Bio


Blake Thomson is a health disparities researcher and medical student at Stanford. An epidemiologist by training, he holds an MPhil in Epidemiology from the University of Cambridge and a DPhil (PhD) in Population Health from the University of Oxford. He has held several posts focused on health equity science, with an emphasis on disease prevention among groups historically underrepresented in medical research. He joined Stanford from the American Cancer Society, where he was Principal Scientist in Cancer Disparities Research.

Blake has authored or co-authored more than 30 articles in medical and public health journals, including The Lancet and JAMA. His first-author publications have appeared in such journals as The Lancet Global Health, JAMA Internal Medicine, JAMA Oncology, JAMA Neurology, and Circulation, among others. This work has received media attention from such outlets as The Washington Post, Nature, and National Geographic. His clinical and academic interests are focused on the prevention and control of common and debilitating diseases, particularly among those historically underrepresented in medical research.

Honors & Awards


  • The Year in Review, Top 3 articles by Altmetric score, JAMA Oncology (2021)
  • Nuffield Department of Population Health Scholarship, University of Oxford (2016)
  • Gates Cambridge Scholarship, Gates Cambridge Trust (2015)
  • Moeur Award, Arizona State University (2013)
  • Outstanding Graduate in the Social Sciences, Arizona State University (2013)
  • Flinn Scholarship, Flinn Foundation (2009)

Education & Certifications


  • DPhil (PhD), University of Oxford, Population Health (2020)
  • MPhil, University of Cambridge, Epidemiology (2016)
  • BA, Arizona State University, Global Health (2013)

All Publications


  • Association of Smoking Cessation and Cardiovascular, Cancer, and Respiratory Mortality. JAMA internal medicine Thomson, B., Islami, F. 2023

    View details for DOI 10.1001/jamainternmed.2023.6419

    View details for PubMedID 38010645

  • Association Between Smoking, Smoking Cessation, and Mortality by Race, Ethnicity, and Sex Among US Adults. JAMA network open Thomson, B., Emberson, J., Lacey, B., Lewington, S., Peto, R., Jemal, A., Islami, F. 2022; 5 (10): e2231480

    Abstract

    Patterns of cigarette smoking and smoking cessation vary considerably across demographic groups in the US, but there is limited evidence on whether the hazards of smoking and benefits of quitting vary across these groups. Population-specific evidence on the benefits of quitting smoking may motivate cessation among groups historically underrepresented in medical research.To quantify the association between smoking, smoking cessation, and mortality by race, ethnicity, and sex.This nationally representative, prospective cohort study used data from the US National Health Interview Survey collected via questionnaire between January 1997 and December 2018 among adults aged 25 to 84 years at recruitment. Participants were followed up for cause-specific mortality through December 31, 2019.Self-reported smoking status at recruitment, age at quitting smoking, and years since quitting smoking.The main outcomes were all-cause mortality and mortality from cancer, cardiovascular disease, and lower respiratory disease. Adjusted mortality rate ratios comparing never, former, and current smokers were calculated using Cox proportional hazards regression. Weighted analyses were conducted by race, ethnicity, and sex as reported by participants.Among the 551 388 participants in the main analyses, the mean (SD) age at recruitment was 48.9 (15.3) years; 307 601 (55.8%) were women, 87 207 (15.8%) were Hispanic, 75 545 (13.7%) were non-Hispanic Black, 355 782 (64.5%) were non-Hispanic White, and 32 854 (6.0%) identified as other non-Hispanic race and ethnicity. There were 74 870 deaths among participants aged 25 to 89 years during follow-up (36 792 [49.1%] among men; 38 078 [50.9%] among women). The all-cause mortality rate ratio (RR) for current vs never smoking was 2.80 (95% CI, 2.73-2.88) overall. The RRs were similar by sex but varied by race and ethnicity: Hispanic, 2.01 (95% CI, 1.84-2.18); non-Hispanic Black, 2.19 (95% CI, 2.06-2.33); non-Hispanic White, 3.00 (95% CI, 2.91-3.10); and other non-Hispanic race and ethnicity, 2.16 (95% CI, 1.88-2.47). When comparing those who quit smoking before age 45 years with never smokers, all-cause mortality RRs were 1.15 (95% CI, 1.03-1.28) among Hispanic individuals, 1.16 (95% CI, 1.07-1.25) among non-Hispanic Black individuals, 1.11 (95% CI, 1.08-1.15) among non-Hispanic White individuals, and 1.17 (95% CI, 0.99-1.39) among other non-Hispanic individuals.In this prospective cohort study, among men and women from diverse racial and ethnic groups, current smoking was associated with at least twice the all-cause mortality rate of never smoking. Quitting smoking, particularly at younger ages, was associated with substantial reductions in the relative excess mortality associated with continued smoking.

    View details for DOI 10.1001/jamanetworkopen.2022.31480

    View details for PubMedID 36279139

  • American Cancer Society's report on the status of cancer disparities in the United States, 2021 CA-A CANCER JOURNAL FOR CLINICIANS Islami, F., Guerra, C. E., Minihan, A., Yabroff, K., Fedewa, S. A., Sloan, K., Wiedt, T. L., Thomson, B., Siegel, R. L., Nargis, N., Winn, R. A., Lacasse, L., Makaroff, L., Daniels, E. C., Patel, A., Cance, W. G., Jemal, A. 2022; 72 (2): 112-143

    Abstract

    In this report, the authors provide comprehensive and up-to-date US data on disparities in cancer occurrence, major risk factors, and access to and utilization of preventive measures and screening by sociodemographic characteristics. They also review programs and resources that have reduced cancer disparities and provide policy recommendations to further mitigate these inequalities. The overall cancer death rate is 19% higher among Black males than among White males. Black females also have a 12% higher overall cancer death rate than their White counterparts despite having an 8% lower incidence rate. There are also substantial variations in death rates for specific cancer types and in stage at diagnosis, survival, exposure to risk factors, and receipt of preventive measures and screening by race/ethnicity, socioeconomic status, and geographic location. For example, kidney cancer death rates by sex among American Indian/Alaska Native people are ≥64% higher than the corresponding rates in each of the other racial/ethnic groups, and the 5-year relative survival for all cancers combined is 14% lower among residents of poorer counties than among residents of more affluent counties. Broad and equitable implementation of evidence-based interventions, such as increasing health insurance coverage through Medicaid expansion or other initiatives, could substantially reduce cancer disparities. However, progress will require not only equitable local, state, and federal policies but also broad interdisciplinary engagement to elevate and address fundamental social inequities and longstanding systemic racism.

    View details for DOI 10.3322/caac.21703

    View details for Web of Science ID 000728057600001

    View details for PubMedID 34878180

  • Association of Smoking Initiation and Cessation Across the Life Course and Cancer Mortality: Prospective Study of 410 000 US Adults JAMA ONCOLOGY Thomson, B., Emberson, J., Lacey, B., Lewington, S., Peto, R., Islami, F. 2021; 7 (12): 1901-1903

    View details for DOI 10.1001/jamaoncol.2021.4949

    View details for Web of Science ID 000709921900006

    View details for PubMedID 34673892

    View details for PubMedCentralID PMC8532035

  • Low-intensity daily smoking and cause-specific mortality in Mexico: prospective study of 150 000 adults INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Thomson, B., Tapia-Conyer, R., Lacey, B., Lewington, S., Ramirez-Reyes, R., Aguilar-Ramirez, D., Gnatiuc, L., Herrington, W. G., Torres, J., Trichia, E., Wade, R., Collins, R., Peto, R., Kuri-Morales, P., Alegre-Diaz, J., Emberson, J. R. 2021; 50 (3): 955-964

    Abstract

    Research is needed to determine the relevance of low-intensity daily smoking to mortality in countries such as Mexico, where such smoking habits are common.Prospective study of 159 755 Mexican adults recruited from 1998-2004 and followed for cause-specific mortality to 1 January 2018. Participants were categorized according to baseline self-reported smoking status. Confounder-adjusted mortality rate ratios (RRs) at ages 35-89 were estimated using Cox regression, after excluding those with previous chronic disease (to avoid reverse causality).Among 42 416 men and 86 735 women aged 35-89 and without previous disease, 18 985 men (45%) and 18 072 women (21%) reported current smoking and 8866 men (21%) and 53 912 women (62%) reported never smoking. Smoking less than daily was common: 33% of male current smokers and 39% of female current smokers. During follow-up, the all-cause mortality RRs associated with the baseline smoking categories of <10 cigarettes per day (average during follow-up 4 per day) or ≥10 cigarettes per day (average during follow-up 10 per day), compared with never smoking, were 1.17 (95% confidence interval 1.10-1.25) and 1.54 (1.42-1.67), respectively. RRs were similar irrespective of age or sex. The diseases most strongly associated with daily smoking were respiratory cancers, chronic obstructive pulmonary disease and gastrointestinal and vascular diseases. Ex-daily smokers had substantially lower mortality rates than those who were current daily smokers at recruitment.In this Mexican population, low-intensity daily smoking was associated with increased mortality. Of those smoking 10 cigarettes per day on average, about one-third were killed by their habit. Quitting substantially reduced these risks.

