Demographic Research

Background: Retirement is a major life transition that may influence cognitive aging. Retirement pathways are becoming increasingly diversified, yet evidence on how heterogeneous retirement trajectories relate to dementia risk remains limited. This study used sequence and cluster analysis to characterize thousands of transition-to-retirement trajectories, including retirement timing and work intensity, to estimate associations with dementia risk. Methods: We used data from 13,879 participants in the U.S. Health and Retirement Study. Our exposure was transition-to-retirement trajectories between ages 51 and 75 identified using sequence and cluster analysis. Our outcome was a validated algorithmically derived dementia probability measure. We estimated associations between trajectory clusters and dementia risk beginning at age 76 using generalized estimating equations, adjusting for sociodemographic characteristics. Inverse probability weights were used to account for attrition. Results: We identified ten distinct transition-to-retirement trajectories characterized by differences in timing of retirement, part-time work, disability, and labor force attachment. Compared with individuals retiring after full-time work in their early-to-mid 60s, dementia risk was similar among those retiring earlier or later from full-time work. In contrast, individuals with sustained part-time employment between ages 51 and 75 had lower odds of dementia (OR: 0.62, 95% CI: 0.48, 0.80), while trajectories characterized by prolonged disability were associated with higher odds of dementia (OR: 1.53, 95% CI: 1.22, 1.91). Conclusions: Retirement timing alone showed limited association with later-life dementia risk, whereas sustained part-time employment and disability-related trajectories were more strongly associated with dementia risk. These findings suggest that employment intensity and health-related exit from the labor force may be more relevant for dementia risk than retirement timing, and that gradual and flexible work-to-retirement transitions may benefit brain health. Background: Retirement is a major life transition that may influence cognitive aging. Retirement pathways are becoming increasingly diversified, yet evidence on how heterogeneous retirement trajectories relate to dementia risk remains limited. This study used sequence and cluster analysis to characterize thousands of transition-to-retirement trajectories, including retirement timing and work intensity, to estimate associations with dementia risk. Methods: We used data from 13,879 participants in the U.S. Health and Retirement Study. Our exposure was transition-to-retirement trajectories between ages 51 and 75 identified using sequence and cluster analysis. Our outcome was a validated algorithmically derived dementia probability measure. We estimated associations between trajectory clusters and dementia risk beginning at age 76 using generalized estimating equations, adjusting for sociodemographic characteristics. Inverse probability weights were used to account for attrition. Results: We identified ten distinct transition-to-retirement trajectories characterized by differences in timing of retirement, part-time work, disability, and labor force attachment. Compared with individuals retiring after full-time work in their early-to-mid 60s, dementia risk was similar among those retiring earlier or later from full-time work. In contrast, individuals with sustained part-time employment between ages 51 and 75 had lower odds of dementia (OR: 0.62, 95% CI: 0.48, 0.80), while trajectories characterized by prolonged disability were associated with higher odds of dementia (OR: 1.53, 95% CI: 1.22, 1.91). Conclusions: Retirement timing alone showed limited association with later-life dementia risk, whereas sustained part-time employment and disability-related trajectories were more strongly associated with dementia risk. These findings suggest that employment intensity and health-related exit from the labor force may be more relevant for dementia risk than retirement timing, and that gradual and flexible work-to-retirement transitions may benefit brain health.

Features of urbanicity have been linked to poor psychiatric health in adulthood, but little is known about their relationship with biological age and cognition earlier in life. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we tested associations between the built environment and epigenetic ages (EpiAgeAltum, EpiAgeHorvath, EpiAgePACE) (n=2,452), brain age (n=751), and cognition (n=12,199). Analyses were replicated in Generation R and triangulated in the Millennium Cohort Study. The built environment was not associated with epigenetic ages ({beta}Altum range = 0.013-0.015, p range = .466-.689; {beta}Horvath range = -0.011-0.023, p range = .182-.728; {beta}PACE range = -0.045-0.013, p range = .131-.524) or brain age ({beta} range = 0.022-0.028, p range = .337-.429). A negative association with cognition was observed in Generation R. We provide no consistent evidence that childhood built environment exposure relates to biological age and cognition in adolescence, suggesting these relationships may emerge in later life.

