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ObjectivesIndividuals increasingly experience delays or interruptions in schooling; we evaluate the association between these non-traditional education trajectories and mental health.MethodsUsing year-by-year education data for 7,501 National Longitudinal Survey of Youth 1979 participants, ages 14-48 (262,535 person-years of education data), we applied sequence analysis and a clustering algorithm to identify educational trajectory groups, incorporating both type and timing to credential. Linear regression models, adjusted for early-life confounders, evaluated relationships between educational trajectories and mental health component scores (MCS) from the 12-item short form instrument at age 50. We evaluated effect modification by race, gender, and race by gender.ResultsWe identified 24 distinct educational trajectories based on highest credential and educational timing. Compared to high school (HS) diplomas, < HS (beta=-3.41, 95%CI:-4.74,-2.07) and general educational development credentials (GEDs) predicted poorer MCS (beta=-2.07,95%CI:-3.16,-0.98). The following educational trajectories predicted better MCS: some college immediately after High School (beta=1.52, 95%CI:0.68,2.37), Associate degrees after long interruptions (beta=1.73, 95%CI:0.27,3.19), and graduate school soon after Bachelor's completion (beta=1.13, 95%CI:0.21,2.06). Compared to White men, Black women especially benefited from educational credentials higher than HS in predicting MCS.ConclusionsBoth type and timing of educational credential predicted mental health. Black women's mental higher especially benefited from higher educational credentials.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

INTRODUCTION: We estimated the ages when associations between Alzheimers disease (AD) genes and brain volumes begin among middle-aged and older adults. METHODS: Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume. RESULTS: AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices. DISCUSSION: APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Higher adult child educational attainment may benefit older parents psychosocial well-being in later life. This may be particularly important in low- and middle-income countries, where recent generations have experienced comparatively large increases in educational attainment. We used data from the 2012 Mexican Health and Aging Study, a nationally representative study of adults aged ≥50 years and leveraged the exogenous variation in adult child education induced by Mexicos compulsory schooling law passed in 1993. We employed two-stage least squares (2SLS) regression to estimate the effects of increased schooling among adult children on parents (respondents) depressive symptoms and life satisfaction scores, controlling for demographic and socioeconomic characteristics. We considered heterogeneity by parent and child gender and other sociodemographic characteristics. Our study included 7186 participants with an average age of 60.1 years; 54.9% were female. In the 2SLS analyses, increased schooling among oldest adult children was associated with fewer depressive symptoms (β = -0.25; 95% CI: -0.51, 0.00) but no difference in life satisfaction (β = 0.01; 95% CI: -0.22, 0.25). Stratified models indicated differences in the magnitude of association with depressive symptoms for mothers (β = -0.27, 95% CI: -0.56, 0.01) and fathers (β = -0.18, 95% CI: -0.63, 0.26) and when considering increased schooling of oldest sons (β = -0.37; 95% CI: -0.73, -0.02) and daughters (β = -0.05, 95% CI: -0.23, 0.13). No parent and child gender differences were found for life satisfaction. Power was limited to detect heterogeneity across other sociodemographic characteristics in the second stage although first-stage estimates were larger for urban (vs. rural) dwelling and more (vs. less) highly educated respondents. Results were similar when considering the highest educated child as well as increased schooling across all children. Our findings suggest that longer schooling among current generations of adult children, particularly sons, may benefit their older parents psychosocial well-being.

IntroductionThe prevalence of poor sleep quality and sleep apnea differs by race and ethnicity and may contribute to racial disparities in cognitive aging. We investigated whether sleep quality and sleep apnea risk were associated with cognitive function and decline and whether the associations differed by race/ethnicity.MethodsParticipants from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE; N = 1690; mean age: 75.7 years) study, a cohort of Asian, Black, Latino, and White participants, completed a modified Pittsburgh Sleep Quality Index assessing subjective sleep quality, latency, duration, disturbances, sleep medication use, and daytime dysfunction. Sleep apnea risk was measured by questions about snoring, tiredness, and whether apnea was observed. Executive function and verbal episodic memory were assessed at three time points over an average of 2.7 years with the Spanish and English Neuropsychological Assessment Scale. We fit linear mixed-effect models and stratified analyses by race/ethnicity.ResultsHigher sleep apnea risk was associated with faster declines in verbal episodic memory (β^ sleep apnea = -0.02, 95% confidence interval [CI], -0.04, -0.001) but not in executive function. Poorer sleep quality was associated with lower levels of and faster decline in executive function but not in verbal episodic memory. Race/ethnicity modified these associations: compared to estimated effects among White participants, poorer global sleep quality (β^ sleep*time = -0.02, 95% CI, -0.02, -0.01) was associated with larger effects on decline in executive function among Black participants. Estimated effects of some individual sleep quality components were also modified by race/ethnicity; for example, sleep medication use was associated with faster declines in executive function (β^ sleep*time = -0.05, 95% CI, -0.07, -0.03) and verbal episodic memory β^ sleep*time = -0.04, 95% CI, -0.07, -0.02) among Black participants compared to White participants.DiscussionObservational evidence indicates sleep quality is a promising target for addressing racial/ethnic disparities in cognitive aging, especially among Black older adults.HighlightsSleep apnea risk was associated with faster declines in verbal episodic memory but not executive function among all participants.Global sleep quality was associated with lower levels of and faster decline in executive function but not verbal episodic memory among all participants.Black older adults were particularly susceptible to the estimated adverse cognitive impacts of global sleep quality, particularly the use of sleep medication.

Incomplete longitudinal data are common in life-course epidemiology and may induce bias leading to incorrect inference. Multiple imputation (MI) is increasingly preferred for handling missing data, but few studies explore MI-method performance and feasibility in real-data settings. We compared 3 MI methods using real data under 9 missing-data scenarios, representing combinations of 10%, 20%, and 30% missingness and missing completely at random, at random, and not at random. Using data from Health and Retirement Study (HRS) participants, we introduced record-level missingness to a sample of participants with complete data on depressive symptoms (1998-2008), mortality (2008-2018), and relevant covariates. We then imputed missing data using 3 MI methods (normal linear regression, predictive mean matching, variable-tailored specification), and fitted Cox proportional hazards models to estimate effects of 4 operationalizations of longitudinal depressive symptoms on mortality. We compared bias in hazard ratios, root mean square error, and computation time for each method. Bias was similar across MI methods, and results were consistent across operationalizations of the longitudinal exposure variable. However, our results suggest that predictive mean matching may be an appealing strategy for imputing life-course exposure data, given consistently low root mean square error, competitive computation times, and few implementation challenges.

