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Objectives There is evidence to suggest that leisure engagement may influence self-perceptions of aging, but disentangling potential bidirectionality in this relationship is challenging. A better understanding of the directionality of this association is essential for designing more effective interventions to promote healthy aging. We, therefore, tested concurrent effects and lagged effects in both directions for a univariate measure of leisure engagement as well as specific domains of community, cognitive, creative, and physical activities. Methods A total of 17,753 adults aged 50 or above living in the United States from the Health and Retirement Study were included in the analysis. They provided 32,703 observations over 3 waves between 2008/2010 and 2016/2018. Data were analyzed using structural equation modeling with both concurrent and lagged associations between self-perceptions of aging and leisure engagement, controlling for confounders including age, gender, ethnicity, socioeconomic position, and health conditions. Results We found consistent evidence for leisure engagement as a predictor of self-perceptions of aging. There was also evidence for a reciprocal relationship where leisure engagement was predicted by older adults' self-perceptions of aging. Similar results were observed for specific domains of leisure engagement. Discussion Our findings provide empirical support for the potential benefits of leisure engagement on positive self-perceptions of aging, regardless of the type of activities. Our study also highlights the importance to consider the directionality in researching leisure engagement and self-perceptions of aging. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic has brought about significant behavioural changes, one of which is increased time spent at home. This could have important public health implications. This study aimed to explore longitudinal patterns of 'home confinement' (defined as not leaving the house/garden) during the COVID-19 pandemic, and the associated predictors and mental health outcomes. Methods: Data were from the UCL COVID-19 Social Study. The analytical sample consisted of 25 390 adults in England who were followed up for 17 months (March 2020–July 2021). Data were analysed using growth mixture models. Results: Our analyses identified three classes of growth trajectories, including one class showing a high level of persistent home confinement (the home-confined, 24.8%), one changing class with clear alignment with national containment measures (the adaptive, 32.0%), and one class with a persistently low level of confinement (the unconfined, 43.1%). A range of factors were associated with the class membership of home-confinement trajectories, such as age, gender, income, employment status, social relationships and health. The home-confined class had the highest number of depressive (diff = 1.34–1.68, p < 0.001) and anxiety symptoms (diff = 0.84–1.05, p < 0.001) at the end of the follow-up than the other two classes. Conclusions: There was substantial heterogeneity in longitudinal patterns of home confinement during the COVID-19 pandemic. People with a persistent high level of confinement had the worst mental health outcomes, calling for special attention in mental health action plans, in particular targeted interventions for at-risk groups. [ABSTRACT FROM AUTHOR]

There are increasing worries that lockdowns and 'stay-at-home' orders due to the COVID-19 pandemic could lead to a rise in loneliness, which is recognised as a major public health concern. But profiles of loneliness during the pandemic and risk factors remain unclear. The current study aimed to examine if and how loneliness levels changed during the strict lockdown and to explore the clustering of loneliness growth trajectories. Data from 38,217 UK adults in the UCL COVID -19 Social Study (a panel study collecting data weekly during the pandemic) were analysed during the strict lockdown period in the UK (23/03/2020–10/05/2020). The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and geographical location. Growth mixture modelling was used to identify the latent classes of loneliness growth trajectories and their predictors. Analyses revealed four classes, with the baseline loneliness level ranging from low to high. In the first a few weeks of lockdown, loneliness levels increased in the highest loneliness group, decreased in the lowest loneliness group, and stayed relatively constant in the middle two groups. Younger adults (OR = 2.17–6.81), women (OR = 1.59), people with low income (OR = 1.3), the economically inactive (OR = 1.3–2.04) and people with mental health conditions (OR = 5.32) were more likely to be in highest loneliness class relative to the lowest. Further, living with others or in a rural area, and having more close friends or greater social support were protective. Perceived levels of loneliness under strict lockdown measures due to COVID-19 were relatively stable in the UK, but for many people these levels were high with no signs of improvement. Results suggest that more efforts are needed to address loneliness. • Our analyses revealed four distinctive latent classes of loneliness trajectories. • During the seven weeks of strict lockdown, loneliness levels were relatively stable. • There is a slight increase in the highest loneliness class and decrease in the lowest class. • A range of demographic, health, and social factors were related to latent classes. [ABSTRACT FROM AUTHOR]