesh, P. A., Pakhale, S., Postma, M. J., Qorbani, M., Quansah, R., Rafiei, A., Rahim, F., Rahimi-Movaghar, V., Rai, R., Reitsma, M., Rezai, M., Rezapour, A., Jesus Rios-Blancas, M., Ronfani, L., Rothenbacher, D., Rubino, S., Saleem, Z., Sambala, E., Samy, A. M., Milicevic, M., Sarmiento-Suarez, R., Sartorius, B., Savic, M., Sawhney, M., Saxena, S., Sbarra, A., Seyedmousavi, S., Shaikh, M., Sheikh, A., Shigematsu, M., Smith, D. L., Sreeramareddy, C. T., Stanaway, J. D., Sufiyan, M., Temsah, M., Tessema, B., Bach Xuan Tran, Khanh Bao Tran, Tsadik, A., Ullah, I., Updike, R. L., Vasankari, T., Veisani, Y., Wada, F., Waheed, Y., Welgan, K., Wiens, K. E., Wiysonge, C., Yimer, E. M., Yonemoto, N., Zaidi, Z., Zar, H. J., Lim, S. S., Vos, T., Mokdad, A. H., Murray, C. L., Kyu, H., Hay, S. I., Reiner, R. C., GBD Lower Resp Infect 2020; 20 (1): 60–79

    Abstract

    Despite large reductions in under-5 lower respiratory infection (LRI) mortality in many locations, the pace of progress for LRIs has generally lagged behind that of other childhood infectious diseases. To better inform programmes and policies focused on preventing and treating LRIs, we assessed the contributions and patterns of risk factor attribution, intervention coverage, and sociodemographic development in 195 countries and territories by drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) LRI estimates.We used four strategies to model LRI burden: the mortality due to LRIs was modelled using vital registration data, demographic surveillance data, and verbal autopsy data in a predictive ensemble modelling tool; the incidence of LRIs was modelled using population representative surveys, health-care utilisation data, and scientific literature in a compartmental meta-regression tool; the attribution of risk factors for LRI mortality was modelled in a counterfactual framework; and trends in LRI mortality were analysed applying changes in exposure to risk factors over time. In GBD, infectious disease mortality, including that due to LRI, is among HIV-negative individuals. We categorised locations based on their burden in 1990 to make comparisons in the changing burden between 1990 and 2017 and evaluate the relative percent change in mortality rate, incidence, and risk factor exposure to explain differences in the health loss associated with LRIs among children younger than 5 years.In 2017, LRIs caused 808 920 deaths (95% uncertainty interval 747 286-873 591) in children younger than 5 years. Since 1990, there has been a substantial decrease in the number of deaths (from 2 337 538 to 808 920 deaths; 65·4% decrease, 61·5-68·5) and in mortality rate (from 362·7 deaths [330·1-392·0] per 100 000 children to 118·9 deaths [109·8-128·3] per 100 000 children; 67·2% decrease, 63·5-70·1). LRI incidence declined globally (32·4% decrease, 27·2-37·5). The percent change in under-5 mortality rate and incidence has varied across locations. Among the risk factors assessed in this study, those responsible for the greatest decrease in under-5 LRI mortality between 1990 and 2017 were increased coverage of vaccination against Haemophilus influenza type b (11·4% decrease, 0·0-24·5), increased pneumococcal vaccine coverage (6·3% decrease, 6·1-6·3), and reductions in household air pollution (8·4%, 6·8-9·2).Our findings show that there have been substantial but uneven declines in LRI mortality among countries between 1990 and 2017. Although improvements in indicators of sociodemographic development could explain some of these trends, changes in exposure to modifiable risk factors are related to the rates of decline in LRI mortality. No single intervention would universally accelerate reductions in health loss associated with LRIs in all settings, but emphasising the most dominant risk factors, particularly in countries with high case fatality, can contribute to the reduction of preventable deaths.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S1473-3099(19)30410-4

    View details for Web of Science ID 000504005300043

    View details for PubMedID 31678026

  • Reexamining Rates of Decline in Lung Cancer Risk after Smoking Cessation: A meta-analysis. Annals of the American Thoracic Society Reitsma, M. n., Kendrick, P. n., Anderson, J. n., Arian, N. n., Feldman, R. n., Gakidou, E. n., Gupta, V. n. 2020

    Abstract

    Prior studies have questioned whether prevailing eligibility criteria for lung cancer screening are sufficiently inclusive of former smokers who remain at elevated risk of disease outside current screening windows.Characterize the percent of the reducible relative risk remaining (RRR) for lung cancer as a function of years since quitting.MEDLINE and PubMed were searched from January 2011 to May 2018; key search terms included smoking and cancer. Current smoker relative risks were extracted to represent former smokers at zero years since quitting; data were transformed assuming a lognormal distribution.The main review included 49 prospective cohorts across 18 studies comprising a total of 139 RRs from 20 countries and territories. At one year since quitting, the percentage of RRR for lung cancer was 81.4% [64.1-98.2]. At five years since quitting, RRR was 57.2% [45.7-67.3]; at 10 years: 36.9% [28.3-47.9]; at 15 years, 26.7% [20.2-34.3]; at 20 years, 19.7% [13.3-26.4]. If eligibility criteria in the US were broadened to screen former smokers up to 20 years since quitting, we estimate an additional 4.2 [3.9-4.5] million former smokers between 55-80 years of age would be eligible for lung cancer screening.At the critical screening threshold of 15 years since quitting, the percentage of excess risk for lung cancer remains high and only marginally declines at time points afterward, excluding millions of former smokers who remain at elevated risk of malignancy. A risk-based screening algorithm for lung cancer screening that de-emphasizes time post-cessation as a key screening determinant would more likely capture these former smokers who remain at elevated risk of malignancy.

    View details for DOI 10.1513/AnnalsATS.201909-659OC

    View details for PubMedID 32603182

  • How do Covid-19 policy options depend on end-of-year holiday contacts in Mexico City Metropolitan Area? A Modeling Study. medRxiv : the preprint server for health sciences Alarid-Escudero, F. n., Gracia, V. n., Luviano, A. n., Peralta, Y. n., Reitsma, M. B., Claypool, A. L., Salomon, J. A., Studdert, D. M., Andrews, J. R., Goldhaber-Fiebert, J. D. 2020

    Abstract

    With more than 20 million residents, Mexico City Metropolitan Area (MCMA) has the largest number of Covid-19 cases in Mexico and is at risk of exceeding its hospital capacity in late December 2020.We used SC-COSMO, a dynamic compartmental Covid-19 model, to evaluate scenarios considering combinations of increased contacts during the holiday season, intensification of social distancing, and school reopening. Model parameters were derived from primary data from MCMA, published literature, and calibrated to time-series of incident confirmed cases, deaths, and hospital occupancy. Outcomes included projected confirmed cases and deaths, hospital demand, and magnitude of hospital capacity exceedance.Following high levels of holiday contacts even with no in-person schooling, we predict that MCMA will have 1·0 million (95% prediction interval 0·5 - 1·7) additional Covid-19 cases between December 7, 2020 and March 7, 2021 and that hospitalizations will peak at 35,000 (14,700 - 67,500) on January 27, 2021, with a >99% chance of exceeding Covid-19-specific capacity (9,667 beds). If holiday contacts can be controlled, MCMA can reopen in-person schools provided social distancing is increased with 0·5 million (0·2 - 1·0) additional cases and hospitalizations peaking at 14,900 (5,600 - 32,000) on January 23, 2021 (77% chance of exceedance).MCMA must substantially increase Covid-19 hospital capacity under all scenarios considered. MCMA's ability to reopen schools in mid-January 2021 depends on sustaining social distancing and that contacts during the end-of-year holiday were well controlled.Society for Medical Decision Making, Gordon and Betty Moore Foundation, and Wadhwani Institute for Artificial Intelligence Foundation.Evidence before this study: As of mid-December 2020, Mexico has the twelfth highest incidence of confirmed cases of Covid-19 worldwide and its epidemic is currently growing. Mexico's case fatality ratio (CFR) - 9·1% - is the second highest in the world. With more than 20 million residents, Mexico City Metropolitan Area (MCMA) has the highest number and incidence rate of Covid-19 confirmed cases in Mexico and a CFR of 8·1%. MCMA is nearing its current hospital capacity even as it faces the prospect of increased social contacts during the 2020 end-of-year holidays. There is limited Mexico-specific evidence available on epidemic, such as parameters governing time-dependent mortality, hospitalization and transmission. Literature searches required supplementation through primary data analysis and model calibration to support the first realistic model-based Covid-19 policy evaluation for Mexico, which makes this analysis relevant and timely.Added value of this study: Study strengths include the use of detailed primary data provided by MCMA; the Bayesian model calibration to enable evaluation of projections and their uncertainty; and consideration of both epidemic and health system outcomes. The model projects that failure to limit social contacts during the end-of-year holidays will substantially accelerate MCMA's epidemic (1·0 million (95% prediction interval 0·5 - 1·7) additional cases by early March 2021). Hospitalization demand could reach 35,000 (14,700 - 67,500), with a >99% chance of exceeding current capacity (9,667 beds). Controlling social contacts during the holidays could enable MCMA to reopen in-person schooling without greatly exacerbating the epidemic provided social distancing in both schools and the community were maintained. Under all scenarios and policies, current hospital capacity appears insufficient, highlighting the need for rapid capacity expansion.Implications of all the available evidence: MCMA officials should prioritize rapid hospital capacity expansion. MCMA's ability to reopen schools in mid-January 2021 depends on sustaining social distancing and that contacts during the end-of-year holiday were well controlled.

    View details for DOI 10.1101/2020.12.21.20248597

    View details for PubMedID 33398301

    View details for PubMedCentralID PMC7781344

  • Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 LANCET Stanaway, J. D., Afshin, A., Gakidou, E., Lim, S. S., Abate, D., Abate, K., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, F., Abdela, J., Abdelalim, A., Abdollahpour, I., Abdulkader, R., Abebe, M., Abebe, Z., Abera, S. F., Abil, O., Abraha, H., Abrham, A., Abu-Raddad, L., Abu-Rmeileh, N. E., Accrombessi, M., Acharya, D., Acharya, P., Adamu, A. A., Adane, A., Adebayo, O. M., Adedoyin, R., Adekanmbi, V., Ademi, Z., Adetokunboh, O., Adib, M. G., Admasie, A., Adsuar, J. C., Afanvi, K., Afarideh, M., Agarwal, G., Aggarwal, A., Aghayan, S., Agrawal, A., Agrawal, S., Ahmadi, A., Ahmadi, M., Ahmadieh, H., Ahmed, M., Aichour, A., Aichour, I., Aichour, M., Akbari, M., Akinyemiju, T., Akseer, N., Al-Aly, Z., Al-Eyadhy, A., Al-Mekhlafi, H. M., Alandab, F., Alam, K., Alam, S., Alam, T., Alashi, A., Alavian, S., Alene, K., Ali, K., Ali, S., Alijanzadeh, M., Alizadeh-Navaei, R., Aljunid, S., Alkerwi, A., Alla, F., Alsharif, U., Altirkawi, K., Alvis-Guzman, N., Amare, A. T., Ammar, W., Anber, N., Anderson, J. A., Andrei, C., Androudi, S., Animut, M., Anjomshoa, M., Ansha, M., Anto, J. M., Antonio, C. T., Anwari, P., Appiah, L., Appiah, S., Arabloo, J., Aremu, O., Amlov, J., Artaman, A., Aryal, K. K., Asayesh, H., Ataro, Z., Ausloos, M., Avokpaho, E. A., Awasthi, A., Quintanilla, B., Ayer, R., Ayuk, T. B., Azzopardi, P. S., Babazadeff, A., Badali, H., Badawi, A., Balakrishnan, K., Bali, A., Ball, K., Bellew, S. H., Banach, M., Banoub, J., Barac, A., Barker-Collo, S., Bamighausen, T., Barrero, L. H., Basu, S., Baune, B. T., Bazargan-Hejazi, S., Bedi, N., Beghi, E., Behzadifar, M., Behzadifar, M., Bejoy, Y., Bekele, B., Bekru, F., Belay, E., Belay, Y., Bell, M. L., Bello, A. K., Bennett, D. A., Bensenor, I. M., Bergeron, G., Berhane, A., Bemabe, E., Bemstein, R. S., Beuran, M., Beyranvand, T., Bhala, N., Bhalla, A., Bhattarai, S., Bhutta, Z. A., Biadgo, B., Bijani, A., Bikbov, B., Bilano, V., Bililign, N., Bin Sayeed, M., Bisanzio, D., Biswas, T., Bjorge, T., Blacker, B. F., Bleyer, A., Borschmann, R., Bou-Orm, I. R., Boufous, S., Bourne, R., Brady, O. J., Brauer, M., Brazinova, A., Breitborde, N. K., Brenner, H., Briko, A., Britton, G., Brugha, T., Buchbindet, R., Burnett, R. T., Busse, R., Butt, Z. A., Cahill, L. E., Cahuana-Hurtado, L., Campos-Nonato, I. R., Cardenas, R., Carreras, G., Carrero, J. J., Carvalho, F., Castaneda-Orjuela, C. 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    Abstract

    How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males.Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2).With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(18)32335-3