    View details for DOI 10.1093/ije/dyab013

    View details for Web of Science ID 000685312900031

    View details for PubMedID 33659992

    View details for PubMedCentralID PMC8271211

  • Childhood Smoking, Adult Cessation, and Cardiovascular Mortality: Prospective Study of 390 000 US Adults JOURNAL OF THE AMERICAN HEART ASSOCIATION Thomson, B., Emberson, J., Lacey, B., Peto, R., Woodward, M., Lewington, S. 2020; 9 (21): e018431

    View details for DOI 10.1161/JAHA.120.018431

    View details for Web of Science ID 000588373500020

    View details for PubMedID 33108954

    View details for PubMedCentralID PMC7763404

  • The COVID-19 Pandemic A Global Natural Experiment CIRCULATION Thomson, B. 2020; 142 (1): 14-16
  • Association of childhood smoking and adult mortality: prospective study of 120 000 Cuban adults LANCET GLOBAL HEALTH Thomson, B., Armas Rojas, N., Lacey, B., Burrett, J., Varona-Perez, P., Calderon Martinez, M., Lorenzo-Vazquez, E., Bess Constanten, S., Morales Rigau, J., Hernandez Lopez, O., Martinez Morales, M., Alonso Aloma, I., Achiong Estupinan, F., Diaz Gonzalez, M., Rosquete Munoz, N., Cendra Asencio, M., Emberson, J., Peto, R., Lewington, S., Duenas Herrera, A. 2020; 8 (6): E850-E857

    Abstract

    The average age at which people start smoking has been decreasing in many countries, but insufficient evidence exists on the adult hazards of having started smoking in childhood and, especially, in early childhood. We aimed to investigate the association between smoking habits (focusing on the age when smokers started) and cause-specific premature mortality in a cohort of adults in Cuba.For this prospective study, adults were recruited from five provinces in Cuba. Participants were interviewed (data collected included socioeconomic status, medical history, alcohol consumption, and smoking habits) and had their height, weight, and blood pressure measured. Participants were followed up until Jan 1, 2017 for cause-specific mortality; a subset was resurveyed in 2006-08. We used Cox regression to calculate adjusted rate ratios (RRs) for mortality at ages 30-69 years, comparing never-smokers with current smokers by age they started smoking and number of cigarettes smoked per day and with ex-smokers by the age at which they had quit.Between Jan 1, 1996, and Nov 24, 2002, 146 556 adults were recruited into the study, of whom 118 840 participants aged 30-69 years at recruitment contributed to the main analyses. 27 264 (52%) of 52 524 men and 19 313 (29%) of 66 316 women were current smokers. Most participants reported smoking cigarettes; few smoked only cigars. About a third of current cigarette smokers had started before age 15 years. Compared with never-smokers, the all-cause mortality RR was highest in participants who had started smoking at ages 5-9 years (RR 2·51, 95% CI 2·21-2·85), followed by ages 10-14 years (1·83, 1·72-1·95), 15-19 years (1·56, 1·46-1·65), and ages 20 years or older (1·50, 1·39-1·62). Smoking accounted for a quarter of all premature deaths in this population, but quitting before about age 40 years avoided almost all of the excess mortality due to smoking.In this cohort of adults in Cuba, starting to smoke in childhood was common and quitting was not. Starting in childhood approximately doubled the rate of premature death (ie, before age 70 years). If this 2-fold mortality RR continues into old age, about half of participants who start smoking before age 15 years and do not stop will eventually die of complications from their habit. The greatest risks were found among adults who began smoking before age 10 years.UK Medical Research Council, Cancer Research UK, British Heart Foundation, US Centers for Disease Control and Prevention (CDC) Foundation (with support from Amgen).

    View details for Web of Science ID 000536463500032

    View details for PubMedID 32446350

    View details for PubMedCentralID PMC7248573

  • What "Medicare for All" Could Mean for US Medical Research Lessons From the United Kingdom CIRCULATION Thomson, B., Lacey, B., Lewington, S. 2019; 140 (19): 1527-1529
  • Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet Ng, M., Fleming, T., Robinson, M., Thomson, B., Graetz, N., Margono, C., Mullany, E. C., Biryukov, S., Abbafati, C., Abera, S. F., Abraham, J. P., Abu-Rmeileh, N. M., Achoki, T., Albuhairan, F. S., Alemu, Z. A., Alfonso, R., Ali, M. K., Ali, R., Guzman, N. A., Ammar, W., Anwari, P., Banerjee, A., Barquera, S., Basu, S., Bennett, D. A., Bhutta, Z., Blore, J., Cabral, N., Nonato, I. C., Chang, J., Chowdhury, R., Courville, K. J., Criqui, M. H., Cundiff, D. K., Dabhadkar, K. C., Dandona, L., Davis, A., Dayama, A., Dharmaratne, S. D., Ding, E. L., Durrani, A. M., Esteghamati, A., Farzadfar, F., Fay, D. F., Feigin, V. L., Flaxman, A., Forouzanfar, M. H., Goto, A., Green, M. A., Gupta, R., Hafezi-Nejad, N., Hankey, G. J., Harewood, H. C., Havmoeller, R., Hay, S., Hernandez, L., Husseini, A., Idrisov, B. T., Ikeda, N., Islami, F., Jahangir, E., Jassal, S. K., Jee, S. H., Jeffreys, M., Jonas, J. B., Kabagambe, E. K., Khalifa, S. E., Kengne, A. P., Khader, Y. S., Khang, Y., Kim, D., Kimokoti, R. W., Kinge, J. M., Kokubo, Y., Kosen, S., Kwan, G., Lai, T., Leinsalu, M., Li, Y., Liang, X., Liu, S., Logroscino, G., Lotufo, P. A., Lu, Y., Ma, J., Mainoo, N. K., Mensah, G. A., Merriman, T. R., Mokdad, A. H., Moschandreas, J., Naghavi, M., Naheed, A., Nand, D., Narayan, K. M., Nelson, E. L., Neuhouser, M. L., Nisar, M. I., Ohkubo, T., Oti, S. O., Pedroza, A., Prabhakaran, D., Roy, N., Sampson, U., Seo, H., Sepanlou, S. G., Shibuya, K., Shiri, R., Shiue, I., Singh, G. M., Singh, J. A., Skirbekk, V., Stapelberg, N. J., Sturua, L., Sykes, B. L., Tobias, M., Tran, B. X., Trasande, L., Toyoshima, H., van de Vijver, S., Vasankari, T. J., Veerman, J. L., Velasquez-Melendez, G., Vlassov, V. V., Vollset, S. E., Vos, T., Wang, C., Wang, X., Weiderpass, E., Werdecker, A., Wright, J. L., Yang, Y. C., Yatsuya, H., Yoon, J., Yoon, S., Zhao, Y., Zhou, M., Zhu, S., Lopez, A. D., Murray, C. J., Gakidou, E. 2014; 384 (9945): 766-781

    Abstract

    In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013.We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down.Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(14)60460-8

    View details for PubMedID 24880830

  • Smoking Prevalence and Cigarette Consumption in 187 Countries, 1980-2012 JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION Marie Ng, Freeman, M. K., Fleming, T. D., Robinson, M., Dwyer-Lindgren, L., Thomson, B., Wollum, A., Sanman, E., Wulf, S., Lopez, A. D., Murray, C. L., Gakidou, E. 2014; 311 (2): 183-192

    Abstract

    Tobacco is a leading global disease risk factor. Understanding national trends in prevalence and consumption is critical for prioritizing action and evaluating tobacco control progress.To estimate the prevalence of daily smoking by age and sex and the number of cigarettes per smoker per day for 187 countries from 1980 to 2012.Nationally representative sources that measured tobacco use (n = 2102 country-years of data) were systematically identified. Survey data that did not report daily tobacco smoking were adjusted using the average relationship between different definitions. Age-sex-country-year observations (n = 38,315) were synthesized using spatial-temporal gaussian process regression to model prevalence estimates by age, sex, country, and year. Data on consumption of cigarettes were used to generate estimates of cigarettes per smoker per day.Modeled age-standardized prevalence of daily tobacco smoking by age, sex, country, and year; cigarettes per smoker per day by country and year.Global modeled age-standardized prevalence of daily tobacco smoking in the population older than 15 years decreased from 41.2% (95% uncertainty interval [UI], 40.0%-42.6%) in 1980 to 31.1% (95% UI, 30.2%-32.0%; P < .001) in 2012 for men and from 10.6% (95% UI, 10.2%-11.1%) to 6.2% (95% UI, 6.0%-6.4%; P < .001) for women. Global modeled prevalence declined at a faster rate from 1996 to 2006 (mean annualized rate of decline, 1.7%; 95% UI, 1.5%-1.9%) compared with the subsequent period (mean annualized rate of decline, 0.9%; 95% UI, 0.5%-1.3%; P = .003). Despite the decline in modeled prevalence, the number of daily smokers increased from 721 million (95% UI, 700 million-742 million) in 1980 to 967 million (95% UI, 944 million-989 million; P < .001) in 2012. Modeled prevalence rates exhibited substantial variation across age, sex, and countries, with rates below 5% for women in some African countries to more than 55% for men in Timor-Leste and Indonesia. The number of cigarettes per smoker per day also varied widely across countries and was not correlated with modeled prevalence.Since 1980, large reductions in the estimated prevalence of daily smoking were observed at the global level for both men and women, but because of population growth, the number of smokers increased significantly. As tobacco remains a threat to the health of the world's population, intensified efforts to control its use are needed.

