Association between neighbourhood cohesion and physical activity trajectories during the COVID-19 pandemic using data from Understanding Society: The UK Household Longitudinal Study & COVID-19 sub-study.

Neighbourhood cohesion is increasingly recognised as a key determinant of health and health-related behaviours. Positive association between social support and physical activity have been demonstrated on an interpersonal level, there is less evidence at group-level. This study aimed to examine the association between neighbourhood cohesion and physical activity trajectories during the COVID-19 pandemic. Hypothesizing that higher neighbourhood cohesion was a protective factor against reduced physical activity during the pandemic. Data from Understand Society (wave 9, Jan 2017-Dec 2019), and the COVID-19 sub-study (waves 1, 5, 7) was used. Participants (N = 14,475) had baseline data and at least one Covid physical activity measure. We used linear mixed models with a random intercept and slope at the individual level and an unstructured correlation matrix to examine the association between neighbourhood cohesion and physical activity during the follow-up period. We found a significant reduction in physical activity (-441 MET-min/wk, (CI 374.51 - 507.65, p < 0.001) through the COVID-19 pandemic, and that higher neighbourhood cohesion was related to higher physical activity after control for covariates. There was a significant difference between neighbourhood cohesion categories and change seen in PA during the 39-month follow-up period (difference in change between lowest and highest neighbourhood cohesion categories = 373 MET-min/wk, p = 0.036), higher neighbourhood cohesion had a protective effect. Strong relationships between public health and urban planning sectors are needed to build communities with structures in place to support a sense of community, social interaction and attraction to the neighbourhood. This will help long-term neighbourhood cohesion and support increased physical activity.

Joint associations of physical activity and sleep duration with cognitive ageing: longitudinal analysis of an English cohort study.

BACKGROUND: Physical activity and sleep duration are key factors associated with cognitive function and dementia risk. How physical activity and sleep interact to influence cognitive ageing is not well explored. We aimed to examine the associations of combinations of physical activity and sleep duration with 10-year cognitive trajectories. METHODS: In this longitudinal study, we analysed data from the English Longitudinal Study of Ageing collected between Jan 1, 2008, and July 31, 2019, with follow-up interviews every 2 years. Participants were cognitively healthy adults aged at least 50 years at baseline. Participants were asked about physical activity and nightly sleep duration at baseline. At each interview, episodic memory was assessed using immediate and delayed recall tasks and verbal fluency using an animal naming task; scores were standardised and averaged to produce a composite cognitive score. We used linear mixed models to examine independent and joint associations of physical activity (lower physical activity or higher physical activity, based on a score taking into account frequency and intensity of physical activity) and sleep duration (short [<6 h], optimal [6-8 h], or long [>8 h]) with cognitive performance at baseline, after 10 years of follow-up, and the rate of cognitive decline. FINDINGS: We included 8958 respondents aged 50-95 years at baseline (median follow-up 10 years [IQR 2-10]). Lower physical activity and suboptimal sleep were independently associated with worse cognitive performance; short sleep was also associated with faster cognitive decline. At baseline, participants with higher physical activity and optimal sleep had higher cognitive scores than all combinations of lower physical activity and sleep categories (eg, difference between those with higher physical activity and optimal sleep vs those with lower physical activity and short sleep at baseline age 50 years was 0·14 SDs [95% CI 0·05-0·24]). We found no difference in baseline cognitive performance between sleep categories within the higher physical activity category. Those with higher physical activity and short sleep had faster rates of cognitive decline than those with higher physical activity and optimal sleep, such that their scores at 10 years were commensurate with those who reported low physical activity, regardless of sleep duration (eg, difference in cognitive performance after 10 years of follow-up between those with higher physical and optimal sleep and those with lower physical activity and short sleep was 0·20 SDs [0·08-0·33]; difference between those with higher physical activity and optimal sleep and those with lower physical activity and short sleep was 0·22 SDs [0·11-0·34]). INTERPRETATION: The baseline cognitive benefit associated with more frequent, higher intensity physical activity was insufficient to ameliorate the more rapid cognitive decline associated with short sleep. Physical activity interventions should also consider sleep habits to maximise benefis of physical activity for long-term cognitive health. FUNDING: UK Economic and Social Research Council.

