School Segregation During Adolescence is Associated with Higher 30-Year Cardiovascular Risk of Black but not White Young Adults.

Although cardiovascular disease (CVD) mortality rates are declining for American adults, a disparity remains between non-Hispanic Black and non-Hispanic White adults. Previous research has shown that residential segregation, a form of structural racism, experienced in childhood is associated with later-life racial and ethnic health disparities, including disparities in CVD and its risk factors. However, little is known about the health consequences of exposure to segregated schools, especially among those living in neighborhoods with high concentrations of minoritized people. This study used data from the In-School, Wave I, and Wave IV surveys of the National Longitudinal Study of Adolescent to Adult Health to examine a novel school measure of school racial segregation (Index of the Concentration of Extremes, ICE) as a predictor of Framingham 30-year CVD risk scores. We used General Estimating Equation models to evaluate the association between ICE, measured at Wave I, and two different 30-year CVD risk scores, measured at Wave IV, and examined whether the relationship varied by race. We observed that higher levels of school segregation were associated with a higher 30-year CVD risk among non-Hispanic Black participants while higher segregation was associated with a lower 30-year CVD risk for non-Hispanic White participants. This research suggests that exposure to segregation in the school setting may contribute to observed disparities in CVD among US adults.

Associations between historical and contemporary measures of structural racism and leukocyte telomere length: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: We assessed the link between two manifestations of structural racism-historical redlining and contemporary racial residential segregation-and baseline and 10-year changes in leukocyte telomere length (LTL). METHODS: We used data on Black and Hispanic/Latinx participants from Exams I and V of the Multi-Ethnic Study of Atherosclerosis Stress Ancillary Study (N = 741, age range = 45-84 years). LTL was defined as the ratio of telomeric DNA to a single copy gene (T/S), and 10-year changes were adjusted for regression to the mean. We used 1930s Home Owners' Loan Corporation maps to assign three historical redlining grades (A&B: best/still desirable, C: declining, D: hazardous/redlined) to participants' neighborhoods (census-tracts) at baseline. The Getis-Ord Gi∗ statistic was used to evaluate census-tract level baseline residential segregation (low/moderate/high). RESULTS: In mixed-effects regression models accounting for neighborhood clustering, individual characteristics, and current neighborhood environments, those living in highly segregated Black neighborhoods had 0.08 shorter baseline LTL (95% CI: -0.13, -0.04), than those residing in the least segregated neighborhoods. We did not find a relationship between residing in segregated neighborhoods and 10-year LTL changes, and associations between residing in historically redlined neighborhoods and both baseline LTL and 10-year changes in LTL were null. Across discriminatory disinvestment trajectories examined, individuals residing in highly segregated but non-redlined neighborhoods had 0.6 shorter baseline LTL than individuals residing in non-redlined neighborhoods with low/moderate segregation (95% CI: -0.12, -0.01). CONCLUSIONS: Our results highlight the impact of racial segregation on cellular aging and underscore the need to ameliorate structural inequities within segregated neighborhoods.

A data harmonization project of three large prospective cardiovascular health-focused cohorts.

Few prospective studies examine multilevel resilience resources and psychosocial factors in relation to cardiovascular health and disease. Recent research indicates that resilience resources are associated with a reduction in the incidence of cardiovascular disease-related events, but few studies have examined this relationship across different racial/ethnic populations or in large cohorts. Harmonization may address these limitations because it allows data from several cohorts to be analyzed together, potentially increasing sample size and in turn power overall and in minority populations. This paper describes the process involved in combining three cardiovascular health-focused cohorts: Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, and Mediators of Atherosclerosis in South Asians Living in America Study. Using a systematic process, we identified appropriate data harmonization techniques to use in harmonizing variables across cohorts. Variables included exposures (e.g., resilience resources), outcomes (e.g., American Heart Association's Life's Simple 7), and covariates (e.g., race and ethnicity). Post harmonization examinations included psychometric analyses of the harmonized variables. A total of 13,284 participants were included in the final harmonized dataset. This project provides opportunities for future research in resilience resources and informs future studies that need to harmonize data. Results based on the harmonized dataset could inform interventions and policies.

Racial and Ethnic Differences in Emotional Reactions to the Flint Water Crisis among Michigan Women in Communities Outside of Flint.