    View details for DOI 10.1001/jama.2013.284692

    View details for Web of Science ID 000329339400024

    View details for PubMedID 24399557

  • Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States, 2019. CA: a cancer journal for clinicians Islami, F., Marlow, E. C., Thomson, B., McCullough, M. L., Rumgay, H., Gapstur, S. M., Patel, A. V., Soerjomataram, I., Jemal, A. 2024

    Abstract

    In 2018, the authors reported estimates of the number and proportion of cancers attributable to potentially modifiable risk factors in 2014 in the United States. These data are useful for advocating for and informing cancer prevention and control. Herein, based on up-to-date relative risk and cancer occurrence data, the authors estimated the proportion and number of invasive cancer cases (excluding nonmelanoma skin cancers) and deaths, overall and for 30 cancer types among adults who were aged 30 years and older in 2019 in the United States, that were attributable to potentially modifiable risk factors. These included cigarette smoking; second-hand smoke; excess body weight; alcohol consumption; consumption of red and processed meat; low consumption of fruits and vegetables, dietary fiber, and dietary calcium; physical inactivity; ultraviolet radiation; and seven carcinogenic infections. Numbers of cancer cases and deaths were obtained from data sources with complete national coverage, risk factor prevalence estimates from nationally representative surveys, and associated relative risks of cancer from published large-scale pooled or meta-analyses. In 2019, an estimated 40.0% (713,340 of 1,781,649) of all incident cancers (excluding nonmelanoma skin cancers) and 44.0% (262,120 of 595,737) of all cancer deaths in adults aged 30 years and older in the United States were attributable to the evaluated risk factors. Cigarette smoking was the leading risk factor contributing to cancer cases and deaths overall (19.3% and 28.5%, respectively), followed by excess body weight (7.6% and 7.3%, respectively), and alcohol consumption (5.4% and 4.1%, respectively). For 19 of 30 evaluated cancer types, more than one half of the cancer cases and deaths were attributable to the potentially modifiable risk factors considered in this study. Lung cancer had the highest number of cancer cases (201,660) and deaths (122,740) attributable to evaluated risk factors, followed by female breast cancer (83,840 cases), skin melanoma (82,710), and colorectal cancer (78,440) for attributable cases and by colorectal (25,800 deaths), liver (14,720), and esophageal (13,600) cancer for attributable deaths. Large numbers of cancer cases and deaths in the United States are attributable to potentially modifiable risk factors, underscoring the potential to substantially reduce the cancer burden through broad and equitable implementation of preventive initiatives.

    View details for DOI 10.3322/caac.21858

    View details for PubMedID 38990124

  • Revisiting the Emergency Department. JAMA neurology Thomson, B. 2024

    View details for DOI 10.1001/jamaneurol.2023.5623

    View details for PubMedID 38345806

  • 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

  • Mortality by Education Before and During the COVID-19 Pandemic, U.S., 2017-2020. American journal of preventive medicine Marlow, E. C., Jemal, A., Thomson, B., Wiese, D., Zhao, J., Siegel, R. L., Islami, F. 2023; 64 (1): 105-116

    Abstract

    INTRODUCTION: Mortality disparities by SES, including education, have steadily increased in the U.S. over the past decades. This study examined whether these disparities overall and for 7 major causes of death were exacerbated in 2020, coincident with the emergence of the COVID-19 pandemic.METHODS: Using data on 7,123,254 U.S. deaths from 2017 to 2020, age-standardized death rates and mortality rate differences per 100,000 population and rate ratios comparing least with most educated were calculated by sex and race/ethnicity.RESULTS: All-cause death rates were approximately 2 times higher among adults with least than among those with most education. Disparities in all-cause mortality by educational attainment slightly increased from 2017 (rate ratio=1.97; 95% CI=1.95, 1.98; rate difference=739.9) to 2019 (rate ratio=2.04; 95% CI=2.03, 2.06; rate difference=761.3) and then greatly increased in 2020 overall (rate ratio=2.32; 95% CI=2.30, 2.33; rate difference=1,042.9) and when excluding COVID-19 deaths (rate ratio=2.27; 95% CI=2.25, 2.28; rate difference=912.3). Similar patterns occurred across race/ethnicity and sex, although Hispanic individuals had the greatest relative increase in disparities for all-cause mortality from 2019 (rate ratio=1.47; 95% CI=1.43, 1.51; rate difference=282.4) to 2020 overall (rate ratio=2.00; 95% CI=1.94, 2.06; rate difference=652.3) and when excluding COVID-19 deaths (rate ratio=1.84; 95% CI=1.79, 1.90; rate difference=458.7). Disparities in cause-specific mortality by education were generally stable from 2017 to 2019, followed by a considerable increase from 2019 to 2020 for heart disease, cancer, cerebrovascular disease, and unintentional injury. Among these causes of death, the relative increase in rate ratio from 2019 to 2020 was greatest for unintentional injury (24.8%; from 3.41 [95% CI=3.23, 3.60] to 4.26 [95% CI=3.99, 4.53]).CONCLUSIONS: Mortality disparities by education widened in the U.S. in 2020, during the COVID-19 pandemic. Further research is warranted to understand the reasons for these widened disparities.

    View details for DOI 10.1016/j.amepre.2022.08.015

    View details for PubMedID 36528352

  • External validation of models for predicting risk of colorectal cancer using the China Kadoorie Biobank. BMC medicine Abhari, R. E., Thomson, B., Yang, L., Millwood, I., Guo, Y., Yang, X., Lv, J., Avery, D., Pei, P., Wen, P., Yu, C., Chen, Y., Chen, J., Li, L., Chen, Z., Kartsonaki, C. 2022; 20 (1): 302

    Abstract

    In China, colorectal cancer (CRC) incidence and mortality have been steadily increasing over the last decades. Risk models to predict incident CRC have been developed in various populations, but they have not been systematically externally validated in a Chinese population.  This study aimed to assess the performance of risk scores in predicting CRC using the China Kadoorie Biobank (CKB), one of the largest and geographically diverse prospective cohort studies in China.Nine models were externally validated in 512,415 participants in CKB and included 2976 cases of CRC. Model discrimination was assessed, overall and by sex, age, site, and geographic location, using the area under the receiver operating characteristic curve (AUC). Model discrimination of these nine models was compared to a model using age alone. Calibration was assessed for five models, and they were re-calibrated in CKB.The three models with the highest discrimination (Ma (Cox model) AUC 0.70 [95% CI 0.69-0.71]; Aleksandrova 0.70 [0.69-0.71]; Hong 0.69 [0.67-0.71]) included the variables age, smoking, and alcohol. These models performed significantly better than using a model based on age alone (AUC of 0.65 [95% CI 0.64-0.66]). Model discrimination was generally higher in younger participants, males, urban environments, and for colon cancer. The two models (Guo and Chen) developed in Chinese populations did not perform better than the others. Among the 10% of participants with the highest risk, the three best performing models identified 24-26% of participants that went on to develop CRC.Several risk models based on easily obtainable demographic and modifiable lifestyle factor have good discrimination in a Chinese population. The three best performing models have a higher discrimination than using a model based on age alone.