Comparison of sex differences in cognitive function in older adults between high- and middle-income countries and the role of education: a population-based multicohort study.

BACKGROUND: The extent to which education explains variations in sex differences in cognitive function between countries at different levels of economic development is unknown. We examined the role of education in sex differences in four cognitive domains in high- and middle-income countries. METHODS: Analyses were based on 70,846 participants, aged 60 years and older, in cohort studies from a high-income (United States) and four middle-income countries (Mexico, Brazil, China, and India). We used weighted linear models to allow nationally-representative comparisons of sex differences in orientation, memory, attention, and fluency using the United States as the reference, before and after adjustment for education, and after stratification by education. RESULTS: Females had lower levels of education than males in all countries, particularly in India. Before adjustment for education, sex differences in orientation and attention in all middle-income countries, memory in Brazil, China, and India, and fluency in India were less favourable to females than in the United States (P < 0.010). For example, females outperformed males in memory in the United States (mean difference [male-female scores] = -0.26 standard deviations [95% CI -0.30, -0.22]) but not in China (0.15 [0.09, 0.21]) or India (0.16 [0.13, 0.19]). Adjustment for education attenuated these sex differences. In analyses stratified by education, there were minimal sex differences in the high education group in all countries. CONCLUSION: Education contributes to larger female disadvantages in cognitive function at older ages in middle-income countries compared with the United States. Gender equity in education is an important target to reduce sex disparities in cognitive function globally.

Identification of physical activity and sedentary behaviour dimensions that predict mortality risk in older adults: Development of a machine learning model in the Whitehall II accelerometer sub-study and external validation in the CoLaus study.

Background: Identification of new physical activity (PA) and sedentary behaviour (SB) features relevant for health at older age is important to diversify PA targets in guidelines, as older adults rarely adhere to current recommendations focusing on total duration. We aimed to identify accelerometer-derived dimensions of movement behaviours that predict mortality risk in older populations. Methods: We used data on 21 accelerometer-derived features of daily movement behaviours in 3991 participants of the UK-based Whitehall II accelerometer sub-study (25.8% women, 60-83 years, follow-up: 2012-2013 to 2021, mean = 8.3 years). A machine-learning procedure was used to identify core PA and SB features predicting mortality risk and derive a composite score. We estimated the added predictive value of the score compared to traditional sociodemographic, behavioural, and health-related risk factors. External validation in the Switzerland-based CoLaus study (N = 1329, 56.7% women, 60-86 years, follow-up: 2014-2017 to 2021, mean = 3.8 years) was conducted. Findings: In total, 11 features related to overall activity level, intensity distribution, bouts duration, frequency, and total duration of PA and SB, were identified as predictors of mortality in older adults and included in a composite score. Both in the derivation and validation cohorts, the score was associated with mortality (hazard ratio = 1.10 (95% confidence interval = 1.05-1.15) and 1.18 (1.10-1.26), respectively) and improved the predictive value of a model including traditional risk factors (increase in C-index = 0.007 (0.002-0.014) and 0.029 (0.002-0.055), respectively). Interpretation: The identified accelerometer-derived PA and SB features, beyond the currently recommended total duration, might be useful for screening of older adults at higher mortality risk and for diversifying PA and SB targets in older populations whose adherence to current guidelines is low. Funding: National Institute on Aging; UK Medical Research Council; British Heart Foundation; Wellcome Trust; French National Research Agency; GlaxoSmithKline; Lausanne Faculty of Biology and Medicine; Swiss National Science Foundation.

Trajectories of physical and mental functioning over 25 years before onset of frailty: results from the Whitehall II cohort study.

