Introduction: Cognitive reserve (CR) describes individual differences in susceptibility to brain damage that translates into varying dementia onsets and may also influence the occurrence of depressive symptoms. Within a population-based cohort of older people, we investigated two operationalizations of CR, residual- and activity-based approaches, in their association with the development of depressive symptoms.

Methods: We analyzed longitudinal data on 402 dementia- and depression-free adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) who underwent brain MRI at baseline. Residual-based reserve was derived by regressing episodic memory on a brain-integrity index incorporating six structural MRI markers. Activity-based reserve factored lifelong CR-enhancing experiences, including education, work complexity, social network, and leisure activities. Clinically relevant depressive symptoms were defined as a Montgomery–Åsberg Depression Rating Scale score >6. Cox hazard models were used to explore the association between both residual- and activity-based CR measures (categorized in tertiles) and incidence of depressive symptoms over a 15-year follow-up, while accounting for sociodemographic, clinical, behavioral factors, and brain integrity. Analyses for the activity-based measure were replicated in the full SNAC-K sample (N = 2709), further exploring depression diagnosis as additional outcome.

Results: Compared to low levels, higher levels of residual-based CR were associated with a lower hazard of depressive symptom onset in fully adjusted models (HR: .43, 95%CI .22, .84). While activity-based CR was not significantly associated with developing depressive symptoms in the MRI subsample (HRhigh .47, 95%CI .21, 1.04), it was in the full sample (HRhigh .52, 95%CI .39, .71). Activity-based CR was further associated with depression diagnoses in the full sample (HRhigh: .45, 95%CI .31, .65).

Discussion: Largely independent of its measurement, CR appears to influence depressive symptomatology in late life. Reserve-enhancing initiatives may be beneficial not only for cognitive but also for mental health in older people.

INTRODUCTION: We investigated the association of cognitive reserve (CR) with transitions across cognitive states and death. METHODS: This population-based cohort study included 2631 participants (age ≥60 years) who were dementia-free at baseline and regularly examined up to 15 years. Data were analyzed using the Markov multistate models. RESULTS: Each 1-point increase in the composite CR score (range: -4.25 to 3.46) was significantly associated with lower risks of transition from normal cognition to cognitive impairment, no dementia (CIND) (multivariable-adjusted hazards ratio = 0.78; 95% confidence interval = 0.72–0.85) and death (0.85; 0.79–0.93), and from CIND to death (0.82; 0.73–0.91), but not from CIND to normal cognition or dementia. A greater composite CR score was associated with a lower risk of transition from CIND to death in people aged 60-72 but not in those aged ≥ 78 years. DISCUSSION: CR contributes to cognitive health by delaying cognitive deterioration in the prodromal phase of dementia. Highlights: We use Markov multistate model to examine the association between cognitive reserve and transitions across cognitive states and death. A great cognitive reserve contributes to cognitive health by delaying cognitive deterioration in the prodromal phase of dementia. A great cognitive reserve is associated with a lower risk of transition from cognitive impairment, no dementia to death in people at the early stage of old age, but not in those at the late stage of old age.

Background: Early growth, stress, and socioeconomic factors are associated with future risk of individual chronic diseases. It is uncertain whether they also affect the rate of multimorbidity accumulation later in life. This study aimed to explore whether early life factors are associated with the rate at which chronic diseases are accumulated across older age.

Methods: In this national birth cohort study, we studied people born at Helsinki University Central Hospital, Helsinki, Finland between Jan 1, 1934, and Dec 31, 1944, who attended child welfare clinics in the city, and were living in Finland in 1971. Individuals who had died or emigrated from Finland before 1987 were excluded, alongside participants without any registry data and who died before the end of the registry follow-up on Dec 31, 2017. Early anthropometry, growth, wartime parental separation, and socioeconomic factors were recorded from birth, child welfare clinic, or school health-care records, and Finnish National Archives. International Classification of Diseases codes of diagnoses for chronic diseases were obtained from the Care Register for Health Care starting from 1987 (when participants were aged 42-53 years) until 2017. Linear mixed models were used to study the association between early-life factors and the rate of change in the number of chronic diseases over 10-year periods.