    View details for DOI 10.1186/s12916-022-02488-w

    View details for PubMedID 36071519

    View details for PubMedCentralID PMC9454206

  • Person-years of life lost and lost earnings from cigarette smoking-attributable cancer deaths, United States, 2019 INTERNATIONAL JOURNAL OF CANCER Islami, F., Marlow, E. C., Zhao, J., Wiese, D., Asare, S., Bandi, P., Thomson, B., Zheng, Z., Nargis, N., Yabroff, K., Jemal, A. 2022

    Abstract

    State-specific information on lost earnings due to smoking-attributable cancer deaths to inform and advocate for tobacco control policies is lacking. We estimated person-years of life lost (PYLL) and lost earnings due to cigarette smoking-attributable cancer deaths in the United States nationally and by state. Proportions and numbers of cigarette smoking-attributable cancer deaths and associated PYLL among individuals aged 25 to 79 years in 2019 were calculated and combined with annual median earnings to estimate lost earnings attributable to cigarette smoking. In 2019, estimated total PYLL and lost earnings associated with cigarette smoking-attributable cancer deaths in ages 25 to 79 years in the United States were 2 188 195 (95% CI, 2 148 707-2 231 538) PYLL and $20.9 billion ($20.0 billion-$21.7 billion), respectively. States with the highest overall age-standardized PYLL and lost earning rates generally were in the South and Midwest. The estimated rate per 100 000 population ranged from 352 (339-366) in Utah to 1337 (1310-1367) in West Virginia for PYLL and from $4.3 million ($3.5 million-$5.2 million) in Idaho to $14.8 million ($10.6 million-$20.7 million) in Missouri for lost earnings. If age-specific PYLL and lost earning rates in Utah had been achieved by all states, 58.2% (57.0%-59.5%) of the estimated total PYLL (1 274 178; 1 242 218-1 306 685 PYLL) and 50.5% (34.2%-62.4%) of lost earnings ($10.5 billion; $7.1 billion-$13.1 billion) in 2019 nationally would have been avoided. Lost earnings due to smoking-attributable cancer deaths are substantial in the United States and are highest in states with weaker tobacco control policies.

    View details for DOI 10.1002/ijc.34217

    View details for Web of Science ID 000838106000001

    View details for PubMedID 35946832

  • Association between disparities in intergenerational economic mobility and cause-specific mortality among Black and White persons in the United States CANCER EPIDEMIOLOGY Islami, F., Fedewa, S. A., Thomson, B., Nogueira, L., Yabroff, K., Jemal, A. 2021; 74: 101998

    Abstract

    Evidence about the association between structural racism and mortality in the United States is limited. We examined the association between ongoing structural racism, measured as inequalities in adulthood income between White and Black children with similar parental household income (economic mobility gap) in a recent birth cohort, and Black-White disparities in death rates (mortality gap) overall and for major causes.Sex-, race/ethnicity-, and county-specific data were used to examine sex-specific associations between economic mobility and mortality gaps for all causes combined, heart diseases, cerebrovascular diseases, chronic obstructive pulmonary disease (COPD), injury/violence, all malignant cancers, and 14 cancer types. Economic mobility data for 1978-1983 birth cohorts and death rates during 2011-2018 were obtained from the Opportunity Atlas and National Center for Health Statistics, respectively. Data from 471 counties were included in analyses of all-cause mortality at ages 30-39 years during 2011-2018 (corresponding to partially overlapping 1978-1983 birth cohorts); and from 1,572 and 1,248 counties in analyses of all-cause and cause-specific mortality in all ages combined, respectively.In ages 30-39 years, a one percentile increase in the economic mobility gap was associated with a 6.8 % (95 % confidence interval 1.8 %-11.8 %) increase in the Black-White mortality gap among males and a 13.5 % (8.9 %-18.1 %) increase among females, based on data from 471 counties. In all ages combined, the corresponding percentages based on data from 1,572 counties were 10.2 % (7.2 %-13.2 %) among males and 14.8 % (11.4 %-18.2 %) among females, equivalent to an increase of 18.4 and 14.0 deaths per 100,000 in the mortality gap, respectively. Similarly, strong associations between economic mobility gap and mortality gap in all ages were found for major causes of death, notably for potentially preventable conditions, including COPD, injury/violence, and cancers of the lung, liver, and cervix.Economic mobility gap conditional on parental income in a recent birth cohort as a marker of ongoing structural racism is strongly associated with Black-White disparities in all-cause mortality and mortality from several causes.

    View details for DOI 10.1016/j.canep.2021.101998

    View details for Web of Science ID 000708131900005

    View details for PubMedID 34364819

  • Evaluating clinical characteristics studies produced early in the Covid-19 pandemic: A systematic review PLOS ONE Manoharan, L., Cattrall, J. S., Harris, C., Newell, K., Thomson, B., Pritchard, M. G., Bannister, P. G., Sigfrid, L., Solomon, T., Horby, P. W., Carson, G., Olliaro, P. 2021; 16 (5): e0251250

    Abstract

    Clinical characterisation studies have been essential in helping inform research, diagnosis and clinical management efforts, particularly early in a pandemic. This systematic review summarises the early literature on clinical characteristics of patients admitted to hospital, and evaluates the quality of evidence produced during the initial stages of the pandemic.MEDLINE, EMBASE and Global Health databases were searched for studies published from January 1st 2020 to April 28th 2020. Studies which reported on at least 100 hospitalised patients with Covid-19 of any age were included. Data on clinical characteristics were independently extracted by two review authors. Study design specific critical appraisal tools were used to evaluate included studies: the Newcastle Ottawa scale for cohort and cross sectional studies, Joanna Briggs Institute checklist for case series and the Cochrane collaboration tool for assessing risk of bias in randomised trials.The search yielded 78 studies presenting data on 77,443 people. Most studies (82%) were conducted in China. No studies included patients from low- and middle-income countries. The overall quality of included studies was low to moderate, and the majority of studies did not include a control group. Fever and cough were the most commonly reported symptoms early in the pandemic. Laboratory and imaging findings were diverse with lymphocytopenia and ground glass opacities the most common findings respectively. Clinical data in children and vulnerable populations were limited.The early Covid-19 literature had moderate to high risk of bias and presented several methodological issues. Early clinical characterisation studies should aim to include different at-risk populations, including patients in non-hospital settings. Pandemic preparedness requires collection tools to ensure observational studies are methodologically robust and will help produce high-quality data early on in the pandemic to guide clinical practice and public health policy.Available at https://osf.io/mpafn.

    View details for DOI 10.1371/journal.pone.0251250

    View details for Web of Science ID 000664630200011

    View details for PubMedID 34003850

    View details for PubMedCentralID PMC8130955

  • Alcohol consumption and cause-specific mortality in Cuba: prospective study of 120 623 adults ECLINICALMEDICINE Armas Rojas, N. B., Lacey, B., Simadibrata, D., Ross, S., Varona-Perez, P., Burrett, J., Calderon Martinez, M., Lorenzo-Vazquez, E., Bess Constanten, S., Thomson, B., Sherliker, P., Morales Rigau, J., Carter, J., Massa, M., Hernandez Lopez, O., Islam, N., Martinez Morales, M., Alonso Aloma, I., Achiong Estupinan, F., Diaz Gonzalez, M., Rosquete Munoz, N., Cendra Asencio, M., Emberson, J., Peto, R., Lewington, S. 2021; 33: 100692

    Abstract

    The associations of cause-specific mortality with alcohol consumption have been studied mainly in higher-income countries. We relate alcohol consumption to mortality in Cuba.In 1996-2002, 146 556 adults were recruited into a prospective study from the general population in five areas of Cuba. Participants were interviewed, measured and followed up by electronic linkage to national death registries until January 1, 2017. After excluding all with missing data or chronic disease at recruitment, Cox regression (adjusted for age, sex, province, education, and smoking) was used to relate mortality rate ratios (RRs) at ages 35-79 years to alcohol consumption. RRs were corrected for long-term variability in alcohol consumption using repeat measures among 20 593 participants resurveyed in 2006-08.After exclusions, there were 120 623 participants aged 35-79 years (mean age 52 [SD 12]; 67 694 [56%] women). At recruitment, 22 670 (43%) men and 9490 (14%) women were current alcohol drinkers, with 15 433 (29%) men and 3054 (5%) women drinking at least weekly; most alcohol consumption was from rum. All-cause mortality was positively and continuously associated with weekly alcohol consumption: each additional 35cl bottle of rum per week (110g of pure alcohol) was associated with ∼10% higher risk of all-cause mortality (RR 1.08 [95%CI 1.05-1.11]). The major causes of excess mortality in weekly drinkers were cancer, vascular disease, and external causes. Non-drinkers had ∼10% higher risk (RR 1.11 [1.09-1.14]) of all-cause mortality than those in the lowest category of weekly alcohol consumption (<1 bottle/week), but this association was almost completely attenuated on exclusion of early follow-up.In this large prospective study in Cuba, weekly alcohol consumption was continuously related to premature mortality. Reverse causality is likely to account for much of the apparent excess risk among non-drinkers. The findings support limits to alcohol consumption that are lower than present recommendations in Cuba.Medical Research Council, British Heart Foundation, Cancer Research UK, CDC Foundation (with support from Amgen).