    View details for Web of Science ID 000449710900006

    View details for PubMedID 30415748

    View details for PubMedCentralID PMC6252083

  • Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017 LANCET Lozano, R., Fullman, N., Abate, D., Abay, S. M., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, F., Abdela, J., Abdelalim, A., Abdel-Rahman, O., Abdi, A., Abdollahpour, I., Abdulkader, R., Abebe, N., Abebe, Z., Abejie, A., Abera, S. P., Abil, O., Aboyans, V., Abraha, H., Abrham, A., Abu-Raddad, L., Abu-Rmeileh, N., Abyu, G. Y., Accrombessi, M., Acharya, D., Acharya, P., Adamu, A. A., Adebayo, O. M., Adedeji, I., Adedoyin, R., Adekanmbi, V., Adetokunboh, O., Adhena, B., Adhikari, T., Adib, M. G., Adou, A., Adsuar, J. C., Afarideh, M., Afshari, M., Afshin, A., Agarwal, G., Aghayan, S., Agius, D., Agrawal, A., Agrawal, S., Ahmadi, A., Ahmadi, M., Ahmadieh, F., Ahmed, M., Ahmed, S., Akalu, T., Akanda, A. 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  • Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017 LANCET Roth, G. A., Collaborotors, G., Abate, D., Abate, K., Abay, S. M., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, L., Abdela, J., Abdelalim, A., Abdollahpour, I., Abdulkader, R., Abebe, H., Abebe, M., Abebe, Z., Abejie, A., Abera, S. F., Abil, O., Abraha, H., Abrham, A., Abu-Raddad, L., Accrombessi, M., Acharya, D., Adamu, A. A., Adebayo, O., Adedoyin, R., Adekanmbi, V., Adookunboh, O., Adhena, B., Adib, M. G., Admasie, A., Afshin, A., Agarwal, G., Agesa, K. M., Agrawal, A., Agrawal, S., Ahmadi, A., Ahmadi, M., Ahmed, M., Ahmed, S., Aichour, A., Aichour, I., Aichour, M., Akbari, M., Akinyeniti, R., Akseer, N., Al-Aly, Z., Al-Eyadhy, A., Al-Raddadi, R. M., Alandab, F., Alam, K., Alam, T., Alebel, A., Alene, K., Alijanzadeh, M., Alizadeh-Navaei, R., Aljunid, S., Alkerwi, A., Alla, F., Allebeck, P., Alonso, J., Altirkawi, K., Alvis-Guzman, N., Amare, A. T., Aminde, L. N., Amini, E., Ammar, W., Amoako, Y., Anber, N., Andrei, C., Androudi, S., Animut, M., Anjomshoa, M., Ansari, H., Aniha, M., Antonio, C. T., Anwari, P., Aremu, O., Arnlov, J., Arora, A., Arora, M., Artaman, A., Aryal, K. K., Asayesh, H., Asfaw, E., Ataro, Z., Atique, S., Atre, S. R., Ausloos, M., Avokpaho, E. A., Awasthi, A., Quintattilla, B., Ayele, Y., Ayer, R., Azzopardi, P. S., Babazadeh, A., Bacha, U., Badali, H., Badawi, A., Bali, A., Ballesteros, K. E., Banach, M., Banerjee, K., Bannick, M. S., Banoub, J., Barboza, M. A., Barker-Collo, S., Barnighausen, T., Barquera, S., Barrero, L., Bassat, Q., Base, S., Baune, B. T., Baynes, H., Bazargan-Hejazi, S., Beth, N., Beghi, E., Behzadifar, M., Behzadifar, M., Bejot, Y., Bekele, B., Belacliew, A., Belay, E., Belay, Y., Bell, M. L., Bello, A. K., Bennett, D. A., Bensenor, I. M., Berman, A. F., Bernabe, E., Bernstein, R. S., Bertolacci, G. J., Beuran, M., Beyranvand, T., Bhalla, A., Bhattarai, S., Bhaumik, S., Bhutta, Z. A., Biadgo, B., Biehl, M. H., Bijani, A., Bikbov, B., Bilano, V., Bililign, N., Bin Sayeed, M., Bisanzio, D., Biswas, T., Blacker, B. F., Basara, B., Borschmann, R., Bosetti, C., Bozorgmehr, K., Brady, O. J., Brant, L. C., Brayne, C., Brazinova, A., Breitborde, N. K., Brenner, H., Briant, P., Britton, G., Brugha, T., Busse, R., Butt, Z. A., Callender, C. H., Campos-Nonato, I. R., Rincon, J., Cano, J., Car, M., Cardenas, R., Carreras, G., Carrero, J. J., Carter, A., Carvalho, F., Castaneda-Orjuela, C. A., Rivas, J., Castle, C. D., Castro, C., Castro, F., Catala-Lopez, F., Cerin, E., Chaiah, Y., Chang, J., Chanson, F. J., Chaturvedi, P., Chiang, P., Chimed-Ochir, O., Chisumpa, V., Chitheet, A., Chowdhury, R., Christensen, H., Christopher, D. J., Chiang, S., Cicuttini, F. M., Ciobanu, L. G., Cirillo, M., Cohen, A. J., Cooper, L., Cortesi, P., Cortinovis, M., Cousin, E., Cowie, B. C., Criqui, M. H., Cromwell, E. A., Crowe, C., Crump, J. A., Cunningham, M., Daba, A., Dadi, A., Dandona, L., Dandona, R., Dang, A., Dargan, P. I., Daryani, A., Das, S. K., Das Gupta, R., Das Neves, J., Dasa, T., Dash, A., Davis, A. C., Weaver, N., Davitoiu, D., Davletov, K., De La Hoz, F., De Neve, J., Degefa, M., Degenhardt, L., Degfie, T. T., Deiparine, S., Demoz, G., Demtsu, B., Denova-Gutierrez, E., Deribe, K., Dervenis, N., Jarlais, D., Dessie, G., Dey, S., Dhannaratne, S. D., Dicker, D., Dinberu, M., Ding, E. L., Dirac, M., Djalalinia, S., Dokova, K., Ter Doku, D., Donnelly, C. A., Dorsey, E., Doshi, P. P., Douwes-Schultz, D., Doyle, K. E., Driscoll, T. R., Dubey, M., Dubljanin, E., Duken, E., Duncan, B. B., Duraes, A. R., Ebrahimi, H., Ebrahimpour, S., Edessa, D., Edvardsson, D., Eggen, A., El Bcheraoui, C., Zaki, M., El-Khatib, Z., Elkout, H., Eltinsel, C., Endres, M., Endries, A., Er, B., Erskine, H. E., Eshrati, B., Eskandarieh, S., Esmaeili, R., Esteghamati, A., Fakhar, M., Fakhim, H., Faramarzi, M., Fareed, M., Farhadi, F., Faninha, C., Faro, A., Farvid, M. S., Farzadfar, F., Farzaei, M., Feign, V. L., Feigl, A. B., Fentahun, N., Eereshtehnejad, S., Fernandes, E., Fernandes, J. C., Ferrari, A. J., Feyissa, G., Filip, I., Finegold, S., Fischer, F., Eitzmaurice, C., Foigt, N. A., Foreman, K. J., Fornari, C., Frank, T. D., Fukumoto, T., Fuller, J. E., Fullman, N., Furst, T., Furtado, J. M., Futran, N. D., Gallus, S., Garcia-Basteiro, A. L., Garcia-Gordillo, M. A., Gardner, W. M., Gebre, A., Gebrehiwol, T., Gebremedhin, A., Gebremichael, B., Gebremichael, T., Gelano, T., Geleijinse, J. M., Genova-Maleras, R., Geramo, Y., Gething, P. W., Gezae, K., Ghadami, M., Ghadimi, R., Falavarjani, K., Ghasemi-Kasman, M., Ghimire, M., Gibney, K. B., Gill, P., Gill, T. K., Gillum, R. F., Ginawi, I., Giroud, M., Giussani, G., Goenka, S., Goldberg, E. M., Goli, S., Gomez-Dantes, H., Gona, P. N., Gopalani, S., Gorman, T. M., Goto, A., Goulart, A. C., Gnedovskaya, E. V., Grada, A., Grosso, G., Gugnani, H., Guimaraes, A., Gun, N., Gupta, P. C., Gupta, R., Gupta, R., Gupta, T., Gutierrez, R., Gyawali, B., Haagsma, J. A., Hafezi-Nejad, N., Hagos, T. B., Hailegiyorgis, T., Hailu, G., Haj-Mirzaian, A., Haj-Mirzaian, A., Hamadeh, R. R., Hamidi, S., Handal, M. J., Hankey, G. J., Harb, H. L., Harikrishnan, S., Haro, J., Hasan, M., Hassankhani, H., Hassen, H., Havmoeller, R., Hay, R. J., Hay, S. I., He, Y., Hedayatizadeh-Omran, A., Hegazy, M. I., Heibati, B., Heidari, M., Hendrie, D., Henok, A., Henry, N. J., Herteliu, C., Heydarpour, F., Heydarpour, P., Heydarpour, S., Hibstu, D., Hoek, H. W., Hole, M. K., Red, E., Hoogar, P., Hosgood, H., Hosseini, S., Hosseinzadeh, M., Hostiuc, M., Hostiuc, S., Hotez, P. J., Hoy, D. C., Hsiao, T., Hu, G., Huang, J. J., Husseini, A., Hussen, M., Hutfless, S., Idrisov, B., Ilesanmi, O., Iqbal, U., Irvani, S., Irvine, C., Islam, N., Islam, S., Islami, F., Jacobsen, K. H., Jahangiry, L., Jahanmehr, N., Jain, S., Jakovlievic, M., Jalu, M., James, S. L., Javanbakht, M., Jayatilleke, A., Jeemon, P., Jenkins, K. J., Jha, R., Jha, V., Johnson, C. O., Johnson, S. C., Jonas, J. B., Joshi, A., Jozwiak, J., Jungari, S., Jurisson, M., Kabir, Z., Kadel, R., Kahsay, A., Kalani, R., Karami, M., Matin, B., Karch, A., Karema, C., Karimi-Sari, H., Kasaeian, A., Kassa, D. H., Kassa, G., Kassa, T., Kassebaum, N. J., Katikireddi, S., Kaul, A., Kazemi, Z., Karyani, A., Kazi, D., Kefale, A., Keiyoro, P., Kemp, G., Kengne, A., Keren, A., Kesavachandran, C., Khader, Y., Khafaei, B., Khafaie, M., Khajavi, A., Khalid, N., Khalil, I. A., Khan, E., Khan, M., Khan, M., Khang, Y., Khater, M. M., Khoja, A. T., Khosravi, A., Khosravi, M., Khubchandani, J., Kiadaliri, A. A., Kibret, G. D., Kidanemariam, Z., Kiirithio, D. N., Kim, D., Kim, Y., Kim, Y., Kimokoti, R. W., Kinfu, Y., Kisa, A., Kissimova-Skarbek, K., Kivimaki, M., Knudsen, A., Kocarnik, J. M., Kochhar, S., Kokubo, Y., Kolola, T., Kopec, J. A., Koul, P. A., Koyanagi, A., Kravchenko, M. A., Krishan, K., Defo, B., Bicer, B., Kumar, G., Kumar, M., Kumar, P., Kutz, M. J., Kuzin, I., Kyu, H., Lad, D. P., Lad, S. D., Lafranconi, A., Lal, D., Lalloo, R., Lallukka, T., Lam, J. O., Lami, F., Lansingh, V. C., Lansky, S., Larson, H. J., Latifi, A., Lau, K., Lazarus, J. V., Lebedev, G., Lee, P. H., Leigh, J., Leili, M., Leshargie, C., Li, S., Li, Y., Liang, J., Lim, L., Lim, S. S., Limenih, M., Linn, S., Liu, S., Liu, Y., Lodha, R., Lansdale, C., Lopez, A. D., Lorkowski, S., Lotufo, P. A., Lozano, R., Lunevicius, R., Ma, S., Macarayan, E., Mackay, M. T., MacLachlan, J. H., Maddison, E. R., Nadotto, F., Abd El Razek, H., Abd El Razek, M., Maghavani, D. P., Majdan, M., Majdzadeh, R., Majeed, A., Malekzadeh, R., Malta, D., Manda, A., Mandarano-Filho, L., Manguerra, H., Mansournia, M., Mapoma, C., Marami, D., Maravilla, J. C., Marcenes, W., Marczak, L., Marks, A., Marks, G. B., Martinez, G., Martins-Melo, F., Martopullo, I., Marz, W., Marron, M. B., Masci, J. R., Lylassenburg, B., Mathur, M., Mathur, P., Matzopoulos, R., Maulik, P. K., Mazidi, M., McAlinden, C., McGrath, J. J., McKee, M., McMahon, B. J., Mehata, S., Mehndiratta, M., Mehrotra, R., Mehta, K. M., Mehta, V., Mekonnen, T. C., Melese, A., Melku, M., Memiah, P. N., Memish, Z. A., Mendoza, W., Mengistu, D., Mengistu, G., Mensah, G. A., Mereta, S., Meretoja, A., Meretoja, T. J., Meshovic, T., Mezgebe, H., Miazgowski, B., Miazgowski, T., Millear, A. I., Miller, T. R., Katherine, M., Petrie, M., Mini, G. K., Mirabi, P., Mirarefin, M., Mirica, A., Mirrakhimov, E. M., Misganaw, A., Mitiku, H., Moazen, B., Mohammad, K., Mohammad, M., Mohammadifard, N., Mohammed, A., Mohammed, S., Mohan, V., Mokdad, A. H., Molokhia, M., Monasta, L., Moradi, G., Moradi-Lakeh, M., Moradinazar, M., Moraga, P., Morawska, L., Velasquez, I., Morgado-Da-Costa, J., Morrison, S., Moschos, M. M., Mouodi, S., Mousavi, S., Muchie, K., Mueller, U., Mukhopadhyay, S., Muller, K., Mumford, J., Musa, J., Musa, K., Mustafa, G., Muthupandian, S., Nachega, J. B., Nagel, G., Naheed, A., Nahvijou, A., Naik, G., Nair, S., Najafi, F., Naldi, L., Nam, H., Nangia, V., Nansseu, J., Nascirnento, B., Natarajan, G., Nearnati, N., Negoi, I., Negoi, R., Nettpane, S., Newton, C. J., Ngalesoni, F. N., Ngunjiri, J. W., Anh Quynh Nguyen, Nguyen, G., Ha Thu Nguyen, Luong Thanh Nguyen, Long Hoang Nguyen, Minh Nguyen, Trang Huyen Nguyen, Nichols, E., Ningnun, D., Nirayo, Y., Nixon, M. R., Nolutshungu, N., Nomura, S., Norhelin, O. F., Noroozi, M., Norrving, B., Noubiap, J., Nouri, H., Shiadeh, M., Nowroozi, M., Nyasulu, P. S., Odell, C. M., Ofori-Asenso, R., Ogbo, F., Oh, I., Oladimeji, O., Olagunju, A. T., Olivares, P. R., Olsen, H., Olusanya, B., Olusanya, J., Ong, K. L., Ong, S., Oren, E., Orpana, H. M., Ortiz, A., Ortiz, J. R., Otstavnov, S. S., Overland, S., Owolabi, M., Ozdemir, R., Mahesh, P. A., Pacella, R., Pakhale, S., Pakhare, A. P., Pakpour, A. H., Pana, A., Panda-Jonas, S., Pandian, J., Parisi, A., Park, E., Parry, C. H., Parsian, H., Patel, S., Pati, S., Patton, G. C., Paturi, V., Paulson, K. R., Pereira, A., Pereira, D. M., Perico, N., Pesudovs, K., Petzold, M., Phillips, M. R., Piel, F. B., Pigott, D. M., Pillay, J., Pirsaheb, M., Pishgar, F., Polinder, S., Postma, M. J., Pourshams, A., Poustchi, H., Pujar, A., Prakash, S., Prasad, N., Purcell, C. A., Qorbani, M., Quintana, H., Quistberg, D., Rade, K., Radfah, A., Rafay, A., Rafiei, A., Rahim, F., Rahimi, K., Rahimi-Movaghar, A., Rahman, M., Rahman, M., Rahman, M., Rai, R., Rajsic, S., Ram, U., Ranabhat, C., Ranjan, P., Rao, P. C., Rawaf, D., Rawaf, S., Razo-Garcia, C., Reddy, K., Reiner, R. C., Reitsma, M. B., Remuzzi, G., Renzaho, A. N., Resnikoff, S., Rezaei, S., Rezaeian, S., Rezai, M., Riahi, S., Ribeiro, A. P., Rios-Blancas, M., Roba, K., Roberts, N. S., Robinson, S. R., Roever, L., Ronfani, L., Roshandel, G., Rostami, A., Rothenbacher, D., Roy, A., Rubagotti, E., Sachdev, P. S., Saddik, B., Sadeghi, E., Safari, H., Safdarian, M., Safi, S., Safiri, S., Sagar, R., Sahebkar, A., Sahraian, M., Salam, N., Salama, J. S., Salamati, P., Saldanha, R., Saleem, Z., Salimi, Y., Salvi, S., Salz, I., Sambala, E., Samy, A. M., Sanabria, J., Sanchez-Nino, M., Santomauro, D., Santos, I. S., Santos, J., Milicevic, M., Jose, B., Sarker, A., Sarmiento-Suarez, R., Sarrafzadegan, N., Sartorius, B., Sarvi, S., Sathian, B., Satpathy, M., Sawant, A. R., Sawhney, M., Saxena, S., Sayyah, M., Schaeffher, E., Schmidt, M., Schneider, I. C., Schottker, B., Schutte, A., Schwebel, D. C., Schwendicke, F., Scott, J. G., Sekerija, M., Sepanlou, S. G., Servan-Mori, E., Seyedmousavi, S., Shabaninejad, H., Shackelford, K., Shafieesabet, A., Shahbazi, M., Shaheen, A. A., Shaikh, M., Shams-Beyranvand, M., Shamsi, M., Shamsizadeh, M., Sharafi, K., Sharif, M., Sharif-Alhoseini, M., Sharma, R., She, J., Sheikh, A., Shi, P., Shiferaw, M., Shigematsu, M., Shiri, R., Shirkoohi, R., Shiue, I., Shokraneh, F., Shrine, M. G., Si, S., Siabani, S., Siddiqi, T. J., Sigfusdottir, I., Sigurvinsdottir, R., Silberberg, D. H., Silva, D., Silva, J., Da Silva, N., Silveira, D., Singh, J. A., Singh, N., Singh, P., Singh, V., Sinha, D., Sliwa, K., Smith, M., Sobaih, B., Sobhani, S., Solangwi, E., Soneji, S. 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  • Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 LANCET James, S. G., Abate, D., Abate, K., Abay, S. M., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, F., Abdela, J., Abdelalim, A., Abdollahpour, I., Abdulkader, R., Abebe, Z., Abera, S. F., Abil, O., Abraha, H., Abu-Raddad, L., Abu-Rmeileh, N. E., Accrombessi, M., Acharya, D., Acharya, P., Ackerman, I. N., Adamu, A. A., Adebayo, O. M., Adekanmbi, V., Adetokunboh, O. O., Adib, M. G., Adsuar, J. C., Afanvi, K., Afarideh, M., Afshin, A., Agarwal, G., Agesa, K. M., Aggarwal, R., Aghayan, S., Agrawal, S., Ahmadi, A., Ahmadi, M., Ahmadieh, H., Ahmed, M., Aichour, A., Aichour, I., Aichour, M., Akinyemiju, T., Akseer, N., Al-Aly, Z., Al-Eyadhy, A., Al-Mekhlafi, H. M., Al-Raddadi, R. M., Alahdab, F., Alam, K., Alam, T., Alashi, A., Alavian, S., Alene, K., Alijanzadeh, M., Alizadeh-Navaei, R., Aljunid, S., Alkerwi, A., Alla, F., Allebeck, P., Alouani, M. L., Altirkawi, K., Alvis-Guzman, N., Amare, A. T., Aminde, L. N., Ammar, W., Amoako, Y., Anber, N., Andrei, C., Androudi, S., Animut, M., Anjomshoa, M., Ansha, M., Antonio, C. T., Anwari, P., Arabloo, J., Arauz, A., Aremu, O., Ariani, F., Armoon, B., Arnlov, J., Arora, A., Artaman, A., Aryal, K. K., Asayesh, H., Asghar, R., Ataro, Z., Atre, S. R., Ausloos, M., Avila-Burgos, L., Avokpaho, E. A., Awasthi, A., Quintanilla, B., Ayer, R., Azzopardi, P. S., Babazadeh, A., Badali, H., Badawi, A., Bali, A., Ballesteros, K. E., Ballew, S. H., Banach, M., Banoub, J., Banstola, A., Barac, A., Barboza, M. A., Barker-Collo, S., Barnighausen, T., Barrero, L. H., Baune, B. T., Bazargan-Hejazi, S., Bedi, N., Beghi, E., Behzadifar, M., Behzadifar, M., Bejot, Y., Belachew, A., Belay, Y., Bel, M. L., Bello, A. K., Bensenor, I. M., Bernabe, E., Bernstein, R. S., Beuran, M., Beyranvand, T., Bhala, N., Bhattarai, S., Bhaumik, S., Bhutta, Z. A., Biadgo, B., Bijani, A., Bikbov, B., Bilano, V., Bililign, N., Bin Sayeed, M., Bisanzio, D., Blacker, B. F., Blyth, F. M., Bou-Orm, I. R., Boufous, S., Bourne, R., Brady, O. J., Brainin, M., Brant, L. C., Brazinova, A., Breitborde, N. K., Brenner, H., Briant, P., Briggs, A. M., Briko, A., Britton, G., Brugha, T., Buchbinder, R., Busse, R., Butt, Z. A., Cahuana-Hurtado, L., Cano, J., Cardenas, R., Carrero, J. J., Carter, A., Carvalho, F., Castaneda-Orjuela, C. A., Rivas, J., Castro, F., Catala-Lopez, F., Cercy, K. M., Cerin, E., Chaiah, Y., Chang, A. R., Chang, H., Chang, J., Charlson, F. J., Chattopadhyay, A., Chattu, V., Chaturvedi, P., Chiang, P., Chin, K., Chitheer, A., Choi, J. J., Chowdhury, R., Christensen, H., Christopher, D. J., Cicuttini, F. M., Ciobanu, L. G., Cirillo, M., Claro, R. M., Collado-Mateo, D., Cooper, C., Coresh, J., Cortesi, P., Cortinovis, M., Costa, M., Cousin, E., Criqui, M. H., Cromwell, E. A., Cross, M., Crump, J. A., Dadi, A., Dandona, L., Dandona, R., Dargan, P. I., Daryani, A., Das Gupta, R., Das Neves, J., Dasa, T., Davey, G., Davis, A. C., Davitoiu, D., De Courten, B., De La Hoz, F., De Leo, D., De Neve, J., Degefa, M., Degenhardt, L., Deiparine, S., Dellavalle, R. P., Demoz, G., Deribe, K., Dervenis, N., Jarlais, D., Dessie, G., Dey, S., Dharmaratne, S., Dinberu, M., Dirac, M., Djalalinia, S., Doan, L., Dokova, K., Doku, D., Dorsey, E., Doyle, K. E., Driscoll, T., Dubey, M., Dubljanin, E., Duken, E., Duncan, B. B., Duraes, A. R., Ebrahimi, H., Ebrahimpour, S., Echko, M., Edvardsson, D., Effiong, A., Ehrlich, J. R., El Bcheraoui, C., Zaki, M., El-Khatib, Z., Elkout, H., Elvazar, I. F., Enayati, A., Endries, A., Er, B., Erskine, H. 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C., Goulart, B., Grada, A., Grams, M. E., Grosso, G., Gugnani, H., Guo, Y., Gupta, P. C., Gupta, R., Gupta, R., Gupta, T., Gyawali, B., Haagsma, J. A., Hachinski, V., Hafezi-Nejad, N., Bidgoli, H., Hagos, T. B., Hailu, G., Haj-Mirzaian, A., Haj-Mirzaian, A., Hamadeh, R. R., Hamidi, S., Handal, A. J., Hankey, G. J., Hao, Y., Harb, H. L., Harikrishnan, S., Haro, J., Hasan, M., Hassankhani, H., Hassen, H., Havmoeller, R., Hawley, C. N., Hay, R. J., Hay, S. I., Hedayatizadeh-Omran, A., Heibati, B., Hendrie, D., Henok, A., Herteliu, C., Heydarpour, S., Hibstu, D., Huong Thanh Hoang, Hoek, H. W., Hoffman, H. J., Hole, M. K., Rad, E., Hoogar, P., Hosgood, H., Hosseini, S., Hosseinzadeh, M., Hostiuc, M., Hostiuc, S., Hotez, P. J., Hoy, D. G., Hsairi, M., Htet, A., Hu, G., Huang, J. J., Humh, C. K., Iburg, K., Ikeda, C., Ileanu, B., Ilesanmi, O., Iqbal, U., Irvani, S., Irvine, C., Islam, S., Islami, F., Jacobsen, K. 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A., Roy, A., Rubagotti, E., Sachdev, P. S., Sadat, N., Saddik, B., Sadeghi, E., Moghaddam, S., Safari, H., Safari, Y., Safari-Faramani, R., Safdarian, M., Safi, S., Safiri, S., Sagar, R., Sahebkar, A., Sahraian, M., Sajadi, H., Salam, N., Salama, J. S., Salamati, P., Saleem, K., Saleem, Z., Salimi, Y., Salomon, J. A., Salvi, S., Sale, I., Samy, A. M., Sanabria, J., Sang, Y., Santomauro, D., Santos, I. S., Santos, J., Milicevic, M., Jose, B., Sardana, M., Sarker, A., Sarrafzadegan, N., Sartorius, B., Sarvi, S., Sathian, B., Satpathy, M., Sawant, A. R., Sawhney, M., Saxena, S., Saylan, M., Schaeffner, E., Schmidt, M., Schneider, I. C., Schoettker, B., Schwebel, D. C., Schwendicke, F., Scott, J. G., Sekerija, M., Sepanlou, S. G., Servan-Mori, E., Seyedmousavi, S., Shabaninejad, H., Shafieesabet, A., Shahbazi, M., Shaheen, A. 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  • Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016. Lancet (London, England) 2018; 391 (10136): 2236–71

