Gerrymandering and the Packing and Cracking of Medical Uninsurance Rates in the United States.

CONTEXT: Technological innovation and access to big data have allowed partisan gerrymandering to increase dramatically in recent redistricting cycles. OBJECTIVE: To understand whether and how partisan gerrymandering, including "packing" and "cracking" (ie, respectively concentrating within or dividing specified social groups across political boundaries), distorts understanding of public health need when health statistics are calculated for congressional districts (CDs). DESIGN: Cross-sectional study using 2020 CDs and nonpartisan simulated districts. SETTING: United States, 2017-2021. PARTICIPANTS: United States residents. MAIN OUTCOME MEASURE: Percent with no medical insurance (uninsured), within-district variance of percent uninsured, and between-district variance of percent uninsured. RESULTS: At the state level, states where partisan redistricting plans showed greater evidence of partisan gerrymandering were more likely to contain CDs with more extreme values of uninsurance rates than districts in states with less evidence for gerrymandering (association between z-scores for gerrymandering and between-district variation in uninsurance = 0.25 (-0.04, 0.53), P = .10). Comparing variation in uninsurance rates for observed CDs vs nonpartisan simulated districts across all states with more than 1 CD, in analyses stratified by state gerrymander status (no gerrymander, Democratic gerrymander, and Republican gerrymander), we found evidence of particularly extreme distortion of rates in Republican gerrymandered states, whereby Republican-leaning districts tended to have lower uninsurance rates (the percentage of Republican-leaning districts that were significantly lower than nonpartisan simulated districts was 5.1 times that of Democratic-leaning districts) and Democrat-leaning districts had higher uninsurance rates (the percentage of Democrat-leaning districts that were significantly higher than nonpartisan simulated districts was 3.0 times that of Republican-leaning districts). CONCLUSIONS: Partisan gerrymandering can affect determination of CD-level uninsurance rates and distort understanding of public health burdens.

Theorizing epidemiology, the stories bodies tell, and embodied truths: a status update on contending 21st c CE epidemiological theories of disease distribution.

This critical review considers the status of 21st-century epidemiological theories of disease distribution, updating to 2024 prior analyses published up through 2014, and discusses the implications of these theories for research, practice, and pedagogy. Three key trends stand out: (a) the continued dominance of individualistic biomedical and lifestyle theories; (b) growth and elaboration of social epidemiological alternatives; and (c) the ongoing inattention to epidemiologic theories of disease distribution in the training of epidemiologists and public health professionals and in current efforts to improve the rigor of epidemiological research and causal inference. In a context of growing global political polarization, climate crisis, broader environmental and ecological crises, and stubbornly persistent health inequities within and between nations, producing actionable knowledge relevant to improving the people's health and advancing health justice will require much greater engagement with social epidemiologic theories of disease distribution in research, pedagogy, and practice. At issue is critically engaging with the embodied truths manifested in the stories bodies tell in population patterns of health, disease, and well-being.

Epigenetic Aging and Racialized, Economic, and Environmental Injustice: NIMHD Social Epigenomics Program.