BACKGROUND: Research on frailty, a major contributor to heterogeneity in health, is undertaken on older adults although the processes leading to frailty are likely to begin earlier in the life course. Using repeat data spanning 25 years, we examined changes in physical and mental functioning before the onset of frailty, defined using Fried's frailty phenotype (FFP). METHODS: Functioning was measured using the Short-Form 36 General Health Survey (SF-36) on nine occasions from 1991 (age range 40-63 years) to 2015 (age range 63-85 years). The poorest of four FFP scores from 2002, 2007, 2012 and 2015 was used to classify participants as frail, pre-frail, or robust. We used linear mixed models with a backward timescale such that time 0 was the person-specific date of frailty classification for frail and pre-frail participants and the end of follow-up for robust participants. Analyses adjusted for socio-demographic factors, health behaviours, body mass index and multi-morbidity status were used to compare SF-36 physical (PCS) and mental (MCS) component summary scores over 25 years before time 0 as a function of FFP classification, with estimates extracted at time 0, -5, -10, -15, -20 and -25 years. We also used illness-death models to examine the prospective association between SF-36 component summary scores at age 50 and incident FFP-defined frailty. RESULTS: Among 7044 participants of the Whitehall II cohort study included in the analysis [29% female, mean age 49.7 (SD = 6.0) at baseline in 1991], 2055 (29%) participants remained robust, and 4476 (64%) became pre-frail and 513 (7%) frail during follow-up. Frail compared with robust participants had lower SF-36 scores at t = -25 before onset of frailty with a difference of 3.4 [95% confidence interval (CI) 1.6, 5.1] in PCS and 1.8 (-0.2, 3.8) in MCS. At t = 0, the differences increased to 11.5 (10.5, 12.5) and 9.1 (8.0, 10.2), respectively. The differences in SF-36 between the robust and pre-frail groups, although smaller [at t = 0, 1.7 (1.2, 2.2) in PCS and 4.0 (3.4, 4.5) in MCS], were already observed 20 and 25 years, respectively, before the onset of pre-frailty. Prospective analyses showed that at age 50, scores in the bottom quartiles of PCS [hazard ratio (HR) compared with the top quartile = 2.39, 95% CI 1.85, 3.07] and MCS [HR = 1.49 (1.15, 1.93)] were associated with a higher risk of FFP-defined frailty at older ages. CONCLUSIONS: Differences in trajectories of physical and mental functioning in individuals who developed physical frailty at older ages were observable 25 years before onset of FFP-defined frailty. These findings highlight the need for a life course approach in efforts to prevent frailty.

Pre-stroke Disability and Long-Term Functional Limitations in Stroke Survivors: Findings From More of 12 Years of Follow-Up Across Three International Surveys of Aging.

Background: Almost 50% of the post-stroke disabled population already have a premorbid disability before stroke. These patients may be offered a different care pathway in the acute and subacute phase than those without pre-morbid disability. Therefore, the aim of this study was to assess the association of the severity of premorbid disability with change of limitations in basic and instrumental activities of daily living (ADL/IADL) 1 year after stroke and over the following decade. Methods: Among 3,432 participants from HRS, SHARE and ELSA cohorts with a first stroke, ADL/IADL limitations were measured at 1-2 years prior to stroke, at 1 year post-stroke, and during the chronic phase. Modified Ranking Scale (P-mRS) was used to categorize the participants by level of premorbid disability (1-2 years pre-stroke). Change in ADL/IADL limitations by P-mRS level (0-1, 2-3, and 4-5) was assessed using a piecewise linear mixed model with a breakpoint set at 1 year post-stroke, stratified by median age groups. Results: Increase in ADL limitations at 1 year post-stroke was less pronounced in P-mRS ≥2 (p < 0.005). After years of relative stability, limitations of ADL increased for all P-mRS levels (p = 0.003). In those aged ≥75 years at stroke event, the increase was similar irrespective of P-mRS (p = 0.090). There were no significant differences in IADL trajectories between P-mRS levels (p ≥ 0.127). Conclusion: These results suggest similar trajectories of functional limitations between P-mRS levels up to 9 years post-stroke, highlighting the possible benefit of including patients with pre-morbid disability to certain treatments during the acute phase.

Individual Barriers to an Active Lifestyle at Older Ages Among Whitehall II Study Participants After 20 Years of Follow-up.