    Abstract

    A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries.GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(18)30994-2

    View details for PubMedID 29893224

  • The Burden of Cardiovascular Diseases Among US States, 1990-2016. JAMA cardiology Roth, G. A., Johnson, C. O., Abate, K. H., Abd-Allah, F. n., Ahmed, M. n., Alam, K. n., Alam, T. n., Alvis-Guzman, N. n., Ansari, H. n., Ärnlöv, J. n., Atey, T. M., Awasthi, A. n., Awoke, T. n., Barac, A. n., Bärnighausen, T. n., Bedi, N. n., Bennett, D. n., Bensenor, I. n., Biadgilign, S. n., Castañeda-Orjuela, C. n., Catalá-López, F. n., Davletov, K. n., Dharmaratne, S. n., Ding, E. L., Dubey, M. n., Faraon, E. J., Farid, T. n., Farvid, M. S., Feigin, V. n., Fernandes, J. n., Frostad, J. n., Gebru, A. n., Geleijnse, J. M., Gona, P. N., Griswold, M. n., Hailu, G. B., Hankey, G. J., Hassen, H. Y., Havmoeller, R. n., Hay, S. n., Heckbert, S. R., Irvine, C. M., James, S. L., Jara, D. n., Kasaeian, A. n., Khan, A. R., Khera, S. n., Khoja, A. T., Khubchandani, J. n., Kim, D. n., Kolte, D. n., Lal, D. n., Larsson, A. n., Linn, S. n., Lotufo, P. A., Magdy Abd El Razek, H. n., Mazidi, M. n., Meier, T. n., Mendoza, W. n., Mensah, G. A., Meretoja, A. n., Mezgebe, H. B., Mirrakhimov, E. n., Mohammed, S. n., Moran, A. E., Nguyen, G. n., Nguyen, M. n., Ong, K. L., Owolabi, M. n., Pletcher, M. n., Pourmalek, F. n., Purcell, C. A., Qorbani, M. n., Rahman, M. n., Rai, R. K., Ram, U. n., Reitsma, M. B., Renzaho, A. M., Rios-Blancas, M. J., Safiri, S. n., Salomon, J. A., Sartorius, B. n., Sepanlou, S. G., Shaikh, M. A., Silva, D. n., Stranges, S. n., Tabarés-Seisdedos, R. n., Tadele Atnafu, N. n., Thakur, J. S., Topor-Madry, R. n., Truelsen, T. n., Tuzcu, E. M., Tyrovolas, S. n., Ukwaja, K. N., Vasankari, T. n., Vlassov, V. n., Vollset, S. E., Wakayo, T. n., Weintraub, R. n., Wolfe, C. n., Workicho, A. n., Xu, G. n., Yadgir, S. n., Yano, Y. n., Yip, P. n., Yonemoto, N. n., Younis, M. n., Yu, C. n., Zaidi, Z. n., Zaki, M. E., Zipkin, B. n., Afshin, A. n., Gakidou, E. n., Lim, S. S., Mokdad, A. H., Naghavi, M. n., Vos, T. n., Murray, C. J. 2018; 3 (5): 375–89

    Abstract

    Cardiovascular disease (CVD) is the leading cause of death in the United States, but regional variation within the United States is large. Comparable and consistent state-level measures of total CVD burden and risk factors have not been produced previously.To quantify and describe levels and trends of lost health due to CVD within the United States from 1990 to 2016 as well as risk factors driving these changes.Using the Global Burden of Disease methodology, cardiovascular disease mortality, nonfatal health outcomes, and associated risk factors were analyzed by age group, sex, and year from 1990 to 2016 for all residents in the United States using standardized approaches for data processing and statistical modeling. Burden of disease was estimated for 10 groupings of CVD, and comparative risk analysis was performed. Data were analyzed from August 2016 to July 2017.Residing in the United States.Cardiovascular disease disability-adjusted life-years (DALYs).Between 1990 and 2016, age-standardized CVD DALYs for all states decreased. Several states had large rises in their relative rank ordering for total CVD DALYs among states, including Arkansas, Oklahoma, Alabama, Kentucky, Missouri, Indiana, Kansas, Alaska, and Iowa. The rate of decline varied widely across states, and CVD burden increased for a small number of states in the most recent years. Cardiovascular disease DALYs remained twice as large among men compared with women. Ischemic heart disease was the leading cause of CVD DALYs in all states, but the second most common varied by state. Trends were driven by 12 groups of risk factors, with the largest attributable CVD burden due to dietary risk exposures followed by high systolic blood pressure, high body mass index, high total cholesterol level, high fasting plasma glucose level, tobacco smoking, and low levels of physical activity. Increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors.Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden. Differences in CVD burden are largely attributable to modifiable risk exposures.

    View details for PubMedID 29641820

    View details for PubMedCentralID PMC6145754

  • Danger ahead: the burden of diseases, injuries, and risk factors in the Eastern Mediterranean Region, 1990-2015. International journal of public health 2018; 63 (Suppl 1): 11–23

    Abstract

    The Eastern Mediterranean Region faces several health challenges at a difficult time with wars, unrest, and economic change.We used the Global Burden of Disease 2015 study to present the burden of diseases, injuries, and risk factors in the Eastern Mediterranean Region from 1990 to 2015.Ischemic heart disease was the leading cause of death in the region in 2015, followed by cerebrovascular disease. Changes in total deaths ranged from a reduction of 25% for diarrheal diseases to an increase of about 42% for diabetes and tracheal, bronchus, and lung cancer. Collective violence and legal intervention increased by 850% during the time period. Diet was the leading risk factor for disability-adjusted life years (DALYs) for men compared to maternal malnutrition for females. Childhood undernutrition was the leading risk factor for DALYs in 1990 and 2005, but the second in 2015 after high blood pressure.Our study shows that the region is facing several health challenges and calls for global efforts to stabilise the region and to address the current and future burden of disease.

    View details for DOI 10.1007/s00038-017-1017-y

    View details for PubMedID 28776238

    View details for PubMedCentralID PMC5973982

  • Burden of obesity in the Eastern Mediterranean Region: findings from the Global Burden of Disease 2015 study. International journal of public health 2018; 63 (Suppl 1): 165–76

    Abstract

    We used the Global Burden of Disease (GBD) 2015 study results to explore the burden of high body mass index (BMI) in the Eastern Mediterranean Region (EMR).We estimated the prevalence of overweight and obesity among children (2-19 years) and adults (≥20 years) in 1980 and 2015. The burden of disease related to high BMI was calculated using the GBD comparative risk assessment approach.The prevalence of obesity increased for adults from 15.1% (95% UI 13.4-16.9) in 1980 to 20.7% (95% UI 18.8-22.8) in 2015. It increased from 4.1% (95% UI 2.9-5.5) to 4.9% (95% UI 3.6-6.4) for the same period among children. In 2015, there were 417,115 deaths and 14,448,548 disability-adjusted life years (DALYs) attributable to high BMI in EMR, which constitute about 10 and 6.3% of total deaths and DALYs, respectively, for all ages.This is the first study to estimate trends in obesity burden for the EMR from 1980 to 2015. We call for EMR countries to invest more resources in prevention and health promotion efforts to reduce this burden.

    View details for DOI 10.1007/s00038-017-1002-5

    View details for PubMedID 28776243

    View details for PubMedCentralID PMC5973977

  • Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories. Lancet (London, England) Foreman, K. J., Marquez, N. n., Dolgert, A. n., Fukutaki, K. n., Fullman, N. n., McGaughey, M. n., Pletcher, M. A., Smith, A. E., Tang, K. n., Yuan, C. W., Brown, J. C., Friedman, J. n., He, J. n., Heuton, K. R., Holmberg, M. n., Patel, D. J., Reidy, P. n., Carter, A. n., Cercy, K. n., Chapin, A. n., Douwes-Schultz, D. n., Frank, T. n., Goettsch, F. n., Liu, P. Y., Nandakumar, V. n., Reitsma, M. B., Reuter, V. n., Sadat, N. n., Sorensen, R. J., Srinivasan, V. n., Updike, R. L., York, H. n., Lopez, A. D., Lozano, R. n., Lim, S. S., Mokdad, A. H., Vollset, S. E., Murray, C. J. 2018; 392 (10159): 2052–90

    Abstract

    Understanding potential trajectories in health and drivers of health is crucial to guiding long-term investments and policy implementation. Past work on forecasting has provided an incomplete landscape of future health scenarios, highlighting a need for a more robust modelling platform from which policy options and potential health trajectories can be assessed. This study provides a novel approach to modelling life expectancy, all-cause mortality and cause of death forecasts -and alternative future scenarios-for 250 causes of death from 2016 to 2040 in 195 countries and territories.We modelled 250 causes and cause groups organised by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical cause structure, using GBD 2016 estimates from 1990-2016, to generate predictions for 2017-40. Our modelling framework used data from the GBD 2016 study to systematically account for the relationships between risk factors and health outcomes for 79 independent drivers of health. We developed a three-component model of cause-specific mortality: a component due to changes in risk factors and select interventions; the underlying mortality rate for each cause that is a function of income per capita, educational attainment, and total fertility rate under 25 years and time; and an autoregressive integrated moving average model for unexplained changes correlated with time. We assessed the performance by fitting models with data from 1990-2006 and using these to forecast for 2007-16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990-2016. We used this model for 195 countries and territories to generate a reference scenario or forecast through 2040 for each measure by location. Additionally, we generated better health and worse health scenarios based on the 85th and 15th percentiles, respectively, of annualised rates of change across location-years for all the GBD risk factors, income per person, educational attainment, select intervention coverage, and total fertility rate under 25 years in the past. We used the model to generate all-cause age-sex specific mortality, life expectancy, and years of life lost (YLLs) for 250 causes. Scenarios for fertility were also generated and used in a cohort component model to generate population scenarios. For each reference forecast, better health, and worse health scenarios, we generated estimates of mortality and YLLs attributable to each risk factor in the future.Globally, most independent drivers of health were forecast to improve by 2040, but 36 were forecast to worsen. As shown by the better health scenarios, greater progress might be possible, yet for some drivers such as high body-mass index (BMI), their toll will rise in the absence of intervention. We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (-2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years [-2·7 to 2·5]) for women. In 2040, Japan, Singapore, Spain, and Switzerland had a forecasted life expectancy exceeding 85 years for both sexes, and 59 countries including China were projected to surpass a life expectancy of 80 years by 2040. At the same time, Central African Republic, Lesotho, Somalia, and Zimbabwe had projected life expectancies below 65 years in 2040, indicating global disparities in survival are likely to persist if current trends hold. Forecasted YLLs showed a rising toll from several non-communicable diseases (NCDs), partly driven by population growth and ageing. Differences between the reference forecast and alternative scenarios were most striking for HIV/AIDS, for which a potential increase of 120·2% (95% UI 67·2-190·3) in YLLs (nearly 118 million) was projected globally from 2016-40 under the worse health scenario. Compared with 2016, NCDs were forecast to account for a greater proportion of YLLs in all GBD regions by 2040 (67·3% of YLLs [95% UI 61·9-72·3] globally); nonetheless, in many lower-income countries, communicable, maternal, neonatal, and nutritional (CMNN) diseases still accounted for a large share of YLLs in 2040 (eg, 53·5% of YLLs [95% UI 48·3-58·5] in Sub-Saharan Africa). There were large gaps for many health risks between the reference forecast and better health scenario for attributable YLLs. In most countries, metabolic risks amenable to health care (eg, high blood pressure and high plasma fasting glucose) and risks best targeted by population-level or intersectoral interventions (eg, tobacco, high BMI, and ambient particulate matter pollution) had some of the largest differences between reference and better health scenarios. The main exception was sub-Saharan Africa, where many risks associated with poverty and lower levels of development (eg, unsafe water and sanitation, household air pollution, and child malnutrition) were projected to still account for substantive disparities between reference and better health scenarios in 2040.With the present study, we provide a robust, flexible forecasting platform from which reference forecasts and alternative health scenarios can be explored in relation to a wide range of independent drivers of health. Our reference forecast points to overall improvements through 2040 in most countries, yet the range found across better and worse health scenarios renders a precarious vision of the future-a world with accelerating progress from technical innovation but with the potential for worsening health outcomes in the absence of deliberate policy action. For some causes of YLLs, large differences between the reference forecast and alternative scenarios reflect the opportunity to accelerate gains if countries move their trajectories toward better health scenarios-or alarming challenges if countries fall behind their reference forecasts. Generally, decision makers should plan for the likely continued shift toward NCDs and target resources toward the modifiable risks that drive substantial premature mortality. If such modifiable risks are prioritised today, there is opportunity to reduce avoidable mortality in the future. However, CMNN causes and related risks will remain the predominant health priority among lower-income countries. Based on our 2040 worse health scenario, there is a real risk of HIV mortality rebounding if countries lose momentum against the HIV epidemic, jeopardising decades of progress against the disease. Continued technical innovation and increased health spending, including development assistance for health targeted to the world's poorest people, are likely to remain vital components to charting a future where all populations can live full, healthy lives.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(18)31694-5

    View details for PubMedID 30340847

    View details for PubMedCentralID PMC6227505

  • HIV-1 second-line failure and drug resistance at high-level and low-level viremia in Western Kenya. AIDS (London, England) Kantor, R. n., DeLong, A. n., Schreier, L. n., Reitsma, M. n., Kemboi, E. n., Orido, M. n., Obonge, S. n., Boinett, R. n., Rono, M. n., Emonyi, W. n., Brooks, K. n., Coetzer, M. n., Buziba, N. n., Hogan, J. n., Diero, L. n. 2018; 32 (17): 2485–96

    Abstract

    Characterize failure and resistance above and below guidelines-recommended 1000 copies/ml virologic threshold, upon second-line failure.Cross-sectional study.Kenyan adults on lopinavir/ritonavir-based second-line were enrolled at AMPATH (Academic Model Providing Access to Healthcare). Charts were reviewed for demographic/clinical characteristics and CD4/viral load were obtained. Participants with detectable viral load had a second visit and pol genotyping was attempted in both visits. Accumulated resistance was defined as mutations in the second, not the first visit. Low-level viremia (LLV) was detectable viral load less than 1000 copies/ml. Failure and resistance associations were evaluated using logistic and Poisson regression, Fisher Exact and t-tests.Of 394 participants (median age 42, 60% women, median 1.9 years on second-line) 48% had detectable viral load; 21% had viral load more than 1000 copies/ml, associated with younger age, tuberculosis treatment, shorter time on second-line, lower CD4count/percentage, longer first-line treatment interruption and pregnancy. In 105 sequences from the first visit (35 with LLV), 79% had resistance (57% dual-class, 7% triple-class; 46% with intermediate-to-high-level resistance to ≥1 future drug option). LLV was associated with more overall and NRTI-associated mutations and with predicted resistance to more next-regimen drugs. In 48 second-visit sequences (after median 55 days; IQR 28-33), 40% accumulated resistance and LLV was associated with more mutation accumulation.High resistance upon second-line failure exists at levels above and below guideline-recommended virologic-failure threshold, impacting future treatment options. Optimization of care should include increased viral load monitoring, resistance testing and third-line ART access, and consideration of lowering the virologic failure threshold, though this demands further investigation.

    View details for DOI 10.1097/QAD.0000000000001964

    View details for PubMedID 30134290

  • Health Effects of Overweight and Obesity in 195 Countries. The New England journal of medicine Afshin, A., Reitsma, M. B., Murray, C. J. 2017; 377 (15): 1496-7