Background Attentional control declines with normal aging, yet the role of modifiable lifestyle factors in accelerating this decline remains incompletely characterised in large, diverse populations. We examined associations between four modifiable risk factors (smoking intensity, alcohol binge drinking, social satisfaction and blood pressure) and sustained attention performance in 13,866 adults drawn from the All of Us Research Program. Methods Cognitive performance was assessed using the Gradual-Onset Continuous Performance Task (GradCPT). A composite cognitive efficiency score was derived via principal component analysis of four GradCPT metrics: d' (perceptual sensitivity), response criterion, median reaction time and reaction time variability. Associations between cognitive efficiency and each risk factor were examined using multiple linear regression adjusted for age, sex and race/ethnicity. Effect sizes were expressed as age-equivalent years of cognitive aging (age-equivalent years = regression coefficient for the risk factor divided by the regression coefficient for age) to aid clinical interpretation. Results GradCPT performance declined progressively with age (p < 0.001). Social satisfaction emerged as the strongest lifestyle predictor: low social satisfaction was associated with approximately 5.8 additional age-equivalent years of cognitive aging relative to high social satisfaction. Smoking showed a dose-response pattern, with heavy smokers (> 20 cigarettes/day) exhibiting an approximately 5-year age-equivalent deficit versus never-smokers. Stage 2 hypertension showed a modest, non-significant negative association. Binge drinking showed limited significant associations, likely complicated by survivor and abstainer biases. Bootstrapped analyses of combined exposures showed that combinations of risk factors, particularly those involving low social satisfaction, produced larger cognitive deficits than expected under an additive model. Conclusions These findings support an interactive rather than a purely additive model of lifestyle-related cognitive vulnerability and highlight the GradCPT as a subclinical measure of attention-based cognitive risk in non-clinical populations. Keywords Cognitive aging, Sustained attention, GradCPT, Modifiable risk factors, Social isolation, Smoking, Hypertension, All of Us Research Program

Importance: Long-term exposure to higher average air pollutant concentrations is associated with poorer cognitive health, but annual averages can obscure substantial differences in day-to-day exposure. Whether recurrent high pollution days are associated with long-term cognitive aging trajectories among people with similar overall air pollution exposure is unclear. Objective: To determine whether the annual number of days exceeding World Health Organization daily guideline values for nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) is associated with subsequent cognitive decline after accounting for annual mean air pollutant exposure. Design: Prospective cohort study using data from waves 1-10 (2002-03 to 2021-23) of the English Longitudinal Study of Ageing. Setting: Population-based cohort of community-dwelling adults in England. Participants: 12,235 adults aged 50+ years at analytic baseline. Exposures: Number of days exceeding World Health Organization daily guideline values ('exceedance days') for NO2, PM2.5, and PM10, derived from residence-linked environmental estimates during the calendar year preceding the analytic baseline. Main Outcomes and Measures: Baseline cognitive performance and model-estimated 14-year cognitive decline (corresponding to the 75th percentile of follow-up duration) in episodic memory and verbal fluency. Results: Exceedance days were not associated with baseline memory or verbal fluency after adjustment for annual mean air pollutant exposure. More NO2 exceedance days were associated with faster cognitive decline: comparing the 75th percentile with the median of NO2 exceedance days, the difference in 14-year decline was -0.09 SD (95% CI, -0.17 to -0.01; p = 0.02) for memory and -0.10 SD (95% CI, -0.19 to 0.00; p = 0.04) for fluency. PM2.5 and PM10 exceedance days were not associated with cognitive decline. Conclusions and Relevance: In this cohort study of older adults, a higher number of NO2 exceedance days was associated with faster subsequent cognitive decline after adjustment for annual mean air pollutant exposure. This suggests that daily exposure to high NO2 concentrations may be related to accelerated cognitive aging even when offset by lower exposure on other days, potentially providing a new rationale for identifying and prioritizing areas with recurrent high NO2 exposure and the local emission sources contributing to it.