Findings: From Jan 1, 1934, to Dec 31, 2017, 11 689 people (6064 [51 center dot 9%] men and 5625 [48 center dot 1%] women) were included in the study. Individuals born to mothers younger than 25 years (beta 0 center dot 09; 95% CI 0 center dot 06-0 center dot 12), mothers with a BMI of 25-30 kg/m2 (0 center dot 08; 0 center dot 05-0 center dot 10), and mothers with a BMI more than 30 kg/m2 (0 center dot 26; 0 center dot 21-0 center dot 31) in late pregnancy accumulated chronic diseases faster than those born to older mothers (25-30 years) and those with a BMI of less than 25 kg/m2. Individuals with a birthweight less than 2 center dot 5 kg (0 center dot 17; 0 center dot 10-0 center dot 25) and those with a rapid growth in height and weight from birth until age 11 years accumulated chronic diseases faster during their life course. Additionally, paternal occupational class (manual workers vs upper-middle class 0 center dot 27; 0 center dot 23-0 center dot 30) and wartime parental separation (0 center dot 24; 0 center dot 19-0 center dot 29 for boys; 0 center dot 31; 0 center dot 25-0 center dot 36 for girls) were associated with a faster rate of chronic disease accumulation. Interpretation Our findings suggest that the foundation for accumulating chronic diseases is established early in life. Early interventions might be needed for vulnerable populations, including war evacuee children and children with lower socioeconomic status.

Background The longitudinal course of late-life depression remains understudied. Aims To describe transitions along the depression continuum in old age and to identify factors associated with specific transition patterns. Method We analysed 15-year longitudinal data on 2745 dementia-free persons aged 60+ from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression (minor and major) was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; subsyndromal depression (SSD) was operationalised as the presence of ≥2 symptoms without depression. Multistate survival models were used to map depression transitions, including death, and to examine the association of psychosocial (social network, connection and support), lifestyle (smoking, alcohol consumption and physical activity) and clinical (somatic disease count) factors with transition patterns. Results Over the follow-up, 19.1% had ≥1 transitions across depressive states, while 6.5% had ≥2. Each additional somatic disease was associated with a higher hazard of progression from no depression (No Dep) to SSD (hazard ratio 1.09; 1.07–1.10) and depression (Dep) (hazard ratio 1.06; 1.04–1.08), but also with a lower recovery (HRSSD−No Dep 0.95; 0.93–0.97 [where ‘HR’ refers to ‘hazard ratio’]; HRDep−No Dep 0.96; 0.93–0.99). Physical activity was associated with an increased hazard of recovery to no depression from SSD (hazard ratio 1.49; 1.28–1.73) and depression (hazard ratio 1.20; 1.00–1.44), while a richer social network was associated with both higher recovery from (HRSSD−No Dep 1.44; 1.26–1.66; HRDep−No Dep 1.51; 1.34–1.71) and lower progression hazards to a worse depressive state (HRNo Dep−SSD 0.81; 0.70–0.94; HRNo Dep−Dep 0.58; 0.46–0.73; HRSSD−Dep 0.66; 0.44–0.98). Conclusions Older people may present with heterogeneous depressive trajectories. Targeting the accumulation of somatic diseases and enhancing social interactions may be appropriate for both depression prevention and burden reduction, while promoting physical activity may primarily benefit recovery from depressive disorders.

Aims. Co-occurring somatic diseases exhibit complex clinical profiles, which can differentially impact the development of late-life depression. Within a community-based cohort, we aimed to explore the association between somatic disease burden, both in terms of the number of diseases and their patterns, and the incidence of depression in older people.

Methods. We analysed longitudinal data of depression- and dementia-free individuals aged 60+ years from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression diagnoses were clinically ascertained following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision over a 15-year follow-up. Somatic disease burden was assessed at baseline through a comprehensive list of chronic diseases obtained by combining information from clinical examinations, medication reviews and national registers and operationalized as (i) disease count and (ii) patterns of co-occurring diseases from latent class analysis. The association of somatic disease burden with depression incidence was investigated using Cox models, accounting for sociodemographic, lifestyle and clinical factors.

Results. The analytical sample comprised 2904 people (mean age, 73.2 [standard deviation (SD), 10.5]; female, 63.1%). Over the follow-up (mean length, 9.6 years [SD, 4 years]), 225 depression cases were detected. Each additional disease was associated with the occurrence of any depression in a dose–response manner (hazard ratio [HR], 1.16; 95% confidence interval [CI]: 1.08, 1.24). As for disease patterns, individuals presenting with sensory/anaemia (HR, 1.91; 95% CI: 1.03, 3.53), thyroid/musculoskeletal (HR, 1.90; 95% CI: 1.06, 3.39) and cardiometabolic (HR, 2.77; 95% CI: 1.40, 5.46) patterns exhibited with higher depression hazards, compared to those without 2+ diseases (multimorbidity). In the subsample of multimorbid individuals (85%), only the cardiometabolic pattern remained associated with a higher depression hazard compared to the unspecific pattern (HR, 1.71; 95% CI: 1.02, 2.84).

