Sedentary Behavior and Incident Dementia Among Older Adults.

Importance: Sedentary behavior is associated with cardiometabolic disease and mortality, but its association with dementia is unclear. Objective: To investigate whether accelerometer-assessed sedentary behavior is associated with incident dementia. Design, Setting, and Participants: A retrospective study of prospectively collected data from the UK Biobank including 49 841 adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer and living in England, Scotland, or Wales. Follow-up began at the time of wearing the accelerometer (February 2013 to December 2015) and continued until September 2021 in England, July 2021 in Scotland, and February 2018 in Wales. Exposures: Mean daily sedentary behavior time (included in the primary analysis) and mean daily sedentary bout length, maximum daily sedentary bout length, and mean number of daily sedentary bouts (included in the secondary analyses) were derived from a machine learning-based analysis of 1 week of wrist-worn accelerometer data. Main Outcome and Measures: Incident all-cause dementia diagnosis from inpatient hospital records and death registry data. Cox proportional hazard models with linear and cubic spline terms were used to assess associations. Results: A total of 49 841 older adults (mean age, 67.19 [SD, 4.29] years; 54.7% were female) were followed up for a mean of 6.72 years (SD, 0.95 years). During this time, 414 individuals were diagnosed with incident all-cause dementia. In the fully adjusted models, there was a significant nonlinear association between time spent in sedentary behavior and incident dementia. Relative to a median of 9.27 hours/d for sedentary behavior, the hazard ratios (HRs) for dementia were 1.08 (95% CI, 1.04-1.12, P < .001) for 10 hours/d, 1.63 (95% CI, 1.35-1.97, P < .001) for 12 hours/d, and 3.21 (95% CI, 2.05-5.04, P < .001) for 15 hours/d. The adjusted incidence rate of dementia per 1000 person-years was 7.49 (95% CI, 7.48-7.49) for 9.27 hours/d of sedentary behavior, 8.06 (95% CI, 7.76-8.36) for 10 hours/d, 12.00 (95% CI, 10.00-14.36) for 12 hours/d, and 22.74 (95% CI, 14.92-34.11) for 15 hours/d. Mean daily sedentary bout length (HR, 1.53 [95% CI, 1.03-2.27], P = .04 and 0.65 [95% CI, 0.04-1.57] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 0.48 hours) and maximum daily sedentary bout length (HR, 1.15 [95% CI, 1.02-1.31], P = .02 and 0.19 [95% CI, 0.02-0.38] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 1.95 hours) were significantly associated with higher risk of incident dementia. The number of sedentary bouts per day was not associated with higher risk of incident dementia (HR, 1.00 [95% CI, 0.99-1.01], P = .89). In the sensitivity analyses, after adjustment for time spent in sedentary behavior, the mean daily sedentary bout length and the maximum daily sedentary bout length were no longer significantly associated with incident dementia. Conclusions and Relevance: Among older adults, more time spent in sedentary behaviors was significantly associated with higher incidence of all-cause dementia. Future research is needed to determine whether the association between sedentary behavior and risk of dementia is causal.

Early-Life Socioeconomic Circumstances and Physical Activity in Older Age: Women Pay the Price.

Health in older age is shaped by early-life socioeconomic circumstances (SECs) and sex. However, whether and why these factors interact is unclear. We examined a cultural explanation of this interaction by distinguishing cultural and material aspects of SECs in the context of physical activity-a major determinant of health. We used data from 56,331 adults between 50 and 96 years old from the Survey of Health, Ageing and Retirement in Europe (SHARE), a 13-year, large-scale, population-based cohort. Confounder-adjusted logistic linear mixed-effects models showed an association between the cultural aspects of early-life SEC disadvantage and physical activity among women, but it was not consistently observed in men. Furthermore, these associations were compensated for only partially by adult-life socioeconomic trajectories. The material aspects of early-life SECs were not associated with adult-life physical activity. These findings highlight the need to distinguish different aspects of SECs because they may relate to health behaviors in diverse ways.