Financial well-being (FWB) encompasses objective and subjective financial status and may influence health. We developed and validated a parsimonious FWB index using data from 23,006 Health and Retirement Study (HRS) participants aged 50 years and older from 2006 to 2022. The FWB-5 Index was derived using correlated two-factor confirmatory factor analysis accounting for household clustering. Indicators included household wealth, household income-to-poverty ratio, monthly financial strain, satisfaction with one's financial situation, and perceived financial mastery. We assessed convergent and discriminant validity using the Consumer Financial Protection Bureau Financial Well-Being (CFPB-FWB) Scale and Satisfaction with Life Scale, respectively. Associations with pre-baseline socioeconomic factors and subsequent depressive symptoms and health conditions were examined to assess construct and predictive validity. Model fit indices supported the two-factor structure (robust comparative fit index = 0.99; robust root mean square error of approximation = 0.05). Correlations were stronger with the CFPB-FWB Scale (Spearman P = 0.80) than with life satisfaction (Spearman P = 0.43). Associations with socioeconomic factors and subsequent health outcomes were in the hypothesized directions. These findings support the FWB-5 Index as a parsimonious measure for examining financial well-being and its associations with health across HRS waves, including those predating the CFPB-FWB Scale.

Health inequalities are often examined through single axes such as class or ethnicity, obscuring how these dimensions interlock. This study applies a longitudinal intersectional approach to examine physical and mental health trajectories across five generations in the UK. We analysed 14 waves of the UK Household Longitudinal Study (2009-2024) using longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). We modelled SF-12 physical and mental health trajectories for 398 intersectional strata defined by gender, ethnicity, occupational class, and generation. Physical health inequalities widened with age, consistent with cumulative disadvantage, while mental health inequalities were more evident among later-born cohorts. The 'Boomer' generation exhibited a relatively flat mental health trajectory across its observed age range. In contrast, 'Generation Z' had lower predicted mental health, particularly among White British women with no work history - a group with poorer predicted trajectories than their South Asian peers. Our study shows how health inequalities are structurally differentiated by cohort and intersectional position. Policy responses should support proportionate universalism, combining broad population-level support with intensified action for groups showing poorer health.

Background: Associations of sleep duration and insomnia symptoms with cognitive decline are inconsistent, and whether they represent modifiable risk factors or early manifestations of neurodegeneration may depend on life stage. We examined how sleep-cognition associations vary with age (44 to >90 years). Methods: We studied 16,884 participants from three cohorts with harmonised measures. In the English Longitudinal Study of Ageing (ELSA: n=9,473, median age 64, range 50 to >=90), linear mixed-effects models examined age-specific differences in cognitive change (recall and fluency) associated with sleep duration, difficulty falling asleep, nocturnal awakenings, incorporating sleep-by-age-by-time interactions, with initial adjustment for sociodemographic factors and further adjustment for health and lifestyle factors. Sleep characteristics showing consistent age-dependent associations in ELSA were further evaluated in Whitehall II (n=5,580, median age 55, range 44 to 68) and the Rush Memory and Aging Project (MAP: n=1,831, median age 80, range 53 to 102). Findings: In ELSA, difficulty falling asleep >=1 time/week (vs <1 time/week) was associated with less favourable 5-year change in recall at age 50 (difference -0.12 SD, 95% CI -0.20 to -0.04), with the association attenuating and reversing towards more favourable change at older ages (p-interaction=0.009 [linear], 0.016 [quadratic]). These persisted after further adjustment for health and lifestyle factors. Short sleep (<=6 h) showed similar patterns that attenuated after further adjustment. Similar age gradients were observed for difficulty falling asleep in Whitehall II and MAP. There was no evidence of age modification on long sleep and nocturnal awakenings. Interpretation: The cognitive implications of sleep disturbances vary by life stage. In midlife, difficulty falling asleep was associated with faster cognitive decline, supporting its role as a modifiable risk factor. In advanced age, the reversal is consistent with diminished arousal capacity accompanying prodromal dementia. Funding: US National Institute on Aging

