A Critique and Examination of the Polysocial Risk Score Approach: Predicting Cognition in the Health and Retirement Study.

Polysocial risk scores were recently proposed as a strategy to improve clinical relevance of knowledge about social determinants of health. The objective of this paper was to assess if the polysocial risk score model improves prediction of cognition and all-cause mortality in middle-aged and older adults beyond simpler models including a smaller set of key social determinants of health. We used a sample of 13,773 individuals aged 50+ at baseline from the 2006 to 2018 waves of the Health and Retirement Study, a US population-based longitudinal cohort. Four linear mixed models were compared: two simple models including a priori selected covariates and two polysocial risk score models which used LASSO regularization to select covariates among 9 or 21 candidate social predictors. All models included age. Predictive accuracy was assessed via R-squared and root mean-squared prediction error (RMSPE) using training/test split and cross-validation. For predicting cognition, the simple model including age, race, gender, and education had an R-squared of 0.31 and an RMSPE of 0.880. Compared with this, the most complex polysocial risk score selected 12 predictors (R-squared=0.35 and RMSPE=0.858; 2.2% improvement). For all-cause mortality, the simple model including age, race, gender, and education had an AUROC of 0.747, while the most complex polysocial risk score did not demonstrate improved performance (AUROC = 0.745). Models built on a smaller set of key social determinants performed comparably to models built on a more complex set of social "risk factors".

Practical Guide to Honest Causal Forests for Identifying Heterogeneous Treatment Effects.

"Heterogeneous treatment effects" is a term which refers to conditional average treatment effects (i.e., CATEs) that vary across population subgroups. Epidemiologists are often interested in estimating such effects because they can help detect populations that may particularly benefit from or be harmed by a treatment. However, standard regression approaches for estimating heterogeneous effects are limited by preexisting hypotheses, test a single effect modifier at a time, and are subject to the multiple-comparisons problem. In this article, we aim to offer a practical guide to honest causal forests, an ensemble tree-based learning method which can discover as well as estimate heterogeneous treatment effects using a data-driven approach. We discuss the fundamentals of tree-based methods, describe how honest causal forests can identify and estimate heterogeneous effects, and demonstrate an implementation of this method using simulated data. Our implementation highlights the steps required to simulate data sets, build honest causal forests, and assess model performance across a variety of simulation scenarios. Overall, this paper is intended for epidemiologists and other population health researchers who lack an extensive background in machine learning yet are interested in utilizing an emerging method for identifying and estimating heterogeneous treatment effects.

Propensity Scores in Health Disparities Research: The Example of Cognitive Aging and the Hispanic Paradox.

BACKGROUND: Individuals of Mexican ancestry in the United States experience substantial socioeconomic disadvantages compared with non-Hispanic white individuals; however, some studies show these groups have similar dementia risk. Evaluating whether migration selection factors (e.g., education) associated with risk of Alzheimer disease and related dementia (ADRD) explain this paradoxical finding presents statistical challenges. Intercorrelation of risk factors, common with social determinants, could make certain covariate patterns very likely or unlikely to occur for particular groups, which complicates their comparison. Propensity score (PS) methods could be leveraged here to diagnose nonoverlap and help balance exposure groups. METHODS: We compare conventional and PS-based methods to examine differences in cognitive trajectories between foreign-born Mexican American, US-born Mexican American, and US-born non-Hispanic white individuals in the Health and Retirement Study (1994-2018). We examined cognition using a global measure. We estimated trajectories of cognitive decline from linear mixed models adjusted for migration selection factors also associated with ADRD risk conventionally or with inverse probability weighting. We also employed PS trimming and match weighting. RESULTS: In the full sample, where PS overlap was poor, unadjusted analyses showed both Mexican ancestry groups had worse baseline cognitive scores but similar or slower rates of decline compared with non-Hispanic white adults; adjusted findings were similar, regardless of method. Focusing analyses on populations where PS overlap was improved (PS trimming and match weighting) did not alter conclusions. CONCLUSIONS: Attempting to equalize groups on migration selection and ADRD risk factors did not explain paradoxical findings for Mexican ancestry groups in our study.

Regression discontinuity design to evaluate the effect of statins on myocardial infarction in electronic health records.

