A data-driven prospective study of incident dementia among older adults in the United States
Jordan Weiss, Eli Puterman, Aric A. Prather, Erin B. Ware, David H. Rehkopf
WWeiss 1 A data-driven prospective study of incident dementia among older adults in the United States Jordan Weiss , Eli Puterman , Aric A. Prather , Erin B. Ware , David H. Rehkopf Population Studies Center and the Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA School of Kinesiology, The University of British Columbia, Vancouver BC, Canada Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA School of Medicine, Stanford University, Palo Alto, CA, USA
Current Address: Department of Demography, UC Berkeley, Berkeley, CA, USA * Correspondence to: [email protected] (DHR), [email protected] (JW) ¶ Contributed equally to data curation and formal analysis & Contributed equally to conceptualization, methodology, and original draft preparation ‡ Contributed equally to interpretation of results and review and editing of manuscript
Abbreviations : ADAMS, Aging, Demographics, and Memory Study; CI, Confidence interval; HR, hazard ratio; HRS, Health and Retirement Study; NIA, National Institute on Aging; PGS, Polygenic score; US, United States.eiss 2
Abstract
We conducted a prospective analysis of incident dementia and its association with 65 sociodemographic, early-life, economic, health and behavioral, social, and genetic risk factors in a sample of 7,908 adults over the age of 50 from the nationally representative US-based Health and Retirement Study. We used traditional survival analysis methods (Fine-Gray models) and a data-driven approach (random survival forests for competing risks) which allowed us to account for the competing risk of death with up to 14 years of follow-up. Overall, the top five predictors across all groups were lower education, loneliness, lower wealth and income, and lower self-reported health. However, we observed variation in the leading predictors of dementia across racial/ethnic and gender groups. Our ranked lists may be useful for guiding future observational and quasi-experimental research that investigates understudied domains of risk and emphasizes life course economic and health conditions as well as disparities therein. eiss 3
Introduction
In 2017, the Lancet Commission on Dementia Prevention and Care published a report to consolidate the state of knowledge on preventive and management strategies for cognitive dementia [1]. The Commission reviewed evidence from over 500 scientific peer-reviewed articles, systematic reviews, and meta-analyses and calculated that nearly one third of dementia cases may be preventable. A wide range of factors may contribute to the ability to prevent one third of these cases including educational attainment, social engagement, physical activity, and management of comorbidities. However, a majority of the studies reviewed in the Commission’s report examined risk factors independent of one another to test a priori hypotheses about how they may be associated with dementia. Few studies have jointly and comparatively analyzed risk factors for dementia across domains of early-life, sociodemographic, economic, health and behavioral, social, and genetic characteristics while also systematically examining whether these factors differ among racial/ethnic and gender groups. A study by Lourida and colleagues [2] reported that a favorable lifestyle (e.g., not being an active smoker, engaging in regular physical activity, and maintaining a healthy diet) was associated with a lower dementia risk irrespective of genetic risk for dementia in a sample of more than 190,000 participants of European ancestry. Another recent study [3] reported that sociodemographic characteristics (e.g., lower educational attainment, Hispanic origin) and measures of health (e.g., lower rated subjective health, higher levels of body mass index [BMI]) were comparatively better predictors of incident dementia than genetic risk of dementia assessed through polygenic scores. Together, these studies suggest that a healthy lifestyle may help offset the genetic risk of dementia. eiss 4 Despite these promising findings, there has been limited work integrating risk factors across multiple domains to understand their relative importance for predicting dementia and how these rankings may vary across racial/ethnic and gender groups. An analytic framework that allows for a comprehensive investigation of dementia risk factors may be useful for hypothesis generation and prioritizing group-specific intervention targets to prevent or delay the onset of dementia [4, 5]. Further, this may help shape our understanding of how intervening on specific risk factors may eradicate or exacerbate documented disparities in dementia risk [6, 7]. Prior studies in which investigators used more contemporary statistical approaches to examine dementia have focused primarily on medical risk factors [8] and neuroimaging biomarkers [9] as well as resilience to genetic predispositions to dementia [10]. Although these characteristics are important to studying the onset of dementia, little work [e.g., 3, 11] has combined genetic and life-course environmental risk factors in pursuit of a more comprehensive prediction model. A study by Casanova and colleagues [11] used data from the Health and Retirement Study (HRS) combined with a data-driven approach to predict cognitive impairment using sociodemographic, health, and genetic data. These researchers found that education, age, gender, and history of stroke were among the leading characteristics predicting cognitive impairment. Despite the novelty and innovation of their approach, the authors did not account for the semi-competing risk of death nor did they examine differential rankings of predictors by race/ethnic and gender. Failure to account for the semi-competing risk of mortality when studying older populations can bias results and overestimate the risk of disease [12]. In addition, documented differences in longevity and dementia incidence among race/ethnicity and gender groups could bias results as they absorb much of the variation in this prior study. Due to data limitations, this prior study also examined a smaller list of predictors, for example, using eiss 5 neighborhood socioeconomic status rather than a range of social and economic factors at the individual level. More recently, Aschwanden and colleagues [3] conducted a similar study using the HRS but did not did not account for the semi-competing risk of death nor did they investigate variation across racial/ethnic and gender groups. Understanding the relative importance and predictive power of these factors remains understudied and is critical for planning group-specific treatment strategies for those who may be at greater risk of dementia. We build on this emerging literature by investigating the relative contribution of 65 early-life, sociodemographic, health, behavioral, social, and genetic characteristics across the life course to dementia in the nationally representative and longitudinal US-based Health and Retirement Study (HRS). We estimated cause-specific hazard ratios of each characteristic for incident dementia while accounting for the semi-competing risk of death. We then compared these results to those obtained within a data-driven framework by utilizing random survival forests for competing risks. All models were stratified by race/ethnicity and gender to examine the differential ranking of each predictor across these demographic strata.
Results
The analytic sample for the primary analysis was comprised of 7,908 respondents with an average age at baseline of 65.6 years (standard error = 0.15). Overall, 37.4% of respondents were non-Hispanic white men; 49.9% of respondents were non-Hispanic white women; 4.5% of respondents were non-Hispanic black men; and non-Hispanic black women comprised 8.2% of the sample. Summary characteristics for the analytic HRS sample at baseline are shown in Table S1. Correlations between all predictors by race/ethnicity and gender are presented in Fig S1. Fig 1 and Supplemental Table S2 present the hazard ratios (HRs) and 95% confidence intervals (CIs) for each risk factor on dementia examined independently in Fine and Gray models eiss 6 stratified by race/ethnicity and gender. Risk factors are categorized by domain and ranked from largest increase in risk of dementia (top of figure) to largest decrease in risk of dementia (bottom of figure). Risk factors with CIs that cross one are not considered statistically significant at the P value = 0.05 level.
Fig 1. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Predictors with HRs equal to zero are excluded from the figure but retained in Table S3. Models use full analytic sample and classify dementia using the Langa-Weir classification scheme. Three of the top 10 characteristics for non-Hispanic white men and women were consistent (lower education, lower neighborhood safety, received food stamps) whereas four were consistent for non-Hispanic white and black men (lower education, received food stamps, reported pain, reported Medicaid) and four of the top 10 characteristics were consistent for non-Hispanic white and black women (lower education, received food stamps, heavy alcohol use, and reported headaches). Across racial/ethnic and gender groups, lower education and receipt of food stamps were the only characteristics that consistently ranked in the top 10 of predictors; receipt of food stamps was the only characteristic that consistently ranked in the top five of predictors. These results were consistent when comparing HRs obtained from cause-specific hazard models (Supplemental Table S3) with the exception of lower education, which did not rank in the top 10 of predictors for non-Hispanic white women. However, it is evident that the point estimates and CIs for most predictors overlap across racial/ethnic and gender groups as shown in Fig S2 eiss 7 suggesting that the differences in the associated hazards across racial/ethnic groups are not statistically significant at the P value = 0.05 level. Results from the random survival forests analysis for competing risks are shown in Fig 2. Blue bars indicate predictors with positive variable importance values; red bars indicate predictors with negative variable importance values, which in this context can be considered statistically insignificant. The positive length of the bar indicates the importance of each predictor. The top predictors across racial/ethnic and gender groups differed from those obtained in the Fine and Gray models, and were more consistent across racial/ethnic groups in the random survival forests analysis. Whereas lower education and lower neighborhood safety were the only consistently ranked predictors in the top 10 across race/ethnicity and gender groups in the Fine and Gray models, lower education and loneliness were consistently ranked in the top 10 in the random survival forests analysis. Lower age at first birth and lower levels of respondent’s mother’s education appeared in the top 10 for non-Hispanic white and black women. Lower income and self-reported health ranked in the top 10 for all groups with the exception of non-Hispanic black men whereas lower wealth ranked in the top 10 for all groups with the exception of non-Hispanic white women. Fig 3 shows the rank order for predictors, overall, and for each race/ethnicity and gender group. The overall rank order was determined by calculating the unweighted mean of predictor rank orders within each of the four demographic strata, and sorting from lowest to highest mean (i.e., highest rank to lowest rank). The values of the overall rank order in Fig 3 do not represent the means themselves but instead correspond to these rankings. These results illustrate the variation across and within racial/ethnic groups. For example, whereas lower wealth is respectively ranked as the second and fifth leading predictor for non-Hispanic white men and non-Hispanic black women, lower wealth ranked 13 th for non-eiss 8 Hispanic white women and 10 th for non-Hispanic black men. Food insecurity, which ranked 10 th overall, was ranked 20 th and 23 rd for non-Hispanic white men and women, but 11 th and 7 th for non-Hispanic black men and women. Fig 2. Variable importance plot for 65 characteristics predicting dementia obtained from random survival forests for competing risks stratified by race and gender.
Model uses full analytic sample and classifies dementia using the Langa-Weir classification scheme.
Fig 3. Rank order of predictors obtained from random survival forests for competing risks stratified by race and gender.
Model uses full analytic sample and classifies dementia using the Langa-Weir classification scheme. In sensitivity analyses among a subsample of 6,746 respondents who were 70+ years of age at baseline and had at least one measure of all four classification schemes for dementia, we observed that the consistency of predictors with the highest HRs from the Fine-Gray models varied by race/ethnicity and gender group. For non-Hispanic white men, four of the top five predictors were consistent across all four classification schemes (lower education, lower neighborhood safety, receipt of food stamps, Medicaid, and psychiatric illness; Figs S3-S6 and Tables S4-S7). Among non-Hispanic white women, only headaches were among the top five predictors with the highest HRs across all four classification schemes (Fig S3-S6). For non-Hispanic black men, only Medicaid was consistently ranked in the top five predictors with the highest HRs and among non-Hispanic black women, self-reported persistent dizziness was the only predictor consistently ranked in the top five (Fig S3-S6). For the random survival forests eiss 9 analysis, three of the top five predictors (lower education, lower income, loneliness) were consistent overall when using the four different classification schemes (Figs S7-S13). When used as the outcome in the Fine-Gray and random survival forests analyses, the Langa-Weir classifier, which does not account for race/ethnicity, gender, or education, resulted in more socioeconomic risk factors being ranked in the top five. Models which used the Hurd, Expert, and LASSO classifiers, which do account for respondent demographics, were more likely to produce health, behavioral, and genetic risk factors as top predictors.
Discussion
In this 14-year population-based study of older adults in the US with available polygenic score data, we found that the relative importance of risk factors for predicting dementia varied across racial/ethnic and gender groups using two distinct methodologies. We also found the predictor rankings to vary based on the type of dementia classification used. Although not all observed differences were statistically significant, our stratified models may offer insight into substantive differences in the relative importance of risk factors across racial/ethnic and gender groups. We observed variation in the rank order of predictors across and within racial/ethnic and gender groups in both the Fine-Gray models and random survival forests. The consistency of our primary results across both analyses suggests that our findings are robust to these two distinct approaches. However, in our sensitivity analyses in which we compared four alternative classification schemes for dementia, we found the results to vary which may be due to the different criteria used in each of these classification schemes for dementia. The low ranking of genetic predictors was apparent across our analyses, whereas we saw stronger associations between characteristics measured in mid- or later-life particularly those in eiss 10 the economic domain. Lower levels of education and receipt of food stamps were the only characteristics that consistently ranked in the top 10 of predictors for all groups in the random survival forests analysis. There was heterogeneity within and outside of the top 10 predictors highlighting the importance of identifying effective methods to promote health and mitigate dementia burden and its risk factors within racial/ethnic and gender groups. The results obtained in our analyses were similar to those reported by Casanova and colleagues [11] and Aschwanden et al. [3] but our account of the competing risk of mortality and stratification by race/ethnicity and gender may offer more accurate estimates and provide additional insight into the differential ranking of risk factors within these groups. In their recent study, Aschwanden and colleagues [3] used Cox proportional hazard models and a machine-learning approach to predict cognitive impairment and dementia in the HRS over a 10-year period. The authors used 52 multi-domain risk factors in their random survival forests analysis and found that increases in body mass index, higher levels of emotional distress, diabetes, self-reporting race as black, and higher reports of childhood trauma were the top five predictors of dementia over the study period. The authors incorporated two polygenic scores—one for Alzheimer’s disease which included the apolipoprotein e4 allele and one which did not. The authors then examined a subset of top predictors from their random survival forests model in a semi-parametric survival analysis framework using Cox proportional hazards model. Of the six predictors the authors examined, only emotional distress was significantly associated with incident dementia. Despite similar methodologies and data, none of the top five predictors from Aschwanden and colleagues’ study appeared in the overall top 10 from our random survival forests model and only two risk factors (education and self-reported childhood health) ranked in eiss 11 both top 10 lists. In our random survival forests analysis which accounted for the competing risk of death, we found that psychiatric illness—which is different from but most comparable to the author’s emotional distress measure—ranked fourth among non-Hispanic white men, 12 th among non-Hispanic white women, 62 nd among non-Hispanic black men, and 41 st among non-Hispanic black women. Interestingly, however, the HR for emotional distress obtained from Aschwanden and colleagues’ study (HR: 1.85; 95%CI: 1.41, 2.44) overlapped with the HR for psychiatric illness among non-Hispanic white men in our independent Fine-Gray model (HR: 1.61; 95%CI: 1.13, 2.31) whereas the HR for psychiatric illness was not statistically significant for any other subgroup in our analysis. Moreover, the prior study reported increasing trajectories of body mass index as the top predictor of dementia in their random survival forests analysis whereas in our study, which used baseline body mass index in the year 2000, body mass index was ranked overall as the 59 th predictor out of 65 and at best, ranked 29 th for non-Hispanic black women. The relationship between body mass index and dementia is complex [13-15], with investigators reporting in one study that midlife obesity was associated with an increased risk of dementia compared to those with normal body mass index whereas this association reversed in later-life [14]. It is possible that, by not accounting for the competing risk of mortality, the top predictors reported in Aschwanden and colleagues’ study are driven by their association with mortality although we did not test this directly. As noted above, a major strength of this study is our account of the competing risk of death. Recent studies have reported that studying age-related conditions, including dementia, while not accounting for the competing risk of death may produce biased or misleading results [16, 17]. An additional strength of our study is the inclusion of 65 risk factors spanning sociodemographic, early-life, economic, health, behavioral, social, and genetic risk factor eiss 12 domains across the life course. Our inclusion of genetic risk factors was in the form of polygenic scores which are able to capture genotypic variation across multiple genetic loci compared to individual genotypes. In addition, we compared our primary results using the Langa-Weir classification scheme to more recent approaches which may be better suited to studying disparities in dementia across racial/ethnic groups as well as among adults who vary with respect to socioeconomic status [18, 19]. This study also had several limitations. First, there were several risk factors in the report by the Lancet Commission on Dementia Prevention and Care that are not available in the HRS. These measures include for example, dietary quality, exposure to environmental contaminants, and questions about cognitive training and stimulation. Second, although we used clinically validated cut points derived from the ADAMS for assessing dementia in the HRS cohort, these classifications may be subject to measurement error. This measurement error could affect the coefficient estimates and rankings if a large enough sample of respondents were misclassified with respect to their cognitive status. We conducted sensitivity analyses using three alternative classification schemes for dementia which may alleviate some of this concern. Third, as with any tree-based approach such as the random forest algorithm, variables with a wider range and therefore more points at which they can be split, tend to have higher predictive power [20]. We addressed this limitation by standardizing continuous measures to make them as equivalent as possible across our study. We identified heterogeneity in the association between dementia and its risk factors within racial/ethnic and gender groups using a more traditional approach to account for competing risks (the Fine-Gray model) as well as a more contemporary data-driven approach (random survival forests for competing risks). These results may be useful for understanding and eiss 13 further exploring recent reports documenting disparity trends in dementia across racial/ethnic and gender groups [7, 21, 22]. We advise caution in treating these results with a causal interpretation and instead suggest that these results can be used for hypothesis generation and to inform future observational and clinical studies to identify the multiple pathways through which these risk factors may be differentially associated with the risk of dementia across demographic strata. Materials and Methods Study population
The HRS is a nationally representative and longitudinal study of more than 30,000 community-dwelling US adults aged 50+ years and their spouses of any age. Since 1992, the HRS has biennially collected economic, social, and health information from respondents who undergo detailed telephone or in-person interviews. Respondents who are unable or unwilling to participate may be surveyed by a proxy respondent, typically a spouse or adult child, who completes the survey on their behalf. The HRS is under current IRB approval at the University of Michigan and the National Institute on Aging (NIA) with support from the NIA (NIA; U01AG009740) and the Social Security Administration [23]. Polygenic score data were available for HRS respondents who consented and provided salivary DNA from 2006 through 2012 [24]. We used a base year of 2000 with follow-up through 2014 during which time cognitive information was consistently ascertained for community-dwelling and nursing home residents. We restricted the analytic sample to non-Hispanic men and women aged 51 years and older who were dementia-free at baseline in 2000 who had polygenic score data, a valid sampling weight, eiss 14 and at least one measure of cognitive function over the study period (2000 to 2014). We further excluded respondents who self-reported their race as “Other Race” due to low sample sizes.
Measures Outcome.
Different protocols were used to assess cognitive function among self- and proxy- respondents in the HRS [25]. Among self-respondents, cognitive function was determined through a series of cognitive tests which included immediate and delayed 10-noun free recall tests (range: 0-10 points each), a serial 7s subtraction test (range: 0-5 points), and a backwards counting test (range: 0-2 points). Scores ranged from 0 to 27, with higher scores reflecting better cognitive performance. Among respondents surveyed through a proxy, cognitive scores were based on the proxy’s assessment of the respondent’s memory (range: 0-4; excellent, very good, good, fair, poor), limitations in five instrumental activities of daily living (range: 0-5; managing money, taking medication, preparing hot meals, using phones and doing groceries), and the interviewer’s assessment of the respondent’s difficulty completing the interview due to cognitive limitations (range: 0-2; none, some, prevents completion) to produce a score ranging from 0 to 11, with higher scores reflecting a higher degree of impairment. Cut points for dementia using these scales in the HRS were validated against the Aging, Demographics, and Memory Study (ADAMS). The ADAMS is a clinical substudy of 856 HRS respondents who underwent extensive in-home neuropsychological and clinical assessments [26]. We used the Langa-Weir approach [27] in our primary analysis to classify respondents with dementia (self-respondent: 0-6 out of 27; proxy: 6-11 out of 11). In sensitivity analyses, we used three additional classification schemes for dementia which are reported to have greater sensitivity to racial/ethnic and sociodemographic disparities [18, 19]. These alternative schemes, referred to as the Hurd Model, the Expert Model, and the eiss 15 LASSO Model were also validated against the ADAMS as described elsewhere [19]. Our sensitivity analyses were conducted in a subsample of respondents who, in addition to the inclusion criteria for the analytic sample, were 70 years or older at baseline and had available information on all four dementia classification methods (which were estimated among HRS respondents aged 70+ years).
Risk factors
We conducted a thorough review of the articles cited in the Lancet Commission’s report and selected 65 risk factors that were available in the HRS. We classified risk factors into seven domains: sociodemographic (1), early-life (2), economic (3), health (4), behavioral (5), social ties (7), and genetic markers (8). A complete list of risk factors, their definition, and coding is provided in the supplemental S1 Appendix. All risk factors measured on a continuous scale were standardized to a normal distribution (mean = 0, standard deviation = 1). Risk factors were coded such that higher scores reflected a higher degree of risk. All risk factors were measured in 1998 or 2000.