    View details for DOI 10.1016/j.eclinm.2020.100692

    View details for Web of Science ID 000645885100001

    View details for PubMedID 33768200

    View details for PubMedCentralID PMC7980059

  • Sex differences in prevalence, treatment and control of cardiovascular risk factors in England HEART Pinho-Gomes, A., Peters, S. E., Thomson, B., Woodward, M. 2021; 107 (6): 462-467

    Abstract

    To investigate sex differences in prevalence, treatment and control of major cardiovascular risk factors in England.Data from the Health Survey for England 2012-2017 on non-institutionalised English adults (aged ≥16 years) were used to investigate sex differences in prevalence, treatment and control of major cardiovascular risk factors: body mass index, smoking, systolic blood pressure and hypertension, diabetes, and cholesterol and dyslipidaemia. Physical activity and diet were not assessed in this study.Overall, 49 415 adults (51% women) were included. Sex differences persisted in prevalence of cardiovascular risk factors, with smoking, hypertension, overweight and dyslipidaemia remaining more common in men than in women in 2017. The proportion of individuals with neither hypertension, dyslipidaemia, diabetes nor smoking increased from 32% to 36% in women and from 28% to 29% in men between 2012 and 2017. Treatment and control of hypertension and diabetes improved over time and were comparable in both sexes in 2017 (66% and 51% for treatment and control of hypertension and 73% and 20% for treatment and control of diabetes). However, women were less likely than men to have treated and controlled dyslipidaemia (21% vs 28% for treatment and 15% vs 24% for control, for women versus men in 2017).Important sex differences persist in cardiovascular risk factors in England, with an overall higher number of risk factors in men than in women. A combination of public health policy and individually tailored interventions is required to further reduce the burden of cardiovascular disease in England.

    View details for DOI 10.1136/heartjnl-2020-317446

    View details for Web of Science ID 000625449100011

    View details for PubMedID 32887737

  • 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

  • Trends in the prevalence of overweight among Bangladeshi children aged 24-59 months (2004-2014) by sex and socioeconomic status INTERNATIONAL JOURNAL OF OBESITY Shawon, M., Hossain, F., Thomson, B., Adhikary, G., Chowdhury, A., Chowdhury, R., Townsend, N. 2020; 44 (3): 664-674

    Abstract

    While recent evidence suggests that the overall prevalence of overweight in young children in Bangladesh is low, little is known about variation in trends by sex, socioeconomic status, urbanicity, and region. We investigated the trends in overweight among children aged 24-59 months by these factors, using nationally representative samples from Bangladesh Demographic and Health Surveys (BDHS) between 2004 and 2014.Data from four BDHS surveys conducted between 2004 and 2014, with valid height and weight measurements of children, were included in this study (n = 15,648). BMI was calculated and the prevalence of overweight (including obesity) was reported using the International Obesity Taskforce (IOTF) classification system. To explore the association between socioeconomic status and childhood overweight, we used multivariable logistic regression.The overall prevalence of overweight among children aged 24-59 months increased from 1.60% (95% CI: 1.20-2.05%) in 2004 to 2.33% (95% CI: 1.82-2.76%) in 2014. Among girls, the overweight trend increased significantly (adjusted odds ratio (OR) comparing 2014 vs. 2004: 2.02 95% CI: 1.52-2.68), whereas among boys the trend remained steady. When compared with households with the poorest wealth index, households with richest wealth index had higher odds of childhood overweight among both boys (OR 2.39, 95% CI: 1.76-3.25) and girls (OR 1.86, 95% CI: 1.35-2.55). Higher household education level was also associated with childhood overweight. Subgroup analyses showed that relative inequalities by these factors increased between 2004 and 2014 when adjusted for potential confounders.There is a rising trend in overweight prevalence exclusively among girls aged 24-59 months in Bangladesh. Childhood overweight is associated with higher household education and wealth index, and the relative disparity by these factors appears to be increasing over time. These unmet inequalities should be considered while developing national public health programs and strategies.

    View details for DOI 10.1038/s41366-019-0507-9

    View details for Web of Science ID 000516908700013

    View details for PubMedID 31848457

  • Cohort Profile: the Cuba Prospective Study INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Armas Rojas, N., Lacey, B., Lewington, S., Varona Perez, P., Burrett, J., Morales Rigau, J., Sherliker, P., Boreham, J., Hernandez Lopez, O., Thomson, B., Achiong Estupinan, F., Diaz Gonzalez, M., Rosquete Munoz, N., Cendra Asencio, M., Emberson, J., Peto, R., Duenas Herrera, A. 2019; 48 (3): 680-+

    View details for DOI 10.1093/ije/dyy297

    View details for Web of Science ID 000486642400007

    View details for PubMedID 30796445

    View details for PubMedCentralID PMC6659378

  • The overweight and obesity transition from the wealthy to the poor in low- and middle-income countries: A survey of household data from 103 countries. PLoS medicine Templin, T. n., Cravo Oliveira Hashiguchi, T. n., Thomson, B. n., Dieleman, J. n., Bendavid, E. n. 2019; 16 (11): e1002968

    Abstract

    In high-income countries, obesity prevalence (body mass index greater than or equal to 30 kg/m2) is highest among the poor, while overweight (body mass index greater than or equal to 25 kg/m2) is prevalent across all wealth groups. In contrast, in low-income countries, the prevalence of overweight and obesity is higher among wealthier individuals than among poorer individuals. We characterize the transition of overweight and obesity from wealthier to poorer populations as countries develop, and project the burden of overweight and obesity among the poor for 103 countries.Our sample used 182 Demographic and Health Surveys and World Health Surveys (n = 2.24 million respondents) from 1995 to 2016. We created a standard wealth index using household assets common among all surveys and linked national wealth by country and year identifiers. We then estimated the changing probability of overweight and obesity across every wealth decile as countries' per capita gross domestic product (GDP) rises using logistic and linear fixed-effect regression models. We found that obesity rates among the wealthiest decile were relatively stable with increasing national wealth, and the changing gradient was largely due to increasing obesity prevalence among poorer populations (3.5% [95% uncertainty interval: 0.0%-8.3%] to 14.3% [9.7%-19.0%]). Overweight prevalence among the richest (45.0% [35.6%-54.4%]) and the poorest (45.5% [35.9%-55.0%]) were roughly equal in high-income settings. At $8,000 GDP per capita, the adjusted probability of being obese was no longer highest in the richest decile, and the same was true of overweight at $10,000. Above $25,000, individuals in the richest decile were less likely than those in the poorest decile to be obese, and the same was true of overweight at $50,000. We then projected overweight and obesity rates by wealth decile to 2040 for all countries to quantify the expected rise in prevalence in the relatively poor. Our projections indicated that, if past trends continued, the number of people who are poor and overweight will increase in our study countries by a median 84.4% (range 3.54%-383.4%), most prominently in low-income countries. The main limitations of this study included the inclusion of cross-sectional, self-reported data, possible reverse causality of overweight and obesity on wealth, and the lack of physical activity and food price data.Our findings indicate that as countries develop economically, overweight prevalence increased substantially among the poorest and stayed mostly unchanged among the wealthiest. The relative poor in upper- and lower-middle income countries may have the greatest burden, indicating important planning and targeting needs for national health programs.

    View details for DOI 10.1371/journal.pmed.1002968

    View details for PubMedID 31774821

  • Public knowledge of cardiovascular disease and response to acute cardiac events in three cities in China and India HEART Duber, H. C., McNellan, C. R., Wollum, A., Phillips, B., Allen, K., Brown, J. C., Bryant, M., Guptam, R. B., Li, Y., Majumdar, P., Roth, G. A., Thomson, B., Wilson, S., Woldeab, A., Zhou, M., Ng, M. 2018; 104 (1): 67-72

    Abstract

    To inform interventions targeted towards reducing mortality from acute myocardial infarction (AMI) and sudden cardiac arrest in three megacities in China and India, a baseline assessment of public knowledge, attitudes and practices was performed.A household survey, supplemented by focus group and individual interviews, was used to assess public understanding of cardiovascular disease (CVD) risk factors, AMI symptoms, cardiopulmonary resuscitation (CPR) and automated external defibrillators (AEDs). Additionally, information was collected on emergency service utilisation and associated barriers to care.5456 household surveys were completed. Hypertension was most commonly recognised among CVD risk factors in Beijing and Shanghai (68% and 67%, respectively), while behavioural risk factors were most commonly identified in Bangalore (smoking 91%; excessive alcohol consumption 64%). Chest pain/discomfort was reported by at least 60% of respondents in all cities as a symptom of AMI, but 21% of individuals in Bangalore could not name a single symptom. In Beijing, Shanghai and Bangalore, 26%, 15% and 3% of respondents were trained in CPR, respectively. Less than one-quarter of participants in all cities recognised an AED. Finally, emergency service utilisation rates were low, and many individuals expressed concern about the quality of prehospital care.Overall, we found low to modest knowledge of CVD risk factors and AMI symptoms, infrequent CPR training and little understanding of AEDs. Interventions will need to focus on basic principles of CVD and its complications in order for patients to receive timely and appropriate care for acute cardiac events.