Objective: To determine whether Black women in Michigan communities outside of Flint were more likely than women in other racial and ethnic groups to report negative emotional reactions to the Flint Water Crisis, an ongoing public health disaster that has been widely attributed to anti-Black structural racism. Methods: Data were from a 2020 survey of Michigan women aged 18-45 in communities outside of Flint (N=888). We used logistic regression models to examine racial and ethnic differences in the odds of negative emotional reactions to the Flint Water Crisis. Results: Compared with Black women, White women had lower odds of feeling scared (odds ratio [OR]=0.58; 95% CI, 0.40-0.84), hopeless (OR=0.53; 95% CI, 0.38-0.74), tired (OR=0.45; 95% CI, 0.32-0.64), and numb (OR=0.52; 95% CI, 0.35-0.75) when thinking about the water crisis. There were no differences between Black and Hispanic women, whereas women of other races or ethnicities had lower odds than Black women of feeling numb (OR=0.32; 95% CI, 0.14-0.72). Conclusions: The Flint Water Crisis was a racialized stressor, with potential implications for mental health inequities among Michigan women who were not directly affected by the crisis.

Could differential under-reporting of loneliness between men and women bias the gender-specific association between loneliness duration and rate of memory decline? A probabilistic bias analysis of effect modification.

Gender is an observed effect modifier of the association between loneliness and memory aging. However, this effect modification may be a result of information bias due to differential loneliness under-reporting by gender. We applied probabilistic bias analyses to examine whether effect modification of the loneliness-memory decline relationship by gender is retained under three simulation scenarios with various magnitudes of differential loneliness under-reporting between men and women. Data were from biennial interviews with adults aged 50+ in the US Health and Retirement Study from 1996-2016 (5,646 women and 3,386 men). Loneliness status (yes vs. no) was measured from 1996-2004 using the CES-D loneliness item and memory was measured from 2004-2016. Simulated sensitivity and specificity of the loneliness measure were informed by a validation study using the UCLA Loneliness Scale as a gold standard. The likelihood of observing effect modification by gender was higher than 90% in all simulations, although the likelihood reduced with an increasing difference in magnitude of the loneliness under-reporting between men and women. The gender difference in loneliness under-reporting did not meaningfully affect the observed effect modification by gender in our simulations. Our simulation approach may be promising to quantify potential information bias in effect modification analyses.

Exposure to structural racism-related state laws is associated with worse cardiovascular health among US adults, BRFSS 2011 and 2013.

The objective of this study was to determine whether exposure to structural racism-related state laws is associated with cardiovascular health among a racially and ethnically diverse sample of US adults. Data were from the Database of Structural Racism-Related State Laws and the Behavioral Risk Factor Surveillance System (BRFSS). The sample included 958,019 BRFSS 2011 and 2013 respondents aged 18+ from all 50 US states. The exposure was a summary index of 22 state laws related to the criminal legal system, economics and labor, education, healthcare, housing, immigration, and political participation. The outcome was the American Heart Association's Life's Simple 7 (LS7), a summary index of seven cardiovascular health indicators. Linear regression models included fixed effects for year and state to control for time trends and unmeasured time-invariant state-level contextual factors. In the full sample, a one standard deviation increase in the structural racism state legal index was associated with a 0.06-unit decrease in the LS7 (b=-0.06; 95% CI:-0.09, 0.02; p=0.001), controlling for individual- and state-level covariates. Contrary to expectations, stratified models revealed no statistically significant differences by race and ethnicity in the association between the structural racism state legal index and the LS7.

The study of ableism in population health: a critical review.

Over the past three decades, health equity has become a guiding framework for documenting, explaining, and informing the promotion of population health. With these developments, scholars have widened public health's aperture, bringing systems of oppression sharply into focus. Additionally, some researchers in disability and health have advocated for utilizing socially grounded frameworks to investigate the health of disabled people. Yet, naming ableism, much less operationalizing it for the empirical study of health, remains scant. This paper critically reviews the study of ableism as a social determinant of disabled people's health within population health research. First, we provide an orientation to the present state of this literature by looking to the past. We briefly trace a history of traditional approaches to studying disability and health and alternatives that have emerged from critiques of the individualized lens that has dominated this work. Next, we delineate the operation of ableism across social levels. We characterize how ableism has been studied in population health in terms of levels of analysis (intrapersonal, interpersonal, institutional, and structural) and measures of interest. To conclude, we discuss hinderances to and promising avenues toward population health research that advances health equity for disabled people.

Clinical biomarker-based biological age predicts deaths in Brazilian adults: the ELSA-Brasil study.

