How "Clocking in" Ages Us: An Examination of Work History, Work Quality, and Accelerated Epigenetic Aging in Older Adulthood.

BACKGROUNDDepression is a significant risk factor for diabetes, particularly type 2 diabetes. However, depressive symptoms differ from clinical depression. Previous research has not fully considered the relationship between the trajectory of depressive symptoms and the risk of developing diabetes over time.AIMTo investigate the association between depressive symptoms, their trajectories, and the risk of developing diabetes in two prospective cohort studies.METHODSIn the first phase we analyzed the association between depressive symptoms and the risk of developing diabetes separately using the Health and Retirement Study (HRS). Depressive symptom trajectories were assessed by examining changes in depressive symptoms at baseline and again 8 years later. We then identified specific depressive symptom trajectories that increased the risk of diabetes in the second phase. Finally, we confirmed the association between depressive symptoms and their trajectories with diabetes risk using the English Longitudinal Study of Ageing (ELSA) as a validation study. Depressive symptom trajectories were categorized into five states based on changes in the modified 8-item Center for Epidemiological Studies-Depression scores: Persistently high; increasing; fluctuating; decreasing; and persistently low. Diabetes mellitus was defined as self-reported, physician-diagnosed diabetes. Cox proportional hazards models were used to assess hazard ratios (HR) and 95% confidence intervals (CI), adjusting for potential confounders.RESULTSIn the first phase a total of 27658 participants were included (HRS: 18633, ELSA: 9025), among whom 6582 had depressive symptoms (HRS: 4547, ELSA: 2035), 6407 had somatic depressive symptoms (HRS: 4414, ELSA: 1993), and 26415 had cognitive-affective depressive symptoms (HRS: 17755, ELSA: 8660). We found that overall depressive symptoms (HRS: HR = 1.14, 95%CI: 1.07-1.22; ELSA: HR = 1.18, 95%CI: 1.03-1.34) and somatic depressive symptoms (HRS: HR = 1.14, 95%CI: 1.07-1.22; ELSA: HR = 1.25, 95%CI: 1.10-1.42) increased the risk of diabetes, while cognitive depressive symptoms were not associated with diabetes risk. Over an 8-year follow-up we identified 19729 trajectories of overall, somatic, and cognitive-affective depressive symptoms (HRS: 13918, ELSA: 5811). In the second phase we found that persistently high (HRS: HR = 1.22, 95%CI: 1.06-1.40, ELSA: HR = 1.54, 95%CI: 1.16-2.05 in total and HRS: HR = 1.24, 95%CI: 1.07-1.43, ELSA: HR = 1.79, 95%CI: 1.36-2.35 in somatic) and fluctuating (HRS: HR = 1.09, 95%CI: 1.01-1.17, ELSA: HR = 1.33, 95%CI: 1.14-1.55 in total and HRS: HR = 1.10, 95%CI: 1.02-1.18, ELSA: HR = 1.31, 95%CI: 1.13-1.53 in somatic) trajectories of overall and somatic depressive symptoms increased the risk of diabetes, while increasing trajectories may also raise diabetes risk. However, decreasing trajectories were not associated with diabetes risk. Cognitive-affective depressive symptoms showed no association with diabetes risk regardless of trajectory changes. Sensitivity analyses confirmed the reliability of the findings.CONCLUSIONPersistently high and fluctuating trajectories of overall and somatic depressive symptoms increased the risk of diabetes, while decreasing trajectories were not associated with diabetes risk. In contrast trajectories of cognitive-affective depressive symptoms show no relationship with diabetes risk. Focusing on depressive symptom trajectories, particularly those of somatic depressive symptoms, represented a viable strategy for future diabetes prevention.