Physical inactivity amplifies the negative association between sleep quality and depressive symptoms.

Poor sleep quality and physical inactivity are known risk factors for depressive symptoms. Yet, whether these factors differently contribute to depressive symptoms and whether they interact with one another remains unclear. Here, we examined how sleep quality and physical activity influence depressive symptoms in 79,274 adults 50 years of age or older (52.4% women) from the Survey of Health, Aging and Retirement in Europe (SHARE) study. Sleep quality (poor vs. good), physical activity (inactive vs. active), and depressive symptoms (0 to 12 score) were repeatedly collected (7 waves of data collection) between 2004 and 2017. Results showed that sleep quality and physical activity were associated with depressive symptoms. Specifically, participants with poorer sleep quality reported more depressive symptoms than participants with better sleep quality (b = 1.85, 95% CI = 1.83-1.86, p < .001). Likewise, compared to physically active participants, physically inactive participants reported more depressive symptoms (b = 0.44, 95% CI = 0.42-0.45, p < .001). Moreover, sleep quality and physical activity showed an interactive association with depressive symptoms (b = 0.17, 95% CI = 0.13-0.20, p < .001). The negative association between poor sleep quality and higher depressive symptoms was stronger in physically inactive than active participants. These findings suggest that, in adults 50 years of age or older, both poor sleep quality and physical inactivity are related to an increase in depressive symptoms. Moreover, the detrimental association between poor sleep quality and depressive symptoms is amplified in physically inactive individuals.

Why Are Individuals With Diabetes Less Active? The Mediating Role of Physical, Emotional, and Cognitive Factors.

BACKGROUND: Despite the key role of physical activity in the management of diabetes, many individuals with diabetes do not engage in the recommended levels of physical activity. However, our knowledge of the mechanisms underlying the relationship between diabetes and physical inactivity is limited. PURPOSE: To investigate the associations between diabetes and the levels and evolution of physical activity across aging, and to determine whether physical, emotional, and cognitive factors mediate these associations. METHODS: Data from 105,622 adults aged 50-96 years from the Survey of Health, Ageing and Retirement in Europe (SHARE) were used in adjusted linear mixed models to examine whether diabetes was associated with physical activity levels and variations across aging. The potential mediators were subjective energy, muscle strength, physical and cognitive disability, sleep problems, depressive symptoms, and cognitive functions. The variables were measured up to seven times over a 13-year period. RESULTS: Individuals with diabetes demonstrated a lower level and a steeper decrease in physical activity across aging than individual without diabetes. Mediators explained ~53% and 94% of the association of diabetes with the level of physical activity and with the linear evolution of physical activity across aging, respectively. All mediators were significantly associated with physical activity. Physical and cognitive disability as well as depressive symptoms were the strongest mediators, while sleep was the lowest one. CONCLUSIONS: These findings suggest that the etiology of physical inactivity in individuals with diabetes can result from several physical, emotional, and cognitive changes associated with the emergence of this disease.

Muscle strength explains the protective effect of physical activity against COVID-19 hospitalization among adults aged 50 years and older.

Physical activity has been proposed as a protective factor for COVID-19 hospitalisation. However, the mechanisms underlying this association are unclear. We examined the association between physical activity and COVID-19 hospitalisation and whether this relationship was explained by risk factors (chronic conditions, weak muscle strength). We used data from adults over 50 years from the Survey of Health, Ageing and Retirement in Europe. The outcome was self-reported hospitalisation due to COVID-19, before August 2020. The main exposure was physical activity, self-reported between 2004 and 2017. Among the 3139 participants included (69.3 ± 8.5 years, 1763 women), 266 were tested positive for COVID-19, 66 were hospitalised. Logistic regression models showed that individuals who engaged in physical activity more than once a week had lower odds of COVID-19 hospitalisation than individuals who hardly ever or never engaged in physical activity (odds ratios = 0.41, 95% confidence interval = 0.22-0.74, p = .004). This association between physical activity and COVID-19 hospitalisation was explained by muscle strength, but not by other risk factors. These findings suggest that, after 50 years, engaging in physical activity is associated with lower odds of COVID-19 hospitalisation. This protective effect of physical activity may be explained by muscle strength.

