County-Level Factors Associated With Cardiovascular Mortality by Race/Ethnicity.
Journal of the American Heart Association
Background Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity-specific CVD mortality and county-level factors. Methods and Results Using 2017 county-level data, we studied the association between race/ethnicity-specific CVD age-adjusted mortality rate (AAMR) and county-level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors; R2 values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals). There were 659740 CVD deaths among non-Hispanic White individuals in 2698 counties; 100475 deaths among non-Hispanic Black individuals in 717 counties; and 49493 deaths among Hispanic/Latinx individuals across 267 counties. Non-Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (R2) in CVD AAMR was explained by physical inactivity for non-Hispanic White individuals (32.3%), median household income for non-Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county-level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non-Hispanic White individuals (35.3%), socioeconomic factors for non-Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%). Conclusions The associations between race/ethnicity-specific age-adjusted CVD mortality and county-level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.
View details for DOI 10.1161/JAHA.120.018835
View details for PubMedID 33653083
Multimethod, multidataset analysis reveals paradoxical relationships between sociodemographic factors, Hispanic ethnicity and diabetes.
BMJ open diabetes research & care
2020; 8 (2)
INTRODUCTION: Population-level and individual-level analyses have strengths and limitations as do 'blackbox' machine learning (ML) and traditional, interpretable models. Diabetes mellitus (DM) is a leading cause of morbidity and mortality with complex sociodemographic dynamics that have not been analyzed in a way that leverages population-level and individual-level data as well as traditional epidemiological and ML models. We analyzed complementary individual-level and county-level datasets with both regression and ML methods to study the association between sociodemographic factors and DM.RESEARCH DESIGN AND METHODS: County-level DM prevalence, demographics, and socioeconomic status (SES) factors were extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings and merged with US Census data. Analogous individual-level data were extracted from 2007 to 2016 National Health and Nutrition Examination Survey studies and corrected for oversampling with survey weights. We used multivariate linear (logistic) regression and ML regression (classification) models for county (individual) data. Regression and ML models were compared using measures of explained variation (area under the receiver operating characteristic curve (AUC) and R2).RESULTS: Among the 3138 counties assessed, the mean DM prevalence was 11.4% (range: 3.0%-21.1%). Among the 12824 individuals assessed, 1688 met DM criteria (13.2% unweighted; 10.2% weighted). Age, gender, race/ethnicity, income, and education were associated with DM at the county and individual levels. Higher county Hispanic ethnic density was negatively associated with county DM prevalence, while Hispanic ethnicity was positively associated with individual DM. ML outperformed regression in both datasets (mean R2 of 0.679 vs 0.610, respectively (p<0.001) for county-level data; mean AUC of 0.737 vs 0.727 (p<0.0427) for individual-level data).CONCLUSIONS: Hispanic individuals are at higher risk of DM, while counties with larger Hispanic populations have lower DM prevalence. Analyses of population-level and individual-level data with multiple methods may afford more confidence in results and identify areas for further study.
View details for DOI 10.1136/bmjdrc-2020-001725
View details for PubMedID 33229378
- The Hispanic paradox in the prevalence of obesity at the county-level OBESITY SCIENCE & PRACTICE 2020
COUNTY-LEVEL FACTORS ASSOCIATED WITH CARDIOVASCULAR MORTALITY DISAGGREGATED BY RACE/ETHNICITY
ELSEVIER SCIENCE INC. 2020: 1884
View details for Web of Science ID 000522979101871
Prolonged Expression of a Putative Invertase Inhibitor in Micropylar Endosperm Suppressed Embryo Growth in Arabidopsis
FRONTIERS IN PLANT SCIENCE
2018; 9: 61
Proper seed development requires coordinated growth among the three genetically distinct components, the embryo, the endosperm, and the seed coat. In Arabidopsis, embryo growth rate accelerates after endosperm cellularization, which requires a chromatin-remodeling complex, the FIS2-Polycomb Repressive Complex 2 (PRC2). After cellularization, the endosperm ceases to grow and is eventually absorbed by the embryo. This sequential growth pattern displayed by the endosperm and the embryo suggests a possibility that the supply of sugar might be shifted from the endosperm to the embryo upon endosperm cellularization. Since invertases and invertase inhibitors play an important role in sugar partition, we investigated their expression pattern during early stages of seed development in Arabidopsis. Two putative invertase inhibitors (InvINH1 and InvINH2) were identified as being preferentially expressed in the micropylar endosperm that surrounds the embryo. After endosperm cellularization, InvINH1 and InvINH2 were down-regulated in a FIS2-dependent manner. We hypothesized that FIS2-PRC2 complex either directly or indirectly represses InvINH1 and InvINH2 to increase invertase activity around the embryo, making more hexose available to support the accelerated embryo growth after endosperm cellularization. In support of our hypothesis, embryo growth was delayed in transgenic lines that ectopically expressed InvINH1 in the cellularized endosperm. Our data suggested a novel mechanism for the FIS2-PRC2 complex to control embryo growth rate via the regulation of invertase activity in the endosperm.
View details for DOI 10.3389/fpls.2018.00061
View details for Web of Science ID 000423533500001
View details for PubMedID 29441087
View details for PubMedCentralID PMC5797552