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BackgroundDespite evidence linking posttraumatic stress disorder (PTSD), depression, and head injury, separately, with worse cognitive performance, investigations of their combined effects on cognition are limited in civilian women.MethodsThe Cogstate Brief Battery assessment was administered in 10,681 women from the Nurses' Health Study II cohort, mean age 64.9 years (SD = 4.6). Psychological trauma, PTSD, depression, and head injury were assessed using online questionnaires. In this cross-sectional analysis, we used linear regression models to estimate mean differences in cognition by PTSD/depression status and stratified by history of head injury.ResultsHistory of head injury was prevalent (36%), and significantly more prevalent among women with PTSD and depression (57% of women with PTSD and depression, 21% of women with no psychological trauma or depression). Compared to having no psychological trauma or depression, having combined PTSD and depression was associated with worse performance on psychomotor speed/attention ( β  = -.15, p = .001) and learning/working memory ( β  = -.15, p

ObjectiveTo test the hypothesis that life course patterns of employment, marriage, and childrearing influence later-life rate of memory decline among women, we examined the relationship of work-family experiences between ages 16 and 50 years and memory decline after age 55 years among US women.MethodsParticipants were women ages ≥55 years in the Health and Retirement Study. Participants reported employment, marital, and parenthood statuses between ages 16 and 50 years. Sequence analysis was used to group women with similar work-family life histories; we identified 5 profiles characterized by similar timing and transitions of combined work, marital, and parenthood statuses. Memory performance was assessed biennially from 1995 to 2016. We estimated associations between work-family profiles and later-life memory decline with linear mixed-effects models adjusted for practice effects, baseline age, race/ethnicity, birth region, childhood socioeconomic status, and educational attainment.ResultsThere were 6,189 study participants (n = 488 working nonmothers, n = 4,326 working married mothers, n = 530 working single mothers, n = 319 nonworking single mothers, n = 526 nonworking married mothers). Mean baseline age was 57.2 years; average follow-up was 12.3 years. Between ages 55 and 60, memory scores were similar across work-family profiles. After age 60, average rate of memory decline was more than 50% greater among women whose work-family profiles did not include working for pay after childbearing, compared with those who were working mothers.ConclusionsWomen who worked for pay in early adulthood and midlife experienced slower rates of later-life memory decline, regardless of marital and parenthood status, suggesting participation in the paid labor force may protect against later-life memory decline.

Social support during childhood lays the foundation for social relationships throughout the life course and has been shown to predict a wide range of mental and physical health outcomes. Social support measured in late life is prospectively associated with better cognitive aging, but few studies have evaluated social support received earlier in the life course. We quantified the effects of childhood social support, reported retrospectively, on later-life cognitive trajectories and investigated biopsychosocial mechanisms underlying these associations. Latent growth curve models estimated 10-year cognitive trajectories in 8,538 participants (baseline ages 45-93; Mage = 63) in the REasons for Geographic And Racial Differences in Stroke (REGARDS) project. Independent of sociodemographics, childhood socioeconomic status, and household size, greater retrospective childhood social support was associated with better initial episodic memory, but not verbal fluency or cognitive change, in later adulthood. Associations with initial memory level were mediated by sociodemographic and psychosocial variables; specifically, those who reported greater childhood social support reported higher educational attainment and had better physical and emotional health in adulthood, which were each associated with better memory. These results provide support for broad and enduring effects of childhood social support on mental, physical, and cognitive health decades later. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background: Evaluating the long-term health consequences of migration requires longitudinal data on migrants and non-migrants to facilitate adjustment for time-varying confounder-mediators of the effect of migration on health.Methods: We merged harmonized data on subjects aged 50+ from the US-based Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS). Our exposed group includes MHAS-return migrants (n = 1555) and HRS Mexican-born migrants (n = 924). Our unexposed group includes MHAS-never migrants (n = 16,954). We constructed a lifecourse data set from birth (age 0) until either age at migration to the United States or age at study entry. To account for confounding via inverse probability of treatment weights (IPTW), we modeled the probability of migration at each year of life using time-varying pre-migration characteristics. We then evaluated the effect of migration on mortality hazard estimated with and without IPTW.Results: Mexico to the United States migration was predicted by time-varying factors that occurred before migration. Using measured covariates at time of enrollment to account for selective migration, we estimated that, for women, migrating reduces mortality risk by 13%, although this estimate was imprecise and results were compatible with either large protective or deleterious associations (hazard ratio [HR] =0.87, 95% confidence interval [CI]: 0.60, 1.27). When instead using IPTWs, the estimated effect on mortality was similarly imprecise (HR = 0.98, 95% CI: 0.77, 1.25). The relationship among men was similarly uncertain in both models.Conclusions: Although time-varying social factors predicted migration, IPTW weighting did not affect our estimates. Larger samples are needed to precisely estimate the health effects of migration. [ABSTRACT FROM AUTHOR]