Regression discontinuity design (RDD) is a quasi-experimental method intended for causal inference in observational settings. While RDD is gaining popularity in clinical studies, there are limited real-world studies examining the performance on estimating known trial casual effects. The goal of this paper is to estimate the effect of statins on myocardial infarction (MI) using RDD and compare with propensity score matching and Cox regression. For the RDD, we leveraged a 2008 UK guideline that recommends statins if a patient's 10-year cardiovascular disease (CVD) risk score > 20%. We used UK electronic health record data from the Health Improvement Network on 49,242 patients aged 65 + in 2008-2011 (baseline) without a history of CVD and no statin use in the two years prior to the CVD risk score assessment. Both the regression discontinuity (n = 19,432) and the propensity score matched populations (n = 24,814) demonstrated good balance of confounders. Using RDD, the adjusted point estimate for statins on MI was in the protective direction and similar to the statin effect observed in clinical trials, although the confidence interval included the null (HR = 0.8, 95% CI 0.4, 1.4). Conversely, the adjusted estimates using propensity score matching and Cox regression remained in the harmful direction: HR = 2.42 (95% CI 1.96, 2.99) and 2.51 (2.12, 2.97). RDD appeared superior to other methods in replicating the known protective effect of statins with MI, although precision was poor. Our findings suggest that, when used appropriately, RDD can expand the scope of clinical investigations aimed at causal inference by leveraging treatment rules from everyday clinical practice.

Racial Residential Segregation in Young Adulthood and Brain Integrity in Middle Age: Can We Learn From Small Samples?

Racial residential segregation is associated with multiple adverse health outcomes in Black individuals. Yet, the influence of structural racism and racial residential segregation on brain aging is less understood. In this study, we investigated the association between cumulative exposure to racial residential segregation over 25 years (1985-2010) in young adulthood, as measured by the Getis-Ord Gi* statistic, and year 25 measures of brain volume (cerebral, gray matter, white matter, and hippocampal volumes) in midlife. We studied 290 Black participants with available brain imaging data who were enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort study. CARDIA investigators originally recruited 2,637 Black participants aged 18-30 years from 4 field centers across the United States. We conducted analyses using marginal structural models, incorporating inverse probability of treatment weighting and inverse probability of censoring weighting. We found that compared with low/medium segregation, greater cumulative exposure to a high level of racial residential segregation throughout young adulthood was associated with smaller brain volumes in general (e.g., for cerebral volume, ß = -0.08, 95% confidence interval: -0.15, -0.02) and with a more pronounced reduction in hippocampal volume, though results were not statistically significant. Our findings suggest that exposure to segregated neighborhoods may be associated with worse brain aging.

Associations of Food Insecurity and Memory Function Among Middle to Older-Aged Adults in the Health and Retirement Study.

Importance: Food insecurity is a leading public health issue in the US. Research on food insecurity and cognitive aging is scarce, and is mostly cross-sectional. Food insecurity status and cognition both can change over the life course, but their longitudinal relationship remains unexplored. Objective: To examine the longitudinal association between food insecurity and changes in memory function during a period of 18 years among middle to older-aged adults in the US. Design, Setting, and Participants: The Health and Retirement Study is an ongoing population-based cohort study of individuals aged 50 years or older. Participants with nonmissing information on their food insecurity in 1998 who contributed information on memory function at least once over the study period (1998-2016) were included. To account for time-varying confounding and censoring, marginal structural models were created, using inverse probability weighting. Data analyses were conducted between May 9 and November 30, 2022. Main outcomes and Measures: In each biennial interview, food insecurity status (yes/no) was assessed by asking respondents whether they had enough money to buy food or ate less than they felt they should. Memory function was a composite score based on self-completed immediate and delayed word recall task of a 10-word list and proxy-assessed validated instruments. Results: The analytic sample included 12 609 respondents (mean [SD] age, 67.7 [11.0] years, 8146 [64.60%] women, 10 277 [81.51%] non-Hispanic White), including 11 951 food-secure and 658 food-insecure individuals in 1998. Over time, the memory function of the food-secure respondents decreased by 0.045 SD units annually (ß for time, -0.045; 95% CI, -0.046 to -0.045 SD units). The memory decline rate was faster among food-insecure respondents than food-secure respondents, although the magnitude of the coefficient was small (ß for food insecurity × time, -0.0030; 95% CI, -0.0062 to -0.00018 SD units), which translates to an estimated 0.67 additional (ie, excess) years of memory aging over a 10-year period for food-insecure respondents compared with food-secure respondents. Conclusions and Relevance: In this cohort study of middle to older-aged individuals, food insecurity was associated with slightly faster memory decline, suggesting possible long-term negative cognitive function outcomes associated with exposure to food insecurity in older age.

Racial Differences in Employment and Poverty Histories and Health in Older Age.