BACKGROUNDDepressive symptoms differ from clinical depression. However, the relationship between depressive symptom trajectories and stroke risk across diverse geographic regions remains unclear.AIMTo address the gap in the existing understanding of the relationship between depressive symptom trajectories and stroke risk, the current study utilized three representative cohorts.METHODSIn this study, we used three representative cohorts from Asia, Europe, and the Americas: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), and Health and Retirement Study (HRS). Depressive symptoms were assessed using the 8-item Center for Epidemiological Studies Depression scale and categorized into somatic and cognitive-affective subtypes. The trajectories of depressive symptoms were monitored over four surveys starting from baseline and classified into five distinct states: persistently low, decreasing, fluctuating, increasing, and consistently high. Self-reported physician diagnoses were used to evaluate the subsequent stroke events. Hazard ratios (HRs) and 95% confidence intervals (95%CIs) were computed using Cox proportional-risk models adjusted for potential confounding factors.RESULTSA total of 7990 participants from CHARLS (females: 52.3%, mean age: 63.4 years), 5642 participants from ELSA (females: 56.2%, mean age: 63.7 years), and 12260 participants from HRS (females: 61.4%, mean age: 64.7 years) participated in this study. The median follow-up periods were 5 years for CHARLS, 8 years for ELSA, and 10 years for HRS. In comparison with the persistently low trajectory, consistently high and fluctuating trajectories of total depressive symptoms increased the risk of stroke in all three cohorts (CHARLS: HR = 1.80, 95%CI: 1.36-2.38; ELSA: HR = 1.50, 95%CI: 1.02-2.21; HRS: HR = 1.45, 95%CI: 1.29-1.62 for consistently high; CHARLS: HR = 1.47, 95%CI: 1.14-1.90; ELSA: HR = 1.44, 95%CI: 1.17-1.77; HRS: HR = 1.26, 95%CI: 1.13-1.41 for fluctuating). Increasing trajectories enhanced the risk in the European cohort (ELSA: HR = 1.71, 95%CI: 1.06-2.74), while decreasing trajectories did not increase stroke risk in any cohort. For somatic depressive symptoms, consistently high and fluctuating trajectories increased the risk of stroke across all cohorts (CHARLS: HR = 2.16, 95%CI: 1.67-2.79; ELSA: HR = 1.94, 95%CI: 1.34-2.81; HRS: HR = 1.79, 95%CI: 1.49-2.15 for consistently high; CHARLS: HR = 1.35, 95%CI: 1.20-1.62; ELSA: HR = 1.56, 95%CI: 1.27-1.92; HRS: HR = 1.33, 95%CI: 1.20-1.46 for fluctuating). Increasing trajectories only increased the risk in the European cohort (ELSA: HR = 1.95, 95%CI: 1.11-3.43), while decreasing trajectories did not increase stroke risk in the European and American cohorts. For cognitive-affective depressive symptoms, consistently high and fluctuating trajectories increased the risk in the Asian and European cohorts (CHARLS: HR = 2.06, 95%CI: 1.52-2.81; ELSA: HR = 1.25, 95%CI: 1.02-1.54 for consistently high; CHARLS: HR = 1.63, 95%CI: 1.23-2.16; ELSA: HR = 1.58, 95%CI: 1.11-2.24 for fluctuating). Increasing trajectories increased the risk only in the American cohort (HRS: HR = 14.67, 95%CI: 1.87-114.91).CONCLUSIONConsistently high and fluctuating trajectories of total and somatic depressive symptoms were associated with an increased risk for stroke across all populations. Consistently high, fluctuating, and increasing trajectories of cognitive-affective symptoms pose a risk for certain populations. These findings highlight the importance of targeted interventions for managing depressive symptoms as potential strategies for stroke prevention, particularly in regions where specific symptom trajectories are prevalent.