    View details for DOI 10.1136/heartjnl-2017-311388

    View details for Web of Science ID 000417703500015

    View details for PubMedID 28663360

  • 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

  • Navigating Support, Resilience, and Care: Exploring the Impact of Informal Social Networks on the Rehabilitation and Care of Young Female Survivors of Sexual Violence in Northern Uganda PEACE AND CONFLICT-JOURNAL OF PEACE PSYCHOLOGY Stark, L., Landis, D., Thomson, B., Potts, A. 2016; 22 (3): 217-225

    View details for DOI 10.1037/pac0000162

    View details for Web of Science ID 000383593100004

  • Identifying High-Risk Neighborhoods Using Electronic Medical Records: A Population-Based Approach for Targeting Diabetes Prevention and Treatment Interventions PLOS ONE Gabert, R., Thomson, B., Gakidou, E., Roth, G. 2016; 11 (7): e0159227

    Abstract

    Increasing attention is being paid to the marked disparities in diabetes prevalence and health outcomes in the United States. There is a need to identify the small-area geographic variation in diabetes risk and related outcomes, a task that current health surveillance methods, which often rely on a self-reported diagnosis of diabetes, are not detailed enough to achieve. Broad adoption of electronic health records (EHR) and routine centralized reporting of patient-level data offers a new way to examine diabetes risk and highlight hotspots for intervention.We examined small-area geographic variation in hemoglobin A1c (HgbA1C) levels in three counties though a retrospective observational analysis of the complete population of diabetic patients receiving at least two ambulatory care visits for diabetes in three counties (two urban, one rural) in Minnesota in 2013, with clinical performance measures re-aggregated to patient home zip code area. Patient level performance measures included HgbA1c, blood pressure, low-density lipoprotein cholesterol and smoking. Diabetes care was provided to 63,053 patients out of a total population of 1.48 million people aged 18-74. Within each zip code area, on average 4.1% of the population received care for diabetes. There was significant and largely consistent geographic variation in the proportion of patients within their zip code area of residence attaining HgbA1C <8.0%, ranging from 59-90% of patients within each zip code area (interquartile range (IQR) 72.0%-78.1%). Attainment of performance measures for a zip code area were correlated with household income, educational attainment and insurance coverage for the same zip code area (all p < .001).We identified small geographic areas with the least effective control of diabetes. Centrally-aggregated EHR provides a new means of identifying and targeting at-risk neighborhoods for community-based interventions.

    View details for DOI 10.1371/journal.pone.0159227

    View details for Web of Science ID 000381515900031

    View details for PubMedID 27463641

    View details for PubMedCentralID PMC4963128

  • A novel method for estimating distributions of body mass index POPULATION HEALTH METRICS Ng, M., Liu, P., Thomson, B., Murray, C. L. 2016; 14: 6

    Abstract

    Understanding trends in the distribution of body mass index (BMI) is a critical aspect of monitoring the global overweight and obesity epidemic. Conventional population health metrics often only focus on estimating and reporting the mean BMI and the prevalence of overweight and obesity, which do not fully characterize the distribution of BMI. In this study, we propose a novel method which allows for the estimation of the entire distribution.The proposed method utilizes the optimization algorithm, L-BFGS-B, to derive the distribution of BMI from three commonly available population health statistics: mean BMI, prevalence of overweight, and prevalence of obesity. We conducted a series of simulations to examine the properties, accuracy, and robustness of the method. We then illustrated the practical application of the method by applying it to the 2011-2012 US National Health and Nutrition Examination Survey (NHANES).Our method performed satisfactorily across various simulation scenarios yielding empirical (estimated) distributions which aligned closely with the true distributions. Application of the method to the NHANES data also showed a high level of consistency between the empirical and true distributions. In situations where there were considerable outliers, the method was less satisfactory at capturing the extreme values. Nevertheless, it remained accurate at estimating the central tendency and quintiles.The proposed method offers a tool that can efficiently estimate the entire distribution of BMI. The ability to track the distributions of BMI will improve our capacity to capture changes in the severity of overweight and obesity and enable us to better monitor the epidemic.