Importance: Identification of individual-level barriers associated with decreased activity in older age is essential to inform effective strategies for preventing the health outcomes associated with high sedentary behavior and lack of physical activity during aging. Objective: To assess cross-sectional and prospective associations of a large set of factors with objectively assessed sedentary time and physical activity at older age. Design, Setting, and Participants: This population-based cohort study was conducted among participants in the Whitehall II accelerometer substudy with accelerometer data assessed in 2012 to 2013. Among 4880 participants invited to the accelerometer substudy, 4006 individuals had valid accelerometer data. Among them, 3808 participants also had factors assessed in 1991 to 1993 (mean [SD] follow-up time, 20.3 [0.5] years), 3782 participants had factors assessed in 2002 to 2004 (mean [SD] follow-up time, 9.1 [0.3] years), and 3896 participants had factors assessed in 2012 to 2013 (mean follow up time, 0 years). Data were analyzed from May 2020 through July 2021. Exposures: Sociodemographic factors (ie, age, sex, race and ethnicity, occupational position, and marital status), behavioral factors (ie, smoking, alcohol intake, and fruit and vegetable intake), and health-related factors (ie, body mass index, 36-Item Short Form Health Survey (SF-36) physical and mental component summary scores [PCS and MCS], and number of chronic conditions) were assessed among 3808 individuals in 1991 to 1993; 3782 individuals in 2002 to 2004; and 3896 individuals in 2012 to 2013. High alcohol intake was defined as more than 14 units of alcohol per week, and high fruit and vegetable intake was defined as twice daily or more. Main Outcomes and Measures: Accelerometer-assessed time spent in sedentary behavior, light-intensity physical activity (LIPA), and moderate to vigorous physical activity (MVPA) in 2012 to 2013 were analyzed in 2021 using multivariate linear regressions. Results: A total of 3896 participants (986 [25.3%] women; age range, 60-83 years; mean [SD] age, 69.4 [5.7] years) had accelerometer data and exposure factors available in 2012 to 2013. Older age, not being married or cohabiting, having overweight, having obesity, more chronic conditions, and poorer SF-36 PCS, assessed in midlife or later life, were associated with increased sedentary time at the expense of time in physical activity. Mean time differences ranged from 9.8 min/d (95% CI, 4.1 to 15.6 min/d) of sedentary behavior per 10-point decrease in SF-36 PCS to 51.4 min/d (95% CI, 37.2 to65.7 min/d) of sedentary behavior for obesity vs reference range weight, from -6.2 min/d (95% CI, -8.4 to -4.1 min/d) of LIPA per 5 years of age to -28.0 min/d (95% CI, -38.6 to -17.4 min/d) of LIPA for obesity vs reference range weight, and from -5.3 min/d (95% CI, -8.2 to -2.4 min/d) of MVPA per new chronic condition to -23.4 min/d (95% CI, -29.2 to -17.6 min/d) of MVPA for obesity vs reference range weight in 20-year prospective analyses for men. There was also evidence of clustering of behavioral factors: high alcohol intake, high fruit and vegetable consumption, and no current smoking were associated with decreased sedentary time (mean time difference in cross-sectional analysis in men: -12.7 min/d [95% CI, -19.8 to -5.5 min/d]; -6.0 min/d [95% CI, -12.3 to -0.2]; and -37.4 min/d [95% CI, - 56.0 to -18.8 min/d], respectively) and more physical activity. Conclusions and Relevance: This study found a large range of individual-level barriers associated with a less active lifestyle in older age, including sociodemographic, behavioral, and health-related factors. These barriers were already evident in midlife, suggesting the importance of early implementation of targeted interventions to promote physical activity and reduce sedentary time.

Association between age at onset of multimorbidity and incidence of dementia: 30 year follow-up in Whitehall II prospective cohort study.