    View details for DOI 10.1056/NEJMc1710026

    View details for PubMedID 29020584

  • Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016 LANCET Naghavi, M., Abajobir, A., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abera, S., Aboyans, V., Adetokunboh, O., Arnlov, J., Afshin, A., Agrawal, A., Kiadaliri, A., Ahmadi, A., Ahmed, M., Aichour, A., Aichour, I., Aichour, M., Aiyar, S., Al-Eyadhy, A., Alahdab, F., Al-Aly, Z., Alam, K., Alam, N., Alam, T., Alene, K., Ali, S., Alizadeh-Navaei, R., Alkaabi, J. M., Alkerwi, A., Alla, F., Allebeck, P., Allen, C., Al-Raddadi, R., Alsharif, U., Altirkawi, K. A., Alvis-Guzman, N., Amare, A. T., Amini, E., Ammar, W., Amoako, Y., Anber, N., Andersen, H. H., Andrei, C., Androudi, S., Ansari, H., Antonio, C. T., Anwari, P., Arora, M., Artaman, A., Aryal, K., Asayesh, H., Asgedom, S. W., Atey, T., Avila-Burgos, L., Avokpaho, E., Awasthi, A., Paulina, B., Quintanilla, A., Bejot, Y., Babalola, T., Bacha, U., Balakrishnan, K., Barac, A., Barboza, M. A., Barker-Collo, S. L., Barquera, S., Barregard, L., Barrero, L. H., Baune, B. T., Bedi, N., Beghi, E., Bekele, B., Bell, M. L., Bennett, J. R., Bensenor, I. M., Berhane, A., Bernabe, E., Betsu, B., Beuran, M., Bhatt, S., Biadgilign, S., Bienhoff, K., Bikbov, B., Bisanzio, D., Bourne, R. A., Breitborde, N. K., Negesa, L., Bulto, B., Bumgarner, B. R., Butt, Z. A., Cardenas, R., Cahuana-Hurtado, L., Cameron, E., Cesar Campuzano, J., Car, J., Jesus Carrero, J., Carter, A., Casey, D. C., Castaneda-Orjuela, C. A., Catala-Lopez, F., Charlson, F. J., Chibueze, C., Chimed-Ochir, O., Chisumpa, V., Chitheer, A. A., Christopher, D., Ciobanu, L. G., Cirillo, M., Cohen, A. J., Colombara, D., Cooper, C., Cowie, B. C., Criqui, M. H., Dandona, L., Dandona, R., Dargan, P. I., das Neves, J., Davitoiu, D. V., Davletov, K., de Courten, B., Degenhardt, L., Deiparine, S., Deribe, K., Deribew, A., Dey, S., Dicker, D., Ding, E. L., Djalalinia, S., Huyen Phuc Do, Doku, D., Douwes-Schultz, D., Driscoll, T. R., Dubey, M., Duncan, B., Echko, M., El-Khatib, Z., Ellingsen, C., Enayati, A., Erskine, H. E., Eskandarieh, S., Esteghamati, A., Ermakov, S. P., Estep, K., E Sa Farinha, C., Faro, A., Farzadfar, F., Feigin, V. L., Fereshtehnejad, S., Fernandes, J. C., Ferrari, A. J., Feyissa, T., Filip, I., Finegold, S., Fischer, F., Fitzmaurice, C., Flaxman, A. D., Foigt, N., Frank, T., Fraser, M., Fullman, N., Furst, T., Furtado, J. M., Gakidou, E., Garcia-Basteiro, A. L., Gebre, T., Gebregergs, G., Gebrehiwot, T., Gebremichael, D., Geleijnse, J. M., Genova-Maleras, R., Gesesew, H., Gething, P. W., Gillum, R. F., Ginawi, I., Giref, A., Giroud, M., Giussani, G., Godwin, W. W., Gold, A. L., Goldberg, E. M., Gona, P. N., Gopalani, S., Gouda, H. N., Goulart, A., Griswold, M., Gupta, P. C., Gupta, R., Gupta, T., Gupta, V., Haagsma, J. A., Hafezi-Nejad, N., Hailu, A., Hailu, G., Hamadeh, R., Hambisa, M., Hamidi, S., Hammami, M., Hancock, J., Handal, A. J., Hankey, G. J., Hao, Y., Harb, H. L., Hareri, H., Hassanvand, M., Havmoeller, R., Hay, S. I., He, F., Hedayati, M. T., Henry, N. J., Beatriz Heredia-Pi, I., Herteliu, C., Hoek, H. W., Horino, M., Horita, N., Hosgood, H., Hostiuc, S., Hotez, P. J., Hoy, D. G., Huynh, C., Iburg, K., Ikeda, C., Ileanu, B., Irenso, A., Irvine, C., Irenso, A., Irvine, C., Jurisson, M., Jacobsen, K. H., Jahanmehr, N., Jakovljevic, M. B., Javanbakht, M., Jayaraman, S. P., Jeemon, P., Jha, V., John, D., Johnson, C. O., Johnson, S., Jonas, J. B., Kabir, Z., Kadel, R., Kahsay, A., Kamal, R., Karch, A., Karimi, S. M., Karimkhani, C., Kasaeian, A., Kassaw, N., Kassebaum, N. J., Katikireddi, S., Kawakami, N., Keiyoro, P., Kemmer, L., Kesavachandran, C., Khader, Y., Khan, E., Khang, Y., Khoja, A., Khosravi, A., Khosravi, M., Khubchandani, J., Kieling, C., Kievlan, D., Kim, D., Kim, Y., Kimokoti, R. W., Kinfu, Y., Kissoon, N., Kivimaki, M., Knudsen, A., Kopec, J. A., Kosen, S., Koul, P. A., Koyanagi, A., Defo, B., Kulikoff, X., Kumar, G., Kumar, P., Kutz, M., Kyu, H. H., Lal, D., Lalloo, R., Lallukka, T., Lambert, N., Lan, Q., Lansingh, V. C., Larsson, A., Lee, P. H., Leigh, J., Leung, J., Levi, M., Li, Y., Kappe, D., Liang, X., Liben, M., Lim, S. S., Liu, A., Liu, P. Y., Liu, Y., Lodha, R., Logroscino, G., Lorkowski, S., Lotufo, P. A., Lozano, R., Lucas, T. D., Ma, S., Macarayan, E., Maddison, E. R., Abd el Razek, M., Majdan, M., Majdzadeh, R., Majeed, A., Malekzadeh, R., Malhotra, R., Malta, D., Manguerra, H., Manyazewal, T., Mapoma, C. C., Marczak, L. B., Markos, D., Martinez-Raga, J., Martins-Melo, F., Martopullo, I., McAlinden, C., McGaughey, M., McGrath, J. J., Mehata, S., Meier, T., Meles, K., Memiah, P., Memish, Z. A., Mengesha, M., Mengistu, D., Menota, B., Mensah, G. A., Meretoja, A., Meretoja, T. J., Millear, A., Miller, T. R., Minnig, S., Mirarefin, M., Mirrakhimov, E. M., Misganaw, A., Mishra, S., Mohammad, K., Mohammadi, A., Mohammed, S., Mokdad, A. H., Mola, G. D., Mollenkopf, S. K., Molokhia, M., Monasta, L., Montanez Hernandez, J. C., Montico, M., Mooney, M. D., Moradi-Lakeh, M., Moraga, P., Morawska, L., Morrison, S. D., Morozoff, C., Mountjoy-Venning, C., Mruts, K., Muller, K., Murthy, G., Musa, K., Nachega, J. B., Naheed, A., Naldi, L., Nangia, V., Nascimento, B., Nasher, J. T., Natarajan, G., Negoi, I., Ngunjiri, J., Cuong Tat Nguyen, Grant Nguyen, Minh Nguyen, Quyen Le Nguyen, Trang Huyen Nguyen, Nichols, E., Ningrum, D., Vuong Minh Nong, Noubiap, J. N., Ogbo, F., Oh, I., Okoro, A., Olagunju, A., Olsen, H. E., Olusanya, B., Olusanya, J., Ong, K., Opio, J., Oren, E., Ortiz, A., Osman, M., Ota, E., Pa, M., Pacella, R. E., Pakhale, S., Pana, A., Panda, B., Panda-Jonas, S., Papachristou, C., Park, E., Patten, S. B., Patton, G. C., Paudel, D., Paulson, K., Pereira, D. M., Perez-Ruiz, F., Perico, N., Pervaiz, A., Petzold, M., Phillips, M., Pigott, D. M., Pinho, C., Plass, D., Pletcher, M. A., Polinder, S., Postma, M. J., Pourmalek, F., Purcell, C., Qorbani, M., Radfar, A., Rafay, A., Rahimi-Movaghar, V., Rahman, M., Rahman, M., Rai, R., Ranabhat, C., Rankin, Z., Rao, P. C., Rath, G., Rawaf, S., Ray, S. E., Rehm, J., Reiner, R. C., Reitsma, M. B., Remuzzi, G., Rezaei, S., Rezai, M., Rokni, M., Ronfani, L., Roshandel, G., Roth, G. A., Rothenbacher, D., Ruhago, G., Saadat, R., Sachdev, P. S., Sadat, N., Safdarian, M., Safi, S., Safiri, S., Sagar, R., Sahathevan, R., Salama, J., Salamati, P., Salomon, J. A., Samy, A. M., Sanabria, J., Dolores Sanchez-Nino, M., Santomauro, D., Santos, I. S., Milicevic, M., Sartorius, B., Satpathy, M., Shahraz, S., Schmidt, M., Schneider, I. C., Schulhofer-Wohl, S., Schutte, A. E., Schwebel, D. C., Schwendicke, F., Sepanlou, S. G., Servan-Mori, E. E., Shackelford, K., Shaikh, M., Shamsipour, M., Shamsizadeh, M., Islam, S., Sharma, J., Sharma, R., She, J., Sheikhbahaei, S., Shey, M., Shi, P., Shields, C., Shields, C., Shigematsu, M., Shiri, R., Shirude, S., Shiue, I., Shoman, H., Shrime, M. G., Sigfusdottir, I., Silpakit, N., Silva, J., Singh, A., Singh, J. A., Skiadaresi, E., Sligar, A., Smith, A., Smith, D. L., Smith, M., Sobaih, B. A., Soneji, S., Sorensen, R. D., Soriano, J. B., Sreeramareddy, C. T., Srinivasan, V., Stanaway, J. D., Stathopoulou, V., Steel, N., Stein, D. J., Steiner, C., Steinke, S., Stokes, M., Strong, M., Strub, B., Subart, M., Sufiyan, M., Sunguya, B. F., Sur, P. J., Swaminathan, S., Sykes, B. L., Tabares-Seisdedos, R., Tadakamadla, S., Takahashi, K., Takala, J. S., Talongwa, R., Tarawneh, M., Tavakkoli, M., Taveira, N., Tegegne, T., Tehrani-Banihashemi, A., Temsah, M., Terkawi, A., Thakur, J. S., Thamsuwan, O., Thankappan, K., Thomas, K. E., Thompson, A. H., Thomson, A. J., Thrift, A. G., Tobe-Gai, R., Topor-Madry, R., Torre, A., Tortajada, M., Towbin, J., Bach Xuan Tran, Troeger, C., Truelsen, T., Tsoi, D., Tuzcu, E., Tyrovolas, S., Ukwaja, K. N., Undurraga, E. A., Updike, R., Uthman, O. A., Uzochukwu, B., van Boven, J. M., Vasankari, T., Venketasubramanian, N., Violante, F. S., Vlassov, V., Vollset, S., Vos, T., Wakayo, T., Wallin, M. T., Wang, Y., Weiderpass, E., Weintraub, R. G., Weiss, D. J., Werdecker, A., Westerman, R., Whetter, B., Whiteford, H. A., Wijeratne, T., Wiysonge, C., Woldeyes, B., Wolfe, C. A., Woodbrook, R., Workicho, A., Xavier, D., Xiao, Q., Xu, G., Yaghoubi, M., Yakob, B., Yano, Y., Yaseri, M., Yimam, H., Yonemoto, N., Yoon, S., Yotebieng, M., Younis, M. Z., Zaidi, Z., Zaki, M., Zegeye, E., Zenebe, Z., Zerfu, T., Zhang, A., Zhang, X., Zipkin, B., Zodpey, S., Lopez, A. D., Murray, C. L., GBD 2016 Causes Death Collaborato 2017; 390 (10100): 1151–1210

    Abstract

    Monitoring levels and trends in premature mortality is crucial to understanding how societies can address prominent sources of early death. The Global Burden of Disease 2016 Study (GBD 2016) provides a comprehensive assessment of cause-specific mortality for 264 causes in 195 locations from 1980 to 2016. This assessment includes evaluation of the expected epidemiological transition with changes in development and where local patterns deviate from these trends.We estimated cause-specific deaths and years of life lost (YLLs) by age, sex, geography, and year. YLLs were calculated from the sum of each death multiplied by the standard life expectancy at each age. We used the GBD cause of death database composed of: vital registration (VR) data corrected for under-registration and garbage coding; national and subnational verbal autopsy (VA) studies corrected for garbage coding; and other sources including surveys and surveillance systems for specific causes such as maternal mortality. To facilitate assessment of quality, we reported on the fraction of deaths assigned to GBD Level 1 or Level 2 causes that cannot be underlying causes of death (major garbage codes) by location and year. Based on completeness, garbage coding, cause list detail, and time periods covered, we provided an overall data quality rating for each location with scores ranging from 0 stars (worst) to 5 stars (best). We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to generate estimates for each location, year, age, and sex. We assessed observed and expected levels and trends of cause-specific deaths in relation to the Socio-demographic Index (SDI), a summary indicator derived from measures of average income per capita, educational attainment, and total fertility, with locations grouped into quintiles by SDI. Relative to GBD 2015, we expanded the GBD cause hierarchy by 18 causes of death for GBD 2016.The quality of available data varied by location. Data quality in 25 countries rated in the highest category (5 stars), while 48, 30, 21, and 44 countries were rated at each of the succeeding data quality levels. Vital registration or verbal autopsy data were not available in 27 countries, resulting in the assignment of a zero value for data quality. Deaths from non-communicable diseases (NCDs) represented 72·3% (95% uncertainty interval [UI] 71·2-73·2) of deaths in 2016 with 19·3% (18·5-20·4) of deaths in that year occurring from communicable, maternal, neonatal, and nutritional (CMNN) diseases and a further 8·43% (8·00-8·67) from injuries. Although age-standardised rates of death from NCDs decreased globally between 2006 and 2016, total numbers of these deaths increased; both numbers and age-standardised rates of death from CMNN causes decreased in the decade 2006-16-age-standardised rates of deaths from injuries decreased but total numbers varied little. In 2016, the three leading global causes of death in children under-5 were lower respiratory infections, neonatal preterm birth complications, and neonatal encephalopathy due to birth asphyxia and trauma, combined resulting in 1·80 million deaths (95% UI 1·59 million to 1·89 million). Between 1990 and 2016, a profound shift toward deaths at older ages occurred with a 178% (95% UI 176-181) increase in deaths in ages 90-94 years and a 210% (208-212) increase in deaths older than age 95 years. The ten leading causes by rates of age-standardised YLL significantly decreased from 2006 to 2016 (median annualised rate of change was a decrease of 2·89%); the median annualised rate of change for all other causes was lower (a decrease of 1·59%) during the same interval. Globally, the five leading causes of total YLLs in 2016 were cardiovascular diseases; diarrhoea, lower respiratory infections, and other common infectious diseases; neoplasms; neonatal disorders; and HIV/AIDS and tuberculosis. At a finer level of disaggregation within cause groupings, the ten leading causes of total YLLs in 2016 were ischaemic heart disease, cerebrovascular disease, lower respiratory infections, diarrhoeal diseases, road injuries, malaria, neonatal preterm birth complications, HIV/AIDS, chronic obstructive pulmonary disease, and neonatal encephalopathy due to birth asphyxia and trauma. Ischaemic heart disease was the leading cause of total YLLs in 113 countries for men and 97 countries for women. Comparisons of observed levels of YLLs by countries, relative to the level of YLLs expected on the basis of SDI alone, highlighted distinct regional patterns including the greater than expected level of YLLs from malaria and from HIV/AIDS across sub-Saharan Africa; diabetes mellitus, especially in Oceania; interpersonal violence, notably within Latin America and the Caribbean; and cardiomyopathy and myocarditis, particularly in eastern and central Europe. The level of YLLs from ischaemic heart disease was less than expected in 117 of 195 locations. Other leading causes of YLLs for which YLLs were notably lower than expected included neonatal preterm birth complications in many locations in both south Asia and southeast Asia, and cerebrovascular disease in western Europe.The past 37 years have featured declining rates of communicable, maternal, neonatal, and nutritional diseases across all quintiles of SDI, with faster than expected gains for many locations relative to their SDI. A global shift towards deaths at older ages suggests success in reducing many causes of early death. YLLs have increased globally for causes such as diabetes mellitus or some neoplasms, and in some locations for causes such as drug use disorders, and conflict and terrorism. Increasing levels of YLLs might reflect outcomes from conditions that required high levels of care but for which effective treatments remain elusive, potentially increasing costs to health systems.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(17)32152-9