    View details for DOI 10.1186/s12963-016-0076-2

    View details for Web of Science ID 000371767500002

    View details for PubMedID 26973438

    View details for PubMedCentralID PMC4789291

  • Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013 LANCET Forouzanfar, M. H., Alexander, L., Anderson, H. R., Bachman, V. F., Biryukov, S., Brauer, M., Burnett, R., Casey, D., Coates, M. M., Cohen, A., Delwiche, K., Estep, K., Frostad, J. J., Astha, K. C., Kyu, H. H., Moradi-Lakeh, M., Ng, M., Slepak, E. L., Thomas, B. A., Wagner, J., Aasvang, G. M., Abbafati, C., Ozgoren, A. A., Abd-Allah, F., Abera, S. F., Aboyans, V., Abraham, B., Abraham, J. P., Abubakar, I., Abu-Rmeileh, N. M., Aburto, T. C., Achoki, T., Adelekan, A., Adofo, K., Adou, A. K., Adsuar, J. C., Afshin, A., Agardh, E. E., Al Khabouri, M. J., Al Lami, F. H., Alam, S. S., Alasfoor, D., Albittar, M. I., Alegretti, M. A., Aleman, A. V., Alemu, Z. A., Alfonso-Cristancho, R., Alhabib, S., Ali, R., Ali, M. K., Alla, F., Allebeck, P., Allen, P. J., Alsharif, U., Alvarez, E., Alvis-Guzman, N., Amankwaa, A. A., Amare, A. T., Ameh, E. A., Ameli, O., Amini, H., Ammar, W., Anderson, B. O., Antonio, C. A., Anwari, P., Cunningham, S. A., Arnlov, J., Arsenijevic, V. S., Artaman, A., Asghar, R. J., Assadi, R., Atkins, L. S., Atkinson, C., Avila, M. A., Awuah, B., Badawi, A., Bahit, M. C., Bakfalouni, T., Balakrishnan, K., Balalla, S., Balu, R. K., Banerjee, A., Barber, R. M., Barker-Collo, S. L., Barquera, S., Barregard, L., Barrero, L. H., Barrientos-Gutierrez, T., Basto-Abreu, A. C., Basu, A., Basu, S., Basulaiman, M. O., Ruvalcaba, C. B., Beardsley, J., Bedi, N., Bekele, T., Bell, M. L., Benjet, C., Bennett, D. A., Benzian, H., Bernabe, E., Beyene, T. J., Bhala, N., Bhalla, A., Bhutta, Z. Q., Bikbov, B., Bin Abdulhak, A. A., Blore, J. D., Blyth, F. M., Bohensky, M. A., Basara, B. B., Borges, G., Bornstein, N. M., Bose, D., Boufous, S., Bourne, R. R., Brainin, M., Brazinova, A., Breitborde, N. J., Brenner, H., Briggs, A. D., Broday, D. M., Brooks, P. M., Bruce, N. G., Brugha, T. S., Brunekreef, B., Buchbinder, R., Bui, L. N., Bukhman, G., Bulloch, A. G., Burch, M., Burney, P. G., Campos-Nonato, I. R., Campuzano, J. C., Cantoral, A. J., Caravanos, J., Cardenas, R., Cardis, E., Carpenter, D. O., Caso, V., Castaneda-Orjuela, C. A., Castro, R. E., Catala-Lopez, F., Cavalleri, F., Cavlin, A., Chadha, V. K., Chang, J., Charlson, F. J., Chen, H., Chen, W., Chen, Z., Chiang, P. P., Chimed-Ochir, O., Chowdhury, R., Christophi, C. A., Chuang, T., Chugh, S. S., Cirillo, M., Classen, T. K., Colistro, V., Colomar, M., Colquhoun, S. M., Contreras, A. G., Cooper, C., Cooperrider, K., Cooper, L. T., Coresh, J., Courville, K. J., Criqui, M. H., Cuevas-Nasu, L., Damsere-Derry, J., Danawi, H., Dandona, L., Dandona, R., Dargan, P. I., Davis, A., Davitoiu, D. V., Dayama, A., de Castro, E. F., De la Cruz-Gongora, V., De Leo, D., de Lima, G., Degenhardt, L., Del Pozo-Cruz, B., Dellavalle, R. P., Deribe, K., Derrett, S., Jarlais, D. C., Dessalegn, M., deVeber, G. A., Devries, K. M., Dharmaratne, S. D., Dherani, M. K., Dicker, D., Ding, E. L., Dokova, K., Dorsey, E. R., Driscoll, T. R., Duan, L., Durrani, A. M., Ebel, B. E., Ellenbogen, R. G., Elshrek, Y. M., Endres, M., Ermakov, S. P., Erskine, H. E., Eshrati, B., Esteghamati, A., Fahimi, S., Faraon, E. J., Farzadfar, F., Fay, D. F., Feigin, V. L., Feigl, A. B., Fereshtehnejad, S., Ferrari, A. J., Ferri, C. P., Flaxman, A. D., Fleming, T. D., Foigt, N., Foreman, K. J., Paleo, U. F., Franklin, R. C., Gabbe, B., Gaffikin, L., Gakidou, E., Gamkrelidze, A., Gankpe, F. G., Gansevoort, R. T., Garcia-Guerra, F. A., Gasana, E., Geleijnse, J. M., Gessner, B. D., Gething, P., Gibney, K. B., Gillum, R. F., Ginawi, I. A., Giroud, M., Giussani, G., Goenka, S., Goginashvili, K., Dantes, H. G., Gona, P., de Cosio, T. G., Gonzalez-Castell, D., Gotay, C. C., Goto, A., Gouda, H. N., Guerrant, R. L., Gugnani, H. C., Guillemin, F., Gunnell, D., Gupta, R., Gupta, R., Gutierrez, R. A., Hafezi-Nejad, N., Hagan, H., Hagstromer, M., Halasa, Y. A., Hamadeh, R. R., Hammami, M., Hankey, G. J., Hao, Y., Harb, H. L., Haregu, T. N., Haro, J. M., Havmoeller, R., Hay, S. I., Hedayati, M. T., Heredia-Pi, I. B., Hernandez, L., Heuton, K. R., Heydarpour, P., Hijar, M., Hoek, H. W., Man, H. J., Hornberger, J. C., Hosgood, H. D., Hoy, D. G., Hsairi, M., Hu, G., Hu, H., Huang, C., Huang, J. J., Hubbell, B. J., Huiart, L., Husseini, A., Iannarone, M. L., Iburg, K. M., Idrisov, B. T., Ikeda, N., Innos, K., Inoue, M., Islami, F., Ismayilova, S., Jacobsen, K. H., Jansen, H. A., Jarvis, D. L., Jassal, S. K., Jauregui, A., Jayaraman, S., Jeemon, P., Jensen, P. N., Jha, V., Jiang, F., Jiang, G., Jiang, Y., Jonas, J. B., Juel, K., Kan, H., Roseline, S. S., Karam, N. E., Karch, A., Karema, C. K., Karthikeyan, G., Kaul, A., Kawakami, N., Kazi, D. S., Kemp, A. H., Kengne, A. P., Keren, A., Khader, Y. S., Khalifa, S. E., Khan, E. A., Khang, Y., Khatibzadeh, S., Khonelidze, I., Kieling, C., Kim, D., Kim, S., Kim, Y., Kimokoti, R. W., Kinfu, Y., Kinge, J. M., Kissela, B. M., Kivipelto, M., Knibbs, L. D., Knudsen, A. K., Kokubo, Y., Kose, M. R., Kosen, S., Kraemer, A., Kravchenko, M., Krishnaswami, S., Kromhout, H., Ku, T., Defo, B. K., Bicer, B. K., Kuipers, E. J., Kulkarni, C., Kulkarni, V. S., Kumar, G. A., Kwan, G. F., Lai, T., Balaji, A. L., Lalloo, R., Lallukka, T., Lam, H., Lan, Q., Lansingh, V. C., Larson, H. J., Larsson, A., Laryea, D. O., Lavados, P. M., Lawrynowicz, A. E., Leasher, J. L., Lee, J., Leigh, J., Leung, R., Levi, M., Li, Y., Li, Y., Liang, J., Liang, X., Lim, S. S., Lindsay, M. P., Lipshultz, S. E., Liu, S., Liu, Y., Lloyd, B. K., Logroscino, G., London, S. J., Lopez, N., Lortet-Tieulent, J., Lotufo, P. A., Lozano, R., Lunevicius, R., Ma, J., Ma, S., Machado, V. M., MacIntyre, M. F., Magis-Rodriguez, C., Mahdi, A. A., Majdan, M., Malekzadeh, R., Mangalam, S., Mapoma, C. C., Marape, M., Marcenes, W., Margolis, D. J., Margono, C., Marks, G. B., Martin, R. V., Marzan, M. B., Mashal, M. T., Masiye, F., Mason-Jones, A. J., Matsushita, K., Matzopoulos, R., Mayosi, B. M., Mazorodze, T. T., Mckay, A. C., McKee, M., McLain, A., Meaney, P. A., Medina, C., Mehndiratta, M. M., Mejia-Rodriguez, F., Mekonnen, W., Melaku, Y. A., Meltzer, M., Memish, Z. A., Mendoza, W., Mensah, G. A., Meretoja, A., Mhimbira, F. A., Micha, R., Miller, T. R., Mills, E. J., Misganaw, A., Mishra, S., Ibrahim, N. M., Mohammad, K. A., Mokdad, A. H., Mola, G. L., Monasta, L., Hernandez, J. C., Montico, M., Moore, A. R., Morawska, L., Mori, R., Moschandreas, J., Moturi, W. N., Arian, D. M., Mueller, U. O., Mukaigawara, M., Mullany, E. C., Murthy, K. S., Naghavi, M., Nahas, Z., Naheed, A., Naidoo, K. S., Naldi, L., Nand, D., Nangia, V., Narayan, K. M., Nash, D., Neal, B., Nejjari, C., Neupane, S. P., Newton, C. R., Ngalesoni, F. N., Ngirabega, J. d., Nguyen, G., Nguyen, N. T., Nieuwenhuijsen, M. J., Nisar, M. I., Nogueira, J. R., Nolla, J. M., Nolte, S., Norheim, O. F., Norman, R. E., Norrving, B., Nyakarahuka, L., Oh, I., Ohkubo, T., Olusanya, B. O., Omer, S. B., Opio, J. N., Orozco, R., Pagcatipunan, R. S., Pain, A. W., Pandian, J. D., Panelo, C. I., Papachristou, C., Park, E., Parry, C. D., Caicedo, A. J., Patten, S. B., Paul, V. K., Pavlin, B. I., Pearce, N., Pedraza, L. S., Pedroza, A., Stokic, L. P., Pekericli, A., Pereira, D. M., Perez-Padilla, R., Perez-Ruiz, F., Perico, N., Perry, S. A., Pervaiz, A., Pesudovs, K., Peterson, C. B., Petzold, M., Phillips, M. R., Phua, H. P., Plass, D., Poenaru, D., Polanczyk, G. V., Polinder, S., Pond, C. D., Pope, C. A., Pope, D., Popova, S., Pourmalek, F., Powles, J., Prabhakaran, D., Prasad, N. M., Qato, D. M., Quezada, A. D., Quistberg, D. A., Racape, L., Rafay, A., Rahimi, K., Rahimi-Movaghar, V., Rahman, S. u., Raju, M., Rakovac, I., Rana, S. M., Rao, M., Razavi, H., Reddy, K. S., Refaat, A. H., Rehm, J., Remuzzi, G., Ribeiro, A. L., Riccio, P. M., Richardson, L., Riederer, A., Robinson, M., Roca, A., Rodriguez, A., Rojas-Rueda, D., Romieu, I., Ronfani, L., Room, R., Roy, N., Ruhago, G. M., Rushton, L., Sabin, N., Sacco, R. L., Saha, S., Sahathevan, R., Sahraian, M. A., Salomon, J. A., Salvo, D., Sampson, U. K., Sanabria, J. R., Sanchez, L. M., Sanchez-Pimienta, T. G., Sanchez-Riera, L., Sandar, L., Santos, I. S., Sapkota, A., Satpathy, M., Saunders, J. E., Sawhney, M., Saylan, M. I., Scarborough, P., Schmidt, J. C., Schneider, I. J., Schoettker, B., Schwebel, D. C., Scott, J. G., Seedat, S., Sepanlou, S. G., Serdar, B., Servan-Mori, E. E., Shaddick, G., Shahraz, S., Levy, T. S., Shangguan, S., She, J., Sheikhbahaei, S., Shibuya, K., Shin, H. H., Shinohara, Y., Shiri, R., Shishani, K., Shiue, I., Sigfusdottir, I. D., Silberberg, D. H., Simard, E. P., Sindi, S., Singh, A., Singh, G. M., Singh, J. A., Skirbekk, V., Sliwa, K., Soljak, M., Soneji, S., Soreide, K., Soshnikov, S., Sposato, L. A., Sreeramareddy, C. T., Stapelberg, N. J., Stathopoulou, V., Steckling, N., Stein, D. J., Stein, M. B., Stephens, N., Stoeckl, H., Straif, K., Stroumpoulis, K., Sturua, L., Sunguya, B. F., Swaminathan, S., Swaroop, M., Sykes, B. L., Tabb, K. M., Takahashi, K., Talongwa, R. T., Tandon, N., Tanne, D., Tanner, M., Tavakkoli, M., Ao, B. J., Teixeira, C. M., Rojo, M. M., Terkawi, A. S., Texcalac-Sangrador, J. L., Thackway, S. V., Thomson, B., Thorne-Lyman, A. L., Thrift, A. G., Thurston, G. D., Tillmann, T., Tobollik, M., Tonelli, M., Topouzis, F., Towbin, J. R., Toyoshima, H., Traebert, J. E., Tran, B. X., Trasande, L., Trillini, M., Trujillo, U., Dimbuene, Z. T., Tsilimbaris, M., Tuzcu, E. M., Uchendu, U. S., Ukwaja, K. N., Uzun, S. B., van de Vijver, S., Van Dingenen, R., van Gool, C. H., van Os, J., Varakin, Y. Y., Vasankari, T. J., Vasconcelos, A. M., Vavilala, M. S., Veerman, L. J., Velasquez-Melendez, G., Venketasubramanian, N., Vijayakumar, L., Villalpando, S., Violante, F. S., Vlassov, V. V., Vollset, S. E., Wagner, G. R., Waller, S. G., Wallin, M. T., Wan, X., Wang, H., Wang, J., Wang, L., Wang, W., Wang, Y., Warouw, T. S., Watts, C. H., Weichenthal, S., Weiderpass, E., Weintraub, R. G., Werdecker, A., Wessells, K. R., Westerman, R., Whiteford, H. A., Wilkinson, J. D., Williams, H. C., Williams, T. N., Woldeyohannes, S. M., Wolfe, C. D., Wong, J. Q., Woolf, A. D., Wright, J. L., Wurtz, B., Xu, G., Yan, L. L., Yang, G., Yano, Y., Ye, P., Yenesew, M., Yentuer, G. K., Yip, P., Yonemoto, N., Yoon, S., Younis, M. Z., Younoussi, Z., Yu, C., Zaki, M. E., Zhao, Y., Zheng, Y., Zhou, M., Zhu, J., Zhu, S., Zou, X., Zunt, J. R., Lopez, A. D., Vos, T., Murray, C. J. 2015; 386 (10010): 2287-2323