IntroductionHigher occupational complexity has been linked to favorable cognitive outcomes, but rarely examined in racially and ethnically diverse populations.MethodsIn a diverse cohort (n = 1536), linear mixed-effects models estimated associations between main lifetime occupational complexity and domain-specific cognitive decline (z-standardized). Occupational complexity with data, people, and things were classified using the Dictionary of Occupational Titles.ResultsFor occupational complexity with data, highest tertile (vs. lowest) was associated with higher baseline executive function (β = 0.11; 95% confidence interval [CI] 0.00-0.22) and slower annual rate of decline (β = 0.03; 95% CI 0.01-0.06), and higher baseline semantic memory (β = 0.14; 95% CI 0.04-0.25). Highest tertile of occupational complexity with people was associated with higher baseline executive function (β = 0.29; 95% CI 0.18-0.40), verbal episodic memory (β = 0.12; 95% CI 0.00-0.24), and semantic memory (β = 0.23; 95% CI 0.12-0.34).DiscussionIn a diverse cohort, higher occupational complexity is associated with better cognition. Findings should be verified in larger cohorts.HighlightFew studies have examined associations of occupational complexity with cognition in diverse populations. Racial and ethnic minorities are disproportionately exposed to lower occupational complexity. Occupational complexity with data and people are associated with better cognition.

OBJECTIVE: Researchers are often interested in assessing the causal effect of an exposure on an outcome when randomization is not ethical or feasible. Estimating causal effects by controlling for confounders can be unconvincing because important potential confounders remain unmeasured. Study designs leveraging instrumental variables (IVs) offer alternatives to confounder-control methods but are rarely used in stress and trauma research. METHOD: We review the conceptual foundations and implementation of IV methods. We discuss strengths and limitations of IV approaches, contrasting with confounder-control methods, and illustrate the relevance of IVs for stress and trauma research. RESULTS: IV approaches leverage an external or exogenous source of variation in the exposure. Instruments are variables that meet three conditions: relevance (variation in the IV is associated with variation in the chance of exposure), exclusion (the IV only affects the outcome through the exposure), and exchangeability (no unmeasured confounding of the IV-outcome relationship). Interpreting estimates from IV analyses requires an additional assumption, such as monotonicity (the instrument does not change the chance of exposure in different directions for any two individuals). Valid IVs circumvent the need to correctly identify, measure, and control for all confounders of the exposure-outcome relationship. The primary challenge is identifying a valid instrument. CONCLUSIONS: IV approaches have strengths and weaknesses compared with confounder-control approaches. IVs offers a promising complementary study design to improve evidence about the causal effects of exposures on outcomes relevant to stress and trauma. Collaboration with scientists who are experienced with identifying and analyzing IVs will support this work. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

IntroductionThe challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory.MethodsIn three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data.ResultsAPM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used.DiscussionConstraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change.HighlightsThe magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

IntroductionBlack students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, potentially offsetting the established benefits of college for lowering dementia incidence.MethodsBlack participants in two cohorts (the Kaiser Healthy Aging and Diverse Life Experiences [KHANDLE] and the Study of Healthy Aging in African Americans [STAR]) who had attended college (N = 716) self-reported the college name (classified as HBCU vs. PWI) and completed three waves of executive function (EF) and verbal episodic memory (VEM) assessments. HBCU effects on cognitive level and decline were estimated using adjusted linear mixed-effects models.ResultsHBCU (vs. PWI) attendees averaged better EF (β = 0.05 [-0.22, 0.32]) and VEM (β = 0.21 [-0.06, 0.46]) at age 70 though neither association was statistically significant. HBCU attendance was associated with slightly faster VEM decline (β = -0.03 [-0.05, 0.00]).DiscussionHarmonized analyses with larger studies are needed to estimate important effects of HBCU attendance.HighlightsHigher education is robustly linked to lower dementia risk, yet Black-White inequities persist among college-educated adults. Black students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, which may offset the established benefits of college for lowering dementia incidence. HBCU (vs. non-HBCU) attendees averaged better executive function and verbal episodic memory (VEM) at average age 70, though confidence intervals were wide and associations were not statistically significant, and averaged slightly faster decline in VEM. Harmonized analyses using larger nationally representative studies are likely needed to avoid underestimating the health effects of HBCU attendance.

ImportanceAdults with Alzheimer disease and related dementias (ADRD) are particularly vulnerable to the direct and indirect effects of the COVID-19 pandemic. Deaths associated with ADRD increased substantially in pandemic year 1. It is unclear whether mortality associated with ADRD declined when better prevention strategies, testing, and vaccines became widely available in year 2.ObjectiveTo compare pandemic-era excess deaths associated with ADRD between year 1 and year 2 overall and by age, sex, race and ethnicity, and place of death.Design, setting, and participantsThis time series analysis used all death certificates of US decedents 65 years and older with ADRD as an underlying or contributing cause of death from January 2014 through February 2022.ExposureCOVID-19 pandemic era.Main outcomes and measuresPandemic-era excess deaths associated with ADRD were defined as the difference between deaths with ADRD as an underlying or contributing cause observed from March 2020 to February 2021 (year 1) and March 2021 to February 2022 (year 2) compared with expected deaths during this period. Expected deaths were estimated using data from January 2014 to February 2020 fitted with autoregressive integrated moving average models.ResultsOverall, 2 334 101 death certificates were analyzed. A total of 94 688 (95% prediction interval [PI], 84 192-104 890) pandemic-era excess deaths with ADRD were estimated in year 1 and 21 586 (95% PI, 10 631-32 450) in year 2. Declines in ADRD-related deaths in year 2 were substantial for every age, sex, and racial and ethnic group evaluated. Pandemic-era ADRD-related excess deaths declined among nursing home/long-term care residents (from 34 259 [95% PI, 25 819-42 677] in year 1 to -22 050 [95% PI, -30 765 to -13 273] in year 2), but excess deaths at home remained high (from 34 487 [95% PI, 32 815-36 142] in year 1 to 28 804 [95% PI, 27 067-30 571] in year 2).Conclusions and relevanceThis study found that large increases in mortality with ADRD as an underlying or contributing cause of death occurred in COVID-19 pandemic year 1 but were largely mitigated in pandemic year 2. The most pronounced declines were observed for deaths in nursing home/long-term care settings. Conversely, excess deaths at home and in medical facilities remained high in year 2.

Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.

Abstract: Background: SuperAgers are individuals who maintain superior cognitive performance despite advanced age. Most studies define SuperAgers as superior performers only in episodic memory. Our aim was to assess in a diverse oldest‐old cohort if superior performance in one domain indicates superior performance in other domains and explore demographic characteristics. Methods: The LifeAfter90 study is a multi‐ethnic cohort of members of Kaiser Permanente Northern California aged 90 or older. Baseline verbal episodic memory (VEM), semantic memory (SM), and executive function (EF) were evaluated using the Spanish and English Neuropsychological Assessment Scale (SENAS). SuperAgers were individuals who scored above the mean of domain and race‐specific SENAS scores from a reference cohort aged 65‐70 years. The reference group were similar participants from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study. To assess the association between age, sex, education, and being a SuperAger, odds ratios (OR) and 95% confidence interval (CI) were calculated using multiple logistic regression. Results: The 617 study participants (236 men and 381 women) had a mean age of 92.9 years (Table1). 53.6% of individuals were SuperAgers in one domain, 22.8% in any two domains, and 7.7% in all three domains. 7.0% of individuals were SuperAgers in SM and EF, 4.5% in VEM and EF, and 3.5% in VEM and SM (Figure1). SuperAgers were younger than non‐SuperAgers. Women were more likely to be SuperAgers in VEM (OR = 2.13; 95%CI: 1.43,3.18) and EF (OR = 2.18; 95%CI: 1.44,3.30) and less likely in SM (OR = 0.49; 95%CI: 0.34,0.71) compared to men. Higher education was related to being a SuperAger in SM (OR = 1.85; 95%CI: 1.28,2.67) and EF (OR = 2.56; 95%CI: 1.74,3.78) but not VEM (Table2). Conclusion: In this diverse cohort of oldest‐old SuperAgers we found that exceptional episodic memory performance does not indicate exceptional performance in other cognitive domains. Education was not a predictor of exceptional performance in all domains. Future work should investigate predictors of exceptional cognitive aging after age 90.

Substantial heterogeneity in effects of social policies on health across subgroups may be common, but has not been systematically characterized. Using a sample of 55 contemporary studies on health effects of social policies, we recorded how often heterogeneous treatment effects (HTEs) were assessed, for what subgroups (e.g., male, female), and the subgroup-specific effect estimates expressed as Standardized Mean Differences (SMDs). For each study, outcome, and dimension (e.g., gender), we fit a random-effects meta-analysis. We characterized the magnitude of heterogeneity in policy effects using the standard deviation of the subgroup-specific effect estimates (τ). Among the 44% of studies reporting subgroup-specific estimates, policy effects were generally small ( 0.1 SMDs. For 26% of study-outcome-dimensions, the magnitude of τ indicated that effects of opposite signs were plausible across subgroups. Heterogeneity was more common in policy effects not specified a priori. Our findings suggest social policies commonly have heterogeneous effects on health of different populations; these HTEs may substantially impact disparities. Studies of social policies and health should routinely evaluate HTEs.

PURPOSE: Refugees are vulnerable to psychiatric disorders because of risk factors linked to migration. Limited evidence exist on the impact of the neighbourhood in which refugee resettle. We examined whether resettling in a socioeconomically disadvantaged neighbourhood increased refugees risk of psychiatric disorders. METHODS: This register-based cohort study included 42,067 adults aged 18 years and older who came to Denmark as refugees during 1986-1998. Resettlement policies in those years assigned refugees in a quasi-random fashion to neighbourhoods across the country. A neighbourhood disadvantage index was constructed using neighbourhood-level data on income, education, unemployment, and welfare receipt. Main outcomes were psychiatric diagnoses and psychiatric medication usage ascertained from nationwide patient and prescription drug registers, with up to 30-year follow-up. Associations of neighbourhood disadvantage with post-migration risk of psychiatric disorders were examined using Cox proportional hazards and linear probability models adjusted for individual, family, and municipality characteristics. RESULTS: The cumulative risk of psychiatric diagnoses and medication was 13.7% and 46.1%, respectively. Refugees risk of psychiatric diagnoses and psychiatric medication usage was higher among individuals assigned to high-disadvantage compared with low-disadvantage neighbourhoods in analyses including fixed effects for assigned municipality (psychiatric diagnoses: hazard ratio (HR) = 1.14, 95% CI 1.04, 1.25; psychiatric medication: HR = 1.05, 95% CI 1.00, 1.11). Consistent results were found using linear probability models. Results for diagnostic categories and subclasses of medications suggested that the associations were driven by neurotic and stress-related disorders and use of anxiolytic medications. CONCLUSION: Resettlement in highly disadvantaged neighbourhoods was associated with an increase in refugees risk of psychiatric disorders, suggesting that targeted placement of newly arrived refugees could benefit refugee mental health. The results contribute quasi-experimental evidence to support links between neighbourhood characteristics and health.

ObjectivesNeighborhood disadvantage may increase the risk of adverse health outcomes among older refugees. Yet few studies rigorously estimate the effects of place-based factors on later-life health, particularly dementia and mortality. Evidence about refugees is especially sparse.MethodsThis study leveraged a natural experiment in the form of a Danish policy (1986-1998) that dispersed refugees quasi-randomly across neighborhoods upon arrival. We used longitudinal registers allowing 30 years of follow-up among refugees aged 40+ years upon arrival in Denmark (N = 9,854). Cox models assessed the association between neighborhood disadvantage and risk of dementia and mortality. We examined heterogeneous effects by sex, age, and family size. We also examined associations among non-refugee immigrants and native-born Danes.ResultsNeighborhood disadvantage was not associated with dementia in any group. One unit increase in neighborhood disadvantage index (ranges -8 to 5.7) was associated with greater mortality risk among non-refugee immigrants (HR 1.06, 95%CI: 1.02, 1.10) and native-born Danes (HR 1.11, 95%CI: 1.06, 1.17). In contrast, neighborhood disadvantage was associated with lower mortality risk among refugees (HR 0.96, 95%CI: 0.93, 0.99). Neighborhood disadvantage remained negatively associated with mortality risk in subgroups: refugees who are female (on moderate-disadvantage compared to low-disadvantage), aged 60+, and who arrived with families.DiscussionWhile neighborhood disadvantage was associated with lower mortality risk among refugees, it was associated with greater mortality risk among non-refugee immigrants and native-born Danes, perhaps due to confounding in the latter groups or different place-based experiences by immigration status. Future research is warranted to explain the reasons for contrasting findings.