Recent lifespan frameworks of aging theorize that pubertal development and cellular aging are governed by overlapping pathways, but the time lag between adolescence and older adulthood complicates the study of shared molecular mechanisms. Here we compare a DNA-methylation-based epigenetic index of pubertal development to epigenetic clocks, which were designed to measure biological aging, as a putative biomarker of adult aging and health in two adult cohorts: 3,642 older Americans in the Health and Retirement Study (HRS; age range, 56 to 100 years; 2,106 females) and 18,676 adults from Generation Scotland (GS; age range, 18 to 98 years; 10,974 females). Epigenetic puberty was correlated with chronological age in both cohorts, moderately in the older HRS sample (r = 0.51 in females, r = 0.51 in males) and strongly across the wider adult age range of GS (r = 0.82 in females, r = 0.86 in males). In both cohorts, age-residualized epigenetic puberty was associated with accelerated biological aging as measured by epigenetic clocks and other aging biomarkers (standardized coefficients: HRS, 0.13 to 0.47, all P < 0.005; GS, 0.05 to 0.40, all P < 0.001). Epigenetic puberty was linked with multiple health outcomes: mortality in HRS in both sexes (ORs, 1.39 and 1.46, both P [&le;] 0.001) and in GS among females (HR, 1.12, P = 0.003); 10-year onset of diabetes, any cancer and lung disease in GS (HRs, 1.12 to 1.19, all P < 0.005); and with multimorbidity, functional limitations and BMI in females in HRS (standardized coefficients, 0.10 to 0.16, all P < 0.001). It also accounted for a unique, albeit smaller, proportion of variance in aging-related outcomes beyond that explained by epigenetic clocks. These findings indicate that the epigenetic puberty index reflects pro-aging underlying biology, showing overlapping molecular pathways between pubertal development and cellular aging, and support a lifespan-based approach to studying biological aging.

Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD +- 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.

Disability is an important population-health concern, but adult-specific evidence on its distribution and socioeconomic patterning remains limited in Somaliland. This study estimated the prevalence and distribution of reported disability among adults in Somaliland and examined socioeconomic inequality, reported mental/psychological illness, and their co-occurrence. We conducted a cross-sectional secondary analysis of the 2020 Somaliland Health and Demographic Survey. The analysis included 14,579 adults aged [&ge;]18 years who were usual residents, had the disability module administered, and had a defined reported mental/psychological illness measure. Reported disability was defined as at least one positive response across seven disability domains: sight, hearing, speech, learning, mobility, self-care, and mental. Survey-weighted prevalence estimates and design-based comparisons were calculated. Survey-weighted logistic regression assessed associations with household wealth and other covariates. Socioeconomic inequality was assessed using a concentration index and the normalized Erreygers concentration index. Co-occurrence was evaluated by comparing observed joint prevalence with that expected under statistical independence and by survey-weighted logistic regression. The survey-weighted prevalence of any reported disability was 7.30% (95% CI 6.65-8.02). Sight was the most frequently reported domain (3.83%, 95% CI 3.19-4.59), followed by hearing (1.54%, 95% CI 1.20-1.97) and mobility (1.39%, 95% CI 1.14-1.70). Disability prevalence increased markedly with age, from 4.15% among adults aged 18-29 years to 23.96% among those aged [&ge;]60 years. The crude wealth pattern was non-monotonic and was not statistically detectable after adjustment for residence and region. The concentration index for reported disability was 0.0584 (SE 0.0284, p=0.0415). Reported mental/psychological illness had a weighted prevalence of 0.71% (95% CI 0.50-1.00). Both reported disability and reported mental/psychological illness occurred in 0.5032% of adults, compared with 0.05185% expected under statistical independence; the observed-to-expected ratio was 9.70 (95% CI 7.60-11.81). After adjustment for age group and sex, reported disability was strongly associated with reported mental/psychological illness (OR 42.99, 95% CI 18.45-100.18). Reported disability affected approximately one in fourteen adults in Somaliland and showed a marked age gradient and substantial geographic variation. The crude socioeconomic pattern was attenuated after adjustment for geographic context, while concentration analysis indicated modest marginal concentration toward higher wealth ranks. Reported mental/psychological illness was uncommon but co-occurred with reported disability more often than expected under independence. These findings provide an adult population baseline for Somaliland while highlighting the need to distinguish survey-reported disability from the separate mental/psychological illness construct and to interpret the findings within the limitations of cross-sectional, survey-reported measures.