Biological age is a construct that seeks to evaluate the biological wear and tear process of the organism that cannot be observed by chronological age. We estimate individuals' biological age based on biomarkers from multiple systems and validate it through its association with mortality from natural causes. Biological age was estimated in 12,109 participants (6621 women and 5488 men) from the first visit of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) who had valid data for the biomarkers used in the analyses. Biological age was estimated using the Klemera and Doubal method. The difference between chronological age and biological age (Δage) was computed. Cox proportional hazard models stratified by sex were used to assess whether Δage was associated with mortality risk after a median follow-up of 9.1 years. The accuracy of the models was estimated by the area under the curve (AUC). Δage had equal mean for men and women, with greater variability for men. Cox models showed that every 1-year increase in Δage was associated with increased mortality in men (HR (95% CI) 1.21; 1.17-1.25) and women (HR (95% CI) 1.24; 1.15-1.34), independently of chronological age. Results of the AUC demonstrated that the predictive power of models that only included chronological age (AUC chronological age = 0.7396) or Δage (AUC Δage = 0.6842) was lower than those that included both, chronological age and Δage (AUC chronological age + Δage = 0.802), in men. This difference was not observed in women. We demonstrate that biological age is strongly related to mortality in both genders and is a valid predictor of death in Brazilian adults, especially among men.

Severe drought exposure in utero associates to children's epigenetic age acceleration in a global climate change hot spot.

The goal of this study is to examine the association between in utero drought exposure and epigenetic age acceleration (EAA) in a global climate change hot spot. Calculations of EAA in adults using DNA methylation have been found to accurately predict chronic disease and longevity. However, fewer studies have examined EAA in children, and drought exposure in utero has not been investigated. Additionally, studies of EAA in low-income countries with diverse populations are rare. We assess EAA using epigenetic clocks and two DNAm-based pace-of-aging measurements from whole saliva samples in 104 drought-exposed children and 109 same-sex sibling controls in northern Kenya. We find a positive association between in utero drought exposure and EAA in two epigenetic clocks (Hannum's and GrimAge) and a negative association in the DNAm based telomere length (DNAmTL) clock. The combined impact of drought's multiple deleterious stressors may reduce overall life expectancy through accelerated epigenetic aging.

Epigenome-wide association study of long-term psychosocial stress in older adults.

Long-term psychosocial stress is strongly associated with negative physical and mental health outcomes, as well as adverse health behaviours; however, little is known about the role that stress plays on the epigenome. One proposed mechanism by which stress affects DNA methylation is through health behaviours. We conducted an epigenome-wide association study (EWAS) of cumulative psychosocial stress (n = 2,689) from the Health and Retirement Study (mean age = 70.4 years), assessing DNA methylation (Illumina Infinium HumanMethylationEPIC Beadchip) at 789,656 CpG sites. For identified CpG sites, we conducted a formal mediation analysis to examine whether smoking, alcohol use, physical activity, and body mass index (BMI) mediate the relationship between stress and DNA methylation. Nine CpG sites were associated with psychosocial stress (all p < 9E-07; FDR q < 0.10). Additionally, health behaviours and/or BMI mediated 9.4% to 21.8% of the relationship between stress and methylation at eight of the nine CpGs. Several of the identified CpGs were in or near genes associated with cardiometabolic traits, psychosocial disorders, inflammation, and smoking. These findings support our hypothesis that psychosocial stress is associated with DNA methylation across the epigenome. Furthermore, specific health behaviours mediate only a modest percentage of this relationship, providing evidence that other mechanisms may link stress and DNA methylation.

Do Police Encounters Increase the Risk for Cardiovascular Disease? Police Encounters and Framingham 30-Year Cardiovascular Risk Score.

INTRODUCTION: Despite increased attention to the societal consequences of aggressive policing, the focus on rarer instances of deaths/severe injuries fails to fully capture the day-to-day experiences that racially minoritized groups face during police encounters (PEs). We explored differential vulnerability by race/ethnicity in the relationship between PEs and cardiovascular disease (CVD) risk. METHODS: Using data from the National Longitudinal Study of Adolescent to Adult Health, we regressed the Framingham 30-Year CVD risk score on a high number of lifetime PEs (6 + among men and 2 + among women). To explore differential vulnerability by race, we added an interaction between PEs and race/ethnicity. We also examined sex- and race and sex-stratified models. RESULTS: We observed no association between PEs and CVD risk in the sample overall, but the interaction between PEs and race/ethnicity was statistically significant. In race stratified models, we found that higher PEs were associated with a lower CVD risk among Black respondents, whereas among White respondents there was no relationship. In the sex-stratified analysis, reporting higher PEs was associated with lower CVD risk among men, while among women there was no relationship. In sex- and race-stratified models, higher PEs was associated with lower CVD risk among Black men and higher CVD risk among White women, while there was no association among Black women and White men. CONCLUSION: The association between PEs and CVD risk depends on race/ethnicity and sex. More work is needed to understand the counterintuitive finding that high PEs are associated with lower CVD risk among Black men.

Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons.

Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large multi-ethnic cohort in the United States, while providing an R package for their seamless implementation and adoption. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model (BSLMM) and high-dimensional mediation analysis (HDMA); while the preferred methods for estimating the global mediation effect are high-dimensional linear mediation analysis (HILMA) and principal component mediation analysis (PCMA). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.

Legislating Inequity: Structural Racism In Groups Of State Laws And Associations With Premature Mortality Rates.

Most evaluations of health equity policy have focused on the effects of individual laws. However, multiple laws' combined effects better reflect the crosscutting nature of structurally racist legal regimes. To measure the combined effects of multiple laws, we used latent class analysis, a method for detecting unobserved "subgroups" in a population, to identify clusters of US states based on thirteen structural racism-related legal domains in 2013. We identified three classes of states: one with predominantly harmful laws ([Formula: see text]), another with predominantly protective laws ([Formula: see text]), and a third with a mix of both ([Formula: see text]). Premature mortality rates overall-defined as deaths before age seventy-five per 100,000 population-were highest in states with predominantly harmful laws, which included eighteen states with past Jim Crow laws. This study offers a new method for measuring structural racism on the basis of how groups of laws are associated with premature mortality rates.

Network Types and Functional Health in Old Age: It is Not Just the Size of the Network That Matters.

OBJECTIVES: Findings on the effect of network size and support on functional health are mixed. We examine whether network types, that simultaneously incorporate multiple network characteristics, are associated with functional health in late life. METHODS: Data are from the National Social Life, Health, and Aging Project (N = 3005). We estimated the longitudinal effect of membership in five multidimensional network types on disability in six activities of daily living using negative binomial regression, and on mobility (assessed using a timed walk test) using a generalized linear mixed model. RESULTS: Compared to those in the large without strain network, older adults in the small, restricted, high contact network had fewer disabilities but worse mobility, while those in the large network with strain also had worse mobility. DISCUSSION: Care plans focusing on function and mobility should consider multiple aspects of older adults' social networks including network size, diversity, and relationship strain.

Examining the Relationship Between Multilevel Resilience Resources and Cardiovascular Disease Incidence, Overall and by Psychosocial Risks, Among Participants in the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study.

We examined relationships between resilience resources (optimism, social support, and neighborhood social cohesion) and cardiovascular disease (CVD) incidence and assessed potential effect-measure modification by psychosocial risk factors (e.g., stress, depression) among adults without CVD in 3 cohort studies (2000-2018): the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study. We fitted adjusted Cox models accounting for within-neighborhood clustering while censoring at dropout or non-CVD death. We assessed for effect-measure modification by psychosocial risks. In secondary analyses, we estimated standardized risk ratios using inverse-probability-weighted Aalen-Johansen estimators to account for confounding, dropout, and competing risks (non-CVD deaths) and obtained 95% confidence intervals (CIs) using cluster bootstrapping. For high and medium (versus low) optimism (n = 6,243), adjusted hazard ratios (HRs) for incident CVD were 0.94 (95% CI: 0.78, 1.13) and 0.90 (95% CI: 0.75, 1.07), respectively. Corresponding HRs were 0.88 (95% CI: 0.74, 1.04) and 0.92 (95% CI: 0.79, 1.06) for social support (n = 7,729) and 1.10 (95% CI: 0.94, 1.29) and 0.99 (95% CI: 0.85, 1.16) for social cohesion (n = 7,557), respectively. Some psychosocial risks modified CVD HRs. Secondary analyses yielded similar findings. For optimism and social support, an inverse relationship was frequently most compatible with the data, but a positive relationship was also compatible. For neighborhood social cohesion, positive and null relationships were most compatible. Thus, specific resilience resources may be potential intervention targets, especially among certain subgroups.

A multilevel framework to investigate cardiovascular health disparities among South Asian immigrants in the United States.

PURPOSE: Prior studies of cardiovascular health (CVH) disparities among immigrants of South Asian origin in the United States have examined South Asians as one homogenous group, focused primarily on Indian-origin immigrants, and examined risk at the individual level. METHODS: We present current knowledge and evidence gaps about CVH in the three largest South Asian-origin populations in the United States-Bangladeshi, Indian, and Pakistani-and draw on socioecological and lifecourse frameworks to propose a conceptual framework for investigating multilevel risk and protective factors of CVH across these groups. RESULTS: The central hypothesis is that CVH disparities among South Asian populations exist due to differences in structural and social determinants, including lived experiences like discrimination, and that acculturation strategies and resilience resources (e.g., neighborhood environment, education, religiosity, social support) ameliorate stressors to act as health protective factors. RESULTS: Conclusions: Our framework advances conceptualization of the heterogeneity and drivers of cardiovascular disparities in diverse South Asian-origin populations. We present specific recommendations to inform the design of future epidemiologic studies on South Asian immigrant health and the development of multilevel interventions to reduce CVH disparities and promote well-being.