Relationships between changes in self-reported physical activity, sedentary behaviour and health during the coronavirus (COVID-19) pandemic in France and Switzerland.

To assess whether changes in physical activity and sedentary behaviour during the COVID-19 lockdown are associated with changes in mental and physical health. Observational longitudinal study. Participants living in France or Switzerland responded to online questionnaires measuring physical activity, physical and mental health, anxiety, and depressive symptoms. Paired sample t-tests were used to assess differences in physical activity and sedentary behaviour before and during lockdown. Multiple linear regressions were used to investigate associations between changes in physical activity and changes in mental and physical health during lockdown. 267 (wave1) and 110 participants (wave2; 2 weeks later) were recruited. Lockdown resulted in higher time spent in walking and moderate physical activity (~10min/day) and in sedentary behaviour (~75min/day), compared to pre COVID-19. Increased physical activity during leisure time from week 2 to week 4 of lockdown was associated with improved physical health (ß=.24, p=.002). Additionally, an increase in sedentary behaviour during leisure time was associated with poorer physical health (ß=-.35, p=.002), mental health (ß=-.25, p=.003), and subjective vitality (ß=-.30, p=.004). Ensuring sufficient levels of physical activity and reducing sedentary time can play a vital role in helping people to cope with a major stressful event, such as the COVID-19 pandemic.

Development and validation of the physical effort scale (PES).

OBJECTIVES: Previous literature has primarily viewed physical effort as an aversive experience. However, recent research suggests that effort can also be valued positively. These differences in approach and avoidance tendencies toward physical effort may play a key role in the self-regulation of physical activity behaviors. The aim of this study was to develop a scale that measures these tendencies and contributes to a better understanding of physical effort and how it affects behavior. METHODS: The Physical Effort Scale (PES) was developed in Study 1 based on expert evaluations (n = 9) and cognitive interviews (n = 10). In Study 2 (n = 680, 69% female), content validity and dimensional structure were examined using principal component analysis and confirmatory factor analysis. Item reduction was conducted using item response theory. Preliminary construct validity was explored using regression. Study 3 (n = 297, 71% female) was used to validate dimensional structure, internal consistency, and construct validity, and to assess test-retest reliability. RESULTS: In Study 1, 44 items were rated for content validity, of which 18 were selected and refined based on cognitive interviews. Analyses from Study 2 allowed reducing the scale to 8 items with a two-dimension structure: tendency to approach (n = 4) and to avoid physical effort (n = 4). The two subscales showed high internal consistency (α = 0.897 for the approach dimension and 0.913 for the avoidance dimension) and explained usual levels of physical activity, providing preliminary evidence of construct validity. Study 3 confirmed the two-dimension structure with high internal consistency (α = 0.907 and 0.916 for the approach and avoidance dimension, respectively) and revealed acceptable test-retest reliability (intraclass correlation >0.66). Patterns of associations with other constructs showed expected relationships, confirming the concurrent, convergent, and discriminant validity of the scale. CONCLUSIONS: The PES is a valid and reliable measure of individual differences in the valuation of physical effort. This scale can assess the propensity to engage in physically demanding tasks in non-clinical populations. The PES and its manual are available in the Supplementary Material.

Sociodemographic precursors of explicit and implicit attitudes towards physical activity.