OBJECTIVES: Telephone-administered cognitive assessments are a cost-effective and sometimes necessary alternative to face-to-face assessments. There is limited information in large studies concerning mode effects, or differences in cognition attributable to the assessment method, as a potential measurement threat. We evaluated mode effects on cognitive scores using a population-based sample of community-living older adults. METHODS: We used data from participants aged 65-79 in the 2014 Health and Retirement Study for whom the interview mode was randomized (n = 6,825). We assessed mode differences in test means, whether mode modifies associations of cognition with criterion variables, and formal measurement invariance testing. RESULTS: Relative to face-to-face assessment, telephone assessment was associated with higher scores for memory and calculation (0.06 to 0.013 standard deviations [SD]) and lower scores for nonmemory items (-0.09 to -0.01 SD). Cognition was significantly differentially related to instrumental activities of daily living difficulty depending on assessment mode. Measurement invariance testing identified evidence of mode differences in certain tests as a function of mode: adjusting for underlying cognition, the largest mode differences in memory and attention: immediate noun recall, delayed word recall, and serial-7s scores were higher given telephone administration. DISCUSSION: Differences by mode of administration are apparent in cognitive measurement in older adults, albeit to a small degree in our study, and most pronounced for tests of memory and attention. The importance of accounting for mode differences ultimately depends on ones research question and study sample: not all associations may be affected by mode differences, and such modification may only be apparent among those with lower cognitive functioning.

PURPOSE: Capture-recapture methods estimate the size of hidden populations by leveraging the proportion of overlap of the population on independent lists. Log-linear modeling relaxes the assumption of list independence, but best model selection criteria remain uncertain. Incorrect model selection can deliver incorrect and even implausible size estimates. METHODS: We used simulations to model when capture-recapture methods deliver biased or unbiased estimates and compare model selection criteria. Simulations included five scenarios for list dependence among three incomplete lists of population of interest. We compared metrics of log-linear model selection, accuracy, and precision. We also compared log-linear model performance to the decomposable graph approach (a Bayesian model average), the sparse multiple systems estimation (SparseMSE) approach that accounts for zero or low cell counts, and the Sample Coverage approach. RESULTS: Log-linear models selected by Akaikes information criterion (AIC) calculated accurate population size estimates in all scenarios except for those with sparse or zero cell counts. In these scenarios, the decomposable graph and the Sample Coverage models produced more accurate size estimates. CONCLUSIONS: Conventional capture-recapture model selection fails with sparse cell counts. This naïve approach to model selection should be replaced with the implementation of multiple different models in order triangulate the truth in real-world applications.

ObjectivesWe examined the association of generational status and age at immigration with later life cognitive outcomes in a diverse sample of Latinos and Asian Americans.DesignBaseline data were obtained from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study, and a prospective cohort is initiated in 2017.SettingOlder adults in Northern California.ParticipantsOur cohort consisted of Asians (n = 411) and Latinos (n = 340) who were on average 76 years old (SD = 6.8).MeasurementsWe used multivariable linear regression models to estimate associations between generational status and age at immigration (collapsed into one five-level variable) with measures of verbal episodic memory, semantic memory, and executive function, adjusting for age, gender, race and ethnicity, and own- and parental education.ResultsGenerational status and age at immigration were associated with cognitive outcomes in a graded manner. Compared to third-generation or higher immigrants, first-generation immigration in adulthood was associated with lower semantic memory (β = -0.96; 95% CI: -1.12, -0.81) than immigration in adolescence (β = -0.68; 95% CI: -0.96, -0.41) or childhood (β = -0.28; 95% CI: -0.49, -0.06). Moreover, immigration in adulthood was associated with lower executive function (β = -0.63; 95% CI: -0.78, -0.48) than immigration in adolescence (β = -0.49; 95% CI: -0.75, -0.23). Similarly, compared to third-generation individuals, first-generation immigrants had lower executive functioning scores.ConclusionsOur study supports the notion that sociocontextual influences in early life impact later life cognitive scores. Longitudinal studies are needed to further clarify how immigration characteristics affect cognitive decline.

BackgroundModifiable risks for dementia are more prevalent in rural populations, yet there is a dearth of research examining life course rural residence on late-life cognitive decline.MethodsThe association of rural residence and socioeconomic status (SES) in childhood and adulthood with late-life cognitive domains (verbal episodic memory, executive function, and semantic memory) and cognitive decline in the Kaiser Healthy Aging and Diverse Life Experiences cohort was estimated using marginal structural models with stabilized inverse probability weights.ResultsAfter adjusting for time-varying SES, the estimated marginal effect of rural residence in childhood was harmful for both executive function (β = -0.19, 95% confidence interval [CI] = -0.32, -0.06) and verbal episodic memory (β = -0.22, 95% CI = -0.35, -0.08). Effects of adult rural residence were imprecisely estimated with beneficial point estimates for both executive function (β = 0.19; 95% CI = -0.07, 0.44) and verbal episodic memory (β = 0.24, 95% CI = -0.07, 0.55).ConclusionsChildhood rurality is associated with poorer late-life cognition independent of SES.

BackgroundLong-lasting insecticidal nets (LLINs) are the main vector control tool for pregnant women, but their efficacy may be compromised, in part, due to pyrethroid resistance. In 2017, the Ugandan Ministry of Health embedded a cluster randomized controlled trial into the national LLIN campaign, where a random subset of health subdistricts (HSDs) received LLINs treated with piperonyl butoxide (PBO), a chemical synergist known to partially restore pyrethroid sensitivity. Using data from a small, non-randomly selected subset of HSDs, this secondary analysis used quasi-experimental methods to quantify the overall impact of the LLIN campaign on pregnancy outcomes. In an exploratory analysis, differences between PBO and conventional (non-PBO) LLINs on pregnancy outcomes were assessed.MethodsBirth registry data (n = 39,085) were retrospectively collected from 21 health facilities across 12 HSDs, 29 months before and 9 months after the LLIN campaign (from 2015 to 2018). Of the 12 HSDs, six received conventional LLINs, five received PBO LLINs, and one received a mix of conventional and PBO LLINs. Interrupted time-series analyses (ITSAs) were used to estimate changes in monthly incidence of stillbirth and low birthweight (LBW;

IntroductionMost dementia studies are not population-representative; statistical tools can be applied to samples to obtain critically-needed population-representative estimates, but are not yet widely used.MethodsWe pooled data from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) study and the California Behavioral Risk Factor Surveillance System (CA-BRFSS), a population-representative study. Using weights accounting for sociodemographic/health differences between KHANDLE and CA-BRFSS, we estimated cognitive impairment prevalence and age- and sex-adjusted racial/ethnic inequalities in California adults 65+ without prior dementia diagnosis.ResultsAfter weighting KHANDLE, the estimated cognitive impairment prevalence in California was 20.3% (95% confidence interval 17.8-23.0); unweighted prevalence was 24.8% (23.1%-26.6%). Inequalities (larger prevalences) were observed among Black and Asian groups versus whites.DiscussionWe used a novel statistical approach to estimate population-representative cognitive impairment prevalence and inequalities. Such statistical tools can help obtain population-representative estimates from existing studies and inform efforts to reduce racial/ethnic disparities.