OBJECTIVE: To examine the association of midlife and late life multimorbidity, including severity of multimorbidity, with incident dementia. DESIGN: Prospective cohort study. SETTING: Civil service departments in London (Whitehall II study, study inception in 1985-88). PARTICIPANTS: 10 095 participants, aged 35 to 55 at baseline. MAIN OUTCOME MEASURE: Incident dementia at follow-up between 1985 and 2019. Cause specific Cox proportional hazards regression was used to examine the association of multimorbidity overall and at age 55, 60, 65, and 70 with subsequent dementia, taking into account the competing risk of death. RESULTS: The prevalence of multimorbidity (≥2 chronic diseases) was 6.6% (655/9937) at age 55 and 31.7% (2464/7783) at age 70; 639 cases of incident dementia occurred over a median follow-up of 31.7 years. After adjustment for sociodemographic factors and health behaviours, multimorbidity at age 55 was associated with subsequent risk of dementia (difference in incidence rate per 1000 person years 1.56, 95% confidence interval 0.62 to 2.77; hazard ratio 2.44, 95% confidence interval 1.82 to 3.26). The association weakened progressively with older age at onset of multimorbidity. At age 65, onset of multimorbidity before age 55 was associated with 3.86 (1.80 to 6.52) per 1000 person years higher incidence of dementia (hazard ratio 2.46, 1.80 to 2.26) and onset between 60 and 65 was associated with 1.85 (0.64 to 3.39) per 1000 person years higher incidence (1.51, 1.16 to 1.97). Severity of multimorbidity (≥3 chronic diseases) at age 55 was associated with a 5.22 (1.14 to 11.95) per 1000 person years higher incidence of dementia (hazard ratio 4.96, 2.54 to 9.67); the same analyses at age 70 showed 4.49 (2.33 to 7.19) per 1000 person years higher incidence (1.65, 1.25 to 2.18). CONCLUSION: Multimorbidity, particularly when onset is in midlife rather than late life, has a robust association with subsequent dementia. The increasingly younger age at onset of multimorbidity makes prevention of multimorbidity in people with a first chronic disease important.

Long-Term Evolution of Functional Limitations in Stroke Survivors Compared With Stroke-Free Controls: Findings From 15 Years of Follow-Up Across 3 International Surveys of Aging.

BACKGROUND AND PURPOSE: In the chronic phase 2 to 5 years poststroke, limitations in activities of daily living (ADL) and instrumental ADL (IADL) initially plateau before steady increasing. However, the impact of age and differences in initial levels of disability on the evolution of these limitations remains unclear. As such, this study aims to evaluate differences in long-term evolution of ADL/IADL limitations between stroke survivors and stroke-free population, and how limitations differ by initial level of disability for stroke survivors. METHODS: Thirty-three thousand six hundred sixty participants (5610 first-ever stroke cases with no recurrence during follow-up and 28 050 stroke-free controls) aged ≥50 from the Health and Retirement Study, Survey of Health, Ageing and Retirement in Europe, and English Longitudinal Study of Ageing were assessed for number of ADL/IADL limitations during the poststroke chronic phase (for cases) and over follow-up years 1996 to 2018 (for controls). Three thousand seven hundred eighteen stroke cases were additionally categorized by disability level using the modified Rankin Scale score of 1 to 2 years poststroke. Evolution of ADL/IADL limitations was assessed in stroke cases and controls and by modified Rankin Scale score (0-1, 2-3, 4-5) using linear mixed models. Models were stratified by age group (50-74 and ≥75 years) and adjusted for baseline characteristics, health behaviors, BMI, and comorbidities. RESULTS: Findings showed relative stability of ADL/IADL limitations during 3 to 6 years poststroke followed by an increase for both populations, which was faster for younger stroke cases, suggesting a differential age-effect (P<0.001). Disability level at 1 to 2 years poststroke influenced the evolution of limitations over time, especially for severe disability (modified Rankin Scale score, 4-5) associated with a reduction in limitations at 5 to 6 years poststroke. CONCLUSIONS: Our findings showed that during the poststroke chronic phase functional limitations first plateau and then increase and the evolution differs by disability severity. These results highlight the importance of adaptive long-term health and social care measures for stroke survivors.

Sex differences in functional limitations and the role of socioeconomic factors: a multi-cohort analysis.