OBJECTIVE: In high-income countries, people with low socio-economic status (SES) engage in less leisure-time physical activity (PA) than those with higher SES. Beyond a materialistic account of this difference, the role of motivational precursors-among which attitudes are emblematic-remains poorly understood, particularly when it comes to dissociating the automatic vs. deliberative components of attitudes. This pre-registered study aimed to examine the associations between SES (i.e. income and educational attainment) and motivational precursors of PA (i.e. explicit and implicit attitudes), and whether gender and age may moderate these relationships. METHOD: We used data from 970 adults (64% of women; mean age = 33 ± 12 years) from the Attitudes, Identities, and Individual Differences (AIID) study. RESULTS: Results of multiple linear regression analyses showed that participants with the highest level of income (>150,000$ per year) reported more positive explicit and implicit attitudes towards PA than those with lower income. Exploratory analysis further showed that women reported weaker explicit attitudes towards PA, while both explicit and implicit attitudes towards PA became weaker at age increases. In contrast, educational attainment was not significantly associated with those attitudes, and there was only mixed evidence for a moderating role of participants' gender on the pattern of associations. CONCLUSION: Our findings suggest that both the explicit and implicit attitudes towards PA may be socially patterned. Future intervention studies should examine whether these attitudinal differences could be reduced, and whether such a reduction could help buffer the unequal participation in PA behaviors across social groups.

Autonomous motivation promotes goal attainment through the conscious investment of effort, but mental contrasting with implementation intentions makes goal striving easier.

People with autonomous motives (e.g., personal importance) may use automated strategies to effortlessly sustain goal-directed behavior and overcome obstacles. We investigated whether conscious effort, ease of goal striving, physiological effort, and the number of obstacles encountered mediate relations between motives and goal attainment for a competitive cycling goal. Additionally, half the participants (n = 57) were trained in Mental Contrasting with Implementation Intentions (MCII) - a technique that facilitates development of goal-directed behavior - with remaining participants (n = 54) treated as controls. Conscious investment of effort mediated relations between autonomous motives and goal attainment. Subjective ease of goal striving and physiological effort did not. This result indicates that successful goal striving is not perceived as effortless for autonomously motivated individuals working on competitive goals. Conversely, MCII predicted a reduction in obstacles, which in turn was associated with easier goal striving but not goal attainment. Although MCII did not support goal attainment in the current study, its ability to minimize the influence of obstacles may still be useful for other types of goals or for sustaining long-term goal pursuit.

Improving physical activity using a single personalized consequence-based approach-avoidance training: Effects on self-reported behaviors, attitudes, and choices.

OBJECTIVE: Despite their potential in improving health behaviors, such as physical activity (PA), the effectiveness of interventions targeting automatic precursors remains contrasted. We examined the effects of a single session of ABC training - a personalized consequence-based approach-avoidance training - on PA, relative to an active control condition and a control condition. METHODS: Middle-aged US participants (N = 360, 53 % of women) either completed an ABC training (being instructed to approach PA to obtain self-relevant consequences), an approach-avoidance training (approaching PA in 90 % of trials), or a control training (approaching PA in 50 % of trials). Participants selected antecedents (e.g., "When I have little time") in which personalized choices between PA and sedentary alternatives were likely to occur. In the ABC training only, after approaching PA, self-relevant consequences were displayed (e.g., increase in the health status of participant's avatar). Primary outcome was self-reported PA seven days after the intervention. Secondary outcomes included choices for PA (vs sedentary) alternatives in a hypothetical free-choice task, intention, automatic and explicit attitudes toward PA. RESULTS: No significant effect of the ABC intervention on PA was observed, so as on intention and explicit attitudes. However, the ABC intervention was associated with higher odds of choosing PA alternatives in the free-choice task and with more positive automatic attitudes toward PA. CONCLUSIONS: While the ABC training was not effective at improving PA, its effects on choices and automatic attitudes suggest that this intervention may still have potential. Future studies with intensive trainings and device-based measures of PA remains needed.

Associations between accelerometer-derived sedentary behavior and physical activity with white matter hyperintensities in middle-aged to older adults.