Heavy snowpack can be a severe constraint for alpine herbivores, yet adult survival in long-lived temperate ungulates is typically canalized against environmental variation. Using a 45-year individual-based dataset on bighorn sheep (Ovis canadensis) and historical snow reconstructions at Ram Mountain, Canada, we evaluated the direct and indirect effects of snow conditions on age- and sex-specific survival. For both sexes, survival of lambs and senescent individuals decreased with increasing average snow depth, whereas non-senescent adults (aged [&ge;] 1 year and < 8 years) showed high survival under mean conditions. However, this resilience broke down once specific thresholds of snow depth were crossed, with sharp survival declines beyond 90 cm of snow depth for females and 100 cm for males. Lamb survival, already reduced by increasing average snow depth, declined further once snow depth exceeded 90 cm. Crucially, the annual probability of snow depth exceeding 90 cm increased markedly over the study period, along with a density-independent temporal decline in survival across all demographic groups. Lamb survival declined by 0.37, and adult female survival, the most critical vital rate for population growth, dropped by 0.13 over the study period. Our findings challenge the established paradigm of demographic buffering in prime-aged adults, demonstrating that their resilience to environmental variability is fundamentally non-linear and breaks down once a changing climate regime breaches adult physiological boundaries, severely compromising population viability.

Background: Excess mortality estimates depend on an expected baseline, an unobservable quantity typically derived from models with prescribed functional forms and short reference periods that exclude exceptional events. Singular Spectrum Analysis (SSA) offers a nonparametric alternative but requires subjective component selection and is sensitive to outliers. We combined SSA with automated component selection and outlier interpolation to estimate long-term baselines and compile a catalog of excess mortality events (EMEs). Methods: We analyzed weekly all-cause mortality (2015-2024) for six metropolitan areas with contrasting climatic, demographic, and epidemiological contexts: Brussels, Antwerp, and Liege (Belgium), and Athens, Thessaloniki, and Larisa (Greece). SSA was applied to standardized log-mortality rates; components were selected using Monte Carlo SSA, and COVID-19 periods were interpolated iteratively. EMEs were defined as weeks exceeding a quasi-Poisson two-z-score threshold, then screened for coincidence with heat waves, cold waves, COVID-19 periods, and influenza epidemics. Results: Baselines were consistent within countries: annual cycles in Belgium, with an additional significant semiannual cycle in Greece reflecting summer mortality. We cataloged 170 EMEs spanning 456 weeks and 14,210 excess deaths. Pandemic weeks accounted for 77% of excess mortality, and 96 weeks coincided with temperature extremes; 56 EMEs, representing 3.7% of excess mortality, remained unmatched. Conclusions: SSA yields reproducible, low-assumption baselines that capture country-specific seasonality. Because flexible baselines can absorb recurrent seasonal mortality, component selection is a substantive choice that should be reported explicitly, together with its sensitivity.

Although physical activity is associated with better physical functioning, the effects of initiating regular physical activity among older adults with persistent inactivity remain unclear. We conducted a sequential target trial emulation using Health and Retirement Study (HRS) data to estimate the effect of physical activity initiation versus noninitiation on incident mobility difficulty. Participants were included in the analysis if they were aged [&ge;]65 years at the previous wave, reported no regular physical activity at the previous two waves, and had no mobility, activities of daily living (ADL), or instrumental activities of daily living (IADL) difficulties at baseline. Stabilized inverse probability of treatment weighting was applied to adjust for measured confounding. Weighted cumulative incidence was then estimated with death treated as a competing event, and risk differences were calculated at approximately 2, 4, and 6 years. At 2 years, the cumulative incidence of mobility difficulty was 32.75% among initiators and 39.73% among noninitiators, with a risk difference of -6.98 percentage points (95% CI, -13.11 to -0.88). At 4 and 6 years, risk differences were -2.90 percentage points (95% CI, -9.77 to 4.29) and -5.44 percentage points (95% CI, -12.27 to 1.99), respectively. Initiating regular moderate or vigorous physical activity was associated with a lower risk of incident mobility difficulty at approximately 2 years among older adults with persistent inactivity. This difference was less evident at later follow-up, and no clear differences were observed for incident ADL or IADL difficulty.