BACKGROUND: Women are more likely to have functional limitations than are men, partly because of greater socioeconomic disadvantage. However, how sex differences vary by severity of functional limitations remains unclear. We examined sex differences in functional limitations, with attention to socioeconomic factors and severity of limitations. METHODS: Longitudinal data on limitations in basic activities of daily living (ADL) and instrumental activities of daily living (IADL) and mobility activities were drawn from 62 375 participants from 14 countries. For ADL, IADL, and mobility, participants were categorised based on number of limited activities (0, 1, 2, or ≥3). Sex differences in limitations in four birth cohorts (1895-1929, 1930-38, 1939-45, and 1946-60) were analysed before and after adjustment for socioeconomic factors (education and labour force status). FINDINGS: The prevalence of IADL and ADL limitations was higher in women than in men. After adjustment for socioeconomic factors, this sex difference was attenuated. The sex difference in IADL limitations at age 75 years (in the 1895-1929 cohort) was 3·7% before adjustment for socioeconomic factors (95% CI 2·6-4·7) and 1·7% (1·1-2·2) after adjustment. For ADL, the sex difference in limitations at age 75 years (in the 1895-1929 cohort) was 3·2% (2·3-4·1) before adjustment for socioeconomic factors and 1·4% (0·9-1·8) after adjustment. Sex differences in mobility limitations (16·1%, 95% CI 14·4-17·7) remained after adjustment for socioeconomic factors (14·3%, 12·7-15·9). After age 85 years, women were more likely to have three or more IADL or mobility limitations and men were more likely to have one or two limitations. INTERPRETATION: Socioeconomic factors largely explain sex differences in IADL and ADL limitations but not mobility. Sex differences in mobility limitations in midlife are important targets for future research and interventions. FUNDING: National Institute on Aging, UK National Institute for Health Research, European Commission, and US Social Security Administration.

Sex differences and the role of education in cognitive ageing: analysis of two UK-based prospective cohort studies.

BACKGROUND: Previous studies have shown an excess risk of Alzheimer's disease and related dementias among women. Education is thought to have a causal association with dementia onset. We aimed to investigate the role of education in influencing sex differences in cognitive ageing. METHODS: We analysed data from two prospective cohort studies in the UK; the English Longitudinal Study of Ageing (ELSA) and the Whitehall II study, to assess sex differences in cognitive performance and cognitive decline by birth cohort (birth year 1930-38, 1939-45, or 1946-55), before and after adjustment for education, and by high and low education level. Memory was assessed using immediate recall, for which data were available from all waves of the ELSA (2002-14) and Whitehall II (1997-2015) studies. Fluency was assessed using a semantic fluency test based on an animal naming task, with data available from all waves of the Whitehall II study and waves one to five (2002-10) and wave seven (2014) of the ELSA study. Cognitive scores were standardised separately in each study based on the mean and SD of the corresponding test among participants aged 50-59 years with secondary education. FINDINGS: 15 924 participants were included from the two studies. In pooled analyses, women had better memory scores than men in all birth cohorts, irrespective of adjustment for education (eg, at age 60 years, birth cohort 1930-38, mean difference between sexes [male scores minus female scores] -0·25 SDs [95% CI -0·32 to -0·19] after adjustment for education), and in both education level groups. Memory decline was faster in men than in women (at age 60 years, birth cohort 1946-55, mean difference in 13-year change -0·15 SDs [-0·20 to -0·09]; after adjustment for education -0·14 SDs [-0·20 to -0·08]). Men had better fluency scores than women in earlier birth cohorts and in the low education group (at age 60 years, birth cohort 1930-38, mean difference 0·20 SDs [95% CI 0·05 to 0·36]); but women had better fluency scores than men in later birth cohorts and in the high education group (at age 60 years, birth cohort 1946-55, mean difference -0·17 SDs [-0·24 to -0·10]). No sex differences were observed for fluency decline. INTERPRETATION: Our findings suggest that decreasing disparities between sexes in education, due to secular increases in educational opportunities, could attenuate sex differences in dementia risk and cognitive decline in the future. FUNDING: National Institute on Aging, National Institutes of Health; UK Medical Research Council; British Heart Foundation; and National Institute for Health Research.