Conclusions. Both number and patterns of co-occurring somatic diseases are associated with an increased risk of late-life depression. Mental health should be closely monitored among older adults with high somatic burden, especially if affected by cardiometabolic multimorbidity.

Objective: Individual aspects of social health (SH; eg, network, engagement, support) have been linked to cognitive health. However, their combined effect and the role of the structural properties of the brain (brain reserve [BR]) remain unclear. We investigated the interplay of SH and BR on cognitive change in older adults.

Methods: Within the Swedish National Study on Aging and Care–Kungsholmen, 368 dementia-free adults aged ≥60 years with baseline brain magnetic resonance imaging were followed over 12 years to assess cognitive change. A measure of global cognition was computed at each of the 5 waves of assessment by averaging domain-specific Z scores for episodic memory, perceptual speed, semantic memory, and letter and category fluency. An SH composite score was computed at baseline by combining leisure activities and social network. BR was proxied by total brain tissue volume (TBTV). Linear mixed models (adjusted for sociodemographic, vascular, and genetic factors) were used to estimate cognitive trajectories in relation to SH and TBTV. Interaction analysis and stratification were used to examine the interplay between SH and TBTV.

Results: Moderate–good SH (n = 245; vs poor, β-slope = 0.01, 95% confidence interval [CI] = 0.002–0.02, p = 0.018) and moderate-to-large TBTV (n = 245; vs small, β-slope = 0.03, 95% CI = 0.02–0.04, p < 0.001) were separately associated with slower cognitive decline. In stratified analysis, moderate–good SH was associated with higher cognitive levels (but not change) only in participants with moderate-to-large TBTV (β-intercept = 0.21, 95% CI = 0.06–0.37, p < 0.01; interaction SH * TBTV, p < 0.05).

Interpretation: Our findings highlight the interplay between SH and BR that likely unfolds throughout the entire life course to shape old-age cognitive outcomes.

Background: the socioeconomic distribution of unplanned hospital admissions in older adults is poorly understood. We compared associations of two life-course measures of socioeconomic status (SES) with unplanned hospital admissions while comprehensively accounting for health, and examined the role of social network in this association.

Methods: in 2,862 community-dwelling adults aged 60+ in Sweden, we derived (i) an aggregate life-course SES measure grouping individuals into Low, Middle or High SES based on a summative score, and (ii) a latent class measure that additionally identified a Mixed SES group, characterised by financial difficulties in childhood and old age. The health assessment combined measures of morbidity and functioning. The social network measure included social connections and support components. Negative binomial models estimated the change in hospital admissions over 4 years in relation to SES. Stratification and statistical interaction assessed effect modification by social network.

Results: adjusting for health and social network, unplanned hospitalisation rates were higher for the latent Low SES and Mixed SES group (incidence rate ratio [IRR] = 1.38, 95% confidence interval [CI]: 1.12–1.69, P = 0.002; IRR = 2.06, 95% CI: 1.44–2.94, P < 0.001; respectively; ref: High SES). Mixed SES was at a substantially greater risk of unplanned hospital admissions among those with poor (and not rich) social network (IRR: 2.43, 95% CI: 1.44–4.07; ref: High SES), but the statistical interaction test was non-significant (P = 0.493).

Conclusion: socioeconomic distributions of older adults’ unplanned hospitalisations were largely driven by health, although considering SES dynamics across life can reveal at-risk sub-populations. Financially disadvantaged older adults might benefit from interventions aimed at improving their social network.

Background: Physical activity (PA) decreased during the COVID-19 pandemic, especially among older adults, potentially leading to adverse consequences for their health. However, factors associated with reductions of PA during the pandemic have not been examined in a population-based sample of older adults. Thus, the aim of this study was to explore the association of pre-pandemic physical, mental, social and lifestyle factors with reductions in PA in older adults during the first wave of COVID-19, and whether the associations differed by age and sex.

Methods: A population-based sample of 624 participants aged 65-99 years were identified from the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) COVID19 Study. Information on pre-pandemic factors was collected through clinical examinations, interviews, and self-administered questionnaires in 2016-2019. Changes in light and intense PA during the first wave of the pandemic (May-September 2020) were self-reported. Data were analyzed using multiple logistic regression models, stratified by age (<70 vs. >80 years) and sex.