Importance: Epigenetic age acceleration is associated with exposure to social and economic adversity and may increase the risk of premature morbidity and mortality. However, no studies have included measures of structural racism, and few have compared estimates within or across the first and second generation of epigenetic clocks. Objective: To determine whether epigenetic age acceleration is positively associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design, Setting, and Participants: This cross-sectional study used data from the My Body My Story (MBMS) study between August 8, 2008, and December 31, 2010, and examination 5 of the Multi-Ethnic Atherosclerosis Study (MESA) from April 1, 2010, to February 29, 2012. In the MBMS, DNA extraction was performed in 2021; linkage of structural measures to the MBMS and MESA, in 2022. US-born individuals were randomly selected from 4 community health centers in Boston, Massachusetts (MBMS), and 4 field sites in Baltimore, Maryland; Forsyth County, North Carolina; New York City, New York; and St Paul, Minnesota (MESA). Data were analyzed from November 13, 2021, to August 31, 2023. Main Outcomes and Measures: Ten epigenetic clocks (6 first-generation and 4 second-generation), computed using DNA methylation data (DNAm) from blood spots (MBMS) and purified monocytes (MESA). Results: The US-born study population included 293 MBMS participants (109 men [37.2%], 184 women [62.8%]; mean [SD] age, 49.0 [8.0] years) with 224 Black non-Hispanic and 69 White non-Hispanic participants and 975 MESA participants (492 men [50.5%], 483 women [49.5%]; mean [SD] age, 70.0 [9.3] years) with 229 Black non-Hispanic, 191 Hispanic, and 555 White non-Hispanic participants. Of these, 140 (11.0%) exhibited accelerated aging for all 5 clocks whose estimates are interpretable on the age (years) scale. Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 (95% CI, 0.003-0.27) SDs and with birth state conservatism by 0.06 (95% CI, 0.01-0.12) SDs, pooling across all clocks. Low parental educational level was associated with epigenetic age acceleration, pooling across all clocks, for both Black non-Hispanic (0.24 [95% CI, 0.08-0.39] SDs) and White non-Hispanic (0.27 [95% CI, 0.03-0.51] SDs) MBMS participants. Adult impoverishment was positively associated with the pooled second-generation clocks among the MESA participants (Black non-Hispanic, 0.06 [95% CI, 0.01-0.12] SDs; Hispanic, 0.07 [95% CI, 0.01-0.14] SDs; White non-Hispanic, 0.05 [95% CI, 0.01-0.08] SDs). Conclusions and Relevance: The findings of this cross-sectional study of MBMS and MESA participants suggest that epigenetic age acceleration was associated with racialized and economic injustice, potentially contributing to well-documented inequities in premature mortality. Future research should test the hypothesis that epigenetic accelerated aging may be one of the biological mechanisms underlying the well-documented elevated risk of premature morbidity and mortality among social groups subjected to racialized and economic injustice.

Advancing gender transformative intersectional science for health justice: An ecosocial analysis.

At a time when health-oriented institutions both globally and nationally are increasingly recognizing the need to support research, interventions and training that engage with analysis of how gendered social systems shape population health, independent of and in conjunction with sex-linked biology, it is essential that this work reject biological essentialism and instead embrace embodied integration. In this essay, guided by the ecosocial theory of disease distribution, I clarify connections and distinctions between biological versus social reproduction and inheritance, underscore the non-equivalence of the categories "sex" and "race," and offer a set of examples analyzing the production of gendered health inequities and who needs to do what to address them. The examples concern the worlds of work (sexual harassment; breastfeeding; sex work), ecologic environments (water access; fracking, sexually transmitted infections, & sexual violence); sexual reproduction and reproductive justice (gender stereotyping of reproductive biology; sterilization abuse and abortion bans); and (4) gender transformative initiatives (violence; health interventions). To advance gender transformative intersectional science for health justice, I offer recommendations regarding requirements for justifying data conceptualization, analysis and governance that can be implemented by institutions with the power to shape the funding, translation, and publication of science involving gender, sex-linked biology, and the people's health.

1965 US Voting Rights Act Impact on Black and Black Versus White Infant Death Rates in Jim Crow States, 1959-1980 and 2017-2021.

Objectives. To investigate the impact of the US Voting Rights Act (VRA) of 1965 on Black and Black versus White infant deaths in Jim Crow states. Methods. Using data from 1959 to 1980 and 2017 to 2021, we applied difference-in-differences methods to quantify differential pre-post VRA changes in infant deaths in VRA-exposed versus unexposed counties, controlling for population size and social, economic, and health system characteristics. VRA-exposed counties, identified by Section 4, were subject to government interventions to remove existing racist voter suppression policies. Results. Black infant deaths in VRA-exposed counties decreased by an average of 11.4 (95% confidence interval [CI] = 1.7, 21.0) additional deaths beyond the decrease experienced by unexposed counties between the pre-VRA period (1959-1965) and the post-VRA period (1966-1970). This translates to 6703 (95% CI = 999.6, 12 348) or 17.5% (95% CI = 3.1%, 28.1%) fewer deaths than would have been experienced in the absence of the VRA. The equivalent differential changes were not significant among the White or total population. Conclusions. Passage of the VRA led to pronounced reductions in Black infant deaths in Southern counties subject to government intervention because these counties had particularly egregious voter suppression practices. (Am J Public Health. 2024;114(3):300-308. https://doi.org/10.2105/AJPH.2023.307518).

Magnesium Decreases Urine Supersaturation but Not Calcium Oxalate Stone Formation in Genetic Hypercalciuric Stone-Forming Rats.