    View details for Web of Science ID 000410630000003

    View details for PubMedID 28919116

    View details for PubMedCentralID PMC5605883

  • Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016 LANCET Gakidou, E., Afshin, A., Abajobir, A., Abate, K., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulle, A. M., Abera, S., Aboyans, V., Abu-Raddad, L. J., Abu-Rmeileh, N. E., Abyu, G., Adedeji, I., Adetokunboh, O., Afarideh, M., Agrawal, A., Agrawal, S., Kiadaliri, A., Ahmadieh, H., Ahmed, M., Aichour, A., Aichour, I., Aichour, M., Akinyemi, R., Akseer, N., Alahdab, F., Al-Aly, Z., Alam, K., Alam, N., Alam, T., Alasfoor, D., Alene, K., Ali, K., Alizadeh-Navaei, R., Alkerwi, A., Alla, F., Allebeck, P., Al-Raddadi, R., Alsharif, U., Altirkawi, K. A., Alvis-Guzman, N., Amare, A. T., Amini, E., Ammar, W., Amoako, Y., Ansari, H., Anto, J. M., Antonio, C. T., Anwari, P., Arian, N., Arnlov, J., Artaman, A., Aryal, K., Asayesh, H., Asgedom, S., Atey, T., Avila-Burgos, L., Avokpaho, E., Awasthi, A., Azzopardi, P., Bacha, U., Badawi, A., Balakrishnan, K., Ballew, S. H., Barac, A., Barber, R. M., Barker-Collo, S. L., Barnighausen, T., Barquera, S., Barregard, L., Barrero, L. H., Batis, C., Battle, K. E., Baune, B. T., Beardsley, J., Bedi, N., Beghi, E., Bell, M. L., Bennett, D. A., Bennett, J. R., Bensenor, I. M., Berhane, A., Berhe, D., Bernabe, E., Betsu, B., Beuran, M., Beyene, A., Bhansali, A., Bhutta, Z. A., Bikbov, B., Birungi, C., Biryukov, S., Blosser, C. D., Boneya, D., Bou-Orm, I. R., Brauer, M., Breitborde, N. K., Brenner, H., Brugha, T. S., Bulto, L., Baumgarner, B. R., Butt, Z. A., Cahuana-Hurtado, L., Cardenas, R., Carrero, J., Castaneda-Orjuela, C. A., Catala-Lopez, F., Cercy, K., Chang, H., Charlson, F. J., Chimed-Ochir, O., Chisumpa, V., Chitheer, A. A., Christensen, H., Christopher, D., Cirillo, M., Cohen, A. J., Comfort, H., Cooper, C., Coresh, J., Cornaby, L., Cortesi, P., Criqui, M. H., Crump, J. A., Dandona, L., Dandona, R., das Neves, J., Davey, G., Davitoiu, D. V., Davletov, K., de Courten, B., Degenhardt, L., Deiparine, S., Dellavalle, R. P., Deribe, K., Deshpande, A., Dharmaratne, S. D., Ding, E. L., Djalalinia, S., Huyen Phuc Do, Dokova, K., Doku, D., Dorsey, E., Driscoll, T. R., Dubey, M., Duncan, B., Duncan, S., Ebert, N., Ebrahimi, H., El-Khatib, Z., Enayati, A., Endries, A., Ermakov, S., Erskine, H. E., Eshrati, B., Eskandarieh, S., Esteghamati, A., Estep, K., Faraon, E., E Sa Farinha, C., Faro, A., Farzadfar, F., Fay, K., Feigin, V. L., Fereshtehnejad, S., Fernandes, J. C., Ferrari, A. J., Feyissa, T., Filip, I., Fischer, F., Fitzmaurice, C., Flaxman, A. D., Foigt, N., Foreman, K. J., Frostad, J. J., Fullman, N., Furst, T., Furtado, J. M., Ganji, M., Garcia-Basteiro, A. L., Gebrehiwot, T., Geleijnse, J. M., Geleto, A., Gemechu, B., Gesesew, H., Gething, P. W., Ghajar, A., Gibney, K. B., Gill, P., Gillum, R. F., Giref, A., Gishu, M., Giussani, G., Godwin, W. W., Gona, P. N., Goodridge, A., Gopalani, S., Goryakin, Y., Goulart, A., Graetz, N., Gugnani, H., Guo, J., Gupta, R., Gupta, T., Gupta, V., Gutierrez, R. A., Hachinski, V., Hafezi-Nejad, N., Hailu, G., Hamadeh, R., Hamidi, S., Hammami, M., Handal, A. J., Hankey, G. J., Harb, H. L., Hareri, H., Hassanvand, M., Havmoeller, R., Hawley, C., Hay, S. I., Hedayati, M. T., Hendrie, D., Beatriz Heredia-Pi, I., Hoek, H. W., Horita, N., Hosgood, H., Hostiuc, S., Hoy, D. G., Hsairi, M., Hu, G., Huang, H., Huang, J. J., Iburg, K., Ikeda, C., Inoue, M., Irvine, C., Jackson, M., Jacobsen, K. H., Jahanmehr, N., Jakovljevic, M. B., Jauregui, A., Javanbakht, M., Jeemon, P., Johansson, L. K., Johnson, C. O., Jonas, J. B., Jurisson, M., Kabir, Z., Kadel, R., Kahsay, A., Kamal, R., Karch, A., Karema, C., Kasaeian, A., Kassebaum, N. J., Kastor, A., Katikireddi, S., Kawakami, N., Keiyoro, P., Kelbore, S., Kemmer, L., Kengne, A., Kesavachandran, C., Khader, Y., Khalil, I. A., Khan, E., Khang, Y., Khosravi, A., Khubchandani, J., Kieling, C., Kim, D., Kim, J. Y., Kim, Y., Kimokoti, R. W., Kinfu, Y., Kisa, A., Kissimova-Skarbek, K. A., Kivimaki, M., Knibbs, L. D., Knudsen, A., Kopec, J. A., Kosen, S., Koul, P. A., Koyanagi, A., Kravchenko, M., Krohn, K. J., Kromhout, H., Defo, B., Bicer, B., Kumar, G., Kutz, M., Kyu, H. H., Lal, D., Lalloo, R., Lallukka, T., Lan, Q., Lansingh, V. C., Larsson, A., Lee, A., Lee, P. H., Leigh, J., Leung, J., Levi, M., Li, Y., Li, Y., Liang, X., Liben, M., Linn, S., Liu, P., Lodha, R., Logroscino, G., Looker, K. J., Lopez, A. D., Lorkowski, S., Lotufo, P. A., Lozano, R., Lunevicius, R., Macarayan, E., Abd el Razek, H., Abd el Razek, M., Majdan, M., Majdzadeh, R., Majeed, A., Malekzadeh, R., Malhotra, R., Malta, D., Mamun, A. A., Manguerra, H., Mantovani, L. G., Mapoma, C. C., Martin, R. V., Martinez-Raga, J., Martins-Melo, F., Mathur, M., Matsushita, K., Matzopoulos, R., Mazidi, M., McAlinden, C., McGrath, J. J., Mehata, S., Mehndiratta, M., Meier, T., Melaku, Y., Memiah, P., Memish, Z. A., Mendoza, W., Mengesha, M., Mensah, G. A., Mensink, G. M., Mereta, S., Meretoja, A., Meretoja, T. J., Mezgebe, H., Micha, R., Millear, A., Miller, T. R., Minnig, S., Mirarefin, M., Mirrakhimov, E. M., Misganaw, A., Mishra, S., Mohammad, K., Mohammed, K., Mohammed, S., Ibrahim, N., Mohan, M. V., Mokdad, A. H., Monasta, L., Montanez Hernandez, J., Montico, M., Moradi-Lakeh, M., Moraga, P., Morawska, L., Morrison, S. D., Mountjoy-Venning, C., Mueller, U. O., Mullany, E. C., Muller, K., Murthy, G., Musa, K., Naghavi, M., Naheed, A., Nangia, V., Natarajan, G., Negoi, I., Negoi, R., Cuong Tat Nguyen, Grant Nguyen, Minh Nguyen, Quyen Le Nguyen, Trang Huyen Nguyen, Nichols, E., Ningrum, D., Nomura, M., Vuong Minh Nong, Norheim, O. F., Norrving, B., Noubiap, J. N., Obermeyer, C., Ogbo, F., Oh, H., Oladimeji, O., Olagunju, A., Olagunju, T., Olivares, P. R., Olsen, H. E., Olusanya, B., Olusanya, J., Opio, J., Oren, E., Ortiz, A., Ota, E., Owolabi, M. O., Pa, M., Pacella, R. E., Pana, A., Panda, B., Panda-Jonas, S., Pandian, J. D., Papachristou, C., Park, E., Parry, C. D., Patten, S. B., Patton, G. C., Pereira, D. M., Perico, N., Pesudovs, K., Petzold, M., Phillips, M., Pillay, J., Piradov, M. A., Pishgar, F., Plass, D., Pletcher, M. A., Polinder, S., Popova, S., Poulton, R. G., Pourmalek, F., Prasad, N., Purcell, C., Qorbani, M., Radfar, A., Rafay, A., Rahimi-Movaghar, A., Rahimi-Movaghar, V., Rahman, M., Rahman, M., Rahman, M., Rai, R., Rajsic, S., Ram, U., Rawaf, S., Rehm, C. D., Rehm, J., Reiner, R. C., Reitsma, M. B., Myriam Reynales-Shigematsu, L., Remuzzi, G., Renzaho, A. N., Resnikoff, S., Rezaei, S., Ribeiro, A. L., Rivera, J. A., Roba, K., Rojas-Rueda, D., Roman, Y., Room, R., Roshandel, G., Roth, G. A., Rothenbacher, D., Rubagotti, E., Rushton, L., Sadat, N., Safdarian, M., Safi, S., Safiri, S., Sahathevan, R., Salama, J., Salomon, J. A., Samy, A. M., Sanabria, J., Dolores Sanchez-Nino, M., Sanchez-Pimienta, T. G., Santomauro, D., Santos, I. S., Milicevic, M., Sartorius, B., Satpathy, M., Sawhney, M., Saxena, S., Schaeffner, E., Schmidt, M., Schneider, I. C., Schutte, A. E., Schwebel, D. C., Schwendicke, F., Seedat, S., Sepanlou, S. G., Serdar, B., Servan-Mori, E. E., Shaddick, G., Shaheen, A., Shahraz, S., Shaikh, M., Levy, T., Shamsipour, M., Shamsizadeh, M., Islam, S., Sharma, J., Sharma, R., She, J., Shen, J., Shi, P., Shibuya, K., Shields, C., Shiferaw, M., Shigematsu, M., Shin, M., Shiri, R., Shirkoohi, R., Shishani, K., Shoman, H., Shrime, M. G., Sigfusdottir, I., Santos Silva, D., Silva, J., Alves Silveira, D., Singh, J. A., Singh, V., Sinha, D., Skiadaresi, E., Slepak, E., Smith, D. L., Smith, M., Sobaih, B. A., Sobngwi, E., Soneji, S., Sorensen, R. D., Sposato, L. A., Sreeramareddy, C. T., Srinivasan, V., Steel, N., Stein, D. J., Steiner, C., Steinke, S., Stokes, M., Strub, B., Subart, M., Sufiyan, M., Strub, B., Subart, M., Sufiyan, M., Suliankatchi, R., Sur, P. J., Swaminathan, S., Sykes, B. L., Szoeke, C. I., Tabares-Seisdedos, R., Tadakamadla, S., Takahashi, K., Takala, J. S., Tandon, N., Tanner, M., Tarekegn, Y. L., Tavakkoli, M., Tegegne, T., Tehrani-Banihashemi, A., Terkawi, A., Tesssema, B., Thakur, J. S., Thamsuwan, O., Thankappan, K., Theis, A. M., Thomas, M., Thomson, A. J., Thrift, A. G., Tillmann, T., Tobe-Gai, R., Tobollik, M., Tollanes, M. C., Tonelli, M., Topor-Madry, R., Torre, A., Tortajada, M., Touvier, M., Tran, B., Truelsen, T., Tuem, K., Tuzcu, E., Tyrovolas, S., Ukwaja, K., Uneke, C., Updike, R., Uthman, O. A., van Boven, J. M., van Donkelaar, A., Varughese, S., Vasankari, T., Veerman, L. J., Venkateswaran, V., Venketasubramanian, N., Violante, F. S., Vladimirov, S. K., Vlassov, V., Vollset, S., Vos, T., Wadilo, F., Wakayo, T., Wallin, M. T., Wang, Y., Weichenthal, S., Weiderpass, E., Weintraub, R. G., Weiss, D. J., Werdecker, A., Westerman, R., Whiteford, H. A., Wiysonge, C., Woldeyes, B., Wolfe, C. A., Woodbrook, R., Workicho, A., Hanson, S., Xavier, D., Xu, G., Yadgir, S., Yakob, B., Yan, L. L., Yaseri, M., Yimam, H., Yip, P., Yonemoto, N., Yoon, S., Yotebieng, M., Younis, M. Z., Zaidi, Z., Zaki, M., Zavala-Arciniega, L., Zhang, X., Zimsen, S. M., Zipkin, B., Zodpey, S., Lim, S. S., Murray, C. L., GBD Risk Factors Collaborators 2017; 390 (10100): 1345–1422

    Abstract

    The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context.We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined.Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to 137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9·3% (6·9-11·6) decline in deaths and a 10·8% (8·3-13·1) decrease in DALYs at the global level, while population ageing accounts for 14·9% (12·7-17·5) of deaths and 6·2% (3·9-8·7) of DALYs, and population growth for 12·4% (10·1-14·9) of deaths and 12·4% (10·1-14·9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9-29·7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks.Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade.The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.

    View details for DOI 10.1016/S0140-6736(17)32366-8

    View details for Web of Science ID 000410630000006

    View details for PubMedID 28919119

    View details for PubMedCentralID PMC5614451

  • Health Effects of Overweight and Obesity in 195 Countries over 25 Years NEW ENGLAND JOURNAL OF MEDICINE Afshin, A., Forouzanfar, M. H., Reitsma, M. B., Sur, P., Estep, K., Lee, A., Marczak, L., Mokdad, A. H., Moradi-Lakeh, M., Naghavi, M., Salama, J. S., Vos, T., Abate, K. H., Abbafati, C., Ahmed, M. B., Al-Aly, Z., Alkerwi, A., Al-Raddadi, R., Amare, A. T., Amberbir, A., Amegah, A. K., Amini, E., Amrock, S. M., Anjana, R. M., Arnlov, J., Asayesh, H., Banerjee, A., Barac, A., Baye, E., Bennett, D. A., Beyene, A. S., Biadgilign, S., Biryukov, S., Bjertness, E., Boneya, D. J., Campos-Nonato, I., Carrero, J. J., Cecilio, P., Cercy, K., Ciobanu, L. G., Cornaby, L., Damtew, S. A., Dandona, L., Dandona, R., Dharmaratne, S. D., Duncan, B. B., Eshrati, B., Esteghamati, A., Feigin, V. L., Fernandes, J. C., Furst, T., Gebrehiwot, T. T., Gold, A., Gona, P. N., Goto, A., Habtewold, T. D., Hadush, K. T., Hafezi-Nejad, N., Hay, S. I., Horino, M., Islami, F., Kamal, R., Kasaeian, A., Katikireddi, S. V., Kengne, A. P., Kesavachandran, C. N., Khader, Y. S., Khang, Y., Khubchandani, J., Kim, D., Kim, Y. J., Kinfu, Y., Kosen, S., Ku, T., Defo, B., Kumar, G., Larson, H. J., Leinsalu, M., Liang, X., Lim, S. S., Liu, P., Lopez, A. D., Lozano, R., Majeed, A., Malekzadeh, R., Malta, D. C., Mazidi, M., McAlinden, C., McGarvey, S. T., Mengistu, D. T., Mensah, G. A., Mensink, G. M., Mezgebe, H. B., Mirrakhimov, E. M., Mueller, U. O., Noubiap, J. J., Obermeyer, C. M., Ogbo, F. A., Owolabi, M. O., Patton, G. C., Pourmalek, F., Qorbani, M., Rafay, A., Rai, R. K., Ranabhat, C. L., Reinig, N., Safiri, S., Salomon, J. A., Sanabria, J. R., Santos, I. S., Sartorius, B., Sawhney, M., Schmidhuber, J., Schutte, A. E., Schmidt, M. I., Sepanlou, S. G., Shamsizadeh, M., Sheikhbahaei, S., Shin, M., Shiri, R., Shiue, I., Roba, H. S., Silva, D. S., Silverberg, J. I., Singh, J. A., Stranges, S., Swaminathan, S., Tabares-Seisdedos, R., Tadese, F., Tedla, B. A., Tegegne, B. S., Terkawi, A. S., Thakur, J. S., Tonelli, M., Topor-Madry, R., Tyrovolas, S., Ukwaja, K. N., Uthman, O. A., Vaezghasemi, M., Vasankari, T., Vlassov, V. V., Vollset, S. E., Weiderpass, E., Werdecker, A., Wesana, J., Westerman, R., Yano, Y., Yonemoto, N., Yonga, G., Zaidi, Z., Zenebe, Z. M., Zipkin, B., Murray, C. L., GBD 2015 Obesity Collaborators 2017; 377 (1): 13–27

    Abstract

    Although the rising pandemic of obesity has received major attention in many countries, the effects of this attention on trends and the disease burden of obesity remain uncertain.We analyzed data from 68.5 million persons to assess the trends in the prevalence of overweight and obesity among children and adults between 1980 and 2015. Using the Global Burden of Disease study data and methods, we also quantified the burden of disease related to high body-mass index (BMI), according to age, sex, cause, and BMI in 195 countries between 1990 and 2015.In 2015, a total of 107.7 million children and 603.7 million adults were obese. Since 1980, the prevalence of obesity has doubled in more than 70 countries and has continuously increased in most other countries. Although the prevalence of obesity among children has been lower than that among adults, the rate of increase in childhood obesity in many countries has been greater than the rate of increase in adult obesity. High BMI accounted for 4.0 million deaths globally, nearly 40% of which occurred in persons who were not obese. More than two thirds of deaths related to high BMI were due to cardiovascular disease. The disease burden related to high BMI has increased since 1990; however, the rate of this increase has been attenuated owing to decreases in underlying rates of death from cardiovascular disease.The rapid increase in the prevalence and disease burden of elevated BMI highlights the need for continued focus on surveillance of BMI and identification, implementation, and evaluation of evidence-based interventions to address this problem. (Funded by the Bill and Melinda Gates Foundation.).

    View details for DOI 10.1056/NEJMoa1614362

    View details for Web of Science ID 000404730000005

    View details for PubMedID 28604169

    View details for PubMedCentralID PMC5477817

  • Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015: a novel analysis from the Global Burden of Disease Study 2015. Lancet (London, England) 2017

    Abstract

    National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time.Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0-42·8) in 1990 to 53·7 (52·2-55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015.This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(17)30818-8

    View details for PubMedID 28528753

    View details for PubMedCentralID PMC5528124

  • Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015: a systematic analysis from the Global Burden of Disease Study 2015 LANCET Reitsma, M. B., Fullman, N., Ng, M., Salama, J. S., Abajobir, A., Abate, K., Abbafati, C., Abera, S., Abraham, B., Abyu, G., Adebiyi, A., Al-Aly, Z., Aleman, A. V., Ali, R., Al Alkerwi, A., Allebeck, P., Al-Raddadi, R., Amare, A. T., Amberbir, A., Ammar, W., Amrock, S., Antonio, C. T., Asayesh, H., Atnafu, N., Azzopardi, P., Banerjee, A., Barac, A., Barrientos-Gutierrez, T., Basto-Abreu, A., Bazargan-Hejazi, S., Bedi, N., Bell, B., Bello, A. K., Bensenor, I. M., Beyene, A., Bhala, N., Biryukov, S., Bolt, K., Brenner, H., Butt, Z., Cavalleri, F., Cercy, K., Chen, H., Christopher, D., Ciobanu, L. G., Colistro, V., Colomar, M., Cornaby, L., Dai, X., Damtew, S., Dandona, L., Dandona, R., Dansereau, E., Davletov, K., Dayama, A., Degfie, T., Deribew, A., Dharmaratne, S. D., Dimtsu, B., Doyle, K. E., Endries, A., Ermakov, S., Estep, K., Faraon, E., Farzadfar, F., Feigin, V. L., Feigl, A. B., Fischer, F., Friedman, J., Ghiwot, T., Gall, S. L., Gao, W., Gillum, R. F., Gold, A. L., Gopalani, S., Gotay, C. C., Gupta, R., Gupta, R., Gupta, V., Hamadeh, R., Hankey, G., Harb, H. L., Hay, S. I., Horino, M., Horita, N., Hosgood, H., Husseini, A., Ileanu, B., Islami, F., Jiang, G., Jiang, Y., Jonas, J. B., Kabir, Z., Kamal, R., Kasaeian, A., Kesavachandran, C., Khader, Y. S., Khalil, I., Khang, Y., Khera, S., Khubchandani, J., Kim, D., Kim, Y., Kimokoti, R. W., Kinfu, Y., Knibbs, L. D., Kokubo, Y., Kolte, D., Kopec, J., Kosen, S., Kotsakis, G. A., Koul, P. A., Koyanagi, A., Krohn, K. J., Krueger, H., Defo, B., Bicer, B., Kulkarni, C., Kumar, G., Leasher, J. L., Lee, A., Leinsalu, M., Li, T., Linn, S., Liu, P., Liu, S., Lo, L., Lopez, A. D., Ma, S., Abd El Razek, H., Majeed, A., Malekzadeh, R., Malta, D., Manamo, W., Martinez-Raga, J., Mekonnen, A., Mendoza, W., Miller, T. R., Mohammad, K., Morawska, L., Musa, K., Nagel, G., Neupane, S., Quyen Nguyen, Nguyen, G., Oh, I., Oyekale, A., Mahesh, P. A., Pana, A., Park, E., Patil, S. T., Patton, G. C., Pedro, J., Qorbani, M., Rafay, A., Rahman, M., Rai, R., Ram, U., Ranabhat, C., Refaat, A. H., Reinig, N., Roba, H., Rodriguez, A., Roman, Y., Roth, G., Roy, A., Sagar, R., Salomon, J., Sanabria, J., Santos, I., Sartorius, B., Satpathy, M., Sawhney, M., Sawyer, S., Saylan, M., Schaub, M. P., Schluger, N., Schutte, A., Sepanlou, S. G., Serdar, B., Shaikh, M., She, J., Shin, M., Shiri, R., Shishani, K., Shiue, I., Sigfusdottir, I., Silverberg, J. I., Singh, J., Singh, V., Slepak, E., Soneji, S., Soriano, J. B., Soshnikov, S., Sreeramareddy, C. T., Stein, D. J., Stranges, S., Subart, M. L., Swaminathan, S., Szoeke, C. I., Tefera, W., Topor-Madry, R., Tran, B., Tsilimparis, N., Tymeson, H., Ukwaja, K., Updike, R., Uthman, O. A., Violante, F., Vladimirov, S. K., Vlassov, V., Vollset, S., Vos, T., Weiderpass, E., Wen, C., Werdecker, A., Wilson, S., Wubshet, M., Xiao, L., Yakob, B., Yano, Y., Ye, P., Yonemoto, N., Yoon, S., Younis, M. Z., Yu, C., Zaidi, Z., Zaki, M., Zhang, A., Zipkin, B., Murray, C. L., Forouzanfar, M. H., Gakidou, E., GBD 2015 Tobacco Collaborators 2017; 389 (10082): 1885–1906

    Abstract

    The scale-up of tobacco control, especially after the adoption of the Framework Convention for Tobacco Control, is a major public health success story. Nonetheless, smoking remains a leading risk for early death and disability worldwide, and therefore continues to require sustained political commitment. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) offers a robust platform through which global, regional, and national progress toward achieving smoking-related targets can be assessed.We synthesised 2818 data sources with spatiotemporal Gaussian process regression and produced estimates of daily smoking prevalence by sex, age group, and year for 195 countries and territories from 1990 to 2015. We analysed 38 risk-outcome pairs to generate estimates of smoking-attributable mortality and disease burden, as measured by disability-adjusted life-years (DALYs). We then performed a cohort analysis of smoking prevalence by birth-year cohort to better understand temporal age patterns in smoking. We also did a decomposition analysis, in which we parsed out changes in all-cause smoking-attributable DALYs due to changes in population growth, population ageing, smoking prevalence, and risk-deleted DALY rates. Finally, we explored results by level of development using the Socio-demographic Index (SDI).Worldwide, the age-standardised prevalence of daily smoking was 25·0% (95% uncertainty interval [UI] 24·2-25·7) for men and 5·4% (5·1-5·7) for women, representing 28·4% (25·8-31·1) and 34·4% (29·4-38·6) reductions, respectively, since 1990. A greater percentage of countries and territories achieved significant annualised rates of decline in smoking prevalence from 1990 to 2005 than in between 2005 and 2015; however, only four countries had significant annualised increases in smoking prevalence between 2005 and 2015 (Congo [Brazzaville] and Azerbaijan for men and Kuwait and Timor-Leste for women). In 2015, 11·5% of global deaths (6·4 million [95% UI 5·7-7·0 million]) were attributable to smoking worldwide, of which 52·2% took place in four countries (China, India, the USA, and Russia). Smoking was ranked among the five leading risk factors by DALYs in 109 countries and territories in 2015, rising from 88 geographies in 1990. In terms of birth cohorts, male smoking prevalence followed similar age patterns across levels of SDI, whereas much more heterogeneity was found in age patterns for female smokers by level of development. While smoking prevalence and risk-deleted DALY rates mostly decreased by sex and SDI quintile, population growth, population ageing, or a combination of both, drove rises in overall smoking-attributable DALYs in low-SDI to middle-SDI geographies between 2005 and 2015.The pace of progress in reducing smoking prevalence has been heterogeneous across geographies, development status, and sex, and as highlighted by more recent trends, maintaining past rates of decline should not be taken for granted, especially in women and in low-SDI to middle-SDI countries. Beyond the effect of the tobacco industry and societal mores, a crucial challenge facing tobacco control initiatives is that demographic forces are poised to heighten smoking's global toll, unless progress in preventing initiation and promoting cessation can be substantially accelerated. Greater success in tobacco control is possible but requires effective, comprehensive, and adequately implemented and enforced policies, which might in turn require global and national levels of political commitment beyond what has been achieved during the past 25 years.Bill & Melinda Gates Foundation and Bloomberg Philanthropies.