BackgroundEarlier research has documented an association between depressive symptomatology and heightened stroke risk. However, prior work largely assessed depressive manifestations at isolated time points and failed to differentiate symptom subtypes. This investigation seeks to characterize the longitudinal progression of depressive symptoms via repeated measurement and explore their link to stroke risk by considering total depressive symptoms alongside cognitive-affective and somatic dimensions.MethodsThis prospective cohort study included individuals aged ≥ 45 years from the Health and Retirement Study (HRS) in the United States and the English Longitudinal Study of Ageing (ELSA) in the United Kingdom, excluding those with a history of stroke during the exposure period. Depressive symptoms were measured using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D) across four biennial assessments. Individuals were categorized into five distinct depressive symptom trajectories: consistently low, decreasing, fluctuating, increasing, and consistently high, based on assessment scores. Over a subsequent decade of follow-up, incident strokes were identified through self-reported physician diagnoses. The analyses incorporated adjustments for demographic factors (sex, age, etc.), health-related behaviors (smoking, drinking, etc.), and health status covariates (hypertension, diabetes, etc.). Cox proportional hazards regression models generated hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate links between trajectories of total depressive symptoms, cognitive-affective and somatic subtypes, and stroke occurrence.ResultsThe final cohort included 10,011 participants (63.3% female; mean age 60.2 years). During the 10-year follow-up, 720 incident strokes were recorded. Analyses demonstrated that, after adjusting for the aforementioned demographic and health-related confounders, relative to the consistently low trajectory, participants with fluctuating (HR = 1.24, 95% CI: 1.01–1.52), increasing (HR = 1.31, 95% CI: 1.03–1.67), and consistently high (HR = 1.42, 95% CI: 1.03–1.97) total depressive symptom trajectories exhibited significantly elevated stroke risk. Conversely, the decreasing trajectory (HR = 1.11, 95% CI: 0.85–1.45) did not significantly impact stroke risk. Furthermore, an increasing trajectory of cognitive-affective depressive symptoms (HR = 1.43, 95% CI: 1.13–1.82), alongside fluctuating (HR = 1.27, 95% CI: 1.03–1.55) and consistently high (HR = 1.97, 95% CI: 1.42–2.74) somatic depressive symptom trajectories, were each significantly associated with heightened stroke risk. Critically, the consistently high somatic trajectory demonstrated the most robust association with stroke.ConclusionTrajectories of total depressive symptoms marked by escalation, instability, or sustained elevation exhibited significantly elevated stroke risk. In contrast, individuals displaying decreasing depressive symptoms exhibit stroke risk comparable to those maintaining consistently low levels. Specifically, an ascending trajectory of cognitive-affective symptoms, alongside unstable and persistently elevated trajectories of somatic symptoms, are linked to increased stroke risk. These findings emphasize the clinical importance of monitoring dynamic changes in depressive symptoms and their subtypes for stroke prevention. Future investigations should elucidate underlying mechanisms to refine identification and intervention strategies for high-risk populations.

While cardiovascular disease and cancer share common risk factors and exhibit complex bidirectional interplay, evidence regarding the interacting and joint effects of frailty and depressive symptoms on the risk of cardio-oncology comorbidity in older adults remains scarce. This study aimed to examine the association between frailty and depressive symptoms with the risk of cardio-oncology comorbidity, and to explore their interacting and joint effects. This study harmonized data from three prospective, nationally representative cohort studies: China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the Health and Retirement Study (HRS). The final analytical sample included 10,937 participants aged ≥ 65 years without baseline cardio-oncology comorbidity. Frailty and depressive symptoms were assessed at baseline. Cardio-oncology comorbidity was ascertained based on self-reported physician diagnoses of cardiovascular disease and cancer. Cox proportional hazards models were utilized to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Multiplicative and additive interaction analyses were conducted, followed by joint association evaluations. Frailty (CHARLS HR = 1.71; ELSA HR = 1.41; HRS HR = 1.38) and depressive symptoms (CHARLS HR = 1.27; ELSA HR = 1.20; HRS HR = 1.18) were independently associated with significantly increased cardio-oncology comorbidity risk. While interaction analyses demonstrated the absence of significant multiplicative or additive interactions, the joint effect analysis revealed that cardio-oncology comorbidity risk was elevated among individuals with both frailty and depressive symptoms by 80% in CHARLS, 57% in ELSA, and 47% in HRS compared to those with neither condition. Concurrent frailty and depressive symptoms constitute the highest-risk phenotype for cardio-oncology comorbidity in community-dwelling older adults. These findings suggest that combined assessment of frailty and depressive symptoms may improve baseline risk stratification of cardio-oncology comorbidity.