INTRODUCTION: We examined the relationship between sedentary behavior (SB), moderate-to-vigorous physical activity (MVPA), and white matter hyperintensity (WMH) volumes, a common magnetic resonance imaging (MRI) marker associated with risk of neurodegenerative disease in middle-aged to older adults. METHODS: We used data from the UK Biobank (n = 14,415; 45 to 81 years) that included accelerometer-derived measures of SB and MVPA, and WMH volumes from MRI. RESULTS: Both MVPA and SB were associated with WMH volumes (ßMVPA = -0.03 [-0.04, -0.01], p < 0.001; ßSB = 0.02 [0.01, 0.03], p = 0.007). There was a significant interaction between SB and MVPA on WMH volumes (ßSB×MVPA = -0.015 [-0.028, -0.001], p SB×MVPA = 0.03) where SB was positively associated with WMHs at low MVPA, and MVPA was negatively associated with WMHs at high SB. DISCUSSION: While this study cannot establish causality, the results highlight the potential importance of considering both MVPA and SB in strategies aimed at reducing the accumulation of WMH volumes in middle-aged to older adults. Highlights: SB is associated with greater WMH volumes and MVPA is associated with lower WMH volumes.Relationships between SB and WMH are strongest at low levels of MVPA.Associations between MVPA and WMH are strongest at high levels of SB.Considering both SB and MVPA may be effective strategies for reducing WMHs.

Sedentary behavior and lifespan brain health.

Higher levels of physical activity are known to benefit aspects of brain health across the lifespan. However, the role of sedentary behavior (SB) is less well understood. In this review we summarize and discuss evidence on the role of SB on brain health (including cognitive performance, structural or functional brain measures, and dementia risk) for different age groups, critically compare assessment approaches to capture SB, and offer insights into emerging opportunities to assess SB via digital technologies. Across the lifespan, specific characteristics of SB (particularly whether they are cognitively active or cognitively passive) potentially act as moderators influencing the associations between SB and specific brain health outcomes. We outline challenges and opportunities for future research aiming to provide more robust empirical evidence on these observations.

Recent trends and disparities in 24-hour movement behaviors among US youth with mental, behavioral and neurodevelopmental conditions.

BACKGROUND: Meeting 24-h movement behaviors (24-HMB: physical activity [PA], screen time [ST], and sleep [SL]) recommendations may be associated with positive health outcomes among youth with specific mental, behavioral, and neurodevelopmental (MBD) conditions. However, temporal trends and disparities in meeting 24-HMB guidelines in these higher-risk groups have not been investigated, hampering the development of evidence-based clinical and public health interventions. METHODS: Serial, cross-sectional analyses of nationally National Survey of Children's Health (NSCH) data (including U.S. youth aged 6-17 years with MBD conditions) were conducted. The time-trends survey data was conducted between 2016 and 2021. The prevalence of 24-HMB adherence estimates were reported for the overall sample and for various sociodemographic subgroups. The subgroups analyzed included: age group (children[aged 6 to 13 years], adolescents[aged 14 to 17 years]), sex, socioeconomic status, and ethnicity. RESULTS: Data on 52,634 individuals (mean age, 12.0 years [SD,3.5]; 28,829 [58.0 %] boys) were analyzed. From 2016 to 2021 the estimated trend in meeting PA + ST + SL guidelines declined (-0.8 % [95%CI, -1.0 % to -0.5 %], P for trend <0.001), whereas meeting none of 24-HMB guidelines increased (2.2 % [1.8 % to 2.6 %], P for trend <0.001). White participants, children, and boys reported higher estimated prevalence of meeting full integrated (PA + ST + SL) guidelines. DISCUSSION: The temporal trends observed in this study highlight the importance of consistently monitoring movement behavior among MBD youth and identifying variations by sociodemographic groups in meeting 24-HMB guidelines for health promotion within these vulnerable groups.