BACKGROUND/AIMS: Hypercalciuria is the most common identifiable risk factor predisposing to CaOx stone formation. Increased oral magnesium intake may lead to decreased CaOx stone formation by binding intestinal Ox leading to decreased absorption and/or binding urinary Ox to decrease urinary supersaturation. This study assessed the effect of oral magnesium on 24-h urine ion excretion, supersaturation, and kidney stone formation in a genetic hypercalciuric stone-forming (GHS) rat model of human idiopathic hypercalciuria. METHODS: When fed the oxalate precursor, hydroxyproline, every GHS rat develops CaOx stones. The GHS rats, fed a normal calcium and phosphorus diet supplemented with hydroxyproline to induce CaOx, were divided into three groups of ten rats per group: control diet with 4.0 g/kg MgO, low MgO diet (0.5 g/kg), and high MgO diet (8 g/kg). At 6 weeks, 24-h urines were collected, and urine chemistry and supersaturation were determined. Stone formation was quantified. RESULTS: The GHS rats fed the low and high Mg diets had a significant reduction and increase, respectively, in urinary Mg compared to those fed the control diet. Dietary Mg did not alter urine Ca excretion while the low Mg diet led to a significant fall in urinary Ox. Urine supersaturation with respect to CaOx was significantly increased with low Mg, whereas urine supersaturation was significantly decreased with high Mg. There was no effect of dietary Mg on stone formation within 6 weeks of treatment. CONCLUSION: Dietary magnesium decreases urine supersaturation but not CaOx stone formation in GHS rats.

An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution.

Importance: DNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. Objective: Our study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. Design: A series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). Setting: MBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. Participants: Two population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). Exposures: Eight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcome: Genome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. Results: We observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and Relevance: Overall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics.

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

Immune tolerance via FCR001 cell therapy compared with maintenance immunosuppression for kidney transplantation: Real-world evidence analysis of safety and efficacy.

While kidney transplantation (KTx) has traditionally required lifelong immunosuppression, an investigational stem cell therapy, FCR001, has been demonstrated to induce tolerance and eliminate the need for immunosuppression through the establishment of persistent mixed chimerism in a phase 2 clinical study. Real-world evidence (RWE) methods were employed to compare the safety and efficacy of non-myeloablative conditioning with FCR001 with standard of care [SOC] immunosuppression in a retrospective single-center analysis of outcomes among propensity score matched living-donor KTx receiving SOC (n = 144) or FCR001 (n = 36). Among the FCR001 recipients, 26 (72%) developed persistent chimerism allowing durable elimination of all immunosuppression. There was no significant difference in the composite primary endpoint (biopsy-proven acute rejection [BPAR], graft loss, or death) at 60 months (FCR001 27.8%, n = 10 and SOC 28.5%, n = 41; p = .9). FCR001 recipients demonstrated superior kidney function at 5 years (estimated glomerular filtration rate [eGFR] [mean ± standard deviation]: 64.1 ± 15.3) compared to SOC (51.7 ± 18.8; p = .02). At 5 years, FCR001 recipients experienced fewer complications including new-onset diabetes post-transplant, although two patients developed graft versus host disease. In conclusion, RWE demonstrated that KTx combined with non-myeloablative conditioning and FCR001 resulting in superior kidney function without increasing the risk of rejection, graft loss, or death among patients off immunosuppression.

Impacts of census differential privacy for small-area disease mapping to monitor health inequities.

The U.S. Census Bureau will implement a modernized privacy-preserving disclosure avoidance system (DAS), which includes application of differential privacy, on publicly released 2020 census data. There are concerns that the DAS may bias small-area and demographically stratified population counts, which play a critical role in public health research, serving as denominators in estimation of disease/mortality rates. Using three DAS demonstration products, we quantify errors attributable to reliance on DAS-protected denominators in standard small-area disease mapping models for characterizing health inequities. We conduct simulation studies and real data analyses of inequities in premature mortality at the census tract level in Massachusetts and Georgia. Results show that overall patterns of inequity by racialized group and economic deprivation level are not compromised by the DAS. While early versions of DAS induce errors in mortality rate estimation that are larger for Black than non-Hispanic white populations in Massachusetts, this issue is ameliorated in newer DAS versions.