The association between depressive symptoms and respiratory health remains inconclusive, with limited research exploring dynamic changes in overall and symptom-specific depression. This study aimed to investigate the relationship between depressive symptom trajectories and the risk of chronic lung diseases (CLDs) as well as pulmonary function. We used data from two prospective cohorts: the China Health and Retirement Longitudinal Study (CHARLS) and the Health and Retirement Study (HRS). Depressive symptoms were assessed using the 10-item and 8-item CES-D scales, respectively, at three time points (CHARLS: wave1-3; HRS: wave 5-7), and classified into five trajectories: consistently low, decreasing, fluctuating, increasing, and consistently high. Incident CLDs were identified by self-reported physician diagnoses (CHARLS: wave 4-5; HRS: wave 8-12), and pulmonary function was evaluated by peak expiratory flow (PEF, CHARLS: wave 3; HRS: wave 8). Cox proportional hazards and linear regression models were used to estimate hazard ratios (HRs), beta coefficients (β), and 95% confidence intervals (CIs), adjusting for potential confounders. At baseline, individuals with depressive symptoms had a higher risk of Incident CLDs and lower PEF values. Compared to the consistently low group, the fluctuating (CHARLS: HR = 1.56, 95% CI: 1.33, 1.84; HRS: HR = 1.52, 95% CI: 1.30, 1.77), increasing (CHARLS: HR = 2.39, 95% CI: 1.86, 3.07; HRS: HR = 1.62, 95% CI: 1.13, 2.31), and consistently high (CHARLS: HR = 2.59, 95% CI: 2.16, 3.11; HRS: HR = 1.66, 95% CI: 1.30, 2.13) trajectories were associated with significantly increased CLDs risk. These trajectories were also significantly associated with lower PEF. The decreasing trajectory showed no significant association with CLDs risk or PEF. Total and somatic depressive symptoms demonstrated stronger associations with adverse respiratory outcomes. Depressive symptom trajectories characterized by fluctuation, increase, or persistent elevation are associated with higher CLDs risk and poorer pulmonary function. In contrast, symptom remission appears unrelated to respiratory outcomes. Total and somatic symptoms may serve as more sensitive indicators for predicting respiratory health.

The Developmental Origins of Health and Disease hypothesis proposes that insults to early-life development can result in increased risk for aging-related disease later in life. There is growing interest within gerontology in the potential role such early life exposures play in shaping processes of aging. However, causal research linking early-life exposures to processes of aging in later life is rare. Moreover, there are difficulties in distinguishing the impacts of exposures occurring at different stages of early life development. In this study, we build on a quasi-natural experiment design we developed that leverages state-year variation in economic shocks during the Great Depression to examine the causal effect of environmental exposure in early life on aging outcomes in the US Health and Retirement Study (HRS) (2022 PNAS). Our design allows us to distinguish effects of exposure during different periods of early life development – in-utero, in the first year of life, and later in childhood. In the present study, we apply this framework specifically to study impacts of early-life exposure to the Great Depression on pace of aging in later life. We measure pace of aging using repeated-measures longitudinal functional test and biomarker data and, in parallel, a single-timepoint blood-DNA methylation assessment of the DunedinPACE epigenetic clock through the 2016 HRS assessment wave. We further examine whether impacts of the Great Depression on the pace of aging translate into differences in morbidity and mortality through 2020.

Major life events trigger change processes in mental health. We examined how depressive symptoms change in conjunction with cancer diagnosis during adulthood and old age, and whether sociodemographic variables, cognitive and health resources, and cancer-specific mortality risks moderate event-related reaction and adaptation. Specifically, we applied multiphase growth models to prospective longitudinal data from 2,848 participants (age at diagnosis: M = 69, SD = 9.91; 46% women) in the Health and Retirement Study (HRS) who reported receiving a cancer diagnosis while enrolled in the study. On average, individuals experienced a significant increase in depressive symptoms within 2 years of cancer diagnosis, still-elevated levels 2 years postdiagnosis, and smaller increases in depressive symptoms postdiagnosis relative to the increases observed prediagnosis. Better memory and lower cancer-specific mortality risks were protective against increases in depressive symptoms within 2 years of diagnosis and were associated with reporting fewer depressive symptoms 2 years postdiagnosis. Findings suggest that diagnosis-related changes in depressive symptoms are typically characterized by a multiphase pattern, but tremendous between-person differences also emerged within each phase. Follow-up analyses comparing a matched group (N = 2,272) who did not experience cancer provided an additional layer of evidence supporting our inferences. Results indicate that, on average, people adapt and adjust to the challenges accompanying a cancer diagnosis, and illustrate the utility of using natural experiments such as major life events as a paradigm for studying developmental change processes.