Statistical Analysis
All statistical analysis was performed in R version 3.6.1 [28]. All analyses used respondent-level sampling weights and, where appropriate, included robust standard errors to account for the clustering of individuals within households in the HRS. In preparing the data file, we excluded risk factors that were missing among 20% or more of respondents (see Table S1). Missing data values for the remaining predictors were imputed using a non-parametric approach implemented with the R package ‘missForest’ with five iterations each fit with 500 trees [29]. We examined associations between all predictors by creating correlation matrices for all risk factors across racial/ethnic and gender groups. The distribution of all 65 risk factors at baseline eiss 16 was examined by computing the prevalence or mean and standard deviation of each risk factor after imputation. We used inverse probability weighting to account for selection into the HRS genetic sample. This process upweighted respondents with a lower propensity for providing genetic data, creating a pseudo population which more closely reflects the representativeness of the HRS sample [30, 31]. The respondent-level sampling weights used to generate new base weights for our analysis were calculated and provided by the HRS investigators. Specifically, we used the respondent-level sampling weights that account for both community-dwelling respondents and those residing in nursing homes. All analysis used these We examined bivariate associations between each predictor and dementia using the method proposed by Fine and Gray [32] to account for the semi-competing risk of death. This approach accounts for the fact that respondents who die prior to incident dementia are no longer considered at risk for dementia, as opposed to methods such as the Kaplan-Meier estimator which treats the semi-competing risk of death as noninformative censoring which may bias results and overestimate associations between risk factors and dementia [12]. Respondents were observed from baseline until incident dementia, death, or censoring. We used age as the timescale (i.e., age at first dementia diagnosis, age at death, age at last visit) due to its strong association with dementia. All models were stratified by race/ethnicity and gender due to known differences in longevity and dementia risk across these strata [33, 34]. We separately examined bivariate associations between each predictor and dementia following the same procedures as described above but using cause-specific hazard models as recommended by Latouche and colleagues [35]. More details on the Fine-Gray model are provided in the supplemental S2 Appendix eiss 17 We then used random survival forests for competing risks [36] to simultaneously investigate the relative importance of each predictor for dementia across racial/ethnic and gender groups while accounting for the semi-competing risk of death. Age was used as the timescale. Random survival forests are an extension of the random forest algorithm, an ensemble-based classification method which fits a series of classification and regression trees and then pools results across the trees [37]. We implemented this approach using the R package ‘randomForestSRC’ with 1,000 trees [38]. More details on the random survival forests procedure is provided in the supplemental S2 Appendix eiss 18
References l l ll l lll lll l ll lll ll lll lll ll lll l l ll l lll llll ll l lll ll llll lll lllll
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Hazard Ratio P r ed i c t o r NH White Women (n=3946) l llll l lll lll l ll llllll l lll llll ll lll ll lll l ll ll llll ll lll lll l lll ll
No InsuranceVeteranCancerFood InsecurityRetiredHeart ProblemsHigher Coronary Artery Disease PGSFatigueHigher Age at Last BirthHigher BMIEver WidowedLower Education PGSLower General Cognition PGSLower Height PGSHeavy Alcohol UseLower Neighborhood SafetyHigher Diabetes PGSMedicareEver DivorcedNot Married/PartneredLess ReligiousHigher Parity PGSHypertensionLower Age at First Birth PGSLower SR HearingHigher Myocardial Infarction PGSDiabetesLower Age at First BirthLow/No Vigorous Physical ActivityArthritisForeign BornHigher AD PGSStrokeChildlessPsychiatric IllnessLower Longevity PGSLower IncomeLower WealthLower SR Childhood SESActive SmokerNo Friends NearbyNo Relatives NearbyHigher ParityLower SR Childhood HealthLower Mother's EducationDizzinessHeadachesWheezingLung DiseaseLonelyEver SmokedLower SR HealthSouthern BornBack PainLower Father's EducationLower SR VisionPainShort of BreathMedicaidLower EducationReceived Food StampsLower Father Occupational Status
Hazard Ratio P r ed i c t o r NH Black Men (n=353) l l llll lll ll ll ll lll ll ll l lll llll l ll ll l ll lllll llll ll ll ll l llll ll ll lll
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Hazard Ratio P r ed i c t o r NH Black Women (n=649) ll ll ll l
Early−LifeSociodemographic EconomicSocial Ties BehaviorsHealth Genetic
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Variable Importance P r ed i c t o r NH White Men (n=2960)
MedicareEver SmokedLower Longevity PGSLess ReligiousHigher ParityWheezingShort of BreathLung DiseaseLow/No Vigorous Physical ActivityActive SmokerBack PainNo Relatives NearbyArthritisHigher BMILower General Cognition PGSHigher Myocardial Infarction PGSReceived Food StampsLower Age at Menopause PGSEver DivorcedChildlessVeteranHigher AD PGSPainNo Friends NearbyHeavy Alcohol UseLower Age at First Birth PGSUnemployedRetiredStrokeEver WidowedNot Married/PartneredHypertensionLower Height PGSForeign BornLower SR Childhood HealthMedicaidCancerHigher Diabetes PGSHigher Coronary Artery Disease PGSDizzinessLower Age at Menarche PGSHeart ProblemsFood InsecurityHigher Parity PGSNo InsuranceLower SR Childhood SESLower Neighborhood SafetyLower Education PGSLower SR HearingDiabetesLower SR VisionSouthern BornLower WealthPsychiatric IllnessLower Father's EducationLower Father Occupational StatusHigher Age at Last BirthLower SR HealthHeadachesLower Mother's EducationLower Age at First BirthLower IncomeFatigueLonelyLower Education
Variable Importance P r ed i c t o r NH White Women (n=3946)
Lower General Cognition PGSPsychiatric IllnessEver DivorcedWheezingLower Age at First BirthChildlessPainHigher Diabetes PGSFatigueArthritisEver WidowedMedicareLower Neighborhood SafetyForeign BornNot Married/PartneredHeart ProblemsDizzinessLower SR HearingDiabetesCancerStrokeLung DiseaseUnemployedHypertensionLower Education PGSLow/No Vigorous Physical ActivityNo Friends NearbyActive SmokerHeavy Alcohol UseLower Age at First Birth PGSBack PainLower SR Childhood SESMedicaidShort of BreathHigher BMILower Longevity PGSEver SmokedHigher AD PGSLower Height PGSLess ReligiousNo Relatives NearbyHigher Myocardial Infarction PGSHigher Parity PGSHigher ParityHeadachesSouthern BornLower IncomeReceived Food StampsLower SR HealthLower Mother's EducationHigher Age at Last BirthNo InsuranceFood InsecurityLower WealthHigher Coronary Artery Disease PGSLower Father Occupational StatusLower SR Childhood HealthLower Father's EducationRetiredLonelyLower SR VisionLower EducationVeteran
Variable Importance P r ed i c t o r NH Black Men (n=353)
Lower General Cognition PGSMedicareLower Age at Menarche PGSHigher AD PGSNo InsuranceHigher Myocardial Infarction PGSActive SmokerLower Longevity PGSArthritisFatigueWheezingBack PainLow/No Vigorous Physical ActivityLower Age at Menopause PGSHeadachesHigher Diabetes PGSLower Age at First Birth PGSHigher BMICancerDiabetesNot Married/PartneredVeteranLung DiseaseUnemployedPsychiatric IllnessLower Height PGSLower Education PGSEver SmokedNo Friends NearbyChildlessEver WidowedShort of BreathSouthern BornLower Neighborhood SafetyLess ReligiousLower SR Childhood SESEver DivorcedHeart ProblemsForeign BornStrokeRetiredLower Father Occupational StatusHigher Parity PGSHigher Coronary Artery Disease PGSReceived Food StampsNo Relatives NearbyPainHigher Age at Last BirthHeavy Alcohol UseMedicaidLower SR VisionLower SR HearingDizzinessLower Father's EducationLower SR Childhood HealthLower Age at First BirthHypertensionLonelyFood InsecurityLower Mother's EducationLower WealthHigher ParityLower IncomeLower SR HealthLower Education
Variable Importance P r ed i c t o r NH Black Women (n=649)
Fig 2 O v e r a ll NH W h i t e M en NH W h i t e W o m en NH B l a ck M en NH B l a ck W o m en Low/No Vigorous Physical ActivityArthritisLower Age at Menopause PGSMedicareLower General Cognition PGSChildlessHigher BMILower Age at First Birth PGSWheezingHigher Diabetes PGSEver DivorcedNot Married/PartneredLower Age at Menarche PGSBack PainEver SmokedCancerLower Longevity PGSActive SmokerForeign BornUnemployedLung DiseaseEver WidowedLower Height PGSHigher Myocardial Infarction PGSFatigueNo Relatives NearbyShort of BreathLess ReligiousLower Education PGSHeart ProblemsNo Friends NearbyHigher AD PGSHypertensionNo InsuranceHigher ParityPainLower SR Childhood SESDiabetesVeteranHigher Parity PGSHeadachesHeavy Alcohol UseStrokePsychiatric IllnessDizzinessLower Neighborhood SafetyHigher Coronary Artery Disease PGSReceived Food StampsSouthern BornLower Age at First BirthRetiredMedicaidLower SR HearingLower Father Occupational StatusLower Father's EducationFood InsecurityLower SR Childhood HealthHigher Age at Last BirthLower Mother's EducationLower SR VisionLower SR HealthLower IncomeLower WealthLonelyLower Education 604020
VIMP Rank Order
Fig 3 eiss 1
Supporting information
S1 Fig. Correlation matrices for 65 predictors stratified by race and gender. S2 Fig. Comparison of hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Model uses full analytic sample and classifies dementia using the Langa-Weir classification scheme.
S3 Fig. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from cause-specific regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Langa-Weir classification scheme. Predictors with HRs equal to zero are excluded from the figure but retained in Table S5.
S4 Fig. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Hurd classification scheme. Predictors with HRs equal to zero are excluded from the figure but retained in Table S6.
S5 Fig. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Expert eiss 2 classification scheme. Predictors with HRs equal to zero are excluded from the figure but retained in Table S7.
S6 Fig. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the LASSO classification scheme. Predictors with HRs equal to zero are excluded from the figure but retained in Table S8.
S7 Fig. Variable importance plot for 65 characteristics predicting dementia obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Langa-Weir classification scheme.
S8 Fig. Variable importance plot for 65 characteristics predicting dementia obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Hurd classification scheme.
S9 Fig. Variable importance plot for 65 characteristics predicting dementia obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Expert classification scheme. eiss 3
S10 Fig. Variable importance plot for 65 characteristics predicting dementia obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the LASSO classification scheme.
S11 Fig. Rank order of predictors obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Langa-Weir classification scheme.
S12 Fig. Rank order of predictors obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Hurd classification scheme.
S13 Fig. Rank order of predictors obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the Expert classification scheme.
S14 Fig. Rank order of predictors obtained from random survival forests for competing risks stratified by race and gender.
Model uses restricted analytic sample and classifies dementia using the LASSO classification scheme. eiss 4
S1 Table. Descriptive characteristics of the full analytic sample, HRS 2000.
Characteristic Statistic * % Missing Sociodemographic
Baseline Age 65.59 (0.15) 0.000 Female, % 0.56 (0.01) 0.000 Non-Hispanic Black, % 0.10 (0.00) 0.000 Foreign Born, % 0.08 (0.01) 0.001 Southern Born, % 0.31 (0.01) 0.001 Veteran, % 0.28 (0.01) 0.001 Childless, % 0.03 (0.00) 0.001 Parity 2.94 (0.02) 0.001 Age at First Birth 24.90 (0.08) 0.000 Age at Last Birth 31.98 (0.10) 0.000
Early-Life
Mother's Education, years 9.64 (0.05) 0.08 Father's Education, years 9.26 (0.05) 0.123 Father's Occupational Status, unit 2.15 (0.03) 0.132 SR Childhood Health 4.27 (0.01) 0.013 SR Childhood SES 1.80 (0.01) 0.013 Education, years 3.32 (0.02) 0.000
Economic
Food Insecurity, % 0.04 (0.00) 0.005 Income, dollars 66270.17 (2039.69) 0.000 Neighborhood Safety 1.91 (0.01) 0.006 Wealth, dollars 371402.5 (13790.59) 0.000 Medicaid, % 0.04 (0.00) 0.001 Medicare, % 0.45 (0.01) 0.001 No Insurance, % 0.37 (0.01) 0.021 Received Food Stamps, % 0.03 (0.00) 0.006 Retired, % 0.52 (0.01) 0.000 Unemployed, % 0.01 (0.00) 0.000
Health
Arthritis, % 0.49 (0.01) 0.001 Back Pain, % 0.31 (0.01) 0.000 Cancer, % 0.11 (0.00) 0.001 Diabetes, % 0.11 (0.00) 0.000 Dizziness, % 0.09 (0.00) 0.000 Fatigue, % 0.14 (0.01) 0.000 Headaches, % 0.08 (0.00) 0.000 Heart Problems, % 0.17 (0.01) 0.000 Hypertension, % 0.42 (0.01) 0.001 SR Health 3.53 (0.02) 0.000 SR Hearing 4.47 (0.02) 0.001 SR Vision 4.36 (0.01) 0.000 Lung Disease, % 0.05 (0.00) 0.000 eiss 5 Pain, % 0.26 (0.01) 0.000 Psychiatric Illness, % 0.08 (0.00) 0.000 Short of Breath, % 0.13 (0.00) 0.000 Stroke, % 0.05 (0.00) 0.000 Wheezing, % 0.10 (0.00) 0.000 Cataracts [Excluded] 0.545 Falls [Excluded] 0.522 Glaucoma [Excluded] 0.541 Swelling [Excluded] 0.448
Behaviors
Active Smoker, % 0.14 (0.01) 0.000 Ever Smoked, % 0.59 (0.01) 0.000 Heavy Alcohol Use, % 0.06 (0.00) 0.001 BMI 27.27 (0.07) 0.01 Low/No Vigorous Physical Activity, % 0.5 (0.01) 0.000
Social Connections
Ever Divorced, % 0.29 (0.01) 0.000 Ever Widowed, % 0.23 (0.01) 0.000 Religious 2.52 (0.01) 0.001 Lonely, % 0.15 (0.01) 0.038 No Friends Nearby, % 0.69 (0.01) 0.005 No Relatives Nearby, % 0.30 (0.01) 0.006 Not Married/Partnered, % 0.33 (0.01) 0.001
Genetic
AD PGS 0.00 (0.01) 0.000 Coronary Artery Disease PGS -0.01 (0.01) 0.000 Diabetes PGS 0.01 (0.01) 0.000 Myocardial Infarction PGS 0.01 (0.01) 0.000 Parity PGS -0.01 (0.01) 0.000 Age at First Birth PGS 0.00 (0.01) 0.000 Age at Menarche PGS 0.00 (0.01) 0.000 Age at Menopause PGS 0.00 (0.01) 0.000 Education PGS 0.00 (0.01) 0.000 General Cognition PGS 0.00 (0.01) 0.000 Height PGS 0.00 (0.01) 0.000 Longevity PGS 0.00 (0.01) 0.000 * Weighted means or proportions with standard errors listed in parentheses. eiss 6
S2 Table. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use full analytic sample and classify dementia using the Langa-Weir classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.13 (0.73, 1.74) 1.28 (0.83, 1.98) 1.07 (0.37, 3.13) 0.70 (0.28, 1.76) Southern Born 1.11 (0.89, 1.38) 1.15 (0.95, 1.38) 1.30 (0.57, 2.97) 1.22 (0.81, 1.83) Veteran 0.86 (0.69, 1.07) 0.35 (0.09, 1.33) 0.65 (0.43, 0.99) 1.05 (0.21, 5.13) Childless 0.95 (0.58, 1.56) 0.72 (0.38, 1.38) 1.10 (0.34, 3.58) 0.73 (0.57, 0.95) Higher Parity 1.04 (0.84, 1.28) 1.09 (0.90, 1.31) 1.17 (0.97, 1.40) 1.15 (0.97, 1.37) Lower Age at First Birth 1.06 (0.87, 1.30) 1.31 (1.07, 1.61) 1.03 (0.70, 1.52) 1.12 (0.89, 1.42) Higher Age at Last Birth 1.07 (0.87, 1.32) 1.11 (0.93, 1.33) 0.88 (0.65, 1.19) 0.98 (0.79, 1.23)
Early-Life
Lower Mother's Education 1.21 (0.95, 1.54) 1.16 (0.91, 1.49) 1.20 (0.84, 1.70) 1.27 (0.91, 1.76) Lower Father's Education 1.15 (0.94, 1.42) 1.11 (0.86, 1.43) 1.33 (0.87, 2.04) 1.30 (0.96, 1.75) Lower Father's Occupational Status 1.18 (0.95, 1.46) 1.11 (0.93, 1.32) 2.20 (0.75, 6.42) 1.70 (0.81, 3.56) Lower SR Childhood Health 1.24 (1.02, 1.50) 1.20 (0.92, 1.58) 1.17 (0.80, 1.72) 1.20 (0.94, 1.52) Lower SR Childhood SES 1.02 (0.84, 1.23) 1.12 (0.92, 1.37) 1.15 (0.73, 1.81) 1.20 (0.92, 1.58) Lower Education 1.56 (1.29, 1.89) 1.35 (1.10, 1.65) 1.59 (1.03, 2.47) 1.47 (1.12, 1.92)
Economic
Food Insecurity 0.75 (0.40, 1.43) 0.78 (0.52, 1.17) 0.74 (0.44, 1.26) 0.68 (0.52, 0.91) Lower Income 1.18 (1.02, 1.37) 1.36 (1.14, 1.62) 1.13 (0.90, 1.42) 1.17 (1.07, 1.28) Lower Neighborhood Safety 1.44 (0.95, 2.17) 1.37 (0.69, 2.71) 0.94 (0.57, 1.55) 1.22 (0.91, 1.63) Lower Wealth 1.21 (0.98, 1.51) 1.14 (0.85, 1.51) 1.14 (0.91, 1.42) 1.15 (1.02, 1.30) Medicaid 2.04 (1.09, 3.81) 1.07 (0.67, 1.70) 1.57 (0.84, 2.95) 1.36 (1.01, 1.81) Medicare 0.77 (0.63, 0.95) 0.82 (0.62, 1.08) 0.95 (0.59, 1.52) 0.89 (0.67, 1.18) No Insurance 0.93 (0.76, 1.14) 0.93 (0.77, 1.12) 0.58 (0.38, 0.89) 0.71 (0.51, 0.99) Received Food Stamps 1.47 (0.58, 3.75) 1.41 (0.46, 4.34) 1.60 (0.93, 2.76) 1.39 (1.00, 1.94) Retired 0.84 (0.68, 1.04) 0.94 (0.77, 1.13) 0.76 (0.49, 1.18) 0.82 (0.63, 1.07) Unemployed 0.99 (0.27, 3.55) 0.94 (0.23, 3.79) 0.00 (0.00, 0.00) 1.25 (0.53, 2.94)
Health eiss 7 Arthritis 0.92 (0.75, 1.12) 1.11 (0.93, 1.32) 1.06 (0.70, 1.62) 0.98 (0.74, 1.28) Back Pain 1.07 (0.87, 1.33) 0.99 (0.80, 1.22) 1.33 (0.86, 2.06) 0.90 (0.67, 1.22) Cancer 0.90 (0.67, 1.19) 0.82 (0.64, 1.05) 0.71 (0.33, 1.49) 0.91 (0.56, 1.48) Diabetes 1.06 (0.81, 1.39) 1.05 (0.81, 1.36) 1.02 (0.56, 1.87) 1.06 (0.77, 1.44) Dizziness 1.21 (0.88, 1.66) 1.17 (0.83, 1.66) 1.20 (0.68, 2.11) 1.51 (1.09, 2.08) Fatigue 1.15 (0.83, 1.60) 1.24 (0.96, 1.59) 0.86 (0.44, 1.67) 1.24 (0.88, 1.73) Headaches 1.01 (0.59, 1.72) 1.65 (1.14, 2.39) 1.22 (0.71, 2.12) 1.35 (0.88, 2.09) Heart Problems 1.03 (0.82, 1.28) 0.97 (0.78, 1.20) 0.78 (0.39, 1.55) 1.17 (0.82, 1.67) Hypertension 0.95 (0.77, 1.16) 1.04 (0.86, 1.25) 1.00 (0.66, 1.52) 1.30 (0.96, 1.77) Lower SR Health 1.24 (1.00, 1.54) 1.24 (0.96, 1.61) 1.29 (0.83, 2.01) 1.35 (1.01, 1.79) Lower SR Hearing 1.17 (0.94, 1.46) 1.08 (0.87, 1.33) 1.01 (0.65, 1.58) 0.98 (0.72, 1.33) Lower SR Vision 1.13 (0.93, 1.38) 1.10 (0.92, 1.32) 1.37 (0.81, 2.29) 1.09 (0.82, 1.43) Lung Disease 0.71 (0.43, 1.18) 1.14 (0.61, 2.12) 1.22 (0.56, 2.66) 0.97 (0.44, 2.13) Pain 1.22 (0.96, 1.54) 1.12 (0.91, 1.38) 1.38 (0.85, 2.24) 1.18 (0.89, 1.57) Psychiatric Illness 1.61 (1.13, 2.31) 1.21 (0.95, 1.54) 1.12 (0.41, 3.09) 1.19 (0.77, 1.84) Short of Breath 1.15 (0.86, 1.53) 1.11 (0.80, 1.54) 1.48 (0.86, 2.55) 1.26 (0.92, 1.74) Stroke 1.13 (0.81, 1.59) 1.28 (0.78, 2.10) 1.08 (0.53, 2.19) 0.99 (0.54, 1.85) Wheezing 1.10 (0.83, 1.46) 1.17 (0.78, 1.75) 1.22 (0.69, 2.16) 1.15 (0.81, 1.65)
Behaviors
Active Smoker 1.23 (0.91, 1.67) 1.15 (0.71, 1.86) 1.14 (0.77, 1.69) 1.01 (0.66, 1.55) Ever Smoked 1.10 (0.87, 1.39) 1.27 (0.68, 2.38) 1.02 (0.85, 1.22) 0.98 (0.75, 1.29) Heavy Alcohol Use 0.98 (0.69, 1.39) 0.93 (0.45, 1.89) 1.57 (0.53, 4.69) 1.44 (0.65, 3.19) Higher BMI 1.01 (0.78, 1.31) 0.89 (0.60, 1.33) 0.97 (0.80, 1.18) 1.04 (0.81, 1.33) Low/No Vigorous Physical Activity 1.05 (0.86, 1.29) 1.05 (0.68, 1.61) 1.01 (0.85, 1.21) 1.00 (0.76, 1.33)
Social Connections
Ever Divorced 1.08 (0.85, 1.37) 1.17 (0.89, 1.54) 0.95 (0.59, 1.53) 1.04 (0.75, 1.44) Ever Widowed 0.91 (0.66, 1.24) 0.93 (0.79, 1.10) 0.90 (0.53, 1.53) 1.02 (0.77, 1.34) Less Religious 0.98 (0.81, 1.18) 0.92 (0.75, 1.12) 0.98 (0.54, 1.76) 0.57 (0.26, 1.25) Lonely 1.05 (0.77, 1.42) 1.35 (1.08, 1.69) 1.26 (0.81, 1.95) 1.21 (0.87, 1.69) No Friends Nearby 0.93 (0.75, 1.16) 1.12 (0.91, 1.37) 1.16 (0.72, 1.87) 1.10 (0.81, 1.49) No Relatives Nearby 1.14 (0.92, 1.41) 1.02 (0.86, 1.21) 1.17 (0.74, 1.83) 1.20 (0.92, 1.57) Not Married/Partnered 1.10 (0.80, 1.51) 1.02 (0.85, 1.24) 0.96 (0.60, 1.52) 0.96 (0.72, 1.27) eiss 8
Genetic
Higher AD PGS 0.95 (0.78, 1.15) 1.04 (0.88, 1.23) 1.08 (0.56, 2.06) 1.29 (0.74, 2.26) Higher Coronary Artery Disease PGS 0.97 (0.79, 1.19) 1.06 (0.87, 1.29) 0.81 (0.49, 1.34) 1.11 (0.90, 1.37) Higher Diabetes PGS 1.04 (0.87, 1.24) 1.09 (0.89, 1.34) 0.94 (0.54, 1.65) 1.07 (0.74, 1.55) Higher Myocardial Infarction PGS 0.90 (0.75, 1.09) 0.98 (0.83, 1.16) 1.01 (0.60, 1.72) 0.88 (0.66, 1.17) Higher Parity PGS 0.95 (0.78, 1.16) 1.01 (0.82, 1.25) 0.98 (0.63, 1.55) 0.99 (0.75, 1.30) Lower Age at First Birth PGS 0.94 (0.76, 1.15) 0.97 (0.82, 1.15) 1.01 (0.70, 1.45) 0.99 (0.76, 1.29) Lower Age at Menarche PGS — 1.11 (0.95, 1.29) — 0.98 (0.76, 1.25) Lower Age at Menopause PGS — 1.09 (0.94, 1.27) — 1.02 (0.80, 1.30) Lower Education PGS 0.93 (0.77, 1.12) 0.96 (0.79, 1.18) 0.92 (0.62, 1.37) 0.91 (0.69, 1.18) Lower General Cognition PGS 0.96 (0.78, 1.18) 1.00 (0.81, 1.24) 0.93 (0.60, 1.42) 1.01 (0.78, 1.30) Lower Height PGS 0.95 (0.78, 1.16) 0.96 (0.78, 1.18) 0.93 (0.64, 1.34) 1.15 (0.83, 1.59) Lower Longevity PGS 1.08 (0.87, 1.34) 1.03 (0.88, 1.22) 1.12 (0.81, 1.55) 0.99 (0.77, 1.27) eiss 9
S3 Table. Cause-specific hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from independent Cox models stratified by race and gender.