Contextualizing Response Rates During the COVID-19 Pandemic: Experiences From a Boston-Based Community Health Centers Study.

OBJECTIVES: The focus of this study was to calculate and contextualize response rates for a community-based study conducted during the COVID-19 pandemic, a topic on which scant data exist, and to share lessons learned from recruiting and enrolling for implementation of future studies. DESIGN: The Life+Health Study, a cross-sectional population-based study designed to advance novel methods to measure and analyze multiple forms of discrimination for population health research. SETTING: The study recruited participants from 3 community health centers in Boston, Massachusetts, between May 2020 and July 2022. PARTICIPANTS: A total of 699 adult participants between the ages of 25 and 64 years who were born in the United States and had visited one of the health centers within the last 2 years. MAIN OUTCOME MEASURES: The response rate was calculated as follows: (number of completions + number of dropouts)/(dropouts + enrollments). To contextualize this response rate, we synthesized evidence pertaining to local COVID-19 case counts, sociopolitical events, pandemic-related restrictions and project protocol adjustments, and examples of interactions with patients. RESULTS: Our study had a lower-than-expected response rate (48.4%), with the lowest rates from the community health centers serving primarily low-income patients of color. Completion rates were lower during periods of higher COVID-19 case counts. We describe contextual factors that led to challenges and lessons learned from recruiting during the pandemic, including the impact of US sociopolitical events. CONCLUSIONS: The Life+Health Study concluded recruitment during the pandemic with a lower-than-expected response rate, as also reported in 4 other US publications focused on the impact of COVID-19 on response rates in community-based studies. Our results provide an example of the impact of the pandemic and related US sociopolitical events on response rates that can serve as a framework for contextualizing other research conducted during the pandemic and highlight the importance of best practices in research recruitment with underserved populations.

Systematic review of how racialized health inequities are addressed in Epidemiologic Reviews articles (1979-2021): a critical conceptual and empirical content analysis and recommendations for best practices.

Critical analysis of the determinants of current and changing racialized health inequities, including the central role of racism, is an urgent priority for epidemiology, for both original research studies and epidemiologic review articles. Motivating our systematic overview review of Epidemiologic Reviews articles is the critical role of epidemiologic reviews in shaping discourse, research priorities, and policy relevant to the social patterning of population health. Our approach was first to document the number of articles published in Epidemiologic Reviews (1979-2021; n = 685) that either: (1) focused the review on racism and health, racial discrimination and health, or racialized health inequities (n = 27; 4%); (2) mentioned racialized groups but did not focus on racism or racialized health inequities (n = 399; 59%); or (3) included no mention of racialized groups or racialized health inequities (n = 250; 37%). We then conducted a critical content analysis of the 27 review articles that focused on racialized health inequities and assessed key characteristics, including (1) concepts, terms, and metrics used regarding racism and racialized groups (notably only 26% addressed the use or nonuse of measures explicitly linked to racism; 15% provided explicit definitions of racialized groups); (2) theories of disease distribution guiding (explicitly or implicitly) the review's approach; (3) interpretation of findings; and (4) recommendations offered. Guided by our results, we offer recommendations for best practices for epidemiologic review articles for addressing how epidemiologic research does or does not address ubiquitous racialized health inequities.

Telomere Length, Health, and Mortality in a Cohort of Older Black South African Adults.

Telomere length (TL) may be a biomarker of aging processes as well as age-related diseases. However, most studies of TL and aging are conducted in high-income countries. Less is known in low- and middle-income countries (LMICs) such as South Africa, where life expectancy remains lower despite population aging. We conducted a descriptive analysis of TL in a cohort of older adults in rural South Africa. TL was assayed from venous blood draws using quantitative polymerase chain reaction (T/S ratio). We examined the correlation between TL and biomarkers, demographic characteristics, mental/cognitive health measures, and physical performance measures in a subsample of the Wave 1 2014-2015 "Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI) cohort (n = 510). We used logistic regression to measure the association between TL and mortality through Wave 3 (2021-2022). In bivariate analyses, TL was significantly correlated with age (r = -0.29, p < .0001), self-reported female sex (r = 0.13, p = .002), mortality (r = -0.1297, p = .003), diastolic blood pressure (r = 0.09, p = .037), pulse pressure (r = -0.09, p = .045), and being a grandparent (r = -0.17, p = .0001). TL was significantly associated with age (ß = -0.003; 95% confidence interval [CI] = -0.005, -0.003). TL was significantly associated in unadjusted multivariate analyses with mortality, but the relationship between TL and mortality was attenuated after adjusting for age (odds ratio [OR] = 0.19; 95% CI = 0.03, 1.27) and other covariates (OR = 0.17; 95% CI = 0.02, 1.19). Our study is the first analysis of TL in an older adult South African population. Our results corroborate existing relationships between TL and age, sex, cardiometabolic disease, and mortality found in higher-income countries.