We examined whether veteran status was associated with elevated depression and anxiety symptoms in men aged 50 and older after adjusting for sociodemographic factors. Participants were 6577 men aged 50 years and older who completed the 2006 wave of the Health and Retirement Study (HRS). Forty-nine percent of participants were veterans. A randomly selected subset of participants completed the HRS Psychosocial Questionnaire (N = 2957), which contained the anxiety items. Elevated depression and anxiety symptoms were determined based on brief versions of Center for Epidemiologic Studies--Depression Scale (CES-D total score ≥ 4) and Beck Anxiety Inventory (BAI total score ≥ 12). Elevated depression and anxiety symptoms were found in 11.0 and 9.9% of veterans, respectively, compared with 12.8 and 12.3% of non-veterans. Veteran status was not associated with increased odds of anxiety or depression symptoms in the multivariable-adjusted logistic regression analyses. Additional analyses indicated that Vietnam War veterans were more than twice as likely as World War II or Korean War veterans to have elevated depression symptoms (OR = 2.15, 95% CI: 1.54-3.00) or anxiety symptoms (OR = 2.12, 95% CI: 1.28-3.51). In a community-based sample of men aged 50 and older, veteran status was not associated with the presence of elevated depression and anxiety symptoms. Rather, these symptoms were associated with age, ethnicity, education, and medical conditions. Among veterans, cohort effects accounted for differences in psychiatric symptoms. Including younger cohorts from the Global War on Terror may yield different results in future studies.

Depression is highly prevalent among older adults and has consistently been identified as an independent risk factor for incident stroke. Most previous cohort studies have relied on a single baseline measure of depressive symptoms. However, accumulating evidence suggests that the dynamic progression of depression - its persistence, remission, or emergence over time - may differentially affect cerebrovascular risk. Furthermore, existing research has predominantly been limited to individual national cohorts, thereby restricting the generalizability of findings across diverse sociocultural and healthcare contexts. To address these limitations, we analyzed depressive symptom trajectories over multiple waves and their association with subsequent stroke onset in three large, prospective aging cohorts: the Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA), and the China Health and Retirement Longitudinal Study (CHARLS). In this study, depressive symptoms were evaluated biennially using the Center for Epidemiologic Studies Depression Scale (CES-D) for participants in HRS and ELSA and CHARLS. Through rule-based trajectory modeling, four distinct patterns of symptom burden trajectory were identified: no, decreasing, increasing, and consistently high. Stroke events were ascertained via self-reported physician diagnosis in HRS and ELSA, and through medical record linkage in CHARLS. For each cohort, logistic regression models were applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for stroke risk across the trajectory groups, using the persistent low group as the reference. The models were adjusted for potential confounders, including demographic variables, health behaviors, and history of chronic disorders. Furthermore, stratified analyses were performed across subgroups to explore potential heterogeneity in the associations between depressive symptom trajectories and stroke risk. The study included 4587 participants from HRS, 4879 from ELSA, and 7792 from CHARLS. During the follow-up period, there were 376, 137, and 133 incident strokes reported in the HRS, ELSA, and CHARLS cohorts, respectively. The "Consistently high" depressive-symptom trajectory was associated with a significantly increased risk of stroke across all three cohorts (CHARLS: OR 2.56, 95% CI: 1.62-4.04; ELSA: OR 2.96, 95% CI: 1.28-6.84; HRS: OR 1.56, 95% CI: 1.03-2.36) compared to the "No" group. The "decreasing" trajectory did not show a significant association with stroke, whereas the "increasing" trajectory was linked to a moderate elevation in stroke risk in the ELSA and HRS cohorts. Older adults exhibiting persistently high or increasing depressive symptoms are at a significantly elevated risk of stroke. Continuous monitoring and early intervention targeting these high-risk depression trajectories may offer a novel strategy for primary stroke prevention.