IntroductionUnderstanding educational patterns in excess mortality during the coronavirus disease 2019 (COVID-19) pandemic may help to identify strategies to reduce disparities. It is unclear whether educational inequalities in COVID-19 mortality have persisted throughout the pandemic, spanned the full range of educational attainment, or varied by other demographic indicators of COVID-19 risks, such as age or occupation.MethodsThis study analyzed individual-level California Department of Public Health data on deaths occurring between January 2016 and February 2021 among individuals aged ≥25 years (1,502,202 deaths). Authors applied ARIMA (autoregressive integrated moving average) models to subgroups defined by the highest level of education and other demographics (age, sex, race/ethnicity, U.S. nativity, occupational sector, and urbanicity). Authors estimated excess deaths (the number of observed deaths minus the number of deaths expected to occur under the counterfactual of no pandemic) and excess deaths per 100,000 individuals.ResultsEducational inequalities in excess mortality emerged early in the pandemic and persisted throughout the first year. The greatest per-capita excess occurred among people without high-school diplomas (533 excess deaths/100,000), followed by those with a high-school diploma but no college (466/100,000), some college (156/100,000), and bachelor's degrees (120/100,000), and smallest among people with graduate/professional degrees (101/100,000). Educational inequalities occurred within every subgroup examined. For example, per-capita excess mortality among Latinos with no college experience was 3.7 times higher than among Latinos with at least some college experience.ConclusionsPervasive educational inequalities in excess mortality during the pandemic suggest multiple potential intervention points to reduce disparities.

BackgroundMalaria is a risk factor for adverse pregnancy outcomes. Indoor residual spraying with insecticide (IRS) reduces malaria infections, yet the effects of IRS on pregnancy outcomes are not well established. We evaluated the impact of a large-scale IRS campaign on pregnancy outcomes in Eastern Uganda.MethodsBirth records (n = 59 992) were obtained from routine surveillance data at 25 health facilities from five districts that were part of the IRS campaign and six neighbouring control districts ∼27 months before and ∼24 months after the start of the campaign (January 2013-May 2017). Campaign effects on low birthweight (LBW) and stillbirth incidence were estimated using the matrix completion method (MC-NNM), a machine-learning approach to estimating potential outcomes, and compared with the difference-in-differences (DiD) estimator. Subgroup analyses were conducted by HIV and gravidity.ResultsMC-NNM estimates indicated that the campaign was associated with a 33% reduction in LBW incidence: incidence rate ratio (IRR) = 0.67 [95% confidence interval (CI): 0.49-0.93)]. DiD estimates were similar to MC-NNM [IRR = 0.69 (0.47-1.01)], despite a parallel trends violation during the pre-IRS period. The campaign was not associated with substantial reductions in stillbirth incidence [IRRMC-NNM = 0.94 (0.50-1.77)]. HIV status modified the effects of the IRS campaign on LBW [βIRSxHIV = 0.42 (0.05-0.78)], whereby HIV-negative women appeared to benefit from the campaign [IRR = 0.70 (0.61-0.81)], but not HIV-positive women [IRR = 1.12 (0.59-2.12)].ConclusionsOur results support the effectiveness of the campaign in Eastern Uganda based on its benefit to LBW prevention, though HIV-positive women may require additional interventions. The IRS campaign was not associated with a substantively lower stillbirth incidence, warranting further research.

As research documenting disparate impacts of COVID-19 by race and ethnicity grows, little attention has been given to dynamics in mortality disparities during the pandemic and whether changes in disparities persist. We estimate age-standardized monthly all-cause mortality in the United States from January 2018 through February 2022 for seven racial/ethnic populations. Using joinpoint regression, we quantify trends in race-specific rate ratios relative to non-Hispanic White mortality to examine the magnitude of pandemic-related shifts in mortality disparities. Prepandemic disparities were stable from January 2018 through February 2020. With the start of the pandemic, relative mortality disadvantages increased for American Indian or Alaska Native (AIAN), Native Hawaiian or other Pacific Islander (NHOPI), and Black individuals, and relative mortality advantages decreased for Asian and Hispanic groups. Rate ratios generally increased during COVID-19 surges, with different patterns in the summer 2021 and winter 2021/2022 surges, when disparities approached prepandemic levels for Asian and Black individuals. However, two populations below age 65 fared worse than White individuals during these surges. For AIAN people, the observed rate ratio reached 2.25 (95% CI = 2.14, 2.37) in October 2021 vs. a prepandemic mean of 1.74 (95% CI = 1.62, 1.86), and for NHOPI people, the observed rate ratio reached 2.12 (95% CI = 1.92, 2.33) in August 2021 vs. a prepandemic mean of 1.31 (95% CI = 1.13, 1.49). Our results highlight the dynamic nature of racial/ethnic disparities in mortality and raise alarm about the exacerbation of mortality inequities for Indigenous groups due to the pandemic.

The vast majority of studies investigating participation in, persistence through, and consequences of postsecondary education focus on educational attainment status among the so-called traditional population of collegegoers between the ages of 18 and 24. This narrow focus leaves largely invisible the role that an expanding set of educational trajectories throughout adulthood plays in shaping social stratification. Using 35-plus and 20 years of follow-up data from the US National Longitudinal Survey of Youth (NLSY)’s 1979 and 1997 cohorts, we find that a substantial share within each cohort is attaining education well into adulthood, and that these trajectories are patterned according to key social and demographic characteristics. In both cohorts, racial/ethnic differences in educational attainment grew over time and, for those attaining the same degree, members of historically disadvantaged groups did so at an older age. Cohort differences in trajectories emerged, however, when considering the intersection of race/ethnicity and socialized gender. Through careful descriptive analysis of two generational cohorts, our study makes clear the role of educational trajectories in the process of cumulative (dis)advantage across the life course, as well as across generations.