Models use full analytic sample and classify dementia using the Langa-Weir classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.07 (0.68, 1.67) 1.23 (0.79, 1.91) 1.12 (0.40, 3.19) 0.69 (0.26, 1.83) Southern Born 1.22 (0.97, 1.53) 1.21 (0.99, 1.47) 1.27 (0.56, 2.86) 1.23 (0.80, 1.87) Veteran 0.87 (0.69, 1.09) 0.36 (0.09, 1.38) 0.58 (0.36, 0.92) 1.03 (0.21, 5.07) Childless 0.96 (0.60, 1.55) 0.80 (0.43, 1.50) 1.07 (0.33, 3.49) 0.29 (0.04, 2.17) Higher Parity 1.07 (0.87, 1.33) 1.12 (0.93, 1.35) 1.14 (0.96, 1.37) 1.17 (0.98, 1.39) Lower Age at First Birth 1.20 (0.96, 1.51) 1.46 (1.18, 1.81) 1.00 (0.67, 1.50) 1.20 (0.95, 1.52) Higher Age at Last Birth 1.17 (0.93, 1.47) 1.16 (0.97, 1.39) 0.92 (0.67, 1.25) 1.01 (0.80, 1.27)
Early-Life
Lower Mother's Education 1.13 (0.86, 1.48) 1.08 (0.80, 1.45) 1.17 (0.81, 1.69) 1.27 (0.90, 1.80) Lower Father's Education 1.12 (0.88, 1.42) 1.13 (0.83, 1.52) 1.27 (0.82, 1.98) 1.28 (0.94, 1.74) Lower Father's Occupational Status 1.23 (0.98, 1.53) 1.13 (0.95, 1.35) 2.11 (0.78, 5.71) 1.78 (0.80, 3.96) Lower SR Childhood Health 1.22 (1.00, 1.48) 1.18 (0.89, 1.57) 1.17 (0.80, 1.70) 1.20 (0.94, 1.53) Lower SR Childhood SES 1.01 (0.83, 1.23) 1.16 (0.94, 1.43) 1.09 (0.69, 1.72) 1.14 (0.85, 1.53) Lower Education 1.62 (1.34, 1.97) 1.32 (1.07, 1.64) 1.58 (1.02, 2.44) 1.46 (1.11, 1.92)
Economic
Food Insecurity 0.66 (0.34, 1.27) 0.75 (0.49, 1.16) 0.71 (0.44, 1.17) 0.67 (0.50, 0.91) Lower Income 1.24 (1.06, 1.44) 1.35 (1.13, 1.62) 1.13 (0.90, 1.42) 1.17 (1.07, 1.28) Lower Neighborhood Safety 1.47 (0.95, 2.27) 1.45 (0.73, 2.90) 0.95 (0.59, 1.56) 1.26 (0.93, 1.70) Lower Wealth 1.31 (1.05, 1.65) 1.18 (0.89, 1.58) 1.11 (0.87, 1.42) 1.16 (1.02, 1.32) Medicaid 2.31 (1.20, 4.47) 1.14 (0.71, 1.84) 1.63 (0.86, 3.10) 1.44 (1.05, 1.97) Medicare 0.55 (0.42, 0.71) 0.57 (0.42, 0.78) 0.81 (0.48, 1.36) 0.69 (0.51, 0.92) No Insurance 0.96 (0.78, 1.18) 0.97 (0.80, 1.17) 0.61 (0.40, 0.94) 0.73 (0.52, 1.03) Received Food Stamps 1.80 (0.60, 5.38) 1.73 (0.57, 5.23) 1.63 (0.98, 2.72) 1.63 (1.22, 2.18) Retired 0.70 (0.56, 0.89) 0.93 (0.76, 1.14) 0.62 (0.38, 1.01) 0.75 (0.57, 1.00) Unemployed 1.03 (0.28, 3.81) 1.20 (0.31, 4.70) 0.00 (0.00, 0.00) 1.44 (0.77, 2.69)
Health eiss 10 Arthritis 0.93 (0.76, 1.13) 1.09 (0.91, 1.31) 1.02 (0.66, 1.57) 1.00 (0.75, 1.33) Back Pain 1.09 (0.88, 1.36) 1.02 (0.82, 1.26) 1.37 (0.88, 2.12) 0.93 (0.69, 1.26) Cancer 0.87 (0.66, 1.17) 0.79 (0.60, 1.04) 0.75 (0.36, 1.55) 1.01 (0.66, 1.54) Diabetes 1.10 (0.83, 1.46) 1.20 (0.92, 1.56) 1.09 (0.60, 1.96) 1.17 (0.86, 1.60) Dizziness 1.16 (0.83, 1.63) 1.19 (0.84, 1.70) 1.15 (0.62, 2.14) 1.55 (1.11, 2.16) Fatigue 1.23 (0.87, 1.75) 1.29 (1.00, 1.67) 0.93 (0.50, 1.72) 1.35 (0.96, 1.89) Headaches 1.14 (0.67, 1.97) 1.76 (1.20, 2.58) 1.22 (0.69, 2.15) 1.56 (1.05, 2.31) Heart Problems 1.01 (0.80, 1.27) 1.00 (0.80, 1.25) 0.81 (0.41, 1.60) 1.22 (0.83, 1.78) Hypertension 0.95 (0.77, 1.16) 1.04 (0.86, 1.26) 1.02 (0.67, 1.57) 1.31 (0.96, 1.78) Lower SR Health 1.32 (1.05, 1.65) 1.33 (1.02, 1.74) 1.31 (0.84, 2.04) 1.48 (1.10, 2.00) Lower SR Hearing 1.10 (0.88, 1.38) 1.03 (0.82, 1.28) 1.04 (0.67, 1.62) 0.97 (0.71, 1.34) Lower SR Vision 1.11 (0.91, 1.36) 1.08 (0.90, 1.30) 1.51 (0.90, 2.51) 1.06 (0.80, 1.41) Lung Disease 0.83 (0.50, 1.37) 1.34 (0.72, 2.47) 1.23 (0.52, 2.90) 1.13 (0.56, 2.28) Pain 1.27 (0.99, 1.62) 1.16 (0.94, 1.44) 1.42 (0.87, 2.33) 1.24 (0.93, 1.66) Psychiatric Illness 1.79 (1.25, 2.57) 1.24 (0.96, 1.61) 1.18 (0.45, 3.06) 1.34 (0.90, 2.02) Short of Breath 1.28 (0.95, 1.72) 1.21 (0.87, 1.66) 1.45 (0.81, 2.60) 1.36 (0.98, 1.88) Stroke 1.18 (0.84, 1.65) 1.28 (0.77, 2.12) 1.10 (0.57, 2.13) 1.05 (0.60, 1.85) Wheezing 1.15 (0.85, 1.55) 1.33 (0.90, 1.98) 1.22 (0.67, 2.21) 1.13 (0.78, 1.65)
Behaviors
Active Smoker 1.56 (1.15, 2.13) 1.50 (1.02, 2.20) 1.30 (0.81, 2.08) 1.20 (0.80, 1.79) Ever Smoked 1.17 (0.92, 1.50) 1.14 (0.95, 1.36) 1.24 (0.67, 2.30) 1.04 (0.79, 1.38) Heavy Alcohol Use 1.07 (0.76, 1.51) 1.67 (0.56, 4.99) 0.93 (0.44, 1.99) 1.50 (0.66, 3.42) Higher BMI 1.13 (0.86, 1.49) 1.04 (0.83, 1.31) 0.92 (0.60, 1.39) 1.10 (0.86, 1.40) Low/No Vigorous Physical Activity 1.11 (0.90, 1.35) 1.02 (0.85, 1.22) 1.05 (0.68, 1.61) 1.02 (0.76, 1.37)
Social Connections
Ever Divorced 1.25 (0.98, 1.60) 1.37 (1.04, 1.80) 0.94 (0.58, 1.52) 1.11 (0.78, 1.58) Ever Widowed 0.84 (0.60, 1.16) 0.86 (0.72, 1.02) 0.86 (0.51, 1.45) 0.91 (0.67, 1.23) Less Religious 0.98 (0.81, 1.19) 0.91 (0.74, 1.11) 0.96 (0.53, 1.75) 0.62 (0.26, 1.48) Lonely 1.05 (0.76, 1.44) 1.36 (1.08, 1.72) 1.25 (0.81, 1.95) 1.29 (0.92, 1.81) No Friends Nearby 0.90 (0.72, 1.13) 1.08 (0.87, 1.33) 1.14 (0.71, 1.83) 1.02 (0.76, 1.38) No Relatives Nearby 1.13 (0.91, 1.41) 0.98 (0.82, 1.17) 1.26 (0.82, 1.96) 1.25 (0.96, 1.65) Not Married/Partnered 1.14 (0.82, 1.59) 1.09 (0.89, 1.33) 1.03 (0.63, 1.67) 1.02 (0.76, 1.36) eiss 11
Genetic
Higher AD PGS 0.95 (0.78, 1.15) 1.04 (0.88, 1.23) 1.32 (0.67, 2.61) 1.32 (0.74, 2.38) Higher Coronary Artery Disease PGS 0.98 (0.80, 1.21) 1.07 (0.87, 1.31) 0.78 (0.47, 1.30) 1.14 (0.92, 1.42) Higher Diabetes PGS 1.04 (0.86, 1.26) 1.09 (0.88, 1.34) 0.94 (0.54, 1.64) 1.12 (0.77, 1.63) Higher Myocardial Infarction PGS 0.93 (0.77, 1.12) 0.98 (0.83, 1.17) 1.01 (0.59, 1.75) 0.85 (0.64, 1.14) Higher Parity PGS 0.95 (0.78, 1.16) 1.01 (0.81, 1.25) 0.98 (0.62, 1.56) 1.00 (0.75, 1.33) Lower Age at First Birth PGS 0.92 (0.75, 1.13) 0.97 (0.82, 1.16) 1.03 (0.71, 1.48) 1.01 (0.76, 1.33) Lower Age at Menarche PGS — 1.08 (0.92, 1.27) — 0.97 (0.76, 1.23) Lower Age at Menopause PGS — 1.08 (0.93, 1.26) — 1.09 (0.84, 1.41) Lower Education PGS 0.93 (0.77, 1.12) 0.97 (0.79, 1.20) 0.96 (0.64, 1.42) 0.88 (0.67, 1.16) Lower General Cognition PGS 0.97 (0.78, 1.19) 1.01 (0.81, 1.26) 0.98 (0.65, 1.48) 1.01 (0.76, 1.34) Lower Height PGS 0.97 (0.79, 1.19) 0.99 (0.80, 1.22) 0.92 (0.64, 1.33) 1.13 (0.80, 1.59) Lower Longevity PGS 1.09 (0.88, 1.35) 1.03 (0.88, 1.22) 1.13 (0.82, 1.56) 0.98 (0.77, 1.26) eiss 12
S4 Table. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Langa-Weir classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.14 (0.73, 1.77) 1.26 (0.81, 1.97) 1.20 (0.39, 3.69) 0.65 (0.23, 1.78) Southern Born 1.09 (0.87, 1.37) 1.15 (0.95, 1.39) 1.18 (0.50, 2.82) 1.28 (0.83, 1.98) Veteran 0.85 (0.68, 1.06) 0.36 (0.09, 1.35) 0.69 (0.44, 1.09) 1.13 (0.22, 5.67) Childless 0.98 (0.60, 1.60) 0.73 (0.38, 1.41) 1.17 (0.34, 3.95) 0.72 (0.56, 0.94) Higher Parity 1.03 (0.83, 1.29) 1.08 (0.90, 1.31) 1.13 (0.92, 1.40) 1.15 (0.96, 1.38) Lower Age at First Birth 1.06 (0.85, 1.33) 1.30 (1.05, 1.60) 1.02 (0.68, 1.52) 1.11 (0.87, 1.41) Higher Age at Last Birth 1.07 (0.86, 1.33) 1.12 (0.94, 1.34) 0.88 (0.63, 1.22) 0.98 (0.79, 1.22)
Early-Life
Lower Mother's Education 1.19 (0.92, 1.55) 1.13 (0.88, 1.46) 1.26 (0.86, 1.85) 1.25 (0.90, 1.74) Lower Father's Education 1.15 (0.93, 1.44) 1.09 (0.84, 1.42) 1.39 (0.91, 2.12) 1.25 (0.91, 1.72) Lower Father's Occupational Status 1.15 (0.92, 1.43) 1.12 (0.94, 1.33) 2.67 (0.61, 11.66) 1.72 (0.77, 3.87) Lower SR Childhood Health 1.23 (1.01, 1.50) 1.21 (0.92, 1.59) 1.16 (0.76, 1.77) 1.18 (0.91, 1.51) Lower SR Childhood SES 1.02 (0.84, 1.24) 1.10 (0.90, 1.35) 1.19 (0.72, 1.96) 1.17 (0.88, 1.57) Lower Education 1.55 (1.28, 1.87) 1.34 (1.09, 1.65) 1.61 (1.01, 2.57) 1.47 (1.11, 1.94)
Economic
Food Insecurity 0.73 (0.36, 1.45) 0.74 (0.49, 1.13) 0.77 (0.44, 1.37) 0.65 (0.48, 0.87) Lower Income 1.22 (1.03, 1.43) 1.38 (1.16, 1.63) 1.07 (0.83, 1.39) 1.19 (1.08, 1.31) Lower Neighborhood Safety 1.44 (0.93, 2.23) 1.33 (0.64, 2.77) 0.89 (0.52, 1.54) 1.24 (0.92, 1.67) Lower Wealth 1.28 (1.00, 1.63) 1.14 (0.84, 1.53) 1.12 (0.88, 1.42) 1.13 (1.00, 1.28) Medicaid 1.94 (0.97, 3.88) 1.03 (0.64, 1.67) 1.44 (0.73, 2.82) 1.36 (1.00, 1.85) Medicare 0.71 (0.56, 0.91) 0.75 (0.53, 1.06) 0.73 (0.45, 1.19) 0.83 (0.60, 1.15) No Insurance 0.94 (0.76, 1.15) 0.94 (0.78, 1.13) 0.67 (0.42, 1.06) 0.73 (0.51, 1.03) Received Food Stamps 1.89 (0.64, 5.57) 1.44 (0.47, 4.48) 1.42 (0.87, 2.33) 1.49 (1.05, 2.12) Retired 0.83 (0.65, 1.05) 0.92 (0.77, 1.12) 0.72 (0.43, 1.21) 0.83 (0.62, 1.09) Unemployed 1.08 (0.29, 4.06) 0.98 (0.24, 4.03) 0.00 (0.00, 0.00) 1.61 (0.89, 2.93)
Health eiss 13 Arthritis 0.89 (0.73, 1.09) 1.11 (0.93, 1.33) 0.99 (0.63, 1.56) 0.93 (0.70, 1.24) Back Pain 1.09 (0.87, 1.36) 0.99 (0.80, 1.23) 1.18 (0.73, 1.92) 0.85 (0.62, 1.15) Cancer 0.89 (0.66, 1.18) 0.81 (0.63, 1.05) 0.62 (0.30, 1.27) 0.97 (0.59, 1.59) Diabetes 1.04 (0.79, 1.38) 1.07 (0.82, 1.39) 1.18 (0.63, 2.22) 1.13 (0.81, 1.56) Dizziness 1.22 (0.88, 1.70) 1.18 (0.83, 1.67) 1.12 (0.60, 2.07) 1.51 (1.07, 2.12) Fatigue 1.20 (0.85, 1.69) 1.25 (0.96, 1.61) 0.88 (0.42, 1.83) 1.25 (0.88, 1.79) Headaches 1.14 (0.66, 1.96) 1.69 (1.15, 2.49) 1.12 (0.64, 1.99) 1.36 (0.85, 2.19) Heart Problems 1.00 (0.80, 1.26) 0.97 (0.78, 1.20) 0.69 (0.31, 1.52) 1.18 (0.81, 1.73) Hypertension 0.93 (0.75, 1.14) 1.03 (0.86, 1.25) 0.94 (0.59, 1.49) 1.27 (0.93, 1.74) Lower SR Health 1.29 (1.03, 1.62) 1.26 (0.96, 1.65) 1.13 (0.72, 1.76) 1.38 (1.01, 1.89) Lower SR Hearing 1.15 (0.92, 1.44) 1.07 (0.86, 1.33) 1.07 (0.69, 1.67) 0.93 (0.68, 1.29) Lower SR Vision 1.11 (0.90, 1.36) 1.10 (0.92, 1.32) 1.27 (0.74, 2.17) 1.04 (0.79, 1.38) Lung Disease 0.75 (0.45, 1.25) 1.15 (0.60, 2.20) 1.36 (0.58, 3.15) 1.14 (0.51, 2.56) Pain 1.23 (0.97, 1.57) 1.13 (0.91, 1.39) 1.16 (0.67, 2.01) 1.12 (0.83, 1.51) Psychiatric Illness 1.57 (1.07, 2.31) 1.20 (0.94, 1.53) 0.79 (0.23, 2.67) 1.37 (0.89, 2.11) Short of Breath 1.18 (0.88, 1.59) 1.11 (0.80, 1.55) 1.39 (0.77, 2.51) 1.17 (0.83, 1.66) Stroke 1.13 (0.80, 1.59) 1.27 (0.77, 2.10) 1.00 (0.49, 2.05) 0.89 (0.47, 1.70) Wheezing 1.13 (0.84, 1.51) 1.17 (0.77, 1.77) 1.09 (0.59, 2.05) 1.13 (0.77, 1.66)
Behaviors
Active Smoker 1.24 (0.90, 1.72) 1.15 (0.75, 1.78) 1.11 (0.64, 1.93) 1.04 (0.65, 1.66) Ever Smoked 1.13 (0.89, 1.44) 1.02 (0.85, 1.22) 1.27 (0.65, 2.51) 1.00 (0.75, 1.32) Heavy Alcohol Use 1.02 (0.71, 1.45) 1.62 (0.54, 4.86) 0.86 (0.37, 2.02) 1.19 (0.56, 2.53) Higher BMI 1.01 (0.77, 1.32) 0.99 (0.81, 1.21) 0.92 (0.56, 1.52) 1.00 (0.78, 1.28) Low/No Vigorous Physical Activity 1.06 (0.87, 1.30) 1.02 (0.85, 1.22) 0.99 (0.62, 1.58) 0.98 (0.73, 1.33)
Social Connections
Ever Divorced 1.10 (0.86, 1.41) 1.21 (0.91, 1.60) 0.92 (0.54, 1.56) 1.07 (0.75, 1.54) Ever Widowed 0.90 (0.66, 1.24) 0.91 (0.77, 1.08) 0.86 (0.50, 1.46) 0.98 (0.73, 1.31) Less Religious 1.00 (0.82, 1.21) 0.92 (0.75, 1.13) 1.04 (0.55, 1.94) 0.61 (0.28, 1.34) Lonely 1.00 (0.73, 1.38) 1.35 (1.07, 1.70) 1.30 (0.83, 2.05) 1.26 (0.88, 1.81) No Friends Nearby 0.93 (0.74, 1.17) 1.11 (0.90, 1.37) 1.32 (0.79, 2.20) 1.06 (0.77, 1.46) No Relatives Nearby 1.13 (0.91, 1.41) 1.02 (0.85, 1.21) 1.12 (0.69, 1.82) 1.22 (0.93, 1.61) Not Married/Partnered 1.11 (0.80, 1.54) 1.03 (0.86, 1.25) 1.01 (0.60, 1.68) 1.02 (0.76, 1.37) eiss 14
Genetic
Higher AD PGS 0.95 (0.79, 1.16) 1.05 (0.88, 1.24) 1.00 (0.49, 2.02) 1.42 (0.78, 2.58) Higher Coronary Artery Disease PGS 0.95 (0.77, 1.17) 1.06 (0.87, 1.30) 0.78 (0.43, 1.44) 1.14 (0.91, 1.43) Higher Diabetes PGS 1.05 (0.87, 1.27) 1.11 (0.89, 1.37) 0.96 (0.53, 1.72) 1.07 (0.73, 1.57) Higher Myocardial Infarction PGS 0.91 (0.75, 1.10) 0.99 (0.83, 1.17) 0.96 (0.53, 1.73) 0.85 (0.63, 1.14) Higher Parity PGS 0.98 (0.80, 1.20) 1.03 (0.83, 1.28) 1.02 (0.61, 1.71) 0.99 (0.74, 1.33) Lower Age at First Birth PGS 0.93 (0.75, 1.14) 0.98 (0.82, 1.16) 1.02 (0.67, 1.54) 1.01 (0.76, 1.35) Lower Age at Menarche PGS — 1.11 (0.95, 1.31) — 0.97 (0.75, 1.25) Lower Age at Menopause PGS — 1.09 (0.94, 1.27) — 1.02 (0.79, 1.31) Lower Education PGS 0.93 (0.77, 1.13) 0.97 (0.79, 1.20) 0.96 (0.62, 1.48) 0.91 (0.70, 1.18) Lower General Cognition PGS 0.96 (0.77, 1.18) 1.01 (0.81, 1.25) 0.96 (0.60, 1.54) 1.07 (0.81, 1.42) Lower Height PGS 0.97 (0.79, 1.19) 0.97 (0.79, 1.20) 0.92 (0.61, 1.39) 1.11 (0.79, 1.56) Lower Longevity PGS 1.07 (0.86, 1.34) 1.04 (0.88, 1.23) 1.15 (0.83, 1.61) 1.01 (0.78, 1.30) eiss 15