We used differences in state school policies as natural experiments to evaluate the joint influence of educational quantity and quality on late-life physical and mental health. Using US Census microsample data, historical measures of state compulsory schooling and school quality (term length, student-teacher ratio, and attendance rates) were combined via regression modeling on a scale corresponding to years of education (policy-predicted years of education (PPYEd)). PPYEd values were linked to individual-level records for 8,920 black and 14,605 white participants aged ≥45 years in the Reasons for Geographic and Racial Differences in Stroke study (2003–2007). Linear and quantile regression models estimated the association between PPYEd and Physical Component Summary (PCS) and Mental Component Summary (MCS) from the Short Form Health Survey. We examined interactions by race and adjusted for sex, birth year, state of residence at age 6 years, and year of study enrollment. Higher PPYEd was associated with better median PCS (β = 1.28, 95% confidence interval (CI): 0.40, 1.49) and possibly better median MCS (β = 0.46, 95% CI: –0.01, 0.94). Effect estimates were higher among black (vs. white) persons (PCS × race interaction, β = 0.22, 95% CI: –0.62, 1.05, and MCS × race interaction, β = 0.18; 95% CI: –0.08, 0.44). When incorporating both school quality and duration, this quasiexperimental analysis found mixed evidence for a causal effect of education on health decades later. [ABSTRACT FROM AUTHOR]

Trauma, defined as exposure to actual or threatened death, serious injury or sexual violence, is a pervasive, major public health challenge that disproportionately burdens socially disadvantaged groups and has known consequences for health outcomes in early and midlife. Despite plausible mechanisms by which trauma may also be a critically important risk factor for health outcomes in late life, there is presently a lack of literature evaluating the consequences of trauma on aging related health outcomes and inequities, such as dementia. In this commentary, we (a) discuss drivers of the paucity of epidemiological evidence on trauma and health outcomes in late life, namely a lack of available data, supported by detailed review of trauma measures, including interpersonal violence-a particularly common form of trauma-in seven established longitudinal aging cohort studies in the United States (US); (b) address four common concerns about the inclusion of trauma measures in cohort studies; and (c) suggest ways forward, including specific assessment tools to measure interpersonal violence after a structured review of the PhenX Toolkit, to facilitate critical research to understand the impact of trauma on outcomes in late life., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Most prior work in quantitative approaches to generalizability and transportability emphasizes extending causal effect estimates from randomized trials to target populations. Extending findings from observational studies is also of scientific interest, and identifiability assumptions and estimation methods differ from randomized settings when there is selection on both the exposure and exposure-outcome mediators in combination with exposure-outcome confounders (and both confounders and mediators can modify exposure-outcome effects). We argue that this causal structure is common in observational studies, particularly in the field of lifecourse epidemiology, e.g., when extending estimates of the effect of an early-life exposure on a later-life outcome from a cohort enrolled in mid- to late-life. We describe identifiability assumptions and identification using observed data in such settings, highlighting differences from work extending findings from randomized trials. We describe statistical methods, including weighting, outcome modeling, and doubly robust approaches to estimate potential outcome means and verage treatment effects in the target population and illustrate performance of the methods in a simulation study. We show that in the presence of selection into the study sample on both exposure and confounders, estimators must be able to address confounding in the target population. When there is also selection on mediators of the exposure-outcome relationship, estimators need to be able to use different sets of variables to account for selection (including the mediator), and confounding. We discuss conceptual implications of our results, as well as highlight unresolved practical questions for applied work to extend findings from observational studies to target populations., Competing Interests: Conflicts of interest/disclosures: None., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)