ObjectivesTo determine the socioeconomic consequences of receipt versus denial of abortion.MethodsWomen who presented for abortion just before or after the gestational age limit of 30 abortion facilities across the United States between 2008 and 2010 were recruited and followed for 5 years via semiannual telephone interviews. Using mixed effects models, we evaluated socioeconomic outcomes for 813 women by receipt or denial of abortion care.ResultsIn analyses that adjusted for the few baseline differences, women denied abortions who gave birth had higher odds of poverty 6 months after denial (adjusted odds ratio [AOR] = 3.77; P

BackgroundCannabis outlets may affect health and health disparities. Local governments can regulate outlets, but little is known about the effectiveness of local policies in limiting outlet densities and discouraging disproportionate placement of outlets in vulnerable neighborhoods.MethodsFor 241 localities in California, we measured seven policies pertaining to density or location of recreational cannabis outlets. We geocoded outlets using web-scraped data from the online finder Weedmaps between 2018 and 2020. We applied Bayesian spatiotemporal models to evaluate associations of local cannabis policies with Census block group-level outlet counts, accounting for confounders and spatial autocorrelation. We assessed whether associations differed by block group median income or racial-ethnic composition.ResultsSeventy-six percent of localities banned recreational cannabis outlets. Bans were associated with fewer outlets, particularly in block groups with higher median income, fewer Hispanic residents, and more White and Asian residents. Outlets were disproportionately located in block groups with lower median income [posterior RR (95% credible interval): 0.76 (0.70, 0.82) per $10,000], more Hispanic residents [1.05 (1.02, 1.09) per 5%], and fewer Black residents [0.91 (0.83, 0.98) per 5%]. For the six policies in jurisdictions permitting outlets, two policies were associated with fewer outlets and two with more; two policy associations were uninformative. For these policies, we observed no consistent heterogeneity in associations by median income or racial-ethnic composition.ConclusionsSome local cannabis policies in California are associated with lower cannabis outlet densities, but are unlikely to deter disproportionate placement of outlets in racial-ethnic minority and low-income neighborhoods.

BackgroundDuring the first year of the COVID-19 pandemic, workers in essential sectors had higher rates of SARS-CoV-2 infection and COVID-19 mortality than those in non-essential sectors. It is unknown whether disparities in pandemic-related mortality across occupational sectors have continued to occur during the periods of SARS-CoV-2 variants and vaccine availability.MethodsIn this longitudinal cohort study, we obtained data from the California Department of Public Health on all deaths occurring in the state of California, USA, from Jan 1, 2016, to Dec 31, 2021. We restricted our analysis to residents of California who were aged 18-65 years at time of death and died of natural causes. We classified the occupational sector into nine essential sectors; non-essential; or unemployed or without an occupation provided on the death certificate. We calculated the number of COVID-19 deaths in total and per capita that occurred in each occupational sector. Separately, using autoregressive integrated moving average models, we estimated total, per-capita, and relative excess natural-cause mortality by week between March 1, 2020, and Nov 30, 2021, stratifying by occupational sector. We additionally stratified analyses of occupational risk into counties with high versus low vaccine uptake, categorising high-uptake regions as counties where at least 50% of the population were fully vaccinated according to US guidelines by Aug 1, 2021.FindingsFrom March 1, 2020, to Nov 30, 2021, 24 799 COVID-19 deaths were reported in residents of California aged 18-65 years and an estimated 28 751 (95% prediction interval 27 853-29 653) excess deaths. People working in essential sectors were associated with higher COVID-19 deaths and excess deaths than were those working in non-essential sectors, with the highest per-capita COVID-19 mortality in the agriculture (131·8 per 100 000 people), transportation or logistics (107·1 per 100 000), manufacturing (103·3 per 100 000), facilities (101·1 per 100 000), and emergency (87·8 per 100 000) sectors. Disparities were wider during periods of increased infections, including during the Nov 29, 2020, to Feb 27, 2021, surge in infections, which was driven by the delta variant (B.1.617.2) and occurred during vaccine uptake. During the June 27 to Nov 27, 2021 surge, emergency workers had higher COVID-19 mortality (113·7 per 100 000) than workers from any other sector. Workers in essential sectors had the highest COVID-19 mortality in counties with low vaccination uptake, a difference that was more pronounced during the period of the delta infection surge during Nov 29, 2020, to Feb 27, 2021.InterpretationWorkers in essential sectors have continued to bear the brunt of high COVID-19 and excess mortality throughout the pandemic, particularly in the agriculture, emergency, manufacturing, facilities, and transportation or logistics sectors. This high death toll has continued during periods of vaccine availability and the delta surge. In an ongoing pandemic without widespread vaccine coverage and with anticipated threats of new variants, the USA must actively adopt policies to more adequately protect workers in essential sectors.FundingUS National Institute on Aging, Swiss National Science Foundation, and US National Institute on Drug Abuse.

Excess mortality has exceeded reported deaths from Covid-19 during the pandemic. This gap may be attributable to deaths that occurred among individuals with undiagnosed Covid-19 infections or indirect consequences of the pandemic response such as interruptions in medical care; distinguishing these possibilities has implications for public health responses. In the present study, we examined patterns of excess mortality over time and by setting (in-hospital or out-of-hospital) and cause of death using death certificate data from California. The estimated number of excess natural-cause deaths from 2020 March 1 to 2021 February 28 (69,182) exceeded the number of Covid-19 diagnosed deaths (53,667) by 29%. Nearly half, 47.4% (32,775), of excess natural-cause deaths occurred out of the hospital, where only 28.6% (9,366) of excess mortality was attributed to Covid-19. Over time, increases or decreases in excess natural non-Covid-19 mortality closely mirrored increases or decreases in Covid-19 mortality. The time series were positively correlated in out-of-hospital settings, particularly at time lags when excess natural-cause deaths preceded reported Covid-19 deaths; for example, when comparing Covid-19 deaths to excess natural-cause deaths in the week prior, the correlation was 0.73. The strong temporal association of reported Covid-19 deaths with excess out-of-hospital deaths from other reported natural-cause causes suggests Covid-19 deaths were undercounted during the first year of the pandemic.