    View details for DOI 10.1016/S0140-6736(17)30819-X

    View details for Web of Science ID 000400973500025

    View details for PubMedID 28390697

    View details for PubMedCentralID PMC5439023

  • Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016. Lancet (London, England) 2017; 390 (10100): 1423–59

    Abstract

    The UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030.We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment.Globally, the median health-related SDG index was 56·7 (IQR 31·9-66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6-88·9), Iceland (86·0, 84·1-87·6), and Sweden (85·6, 81·8-87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6-11·9), the Central African Republic (11·0, 8·8-13·8), and Somalia (11·3, 9·5-13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past.GBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(17)32336-X

    View details for PubMedID 28916366

    View details for PubMedCentralID PMC5603800

  • Identifying gaps in the continuum of care for hypertension and diabetes in two Indian communities. BMC health services research Gabert, R. n., Ng, M. n., Sogarwal, R. n., Bryant, M. n., Deepu, R. V., McNellan, C. R., Mehra, S. n., Phillips, B. n., Reitsma, M. n., Thomson, B. n., Wilson, S. n., Wollum, A. n., Gakidou, E. n., Duber, H. C. 2017; 17 (1): 846

    Abstract

    Non-communicable diseases (NCDs) represent the largest, and fastest growing, burden of disease in India. This study aimed to quantify levels of diagnosis, treatment, and control among hypertensive and diabetic patients, and to describe demand- and supply-side barriers to hypertension and diabetes diagnosis and care in two Indian districts, Shimla and Udaipur.We conducted household and health facility surveys, as well as qualitative focus group discussions and interviews. The household survey randomly sampled individuals aged 15 and above in rural and urban areas in both districts. The survey included questions on NCD knowledge, history, and risk factors. Blood pressure, weight, height, and blood glucose measurements were obtained. The health facility survey was administered in 48 health care facilities, focusing on NCD diagnosis and treatment capacity, including staffing, equipment, and pharmaceuticals. Qualitative data was collected through semi-structured key informant interviews with health professionals and public health officials, as well as focus groups with patients and community members.Among 7181 individuals, 32% either reported a history of hypertension or were found to have a systolic blood pressure ≥ 140 mmHg and/or diastolic ≥90 mmHg. Only 26% of those found to have elevated blood pressure reported a prior diagnosis, and just 42% of individuals with a prior diagnosis of hypertension were found to be normotensive. A history of diabetes or an elevated blood sugar (Random blood glucose (RBG) ≥200 mg/dl or fasting blood glucose (FBG) ≥126 mg/dl) was noted in 7% of the population. Among those with an elevated RBG/FBG, 59% had previously received a diagnosis of diabetes. Only 60% of diabetics on treatment were measured with a RBG <200 mg/dl. Lower-level health facilities were noted to have limited capacity to measure blood glucose as well as significant gaps in the availability of first-line pharmaceuticals for both hypertension and diabetes.We found high rates of uncontrolled diabetes and undiagnosed and uncontrolled hypertension. Lower level health facilities were constrained by capacity to test, monitor and treat diabetes and hypertension. Interventions aimed at improving patient outcomes will need to focus on the expanding access to quality care in order to accommodate the growing demand for NCD services.

    View details for DOI 10.1186/s12913-017-2796-9

    View details for PubMedID 29282052

    View details for PubMedCentralID PMC5746011

  • The global burden of tuberculosis: results from the Global Burden of Disease Study 2015. The Lancet. Infectious diseases 2017

    Abstract

    An understanding of the trends in tuberculosis incidence, prevalence, and mortality is crucial to tracking of the success of tuberculosis control programmes and identification of remaining challenges. We assessed trends in the fatal and non-fatal burden of tuberculosis over the past 25 years for 195 countries and territories.We analysed 10 691 site-years of vital registration data, 768 site-years of verbal autopsy data, and 361 site-years of mortality surveillance data using the Cause of Death Ensemble model to estimate tuberculosis mortality rates. We analysed all available age-specific and sex-specific data sources, including annual case notifications, prevalence surveys, and estimated cause-specific mortality, to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how observed tuberculosis incidence, prevalence, and mortality differed from expected trends as predicted by the Socio-demographic Index (SDI), a composite indicator based on income per capita, average years of schooling, and total fertility rate. We also estimated tuberculosis mortality and disability-adjusted life-years attributable to the independent effects of risk factors including smoking, alcohol use, and diabetes.Globally, in 2015, the number of tuberculosis incident cases (including new and relapse cases) was 10·2 million (95% uncertainty interval 9·2 million to 11·5 million), the number of prevalent cases was 10·1 million (9·2 million to 11·1 million), and the number of deaths was 1·3 million (1·1 million to 1·6 million). Among individuals who were HIV negative, the number of incident cases was 8·8 million (8·0 million to 9·9 million), the number of prevalent cases was 8·9 million (8·1 million to 9·7 million), and the number of deaths was 1·1 million (0·9 million to 1·4 million). Annualised rates of change from 2005 to 2015 showed a faster decline in mortality (-4·1% [-5·0 to -3·4]) than in incidence (-1·6% [-1·9 to -1·2]) and prevalence (-0·7% [-1·0 to -0·5]) among HIV-negative individuals. The SDI was inversely associated with HIV-negative mortality rates but did not show a clear gradient for incidence and prevalence. Most of Asia, eastern Europe, and sub-Saharan Africa had higher rates of HIV-negative tuberculosis burden than expected given their SDI. Alcohol use accounted for 11·4% (9·3-13·0) of global tuberculosis deaths among HIV-negative individuals in 2015, diabetes accounted for 10·6% (6·8-14·8), and smoking accounted for 7·8% (3·8-12·0).Despite a concerted global effort to reduce the burden of tuberculosis, it still causes a large disease burden globally. Strengthening of health systems for early detection of tuberculosis and improvement of the quality of tuberculosis care, including prompt and accurate diagnosis, early initiation of treatment, and regular follow-up, are priorities. Countries with higher than expected tuberculosis rates for their level of sociodemographic development should investigate the reasons for lagging behind and take remedial action. Efforts to prevent smoking, alcohol use, and diabetes could also substantially reduce the burden of tuberculosis.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S1473-3099(17)30703-X

    View details for PubMedID 29223583

  • Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet (London, England) 2017; 390 (10100): 1260–1344

    Abstract

    Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI).We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate.The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally.At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(17)32130-X

    View details for PubMedID 28919118

    View details for PubMedCentralID PMC5605707

  • Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet (London, England) 2017; 390 (10100): 1211–59

    Abstract

    As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.We estimated prevalence and incidence for 328 diseases and injuries and 2982 sequelae, their non-fatal consequences. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between incidence, prevalence, remission, and cause of death rates for each condition. For some causes, we used alternative modelling strategies if incidence or prevalence needed to be derived from other data. YLDs were estimated as the product of prevalence and a disability weight for all mutually exclusive sequelae, corrected for comorbidity and aggregated to cause level. We updated the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. GBD 2016 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).Globally, low back pain, migraine, age-related and other hearing loss, iron-deficiency anaemia, and major depressive disorder were the five leading causes of YLDs in 2016, contributing 57·6 million (95% uncertainty interval [UI] 40·8-75·9 million [7·2%, 6·0-8·3]), 45·1 million (29·0-62·8 million [5·6%, 4·0-7·2]), 36·3 million (25·3-50·9 million [4·5%, 3·8-5·3]), 34·7 million (23·0-49·6 million [4·3%, 3·5-5·2]), and 34·1 million (23·5-46·0 million [4·2%, 3·2-5·3]) of total YLDs, respectively. Age-standardised rates of YLDs for all causes combined decreased between 1990 and 2016 by 2·7% (95% UI 2·3-3·1). Despite mostly stagnant age-standardised rates, the absolute number of YLDs from non-communicable diseases has been growing rapidly across all SDI quintiles, partly because of population growth, but also the ageing of populations. The largest absolute increases in total numbers of YLDs globally were between the ages of 40 and 69 years. Age-standardised YLD rates for all conditions combined were 10·4% (95% UI 9·0-11·8) higher in women than in men. Iron-deficiency anaemia, migraine, Alzheimer's disease and other dementias, major depressive disorder, anxiety, and all musculoskeletal disorders apart from gout were the main conditions contributing to higher YLD rates in women. Men had higher age-standardised rates of substance use disorders, diabetes, cardiovascular diseases, cancers, and all injuries apart from sexual violence. Globally, we noted much less geographical variation in disability than has been documented for premature mortality. In 2016, there was a less than two times difference in age-standardised YLD rates for all causes between the location with the lowest rate (China, 9201 YLDs per 100 000, 95% UI 6862-11943) and highest rate (Yemen, 14 774 YLDs per 100 000, 11 018-19 228).The decrease in death rates since 1990 for most causes has not been matched by a similar decline in age-standardised YLD rates. For many large causes, YLD rates have either been stagnant or have increased for some causes, such as diabetes. As populations are ageing, and the prevalence of disabling disease generally increases steeply with age, health systems will face increasing demand for services that are generally costlier than the interventions that have led to declines in mortality in childhood or for the major causes of mortality in adults. Up-to-date information about the trends of disease and how this varies between countries is essential to plan for an adequate health-system response.Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.

    View details for DOI 10.1016/S0140-6736(17)32154-2

    View details for PubMedID 28919117

    View details for PubMedCentralID PMC5605509

  • Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015 LANCET Vos, T., Allen, C., Arora, M., Barber, R. M., Bhutta, Z. A., Brown, A., Carter, A., Casey, D. C., Charlson, F. J., Chen, A. Z., Coggeshall, M., Cornaby, L., Dandona, L., Dicker, D. J., Dilegge, T., Erskine, H. E., Ferrari, A. J., Fitzmaurice, C., Fleming, T., Forouzanfar, M. H., Fullman, N., Gething, P. W., Goldberg, E. M., Graetz, N., Haagsma, J. A., Johnson, C. O., Kassebaum, N. J., Kawashima, T., Kemmer, L., Khalil, I. A., Kinfu, Y., Kyu, H. H., Leung, J., Liang, X., Lim, S. S., Lopez, A. D., Lozano, R., Marczak, L., Mensah, G. A., Mokdad, A. H., Naghavi, M., Nguyen, G., Nsoesie, E., Olsen, H., Pigott, D. M., Pinho, C., Rankin, Z., Reinig, N., Salomon, J. A., Sandar, L., Smith, A., Stanaway, J., Steiner, C., Teeple, S., Thomas, B. A., Troeger, C., Wagner, J. A., Wang, H., Wanga, V., Whiteford, H. A., Zoeckler, L., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abraham, B., Abubakar, I., Abu-Raddad, L. J., Abu-Rmeileh, N. M., Ackerman, I. N., Adebiyi, A. O., Ademi, Z., Adou, A. K., Afanvi, K. A., Agardh, E. E., Agarwal, A., Kiadaliri, A. A., Ahmadieh, H., Ajala, O. N., Akinyemi, R. O., Akseer, N., Al-Aly, Z., Alam, K., Alam, N. K., Aldhahri, S. F., Alegretti, M. A., Alemu, Z. A., Alexander, L. T., Alhabib, S., Ali, R., Alkerwi, A., Alla, F., Allebeck, P., Al-Raddadi, R., Alsharif, U., Altirkawi, K. A., Alvis-Guzman, N., Amare, A. T., Amberbir, A., Amini, H., Ammar, W., Amrock, S. M., Andersen, H. H., Anderson, G. M., Anderson, B., Antonio, C. A., Aregay, A. F., Arnlov, J., Al Artaman, Asayesh, H., Assadi, R., Atique, S., Avokpaho, E. F., Awasthi, A., Quintanilla, B. P., Azzopardi, P., Bacha, U., Badawi, A., Balakrishnan, K., Banerjee, A., Barac, A., Barker-Collo, S. L., Barnighausen, T., Barregard, L., Barrero, L. H., Basu, A., Bazargan-Hejazi, S., Bell, B., Bell, M. L., Bennett, D. A., Bensenor, I. M., Benzian, H., Berhane, A., Bernabe, E., Betsu, B. D., Beyene, A. S., Bhala, N., Bhatt, S., Biadgilign, S., Bienhofff, K., Bikbov, B., Biryukov, S., Bisanzio, D., Bjertness, E., Blore, J., Borschmann, R., Boufous, S., Brainin, M., Brazinova, A., Breitborde, N. J., Brown, J., Buchbinder, R., Buckle, G. C., Butt, Z. A., Calabria, B., Ricardo Campos-Nonato, I., Cesar Campuzano, J., Carabin, H., Cardenas, R., Carpenter, D. O., Carrero, J. J., Castaneda-Orjuela, C. A., Castillo Rivas, J., Catala-Lopez, F., Chang, J., Chiang, P. P., Chibueze, C. E., Chisumpa, V. H., Choi, J. J., Chowdhury, R., Christensen, H., Christopher, D. J., Ciobanu, L. G., Cirillo, M., Coates, M. M., Colquhoun, S. M., Cooper, C., Cortinovis, M., Crump, J. A., Damtew, S. A., Dandona, R., Daoud, F., Dargan, P. I., das Neves, J., Davey, G., Davis, A. 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    Abstract

    Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015.We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores.We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4-19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30-2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35-2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20-30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo.Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000385285000008

    View details for PubMedCentralID PMC5055577

  • Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015 LANCET Wang, H., Naghavi, M., Allen, C., Barber, R. M., Bhutta, Z. A., Carter, A., Casey, D. C., Charlson, F. J., Chen, A. Z., Coates, M. M., Coggeshall, M., Dandona, L., Dicker, D. J., Erskine, H. E., Ferrari, A. J., Fitzmaurice, C., Foreman, K., Forouzanfar, M. H., Fraser, M. S., Pullman, N., Gething, P. W., Goldberg, E. M., Graetz, N., Haagsma, J. A., Hay, S. I., Huynh, C., Johnson, C., Kassebaum, N. J., Kinfu, Y., Kulikoff, X. R., Kutz, M., Kyu, H. H., Larson, H. J., Leung, J., Liang, X., Lim, S. S., Lind, M., Lozano, R., Marquez, N., Mensah, G. A., Mikesell, J., Mokdad, A. H., Mooney, M. D., Nguyen, G., Nsoesie, E., Pigott, D. M., Pinho, C., Roth, G. A., Salomon, J. A., Sandar, L., Silpakit, N., Sligar, A., Sorensen, R. J., Stanaway, J., Steiner, C., Teeple, S., Thomas, B. 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    Abstract

    Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.Bill & Melinda Gates Foundation.