S5 Table. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Hurd classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.06 (0.78, 1.45) 1.03 (0.80, 1.34) 0.76 (0.20, 2.95) 0.76 (0.29, 2.00) Southern Born 1.12 (0.94, 1.33) 1.04 (0.91, 1.20) 1.37 (0.68, 2.75) 1.19 (0.75, 1.90) Veteran 0.97 (0.81, 1.15) 0.79 (0.39, 1.59) 0.88 (0.55, 1.41) 0.00 (0.00, 0.00) Childless 0.95 (0.63, 1.45) 0.81 (0.49, 1.34) 1.40 (0.40, 4.92) 0.71 (0.54, 0.93) Higher Parity 0.98 (0.83, 1.16) 0.97 (0.85, 1.11) 1.17 (0.93, 1.47) 1.15 (0.95, 1.40) Lower Age at First Birth 1.01 (0.87, 1.18) 1.15 (1.00, 1.32) 1.40 (0.89, 2.18) 0.95 (0.75, 1.22) Higher Age at Last Birth 1.03 (0.88, 1.20) 1.14 (1.00, 1.31) 1.00 (0.68, 1.47) 0.85 (0.67, 1.09)
Early-Life
Lower Mother's Education 1.23 (1.02, 1.48) 1.06 (0.88, 1.28) 1.07 (0.67, 1.72) 1.16 (0.81, 1.67) Lower Father's Education 1.19 (1.00, 1.42) 1.01 (0.84, 1.22) 1.06 (0.57, 1.98) 1.19 (0.88, 1.62) Lower Father's Occupational Status 1.16 (0.99, 1.36) 1.10 (0.96, 1.26) 1.60 (0.56, 4.54) 0.90 (0.45, 1.83) Lower SR Childhood Health 1.10 (0.94, 1.29) 1.07 (0.95, 1.21) 1.14 (0.74, 1.74) 1.08 (0.82, 1.43) Lower SR Childhood SES 1.06 (0.92, 1.22) 1.11 (0.98, 1.26) 0.91 (0.55, 1.51) 1.18 (0.88, 1.60) Lower Education 1.29 (1.12, 1.47) 1.10 (0.97, 1.25) 1.22 (0.80, 1.86) 1.27 (0.97, 1.67)
Economic
Food Insecurity 0.76 (0.40, 1.45) 0.82 (0.57, 1.16) 1.06 (0.47, 2.37) 0.80 (0.53, 1.21) Lower Income 1.14 (0.96, 1.36) 1.11 (0.98, 1.27) 1.12 (0.85, 1.46) 1.03 (0.83, 1.28) Lower Neighborhood Safety 1.27 (0.88, 1.83) 1.04 (0.74, 1.45) 0.72 (0.40, 1.27) 0.98 (0.69, 1.39) Lower Wealth 1.21 (0.95, 1.54) 1.04 (0.89, 1.22) 1.05 (0.77, 1.42) 1.13 (0.98, 1.30) Medicaid 1.72 (0.95, 3.11) 1.07 (0.73, 1.59) 1.54 (0.63, 3.72) 1.23 (0.88, 1.73) Medicare 0.97 (0.76, 1.23) 0.94 (0.74, 1.18) 1.03 (0.60, 1.80) 0.99 (0.66, 1.50) No Insurance 0.95 (0.82, 1.09) 1.00 (0.88, 1.13) 0.69 (0.43, 1.11) 0.78 (0.54, 1.12) Received Food Stamps 2.62 (1.46, 4.68) 0.92 (0.53, 1.59) 0.91 (0.29, 2.84) 1.28 (0.80, 2.06) Retired 0.95 (0.77, 1.17) 0.92 (0.81, 1.04) 0.90 (0.49, 1.67) 0.96 (0.70, 1.33) Unemployed 0.50 (0.11, 2.25) 1.07 (0.39, 2.93) 0.00 (0.00, 0.00) 1.70 (0.85, 3.40)
Health eiss 16 Arthritis 1.00 (0.86, 1.15) 1.05 (0.93, 1.19) 0.98 (0.62, 1.56) 0.95 (0.71, 1.27) Back Pain 1.07 (0.91, 1.26) 0.96 (0.84, 1.09) 1.24 (0.75, 2.07) 0.94 (0.68, 1.30) Cancer 0.95 (0.78, 1.15) 0.87 (0.72, 1.05) 0.84 (0.43, 1.64) 0.96 (0.55, 1.67) Diabetes 1.11 (0.91, 1.35) 1.04 (0.84, 1.29) 1.32 (0.85, 2.03) 1.05 (0.75, 1.47) Dizziness 1.26 (1.01, 1.59) 1.02 (0.84, 1.24) 1.13 (0.54, 2.38) 1.43 (0.91, 2.22) Fatigue 1.23 (0.95, 1.58) 1.08 (0.92, 1.27) 1.06 (0.47, 2.41) 1.30 (0.88, 1.92) Headaches 1.14 (0.78, 1.66) 1.30 (1.03, 1.63) 1.24 (0.68, 2.26) 1.62 (0.99, 2.67) Heart Problems 1.02 (0.87, 1.20) 1.02 (0.87, 1.21) 0.61 (0.30, 1.25) 1.15 (0.74, 1.78) Hypertension 0.94 (0.81, 1.09) 1.05 (0.93, 1.18) 0.81 (0.51, 1.29) 1.28 (0.93, 1.76) Lower SR Health 1.21 (1.02, 1.43) 1.12 (0.97, 1.29) 0.99 (0.62, 1.58) 1.32 (0.93, 1.87) Lower SR Hearing 1.16 (0.99, 1.36) 1.04 (0.91, 1.17) 1.07 (0.65, 1.79) 0.99 (0.69, 1.43) Lower SR Vision 1.12 (0.97, 1.30) 1.07 (0.95, 1.21) 1.24 (0.71, 2.17) 0.96 (0.72, 1.28) Lung Disease 0.82 (0.58, 1.15) 0.96 (0.73, 1.27) 1.27 (0.44, 3.67) 1.35 (0.71, 2.56) Pain 1.17 (0.98, 1.40) 1.05 (0.92, 1.20) 1.13 (0.64, 1.98) 1.17 (0.84, 1.63) Psychiatric Illness 1.32 (0.91, 1.90) 1.19 (0.97, 1.47) 0.59 (0.12, 2.86) 1.09 (0.62, 1.92) Short of Breath 1.18 (0.95, 1.47) 1.02 (0.85, 1.22) 1.38 (0.78, 2.46) 1.38 (0.94, 2.01) Stroke 1.15 (0.87, 1.52) 1.09 (0.86, 1.38) 1.17 (0.52, 2.63) 1.09 (0.65, 1.84) Wheezing 1.11 (0.90, 1.38) 1.04 (0.85, 1.28) 0.77 (0.33, 1.81) 1.18 (0.77, 1.80)
Behaviors
Active Smoker 1.02 (0.76, 1.36) 0.99 (0.79, 1.25) 1.06 (0.59, 1.90) 1.05 (0.62, 1.78) Ever Smoked 1.05 (0.89, 1.23) 1.03 (0.91, 1.16) 1.13 (0.64, 2.00) 1.02 (0.75, 1.40) Heavy Alcohol Use 0.98 (0.76, 1.27) 1.15 (0.80, 1.64) 0.88 (0.37, 2.13) 1.03 (0.35, 3.05) Higher BMI 1.09 (0.89, 1.34) 1.01 (0.88, 1.16) 0.95 (0.53, 1.68) 1.03 (0.80, 1.33) Low/No Vigorous Physical Activity 1.09 (0.94, 1.26) 1.03 (0.91, 1.17) 0.83 (0.52, 1.32) 0.96 (0.70, 1.31)
Social Connections
Ever Divorced 0.98 (0.79, 1.21) 1.11 (0.94, 1.32) 0.83 (0.48, 1.45) 0.94 (0.61, 1.44) Ever Widowed 0.95 (0.77, 1.17) 0.98 (0.87, 1.11) 0.96 (0.59, 1.57) 1.06 (0.78, 1.44) Less Religious 0.94 (0.82, 1.07) 0.94 (0.81, 1.08) 0.69 (0.32, 1.47) 0.58 (0.26, 1.30) Lonely 1.06 (0.84, 1.34) 1.13 (0.98, 1.31) 1.61 (1.04, 2.50) 1.43 (1.03, 1.98) No Friends Nearby 1.04 (0.87, 1.24) 0.97 (0.84, 1.12) 0.99 (0.59, 1.64) 1.23 (0.87, 1.76) No Relatives Nearby 1.08 (0.92, 1.27) 1.05 (0.93, 1.19) 0.93 (0.53, 1.62) 1.18 (0.87, 1.59) Not Married/Partnered 1.03 (0.83, 1.28) 1.00 (0.89, 1.12) 1.04 (0.64, 1.69) 1.02 (0.75, 1.39) eiss 17
Genetic
Higher AD PGS 1.02 (0.89, 1.18) 1.04 (0.93, 1.16) 0.74 (0.33, 1.69) 1.41 (0.74, 2.68) Higher Coronary Artery Disease PGS 0.99 (0.86, 1.14) 0.99 (0.87, 1.12) 0.94 (0.65, 1.35) 1.10 (0.86, 1.42) Higher Diabetes PGS 1.03 (0.90, 1.19) 1.04 (0.93, 1.16) 0.83 (0.47, 1.48) 0.90 (0.58, 1.39) Higher Myocardial Infarction PGS 0.96 (0.84, 1.10) 1.00 (0.88, 1.14) 0.79 (0.48, 1.28) 0.86 (0.62, 1.18) Higher Parity PGS 0.94 (0.82, 1.07) 1.06 (0.94, 1.20) 0.85 (0.58, 1.24) 0.80 (0.59, 1.09) Lower Age at First Birth PGS 1.00 (0.86, 1.16) 1.02 (0.90, 1.16) 1.09 (0.69, 1.72) 1.13 (0.84, 1.52) Lower Age at Menarche PGS — 1.05 (0.94, 1.18) — 0.95 (0.70, 1.28) Lower Age at Menopause PGS — 0.99 (0.88, 1.11) — 1.01 (0.76, 1.34) Lower Education PGS 0.98 (0.85, 1.13) 1.02 (0.91, 1.15) 0.79 (0.51, 1.21) 0.96 (0.74, 1.23) Lower General Cognition PGS 0.97 (0.83, 1.12) 1.08 (0.95, 1.21) 0.87 (0.58, 1.31) 0.99 (0.73, 1.34) Lower Height PGS 0.96 (0.83, 1.11) 1.04 (0.93, 1.16) 0.79 (0.48, 1.28) 1.13 (0.78, 1.63) Lower Longevity PGS 1.02 (0.88, 1.19) 1.00 (0.89, 1.12) 1.11 (0.82, 1.51) 0.91 (0.70, 1.17) eiss 18
S6 Table. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the Expert classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.07 (0.79, 1.45) 1.09 (0.85, 1.39) 0.86 (0.26, 2.85) 1.02 (0.68, 1.52) Southern Born 1.10 (0.94, 1.29) 1.02 (0.90, 1.16) 1.37 (0.71, 2.63) 1.04 (0.78, 1.38) Veteran 0.88 (0.75, 1.04) 0.87 (0.49, 1.53) 0.99 (0.63, 1.54) 0.94 (0.35, 2.53) Childless 0.78 (0.51, 1.19) 0.82 (0.51, 1.31) 1.93 (0.80, 4.61) 0.29 (0.04, 2.00) Higher Parity 0.96 (0.81, 1.15) 1.04 (0.93, 1.17) 1.08 (0.85, 1.37) 1.19 (1.01, 1.40) Lower Age at First Birth 1.00 (0.86, 1.16) 1.17 (1.03, 1.33) 1.37 (0.85, 2.20) 1.08 (0.87, 1.35) Higher Age at Last Birth 0.99 (0.86, 1.14) 1.08 (0.95, 1.22) 1.05 (0.74, 1.50) 0.93 (0.76, 1.14)
Early-Life
Lower Mother's Education 1.31 (1.08, 1.59) 1.17 (0.97, 1.41) 1.05 (0.64, 1.73) 1.13 (0.83, 1.54) Lower Father's Education 1.23 (1.02, 1.48) 1.15 (0.95, 1.38) 1.05 (0.61, 1.82) 1.07 (0.82, 1.41) Lower Father's Occupational Status 1.20 (1.03, 1.39) 1.17 (1.03, 1.32) 1.34 (0.51, 3.53) 0.96 (0.52, 1.77) Lower SR Childhood Health 1.09 (0.95, 1.26) 1.08 (0.96, 1.21) 1.12 (0.74, 1.68) 1.10 (0.87, 1.40) Lower SR Childhood SES 1.07 (0.94, 1.22) 1.13 (1.00, 1.27) 1.06 (0.64, 1.76) 1.03 (0.83, 1.28) Lower Education 1.35 (1.19, 1.53) 1.17 (1.03, 1.32) 1.03 (0.71, 1.50) 1.08 (0.86, 1.35)
Economic
Food Insecurity 0.93 (0.49, 1.78) 0.85 (0.62, 1.17) 1.02 (0.48, 2.17) 0.75 (0.55, 1.00) Lower Income 1.17 (1.01, 1.35) 1.15 (1.01, 1.31) 1.09 (0.83, 1.42) 1.01 (0.83, 1.23) Lower Neighborhood Safety 1.27 (0.92, 1.75) 1.17 (0.85, 1.61) 0.73 (0.41, 1.27) 1.04 (0.78, 1.40) Lower Wealth 1.16 (0.92, 1.46) 1.05 (0.90, 1.22) 1.13 (0.87, 1.46) 1.07 (0.94, 1.22) Medicaid 1.42 (0.77, 2.61) 1.15 (0.80, 1.65) 1.57 (0.71, 3.47) 1.17 (0.86, 1.59) Medicare 0.97 (0.78, 1.20) 0.94 (0.76, 1.16) 0.86 (0.53, 1.42) 1.00 (0.70, 1.44) No Insurance 0.94 (0.82, 1.07) 0.99 (0.89, 1.11) 0.71 (0.45, 1.13) 0.83 (0.64, 1.08) Received Food Stamps 2.04 (1.19, 3.50) 0.98 (0.60, 1.60) 0.95 (0.33, 2.77) 1.54 (1.11, 2.14) Retired 0.96 (0.79, 1.16) 0.93 (0.83, 1.04) 0.86 (0.49, 1.52) 0.91 (0.69, 1.20) Unemployed 0.63 (0.24, 1.68) 1.23 (0.52, 2.91) 0.00 (0.00, 0.00) 1.35 (0.73, 2.52)
Health eiss 19 Arthritis 1.00 (0.88, 1.15) 1.04 (0.92, 1.16) 1.04 (0.66, 1.63) 1.06 (0.81, 1.37) Back Pain 1.07 (0.92, 1.25) 0.97 (0.85, 1.09) 1.37 (0.85, 2.21) 1.04 (0.80, 1.34) Cancer 0.91 (0.76, 1.10) 0.93 (0.79, 1.10) 0.81 (0.42, 1.55) 0.93 (0.59, 1.49) Diabetes 1.24 (1.03, 1.50) 1.19 (0.98, 1.44) 1.28 (0.85, 1.93) 1.21 (0.86, 1.71) Dizziness 1.24 (1.01, 1.52) 1.03 (0.85, 1.25) 1.03 (0.55, 1.92) 1.42 (0.98, 2.07) Fatigue 1.27 (0.98, 1.65) 1.06 (0.91, 1.23) 0.94 (0.42, 2.09) 1.26 (0.90, 1.75) Headaches 1.08 (0.75, 1.57) 1.26 (1.02, 1.56) 1.30 (0.79, 2.14) 1.34 (0.86, 2.10) Heart Problems 1.03 (0.88, 1.21) 1.01 (0.87, 1.17) 0.56 (0.26, 1.20) 1.23 (0.93, 1.62) Hypertension 0.98 (0.85, 1.12) 1.02 (0.92, 1.15) 0.87 (0.55, 1.37) 1.25 (0.96, 1.63) Lower SR Health 1.23 (1.05, 1.44) 1.15 (1.02, 1.30) 0.96 (0.63, 1.47) 1.42 (1.08, 1.86) Lower SR Hearing 1.18 (1.01, 1.38) 1.07 (0.95, 1.20) 0.96 (0.61, 1.51) 0.92 (0.67, 1.25) Lower SR Vision 1.15 (0.99, 1.33) 1.10 (0.99, 1.23) 1.23 (0.73, 2.07) 1.03 (0.78, 1.35) Lung Disease 0.92 (0.69, 1.23) 1.04 (0.81, 1.34) 1.43 (0.61, 3.36) 1.40 (0.77, 2.55) Pain 1.14 (0.95, 1.37) 1.05 (0.93, 1.19) 1.17 (0.68, 2.01) 1.16 (0.87, 1.53) Psychiatric Illness 1.32 (0.95, 1.83) 1.22 (0.99, 1.51) 0.73 (0.18, 2.93) 1.42 (0.88, 2.30) Short of Breath 1.12 (0.90, 1.40) 0.98 (0.83, 1.17) 1.41 (0.88, 2.26) 1.33 (0.97, 1.83) Stroke 1.16 (0.89, 1.52) 1.09 (0.88, 1.35) 1.05 (0.50, 2.20) 1.24 (0.85, 1.81) Wheezing 1.12 (0.91, 1.39) 1.00 (0.82, 1.23) 0.76 (0.36, 1.61) 1.04 (0.70, 1.55)
Behaviors
Active Smoker 1.13 (0.88, 1.45) 1.02 (0.83, 1.27) 1.06 (0.60, 1.86) 1.05 (0.71, 1.57) Ever Smoked 1.11 (0.95, 1.29) 1.01 (0.90, 1.13) 1.27 (0.71, 2.28) 1.02 (0.79, 1.31) Heavy Alcohol Use 0.98 (0.78, 1.24) 1.09 (0.76, 1.56) 1.01 (0.46, 2.25) 0.81 (0.31, 2.12) Higher BMI 1.14 (0.95, 1.37) 1.06 (0.94, 1.19) 0.96 (0.58, 1.59) 1.05 (0.87, 1.27) Low/No Vigorous Physical Activity 1.10 (0.96, 1.26) 1.02 (0.91, 1.15) 0.94 (0.60, 1.48) 0.90 (0.71, 1.14)
Social Connections
Ever Divorced 1.04 (0.86, 1.27) 1.12 (0.95, 1.32) 1.05 (0.64, 1.73) 1.26 (0.98, 1.62) Ever Widowed 1.01 (0.84, 1.23) 0.97 (0.87, 1.08) 0.93 (0.58, 1.48) 0.94 (0.73, 1.22) Less Religious 0.95 (0.84, 1.07) 0.95 (0.84, 1.08) 0.85 (0.42, 1.70) 0.83 (0.54, 1.27) Lonely 1.11 (0.86, 1.42) 1.14 (0.99, 1.31) 1.65 (1.14, 2.38) 1.33 (0.97, 1.81) No Friends Nearby 1.00 (0.85, 1.19) 0.94 (0.83, 1.07) 1.12 (0.68, 1.86) 1.07 (0.80, 1.44) No Relatives Nearby 1.12 (0.96, 1.30) 1.01 (0.90, 1.14) 0.95 (0.57, 1.60) 1.14 (0.88, 1.47) Not Married/Partnered 0.92 (0.75, 1.13) 1.01 (0.90, 1.13) 0.93 (0.59, 1.47) 0.97 (0.73, 1.29) eiss 20
Genetic
Higher AD PGS 1.04 (0.91, 1.18) 1.02 (0.92, 1.14) 1.01 (0.44, 2.33) 1.45 (0.83, 2.51) Higher Coronary Artery Disease PGS 0.99 (0.88, 1.13) 0.99 (0.88, 1.11) 0.86 (0.58, 1.25) 1.12 (0.89, 1.41) Higher Diabetes PGS 1.04 (0.91, 1.19) 1.03 (0.92, 1.14) 0.83 (0.45, 1.52) 0.84 (0.59, 1.19) Higher Myocardial Infarction PGS 1.01 (0.88, 1.15) 0.99 (0.88, 1.11) 0.80 (0.49, 1.29) 0.88 (0.69, 1.14) Higher Parity PGS 1.03 (0.90, 1.18) 1.02 (0.91, 1.15) 0.85 (0.57, 1.27) 0.95 (0.76, 1.21) Lower Age at First Birth PGS 0.99 (0.86, 1.14) 1.00 (0.89, 1.12) 1.10 (0.70, 1.74) 1.05 (0.83, 1.34) Lower Age at Menarche PGS — 1.00 (0.90, 1.11) — 0.96 (0.74, 1.24) Lower Age at Menopause PGS — 1.01 (0.91, 1.13) — 0.99 (0.78, 1.25) Lower Education PGS 1.03 (0.90, 1.18) 0.99 (0.89, 1.10) 0.79 (0.52, 1.20) 0.96 (0.76, 1.21) Lower General Cognition PGS 0.96 (0.84, 1.10) 1.05 (0.94, 1.17) 0.80 (0.54, 1.19) 0.97 (0.77, 1.23) Lower Height PGS 0.98 (0.86, 1.12) 1.05 (0.94, 1.17) 0.81 (0.51, 1.30) 1.11 (0.82, 1.50) Lower Longevity PGS 0.97 (0.84, 1.13) 1.01 (0.91, 1.13) 1.07 (0.80, 1.43) 0.92 (0.74, 1.16) eiss 21
S7 Table. Hazard ratios (HRs) and 95% confidence intervals (CI) of each predictor for incident dementia obtained from Fine-Gray regression models stratified by race and gender.