    Abstract

    The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol.All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa.Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.Bill & Melinda Gates Foundation.

    View details for DOI 10.1016/S0140-6736(15)00128-2

    View details for Web of Science ID 000365993200031

    View details for PubMedCentralID PMC4685753

  • Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition LANCET Murray, C. J., Barber, R. M., Foreman, K. J., Ozgoren, A. A., Abd-Allah, F., Abera, S. F., Aboyans, V., Abraham, J. P., Abubakar, I., Abu-Raddad, L. J., Abu-Rmeileh, N. M., Achoki, T., Ackerman, I. N., Ademi, Z., Adou, A. K., Adsuar, J. C., Afshin, A., Agardh, E. E., Alam, S. S., Alasfoor, D., Albittar, M. I., Alegretti, M. A., Alemu, Z. A., Alfonso-Cristancho, R., Alhabib, S., Ali, R., Alla, F., Allebeck, P., AlMazroa, M. A., Alsharif, U., Alvarez, E., Alvis-Guzman, N., Amare, A. T., Ameh, E. A., Amini, H., Ammar, W., Anderson, H. R., Anderson, B. O., Antonio, C. A., Anwari, P., Arnlov, J., Arsenijevic, V. S., Artaman, A., Asghar, R. J., Assadi, R., Atkins, L. S., Avila, M. A., Awuah, B., Bachman, V. F., Badawi, A., Bahit, M. C., Balakrishnan, K., Banerjee, A., Barker-Collo, S. L., Barquera, S., Barregard, L., Barrero, L. H., Basu, A., Basu, S., Basulaiman, M. O., Beardsley, J., Bedi, N., Beghi, E., Bekele, T., Bell, M. L., Benjet, C., Bennett, D. A., Bensenor, I. M., Benzian, H., Bernabe, E., Bertozzi-Villa, A., Beyene, T. J., Bhala, N., Bhalla, A., Bhutta, Z. A., Bienhoff, K., Bikbov, B., Biryukov, S., Blore, J. D., Blosser, C. D., Blyth, F. M., Bohensky, M. A., Bolliger, I. W., Basara, B. B., Bornstein, N. M., Bose, D., Boufous, S., Bourne, R. R., Boyers, L. N., Brainin, M., Brayne, C. E., Brazinova, A., Breitborde, N. J., Brenner, H., Briggs, A. D., Brooks, P. M., Brown, J. C., Brugha, T. S., Buchbinder, R., Buckle, G. C., Budke, C. M., Bulchis, A., Bulloch, A. G., Campos-Nonato, I. R., Carabin, H., Carapetis, J. R., Cardenas, R., Carpenter, D. O., Caso, V., Castaneda-Orjuela, C. A., Castro, R. E., Catala-Lopez, F., Cavalleri, F., Cavlin, A., Chadha, V. K., Chang, J., Charlson, F. J., Chen, H., Chen, W., Chiang, P. P., Chimed-Ochir, O., Chowdhury, R., Christensen, H., Christophi, C. A., Cirillo, M., Coates, M. M., Coffeng, L. E., Coggeshall, M. S., Colistro, V., Colquhoun, S. M., Cooke, G. S., Cooper, C., Cooper, L. T., Coppola, L. M., Cortinovis, M., Criqui, M. H., Crump, J. A., Cuevas-Nasu, L., Danawi, H., Dandona, L., Dandona, R., Dansereau, E., Dargan, P. I., Davey, G., Davis, A., Davitoiu, D. V., Dayama, A., De Leo, D., Degenhardt, L., Del Pozo-Cruz, B., Dellavalle, R. P., Deribe, K., Derrett, S., Des Jarlais, D. C., Dessalegn, M., Dharmaratne, S. D., Dherani, M. K., Diaz-Torne, C., Dicker, D., Ding, E. L., Dokova, K., Dorsey, E. R., Driscoll, T. R., Duan, L., Duber, H. C., Ebel, B. E., Edmond, K. M., Elshrek, Y. M., Endres, M., Ermakov, S. P., Erskine, H. E., Eshrati, B., Esteghamati, A., Estep, K., Faraon, E. J., Farzadfar, F., Fay, D. F., Feigin, V. L., Felson, D. T., Fereshtehnejad, S., Fernandes, J. G., Ferrari, A. J., Fitzmaurice, C., Flaxman, A. D., Fleming, T. D., Foigt, N., Forouzanfar, M. H., Fowkes, F. G., Paleo, U. F., Franklin, R. C., Fuerst, T., Gabbe, B., Gaffikin, L., Gankpe, F. G., Geleijnse, J. M., Gessner, B. D., Gething, P., Gibney, K. B., Giroud, M., Giussani, G., Gomez Dantes, H., Gona, P., Gonzalez-Medina, D., Gosselin, R. A., Gotay, C. C., Goto, A., Gouda, H. N., Graetz, N., Gugnani, H. C., Gupta, R., Gupta, R., Gutierrez, R. A., Haagsma, J., Hafezi-Nejad, N., Hagan, H., Halasa, Y. A., Hamadeh, R. R., Hamavid, H., Hammami, M., Hancock, J., Hankey, G. J., Hansen, G. M., Hao, Y., Harb, H. L., Maria Haro, J., Havmoeller, R., Hay, S. I., Hay, R. J., Heredia-Pi, I. B., Heuton, K. R., Heydarpour, P., Higashi, H., Hijar, M., Hoek, H. W., Hoffman, H. J., Hosgood, H. D., Hossain, M., Hotez, P. J., Hoy, D. G., Hsairi, M., Hu, G., Huang, C., Huang, J. J., Husseini, A., Huynh, C., Iannarone, M. L., Iburg, K. M., Innos, K., Inoue, M., Islami, F., Jacobsen, K. H., Jarvis, D. L., Jassal, S. K., Jee, S. H., Jeemon, P., Jensen, P. N., Jha, V., Jiang, G., Jiang, Y., Jonas, J. B., Juel, K., Kan, H., Karch, A., Karema, C. K., Karimkhani, C., Karthikeyan, G., Kassebaum, N. J., Kaul, A., Kawakami, N., Kazanjan, K., Kemp, A. H., Kengne, A. P., Keren, A., Khader, Y. S., Khalifa, S. E., Khan, E. A., Khan, G., Khang, Y., Kieling, C., Kim, D., Kim, S., Kim, Y., Kinfu, Y., Kinge, J. M., Kivipelto, M., Knibbs, L. D., Knudsen, A. K., Kokubo, Y., Kosen, S., Krishnaswami, S., Defo, B. K., Bicer, B. K., Kuipers, E. J., Kulkarni, C., Kulkarni, V. S., Kumar, G. A., Kyu, H. H., Lai, T., Lalloo, R., Lallukka, T., Lam, H., Lan, Q., Lansingh, V. C., Larsson, A., Lawrynowicz, A. E., Leasher, J. L., Leigh, J., Leung, R., Levitz, C. E., Li, B., Li, Y., Li, Y., Lim, S. S., Lind, M., Lipshultz, S. E., Liu, S., Liu, Y., Lloyd, B. K., Lofgren, K. T., Logroscino, G., Looker, K. J., Lortet-Tieulent, J., Lotufo, P. A., Lozano, R., Lucas, R. M., Lunevicius, R., Lyons, R. A., Ma, S., MacIntyre, M. F., Mackay, M. 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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.

    View details for DOI 10.1016/S0140-6736(15)61340-X

    View details for Web of Science ID 000365992600030

    View details for PubMedCentralID PMC5388903