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  • Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015 LANCET Lim, S. S., Allen, K., Bhutta, Z. A., Dandona, L., Forouzanfar, M. H., Fullman, N., Gething, P. W., Goldberg, E. M., Hay, S. I., Holmberg, M., Kinfu, Y., Kutz, M. J., Larson, H. J., Liang, X., Lopez, A. D., Lozano, R., McNellan, C. R., Mokdad, A. H., Mooney, M. D., Naghavi, M., Olsen, H. E., Pigott, D. M., Salomon, J. A., Vos, T., Wang, H., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulle, A. M., Abraham, B., Abubakar, I., Abu-Raddad, L. J., Abu-Rmeileh, N. M., Abyu, G. Y., Achoki, T., Adebiyi, A. O., Adedeji, I. A., Afanvi, K. A., Afshin, A., Agarwal, A., Agrawal, A., Kiadaliri, A. A., Ahmadieh, H., Ahmed, K. Y., Akanda, A. S., Akinyemi, R. O., Akinyemiju, T. F., Akseer, N., Al-Aly, Z., Alam, K., Alam, U., Alasfoor, D., Albuhairan, F. S., Aldhahri, S. F., Dge, R. W., Alemu, Z. 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R., Mills, E. J., Mirarefin, M., Misganaw, A., Mitchell, P. B., Mock, C. N., Mohammadi, A., Mohammed, S., Monasta, L., Monis, J. d., Hernandez, J. C., Montico, M., Moradi-Lakeh, M., Morawska, L., Mori, R., Mueller, U. O., Murdoch, M. E., Murimira, B., Murray, J., Murthy, G. V., Murthy, S., Musa, K. I., Nachega, J. B., Nagel, G., Naidoo, K. S., Naldi, L., Nangia, V., Neal, B., Nejjari, C., Newton, C. R., Newton, J. N., Ngalesoni, F. N., Nguhiu, P., Nguyen, G., Quyen Le Nguyen, Q. L., Nisar, M. I., Pete, P. M., Nolte, S., Nomura, M., Norheim, O. F., Norrving, B., Obermeyer, C. M., Ogbo, F. A., Oh, I., Oladimeji, O., Olivares, P. R., Olusanya, B. O., Olusanya, J. O., Opio, J. N., Oren, E., Ortiz, A., Osborne, R. H., Ota, E., Owolabi, M. O., Mahesh, P. A., Park, E., Park, H., Parry, C. D., Parsaeian, M., Patel, T., Patel, V., Caicedo, A. J., Patil, S. T., Patten, S. B., Patton, G. C., Paudel, D., Pedro, J. M., Pereira, D. M., Perico, N., Pesudovs, K., Petzold, M., Phillips, M. R., Piel, F. B., Pillay, J. D., Pinho, C., Pishgar, F., Polinder, S., Poulton, R. G., Pourmalek, F., Qorbani, M., Rabiee, R. H., Radfar, A., Rahimi-Movaghar, V., Rahman, M., Rahman, M. H., Rahman, S. u., Rai, R. K., Rajsic, S., Raju, M., Ram, U., Rana, S. M., Ranabhat, C. L., Ranganathan, K., Rao, P. C., Refaat, A. H., Reitsma, M. B., Remuzzi, G., Resnikoff, S., Ribeiro, A. L., Blancas, M. J., Rolm, H. S., Roberts, B., Rodriguez, M., Rojas-Rueda, D., Ronfani, L., Roshandel, G., Roth, G. A., Rothenbacher, D., Roy, A., Roy, N., Sackey, B. B., Sagar, R., Saleh, M. M., Sanabria, J. R., Santomauro, D. F., Santos, I. S., Sarmiento-Suarez, R., Sartorius, B., Satpathy, M., Savic, M., Sawhney, M., Sawyer, S. M., Schmidhuber, J., Schmidt, M. I., Schneider, I. J., Schutte, A. E., Schwebel, D. C., Seedat, S., Sepanlou, S. G., Servan-Mori, E. E., Shackelford, K., Shaheen, A., Shaikh, M. A., Levy, T. S., Sharma, R., She, J., Sheikhbahaei, S., Shen, J., Sheth, K. N., Shey, M., Shi, P., Shibuya, K., Shigematsu, M., Shin, M., Shiri, R., Shishani, K., Shiue, I., Sigfusdottir, I. D., Silpakit, N., Silva, D. A., Silverberg, J. I., Simard, E. P., Sindi, S., Singh, A., Singh, G. M., Singh, J. A., Singh, O. P., Singh, P. K., Skirbekk, V., Sligar, A., Soneji, S., Soreide, K., Sorensen, R. J., Soriano, J. B., Soshnikov, S., Sposato, L. A., Sreeramareddy, C. T., Stahl, H., Stanaway, J. D., Stathopoulou, V., Steckling, N., Steel, N., Stein, D. J., Steiner, C., Stockl, H., Stranges, S., Strong, M., Sun, J., Sunguya, B. F., Sur, P., Swaminathan, S., Sykes, B. L., Szoeke, C. E., Tabares-Seisdedos, R., Tabb, K. M., Talongwa, R. T., Tarawneh, M. R., Tavakkoli, M., Taye, B., Taylor, H. R., Tedla, B. A., Tefera, W., Tegegne, T. K., Tekle, D. Y., Shifa, G. T., Terkawi, A. S., Tessema, G. A., Thakur, J. S., Thomson, A. J., Thorne-Lyman, A. L., Thrift, A. G., Thurston, G. D., Tillmann, T., Tobe-Gai, R., Tonelli, M., Topor-Madry, R., Topouzis, F., Tran, B. X., Dimbuene, Z. T., Tura, A. K., Tuzcu, E. M., Tyrovolas, S., Ukwaja, K. N., Undurraga, E. A., Uneke, C. J., Uthman, O. A., van Donkelaar, A., Varakin, Y. Y., Vasankari, T., Vasconcelos, A. M., Veerman, J. L., Venketasubramanian, N., Verma, R. K., Violante, F. S., Vlassov, V. V., Volkow, P., Vollset, S. E., Wagner, G. R., Wallin, M. T., Wang, L., Wanga, V., Watkins, D. A., Weichenthal, S., Weiderpass, E., Weintraub, R. G., Weiss, D. J., Werdecker, A., Westerman, R., Whiteford, H. A., Wilkinson, J. D., Wiysonge, C. S., Wolfe, C. D., Wolfe, I., Won, S., Woolf, A. D., Workie, S. B., Wubshet, M., Xu, G., Yadav, A. K., Yakob, B., Yalew, A. Z., Yan, L. L., Yano, Y., Yaseri, M., Ye, P., Yip, P., Yonemoto, N., Yoon, S., Younis, M. Z., Yu, C., Zaidi, Z., Zaki, M. E., Zambrana-Torrelio, C., Zapata, T., Zegeye, E. A., Zhao, Y., Zhou, M., Zodpey, S., Zonies, D., Murray, C. J. 2016; 388 (10053): 1813-1850

    Abstract

    In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8-61·8) and varied widely by country, ranging from 85·5 (84·2-86·5) in Iceland to 20·4 (15·4-24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2)=0·88) and the MDG index (r(2)=0·92), whereas the non-MDG index had a weaker relation with SDI (r(2)=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0-10·4), and gains on the MDG index (a median change of 10·0 [6·7-13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1-8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened.GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000385285000013

    View details for PubMedID 27665228

    View details for PubMedCentralID PMC5055583

  • Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015 LANCET Kassebaum, N. J., Arora, M., Barber, R. M., Bhutta, Z. A., Carter, A., Casey, D. C., Charlson, F. J., Coates, M. M., Coggeshall, M., Cornaby, L., Dandona, L., Dicker, D. J., Erskine, H. E., Ferrari, A. J., Fitzmaurice, C., Foreman, K., Forouzanfar, M. H., Fullman, N., Gething, P. W., Goldberg, E. M., Graetz, N., Haagsma, J. A., Johnson, C., Kemmer, L., Khalil, I. A., Kinfu, Y., Kutz, M. J., Kyu, H. H., Leung, J., Liang, X., Lim, S. S., Lim, S. S., Lozano, R., Mensah, G. A., Mikesell, J., Mokdad, A. H., Mooney, M. D., Naghavi, M., Nguyen, G., Nsoesie, E., Pigott, D. M., Pinho, C., Rankin, Z., Reinig, N., Salomon, J. A., Sandar, L., Smith, A., Sorensen, R. J., Stanaway, J., Steiner, C., Teeple, S., Thomas, B. A., Troeger, C., VanderZanden, A., Wagner, J. A., Wanga, V., Whiteford, H. A., Zhou, M., Zoeckler, L., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abraham, B., Abubakar, I., Abu-Raddad, L. J., Abu-Rmeileh, N. M., Achoki, T., Ackerman, I. N., Adebiyi, A. O., Adedeji, I. A., Adsuar, J. C., Afanvi, K. A., Afshin, A., Agardh, E. E., Agarwal, A., Kumar, S., Ahmed, M. B., Kiadaliri, A. A., Ahmadieh, H., Akseer, N., Al-Aly, Z., Alam, K., Alam, N. K., Aldhahri, S. F., Alegretti, M. A., Aleman, A. V., Alemu, Z. A., Alexander, L. T., Raghib, A., Alkerwi, A., Alla, F., Allebeck, P., Alsharif, U., Altirkawi, K. A., Martin, E. A., Alvis-Guzman, N., Amare, A. T., Amberbir, A., Amegah, A. K., Amini, H., Ammar, W., Amrock, S. M., Anderson, G. M., Anderson, B. O., Antonio, C. A., Anwari, P., Arnlov, J., Arsenijevic, V. S., Artaman, A., Asayesh, H., Asghar, R. J., Avokpaho, E. F., Awasthi, A., Quintanilla, B. P., Azzopardi, P., Bacha, U., Badawi, A., Balakrishnan, K., Banerjee, A., Barac, A., Barker-Collo, S. L., Barnighausen, T., Barregard, L., Barrero, L. H., Basu, S., Bayou, T. A., Beardsley, J., Bedi, N., Beghi, E., Bell, B., Bell, M. L., Benjet, C., Bennett, D. A., Bensenor, I. M., Berhane, A., Bernabe, E., Betsu, B. D., Beyene, A. S., Bhala, N., Bhansali, A., Bhatt, S., Biadgilign, S., Bienhofff, K., Bikbov, B., Bin Abdulhak, A. A., Bisanzio, D., Bjertness, E., Blore, J. D., Borschmann, R., Boufous, S., Bourne, R. R., Brainin, M., Brazinova, A., Breitborde, N. J., Brugha, T. S., Buchbinder, R., Buckle, G. C., Butt, Z. A., Calabria, B., Campos-Nonato, I. R., Campuzano, J. C., Carabin, H., Carapetis, J. R., Cardenas, R., Carrero, J. J., Castaneda-Orjuela, C. A., Rivas, J. C., Catala-Lopez, F., Cavalleri, F., Chang, J., Chiang, P. P., Chibalabala, M., Chibueze, C. E., Chisumpa, V. H., Choi, J. J., Choudhury, L., Christensen, H., Ciobanu, L. G., Colistro, V., Colomar, M., Colquhoun, S. M., Cortinovis, M., Crump, J. A., Damasceno, A., Dandona, R., Dargan, P. I., das Neves, J., Davey, G., Davis, A. C., De Leo, D., Degenhardt, L., Del Gobbo, L. C., Derrett, S., Des Jarlais, D. C., deVeber, G. A., Dharmaratne, S. D., Dhillon, P. K., Ding, E. L., Doyle, K. E., Driscoll, T. R., Duan, L., Dubey, M., Duncan, B. B., Ebrahimi, H., Ellenbogen, R. G., Elyazar, I., Endries, A. Y., Ermakov, S. P., Eshrati, B., Esteghamati, A., Estep, K., Fahimi, S., Farid, T. A., Sa Farinha, C. S., Faro, A., Farvid, M. S., Farzadfar, F., Feigin, V. L., Fereshtehnejad, S., Fernandes, J. G., Fernandes, J. C., Fischer, F., Fitchett, J. R., Foigt, N., Fowkes, F. G., Franklin, R. C., Friedman, J., Frostad, J., Furst, T., Futran, N. D., Gabbe, B., Gankpe, F. G., Garcia-Basteiro, A. L., Gebrehiwot, T. T., Gebremedhin, A. T., Geleijnse, J. M., Gibney, K. B., Gillum, R. F., Ginawi, I. A., Giref, A. Z., Giroud, M., Gishu, M. D., Godwin, W. W., Gomez-Dantes, H., Gona, P., Goodridge, A., Gopalani, S. V., Gotay, C. C., Goto, A., Gouda, H. N., Guo, Y., Gupta, R., Gupta, R., Gupta, V., Gutierrez, R. A., Hafezi-Nejad, N., Haile, D., Hailu, A. D., Hailu, G. B., Halasa, Y. A., Ribhi, R., Hamadeh, Hamidi, S., Hammami, M., Handal, A. J., Hankey, G. J., Harb, H. L., Harikrishnan, S., Haro, J. M., Hassanvand, M. S., Hassen, T. A., Havmoeller, R., Hay, R. J., Hedayati, M. T., Heredia-Pi, I. B., Heydarpour, P., Hoek, H. W., Hoffman, D. J., Horino, M., Horita, N., Hosgood, H. D., Hoy, D. G., Hsairi, M., Huang, H., Huang, J. J., Iburg, K. M., Idrisov, B. T., Innos, K., Inoue, M., Jacobsen, K. H., Jauregui, A., Jayatilleke, A. U., Jeemon, P., Jha, V., Jiang, G., Jiang, Y., Jibat, T., Jimenez-Corona, A., Jin, Y., Jonas, J. B., Kabir, Z., Kajungu, D. K., Kalkonde, Y., Kamal, R., Kan, H., Kandel, A., Karch, A., Karema, C. K., Karimkhani, C., Kasaeian, A., Katibeh, M., Kaul, A., Kawakami, N., Kazi, D. S., Keiyoro, P. N., Kemp, A. H., Kengne, A. P., Keren, A., Kesavachandran, C. N., Khader, Y. S., Khan, A. R., Khan, E. A., Khang, Y., Khoja, T. A., Khubchandani, J., Kieling, C., Kim, C., Kim, D., Kim, Y. J., Kissoon, N., Kivipelto, M., Knibbs, L. D., Knudsen, A. K., Kokubo, Y., Kolte, D., Kopec, J. A., Koul, P. A., Koyanagi, A., Defo, B. K., Kuchenbecker, R. S., Bicer, B. K., Kuipers, E. J., Kumar, G. A., Kwan, G. F., Lalloo, R., Lallukka, T., Larsson, A., Latif, A. A., Lavados, P. M., Lawrynowicz, A. E., Leasher, J. L., Leigh, J., Leung, R., Li, Y., Li, Y., Lipshultz, S. E., Liu, P. Y., Liu, Y., Lloyd, B. K., Logroscino, G., Looker, K. J., Lotufo, P. A., Lucas, R. M., Lunevicius, R., Lyons, R. A., El Razek, H. M., Mandavi, M., Majdan, M., Majeed, A., Malekzadeh, R., Malta, D. C., Marcenes, W., Martinez-Raga, J., Masiye, F., Mason-Jones, A. J., Matzopoulos, R., Mayosi, B. M., McGrath, J. J., McKee, M., Meaney, P. A., Mehari, A., Melaku, Y. A., Memiah, P., Memish, Z. A., Mendoza, W., Meretoja, A., Meretoja, T. J., Mesfin, Y. M., Mhimbira, F. A., Miller, T. R., Mills, E. J., Mirarefin, M., Mirrakhimov, E. M., Mitchell, P. B., Mock, C. N., Mohammad, K. A., Mohammadi, A., Mohammed, S., Monasta, L., Montanez Hernandez, J. C., Montico, M., Moradi-Lakeh, M., Mori, R., Mueller, U. O., Mumford, J. E., Murdoch, M. E., Murthy, G. V., Nachega, J. B., Naheed, A., Naldi, L., Nangia, V., Newton, J. N., Ng, M., Ngalesoni, F. N., Le Nguyen, Q., Nisar, M. I., Pete, P. M., Nolla, J. M., Norheim, O. F., Norman, R. E., Norrving, B., Obermeyer, C. M., Ogbo, F. A., Oh, I., Oladimeji, O., Olivares, P. R., Olusanya, B. O., Olusanya, J. O., Oren, E., Ortiz, A., Ota, E., Oyekale, A. S., Pa, M., Park, E., Parsaeian, M., Patten, S. B., Patton, G. C., Pedro, J. M., Pereira, D. M., Perico, N., Pesudovs, K., Petzold, M., Phillips, M. R., Piel, F. B., Pillay, J. D., Pishgar, F., Plass, D., Polinder, S., Popova, S., Poulton, R. G., Pourmalek, F., Prasad, N. M., Qorbani, M., Rabiee, R. H., Radfar, A., Rafay, A., Rahimi, K., Rahimi-Movaghar, V., Rahman, M., Rahman, M. H., Rahman, S. u., Rai, D., Rai, R. K., Rajsic, S., Raju, M., Ram, U., Ranganathan, K., Refaat, A. H., Reitsma, M. B., Remuzzi, G., Resnikoff, S., Reynolds, A., Ribeiro, A. L., Ricci, S., Roba, H. S., Rojas-Rueda, D., Ronfani, L., Roshandel, G., Roth, G. A., Roy, A., Sackey, B. B., Sagar, R., Sanabria, J. R., Dolores Sanchez-Nino, M., Santos, I. S., Santos, J. V., Sarmiento-Suarez, R., Sartorius, B., Satpathy, M., Savic, M., Sawhney, M., Schmidt, M. I., Schneider, I. J., Schutte, A. E., Schwebel, D. C., Seedat, S., Sepanlou, S. G., Servan-Mori, E. E., Shahraz, S., Shaikh, M. A., Sharma, R., She, J., Sheikhbahaei, S., Shen, J., Sheth, K. N., Shibuya, K., Shigematsu, M., Shin, M., Shin, R., Sigfusdottir, I. D., Santos Silva, D. A., Silverberg, J. I., Simard, E. P., Singh, A., Singh, J. A., Singh, P. K., Skirbekk, V., Skogen, J. C., Soljak, M., Soreide, K., Sorensen, R. J., Sreeramareddy, C. T., Stathopoulou, V., Steel, N., Stein, D. J., Stein, M. B., Steiner, T. J., Stovner, L. J., Stranges, S., Stroumpoulis, K., Sunguya, B. F., Sur, P. J., Swaminathan, S., Sykes, B. L., Szoeke, C. E., Tabares-Seisdedos, R., Landon, N., Tanne, D., Tavakkoli, M., Taye, B., Taylor, H. R., Ao, B. J., Tegegne, T. K., Tekle, D. Y., Terkawi, A. S., Tessema, G. A., Thakur, J. S., Thomson, A. J., Thorne-Lyman, A. L., Thrift, A. G., Thurston, G. D., Tobe-Gai, R., Tonelli, M., Topor-Madry, R., Topouzis, F., Tran, B. X., Dimbuene, Z. T., Tsilimbaris, M., Tura, A. K., Tuzcu, E. M., Tyrovolas, S., Ukwaja, K. N., Undurraga, E. A., Uneke, C. J., Uthman, O. A., van Gool, C. H., van Os, J., Vasankari, T., Vasconcelos, A. M., Venketasubramanian, N., Violante, F. S., Vlassov, V. V., Vollset, S. E., Wagner, G. R., Wallin, M. T., Wang, L., Weichenthal, S., Weiderpass, E., Weintraub, R. G., Werdecker, A., WestermaM, R., Wijeratne, T., Wilkinson, J. D., Williams, H. C., Wiysonge, C. S., Woldeyohannes, S. M., Wolfe, C. D., Won, S., Xu, G., Yadav, A. K., Yakob, B., Yan, L. L., Yan, Y., Yaseri, M., Ye, P., Yip, P., Yonemoto, N., Yoon, S., Younis, M. Z., Yu, C., Zaidi, Z., Zaki, M. E., Zeeb, H., Zodpey, S., Zonies, D., Zuhlke, L. J., Zeeb, H., Zodpey, S., Zonies, D., Zuhlke, L. J., Vos, T., Lopez, A. D., Murray, C. J. 2016; 388 (10053): 1603-1658

    Abstract

    Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development.We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate.Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9-3·0) for men and 3·5 years (3·4-3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78-0·92) and 1·2 years (1·1-1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs.Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000385285000009