Models use restricted analytic sample and classify dementia using the LASSO classification scheme. NH White NH Black Characteristic Men Women Men Women
Sociodemographic
Foreign Born 1.09 (0.81, 1.47) 0.96 (0.73, 1.27) 1.04 (0.33, 3.23) 1.04 (0.71, 1.52) Southern Born 1.17 (0.99, 1.38) 1.09 (0.96, 1.25) 1.23 (0.64, 2.38) 1.09 (0.80, 1.47) Veteran 0.86 (0.73, 1.02) 0.98 (0.57, 1.68) 1.01 (0.65, 1.58) 0.00 (0.00, 0.00) Childless 0.98 (0.67, 1.43) 0.89 (0.56, 1.41) 1.07 (0.25, 4.49) 0.73 (0.47, 1.16) Higher Parity 0.98 (0.84, 1.15) 0.98 (0.86, 1.12) 1.21 (0.98, 1.49) 1.12 (0.93, 1.35) Lower Age at First Birth 0.98 (0.85, 1.13) 1.14 (0.99, 1.31) 1.42 (0.91, 2.22) 1.07 (0.85, 1.36) Higher Age at Last Birth 0.98 (0.85, 1.13) 1.08 (0.95, 1.23) 0.97 (0.68, 1.39) 0.98 (0.80, 1.21)
Early-Life
Lower Mother's Education 1.26 (1.05, 1.51) 1.11 (0.92, 1.33) 1.11 (0.66, 1.87) 1.07 (0.79, 1.45) Lower Father's Education 1.16 (0.96, 1.41) 1.12 (0.93, 1.35) 1.17 (0.62, 2.20) 0.97 (0.72, 1.30) Lower Father's Occupational Status 1.14 (0.98, 1.33) 1.17 (1.02, 1.34) 1.15 (0.61, 2.18) 0.91 (0.57, 1.45) Lower SR Childhood Health 1.13 (0.98, 1.30) 1.09 (0.97, 1.22) 1.17 (0.77, 1.77) 1.05 (0.80, 1.37) Lower SR Childhood SES 1.05 (0.92, 1.21) 1.15 (1.02, 1.30) 0.87 (0.51, 1.49) 1.13 (0.89, 1.44) Lower Education 1.39 (1.21, 1.59) 1.17 (1.03, 1.32) 1.16 (0.80, 1.70) 1.12 (0.88, 1.41)
Economic
Food Insecurity 0.77 (0.42, 1.43) 0.84 (0.59, 1.18) 1.07 (0.49, 2.37) 0.81 (0.58, 1.14) Lower Income 1.11 (0.93, 1.31) 1.16 (1.01, 1.32) 1.08 (0.83, 1.39) 1.20 (1.03, 1.39) Lower Neighborhood Safety 1.32 (0.93, 1.86) 1.05 (0.78, 1.41) 0.66 (0.39, 1.13) 1.18 (0.88, 1.59) Lower Wealth 1.16 (0.92, 1.47) 1.06 (0.92, 1.22) 1.07 (0.85, 1.35) 1.10 (0.96, 1.26) Medicaid 1.66 (0.95, 2.90) 1.06 (0.75, 1.51) 1.43 (0.65, 3.17) 1.28 (0.92, 1.78) Medicare 0.99 (0.79, 1.25) 0.87 (0.71, 1.07) 0.95 (0.56, 1.61) 0.98 (0.67, 1.42) No Insurance 0.98 (0.85, 1.13) 0.99 (0.88, 1.12) 0.92 (0.59, 1.44) 0.80 (0.61, 1.05) Received Food Stamps 2.23 (1.28, 3.87) 0.87 (0.50, 1.52) 0.90 (0.31, 2.64) 1.48 (1.02, 2.16) Retired 0.92 (0.75, 1.11) 0.99 (0.87, 1.12) 0.85 (0.48, 1.49) 0.92 (0.70, 1.21) Unemployed 0.48 (0.11, 2.06) 0.93 (0.34, 2.55) 0.00 (0.00, 0.00) 1.30 (0.66, 2.54)
Health eiss 22 Arthritis 0.98 (0.85, 1.13) 1.01 (0.90, 1.14) 1.02 (0.66, 1.58) 1.04 (0.78, 1.38) Back Pain 1.05 (0.90, 1.24) 0.96 (0.85, 1.09) 1.36 (0.85, 2.17) 0.91 (0.69, 1.21) Cancer 0.90 (0.74, 1.09) 0.87 (0.73, 1.05) 0.85 (0.42, 1.74) 0.93 (0.58, 1.47) Diabetes 1.10 (0.91, 1.34) 1.06 (0.86, 1.29) 0.98 (0.62, 1.56) 1.09 (0.77, 1.55) Dizziness 1.23 (0.97, 1.55) 0.98 (0.82, 1.18) 1.18 (0.70, 1.99) 1.43 (1.00, 2.04) Fatigue 1.25 (0.96, 1.63) 1.05 (0.90, 1.23) 0.91 (0.41, 2.02) 1.32 (0.96, 1.81) Headaches 1.09 (0.74, 1.61) 1.24 (0.99, 1.55) 1.13 (0.64, 2.00) 1.38 (0.90, 2.12) Heart Problems 1.03 (0.87, 1.22) 1.03 (0.88, 1.20) 0.60 (0.31, 1.15) 1.14 (0.83, 1.56) Hypertension 0.98 (0.85, 1.14) 1.03 (0.92, 1.16) 0.88 (0.56, 1.36) 1.30 (0.98, 1.73) Lower SR Health 1.15 (0.97, 1.36) 1.09 (0.95, 1.25) 1.01 (0.66, 1.53) 1.30 (0.96, 1.74) Lower SR Hearing 1.21 (1.03, 1.43) 1.06 (0.94, 1.19) 1.17 (0.73, 1.86) 0.89 (0.65, 1.22) Lower SR Vision 1.11 (0.96, 1.28) 1.08 (0.97, 1.21) 1.25 (0.73, 2.15) 1.03 (0.78, 1.37) Lung Disease 0.88 (0.64, 1.19) 1.09 (0.83, 1.42) 1.21 (0.48, 3.06) 1.45 (0.78, 2.70) Pain 1.12 (0.93, 1.35) 1.07 (0.94, 1.22) 1.07 (0.61, 1.86) 1.15 (0.84, 1.56) Psychiatric Illness 1.36 (0.96, 1.93) 1.16 (0.94, 1.43) 0.84 (0.25, 2.77) 1.25 (0.72, 2.15) Short of Breath 1.13 (0.89, 1.42) 1.01 (0.85, 1.20) 1.25 (0.71, 2.17) 1.17 (0.79, 1.73) Stroke 1.22 (0.93, 1.61) 1.13 (0.90, 1.41) 1.05 (0.49, 2.27) 0.97 (0.52, 1.81) Wheezing 1.13 (0.90, 1.41) 1.03 (0.83, 1.28) 0.87 (0.43, 1.78) 1.16 (0.77, 1.73)
Behaviors
Active Smoker 1.15 (0.89, 1.50) 1.06 (0.85, 1.32) 0.96 (0.54, 1.69) 1.15 (0.70, 1.88) Ever Smoked 1.05 (0.89, 1.23) 1.02 (0.90, 1.14) 1.14 (0.66, 1.99) 1.06 (0.81, 1.39) Heavy Alcohol Use 0.93 (0.72, 1.20) 1.13 (0.76, 1.69) 0.96 (0.43, 2.13) 0.85 (0.30, 2.39) Higher BMI 0.97 (0.79, 1.19) 0.98 (0.85, 1.12) 0.89 (0.53, 1.52) 0.97 (0.78, 1.20) Low/No Vigorous Physical Activity 1.06 (0.92, 1.23) 1.03 (0.91, 1.16) 0.91 (0.58, 1.40) 1.01 (0.77, 1.33)
Social Connections
Ever Divorced 0.99 (0.80, 1.21) 1.10 (0.93, 1.30) 0.96 (0.58, 1.56) 1.17 (0.87, 1.56) Ever Widowed 0.94 (0.76, 1.16) 1.00 (0.89, 1.12) 0.96 (0.57, 1.60) 0.95 (0.72, 1.25) Less Religious 0.91 (0.79, 1.04) 0.92 (0.81, 1.05) 0.92 (0.51, 1.69) 0.85 (0.53, 1.37) Lonely 1.03 (0.79, 1.33) 1.14 (0.99, 1.32) 1.57 (1.04, 2.38) 1.23 (0.88, 1.72) No Friends Nearby 0.98 (0.82, 1.16) 0.94 (0.82, 1.08) 1.00 (0.62, 1.62) 1.00 (0.73, 1.37) No Relatives Nearby 1.09 (0.93, 1.27) 1.09 (0.96, 1.22) 0.98 (0.58, 1.65) 1.07 (0.81, 1.40) Not Married/Partnered 1.02 (0.81, 1.27) 0.98 (0.87, 1.10) 1.01 (0.64, 1.58) 0.98 (0.72, 1.32) eiss 23
Genetic
Higher AD PGS 1.03 (0.89, 1.18) 1.02 (0.91, 1.13) 0.80 (0.38, 1.70) 1.33 (0.75, 2.36) Higher Coronary Artery Disease PGS 0.96 (0.84, 1.11) 1.01 (0.89, 1.14) 0.72 (0.48, 1.07) 1.09 (0.87, 1.36) Higher Diabetes PGS 1.02 (0.89, 1.18) 1.02 (0.91, 1.14) 0.70 (0.41, 1.20) 0.89 (0.62, 1.27) Higher Myocardial Infarction PGS 0.94 (0.82, 1.08) 1.03 (0.91, 1.17) 0.72 (0.47, 1.11) 0.83 (0.63, 1.09) Higher Parity PGS 0.94 (0.82, 1.08) 1.01 (0.90, 1.14) 0.79 (0.52, 1.20) 0.89 (0.68, 1.16) Lower Age at First Birth PGS 1.01 (0.88, 1.17) 1.00 (0.89, 1.13) 1.11 (0.74, 1.66) 1.01 (0.80, 1.28) Lower Age at Menarche PGS — 1.01 (0.90, 1.13) — 0.96 (0.73, 1.26) Lower Age at Menopause PGS — 1.03 (0.92, 1.15) — 0.93 (0.72, 1.19) Lower Education PGS 0.98 (0.86, 1.13) 1.02 (0.91, 1.14) 0.81 (0.53, 1.25) 0.89 (0.69, 1.15) Lower General Cognition PGS 0.95 (0.82, 1.10) 1.05 (0.93, 1.18) 0.80 (0.54, 1.20) 1.02 (0.79, 1.30) Lower Height PGS 0.97 (0.84, 1.11) 1.02 (0.91, 1.14) 0.71 (0.43, 1.15) 1.05 (0.77, 1.42) Lower Longevity PGS 0.98 (0.84, 1.14) 1.00 (0.89, 1.12) 1.11 (0.83, 1.49) 1.00 (0.78, 1.28) eiss 24
S1 File. Variable Construction.
Sociodemographic characteristics. Respondents were classified as
Childless (1) if they reported never having children compared to reporting at least one child (-1). Respondents were classified as
Foreign Born if they reported being born outside of the United States (1) compared to being born in the US (-1). Among respondents who reported having at least one child,
Higher Age at Last Birth was a standardized measure (with mean zero, standard deviation one) of the respondent’s age when they last gave birth. Among respondents who were classified as childless, H igher Age at Last Birth was set to zero.
Higher Parity was defined as the number of children the respondent reported ever having. Values were reverse coded and standardized such that higher parity reflected higher risk. Among respondents who reported having at least one child,
Lower Age at First Birth was a standardized measure (with mean zero, standard deviation one) of the respondent’s age when they first gave birth. Values were reverse coded such that younger ages reflected higher risk. Among respondents who were classified as childless,
Lower Age at First Birth was set to zero. Respondents were classified as
Southern Born if they reported being born in the South Atlantic, Eastern South Central, or Western South Central Census Divisions of the United States (1) compared to being born outside of these divisions (-1). eiss 25 Respondents who served in the military were classified as a
Veteran (1) compared to not (-1). Early-Life Characteristics. Respondent’s years of completed education were reverse coded and standardized with mean zero and standard deviation one to create the variable
Lower Education . This same process was used to create
Lower Father's Education and
Lower Mother's Education . Lower Father Occupational Status was scored by categorizing the respondent’s father’s occupation as (1) Executives and managers, (2) Professional specialty, (3) Sales and administration, (4) Protection services and armed forces, (5) Cleaning, building, food preparation, and personal services, and (6) Production, construction, and operation occupations. Scores were then standardized with mean zero and standard deviation one. Scores were then standardized with mean zero and standard deviation one. Respondents self-reported their overall health from birth to age 16 as excellent, very good, good, fair, and poor. Responses were scored such that higher values corresponded to worse health and then standardized with mean zero and standard deviation one to generate the variable
Lower SR Childhood Health.
Respondents self-reported their family’s financial well-being from birth to age 16 as being pretty well off financially, about average, or poor. Responses were scored such that higher values corresponded to lower socioeconomic status (SES) and then standardized with mean zero and standard deviation one to generate the variable
Lower SR Childhood SES. eiss 26 Economic Characteristics
Food Insecurity was scored as binary (-1/1), with 1 indicating the respondent had reported not having enough money to buy the food they needed over the two year prior to their interview in 2000, and -1 indicating the respondent had enough money to buy the food they needed. Income was measured in nominal dollars during the respondent’s interview in 2000 and is the sum of all income in a household, including: respondent’s and spouse’s wage/salary income, bonuses/overtime pay/commissions/tips, 2nd job or military reserve earnings, professional practice or trade income; household business or farm income, self-employment earnings, business income, gross rent, dividend and interest income, trust funds or royalties, and other asset income; respondent’s and spouse’s income from all pensions and annuities; respondent’s and spouse’s total Social Security income (including that which is and is not received due to disability); respondent’s and spouse’s income from unemployment and worker’s compensation; respondent’s and spouse’s income from veterans’ benefits, welfare, and food stamps; and alimony, other income, and lump sums from insurance, pension, and inheritance at the household level. This value was then log-transformed, reverse coded, and standardized with mean zero and standard deviation one to generate the variable
Lower Income . Respondents reported the safety of their neighborhood. Response options were excellent, very good, good, fair, and poor. Responses were coded such that higher values corresponded to
Lower Neighborhood Safety and then standardized with mean zero and standard deviation one. Wealth was measured in nominal dollars during the respondent’s interview in 2000 as the sum of all wealth components (except secondary home) less all debt. This value was then log-eiss 27 transformed, reverse coded, and standardized with mean zero and standard deviation one to generate the variable
Lower Wealth.
Medicaid was coded as binary (-1/1), with 1 indicating the respondent reported being covered by Medicaid during their interview in 2000 and -1 indicating otherwise.
Medicare was coded as binary (-1/1), with 1 indicating the respondent reported being covered by Medicare during their interview in 2000 and -1 indicating otherwise.
No Insurance was coded as binary (-1/1), with 1 indicating the respondent reported being uninsured during their interview in 2000 and -1 indicating otherwise.
Food Stamps was scored as binary (-1/1), with 1 indicating the respondent or a family member living with them received government food stamps over the two year prior to their interview in 2000, and -1 indicating otherwise.
Retired was coded as binary (-1/1), with 1 indicating the respondent reported being retired during their interview in 2000 and -1 indicating otherwise.
Unemployed was coded as binary (-1/1), with 1 indicating the respondent reported was not working for pay while actively looking for a job in the last four weeks prior to their interview in 2000 and -1 indicating otherwise. Behaviors
Active Smoker was scored as binary (-1/1), with 1 indicating the respondent reported being a current smoker and -1 otherwise. eiss 28
Ever Smoked was scored as binary (-1/1), with 1 indicating the respondent reported ever smoking and -1 indicating otherwise.
Heavy Alcohol Use was scored as binary (-1/1), with 1 indicating the respondent reported drinking three or more drinks per day on days they drank and -1 otherwise. Body mass index (BMI) was calculated by dividing the respondent's weight by their height-squared and then standardizing with mean zero and standard deviation one. Higher scores reflected
Higher BMI . Low/No Vigorous Activity was scored as binary (-1/1), with -1 indicating the respondent reported completing vigorous activity (including, for example, sports, heavy housework, or a job that involves physical labor) three or more times per week over the 12 month period prior to their interview in 2000 and 1 indicating otherwise. Health Characteristics All binary health characteristics were coded as 1 if the respondent self-reported the condition or was otherwise coded as -1. Respondents were asked whether a doctor ever told them that they had
Arthritis (arthritis or rheumatism),
Cancer (cancer or a malignant tumor, excluding minor skin cancers),
Diabetes (diabetes or high blood sugar),
Heart Problems (heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems),
Hypertension (high blood pressure or eiss 29 hypertension),
Lung Disease (chronic lung disease such as chronic bronchitis or emphysema),
Psychiatric Illness (any emotional, nervous, or psychiatric problems),
Stroke . Respondents were also asked to report whether they had persistent
Back Pain, Dizziness, Fatigue, Headaches , were
Short of Breath, Wheezing , and whether they were often troubled with
Pain over the 12 month period prior to the interview in 2000. Respondents self-reported their overall health (
SR Health ), hearing (
SR Hearing ), and vision (
SR Vision ). Response options were excellent, very good, good, fair, and poor. Responses were coded such that higher values corresponded to worse health/hearing/vision and then standardized with mean zero and standard deviation one. Social Ties
Ever Divorced was coded as binary (-1/1), with 1 indicating the respondent reported being divorced or separated and -1 indicating the respondent never reported being divorced no separated.
Ever Widowed was coded as binary (-1/1), with 1 indicating the respondent reported being widowed and -1 indicating the respondent never reported being widowed. Respondents reported whether religion was very important, somewhat important, or not too important in their lives. Responses were coded such that higher values corresponded to being
Less Religious and then standardized with mean zero and standard deviation one. eiss 30 Respondents reported whether they felt
Lonely much of the week prior to their interview in 2000. Responses were scored (-1/1), with 1 indicating a response of “yes” and -1 indicating a response of “no.” Respondents reported whether they had any good friends or relatives living in their neighborhood. Responses were used to create binary indicators for
No Friends Nearby (1 if “no”; -1 if “yes”) and
No Relatives Nearby (1 if “no”; -1 if “yes”).
Not Married/Partnered was coded as binary (-1/1), with 1 indicating the respondent was not married and not partnered at the time of their interview in 2000 and -1 indicating otherwise.
Genetic All polygenic scores (PGSs) were residualized by regressing the PGS on the first 10 single nucleotide polymorphisms principal components, computing the residuals from the predictions, and standardizing the residual values to a normal distribution with mean zero and standard deviation 1. Some PGSs were reverse coded as described below. Detailed information on sample selection, consent procedures, and assay processes are provided by the Health and Retirement study (HRS) investigators [1].
Higher AD PGS represents the Alzheimer's disease PGS (with apolipoprotein [ApoE] status variants, rs7412 and rs429358) [2]. eiss 31
Higher Coronary Artery Disease PGS represents the PGS for coronary artery disease which was created by HRS investigators using results from a 2011 study conducted by the Coronary Artery Disease Genome wide Replication and Meta-analysis Consortium [3].
Higher Diabetes PGS represents the type 2 diabetes PGS which was created by HRS investigators using GWAS meta-analysis results from a 2012 study conducted by the Diabetes Genetics Replication and Meta-analysis Consortium [4].
Higher Myocardial Infarction PGS represents the myocardial infarction PGS which was created by HRS investigators using 2015 results from a subgroup analysis of coronary artery disease conducted by the Coronary Artery Disease Genome wide Replication and Meta-analysis Consortium [5].
Higher Parity PGS represents a PGS for the number of children ever born created by HRS investigators from a 2016 study conducted by the Sociogenome Consortium [6].