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study

ObjectiveChronic pain and depression are common in older adults, yet pain is dynamic and may follow distinct longitudinal courses. This study examined whether chronic pain trajectories are associated with incident depressive symptoms among adults aged 50 years and older.MethodsAnalyzed were two prospective cohorts of community-dwelling adults: the English Longitudinal Study of Ageing (ELSA) and the US Health and Retirement Study (HRS). Biennial self-reported pain (yes/no) across four waves was used to classify five mutually exclusive pain trajectories: no pain, decreasing pain, fluctuating pain, increasing pain, and consistent pain. Participants with depressive symptoms at baseline were excluded. Incident depressive symptoms were defined as a Center for Epidemiologic Studies Depression scale (CESD-8) score ≥3. Cox proportional hazards models estimated hazard ratios (HRs) adjusted for sociodemographic characteristics, health behaviors, and chronic conditions.ResultsThe analytic samples included 2476 participants in ELSA and 6238 in HRS, with a mean follow-up of 6.3 years and 6.1 years, respectively; incident depressive symptoms occurred in 19.7% and 18.3%, respectively. Compared with the no-pain trajectory, fluctuating, increasing, and consistent pain were associated with higher risk of depressive symptoms in ELSA (HRs, 1.70 [95% CI, 1.37-2.10], 1.76 [95% CI, 1.27-2.45], and 2.60 [95% CI, 1.98-3.43], respectively) and HRS (HRs, 1.48 [95% CI, 1.29-1.71], 1.84 [95% CI, 1.47-2.29], and 2.15 [95% CI, 1.78-2.59], respectively). Decreasing pain was not significantly associated with risk in either cohort.ConclusionsPersistent or worsening pain trajectories were consistently predicted subsequent depressive symptoms in older adults, whereas improving pain was not. Longitudinal pain monitoring may help identify high-risk individuals through earlier depression screening, along with integrated pain-mental health care.

ObjectiveNot known is whether relative fat mass (RFM)-a height- and waist-based estimator of total adiposity-predicts late-life depressive symptoms better than conventional anthropometrics.MethodsThis study analyzed harmonized data from two nationally representative aging cohorts: the English Longitudinal Study of Ageing (ELSA) and the US Health and Retirement Study (HRS). Adults ≥50years without baseline depressive symptoms (CES-D-8 <3) and with valid anthropometrics and covariates were followed biennially for up to 14years (ELSA n = 4176; HRS n = 5054). RFM was computed from measured height and waist circumference and examined continuously (each 1-standard deviation [SD] increase) and by tertiles. Incident depressive symptoms were defined as CES-D-8 ≥3 at follow-up. Cox models estimated hazard ratios (HR) with progressive adjustment. Dose-response was assessed using restricted cubic splines. Predictive performance was compared with body mass index (BMI) and waist circumference (WC) via time-dependent AUCs. Sensitivity analyses used multiple imputation and propensity-score matching.ResultsOver a mean of 8.60years (ELSA) and 8.57years (HRS), 1467 and 1769 participants developed incident depressive symptoms. Higher baseline RFM predicted incident depressive symptoms in both cohorts (for each 1-SD, Model 3: ELSA HR = 1.15, 95% CI = 1.06-1.25; HRS HR = 1.10, 95% CI = 1.05-1.16). Compared with low RFM, high RFM remained associated with higher risk (ELSA HR = 1.37, 95% CI = 1.12-1.67; HRS HR = 1.29, 95% CI = 1.14-1.46). Restricted cubic splines suggested a J-shaped association. Time-dependent AUCs showed RFM consistently outperformed BMI and WC across follow-up. Findings were robust in multiple imputation and propensity-matched analyses.ConclusionsIn two national cohorts of older adults, higher RFM was prospectively associated with incident depressive symptoms and demonstrated superior time-varying discrimination compared with BMI and WC, supporting RFM as a pragmatic tool for late-life depressive symptoms risk stratification.