Non-exponential residence times give rise to history-dependent or memory effects in epidemic dynamics, yet their mathematical formulations remain fragmented. Here we develop a unified framework for a history-dependent SEIR model with general latent- and infectious-period distributions. We first establish the equivalence between the stage-age and renewal formulations and show that both admit a unified transition-flow representation. We then introduce the concept of a transition-flow multiplier, which provides a direct link between residence-time distributions and transition flows. When the multiplier is a weighted sum of shifted power functions, the model admits an exact representation in terms of Riemann-Liouville or tempered Riemann-Liouville fractional operators, providing a first-principles foundation for fractional epidemic models. Finally, using Euler-Lotka equations and stochastic-order arguments, we characterize how the latent- and infectious-period distributions shape epidemic growth and decay. A longer latent period slows both early growth and late decay, while, at fixed means, greater variability in the latent period accelerates early growth but slows late decay, whereas greater variability in the infectious period slows both.

Demographic stochasticity is generally expected to contribute little to population variability when census abundance is large, because random demographic events are increasingly averaged across many individuals. This expectation, however, depends on how evenly individuals contribute to reproduction. In many natural populations, reproductive success is highly skewed, so that a large census population can coexist with a much smaller effective number of breeders (Nb). Although Nb is commonly used as a genetic measure of contemporary effective size, it also summarizes variation in reproductive contribution and may therefore contain information about demographic variability. Here, we develop a female-based age-structured theoretical framework linking Nb to temporal variability in mature population abundance, with N denoting the census number of mature females and Nb the effective number of female breeders. Recruitment variability arises from non-Poisson reproductive variation and environmental stochasticity, and its transmission to mature abundance is described by a life-history coefficient, {gamma}, determined by survival, maturation, and the contribution of overlapping cohorts. When the Poisson component of recruitment variance is negligible and Nb/N is sufficiently small, the coefficient of variation in mature abundance, CV[N], can be approximated from Nb, environmental variability, and {gamma}, with little additional information from census abundance. This approximation does not require specification of the functional form of the relationship between adult abundance and recruitment. Stochastic age-structured simulations closely reproduced the analytical prediction, even when additional demographic stochasticity in survival was included. Substantial fluctuations in mature abundance occurred at census sizes on the order of 105 when Nb was small, whereas overlapping cohorts buffered recruitment fluctuations. Because Nb can be estimated genetically from samples of a single cohort, the framework provides a direct link between genetic monitoring and population dynamics. More broadly, these results show that large census abundance alone does not guarantee weak demographic variability and highlight the potential of genetic data to inform expected population fluctuations when detailed demographic information is limited.

Chronic disease accounts for most health care expenditures in the United States (US), highlighting the need for approaches that address health across interconnected spiritual, mental/emotional, behavioral, physical (including environmental), and social domains. Whole person health (WPH) is increasingly recognized as important for alleviating chronic disease burdens but has not been well-described across various sociodemographic groups of US adults. Using cross-sectional data from the 2025 National Health Interview Survey, we sought to describe the prevalence of WPH and its components among US adults overall and by age, sex, and race along with ethnicity. Participants responded to the nine-item Whole Person Health Index (WPHI), which we used to assess continuous scores (range: 9-45, where higher scores indicated improved health) and ''optimal'' (excellent/very good vs. good/fair/poor) overall and domain-specific WPH. Using survey procedures, we estimated medians (IQR) and prevalence (95% CI) and compared subgroups using multiple comparison correction. Among 23,884 NHIS participants aged 18 years and older (mean age (SE)=48 (0.2) years), representing approximately 261,620,640 US adults, the median WPHI score was 33 (28-37) and slightly over half (57% [56%-58%]) of adults were classified as having ''optimal'' overall WPH. Optimal social/family connections (72% [72%-73%]) were frequently reported; ''optimal'' sleep was infrequently reported (36% [35%-37%]). WPH and its components were generally highest among younger adults. Men and women differed in WPH domains but not in overall WPH. Non-Hispanic (NH) American Indian/Native Alaskan and NH-Black adults generally had lowest prevalence of optimal WPH and its components, which was often higher among Hispanic/Latino adults and highest among NH-Asian and White adults. These results showing variation in WPH in the US may inform future investigations of WPH, related predictors and health outcomes, and health disparities.