Values were coded such that higher PGSs corresponded to higher genetic propensity for higher parity levels.
Lower Age at First Birth PGS represents a PGS for age at first birth created by HRS investigators from a 2016 study conducted by the Sociogenome Consortium [6]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for younger age at first birth.
Lower Age at Menarche PGS represents a PGS for age at menarche created by HRS investigators from a 2014 study conducted by the Reproductive Genetics (ReproGen) Consortium [7]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for younger age at menarche. eiss 32
Lower Age at Menopause PGS represents a PGS for age at menopause created by HRS investigators from a 2014 study conducted by the Reproductive Genetics Consortium [8]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for younger age at menopause.
Lower Education PGS represents a PGS for educational attainment which was created by HRS investigators using results from a 2018 study by the Social Science Genetic Association Consortium [9]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for higher educational attainment
Lower General Cognition PGS represents a PGS for general cognition created by HRS investigators from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, 2015 [10]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for higher cognitive functioning
Lower Height PGS represents a PGS for height created by HRS investigators from a 2014 study conducted by the Genetic Investigation of Anthropometric Traits Consortium [11]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for taller height
Lower Longevity PGS represents a PGS for longevity created by HRS investigators from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium, 2015 [12]. Values were reverse coded such that higher PGSs corresponded to lower genetic propensity for higher longevity eiss 33
S2 File. Statistical Methods. Fine-Gray Estimator
The Kaplan-Meier (KM) estimator is a non-parametric statistical technique that was introduced as a way to study time-to-event data with applications to mortality in the presence of attrition (e.g., study drop-out, loss to follow-up) [13]. In the setting for which it was developed (i.e., studies of mortality with incomplete follow-up is incomplete), the required assumption of uninformative censoring—or that subjects who are lost to follow-up (i.e., censored) have the same survival prospects as those who continue to be followed–is likely to be met within the KM framework. It is assumed that these censored subjects for whom we do not observe an event (i.e., death) remain at risk of the event. However, when using the KM estimator to examine a health outcome, mortality becomes another way in which subjects may be censored. In this application, subjects will be censored of they die prior to developing the health outcome of interest yet they will be considered “at risk” in the same way a subject who was lost to follow-up would be. In this case, the KM estimator does not account for the competing risk of mortality and will yield biased estimates. The Fine-Gray model was introduced to account for competing risks in these settings [14]. Whereas in the KM framework a subject who died prior to experiencing the health outcome of interest would be censored, the Fine-Gray classification scheme uses weights to represent the conditional probability of an event of interest for subjects who experienced the competing event, carrying these subjects forward in the analysis rather than censoring them. eiss 34
Random Forest Algorithm
To complement our analyses using the Fine-Gray model, we used a data-driven classification scheme referred to as random forest competing risks survival analysis [15, 16]. Random forest is a non-parametric, ensemble machine-learning algorithm which iteratively bifurcates a dataset based on predictor variables over a number of permutations set by the user and then ranks the importance of each predictor based on its ability to “split” the data [17]. The basis for this algorithm is fitting multiple decision trees on the data and pooling them together which overcomes the limitations of singular classification and regression tree (CART) classification schemees. To do this, the algorithm repeatedly draws bootstrap samples from the analytic sample and a random selection of predictors to grow a predetermined number of decision trees (i.e., a forest) set by the user across which results are pooled. A training data set consisting of n of N cases (approximately two-thirds of the original sample) is generated for each of k decision trees and the remaining cases (one third of the original sample) are used as test data to estimate the out of bag (OOB) classification error. A random sample m of M predictors is selected at each node and the one predictor that best discriminates discrepancies in the outcome is chosen for that particular split. As a result, the root node of each decision tree represents the strongest predictor and the splits that follow are based on the successively strongest predictors. A final classification is made using a majority of votes across all trees. eiss 35 References
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Machine learning. 2001;45(1):5-32. l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l lll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l 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ea s e H ea r t P r ob l e m s S t r o k e P syc h i a t r i c I ll ne ss A r t h r i t i s S ho r t o f B r ea t h D i zz i ne ss B a ck P a i n H eada c he s F a t i gue W hee z i ngLo w e r S R V i s i onLo w e r S R H ea r i ng P a i nLo w / N o V i go r ou s P h ys i c a l A c t i v i t y E v e r S m o k ed A c t i v e S m o k e r H ea vy A l c oho l U s e H i ghe r B M I N o R e l a t i v e s N ea r b y N o F r i end s N ea r b y Lone l y Le ss R e li g i ou s Lo w e r G ene r a l C ogn i t i on P G S H i ghe r A D P G S H i ghe r D i abe t e s P G S H i ghe r C o r ona r y A r t e r y D i s ea s e P G S H i ghe r M y o c a r d i a l I n f a r c t i on P G S Lo w e r Longe v i t y P G S Lo w e r E du c a t i on P G S Lo w e r H e i gh t P G S H i ghe r P a r i t y P G S Lo w e r A ge a t F i r s t B i r t h P G S Baseline AgeForeign BornSouthern BornLower Father's EducationLower Mother's EducationVeteranChildlessHigher ParityLower Age at First BirthHigher Age at Last BirthLower EducationNot Married/PartneredEver WidowedEver DivorcedLower SR Childhood HealthLower SR Childhood SESLower Father Occupational StatusLower IncomeLower WealthLower Neighborhood SafetyRetiredUnemployedNo InsuranceMedicareMedicaidReceived Food StampsFood InsecurityLower SR HealthHypertensionDiabetesCancerLung DiseaseHeart ProblemsStrokePsychiatric IllnessArthritisShort of BreathDizzinessBack PainHeadachesFatigueWheezingLower SR VisionLower SR HearingPainLow/No Vigorous Physical ActivityEver SmokedActive SmokerHeavy Alcohol UseHigher BMINo Relatives NearbyNo Friends NearbyLonelyLess ReligiousLower General Cognition PGSHigher AD PGSHigher Diabetes PGSHigher Coronary Artery Disease PGSHigher Myocardial Infarction PGSLower Longevity PGSLower Education PGSLower Height PGSHigher Parity PGSLower Age at First Birth PGS
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S a f e t y R e t i r ed U ne m p l o y ed N o I n s u r an c e M ed i c a r e M ed i c a i d R e c e i v ed F ood S t a m p s F ood I n s e c u r i t y Lo w e r S R H ea l t h H y pe r t en s i on D i abe t e s C an c e r Lung D i s ea s e H ea r t P r ob l e m s S t r o k e P syc h i a t r i c I ll ne ss A r t h r i t i s S ho r t o f B r ea t h D i zz i ne ss B a ck P a i n H eada c he s F a t i gue W hee z i ngLo w e r S R V i s i onLo w e r S R H ea r i ng P a i nLo w / N o V i go r ou s P h ys i c a l A c t i v i t y E v e r S m o k ed A c t i v e S m o k e r H ea vy A l c oho l U s e H i ghe r B M I N o R e l a t i v e s N ea r b y N o F r i end s N ea r b y Lone l y Le ss R e li g i ou s Lo w e r G ene r a l C ogn i t i on P G S H i ghe r A D P G S H i ghe r D i abe t e s P G S H i ghe r C o r ona r y A r t e r y D i s ea s e P G S H i ghe r M y o c a r d i a l I n f a r c t i on P G S Lo w e r Longe v i t y P G S Lo w e r E du c a t i on P G S Lo w e r H e i gh t P G S Lo w e r A ge a t M ena r c he P G S Lo w e r A ge a t M enopau s e P G S H i ghe r P a r i t y P G S Lo w e r A ge a t F i r s t B i r t h P G S Baseline AgeForeign BornSouthern BornLower Father's EducationLower Mother's EducationVeteranChildlessHigher ParityLower Age at First BirthHigher Age at Last BirthLower EducationNot Married/PartneredEver WidowedEver DivorcedLower SR Childhood HealthLower SR Childhood SESLower Father Occupational StatusLower IncomeLower WealthLower Neighborhood SafetyRetiredUnemployedNo InsuranceMedicareMedicaidReceived Food StampsFood InsecurityLower SR HealthHypertensionDiabetesCancerLung DiseaseHeart ProblemsStrokePsychiatric IllnessArthritisShort of BreathDizzinessBack PainHeadachesFatigueWheezingLower SR VisionLower SR HearingPainLow/No Vigorous Physical ActivityEver SmokedActive SmokerHeavy Alcohol UseHigher BMINo Relatives NearbyNo Friends NearbyLonelyLess ReligiousLower General Cognition PGSHigher AD PGSHigher Diabetes PGSHigher Coronary Artery Disease 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l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1 B a s e li ne A ge F o r e i gn B o r n S ou t he r n B o r nLo w e r F a t he r ' s E du c a t i onLo w e r M o t he r ' s E du c a t i on V e t e r an C h il d l e ss H i ghe r P a r i t y Lo w e r A ge a t F i r s t B i r t h H i ghe r A ge a t La s t B i r t hLo w e r E du c a t i on N o t M a rr i ed / P a r t ne r ed E v e r W i do w ed E v e r D i v o r c edLo w e r S R C h il dhood H ea l t hLo w e r S R C h il dhood SES Lo w e r F a t he r O cc upa t i ona l S t a t u s Lo w e r I n c o m eLo w e r W ea l t hLo w e r N e i ghbo r hood S a f e t y R e t i r ed U ne m p l o y ed N o I n s u r an c e M ed i c a r e M ed i c a i d R e c e i v ed F ood S t a m p s F ood I n s e c u r i t y Lo w e r S R H ea l t h H y pe r t en s i on D i abe t e s C an c e r Lung D i s ea s e H ea r t P r ob l e m s S t r o k e P syc h i a t r i c I ll ne ss A r t h r i t i s S ho r t o f B r ea t h D i zz i ne ss B a ck P a i n H eada c he s F a t i gue W hee z i ngLo w e r S R V i s i onLo w e r S R H ea r i ng P a i nLo w / N o V i go r ou s P h ys i c a l A c t i v i t y E v e r S m o k ed A c t i v e S m o k e r H ea vy A l c oho l U s e H i ghe r B M I N o R e l a t i v e s N ea r b y N o F r i end s N ea r b y Lone l y Le ss R e li g i ou s Lo w e r G ene r a l C ogn i t i on P G S H i ghe r A D P G S H i ghe r D i abe t e s P G S H i ghe r C o r ona r y A r t e r y D i s ea s e P G S H i ghe r M y o c a r d i a l I n f a r c t i on P G S Lo w e r Longe v i t y P G S Lo w e r E du c a t i on P G S Lo w e r H e i gh t P G S H i ghe r P a r i t y P G S Lo w e r A ge a t F i r s t B i r t h P G S Baseline AgeForeign BornSouthern BornLower Father's EducationLower Mother's EducationVeteranChildlessHigher ParityLower Age at First BirthHigher Age at Last BirthLower EducationNot Married/PartneredEver WidowedEver DivorcedLower SR Childhood HealthLower SR Childhood SESLower Father Occupational StatusLower IncomeLower WealthLower Neighborhood SafetyRetiredUnemployedNo InsuranceMedicareMedicaidReceived Food StampsFood InsecurityLower SR HealthHypertensionDiabetesCancerLung DiseaseHeart ProblemsStrokePsychiatric IllnessArthritisShort of BreathDizzinessBack PainHeadachesFatigueWheezingLower SR VisionLower SR HearingPainLow/No Vigorous Physical ActivityEver SmokedActive SmokerHeavy Alcohol UseHigher BMINo Relatives NearbyNo Friends NearbyLonelyLess ReligiousLower General Cognition PGSHigher AD PGSHigher Diabetes PGSHigher Coronary Artery Disease PGSHigher Myocardial Infarction PGSLower Longevity PGSLower Education PGSLower Height PGSHigher Parity PGSLower Age at First Birth PGS
NH Black Men l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l lll l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l ll l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1 B a s e li ne A ge F o r e i gn B o r n S ou t he r n B o r nLo w e r F a t he r ' s E du c a t i onLo w e r M o t he r ' s E du c a t i on V e t e r an C h il d l e ss H i ghe r P a r i t y Lo w e r A ge a t F i r s t B i r t h H i ghe r A ge a t La s t B i r t hLo w e r E du c a t i on N o t M a rr i ed / P a r t ne r ed E v e r W i do w ed E v e r D i v o r c edLo w e r S R C h il dhood H ea l t hLo w e r S R C h il dhood SES Lo w e r F a t he r O cc upa t i ona l S t a t u s Lo w e r I n c o m eLo w e r W ea l t hLo w e r N e i ghbo r hood S a f e t y R e t i r ed U ne m p l o y ed N o I n s u r an c e M ed i c a r e M ed i c a i d R e c e i v ed F ood S t a m p s F ood I n s e c u r i t y Lo w e r S R H ea l t h H y pe r t en s i on D i abe t e s C an c e r Lung D i s ea s e H ea r t P r ob l e m s S t r o k e P syc h i a t r i c I ll ne ss A r t h r i t i s S ho r t o f B r ea t h D i zz i ne ss B a ck P a i n H eada c he s F a t i gue W hee z i ngLo w e r S R V i s i onLo w e r S R H ea r i ng P a i nLo w / N o V i go r ou s P h ys i c a l A c t i v i t y E v e r S m o k ed A c t i v e S m o k e r H ea vy A l c oho l U s e H i ghe r B M I N o R e l a t i v e s N ea r b y N o F r i end s N ea r b y Lone l y Le ss R e li g i ou s Lo w e r G ene r a l C ogn i t i on P G S H i ghe r A D P G S H i ghe r D i abe t e s P G S H i ghe r C o r ona r y A r t e r y D i s ea s e P G S H i ghe r M y o c a r d i a l I n f a r c t i on P G S Lo w e r Longe v i t y P G S Lo w e r E du c a t i on P G S Lo w e r H e i gh t P G S Lo w e r A ge a t M ena r c he P G S Lo w e r A ge a t M enopau s e P G S H i ghe r P a r i t y P G S Lo w e r A ge a t F i r s t B i r t h P G S Baseline AgeForeign BornSouthern BornLower Father's EducationLower Mother's EducationVeteranChildlessHigher ParityLower Age at First BirthHigher Age at Last BirthLower EducationNot Married/PartneredEver WidowedEver DivorcedLower SR Childhood HealthLower SR Childhood SESLower Father Occupational StatusLower IncomeLower WealthLower Neighborhood SafetyRetiredUnemployedNo InsuranceMedicareMedicaidReceived Food StampsFood InsecurityLower SR HealthHypertensionDiabetesCancerLung DiseaseHeart ProblemsStrokePsychiatric IllnessArthritisShort of BreathDizzinessBack PainHeadachesFatigueWheezingLower SR VisionLower SR HearingPainLow/No Vigorous Physical ActivityEver SmokedActive SmokerHeavy Alcohol UseHigher BMINo Relatives NearbyNo Friends NearbyLonelyLess ReligiousLower General Cognition PGSHigher AD PGSHigher Diabetes PGSHigher Coronary Artery Disease PGSHigher Myocardial Infarction PGSLower Longevity PGSLower Education PGSLower Height PGSLower Age at Menarche PGSLower Age at Menopause PGSHigher Parity PGSLower Age at First Birth PGS
NH Black Women
Fig S1 l ll lll ll lllll ll l llll lll ll ll
Higher Age at Last BirthHigher Parity Lower Age at First BirthVeteran ChildlessForeign Born Southern Born0 1 2 3 4 50 1 2 3 4 5 0 1 2 3 4 50 1 2 3 4 5 0 1 2 3 4 50 1 2 3 4 5 0 1 2 3 4 5
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Sociodemographic
Fig S2 ll l lll ll lll lll llllll ll l
Lower SR Childhood SES Lower Father Occupational StatusLower Education Lower SR Childhood HealthLower Father's Education Lower Mother's Education2 4 6 2 4 62 4 6 2 4 62 4 6 2 4 6
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Early−Life l ll ll llll l ll lll l lll llllll ll ll ll lll lllll
Received Food Stamps Food InsecurityMedicare MedicaidUnemployed No InsuranceLower Neighborhood Safety RetiredLower Income Lower Wealth0 1 2 3 4 0 1 2 3 40 1 2 3 4 0 1 2 3 40 1 2 3 4 0 1 2 3 40 1 2 3 4 0 1 2 3 40 1 2 3 4 0 1 2 3 4
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Economic llll llll llll l llllll lll lll l ll ll lll lll lll llllll ll lll lllll llll lllll lll l lll
Lower SR Hearing PainHeadaches Fatigue Wheezing Lower SR VisionArthritis Short of Breath Dizziness Back PainLung Disease Heart Problems Stroke Psychiatric IllnessLower SR Health Hypertension Diabetes Cancer1 2 3 1 2 31 2 3 1 2 3 1 2 3 1 2 31 2 3 1 2 3 1 2 3 1 2 31 2 3 1 2 3 1 2 3 1 2 31 2 3 1 2 3 1 2 3 1 2 3
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Health lll llllll ll l lllll ll
Higher BMIActive Smoker Heavy Alcohol UseLow/No Vigorous Physical Activity Ever Smoked1 2 3 41 2 3 4 1 2 3 41 2 3 4 1 2 3 4
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Behaviors l ll ll lll lllllll ll l l lll ll l ll
Less ReligiousNo Friends Nearby LonelyEver Divorced No Relatives NearbyNot Married/Partnered Ever Widowed0.5 1.0 1.5 2.00.5 1.0 1.5 2.0 0.5 1.0 1.5 2.00.5 1.0 1.5 2.0 0.5 1.0 1.5 2.00.5 1.0 1.5 2.0 0.5 1.0 1.5 2.0
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Social Ties l llll lll lllllll llllll l ll lll lllllllll llll lll
Higher Parity PGS Lower Age at First Birth PGSLower Age at Menarche PGS Lower Age at Menopause PGSLower Education PGS Lower Height PGSHigher Myocardial Infarction PGS Lower Longevity PGSHigher Diabetes PGS Higher Coronary Artery Disease PGSLower General Cognition PGS Higher AD PGS0 1 2 3 0 1 2 30 1 2 3 0 1 2 30 1 2 3 0 1 2 30 1 2 3 0 1 2 30 1 2 3 0 1 2 30 1 2 3 0 1 2 3
NH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White MenNH Black WomenNH Black MenNH White WomenNH White Men
Hazard Ratio
Genetic l lll l lll lll l ll l l l ll lll lll ll lll l l ll lll l llll ll l lll ll llll lll ll lll
MedicareFood InsecurityLung DiseaseRetiredVeteranCancerArthritisEver WidowedHigher Myocardial Infarction PGSLower Age at First Birth PGSHypertensionLower Education PGSNo Friends NearbyNo InsuranceHigher Coronary Artery Disease PGSHigher AD PGSLower General Cognition PGSLower Height PGSChildlessHigher Parity PGSLess ReligiousHeart ProblemsLonelyHigher BMIHeavy Alcohol UseLower SR Childhood SESHigher ParityDiabetesHigher Diabetes PGSLow/No Vigorous Physical ActivityLower Age at First BirthHigher Age at Last BirthLower Longevity PGSUnemployedBack PainSouthern BornEver DivorcedNot Married/PartneredLower SR VisionStrokeWheezingEver SmokedNo Relatives NearbyHeadachesForeign BornLower SR HearingLower Father Occupational StatusLower Father's EducationShort of BreathLower Mother's EducationFatigueLower IncomeDizzinessPainLower SR Childhood HealthActive SmokerLower WealthLower SR HealthLower Neighborhood SafetyLower EducationPsychiatric IllnessReceived Food StampsMedicaid
Hazard Ratio P r ed i c t o r NH White Men (n=2561) lllll l l ll lll llll ll ll lll l ll llll ll llll ll llllllll l lll l ll lllll lll llll
VeteranChildlessFood InsecurityMedicareCancerEver WidowedLess ReligiousRetiredNo InsuranceHeart ProblemsLower Height PGSLower Education PGSUnemployedLower Age at First Birth PGSHigher Myocardial Infarction PGSHigher BMIBack PainLower General Cognition PGSEver SmokedNo Relatives NearbyLow/No Vigorous Physical ActivityMedicaidHigher Parity PGSHypertensionNot Married/PartneredLower Longevity PGSHigher AD PGSHigher Coronary Artery Disease PGSDiabetesLower SR HearingHigher ParityLower Father's EducationLower Age at Menopause PGSLower SR Childhood SESLower SR VisionHigher Diabetes PGSNo Friends NearbyArthritisShort of BreathLower Age at Menarche PGSLower Father Occupational StatusHigher Age at Last BirthPainLower Mother's EducationLower WealthSouthern BornLung DiseaseActive SmokerWheezingDizzinessPsychiatric IllnessEver DivorcedLower SR Childhood HealthFatigueForeign BornLower SR HealthStrokeLower Age at First BirthLower Neighborhood SafetyLower EducationLonelyLower IncomeReceived Food StampsHeavy Alcohol UseHeadaches
