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.

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.

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.

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.

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.

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.

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.

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.

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.

Better Subjective Sleep Quality Partly Explains the Association Between Self-Reported Physical Activity and Better Cognitive Function.

BACKGROUND: Physical activity has been associated with better cognitive function and better sleep quality. Yet, whether the beneficial effect of physical activity on cognitive function can be explained by an indirect pathway involving better sleep quality is unclear. OBJECTIVE: To investigate whether sleep quality mediates the association between physical activity and cognitive function in adults 50 years of age or older. METHODS: 86,541 community-dwelling European adults were included in the study. Physical activity and sleep quality were self-reported. Indicators of cognitive function (immediate recall, delayed recall, verbal fluency) were assessed using objective tests. All measures were collected six times between 2004 and 2017. The mediation was tested using multilevel mediation analyses. RESULTS: Results showed that self-reported physical activity was associated with better self-reported sleep quality, which was associated with better performance in all three indicators of cognitive function, demonstrating an indirect effect of physical activity on cognitive function through sleep quality. The mediating effect of sleep quality accounted for 0.41%, 1.46%, and 8.88% of the total association of physical activity with verbal fluency, immediate recall, and delayed recall, respectively. CONCLUSION: These findings suggest that self-reported sleep quality partly mediates the association between self-reported physical activity and cognitive function. These results need to be confirmed by device-based data of physical activity and sleep quality.

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.

I Sit but I Don't Know Why: Investigating the Multiple Precursors of Leisure-Time Sedentary Behaviors.

Background: Precursors driving leisure-time sedentary behaviors remain poorly investigated, despite their detrimental consequences. This study aimed to investigate the predictive validity of controlled and automatic motivational precursors toward reducing sedentary behaviors and being physically active on leisure-time sedentary behaviors. The influence of demographic, physical, socio-professional, interpersonal, and environmental variables was also examined and compared with the associations of motivational precursors. Methods: 125 adults completed questionnaires measuring controlled motivational precursors (i.e., intentions, perceived competence), demographical (i.e., sex and age), physical (i.e., body mass index), and interpersonal (i.e., number of children) variables. Regarding automatic motivational precursors, habit strength and approach-avoidance tendencies were captured using the Self-Report Behavioral Automaticity Index and a manikin task. Time at work was computed as a socio-professional variable, days of the week and weather conditions were recorded as environmental precursors. Participants wore an accelerometer for 7 days and leisure time was identified using notebooks. Associations between the different precursors and the leisure-time sedentary behaviors were examined in linear mixed effect models. Results: Intention to be physically active and habit strength toward physical activity were negatively associated with leisure-time sedentary behaviors. Sex, body mass index, time at work, number of children, day of the week, and weather conditions were more strongly associated with leisure-time sedentary behaviors. Conclusion: Our findings show that, in comparison with other variables, the influence of motivational precursors on leisure-time sedentary behaviors is limited. This study supports the adoption of a broad-spectrum of precursors when predicting sedentary behaviors.

Cognitive-bias modification intervention to improve physical activity in patients following a rehabilitation programme: protocol for the randomised controlled IMPACT trial.

INTRODUCTION: Being physically active is associated with a wide range of health benefits in patients. However, many patients do not engage in the recommended levels of physical activity (PA). To date, interventions promoting PA in patients mainly rely on providing knowledge about the benefits associated with PA to develop their motivation to be active. Yet, these interventions focusing on changing patients' conscious goals have proven to be rather ineffective in changing behaviours. Recent research on automatic factors (eg, automatic approach tendencies) may provide additional targets for interventions. However, the implementation and evaluation of intervention designed to change these automatic bases of PA are rare. Consequently, little is known about whether and how interventions that target automatically activated processes towards PA can be effective in changing PA behaviours. The Improving Physical Activity (IMPACT) trial proposes to fill this knowledge gap by investigating the effect of a cognitive-bias modification intervention aiming to modify the automatic approach towards exercise-related stimuli on PA among patients. METHODS AND ANALYSIS: The IMPACT trial is a single-centre, placebo (sham controlled), triple-blinded, phase 3 randomised controlled trial that will recruit 308 patients enrolled in a rehabilitation programme in the Division of General Medical Rehabilitation at the University Hospital of Geneva (Switzerland) and intends to follow up them for up to 1 year after intervention. Immediately after starting a rehabilitation programme, patients will be randomised (1:1 ratio) to receive either the cognitive-bias modification intervention consisting of a 12-session training programme performed over 3 weeks or a control condition (placebo). The cognitive-bias modification intervention aims to improve PA levels through a change in automatic approach tendencies towards PA and sedentary behaviours. The primary outcome is the sum of accelerometer-based time spent in light-intensity, moderate-intensity and vigorous-intensity PA over 1 week after the cognitive-bias modification intervention (in minutes per week). Secondary outcomes are related to changes in (1) automatic approach tendencies and self-reported motivation to be active, (2) physical health and (3) mental health. Sedentary behaviours and self-reported PA will also be examined. The main time point of the analysis will be the week after the end of the intervention. These outcomes will also be assessed during the rehabilitation programme, as well as 1, 3, 6 and 12 months after the intervention for secondary analyses. ETHICS AND DISSEMINATION: The study will be conducted in accordance with the Declaration of Helsinki. This trial was approved by the Ethics Committee of Geneva Canton, Switzerland (reference number: CCER2019-02257). All participants will give an informed consent to participate in the study. Results will be published in relevant scientific journals and be disseminated in international conferences. TRIAL REGISTRATION DETAILS: The clinical trial was registered at the German clinical trials register (reference number: DRKS00023617); Pre-results.