Background: Unpaid caregiving is a recognised social determinant of health, yet most research treats it as a fixed exposure measured at a single time point, and little is known about how patterns of caregiving transitions relate to health behaviours. Methods: Secondary analysis of the UK Household Longitudinal Study (waves 2 to 13, approximately 2010 to 2023; n=25,049). Latent class analysis was applied to binary caregiving status across 12 waves to identify caregiving trajectories. Associations between trajectories and four health behaviours (physical inactivity, fruit and vegetable consumption, problematic drinking, current smoking) at waves 7 to 13 were estimated using logistic and linear regression, adjusting for sociodemographic, health and baseline behavioural confounders. Results: An eight-class solution identified a non-caregiving class comprising 62.9% (n=15,760) of the sample. Among caregivers (n=9,289), trajectories were Temporary (20.0%), Former-short (20.2%), Former-long (10.9%), Emerging-short (15.4%), Emerging-long (11.6%), Long-term (15.7%) and Recurrent (6.3%). In fully adjusted models, Recurrent caregivers had higher odds of smoking (OR=1.67, 95%CI: 1.17 to 2.40) compared with non-caregivers but lower odds of physical inactivity (OR=0.65, 95%CI: 0.53 to 0.81) and problematic drinking (OR=0.75, 95%CI: 0.59 to 0.94). Associations for other trajectory classes were largely attenuated after adjustment. Conclusion: The pattern and timing of caregiving transitions are an under-explored dimension of the caregiving experience. Recurrent caregivers had a distinctive profile, with elevated smoking but lower physical inactivity and problematic drinking. Recurrent caregiving should be recognised alongside intensity and duration, and support systems better equipped for people who move into and out of care repeatedly.

Background: COVID-19 movement restrictions reduced social contact worldwide, curbing viral spread but with unequal economic consequences where social safety nets are limited. Little evidence exists on how these impacts varied by occupation, wealth and age in resource-constrained settings. This paper examined pre-pandemic contact and lockdown-related change. Methods: The paper documents analysis of a population-representative survey (N=8,499) in Manicaland, Zimbabwe, during April-May 2021, capturing typical weekday contacts before and during the first COVID-19 lockdown. Negative binomial regression models assessed pre-lockdown contact counts by socio-economic characteristics, overall and by place (home, school, work, transport, entertainment); linear regression assessed predictors of lockdown declines. Results: Pre-COVID-19, respondents reported a median of 12 daily contacts (interquartile range [IQR] 4-47), with higher counts among manual labourers (incidence rate ratio [IRR] 2.21, 95% confidence interval [CI] 2.00, 2.44), retail and public sector workers (IRR 2.33, 95%CI 2.09, 2.60) and students (IRR 2.59, 95%CI 2.38, 2.82), males, wealthier respondents, under-30s, and urban and agricultural estate residents. Counts were highest in schools. During lockdown, contacts fell across all subgroups to a median of 8 (IQR 4-28). Declines were greatest among those with most pre-COVID-19 contacts: urban (mean -17.5, 95%CI -19.53, -15.37) and agricultural estate residents (-18.1, 95%CI -19.99, -16.13), students and teachers (-17.7, 95%CI -19.82, -15.59), males and 30-44 year olds. Drops were greatest in schools and on transport. Conclusion: Reductions in contact under blanket lockdown varied markedly between subgroups and places in Manicaland, Zimbabwe. Selectively targeting high-contact groups might have achieved similar transmission reductions while limiting economic damage, holding lessons for similar settings.