INTRODUCTION: Black Americans encounter more barriers in the job market and earn less than White Americans. However, the extent to which racial disparities in employment and poverty histories impact health is not fully understood. This study characterized employment‒poverty histories for Black and White middle-aged adults and examined their association with health. METHODS: Respondents born in 1948-1953 and enrolled in the 2004 Health and Retirement Study (NBlack=555, NWhite=2,209) were included. Sequence analysis grouped respondents with similar employment‒poverty trajectories from 2004 to 2016, and confounder-adjusted regression analyses estimated the associations between these trajectories and health in 2018. Analyses were conducted in 2021-2022. RESULTS: More than 23% of Black respondents experienced both employment and poverty fluctuations, including bouts of extreme poverty (<50% of the federal poverty threshold), whereas no trajectory for White respondents included extreme poverty. Adversities in employment‒poverty were associated with worse health. For example, among Black respondents, those who experienced both employment and poverty fluctuations had worse cognition than those employed and not poor (ß= -0.55 standardized units, 95% CI= -0.81, -0.30). Similarly, among White respondents, those who experienced employment fluctuations had worse cognition than those employed (ß= -0.35, 95% CI= -0.46, -0.24). Notably, the employed and not poor trajectory was associated with worse survival among Black respondents than among White respondents. CONCLUSIONS: Employment fluctuations were associated with worse health, especially cognitive function, where the association was stronger among Black Americans who experienced both employment fluctuations and poverty. Findings highlight the importance of enhancing employment stability and of antipoverty programs, especially for Black Americans.

Statins and Cognitive Decline in the Cardiovascular Health Study: A Comparison of Different Analytical Approaches.

BACKGROUND: Despite their well-established benefits for the prevention of cardiovascular disease, robust evidence on the effects of statins on cognition is largely inconclusive. We apply various study designs and analytical approaches to mimic randomized controlled trial effects from observational data. METHODS: We used observational data from 5 580 participants enrolled in the Cardiovascular Health Study from 1989/1990 to 1999/2000. We conceptualized the cohort as an overlapping sequence of nonrandomized trials. We compared multiple selection (eligible population, prevalent users, new users) and analytic approaches (multivariable adjustment, inverse-probability treatment weights, propensity score matching) to evaluate the association between statin use and 5-year change in global cognitive function, assessed using the Modified Mini-Mental State Examination (3MSE). RESULTS: When comparing prevalent users to nonusers (N = 2 772), statin use was associated with slower cognitive decline over 5 years (adjusted annual change in 3MSE = 0.34 points/year; 95% CI: 0.05-0.63). Compared to prevalent user design, estimates from new user designs (eg, comparing eligible statin initiators to noninitiators) were attenuated showing either null or negative association, though not significant. For example, in a propensity score-matched sample of statin-eligible individuals (N = 454), the annual 3MS change comparing statin initiators to noninitiators was -0.21 points/year (95% CI: -0.81 to 0.39). CONCLUSIONS: The association of statin use and cognitive decline is attenuated toward the null when using rigorous analytical approaches that more closely mimic randomized controlled trials. Point estimates, even within the same study, may vary depending on the analytical methods used. Further studies that leverage natural or quasi experiments around statin use are needed to replicate our findings.

Associations Between 20-Year Lipid Variability Throughout Young Adulthood and Midlife Cognitive Function and Brain Integrity.

BACKGROUND: Little is known about long-term lipid variability in young adulthood in relation to cognitive function and brain integrity in midlife. METHOD: We studied 3 328 adults from the Coronary Artery Risk Development in Young Adults. We defined low- and high-density lipoprotein (LDL and HDL) variability as the intraindividual standard deviation of lipid measurements over 20 years of young adulthood (1985-2005). Cognitive tests were administered in 2010. Brain scans were performed in 2010 on 714 participants. To facilitate comparison, cognitive tests and brain metrics were z-scored. RESULTS: Mean age at baseline was 25.4 years. Higher 20-year LDL variability was associated with worse verbal memory in midlife (ß = -0.25, 95% CI: -0.42, -0.08), adjusted for important covariates. Higher 20-year HDL variability was associated with worse processing speed in midlife (ß = -0.80, 95% CI: -1.18, -0.41) and brain integrity, for example, smaller total brain volume (ß = -0.58, 95% CI: -0.82, -0.34) and worse total brain fractional anisotropy (ß = -1.13, 95% CI: -1.87, -0.39). CONCLUSIONS: Higher long-term lipid variability in adulthood was associated with worse cognition and brain integrity in midlife, in a relatively young cohort.