Hazard Ratio P r ed i c t o r NH White Women (n=3377) ll lll llll lll l ll llllll l lll ll ll ll ll l ll lll l ll ll lll l l lllllll l lll ll
CancerNo InsuranceHeart ProblemsVeteranRetiredMedicareFood InsecurityHigher Coronary Artery Disease PGSPsychiatric IllnessEver WidowedHeavy Alcohol UseFatigueHigher Age at Last BirthLower Neighborhood SafetyEver DivorcedLower Height PGSHigher BMIHypertensionLower Education PGSHigher Diabetes PGSHigher Myocardial Infarction PGSLower General Cognition PGSLow/No Vigorous Physical ActivityArthritisHigher AD PGSStrokeNot Married/PartneredLower Age at First Birth PGSLower Age at First BirthHigher Parity PGSLess ReligiousLower SR HearingLower IncomeWheezingActive SmokerLower WealthDizzinessNo Relatives NearbyHeadachesLower SR HealthHigher ParityLower Longevity PGSPainLower SR Childhood HealthChildlessDiabetesBack PainSouthern BornLower SR Childhood SESForeign BornLower Mother's EducationLower SR VisionEver SmokedLonelyNo Friends NearbyLung DiseaseLower Father's EducationShort of BreathReceived Food StampsMedicaidLower EducationLower Father Occupational Status
Hazard Ratio P r ed i c t o r NH Black Men (n=283) l lllll lll lll l ll lll ll ll l l ll llll lll ll l ll lllll lll l ll ll ll l ll ll ll ll lll
Less ReligiousForeign BornFood InsecurityChildlessNo InsuranceRetiredMedicareBack PainHigher Myocardial Infarction PGSStrokeLower Education PGSArthritisLower SR HearingLower Age at Menarche PGSCancerEver WidowedHigher Age at Last BirthLow/No Vigorous Physical ActivityHigher Parity PGSEver SmokedHigher BMILower Longevity PGSLower Age at First Birth PGSLower Age at Menopause PGSNot Married/PartneredActive SmokerLower SR VisionNo Friends NearbyHigher Diabetes PGSLower General Cognition PGSEver DivorcedLower Age at First BirthLower Height PGSPainDiabetesVeteranLower WealthWheezingLung DiseaseHigher Coronary Artery Disease PGSHigher ParityShort of BreathLower SR Childhood SESLower SR Childhood HealthHeart ProblemsHeavy Alcohol UseLower IncomeNo Relatives NearbyLower Neighborhood SafetyLower Mother's EducationLower Father's EducationFatigueLonelyHypertensionSouthern BornMedicaidHeadachesPsychiatric IllnessLower SR HealthHigher AD PGSLower EducationReceived Food StampsDizzinessUnemployedLower Father Occupational Status
Hazard Ratio P r ed i c t o r NH Black Women (n=525)
Langa−Weir Classifier ll ll ll l
Early−LifeSociodemographic EconomicSocial Ties BehaviorsHealth Genetic
Fig S3 l lllllll llll ll ll llll ll l ll ll lll l l ll l ll l lllllllll llllll llll llll l
UnemployedFood InsecurityLung DiseaseLess ReligiousHigher Parity PGSHypertensionNo InsuranceCancerEver WidowedRetiredChildlessHigher Myocardial Infarction PGSLower Height PGSVeteranLower General Cognition PGSMedicareEver DivorcedLower Education PGSHeavy Alcohol UseHigher ParityHigher Coronary Artery Disease PGSLower Age at First Birth PGSArthritisLower Age at First BirthActive SmokerHeart ProblemsLower Longevity PGSHigher AD PGSHigher Age at Last BirthNot Married/PartneredHigher Diabetes PGSNo Friends NearbyEver SmokedLower SR Childhood SESLonelyForeign BornBack PainNo Relatives NearbyLow/No Vigorous Physical ActivityHigher BMILower SR Childhood HealthDiabetesWheezingSouthern BornLower SR VisionHeadachesLower IncomeStrokeLower SR HearingLower Father Occupational StatusPainShort of BreathLower Father's EducationLower SR HealthLower WealthLower Mother's EducationFatigueDizzinessLower Neighborhood SafetyLower EducationPsychiatric IllnessMedicaidReceived Food Stamps
Hazard Ratio P r ed i c t o r NH White Men (n=2561) lll lll l lllll ll llllll lll lll llll l l l lllll lll llllll ll ll ll llllllllll ll
VeteranChildlessFood InsecurityCancerRetiredReceived Food StampsLess ReligiousMedicareBack PainLung DiseaseNo Friends NearbyHigher ParityEver WidowedHigher Coronary Artery Disease PGSLower Age at Menopause PGSActive SmokerNo InsuranceNot Married/PartneredLower Longevity PGSHigher Myocardial Infarction PGSHigher BMILower Father's EducationShort of BreathDizzinessLower Age at First Birth PGSHeart ProblemsLower Education PGSEver SmokedLow/No Vigorous Physical ActivityForeign BornLower SR HearingLower Height PGSLower Neighborhood SafetyHigher AD PGSHigher Diabetes PGSWheezingDiabetesSouthern BornLower WealthHypertensionNo Relatives NearbyPainLower Age at Menarche PGSArthritisLower Mother's EducationHigher Parity PGSLower SR Childhood HealthUnemployedLower SR VisionMedicaidLower General Cognition PGSFatigueStrokeLower Father Occupational StatusLower EducationLower SR Childhood SESLower IncomeEver DivorcedLower SR HealthLonelyHigher Age at Last BirthHeavy Alcohol UseLower Age at First BirthPsychiatric IllnessHeadaches
Hazard Ratio P r ed i c t o r NH White Women (n=3377) l llll ll ll llll ll llll ll l ll lll ll ll ll l ll llll llll lll ll l ll ll l ll lll l l
Psychiatric IllnessHeart ProblemsNo InsuranceLess ReligiousLower Neighborhood SafetyHigher AD PGSForeign BornWheezingHigher Myocardial Infarction PGSLower Education PGSLower Height PGSHypertensionHigher Diabetes PGSLow/No Vigorous Physical ActivityEver DivorcedCancerHigher Parity PGSLower General Cognition PGSVeteranHeavy Alcohol UseRetiredLower SR Childhood SESReceived Food StampsNo Relatives NearbyHigher Coronary Artery Disease PGSHigher BMIEver WidowedArthritisNo Friends NearbyLower SR HealthHigher Age at Last BirthMedicareNot Married/PartneredLower WealthFood InsecurityLower Father's EducationFatigueActive SmokerLower Mother's EducationLower SR HearingLower Age at First Birth PGSLower Longevity PGSLower IncomePainEver SmokedDizzinessLower SR Childhood HealthStrokeHigher ParityLower EducationHeadachesBack PainLower SR VisionLung DiseaseDiabetesSouthern BornShort of BreathLower Age at First BirthChildlessMedicaidLower Father Occupational StatusLonely
Hazard Ratio P r ed i c t o r NH Black Men (n=283) l llll lll ll ll l ll l lll ll l l ll llll lllll l ll llll l ll llll l l ll l ll ll l l ll ll l
Less ReligiousChildlessForeign BornNo InsuranceFood InsecurityHigher Parity PGSHigher Age at Last BirthHigher Myocardial Infarction PGSHigher Diabetes PGSLower Father Occupational StatusLower Longevity PGSEver DivorcedBack PainLower Age at Menarche PGSArthritisLower Age at First BirthLower Education PGSLow/No Vigorous Physical ActivityLower SR VisionCancerRetiredLower Neighborhood SafetyLower General Cognition PGSLower SR HearingMedicareLower Age at Menopause PGSEver SmokedNot Married/PartneredHeavy Alcohol UseLower IncomeHigher BMIActive SmokerDiabetesEver WidowedLower SR Childhood HealthStrokePsychiatric IllnessHigher Coronary Artery Disease PGSLower WealthLower Age at First Birth PGSLower Height PGSHeart ProblemsHigher ParityLower Mother's EducationPainWheezingNo Relatives NearbyLower SR Childhood SESSouthern BornLower Father's EducationNo Friends NearbyMedicaidLower EducationHypertensionReceived Food StampsFatigueLower SR HealthLung DiseaseShort of BreathHigher AD PGSDizzinessLonelyHeadachesUnemployed
Hazard Ratio P r ed i c t o r NH Black Women (n=525)
Hurd Classifier ll ll ll l
Early−LifeSociodemographic EconomicSocial Ties BehaviorsHealth Genetic
Fig S4 l l lll l ll ll ll ll lll lll ll l ll ll lll l l ll l lll lllllllll lll lll lllll ll ll
UnemployedChildlessVeteranCancerNot Married/PartneredLung DiseaseFood InsecurityNo InsuranceLess ReligiousRetiredHigher ParityLower General Cognition PGSMedicareLower Longevity PGSHypertensionLower Height PGSHeavy Alcohol UseHigher Age at Last BirthLower Age at First Birth PGSHigher Coronary Artery Disease PGSLower Age at First BirthNo Friends NearbyArthritisHigher Myocardial Infarction PGSEver WidowedHeart ProblemsHigher Parity PGSLower Education PGSHigher AD PGSHigher Diabetes PGSEver DivorcedForeign BornBack PainLower SR Childhood SESHeadachesLower SR Childhood HealthSouthern BornLow/No Vigorous Physical ActivityLonelyEver SmokedNo Relatives NearbyShort of BreathWheezingActive SmokerHigher BMIPainLower SR VisionStrokeLower WealthLower IncomeLower SR HearingLower Father Occupational StatusLower Father's EducationLower SR HealthDizzinessDiabetesLower Neighborhood SafetyFatigueLower Mother's EducationPsychiatric IllnessLower EducationMedicaidReceived Food Stamps
Hazard Ratio P r ed i c t o r NH White Men (n=2561) ll llll l ll lll ll l lll ll lll lll ll ll ll l lll ll lll llllll llll ll lllll ll lllll
ChildlessFood InsecurityVeteranRetiredCancerMedicareNo Friends NearbyLess ReligiousBack PainEver WidowedReceived Food StampsShort of BreathLower Education PGSHigher Coronary Artery Disease PGSHigher Myocardial Infarction PGSNo InsuranceLower Age at First Birth PGSLower Age at Menarche PGSWheezingHeart ProblemsNot Married/PartneredEver SmokedNo Relatives NearbyLower Longevity PGSLower Age at Menopause PGSActive SmokerLow/No Vigorous Physical ActivitySouthern BornHigher Parity PGSHigher AD PGSHypertensionHigher Diabetes PGSDizzinessArthritisHigher ParityLung DiseaseLower General Cognition PGSLower WealthLower Height PGSPainHigher BMIFatigueLower SR HearingHigher Age at Last BirthLower SR Childhood HealthForeign BornStrokeHeavy Alcohol UseLower SR VisionEver DivorcedLower SR Childhood SESLonelyLower Father's EducationLower SR HealthMedicaidLower IncomeLower Father Occupational StatusLower EducationLower Mother's EducationLower Age at First BirthLower Neighborhood SafetyDiabetesPsychiatric IllnessUnemployedHeadaches
Hazard Ratio P r ed i c t o r NH White Women (n=3377) l llll ll lllll l ll llll ll l ll lll ll ll ll l ll llll ll ll lllll l lll llll lll l l
Heart ProblemsNo InsuranceLower Neighborhood SafetyPsychiatric IllnessWheezingLower Education PGSHigher Myocardial Infarction PGSLower General Cognition PGSCancerLower Height PGSHigher Diabetes PGSLess ReligiousHigher Parity PGSHigher Coronary Artery Disease PGSForeign BornRetiredMedicareHypertensionEver WidowedNot Married/PartneredFatigueLow/No Vigorous Physical ActivityReceived Food StampsNo Relatives NearbyHigher BMILower SR HearingLower SR HealthVeteranHigher AD PGSHeavy Alcohol UseFood InsecurityDizzinessLower EducationArthritisLower Mother's EducationStrokeHigher Age at Last BirthEver DivorcedLower Father's EducationActive SmokerLower SR Childhood SESLower Longevity PGSHigher ParityLower IncomeLower Age at First Birth PGSLower SR Childhood HealthNo Friends NearbyLower WealthPainLower SR VisionEver SmokedDiabetesHeadachesLower Father Occupational StatusSouthern BornLower Age at First BirthBack PainShort of BreathLung DiseaseMedicaidLonelyChildless
Hazard Ratio P r ed i c t o r NH Black Men (n=283) llllll lll lll lllll lll ll l l ll llll lll ll l ll lllll ll lll l ll ll l ll llll llll l
ChildlessFood InsecurityHeavy Alcohol UseLess ReligiousNo InsuranceHigher Diabetes PGSHigher Myocardial Infarction PGSLow/No Vigorous Physical ActivityRetiredLower SR HearingLower Longevity PGSHigher Age at Last BirthCancerVeteranEver WidowedHigher Parity PGSLower Father Occupational StatusLower Education PGSLower Age at Menarche PGSLower General Cognition PGSNot Married/PartneredLower Age at Menopause PGSMedicareLower IncomeForeign BornEver SmokedLower SR Childhood SESLower SR VisionSouthern BornWheezingBack PainLower Neighborhood SafetyLower Age at First Birth PGSHigher BMIActive SmokerArthritisLower WealthNo Friends NearbyLower Father's EducationLower EducationLower Age at First BirthLower SR Childhood HealthLower Height PGSHigher Coronary Artery Disease PGSLower Mother's EducationNo Relatives NearbyPainMedicaidHigher ParityDiabetesHeart ProblemsStrokeHypertensionFatigueEver DivorcedLonelyShort of BreathHeadachesUnemployedLung DiseaseLower SR HealthDizzinessPsychiatric IllnessHigher AD PGSReceived Food Stamps
Hazard Ratio P r ed i c t o r NH Black Women (n=525)
Expert Classifier ll ll ll l
Early−LifeSociodemographic EconomicSocial Ties BehaviorsHealth Genetic
Fig S5 ll ll llll lll l ll ll l lll ll l ll ll lll l l ll l lll lll llll lll ll lll llllllll l
UnemployedFood InsecurityVeteranLung DiseaseCancerLess ReligiousRetiredHeavy Alcohol UseHigher Parity PGSEver WidowedHigher Myocardial Infarction PGSLower General Cognition PGSHigher Coronary Artery Disease PGSLower Height PGSHigher BMINo Friends NearbyArthritisNo InsuranceChildlessHigher Age at Last BirthLower Age at First BirthLower Longevity PGSHypertensionHigher ParityLower Education PGSEver DivorcedMedicareLower Age at First Birth PGSNot Married/PartneredHigher Diabetes PGSHigher AD PGSLonelyHeart ProblemsEver SmokedLower SR Childhood SESBack PainLow/No Vigorous Physical ActivityNo Relatives NearbyForeign BornHeadachesDiabetesLower SR VisionLower IncomePainShort of BreathLower SR Childhood HealthWheezingLower Father Occupational StatusLower SR HealthActive SmokerLower WealthLower Father's EducationSouthern BornLower SR HearingStrokeDizzinessFatigueLower Mother's EducationLower Neighborhood SafetyPsychiatric IllnessLower EducationMedicaidReceived Food Stamps
Hazard Ratio P r ed i c t o r NH White Men (n=2561) l l llll l ll lll ll lllllll ll lll llll ll l lllll lll lllll l ll ll ll llllllllllll
Food InsecurityMedicareCancerReceived Food StampsChildlessLess ReligiousUnemployedNo Friends NearbyBack PainForeign BornHigher BMIVeteranNot Married/PartneredHigher ParityDizzinessRetiredNo InsuranceLower Longevity PGSEver WidowedLower Age at First Birth PGSLower Age at Menarche PGSHigher Coronary Artery Disease PGSShort of BreathHigher Parity PGSArthritisHigher AD PGSEver SmokedLower Education PGSHigher Diabetes PGSLower Height PGSHeart ProblemsLower Age at Menopause PGSLow/No Vigorous Physical ActivityHypertensionWheezingHigher Myocardial Infarction PGSLower Neighborhood SafetyLower General Cognition PGSFatigueLower WealthDiabetesLower SR HearingActive SmokerMedicaidPainLower SR VisionHigher Age at Last BirthNo Relatives NearbyLung DiseaseLower SR HealthSouthern BornLower SR Childhood HealthEver DivorcedLower Mother's EducationLower Father's EducationStrokeHeavy Alcohol UseLower Age at First BirthLonelyLower SR Childhood SESLower IncomePsychiatric IllnessLower EducationLower Father Occupational StatusHeadaches
Hazard Ratio P r ed i c t o r NH White Women (n=3377) l llll l l ll llll ll llll l ll ll lll ll ll ll l ll llll llll llll ll lllllll lll l l
Heart ProblemsLower Neighborhood SafetyHigher Diabetes PGSLower Height PGSHigher Myocardial Infarction PGSHigher Coronary Artery Disease PGSHigher Parity PGSHigher AD PGSLower General Cognition PGSLower Education PGSPsychiatric IllnessRetiredCancerLower SR Childhood SESWheezingHypertensionHigher BMIReceived Food StampsLow/No Vigorous Physical ActivityFatigueNo InsuranceLess ReligiousMedicareEver DivorcedEver WidowedActive SmokerHeavy Alcohol UseHigher Age at Last BirthNo Relatives NearbyDiabetesNo Friends NearbyLower SR HealthNot Married/PartneredVeteranArthritisForeign BornStrokePainChildlessLower WealthFood InsecurityLower IncomeLower Age at First Birth PGSLower Mother's EducationLower Longevity PGSHeadachesEver SmokedLower Father Occupational StatusLower EducationLower SR Childhood HealthLower SR HearingLower Father's EducationDizzinessHigher ParityLung DiseaseSouthern BornShort of BreathLower SR VisionBack PainLower Age at First BirthMedicaidLonely
Hazard Ratio P r ed i c t o r NH Black Men (n=283) l ll ll lll lll ll ll ll ll ll l l ll llll lll ll l ll lllll ll l ll l ll ll l ll ll ll llll l
ChildlessNo InsuranceFood InsecurityHigher Myocardial Infarction PGSLess ReligiousHeavy Alcohol UseHigher Diabetes PGSLower SR HearingHigher Parity PGSLower Education PGSLower Father Occupational StatusBack PainRetiredLower Age at Menopause PGSCancerEver WidowedLower Age at Menarche PGSLower Father's EducationHigher BMIStrokeNot Married/PartneredMedicareHigher Age at Last BirthNo Friends NearbyLower Longevity PGSLower Age at First Birth PGSLow/No Vigorous Physical ActivityLower General Cognition PGSLower SR VisionArthritisForeign BornLower Height PGSLower SR Childhood HealthEver SmokedNo Relatives NearbyLower Mother's EducationLower Age at First BirthSouthern BornHigher Coronary Artery Disease PGSDiabetesLower WealthLower EducationHigher ParityLower SR Childhood SESHeart ProblemsPainActive SmokerWheezingEver DivorcedShort of BreathLower Neighborhood SafetyLower IncomeLonelyPsychiatric IllnessMedicaidLower SR HealthUnemployedHypertensionFatigueHigher AD PGSHeadachesDizzinessLung DiseaseReceived Food Stamps
Hazard Ratio P r ed i c t o r NH Black Women (n=525)
LASSO Classifier ll ll ll l
Early−LifeSociodemographic EconomicSocial Ties BehaviorsHealth Genetic
Fig S6 ower Height PGSEver SmokedHigher BMIForeign BornHigher ParityChildlessLower Father's EducationCancerLower Father Occupational StatusUnemployedLower Education PGSNo Relatives NearbyEver WidowedLess ReligiousHigher Coronary Artery Disease PGSLow/No Vigorous Physical ActivityHeadachesHigher Myocardial Infarction PGSNo InsuranceLower SR Childhood SESFatigueLower Age at First Birth PGSBack PainArthritisSouthern BornNot Married/PartneredHigher Diabetes PGSHeavy Alcohol UseHeart ProblemsLower Longevity PGSHypertensionPainEver DivorcedVeteranDizzinessNo Friends NearbyLower Mother's EducationLung DiseaseActive SmokerFood InsecurityStrokeLower Age at First BirthDiabetesRetiredLower Neighborhood SafetyHigher AD PGSReceived Food StampsHigher Parity PGSShort of BreathHigher Age at Last BirthMedicaidLower SR VisionLower SR Childhood HealthMedicareLower General Cognition PGSWheezingPsychiatric IllnessLonelyLower SR HealthLower IncomeLower SR HearingLower WealthLower Education
Variable Importance P r ed i c t o r NH White Men (n=2561)
ArthritisLower Age at Menarche PGSEver SmokedMedicareLess ReligiousLower Age at First Birth PGSLow/No Vigorous Physical ActivityHigher BMIHigher Myocardial Infarction PGSNo Friends NearbyLower Age at Menopause PGSBack PainActive SmokerLung DiseaseShort of BreathLower Height PGSVeteranEver DivorcedForeign BornReceived Food StampsChildlessCancerWheezingPainUnemployedNo Relatives NearbyHeavy Alcohol UseHigher AD PGSHigher ParityLower Longevity PGSNo InsuranceNot Married/PartneredHeart ProblemsMedicaidEver WidowedLower SR HearingLower Education PGSHigher Diabetes PGSDizzinessRetiredStrokeHypertensionLower Neighborhood SafetyLower SR Childhood SESLower General Cognition PGSFood InsecurityLower SR VisionLower SR Childhood HealthHigher Coronary Artery Disease PGSLower WealthSouthern BornHigher Parity PGSDiabetesPsychiatric IllnessLower Father's EducationLower Father Occupational StatusHeadachesHigher Age at Last BirthLonelyLower Mother's EducationFatigueLower Age at First BirthLower IncomeLower SR HealthLower Education
Variable Importance P r ed i c t o r NH White Women (n=3377)