1. Temperature shapes life histories through its effects on energy allocation among growth, reproduction and maintenance. The resulting temperature dependence of performance is commonly characterised using thermal performance curves (TPCs), which are often treated as static descriptions that apply uniformly throughout life. Yet the response to thermal variability may change across ontogeny. 2. We recorded growth, reproduction and survival throughout the lifetimes of individual Daphnia magna under four thermal regimes: Constant Low (15C), Constant Rearing (20C), Constant High (25C) and Variable (15C to 25C). The mean temperature under Variable closely matched that under Constant Rearing. Using an allometric energy-allocation model, we derived age specific and lifetime performance measures and quantified their uncertainty with a stratified individual-level bootstrap. Our principal quantity was the Jensen contrast, defined as performance under Variable minus that under Constant Rearing. 3. Age specific point estimates of the Jensen contrast changed sign across ontogeny. A positive aggregate contrast in full trajectory growth concealed a negative mid-life contrast; reproductive point estimates were positive during early and mid life but negative later. Bootstrap support was strong for the positive early life and negative mid-life growth contrasts, and for the positive early life reproductive contrast. Under a second-order approximation, this pattern of estimated signs is consistent with ontogenetic changes in effective thermal curvature. 4. The positive early life reproductive response did not carry through to the lifetime outcome: expected lifetime reproduction was lower under Variable than under Constant Rearing, with strong bootstrap support for the negative lifetime contrast. Because lifetime reproduction is survival weighted, lower survival under Variable reduced later reproductive contributions; across the estimated trajectories, the accumulated negative late life contribution out-weighed the earlier positive contributions. 5. These results show why forecasts based on mean temperature, a single life stage or an aggregate TPC may misrepresent lifetime performance under variable thermal regimes. Accounting for both ontogeny and temperature variability may therefore improve forecasts of life-history performance in increasingly variable thermal environments.

Background: Previous studies indicated that regional fluctuations in COVID-19 impact were associated with socioeconomic, demographic and environmental factors early in the pandemic. It is unclear whether factors associated with regional COVID-19 mortality and SARS-CoV-2 infections changed over the course of the pandemic. Methods: We evaluated the association of ecological factors with municipality-specific COVID-19 mortality in the national population of Austria between January 2020 and June 2023. Analyses were conducted separately per calendar year and pooled across years via random-effects meta-analysis. Outcomes were analysed using univariable and multivariable zero-inflated negative binomial (ZINB) regression, including annually averaged environmental exposome exposure (including air pollution and UV radiation), socioeconomic, demographic and infection dissemination predictors with significance threshold set to p<0.005. Secondary analysis modelled SARS-CoV-2 infections using of negative-binomial model (NB). Two additional approaches for smaller predictor set selection were applied as sensitivity analyses. Results: Within the entire observation period 18,430 COVID-19 deaths were reported. In univariable analyses (pooled RR (99.5% CI)), COVID-19 mortality was significantly associated with the proportion of commuters (0.79 (0.73-0.86)), residents aged 75-84 (1.18 (1.01-1.37)) and [&ge;]85 years (1.29 (1.04-1.60)), residents with at most compulsory education (1.15 (1.02-1.29)), employed residents aged 15-64 (0.89 (0.85-0.93)), and homeowners (0.91 (0.83-0.99)), as well as with precipitation (0.94 (0.89-0.99)) and the average time with a mean temperature of 5-15 C (0.95 (0.90-0.99)). In multivariable analyses the share of population aged 85 or older (1.30 (1.09-1.54)) and home ownership (0.92 (0.87-0.98)) were independently significant. Mortality predictor estimates were relatively stable across pandemic years. Across 5,963,882 documented SARS-CoV-2 infections share of employed in 15- to 64-year-olds (1.01 (1.01-1.02)), part-time employment rate (1.01 (1.00-1.02)) and district level nursing care allowance recipiency (0.97 (0.95-0.98)) were associated with detected infections. Overnight stays, population 85 or older, income, compulsory education or less and air pollution all had multiple significant estimates with opposite directionality, leading to non-significant overall associations. Sensitivity analyses outcomes mirrored main analyses outcomes. Conclusions: Throughout the pandemic in Austria, demographic and socioeconomic factors were associated with COVID-19 mortality and infections, but many associations, especially for infections, were unstable over time. These findings underscore the importance of structural vulnerabilities in epidemic impact.