The burden of nonalcoholic steatohepatitis (NASH) in the United States.

BACKGROUND: There is limited data on the comparative economic and humanistic burden of non-alcoholic steatohepatitis (NASH) in the United States. The objective was to examine the burden of disease comparing NASH to a representative sample of the general population and separately to a type 2 diabetes mellitus (T2DM) cohort by assessing health-related quality of life (HRQoL) measures, healthcare resource use (HRU) and work productivity and activity impairment (WPAI). METHODS: Data came from the 2016 National Health and Wellness Survey, a nationally representative patient-reported outcomes survey conducted in the United States. Respondents with physician-diagnosed NASH, physician-diagnosed T2DM, and respondents from the general population were compared. Humanistic burden was examined with mental (MCS) and physical (PCS) component summary scores from the Short-Form (SF)-36v2, concomitant diagnosis of anxiety, depression, and sleep difficulties. Economic burden was analysed based on healthcare professional (HCP) and emergency room (ER) visits, hospitalizations in the past six months; absenteeism, presenteeism, overall work impairment, and activity impairment scores on WPAI questionnaire. Bivariate and multivariable analysis were conducted for each outcome and matched comparative group. RESULTS: After adjusting for baseline demographics and characteristics, NASH (N = 136) compared to the matched general population cohort (N = 544), reported significantly lower (worse) mental (MCS 43.19 vs. 46.22, p = 0.010) and physical (PCS 42.04 vs. 47.10, p < 0.001) status, higher % with anxiety (37.5% vs 25.5%, p = 0.006) and depression (43.4% vs 30.1%, p = 0.004), more HCP visits (8.43 vs. 5.17), ER visits (0.73 vs. 0.38), and hospitalizations (0.43 vs. 0.2) all p's < 0.05, and higher WPAI scores (e.g. overall work impairment 39.64% vs. 26.19%, p = 0.011). NASH cohort did not differ from matched T2DM cohort (N = 272) on mental or work-related WPAI scores, but had significantly worse physical status (PCS 40.52 vs. 44.58, p = 0.001), higher % with anxiety (39.9% vs 27.8%, p = 0.043), more HCP visits (8.63 vs. 5.68, p = 0.003) and greater activity impairment (47.14% vs. 36.07%, p = 0.010). CONCLUSION: This real-world study suggests that burden of disease is higher for all outcomes assessed among NASH compared to matched general controls. When comparing to T2DM, NASH cohort has comparable mental and work-related impairment but worse physical status, daily activities impairment and more HRU.

Decreasing Survey Response Rates in the Time of COVID-19: Implications for Analyses of Population Health and Health Inequities.

Objectives. To examine whether, and if so how, US national and state survey response rates changed after the onset of the COVID-19 pandemic. Methods. We compared the change in response rates between 2020 and 2019 of 6 (3 social and economic, 3 health focused) major US national surveys (2 with state response rates). Results. All the ongoing surveys except 1 reported relative decreases (∼29%) in response rates. For example, the household response rate to the US Census American Community Survey decreased from 86.0% in 2019 to 71.2% in 2020, and the response rate of the US National Health Interview Survey decreased from 60.0% to 42.7% from the first to the second quarter of 2020. For all surveys, the greatest decreases in response rates occurred among persons with lower income and lower education. Conclusions. Socially patterned decreases in response rates pose serious challenges and must be addressed explicitly in all studies relying on data obtained since the onset of the pandemic. Public Health Implications. Artifactual reduction of estimates of the magnitude of health inequities attributable to differential response rates could adversely affect efforts to reduce these inequities. (Am J Public Health. 2023;113(6):667-670. https://doi.org/10.2105/AJPH.2023.307267).

Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices.

Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.