Results: There was an association between pre-pandemic levels of higher depressive symptom burden (Odds Ratio (OR): 2.6, 95% Confidence Interval (CI): 1.1-6.4, <70 years), and impaired balance (OR: 1.7, 95% CI: 1.0-2.8, >80 years old) with reductions in light-intensity PA. Furthermore, the presence of musculoskeletal disease (OR: 1.8, 95% CI: 1.1-2.9, <70 years; OR: 2.3, 95% CI: 1.2-4.4, men), moderate/high levels of neuroticism (OR: 1.6, 95% CI: 1.0-2.6, <70 years; OR: 2.2, 95% CI: 1.3-3.5, women), and poor levels of social support (OR: 2.2, 95% CI: 1.2-4.3, >80 years) were related to reductions in higher-intensity PA. Those who were current smokers (OR: 0.3, 95% CI: 0.1-0.8, <70 years; OR: 0.2, 95% CI: 0.06-0.7, women), or had impaired balance (OR: 0.4, 95% CI: 0.2-0.8, >80 years) were less likely to reduce their levels of higher-intensity PA.

Conclusions: For future pandemics or waves of COVID-19, development of strategies is warranted for older individuals with psychiatric- or physical illness/dysfunction, as well as those with poor social support to counteract reductions in physical activities.

Background and Objectives: The coronavirus disease 2019 (COVID-19) pandemic, as well as the measures intended to limit its spread, have likely affected older adults’ depressive burden. Good physical functioning and a rich social network may benefit older adults’ mental health. We examined whether pre-pandemic physical functioning and social network were associated with depressive burden during the first wave of the COVID-19 pandemic in Stockholm, Sweden.

Research Design and Methods: A telephone assessment of depressive burden using the symptoms of sadness, anxiety, worrying, reduced sleep, and reduced appetite was conducted in May–September 2020 in 930 older adults from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K), an ongoing population-based study. Objective measures of gait speed, muscle strength, and balance; and self-reports of social connections and support were collected in 2016–2019. Logistic models were adjusted for sociodemographic, clinical, lifestyle, and pandemic-related factors (loneliness, change in physical and social engagement, and experience of death due to COVID-19).

Results: Only good muscle strength (odds ratio [OR]: 0.53; 95% confidence interval [CI]: 0.32–0.85; ref: poor strength, ≥17 s) and rich social support (OR: 0.67; 95% CI: 0.45–0.99; ref: poor support) exhibited an independent association with depressive burden, even after accounting for pandemic-related factors. A combination of good muscle strength and rich social support were associated with the greatest reduction in depressive burden (OR: 0.35; 95% CI: 0.18–0.66; ref: poor social support and poor muscle strength).

Discussion and Implications: Prepandemic social support and muscle strength could supply older adults with resilience against the depressive burden associated with the COVID-19 pandemic.

Introduction: Successful aging is a multidimensional construct covering behavioral, social, and psychological domains of well-being. We aimed to identify well-being profiles and their association with mobility-limitation-free survival.

Methods: A total of 1488 healthy individuals aged 60+ from the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) were followed-up for 15 years. Mobility limitation was defined as a walking speed <0.8m/s and vital status information was obtained from the National Cause of Death Register. Well-being profiles were derived from different behavioral, social and psychological indicators using latent class analysis among men and women. Cox and Laplace regression models were applied to examine the association with the incidence of a composite endpoint of mobility limitation or death.

Results: At baseline, three well-being profiles (i.e., worst, intermediate, best) were identified, which followed a clear gradient in all behavioral, social and psychological indicators. Compared to those in the worst profile, men and women in the intermediate profile had 27% (HR 0.73; 95% CI 0.56-0.94) and 23% (HR 0.77; 95% CI 0.59-1.00) lower hazard of developing mobility limitation/death. An even greater protective effect was seen among individuals in the best versus worst profile (HR 0.47; 95% CI 0.31-0.70 in men; HR 0.60; 95% CI 0.46-0.78 in women). Men in the intermediate and best profiles survived 1 and 3 years longer without mobility limitation, respectively; these figures were 2 and 3 years for women.

Conclusions: Better profiles of behavioral, social and psychological well-being may prolong mobility-limitation-free survival by at least one year among older adults. Our findings strengthen the evidence-base to achieve successful aging through multi-domain interventions.