BackgroundSocial participation and digital use are associated with reduced depression risk among older adults, but most supporting evidence does not consider both time-invariant and time-varying confounders and is inconsistent. We aimed to evaluate the impact of social participation and digital use on the incidence of depressive symptoms among older adults by a multi-country cohort considering both time-invariant and time-varying counfounders.MethodsWe used data from four nationally representative observational studies across 18 countries (2008–2021): the Health and Retirement Study (HRS), the Survey of Health, Aging and Retirement in Europe (SHARE), the China Health and Retirement Longitudinal Study (CHARLS), and the Mexican Health and Aging Study (MHAS). Participants aged 50 years or older without depressive symptoms at baseline and without related behaviors pre-baseline were included. Interested exposure social participation and digital use were measured by specific questions. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and the European Depression Scale (EURO-D). Targeted maximum likelihood estimation method was applied to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) for the long-term impact of exposure on depressive symptoms onset.ResultsA total of 69,186 eligible participants were included. At baseline, 77.0%, 44.0%, 34.2%, and 49.8% of participants were exposed to social participation in HRS, SHARE, CHARLS, and MHAS, respectively, and these proportions were 55.7%, 55.9%, 4.5%, and 69.9% for digital use exposure. During follow-up, a total of 18,245 (26.4%) individuals developed depressive symptoms. The RRs (95% CI) of depression risk under social participation versus no social participation were 0.80 (0.68–0.93) in HRS, 0.80 (0.74–0.87) in SHARE, 0.86 (0.77–0.96) in CHARLS, and 0.93 (0.85–1.02) in MHAS. Compared with no digital use, the RRs (95% CI) of depression risk under digital use were 0.88 (0.72–1.08) in HRS, 0.85 (0.77–0.93) in SHARE, 0.75 (0.60–0.92) in CHARLS, and 0.88 (0.79–0.98) in MHAS.ConclusionsEngagement in social participation and digital use are associated with a reduced incidence of depressive symptoms in older adults. In the digital world, besides social participation, promoting digital use for social connection may be an effective strategy for depression prevention in ageing populations.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12916-026-04846-4.

We evaluated the effectiveness of the US Health and Retirement Study (HRS) in representing middle-aged and older cancer survivors by comparing individual- and county-level characteristics with those of a comparable cohort in Surveillance, Epidemiology, and End Results (SEER). We identified incident cancer survivors aged ≥ 50years in the HRS and SEER biennially from 2000 to 2020. We calculated proportions of individual- level and county-level sociodemographic attributes for the sampling-weighted HRS and SEER. We calculated the standardized differences (SD) between the HRS and SEER, with an SD of ≥ 0.1 indicating a meaningful difference. Cancer survivors in the HRS and SEER had similar sociodemographic characteristics, with some exceptions. Across most years, the HRS had a lower proportion of cancer survivors in the younger baseline age group (e.g., in 2020, 1.3% in HRS vs. 7.4% in SEER for ages 50-54), but a higher proportion of non-Hispanic White (e.g., in 2020, 75.7% in HRS, 68.3% in SEER), and married (e.g., in 2020, 59.5% in HRS, 53.2% in SEER), all with SD ≥ 0.1. The general populations of their data collection areas were similar, while the HRS over-represented counties with a higher proportion of Hispanic residents. The sociodemographic profiles of middle-aged and older cancer survivors in the HRS and SEER were similar, with some minor exceptions, reflecting their distinct objectives and data collection methodologies. Understanding the comparability between HRS and SEER is crucial for ensuring that HRS data can reliably inform cancer survivorship research across the US population while providing additional longitudinal aging and covariates data.

Total, somatic, and cognitive-affective depressive symptoms trajectories and urinary incontinence: Evidence from two national longitudinal cohorts.