The impact of county-level fees & fines as exploitative revenue generation on US birth outcomes 2011-2015.

Fees and fines collected through courts and law enforcement can comprise a considerable proportion of revenue for local governments. Law enforcement, as agents of revenue generation, change policing behavior to increase revenue, at times targeting Black and brown neighborhoods to bolster municipal budgets. This structural racism in revenue generation has not yet been assessed as an exposure for adverse health. Using the 2012 Census of Governments, and 2011-2015 vital statistics from the National Center of Health Statistics, we examine the relationship between countyaverage fees and fines as a percent of total own-source revenue and county-level characteristics, and risk of preterm birth and low birthweight across the United States. Mothers residing in counties with the greatest reliance on fees and fines had 1.08 (95% CI: 1.03-1.12) times the odds of preterm birth and 1.07 (95% CI: 1.02-1.11) times the odds of low birthweight than mothers residing in counties with the least reliance on fees and fines, controlling for individual- and county-level covariates. The addition of countylevel racial composition, and the Index of Concentration at the Extremes (ICE), reduced these associations yet remained statistically significant. Future studies should continue to examine how racist, exploitative revenue generation through police and court activities influences the health of residents.

Addressing spatial misalignment in population health research: a case study of US congressional district political metrics and county health data.

Areal spatial misalignment, which occurs when data on multiple variables are collected using mismatched boundary definitions, is a ubiquitous obstacle to data analysis in public health and social science research. As one example, the emerging sub-field studying the links between political context and health in the United States faces significant spatial misalignment-related challenges, as the congressional districts (CDs) over which political metrics are measured and administrative units, e.g., counties, for which health data are typically released, have a complex misalignment structure. Standard population-weighted data realignment procedures can induce measurement error and invalidate inference, which has prompted the development of fully model-based approaches for analyzing spatially misaligned data. One such approach, atom-based regression models (ABRM), holds particular promise but has scarcely been used in practice due to the lack of appropriate software or examples of implementation. ABRM use "atoms", the areas created by intersecting all sets of units on which variables of interest are measured, as the units of analysis and build models for the atom-level data, treating the atom-level variables (generally unmeasured) as latent variables. In this paper, we demonstrate the feasibility and strengths of the ABRM in a case study of the association between political representatives' voting behavior (CD-level) and COVID-19 mortality rates (county-level) in a post-vaccine period. The adjusted ABRM results suggest that more conservative voting record is associated with an increase in COVID-19 mortality rates, with estimated associations smaller in magnitude but consistent in direction with those of standard realignment methods. The results also indicate that ABRM may enable more robust confounding adjustment and more realistic uncertainty estimates, properly representing the uncertainties arising from all analytic procedures. We also implement the ABRM in modern optimized Bayesian computing programs and make our code publicly available, which may enable these methods to be more widely adopted.

Using Implicit Measures of Discrimination: White, Black, and Hispanic Participants Respond Differently to Group-Specific Racial/Ethnic Categories vs. the General Category "People of Color" in the USA.

Recent studies showed that implicit measures are valuable instruments for assessing exposure to discrimination and predicting negative physical conditions. Between March 10, 2020, and April 1, 2020, we conducted three experiments (577 participants) in the USA to evaluate the use of group-specific vs. general race/ethnicity categories in implicit measures of discrimination. We measured implicit discrimination and attitudes towards the general race/ethnicity category "people of color" (POC) and two specific race/ethnicity categories (i.e., "Black people" and "Hispanic people"). Implicit discrimination and attitudes were assessed using the Brief Implicit Association Test (B-IAT). Among participants (mean age = 37, standard deviation = 10.5), 50% identified as White non-Hispanic (NH), 33.3% as Black NH, and 16.7% as Hispanic; 71.7% were female and 72.2% had a bachelor's degree or higher. We found an implicit discrimination towards target groups and an in-group preference among all participant groups only when specific race/ethnicity categories were used in the B-IAT. When the general category POC was used, we observed a discrimination towards POC only for Black NH participants, while White NH participants showed no discrimination. Similarly, Black NH participants showed no in-group preference for POC, but did show an in-group preference for Black people. These results suggest that using the category POC in implicit measures may be inappropriate when evaluating discrimination and attitudes towards Black and Hispanic individuals as it may not capture specific experiences of discrimination and identity in these groups.