Methods for Mediation Analysis with High-Dimensional DNA Methylation Data: Possible Choices and Comparison.

Epigenetic researchers often evaluate DNA methylation as a mediator between social/environmental exposures and disease, but modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large national cohort in the United States, while providing an R package for their implementation. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model by Song et al. (2020) and high-dimensional mediation analysis by Gao et al. (2019); while the superior methods for estimating the global mediation effect are high-dimensional linear mediation analysis by Zhou et al. (2021) and principal component mediation analysis by Huang and Pan (2016). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.

Experiences of the Flint Water Crisis Among Reproductive-Age Michigan Women in Communities Outside of Flint: Differences by Race and Ethnicity.

We sought to understand how women in Michigan communities outside of Flint experienced the Flint water crisis, an avoidable public health disaster widely attributed to structural racism. Using survey data from 950 Michigan women aged 18-45 from communities outside of Flint, we examined racial and ethnic differences in personal connections to Flint, perceived knowledge about the water crisis, and beliefs about the role of anti-Black racism in the water crisis factors that could contribute to poor health via increased psychological stress. We found that White (OR = 0.32; 95% CI: 0.22, 0.46) and Hispanic (OR = 0.21; 95% CI: 0.09, 0.49) women had lower odds than Black women of having family or friends who lived in Flint during the water crisis. Compared to Black women, White women were less likely to be moderately or very knowledgeable about the water crisis (OR = 0.58; 95% CI: 0.41, 0.80). White women (OR = 0.26; 95% CI: 0.18, 0.37), Hispanic women (OR = 0.38; 95% CI: 0.21, 0.68), and women of other races (OR = 0.28; 95% CI: 0.15, 0.54) were less likely than Black women to agree that the water crisis happened because government officials wanted to hurt Flint residents. Among those who agreed, White women (OR = 0.47; 95% CI: 0.30, 0.74) and women of other races (OR = 0.33; 95% CI: 0.12, 0.90) were less likely than Black women to agree that government officials wanted to hurt people in Flint because most residents are Black. We conclude that the Flint water crisis was a racialized stressor, with potential implications for the health of reproductive-age Black women.

Institutional Racism and Health: a Framework for Conceptualization, Measurement, and Analysis.

Despite growing interest in the health-related consequences of racially discriminatory institutional policies and practices, public health scholars have yet to reach a consensus on how to measure and analyze exposure to institutional racism. The purpose of this paper is to provide an overview of the conceptualization, measurement, and analysis of institutional racism in the context of quantitative research on minority health and health disparities in the United States. We begin by providing definitions of key concepts (e.g., racialization, racism, racial inequity) and describing linkages between these ideas. Next, we discuss the hypothesized mechanisms that link exposure to institutional racism with health. We then provide a framework to advance empirical research on institutional racism and health, informed by a literature review that summarizes measures and analytic approaches used in previous studies. The framework addresses six considerations: (1) policy identification, (2) population of interest, (3) exposure measurement, (4) outcome measurement, (5) study design, and (6) analytic approach. Research utilizing the proposed framework will help inform structural interventions to promote minority health and reduce racial and ethnic health disparities.

Did the public attribute the Flint Water Crisis to racism as it was happening? Text analysis of Twitter data to examine causal attributions to racism during a public health crisis.

The Flint Water Crisis (FWC) was an avoidable public health disaster that has profoundly affected the city's residents, a majority of whom are Black. Although many scholars and journalists have called attention to the role of racism in the water crisis, little is known about the extent to which the public attributed the FWC to racism as it was unfolding. In this study, we used natural language processing to analyze nearly six million Flint-related tweets posted between April 1, 2014, and June 1, 2016. We found that key developments in the FWC corresponded to increases in the number and percentage of tweets that mentioned terms related to race and racism. Similar patterns were found for other topics hypothesized to be related to the water crisis, including water and politics. Using sentiment analysis, we found that tweets with a negative polarity score were more common in the subset of tweets that mentioned terms related to race and racism when compared to the full set of tweets. Next, we found that word pairs that included terms related to race and racism first appeared after the January 2016 state and federal emergency declarations and a corresponding increase in media coverage of the FWC. We conclude that many Twitter users connected the events of the water crisis to race and racism in real-time. Given growing evidence of negative health effects of second-hand exposure to racism, this may have implications for understanding minority health and health disparities in the US.