Beyond Individual Cognitions: Time for Intervention Science to Focus on Health Context and Audience.

Intervention science faces a hazardous paradox: on the one hand, vulnerable populations (eg, patients, people from low socioeconomic background, older adults) are those for whom adoption of healthy behaviors is most urgent; on the other hand, behavior change models are less predictive, and interventions less successful, in these populations. This commentary presents 4 reasons that may explain this issue: (1) research mostly focuses on what causes behavior and how to change it, at the expense of investigating among whom and under what conditions models are valid; (2) models put an undue emphasis on individual cognitions; (3) most studies are not conducted on vulnerable populations; and (4) most researchers are from high-income countries. Several avenues are proposed to address this issue: (1) providing a central place to the context and audience in health behavior change modelization, through collaborations with researchers from other disciplines and countries, and with members of the targeted audience; (2) better reporting samples' sociodemographic characteristics and increasing samples' diversity; and (3) using more rigorous and innovative designs (eg, powered randomized controlled trials, N-of-1 trials, intensive longitudinal studies). In conclusion, it becomes urgent to change the way we do research: the social utility and credibility of intervention science depend on it.

Automaticity mediates the association between action planning and physical activity, especially when autonomous motivation is high.

OBJECTIVES: Action planning promotes physical activity (PA). However, mechanisms underlying this association are poorly understood, as are the variables that moderate this link remain unexplored. To fill these gaps, we investigated whether automaticity mediated the association between action planning and PA, and whether autonomous motivation moderated this mediation. METHODS AND MEASURES: PA was measured by accelerometry over seven days among a sample of 124 adults. Action planning, automaticity, and autonomous motivation were assessed by questionnaires. RESULTS: Structural equation models revealed that automaticity mediated the association between action planning and PA (total effect, ß = .29, p < .001) - action planning was associated with automaticity (a path, ß = .47, p < .001), which in turn related to PA (b path, ß = .33, p = .003). Autonomous motivation moderated the a path (ß = .16, p = .035) - action planning was more strongly associated with automaticity when autonomous motivation was high (+1 standard-deviation [SD]) (unstandardized b = 0.77, p < .001) versus low (-1 SD) (b = 0.35, p = .023). CONCLUSION: These findings not only support that action planning favors an automatic behavioral regulation, but also highlight that a high autonomous motivation toward PA may reinforce this mechanism.

Initial status and change in cognitive function mediate the association between academic education and physical activity in adults over 50 years of age.

Higher levels of academic education are associated with higher levels of physical activity throughout the lifespan. However, the mechanisms underlying this association are unclear. Cognitive functioning is a potential mediator of this association because higher levels of education are associated with better cognitive function, which is related to greater engagement in physical activity. Here, we used large-scale longitudinal data from 105,939 adults 50 years of age or older (55% women) from the Survey of Health, Ageing, and Retirement in Europe to investigate whether initial status and change in cognitive function mediate the relationship between education and change in physical activity. Education and physical activity were self-reported. Cognitive function was assessed based on delayed recall and verbal fluency. Academic education was assessed at the first measurement occasion. The other measures were collected seven times between 2004 and 2019. The mediating role of cognitive function was tested using longitudinal mediation analyses combined with growth curve models. We found that higher levels of education were associated with higher levels and slower decreases in cognitive function, which in turn predicted a lower decrease in physical activity across time. These results support the presence of an indirect effect of education on physical activity trajectories by affecting the intercept and slope of cognitive function. Specifically, these findings suggest that both the initial status and change in cognitive function mediate the association between academic education and change in physical activity. In addition, results revealed that, across the aging process, differences in cognitive function and physical activity widen between the low and high educated. In other words, this study demonstrates the long-lasting effect of education on cognitive function and physical activity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Physical activity mediates the effect of education on mental health trajectories in older age.