BackgroundCancer is inversely associated with dementia. Using simulations, we examined whether this inverse association may be explained by dementia diagnosis timing, including death before dementia diagnosis and differential diagnosis patterns by cancer history.MethodsWe used multistate Markov simulation models to generate cohorts 65 years of age and free of cancer and dementia at baseline; follow-up for incident cancer (all cancers, breast, prostate, and lung cancer), dementia, dementia diagnosis among those with dementia, and death occurred monthly over 30 years. Models specified no true effect of cancer on dementia, and used age-specific transition rates calibrated to U.S. population and cohort data. We varied the average lapse between dementia onset and diagnosis, including nondifferential and differential delays by cancer history, and examined observed incidence rate ratios (IRRs) for the effect of cancer on dementia diagnosis.ResultsNondifferential dementia diagnosis delay introduced minimal bias (IRRs = 0.98-1.02) for all cancer, breast, and prostate models and substantial bias (IRR = 0.78) in lung cancer models. For the differential dementia diagnosis delay model of all cancer types combined, simulation scenarios with ≥20% lower dementia diagnosis rate (additional 4.5-month delay) in those with cancer history versus without yielded results consistent with literature estimates. Longer dementia diagnosis delays in those with cancer and higher mortality in those with cancer and dementia yielded more bias.ConclusionsDelays in dementia diagnosis may play a role in the inverse cancer-dementia relationship, especially for more fatal cancers, but moderate differential delays in those with cancer were needed to fully explain the literature-reported IRRs.

BackgroundCardiovascular disease (CVD) disproportionately affects Black adults in the United States. This is increasingly acknowledged to be due to inequitable distribution of health-promoting resources. One potential contributor is inequities in educational opportunities, although it is unclear what aspects of education are most salient. School racial segregation may affect cardiovascular health by increasing stress, constraining socioeconomic opportunities, and altering health behaviors. We investigated the association between school segregation and Black adults' CVD risk.Methods and findingsWe leveraged a natural experiment created by quasi-random (i.e., arbitrary) timing of local court decisions since 1991 that released school districts from court-ordered desegregation. We used the Panel Study of Income Dynamics (PSID) (1991 to 2017), linked with district-level school segregation measures and desegregation court order status. The sample included 1,053 Black participants who ever resided in school districts that were under a court desegregation order in 1991. The exposure was mean school segregation during observed schooling years. Outcomes included several adult CVD risk factors and outcomes. We fitted standard ordinary least squares (OLS) multivariable linear regression models, then conducted instrumental variables (IV) analysis, using the proportion of schooling years spent in districts that had been released from court-ordered desegregation as an instrument. We adjusted for individual- and district-level preexposure confounders, birth year, and state fixed effects. In standard linear models, school segregation was associated with a lower probability of good self-rated health (-0.05 percentage points per SD of the segregation index; 95% CI: -0.08, -0.03; p < 0.001) and a higher probability of binge drinking (0.04 percentage points; 95% CI: 0.002, 0.07; p = 0.04) and heart disease (0.01 percentage points; 95% CI: 0.002, 0.15; p = 0.007). IV analyses also found that school segregation was associated with a lower probability of good self-rated health (-0.09 percentage points; 95% CI: -0.17, -0.02, p = 0.02) and a higher probability of binge drinking (0.17 percentage points; 95% CI: 0.04, 0.30, p = 0.008). For IV estimates, only binge drinking was robust to adjustments for multiple hypothesis testing. Limitations included self-reported outcomes and potential residual confounding and exposure misclassification.ConclusionsSchool segregation exposure in childhood may have longstanding impacts on Black adults' cardiovascular health. Future research should replicate these analyses in larger samples and explore potential mechanisms. Given the recent rise in school segregation, this study has implications for policies and programs to address racial inequities in CVD.

ObjectivesFew researchers have evaluated whether school racial segregation, a key manifestation of structural racism, affects child health, despite its potential impacts on school quality, social networks, and stress from discrimination. We investigated whether school racial segregation affects Black children's health and health behaviors.MethodsWe estimated the association of school segregation with child health, leveraging a natural experiment in which school districts in recent years experienced increased school segregation. School segregation was operationalized as the Black-White dissimilarity index. We used ordinary least squares models as well as quasi-experimental instrumental variables analysis, which can reduce bias from unobserved confounders. Data from the Child Development Supplement of the Panel Study of Income Dynamics (1997-2014, n = 1248 Black children) were linked with district-level school segregation measures. Multivariable regressions were adjusted for individual-, neighborhood-, and district-level covariates. We also performed subgroup analyses by child sex and age.ResultsIn instrumental variables models, a one standard deviation increase in school segregation was associated with increased behavioral problems (2.53 points on a 27-point scale; 95% CI, 0.26 to 4.80), probability of having ever drunk alcohol (0.23; 95% CI, 0.049 to 0.42), and drinking at least monthly (0.20; 95% CI, 0.053 to 0.35). School segregation was more strongly associated with drinking behaviors among girls.ConclusionsSchool segregation was associated with worse outcomes on several measures of well-being among Black children, which may contribute to health inequities across the life span. These results highlight the need to promote school racial integration and support Black youth attending segregated schools.

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

COVID-19 mortality has disproportionately affected specific occupations and industries. The Occupational Safety and Health Administration (OSHA) protects the health and safety of workers by setting and enforcing standards for working conditions. Workers may file OSHA complaints about unsafe conditions. Complaints may indicate poor workplace safety during the pandemic. We evaluated COVID-19-related complaints filed with California (Cal)/OSHA between January 1, 2020 and December 14, 2020 across seven industries. To assess whether workers in occupations with high COVID-19-related mortality were also most likely to file Cal/OSHA complaints, we compared industry-specific per-capita COVID-19 confirmed deaths from the California Department of Public Health with COVID-19-related complaints. Although 7820 COVID-19-related complaints were deemed valid by Cal/OSHA, only 627 onsite inspections occurred, and 32 citations were issued. Agricultural workers had the highest per-capita COVID-19 death rates (402 per 100,000 workers) but were least represented among workplace complaints (44 per 100,000 workers). Health Care workers had the highest complaint rates (81 per 100,000 workers) but the second lowest COVID-19 death rate (81 per 100,000 workers). Industries with the highest inspection rates also had high COVID-19 mortality. Our findings suggest complaints are not proportional to COVID-19 risk. Instead, higher complaint rates may reflect worker groups with greater empowerment, resources, or capacity to advocate for better protections. This capacity to advocate for safe workplaces may account for relatively low mortality rates in potentially high-risk occupations. Future research should examine factors determining worker complaints and complaint systems to promote participation of those with the greatest need of protection.

