Intensity of Leisure-Time Physical Activity and Dimensions of Mental Well-Being: A Reciprocal Approach Using Parallel Latent Growth Curve Modeling

Kim, Changwook; Kim, Jinwon; Thapa, Brijesh

doi:10.1123/jpah.2020-0300

Cited by 8 publications

(2 citation statements)

References 38 publications

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“…Asztalos et al (46) suggest that the relationship between self-reported PA and mental health varies across activity intensity levels and dimensions of mental health among women and men. Previous studies using selfreported PA data have reported the crucial role of moderateto-vigorous PA in the promotion of mental well-being in men (35,46,47). More research using device-based PA data is needed.…”

Section: Discussionmentioning

confidence: 99%

Relationship Between Accelerometer-Based Physical Activity, Sedentary Behavior, and Mental Health in Young Finnish Men

Appelqvist‐Schmidlechner

Raitanen

Vasankari

et al. 2022

Front. Public Health

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Healthy lifestyle behaviors including physical activity (PA) have been recognized to contribute positively to mental health. Most of the evidence on relationship between PA and mental health relies on self-reported PA results. Device-based measures on PA or sedentary behavior (SB) are less frequently used in mental health research. The present study aimed at examining the relationship between mental health and PA/SB measured by accelerometers in young Finnish men. The sample consisted of 409 men (mean age 28 ± 7 years), who participated in the military refresher training in Finland. Self-rated mental health was measured with Mental Health Inventory (MHI-5) and short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS) measuring mental health both from the perspective of mental health problems and mental well-being. PA was measured with accelerometer from the perspective of light, moderate, vigorous, and total activity, as well as SB. Linear regression models and compositional analysis were applied. Age, education, marital status, employment status, BMI, alcohol use and smoking were used as covariates. Evidence on relationship between total PA (standardized regression coefficient 0.340; 95% CI 0.022–0.657, p = 0.036) and SB (standardized regression coefficient −0.340; 95% CI −0.657 to −0.022, p = 0.036) with symptoms of mental health problems was found after adjusting for age, education, marital and employment status. The relationship was marginally significant (p = 0.056) after adjusting also for BMI, alcohol use and smoking. No evidence on relationship between PA or SB and mental well-being was found, neither in standard linear regression analysis nor in compositional approach. In our sample of young adult men, PA seemed to have a stronger relationship with symptoms of mental health problems rather than with mental well-being. The findings lead to a conclusion that all PA per se may not be independently associated with mental well-being in young adult males and raise the question whether the domain of PA and its context play a critical role in these relationships.

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Section: Discussionmentioning

confidence: 99%

Relationship Between Accelerometer-Based Physical Activity, Sedentary Behavior, and Mental Health in Young Finnish Men

Appelqvist‐Schmidlechner

Raitanen

Vasankari

et al. 2022

Front. Public Health

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“…For example, happier people might have the adequate levels of self-control to be active and do exercise whereas the characteristic of low well-being, lack of energy, anhedonia, and social withdrawal, all exert a negative influence on PA (Dishman, 1990;Goodwin, 2003). A recent longitudinal study indeed reported a bidirectional association between self-reported leisure time PA and well-being (Kim et al, 2021), indicating that well-being might lead to more PA and vice versa.…”

Section: Direction Of Associationmentioning

confidence: 99%

Differences in well-being

Vries¹

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Well-being is a complex, and multifaceted construct that includes feeling good and functioning well. There is a growing global recognition of well-being as an important research topic and public policy goal. Well-being is related to less behavioral and emotional problems, and is associated with many positive aspects of daily life, including longevity, higher educational achievement, happier marriage, and more productivity at work. People differ in their levels of well-being, i.e., some people are in general happier or more satisfied with their lives than others. These individual differences in well-being can arise from many different factors, including biological (genetic) influences and environmental influences. To enhance the development of future mental health prevention and intervention strategies to increase well-being, more knowledge about these determinants and factors underlying well-being is needed. In this dissertation, I aimed to increase the understanding of the etiology in a series of studies using different methods, including systematic reviews, meta-analyses, twin designs, and molecular genetic designs. In part I, we brought together all published studies on the neural and physiological factors underlying well-being. This overview allowed us to critically investigate the claims made about the biology involved in well-being. The number of studies on the neural and physiological factors underlying well-being is increasing and the results point towards potential correlates of well-being. However, samples are often still small, and studies focus mostly on a single biomarker. Therefore, more well-powered, data-driven, and integrative studies across biological categories are needed to better understand the neural and physiological pathways that play a role in well-being. In part II, we investigated the overlap between well-being and a range of other phenotypes to learn more about the etiology of well-being. We report a large overlap with phenotypes including optimism, resilience, and depressive symptoms. Furthermore, when removing the genetic overlap between well-being and depressive symptoms, we showed that well-being has unique genetic associations with a range of phenotypes, independently from depressive symptoms. These results can be helpful in designing more effective interventions to increase well-being, taking into account the overlap and possible causality with other phenotypes. In part III, we used the extreme environmental change during the COVID-19 pandemic to investigate individual differences in the effects of such environmental changes on well-being. On average, we found a negative effect of the pandemic on different aspects of well-being, especially further into the pandemic. Whereas most previous studies only looked at this average negative effect of the pandemic on well-being, we focused on the individual differences as well. We reported large individual differences in the effects of the pandemic on well-being in both chapters. This indicates that one-size-fits-all preventions or interventions to maintain or increase well-being during the pandemic or lockdowns will not be successful for the whole population. Further research is needed for the identification of protective factors and resilience mechanisms to prevent further inequality during extreme environmental situations. In part IV, we looked at the real-time assessment of well-being, investigating the feasibility and results of previous studies. The real-time assessment of well-being, related variables, and the environment can lead to new insights about well-being, i.e., results that we cannot capture with traditional survey research. The real-time assessment of well-being is therefore a promising area for future research to unravel the dynamic nature of well-being fluctuations and the interaction with the environment in daily life. Integrating all results in this dissertation confirmed that well-being is a complex human trait that is influenced by many interrelated and interacting factors. Future directions to understand individual differences in well-being will be a data-driven approach to investigate the complex interplay of neural, physiological, genetic, and environmental factors in well-being.

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Spatial spillovers of sport industry clusters and community resilience: Bridging a spatial lens to building a smart tourism city

Kim

2023

Information Processing & Management

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Intensity of Leisure-Time Physical Activity and Dimensions of Mental Well-Being: A Reciprocal Approach Using Parallel Latent Growth Curve Modeling

Cited by 8 publications

References 38 publications

Relationship Between Accelerometer-Based Physical Activity, Sedentary Behavior, and Mental Health in Young Finnish Men

Relationship Between Accelerometer-Based Physical Activity, Sedentary Behavior, and Mental Health in Young Finnish Men

Differences in well-being

Spatial spillovers of sport industry clusters and community resilience: Bridging a spatial lens to building a smart tourism city

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