OBJECTIVE: Why people with lower levels of educational attainment have poorer mental health than people with higher levels can partly be explained by financial circumstances. However, whether behavioral factors can further explain this association remains unclear. Here, we examined the extent to which physical activity mediates the effect of education on mental health trajectories in later life. METHODS: Data from 54,818 adults 50 years of age or older (55 % women) included in the Survey of Health, Aging and Retirement in Europe (SHARE) were analyzed using longitudinal mediation and growth curve models to estimate the mediating role of physical activity (baseline and change) in the association between education and mental health trajectories. Education and physical activity were self-reported. Mental health was derived from depressive symptoms and well-being, which were measured by validated scales. RESULTS: Lower education was associated with lower levels and steeper declines in physical activity over time, which predicted greater increases in depressive symptoms and greater decreases in well-being. In other words, education affected mental health through both levels and trajectories of physical activity. Physical activity explained 26.8 % of the variance in depressive symptoms and 24.4 % in well-being, controlling for the socioeconomic path (i.e., wealth and occupation). CONCLUSIONS: These results suggest that physical activity is an important factor in explaining the association between low educational attainment and poor mental health trajectories in adults aged 50 years and older.

Physical activity matters for everyone's health, but individuals with multimorbidity benefit more.

Multimorbidity, defined as the presence of two or more chronic conditions, is increasingly prevalent and is a major contributor to ill health in old age. Physical activity (PA) is a key protective factor for health and individuals with multimorbidity could particularly benefit from engaging in PA. However, direct evidence that PA has greater health benefits in people with multimorbidity is lacking. The objective of the present study was to investigate whether the associations between PA and health were more pronounced in individuals with (vs. without) multimorbidity. We used data from 121,875 adults aged 50 to 96 years (mean age = 67 ± 10 years, 55% women) enrolled in the Survey of Health, Ageing and Retirement in Europe (SHARE). Multimorbidity and PA were self-reported. Health indicators were assessed using tests and validated scales. Variables were measured up to seven times over a 15-year period. Confounder-adjusted linear mixed-effects models were used to investigate the moderating role of multimorbidity on the associations of PA with the levels and trajectories of health indicators across aging. Results showed that multimorbidity was associated with declines in physical, cognitive, and mental health, as well as poorer general health. Conversely, PA was positively associated with these health indicators. We found a significant interaction between multimorbidity and PA, revealing that positive associations between PA and health indicators were strengthened in people with multimorbidity - although this stronger association became less pronounced in advanced age. These findings suggest that the protective role of PA for multiple health indicators is enhanced in individuals with multimorbidity.

Women carry the weight of deprivation on physical inactivity: Moderated mediation analyses in a European sample of adults over 50 Years of age.

Deprived people are less physically active than privileged individuals. However, pathways underlying the association between deprivation and physical activity remain overlooked. We examined whether the association between deprivation and physical activity was mediated by body mass index (BMI). Consistent with an intersectional perspective (how the combination of belongingness to vulnerable social categories widens inequalities), we tested whether gender moderated this mediating pathway and hypothesized that the mediating effect of BMI would be stronger among women (vs men). Large-scale longitudinal data from 20,961 adults 50 years of age or older (57% women) from the Survey of Health, Ageing and Retirement in Europe were used. Social and material deprivation were measured by questionnaire, BMI and physical activity were reported from two to six years later. Simple mediation models showed that BMI partly mediated the association of material (total effect c = -0.14, proportion of mediated effect = 8%) and of social deprivation (c = -0.24, proportion of mediated effect = 4%) with physical activity. Moderated mediation models revealed that this mediating pathway was moderated by gender. The effect of deprivation on BMI was stronger among women (vs men), with BMI mediating 18% and 7% of the association of material and social deprivation with physical activity among women (vs 4% and 2% among men). Lower levels of physical activity observed among deprived older adults could be partly attributed to a higher BMI. Critically, this mechanism was exacerbated among women, reinforcing the need to understand how deprivation and gender interact to predict health behaviors.