Muscle strength is associated with COVID-19 hospitalization in adults 50 years of age or older.

BACKGROUND: Weak muscle strength has been associated with a wide range of adverse health outcomes. Yet, whether individuals with weaker muscle strength are more at risk for hospitalization due to severe COVID-19 is still unclear. The objective of this study was to investigate the independent association between muscle strength and COVID-19 hospitalization. METHODS: Data from adults 50 years of age or older were analysed using logistic models adjusted for several chronic conditions, body-mass index, age, and sex. Hand-grip strength was repeatedly measured between 2004 and 2017 using a handheld dynamometer. COVID-19 hospitalization during the lockdown was self-reported in summer 2020 and was used as an indicator of COVID-19 severity. RESULTS: The study was based on the Survey of Health, Ageing and Retirement in Europe (SHARE) and included 3600 older adults (68.8 ± 8.8 years, 2044 female), among whom 316 were tested positive for the severe acute respiratory syndrome coronavirus 2 (8.8%), and 83 (2.3%) were hospitalized due to COVID-19. Results showed that higher grip strength was associated with a lower risk of COVID-19 hospitalization [adjusted odds ratio (OR) per increase of 1 standard deviation in grip strength = 0.64, 95% confidence interval (95% CI) = 0.45-0.87, P = 0.015]. Results also showed that age (OR for a 10 -year period = 1.70, 95% CI = 1.32-2.20, P < 0.001) and obesity (OR = 2.01, 95% CI = 1.00-3.69, P = 0.025) were associated with higher risk of COVID-19 hospitalization. Sensitivity analyses using different measurements of grip strength as well as robustness analyses based on rare-events logistic regression and a different sample of participants (i.e. COVID-19 patients) were consistent with the main results. CONCLUSIONS: Muscle strength is an independent risk factor for COVID-19 severity in adults 50 years of age or older.

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.

Evolution of physical activity habits after a context change: The case of COVID-19 lockdown.

OBJECTIVE: Habits, defined as well-learned associations between cues and behaviours, are essential for health-related behaviours, including physical activity (PA). Despite the sensitivity of habits to context changes, little remains known about the influence of a context change on the interplay between PA habits and behaviours. We investigated the evolution of PA habits amidst the spring COVID-19 lockdown, a major context change. Moreover, we examined the association of PA behaviours and autonomous motivation with this evolution. DESIGN: Three-wave observational longitudinal design. METHODS: PA habits, behaviours, and autonomous motivation were collected through online surveys in 283 French and Swiss participants. Variables were self-reported with reference to three time-points: before-, mid-, and end-lockdown. RESULTS: Mixed effect modelling revealed a decrease in PA habits from before- to mid-lockdown, especially among individuals with strong before-lockdown habits. Path analysis showed that before-lockdown PA habits were not associated with mid-lockdown PA behaviours (ß = -.02, p = .837), while mid-lockdown PA habits were positively related to end-lockdown PA behaviours (ß = .23, p = .021). Autonomous motivation was directly associated with PA habits (ps < .001) and withto before- and mid-lockdown PA behaviours (ps < .001) (but not with end-lockdown PA behaviours) and did not moderate the relations between PA behaviours and habits (ps > .072). CONCLUSION: PA habits were altered, and their influence on PA behaviours was impeded during the COVID-19 lockdown. Engagement in PA behaviours and autonomous motivation helped in counteracting PA habits disruption.