BackgroundDespite growing research on the association between discrimination and disparities in cognitive aging, an evidence gap remains on how the association varies by racial/ethnic group. This study evaluates the associations of experiences of discrimination with cognitive function and whether these associations varied by race/ethnicity and nativity.MethodUsing the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) cohort (N = 1 712) with approximately equal groups of Black, White, Latino, and Asian community-dwelling older adults aged 65 years and older, we evaluated the associations between self-reported experiences of everyday and major lifetime discrimination with overall cognitive performance and domain-specific cognition (verbal episodic memory, semantic memory, and executive functioning) across race/ethnicity and nativity. Linear regression models examined the cross-sectional association between self-reported experiences of everyday and major lifetime discrimination with z-standardized coefficients for cognition. We tested for effect modification by race and nativity. All models controlled for age, sex, and education.ResultsAmong KHANDLE participants (mean age: 76 years; SD: 6.8), everyday discrimination was not associated with cognitive scores. Major lifetime discrimination was associated with better average cognitive scores among Black participants but not among other racial/ethnic groups. Major lifetime discrimination was associated with better average cognitive scores among U.S.-born but not among non-U.S.-born individuals.ConclusionOur findings do not imply that discrimination improves cognition, but rather suggest that future research should include more detailed measures on discrimination and unfair treatment that could help disentangle the extent to which relationships are causal or reflect some other underlying factor.

BackgroundHigher educational attainment predicts lower hypertension. Yet, associations between nontraditional educational trajectories (eg, interrupted degree programs) and hypertension are less well understood, particularly among structurally marginalized groups who are more likely to experience these non-traditional trajectories.MethodsIn National Longitudinal Survey of Youth 1979 cohort data (N = 6 317), we used sequence and cluster analyses to identify groups of similar educational sequences-characterized by timing and type of terminal credential-that participants followed from age 14-48 years. Using logistic regression, we estimated associations between the resulting 10 educational sequences and hypertension at age 50. We evaluated effect modification by individual-level indicators of structural marginalization (race, gender, race and gender, and childhood socioeconomic status [cSES]).ResultsCompared to terminal high school (HS) diploma completed at traditional age, terminal GED (OR: 1.32; 95%CI: 1.04, 1.66) or Associate degree after ConclusionsBoth type and timing to terminal credential matter for hypertension but effects may vary by experiences of structural marginalization. Documenting the nuanced ways in which complex educational trajectories are associated with health could elucidate underlying mechanisms and inform systems-level interventions for health equity.

US preterm-birth rates are 1.6 times higher for Black mothers than for White mothers. Although traffic-related air pollution (TRAP) may increase the risk of preterm birth, evaluating its effect on preterm birth and disparities has been challenging because TRAP is often measured inaccurately. This study sought to estimate the effect of TRAP exposure, measured at the street level, on the prevalence of preterm birth by race/ethnicity. We linked birth-registry data with TRAP measured at the street level for singleton births in sampled communities during 2013-2015 in Oakland and San Jose, California. Using logistic regression and marginal standardization, we estimated the effects of exposure to black carbon, nitrogen dioxide and ultrafine particles on preterm birth after confounder adjustment and stratification by race/ethnicity. There were 8823 singleton births, of which 760 (8.6%) were preterm. Shifting black-carbon exposure from the 10th to the 90th percentile was associated with: 6.8%age point higher risk of preterm birth (95% confidence interval = 0.1 to 13.5) among Black women; 2.1%age point higher risk (95% confidence interval = -1.1 to 5.2) among Latinas; and inconclusive null findings among Asian and White women. For Latinas, there was evidence of a positive association between the other pollutants and risk of preterm birth, although effect sizes were attenuated in models that co-adjusted for other TRAP. Exposure to TRAP, especially black carbon, may increase the risk of preterm birth for Latina and Black women but not for Asian and White women.

Extensive empirical health research leverages variation in the timing and location of policy changes as quasi-experiments. Multiple social policies may be adopted simultaneously in the same locations, creating co-occurrence that must be addressed analytically for valid inferences. The pervasiveness and consequences of co-occurring policies have received limited attention. We analyzed a systematic sample of 13 social policy databases covering diverse domains including poverty, paid family leave, and tobacco use. We quantified policy co-occurrence in each database as the fraction of variation in each policy measure across different jurisdictions and times that could be explained by covariation with other policies. We used simulations to estimate the ratio of the variance of effect estimates under the observed policy co-occurrence to variance if policies were independent. Policy co-occurrence ranged from very high for state-level cannabis policies to low for country-level sexual minority-rights policies. For 65% of policies, greater than 90% of the place-time variation was explained by other policies. Policy co-occurrence increased the variance of effect estimates by a median of 57-fold. Co-occurring policies are common and pose a major methodological challenge to rigorously evaluating health effects of individual social policies. When uncontrolled, co-occurring policies confound one another, and when controlled, resulting positivity violations may substantially inflate the variance of estimated effects. Tools to enhance validity and precision for evaluating co-occurring policies are needed.

Social policies have great potential to improve population health and reduce health disparities. Increasingly, those doing empirical research have sought to quantify the health effects of social policies by exploiting variation in the timing of policy changes across places. Multiple social policies are often adopted simultaneously or in close succession in the same locations, creating co-occurrence that must be handled analytically for valid inferences. Although this is a substantial methodological challenge for researchers aiming to isolate social policy effects, only in a limited number of studies have researchers systematically considered analytic solutions within a causal framework or assessed whether these solutions are being adopted. We designated 7 analytic solutions to policy co-occurrence, including efforts to disentangle individual policy effects and efforts to estimate the combined effects of co-occurring policies. We used an existing systematic review of social policies and health to evaluate how often policy co-occurrence is identified as a threat to validity and how often each analytic solution is applied in practice. Of the 55 studies, only in 17 (31%) did authors report checking for any co-occurring policies, although in 36 studies (67%), at least 1 approach was used that helps address policy co-occurrence. The most common approaches were adjusting for measures of co-occurring policies; defining the outcome on subpopulations likely to be affected by the policy of interest (but not other co-occurring policies); and selecting a less-correlated measure of policy exposure. As health research increasingly focuses on policy changes, we must systematically assess policy co-occurrence and apply analytic solutions to strengthen studies on the health effects of social policies.