Lower General Cognition PGSLower Education PGSDizzinessLower SR HearingLower Height PGSLower Age at First Birth PGSChildlessHigher Age at Last BirthSouthern BornNot Married/PartneredForeign BornPsychiatric IllnessNo InsuranceHigher Diabetes PGSCancerPainDiabetesFatigueWheezingMedicareLower Neighborhood SafetyEver WidowedEver DivorcedLow/No Vigorous Physical ActivityNo Friends NearbyUnemployedLung DiseaseHigher Myocardial Infarction PGSShort of BreathHeart ProblemsEver SmokedActive SmokerLower Age at First BirthHypertensionStrokeReceived Food StampsBack PainHeavy Alcohol UseHigher BMILower Longevity PGSArthritisMedicaidHigher Parity PGSHeadachesLower SR HealthFood InsecurityHigher Coronary Artery Disease PGSNo Relatives NearbyLess ReligiousLower SR Childhood SESLower Mother's EducationLower Father's EducationHigher AD PGSLonelyLower SR VisionHigher ParityLower SR Childhood HealthLower IncomeLower WealthRetiredLower Father Occupational StatusVeteranLower Education
Variable Importance P r ed i c t o r NH Black Men (n=283)
Higher Age at Last BirthHigher Diabetes PGSLower Age at First Birth PGSHigher Myocardial Infarction PGSForeign BornNo Relatives NearbyMedicareLower Education PGSHigher BMIBack PainHeadachesLower Age at Menarche PGSLower Height PGSEver DivorcedNo InsuranceRetiredPsychiatric IllnessArthritisChildlessStrokeShort of BreathVeteranFatigueNo Friends NearbyLow/No Vigorous Physical ActivityLung DiseaseEver WidowedLess ReligiousWheezingCancerEver SmokedHigher AD PGSUnemployedHeart ProblemsLower SR HearingActive SmokerHeavy Alcohol UseLower SR Childhood SESLower Longevity PGSNot Married/PartneredDiabetesHigher Parity PGSHypertensionSouthern BornLower Neighborhood SafetyLower Age at Menopause PGSReceived Food StampsLower General Cognition PGSPainLower SR Childhood HealthMedicaidLower Father Occupational StatusDizzinessHigher Coronary Artery Disease PGSLower SR VisionLower Father's EducationLower Mother's EducationLower Age at First BirthLonelyLower IncomeFood InsecurityLower WealthHigher ParityLower SR HealthLower Education
Variable Importance P r ed i c t o r NH Black Women (n=525)
Langa−Weir Classifier
Fig S7 edicareLower Height PGSHigher Coronary Artery Disease PGSEver DivorcedHigher Myocardial Infarction PGSHeart ProblemsEver SmokedArthritisActive SmokerHeavy Alcohol UseNo Friends NearbyNot Married/PartneredForeign BornChildlessCancerLung DiseaseEver WidowedBack PainUnemployedLower General Cognition PGSLow/No Vigorous Physical ActivityHigher Parity PGSHeadachesHigher AD PGSHigher Diabetes PGSHigher ParityLower SR Childhood SESLower Age at First Birth PGSVeteranNo Relatives NearbyLower Longevity PGSLower Education PGSPainWheezingDiabetesShort of BreathNo InsuranceLess ReligiousLower Age at First BirthHigher Age at Last BirthHypertensionSouthern BornLower Father Occupational StatusRetiredLower Neighborhood SafetyHigher BMIReceived Food StampsLower SR Childhood HealthLower SR VisionLower Mother's EducationPsychiatric IllnessLower SR HearingFood InsecurityLower IncomeFatigueMedicaidLower Father's EducationLonelyLower WealthStrokeLower SR HealthDizzinessLower Education
Variable Importance P r ed i c t o r NH White Men (n=2561)
MedicareActive SmokerHigher ParityLower Age at Menarche PGSLung DiseaseEver SmokedBack PainLess ReligiousHigher AD PGSHigher Diabetes PGSCancerHigher BMINo Relatives NearbyLower SR HearingEver DivorcedHigher Myocardial Infarction PGSLow/No Vigorous Physical ActivityNo Friends NearbyLower SR Childhood HealthVeteranChildlessSouthern BornForeign BornReceived Food StampsNo InsurancePainMedicaidEver WidowedLower WealthHypertensionHeavy Alcohol UseHeart ProblemsUnemployedLower Height PGSShort of BreathWheezingLower Age at Menopause PGSArthritisLower SR Childhood SESLower Mother's EducationLower Age at First Birth PGSLower Longevity PGSNot Married/PartneredFood InsecurityDizzinessDiabetesLower Father Occupational StatusRetiredStrokeLower Neighborhood SafetyLower SR VisionFatigueLower Father's EducationLower EducationPsychiatric IllnessHigher Parity PGSLower Education PGSLonelyLower IncomeLower General Cognition PGSHigher Coronary Artery Disease PGSLower Age at First BirthHigher Age at Last BirthHeadachesLower SR Health −0.002 0.000 0.002
Variable Importance P r ed i c t o r NH White Women (n=3377)
Lower Age at First BirthHypertensionLower General Cognition PGSHigher Age at Last BirthHigher Parity PGSHeart ProblemsHigher Diabetes PGSLower SR HealthLower SR Childhood HealthLower Age at First Birth PGSChildlessLower SR Childhood SESLow/No Vigorous Physical ActivityNo Friends NearbyHigher Myocardial Infarction PGSHigher Coronary Artery Disease PGSArthritisNot Married/PartneredCancerEver WidowedLower Father Occupational StatusWheezingNo Relatives NearbyEver DivorcedLower Neighborhood SafetyActive SmokerLung DiseaseShort of BreathForeign BornMedicareEver SmokedFood InsecurityHeadachesUnemployedHigher BMISouthern BornLower Longevity PGSDiabetesPsychiatric IllnessVeteranDizzinessHeavy Alcohol UsePainReceived Food StampsLower WealthLower Height PGSRetiredLower Education PGSLower Father's EducationBack PainLower SR VisionStrokeLess ReligiousLower Mother's EducationHigher ParityLower EducationFatigueNo InsuranceHigher AD PGSMedicaidLower IncomeLonelyLower SR Hearing
Variable Importance P r ed i c t o r NH Black Men (n=283)
Lower Education PGSMedicareLower SR Childhood SESLower Age at First BirthSouthern BornHigher Coronary Artery Disease PGSLower SR HearingHigher Myocardial Infarction PGSHeavy Alcohol UseEver WidowedHeart ProblemsStrokeLow/No Vigorous Physical ActivityNo Relatives NearbyLower Neighborhood SafetyReceived Food StampsCancerForeign BornChildlessLess ReligiousBack PainNot Married/PartneredActive SmokerDiabetesWheezingNo InsuranceHigher Parity PGSArthritisUnemployedRetiredVeteranPsychiatric IllnessLower SR VisionEver DivorcedShort of BreathDizzinessNo Friends NearbyMedicaidLower Father Occupational StatusLower Age at First Birth PGSFatigueEver SmokedLower General Cognition PGSLung DiseaseLower Age at Menopause PGSLower SR Childhood HealthHigher BMIFood InsecurityPainLower EducationLower Mother's EducationHeadachesLower WealthLower Father's EducationHigher AD PGSLower Height PGSLower Age at Menarche PGSHypertensionHigher ParityHigher Diabetes PGSLower IncomeLower Longevity PGSHigher Age at Last BirthLower SR HealthLonely
Variable Importance P r ed i c t o r NH Black Women (n=525)
Hurd Classifier
Fig S8 edicareHigher Coronary Artery Disease PGSArthritisLower SR Childhood SESHypertensionNot Married/PartneredCancerLower Height PGSLung DiseaseEver SmokedHigher AD PGSForeign BornLower Education PGSHigher ParityEver DivorcedHigher Myocardial Infarction PGSRetiredEver WidowedHeadachesUnemployedHigher Age at Last BirthNo Relatives NearbyVeteranLess ReligiousLower General Cognition PGSNo InsuranceReceived Food StampsHeart ProblemsSouthern BornChildlessLower SR Childhood HealthLower Longevity PGSHeavy Alcohol UseShort of BreathHigher Diabetes PGSLower Age at First Birth PGSLower Age at First BirthPainWheezingBack PainMedicaidHigher Parity PGSLow/No Vigorous Physical ActivityNo Friends NearbyDizzinessFood InsecurityPsychiatric IllnessLower Father Occupational StatusLower Mother's EducationLower SR VisionHigher BMILower Neighborhood SafetyActive SmokerLonelyLower Father's EducationFatigueLower WealthLower IncomeDiabetesLower SR HealthStrokeLower SR HearingLower Education
Variable Importance P r ed i c t o r NH White Men (n=2561)
MedicareLower Age at Menarche PGSLower Longevity PGSEver SmokedActive SmokerLower Age at First Birth PGSBack PainNo InsuranceLow/No Vigorous Physical ActivityLess ReligiousHigher ParityCancerHigher Coronary Artery Disease PGSHigher AD PGSLower Age at Menopause PGSLung DiseaseHigher Diabetes PGSReceived Food StampsVeteranLower Height PGSShort of BreathSouthern BornLower Education PGSLower SR Childhood SESChildlessNo Friends NearbyHigher Myocardial Infarction PGSNot Married/PartneredUnemployedHeavy Alcohol UseHeart ProblemsArthritisHigher BMILower SR Childhood HealthEver WidowedNo Relatives NearbyForeign BornRetiredWheezingDizzinessHypertensionStrokeHeadachesFood InsecurityEver DivorcedMedicaidLower SR VisionLower WealthHigher Age at Last BirthHigher Parity PGSLower SR HearingPainLower Neighborhood SafetyLower IncomeLower Age at First BirthLonelyDiabetesFatiguePsychiatric IllnessLower EducationLower Mother's EducationLower Father Occupational StatusLower General Cognition PGSLower SR HealthLower Father's Education −0.002 0.000 0.002 0.004
Variable Importance P r ed i c t o r NH White Women (n=3377)
Higher Coronary Artery Disease PGSHigher Myocardial Infarction PGSLower General Cognition PGSLower SR HealthHigher Diabetes PGSLower Longevity PGSDiabetesShort of BreathHigher Parity PGSHeart ProblemsHeavy Alcohol UseLower Neighborhood SafetyLower Age at First Birth PGSLower SR Childhood SESHigher BMINo Relatives NearbyChildlessFood InsecurityForeign BornLow/No Vigorous Physical ActivityRetiredFatigueVeteranMedicareHypertensionPainNo Friends NearbyArthritisEver SmokedLower Father's EducationLower Height PGSWheezingUnemployedHigher ParityLower WealthHigher Age at Last BirthEver WidowedLung DiseasePsychiatric IllnessDizzinessActive SmokerSouthern BornCancerHigher AD PGSLess ReligiousReceived Food StampsHeadachesLower Father Occupational StatusLower Age at First BirthEver DivorcedLower SR VisionNot Married/PartneredLower EducationStrokeLower IncomeLower Education PGSLower SR Childhood HealthNo InsuranceLower SR HearingMedicaidBack PainLonelyLower Mother's Education −0.0025 0.0000 0.0025 0.0050 0.0075
Variable Importance P r ed i c t o r NH Black Men (n=283)
MedicareLower Age at First BirthHigher Age at Last BirthLow/No Vigorous Physical ActivityLower SR Childhood SESHigher Parity PGSLower SR HearingMedicaidNo Relatives NearbyEver WidowedStrokeSouthern BornHeadachesPsychiatric IllnessLess ReligiousLung DiseaseChildlessHigher Myocardial Infarction PGSLower SR VisionNot Married/PartneredNo Friends NearbyUnemployedVeteranBack PainShort of BreathArthritisLower Neighborhood SafetyCancerActive SmokerHeavy Alcohol UseHigher BMILower Education PGSNo InsurancePainLower General Cognition PGSWheezingRetiredEver SmokedLower Age at First Birth PGSForeign BornLower Father Occupational StatusLower Father's EducationFatigueLower Height PGSHeart ProblemsLower SR Childhood HealthLower Age at Menopause PGSHigher Coronary Artery Disease PGSLower Age at Menarche PGSLower WealthLower Longevity PGSFood InsecurityLower EducationLower Mother's EducationHigher Diabetes PGSEver DivorcedDizzinessDiabetesHypertensionLower IncomeHigher AD PGSReceived Food StampsHigher ParityLonelyLower SR Health
Variable Importance P r ed i c t o r NH Black Women (n=525)
Expert Classifier
Fig S9 ower Longevity PGSEver DivorcedMedicareHigher Coronary Artery Disease PGSForeign BornHigher Age at Last BirthHigher AD PGSEver SmokedBack PainHigher Parity PGSLower Education PGSPainLower Height PGSLower Age at First Birth PGSArthritisLung DiseaseLower SR Childhood SESHeavy Alcohol UseCancerHigher Myocardial Infarction PGSHeadachesHypertensionUnemployedNo InsuranceHeart ProblemsNo Relatives NearbyHigher Diabetes PGSEver WidowedChildlessLower General Cognition PGSHigher ParityWheezingDiabetesShort of BreathRetiredHigher BMINot Married/PartneredNo Friends NearbyVeteranLower Father Occupational StatusLow/No Vigorous Physical ActivityLower Age at First BirthReceived Food StampsLower SR VisionLower Neighborhood SafetyLower SR Childhood HealthLower Father's EducationLess ReligiousSouthern BornMedicaidFood InsecurityActive SmokerLower IncomePsychiatric IllnessLower WealthLower SR HealthFatigueDizzinessLower Mother's EducationLower SR HearingStrokeLonelyLower Education
Variable Importance P r ed i c t o r NH White Men (n=2561)
Ever SmokedActive SmokerLower Longevity PGSHigher BMIHigher AD PGSMedicareHigher ParityLower Height PGSLower Age at Menarche PGSLower Age at Menopause PGSLower Age at First Birth PGSDizzinessHypertensionBack PainArthritisReceived Food StampsHigher Myocardial Infarction PGSForeign BornEver DivorcedLow/No Vigorous Physical ActivityUnemployedVeteranEver WidowedNo InsuranceLower SR Childhood HealthRetiredMedicaidHeavy Alcohol UseChildlessNo Friends NearbyCancerFood InsecurityLess ReligiousWheezingShort of BreathHigher Diabetes PGSLower Education PGSNot Married/PartneredNo Relatives NearbyLower SR HearingSouthern BornHeart ProblemsPsychiatric IllnessLung DiseaseHigher Coronary Artery Disease PGSDiabetesStrokeLower SR Childhood SESHigher Parity PGSHigher Age at Last BirthHeadachesLower Neighborhood SafetyLower Age at First BirthLower SR VisionLower General Cognition PGSPainLower WealthLower Mother's EducationFatigueLower SR HealthLonelyLower Father Occupational StatusLower IncomeLower Father's EducationLower Education −0.002 0.000 0.002 0.004
Variable Importance P r ed i c t o r NH White Women (n=3377)
Higher Coronary Artery Disease PGSHypertensionLower Longevity PGSLower Height PGSHigher BMINo Friends NearbyHigher Age at Last BirthLower General Cognition PGSLower SR HealthLower SR Childhood HealthLow/No Vigorous Physical ActivityLower Age at First Birth PGSEver SmokedHigher Myocardial Infarction PGSHigher Parity PGSForeign BornLung DiseaseRetiredActive SmokerHeavy Alcohol UseNot Married/PartneredDizzinessChildlessFood InsecurityVeteranCancerEver WidowedSouthern BornWheezingArthritisEver DivorcedPsychiatric IllnessLower Neighborhood SafetyLower Father's EducationLower WealthMedicareHeadachesDiabetesUnemployedShort of BreathNo InsuranceNo Relatives NearbyHeart ProblemsLonelyPainFatigueLower Education PGSLess ReligiousStrokeLower Father Occupational StatusHigher Diabetes PGSLower SR Childhood SESBack PainReceived Food StampsLower Age at First BirthHigher AD PGSLower Mother's EducationLower IncomeLower SR VisionMedicaidLower SR HearingLower EducationHigher Parity
Variable Importance P r ed i c t o r NH Black Men (n=283)
Lower Height PGSLower General Cognition PGSLower Age at First BirthLower Longevity PGSHigher Coronary Artery Disease PGSLower SR Childhood SESLower SR HearingLower Father's EducationMedicareLower Age at Menarche PGSLower Father Occupational StatusBack PainNo Relatives NearbyForeign BornLower Education PGSEver WidowedLower SR VisionRetiredLow/No Vigorous Physical ActivityHeart ProblemsHeavy Alcohol UseWheezingStrokeLower Age at First Birth PGSNot Married/PartneredLower Mother's EducationVeteranShort of BreathFatigueUnemployedPsychiatric IllnessEver SmokedLower Age at Menopause PGSArthritisDiabetesNo Friends NearbyChildlessLess ReligiousHigher Parity PGSLower SR Childhood HealthCancerFood InsecurityHeadachesActive SmokerLung DiseaseHigher Age at Last BirthHigher Myocardial Infarction PGSLower Neighborhood SafetyMedicaidDizzinessEver DivorcedLower EducationNo InsuranceSouthern BornHigher AD PGSPainLower WealthReceived Food StampsHigher BMIHypertensionHigher ParityHigher Diabetes PGSLower SR HealthLower IncomeLonely
Variable Importance P r ed i c t o r NH Black Women (n=525)
LASSO Classifier
Fig S10 O v e r a ll NH W h i t e M en NH W h i t e W o m en NH B l a ck M en NH B l a ck W o m en Lower Age at Menarche PGSLower Height PGSLower Age at First Birth PGSForeign BornChildlessLower Education PGSHigher BMIHigher Myocardial Infarction PGSEver SmokedLow/No Vigorous Physical ActivityCancerNo InsuranceHigher Diabetes PGSBack PainArthritisMedicareEver DivorcedNo Relatives NearbyUnemployedNo Friends NearbyLess ReligiousEver WidowedLung DiseaseNot Married/PartneredLower Age at Menopause PGSShort of BreathHigher Age at Last BirthActive SmokerPainFatigueHeart ProblemsWheezingHeadachesSouthern BornHeavy Alcohol UseDizzinessVeteranLower SR HearingStrokeLower Longevity PGSPsychiatric IllnessLower General Cognition PGSHypertensionReceived Food StampsLower SR Childhood SESHigher ParityDiabetesLower Neighborhood SafetyHigher AD PGSRetiredHigher Coronary Artery Disease PGSLower Father's EducationLower Father Occupational StatusMedicaidHigher Parity PGSFood InsecurityLower Age at First BirthLower Mother's EducationLower SR Childhood HealthLower SR VisionLonelyLower SR HealthLower WealthLower IncomeLower Education 604020
VIMP Rank Order
Langa−Weir Classifier
Fig S11 O v e r a ll NH W h i t e M en NH W h i t e W o m en NH B l a ck M en NH B l a ck W o m en MedicareHigher Myocardial Infarction PGSHeart ProblemsActive SmokerCancerLow/No Vigorous Physical ActivityChildlessEver WidowedEver DivorcedNo Friends NearbyNo Relatives NearbyLower SR Childhood SESForeign BornHigher Coronary Artery Disease PGSEver SmokedArthritisHeavy Alcohol UseLung DiseaseNot Married/PartneredBack PainHigher Diabetes PGSSouthern BornLower Age at First BirthHigher Parity PGSUnemployedWheezingLower Age at Menarche PGSLower Age at First Birth PGSLess ReligiousVeteranLower SR Childhood HealthLower General Cognition PGSHypertensionReceived Food StampsShort of BreathLower Neighborhood SafetyLower SR HearingLower Height PGSLower Education PGSHigher BMIHigher ParityDiabetesNo InsuranceHigher AD PGSLower Father Occupational StatusPainLower Age at Menopause PGSRetiredHigher Age at Last BirthHeadachesLower Longevity PGSStrokePsychiatric IllnessFood InsecurityMedicaidLower SR VisionDizzinessLower WealthLower Mother's EducationLower SR HealthFatigueLower Father's EducationLower EducationLower IncomeLonely 604020
VIMP Rank Order
Hurd Classifier
Fig S12 O v e r a ll NH W h i t e M en NH W h i t e W o m en NH B l a ck M en NH B l a ck W o m en MedicareLower SR Childhood SESHigher Myocardial Infarction PGSHigher Coronary Artery Disease PGSLow/No Vigorous Physical ActivityLung DiseaseEver SmokedNo Relatives NearbyVeteranShort of BreathArthritisChildlessCancerLower Longevity PGSLess ReligiousLower Age at First Birth PGSLower Age at Menarche PGSEver WidowedLower Height PGSUnemployedHeavy Alcohol UseSouthern BornNot Married/PartneredHigher Parity PGSForeign BornHigher Age at Last BirthHigher Diabetes PGSRetiredHeart ProblemsNo Friends NearbyLower Age at Menopause PGSHigher ParityHeadachesLower Education PGSNo InsuranceLower General Cognition PGSActive SmokerHypertensionHigher AD PGSHigher BMIBack PainLower Age at First BirthLower Neighborhood SafetyWheezingPainReceived Food StampsMedicaidPsychiatric IllnessFood InsecurityEver DivorcedLower SR VisionLower SR Childhood HealthStrokeFatigueLower SR HearingDiabetesDizzinessLower WealthLower Father's EducationLower SR HealthLower Father Occupational StatusLower Mother's EducationLower IncomeLower EducationLonely 604020
VIMP Rank Order
Expert Classifier
Fig S13 O v e r a ll NH W h i t e M en NH W h i t e W o m en NH B l a ck M en NH B l a ck W o m en Lower Longevity PGSLower Height PGSLower Age at Menarche PGSForeign BornMedicareEver SmokedHigher Coronary Artery Disease PGSLower Age at First Birth PGSLower Age at Menopause PGSHeavy Alcohol UseBack PainLow/No Vigorous Physical ActivityArthritisEver WidowedLower General Cognition PGSHypertensionRetiredHigher Myocardial Infarction PGSEver DivorcedHigher BMIHigher Age at Last BirthLower Education PGSNo Friends NearbyHigher Parity PGSUnemployedVeteranCancerWheezingActive SmokerChildlessNo Relatives NearbyNot Married/PartneredLower SR Childhood HealthLung DiseaseHigher AD PGSLower SR Childhood SESHeart ProblemsShort of BreathNo InsuranceDizzinessFood InsecurityHeadachesDiabetesLower Age at First BirthLower Father's EducationPsychiatric IllnessHigher ParityLower Father Occupational StatusLess ReligiousLower SR HearingPainReceived Food StampsSouthern BornLower SR VisionHigher Diabetes PGSLower Neighborhood SafetyStrokeMedicaidLower SR HealthFatigueLower Mother's EducationLower WealthLonelyLower IncomeLower Education 604020
VIMP Rank Order