    View details for PubMedCentralID PMC5388857

  • Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015 LANCET Forouzanfar, M. H., Afshin, A., Alexander, L. T., Anderson, H. R., Bhutta, Z. A., Biryukov, S., Brauer, M., Burnett, R., Cercy, K., Charlson, F. J., Cohen, A. J., Dandona, L., Estep, K., Ferrari, A. J., Frostad, J. J., Fullman, N., Gething, P. W., Godwin, W. W., Griswold, M., Kinfu, Y., Kyu, H. H., Larson, H. J., Liang, X., Lim, S. S., Liu, P. Y., Lopez, A. D., Lozano, R., Marczak, L., Mensah, G. A., Mokdad, A. H., Moradi-Lakeh, M., Naghavi, M., Neal, B., Reitsma, M. B., Roth, G. A., Salomon, J. A., Sur, P. J., Vos, T., Wagner, J. A., Wang, H., Zhao, Y., Zhou, M., Aasvang, G. M., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulle, A. M., Abera, S. F., Abraham, B., Abu-Raddad, L. J., Abyu, G. Y., Adebiyi, A. O., Adedeji, I. A., Ademi, Z., Adou, A. K., Adsuar, J. C., Agardh, E. E., Agarwal, A., Agrawal, A., Kiadaliri, A. A., Ajala, O. N., Akinyemiju, T. F., Al-Aly, Z., Alam, K., Alam, N. K., Aldhahri, S. F., Aldridge, R. W., Alemu, Z. A., Ali, R., Alkerwi, A., Alla, F., Allebeck, P., Alsharif, U., Altirkawi, K. A., Alvarez Martin, E., Alvis-Guzman, N., Amare, A. T., Amberbir, A., Amegah, A. K., Amini, H., Ammar, W., Amrock, S. M., Andersen, H. H., Anderson, B. O., Antonio, C. A., Anwar, P., Arnlov, J., Al Artaman, Asayesh, H., Asghar, R. J., Assadi, R., Atique, S., Avokpaho, E. F., Awasthi, A., Quintanilla, B. P., Azzopardi, P., Bacha, U., Badawi, A., Bahit, M. C., Balakrishnan, K., Barac, A., Barber, R. M., Barker-Collo, S. L., Baernighausen, T., Barquera, S., Barregard, L., Barrero, L. H., Basu, S., Bans, C., Bazargan-Hejazi, S., Beardsley, J., Bedi, N., Beghi, E., Bell, M. L., Bello, A. K., Bennett, D. A., Bensenor, I. M., Berhane, A., Bernabe, E., Betsu, B. D., Beyene, A. S., Bhala, N., Bhansali, A., Bhatt, S., Biadgilign, S., Bikbov, B., Bisanzio, D., Bjertness, E., Blore, J. D., Borschmann, R., Boufous, S., Bourne, R. R., Brainin, M., Brazinova, A., Breitborde, N. J., Brenner, H., Broday, D. M., Brugha, T. S., Brunekreef, B., Butt, Z. A., Cahill, L. E., Calabria, B., Ricardo Campos-Nonato, I., Cardenas, R., Carpenter, D., Casey, D. C., Castaneda-Oquela, C. A., Castillo Rivas, J., Estanislao Castro, R., Catala-Lopez, F., Chang, J., Chiang, P. P., Chibalabala, M., Chimed-Ochir, O., Chisumpa, V. H., Chitheer, A. A., Choi, J. J., Christensen, H., Christopher, D. J., Ciobanu, L. G., Coates, M. M., Colquhoun, S. M., Cooper, L. T., Cooperrider, K., Cornaby, L., Cortinovis, M., Crump, J. A., Cuevas-Nasu, L., Damasceno, A., Dandona, R., Darby, S. C., Dargan, P. I., das Neves, J., Davis, A. C., Davletov, K., Filipa de Castro, E., De la Cruz-Gongora, V., De Leo, D., Degenhardt, L., Del Gobbo, L. C., Del Pozo-Cruz, B., Dellavalle, R. P., Deribew, A., Des Jarlais, D. C., Dharmaratne, S. D., Dhillon, P. K., Diaz-Tome, C., Dicker, D., Ding, E. L., Dorsey, E. R., Doyle, K. E., Driscoll, T. R., Duan, L., Dubey, M., Duncan, B. B., Elyazar, I., Endries, A. Y., Ermakov, S. P., Erskine, H. E., Eshrati, B., Esteghamati, A., Fahimi, S., Aquino Faraon, E. J., Farid, T. A., Sofia e Sa Farinha, C., Faro, A., Farvid, M. S., Farzadfar, F., Feigin, V. L., Fereshtehnejad, S., Fernandes, J. G., Fischer, F., Fitchett, J. R., Fleming, T., Foigt, N., Foreman, K., Fowkes, F. G., Franklin, R. C., Fuerst, T., Futran, N. D., Gakidou, E., Garcia-Basteiro, A. L., Gebrehiwot, T. T., Gebremedhin, A. T., Geleijnse, J. M., Gessner, B. D., Giref, A. Z., Giroud, M., Gishu, M. D., Goenka, S., Carmen Gomez-Cabrera, M., Gomez-Dantes, H., Gona, P., Goodridge, A., Gopalani, S. V., Gotay, C. C., Goto, A., Gouda, H. N., Gugnani, H. C., Guillemin, F., Guo, Y., Gupta, R., Gupta, R., Gutierrez, R. A., Haagsma, J. A., Hafezi-Nejad, N., Haile, D., Hailu, G. B., Halasa, Y. A., Hamadeh, R. R., Hamidi, S., Handal, A. J., Hankey, G. J., Hao, Y., Harb, H. L., Harikrishnan, S., Maria Haro, J., Hassanvand, M. S., Hassen, T. A., Havmoeller, R., Beatriz Heredia-Pi, I., Francisco Hernandez-Llanes, N., Heydarpour, P., Hoek, H. W., Hoffman, H. J., Horino, M., Horita, N., Hosgood, H. D., Hoy, D. G., Hsairi, M., Htet, A. S., Hu, G., Huang, J. J., Husseini, A., Hutchings, S. J., Huybrechts, I., Iburg, K. M., Idrisov, B. T., Ileanu, B. V., Inoue, M., Jacobs, T. A., Jacobsen, K. H., Jahanmehr, N., Jakovljevic, M. B., Jansen, H. A., Jassal, S. K., Javanbakht, M., Jayatilleke, A. U., Jee, S. H., Jeemon, P., Jha, V., Jiang, Y., Jibat, T., Jin, Y., Johnson, C. O., Jonas, J. B., Kabir, Z., Kalkonde, Y., Kamal, R., Kan, H., Karch, A., Karema, C. K., Karimkhani, C., Kasaeian, A., Kaul, A., Kawakami, N., Kazi, D. S., Keiyoro, P. N., Kemp, A. H., Kengne, A. P., Keren, A., Kesavachandran, C. N., Khader, Y. S., Khan, A. R., Khan, E. A., Khan, G., Khang, Y., Khatibzadeh, S., Khera, S., Khoja, T. A., Khubchandani, J., Kieling, C., Kim, C., Kim, D., Kimokoti, R. W., Kissoon, N., Kivipelto, M., Knibbs, L. D., Kokubo, Y., Kopec, J. A., Koul, P. A., Koyanagi, A., Kravchenko, M., Kromhout, H., Krueger, H., Ku, T., Defo, B. K., Kuchenbecker, R. S., Bicer, B. K., Kuipers, E. J., Kumar, G. A., Kwan, G. F., Lal, D. K., Lalloo, R., Lallukka, T., Lan, Q., Larsson, A., Latif, A. A., Beatriz Lawrynowicz, A. E., Leasher, J. L., Leigh, J., Leung, J., Levi, M., Li, X., Li, Y., Liang, J., Liu, S., Lloyd, B. K., Logroscino, G., Lotufo, P. A., Lunevicius, R., Maclntyre, M., Mahdavi, M., Majdan, M., Majeed, A., Malekzadeh, R., Malta, D. C., Manamo, W. A., Mapoma, C. C., Marcenes, W., Martin, R. V., Martinez-Raga, J., Masiye, F., Matsushita, K., Matzopoulos, R., Mayosi, B. M., McGrath, J. J., McKee, M., Meaney, P. A., Medina, C., Mehari, A., Mena-Rodriguez, F., Mekonnen, A. B., Melaku, Y. A., Memish, Z. A., Mendoza, W., Mensink, G. B., Meretoja, A., Meretoja, T. J., Mesfin, Y. M., Mhimbira, F. A., Miller, T. R., Mills, E. J., Mirarefin, M., Misganaw, A., Mock, C. N., Mohammadi, A., Mohammed, S., Mola, G. L., Monasta, L., Montanez Hernandez, J. C., Montico, M., Morawska, L., Mori, R., Mozaffarian, D., Mueller, U. O., Mullany, E., Mumford, J. E., Murthy, G. V., Nachega, J. B., Naheed, A., Nangia, V., Nassiri, N., Newton, J. N., Ng, M., Quyen Le Nguyen, Q., Nisar, M. I., Pete, P. M., Norheim, O. F., Norman, R. E., Norrving, B., Nyakarahuka, L., Obermeyer, C. M., Ogbo, F. A., Oh, I., Oladimeji, O., Olivares, P. R., Olsen, H., Olusanya, B. O., Olusanya, J. O., Opio, J. N., Oren, E., Orozco, R., Ortiz, A., Ota, E., Mahesh, P. A., Pana, A., Park, E., Parry, C. D., Parsaeian, M., Patel, T., Caicedo, A. J., Patil, S. T., Patten, S. B., Patton, G. C., Pearce, N., Pereira, D. M., Perico, N., Pesudovs, K., Petzold, M., Phillips, M. R., Piel, F. B., Pillay, J. D., Plass, D., Polinder, S., Pond, C. D., Pope, C. A., Pope, D., Popova, S., Poulton, R. G., Pourmalek, F., Prasad, N. M., Qorbani, M., Rabiee, R. H., Radfar, A., Rafay, A., Rahimi-Movaghar, V., Rahman, M., Rahman, M. H., Rahman, S. u., Rai, R. K., Rajsic, S., Raju, M., Ram, U., Rana, S. M., Ranganathan, K., Rao, P., Razo Garcia, C. A., Refaat, A. H., Rehm, C. D., Rehm, J., Reinig, N., Remuzzi, G., Resnikoff, S., Ribeiro, A. L., Rivera, J. A., Rolm, H. S., Rodriguez, A., Rodriguez-Ramirez, S., Rojas-Rueda, D., Roman, Y., Ronfani, L., Roshandel, G., Rothenbacher, D., Roy, A., Saleh, M. M., Sanabria, J. R., Dolores Sanchez-Nino, M., Sanchez-Pimienta, T. G., Sandar, L., Santomauro, D. F., Santos, I. S., Sarmiento-Suarez, R., Sartorius, B., Satpathy, M., Savic, M., Sawhney, M., Schmidhuber, J., Schmidt, M. I., Schneider, I. J., Schoettker, B., Schutte, A. E., Schwebel, D. C., Scott, J. G., Seedat, S., Sepanlou, S. G., Servan-Mori, E. E., Shaheen, A., Shahraz, S., Shaikh, M. A., Levy, T. S., Sharma, R., She, J., Sheikhbahaei, S., Shen, J., Sheth, K. N., Shi, P., Shibuya, K., Shigematsu, M., Shin, M., Shiri, R., Shishani, K., Shiue, I., Shrime, M. G., Sigfusdottir, I. D., Silva, D. A., Alves Silveira, D. G., Silverberg, J. I., Simard, E. P., Sindi, S., Singh, A., Singh, J. A., Singh, P. K., Slepak, E. L., Soljak, M., Soneji, S., Sorensen, R. J., Sposato, L. A., Sreeramareddy, C. T., Stathopoulou, V., Steckling, N., Steel, N., Stein, D. J., Stein, M. B., Stockl, H., Stranges, S., Stroumpoulis, K., Sunguya, B. F., Swaminathan, S., Sykes, B. L., Szoeke, C. E., Tabares-Seisdedos, R., Takahashi, K., Talongwa, R. T., Landon, N., Tanne, D., Tavakkoli, M., Taye, B. W., Taylor, H. R., Tedla, B. A., Tefera, W. M., Tegegne, T. K., Tekle, D. Y., Terkawi, A. S., Thakur, J. S., Thomas, B. A., Thomas, M. L., Thomson, A. J., Thorne-Lyman, A. L., Thrift, A. G., Thurston, G. D., Tillmann, T., Tobe-Gai, R., Tobollik, M., Topor-Madry, R., Topouzis, F., Towbin, J. A., Bach Xuan Tran, B. X., Dimbuene, Z. T., Tsilimparis, N., Tura, A. K., Tuzcu, E. M., Tyrovolas, S., Ukwaja, K. N., Undurraga, E. A., Uneke, C. J., Uthman, O. A., van Donkelaar, A., van Os, J., Varakin, Y. Y., Vasankari, T., Veerman, J. L., Venketasubramanian, N., Violante, F. S., Vollset, S. E., Wagner, G. R., Waller, S. G., Wang, J., Wang, L., Wang, Y., Weichenthal, S., Weiderpass, E., Weintraub, R. G., Werdecker, A., Westerman, R., Whiteford, H. A., Wijeratne, T., Wiysonge, C. S., Wolfe, C. D., Won, S., Woolf, A. D., Wubshet, M., Xavier, D., Xu, G., Yadav, A. K., Yakob, B., Yalew, A. Z., Yano, Y., Yaseri, M., Ye, P., Yip, P., Yonemoto, N., Yoon, S., Younis, M. Z., Yu, C., Zaidi, Z., Zaki, M. E., Zhu, J., Zipkin, B., Zodpey, S., Zuhlke, L. J., Murray, C. J. 2016; 388 (10053): 1659-1724

    Abstract

    The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context.We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6-58·8) of global deaths and 41·2% (39·8-42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa.Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden.Bill & Melinda Gates Foundation.

    View details for Web of Science ID 000385285000010

    View details for PubMedCentralID PMC5388856

  • Treatment failure and drug resistance in HIV-positive patients on tenofovir-based first-line antiretroviral therapy in western Kenya. Journal of the International AIDS Society Brooks, K. n., Diero, L. n., DeLong, A. n., Balamane, M. n., Reitsma, M. n., Kemboi, E. n., Orido, M. n., Emonyi, W. n., Coetzer, M. n., Hogan, J. n., Kantor, R. n. 2016; 19 (1): 20798

    Abstract

    Tenofovir-based first-line antiretroviral therapy (ART) is recommended globally. To evaluate the impact of its incorporation into the World Health Organization (WHO) guidelines, we examined treatment failure and drug resistance among a cohort of patients on tenofovir-based first-line ART at the Academic Model Providing Access to Healthcare, a large HIV treatment programme in western Kenya.We determined viral load (VL), drug resistance and their correlates in patients on ≥six months of tenofovir-based first-line ART. Based on enrolled patients' characteristics, we described these measures in those with (prior ART group) and without (tenofovir-only group) prior non-tenofovir-based first-line ART using Wilcoxon rank sum and Fisher's exact tests.Among 333 participants (55% female; median age 41 years; median CD4 336 cells/µL), detectable (>40 copies/mL) VL was found in 18%, and VL>1000 copies/mL (WHO threshold) in 10%. Virologic failure at both thresholds was significantly higher in 217 participants in the tenofovir-only group compared with 116 in the prior ART group using both cut-offs (24% vs. 7% with VL>40 copies/mL; 15% vs. 1% with VL>1000 copies/mL). Failure in the tenofovir-only group was associated with lower CD4 values and advanced WHO stage. In 35 available genotypes from 51 participants in the tenofovir-only group with VL>40 copies/mL (69% subtype A), any resistance was found in 89% and dual-class resistance in 83%. Tenofovir signature mutation K65R occurred in 71% (17/24) of the patients infected with subtype A. Patients with K65R had significantly lower CD4 values, higher WHO stage and more resistance mutations.In this Kenyan cohort, tenofovir-based first-line ART resulted in good (90%) virologic suppression including high suppression (99%) after switch from non-tenofovir-based ART. Lower virologic suppression (85%) and high observed resistance levels (89%) in the tenofovir-only group impact future treatment options, support recommendations for widespread VL monitoring in such resource limited settings to identify early treatment failure and suggest consideration of individualized resistance testing to design effective subsequent regimens.

    View details for DOI 10.7448/IAS.19.1.20798

    View details for PubMedID 27231099

    View details for PubMedCentralID PMC4882399

  • Pretreatment HIV Drug Resistance and HIV-1 Subtype C Are Independently Associated With Virologic Failure: Results From the Multinational PEARLS (ACTG A5175) Clinical Trial. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Kantor, R. n., Smeaton, L. n., Vardhanabhuti, S. n., Hudelson, S. E., Wallis, C. L., Tripathy, S. n., Morgado, M. G., Saravanan, S. n., Balakrishnan, P. n., Reitsma, M. n., Hart, S. n., Mellors, J. W., Halvas, E. n., Grinsztejn, B. n., Hosseinipour, M. C., Kumwenda, J. n., La Rosa, A. n., Lalloo, U. G., Lama, J. R., Rassool, M. n., Santos, B. R., Supparatpinyo, K. n., Hakim, J. n., Flanigan, T. n., Kumarasamy, N. n., Campbell, T. B., Eshleman, S. H. 2015; 60 (10): 1541–49

    Abstract

    Evaluation of pretreatment HIV genotyping is needed globally to guide treatment programs. We examined the association of pretreatment (baseline) drug resistance and subtype with virologic failure in a multinational, randomized clinical trial that evaluated 3 antiretroviral treatment (ART) regimens and included resource-limited setting sites.Pol genotyping was performed in a nested case-cohort study including 270 randomly sampled participants (subcohort), and 218 additional participants failing ART (case group). Failure was defined as confirmed viral load (VL) >1000 copies/mL. Cox proportional hazards models estimated resistance-failure association.In the representative subcohort (261/270 participants with genotypes; 44% women; median age, 35 years; median CD4 cell count, 151 cells/µL; median VL, 5.0 log10 copies/mL; 58% non-B subtypes), baseline resistance occurred in 4.2%, evenly distributed among treatment arms and subtypes. In the subcohort and case groups combined (466/488 participants with genotypes), used to examine the association between resistance and treatment failure, baseline resistance occurred in 7.1% (9.4% with failure, 4.3% without). Baseline resistance was significantly associated with shorter time to virologic failure (hazard ratio [HR], 2.03; P = .035), and after adjusting for sex, treatment arm, sex-treatment arm interaction, pretreatment CD4 cell count, baseline VL, and subtype, was still independently associated (HR, 2.1; P = .05). Compared with subtype B, subtype C infection was associated with higher failure risk (HR, 1.57; 95% confidence interval [CI], 1.04-2.35), whereas non-B/C subtype infection was associated with longer time to failure (HR, 0.47; 95% CI, .22-.98).In this global clinical trial, pretreatment resistance and HIV-1 subtype were independently associated with virologic failure. Pretreatment genotyping should be considered whenever feasible.NCT00084136.

    View details for DOI 10.1093/cid/civ102

    View details for PubMedID 25681380

    View details for PubMedCentralID PMC4425827

  • Phylogenetic and geospatial evaluation of HIV-1 subtype diversity at the largest HIV center in Rhode Island. Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases Chan, P. A., Reitsma, M. B., DeLong, A. n., Boucek, B. n., Nunn, A. n., Salemi, M. n., Kantor, R. n. 2014; 28: 358–66

    Abstract

    Individuals infected with HIV-1 non-B subtypes are understudied in the United States. Their characterization may augment prevention and treatment interventions. We examined the regional molecular epidemiology of non-B subtypes using a combined phylogenetic and geospatial approach. HIV-1 pol sequences and clinical data obtained for routine clinical care were aggregated from 2004 to 2011 at the largest HIV center in Rhode Island. Subtyping was performed by neighbor-joining and maximum-likelihood phylogeny and compared across eight commonly used tools (HIVdb, REGA, RIP, NCBI, Geno2Pheno, EuResist, jpHMM and STAR) using proportional odds ordinal regression. Individuals with non-B subtypes were characterized according to demographics and risk factors for infection, intra-subtype clustering by maximum-likelihood phylogeny, and geospatial hotspot analysis using Getis-Ord Gi(∗) statistics. Of 1277 unique sequences, phylogenetic subtyping demonstrated 8.3% (N=106, 95% CI 6.8-10%) non-B subtypes and circulating recombinant forms (CRFs): CRF02_AG=46; A=15; C=15; CRF01_AE=6; CRF06_CPX=5; CRF14_BG=5; G=3; CRF43_02G=3; D=3; CRF24_BG=3; CRF11_CPX=1; F1=1. Compared to phylogeny, Geno2Pheno was the most concordant (86% exact match) followed by REGA (85%), EuResist (85%) and STAR (82%). Of 106 individuals with non-B subtypes, 50% were male, 71% acquired infection through heterosexual transmission; 76%, were born in Africa, 6% Southeast Asia, 5% the United States, 3% Central America, 1% Europe, and 9% unknown. Eighty percent of CRF02_AG, 93% of A and 87% of C sequences were from African-born individuals. Twenty-two percent of non-B subtypes formed transmission clusters, including a significant number of younger individuals with perinatally-acquired infection. Geospatial analyses revealed hotspots of B and non-B subtypes in the state capital with a more concentrated focus among non-B subtypes. Molecular examination of regional HIV diversity revealed a larger than expected non-subtype B infected population, mostly born in Africa, with low ongoing regional transmission. Phylogenetic and geospatial characterization of infection clusters is helpful to identify targets for treatment and prevention interventions.

    View details for DOI 10.1016/j.meegid.2014.03.027

    View details for PubMedID 24721515

    View details for PubMedCentralID PMC4190103