Physical Activity Dimensions Differentially Predict Physical and Mental Components of Health-Related Quality of Life: Evidence from a Sport for All Study

Weekend physical activity profiles and their relationship with quality of life: The SOPHYA cohort of Swiss children and adolescents

INTRODUCTION

Quality of life (QoL) is an important health indicator among children and adolescents. Evidence on the effect of physical activity (PA)-related behaviors on QoL among youth remains inconsistent. Conventional accelerometer-derived PA metrics and guidelines with a focus on whole weeks may not adequately characterize QoL relevant PA behavior.

OBJECTIVE

This study aims to a) identify clusters of accelerometer-derived PA profiles during weekend days among children and adolescents living in Switzerland, b) assess their cross-sectional and predictive association with overall QoL and its dimensions, and c) investigate whether the associations of QoL with the newly identified clusters persist upon adjustment for the commonly used PA metrics moderate-to-vigorous physical activity (MVPA) and time spent in sedentary behavior (SB).

METHODS

The population-based Swiss children's Objectively measured PHYsical Activity (SOPHYA) cohort among children and adolescents aged 6 to 16 years was initiated at baseline in 2013. PA and QoL information was obtained twice over a five-year follow-up period. The primary endpoint is the overall QoL score and its six dimension scores obtained by KINDL® questionnaire. The primary predictor is the cluster membership of accelerometer-derived weekend PA profile. Clusters were obtained by applying the k-medoid algorithm to the distance matrix of profiles obtained by pairwise alignments of PA time series using the Dynamic Time Warping (DTW) algorithm. Secondary predictors are accelerometer-derived conventional PA metrics MVPA and SB from two combined weekend days. Linear regression models were applied to assess a) the cross-sectional association between PA cluster membership and QoL at baseline and b) the predictive association between PA cluster membership at baseline and QoL at follow-up, adjusting for baseline QoL.

RESULTS

The study sample for deriving PA profile clusters consisted of 51.4% girls and had an average age of 10.9 [SD 2.5] years). The elbow and silhouette methods indicated that weekend PA profiles are best classified in two or four clusters. The most differentiating characteristic for the two-clusters classification ("lower activity" and "high activity"), and the four-clusters classification ("inactive", "low activity", "medium activity", and "high activity"), respectively was the participant's mean counts per 15-seconds epoch. Participants assigned to high activity clusters were younger and more often male. Neither the clustered PA profiles nor MVPA or SB were cross-sectionally or predictively associated with overall QoL. The only association of a conventional PA metrics with QoL while adjusting for cluster membership was observed between MVPA during the weekend days and social well-being with a mean score difference of 2.4 (95%CI: 0.3 to 4.5; p = 0.025).

CONCLUSION

The absence of strong associations of PA metrics for the weekend with QoL, except for the positive association between MVPA during the weekend days and social well-being, is in line with results from two randomized studies not showing efficacy of PA interventions on youth QoL. But because PA decreases with age, its promotion and relevance to QoL remain important research topics. Larger longitudinal study samples with more than two follow-up time points of children and adolescents are needed to derive new novel accelerometer-derived PA profiles and to associate them with QoL dimensions.

Age-gender differences in the relationships between physical and mental health

Previous studies have identified that smoking, exercise and breadth of social interaction mediate the strong associations between physical and mental health. However, these studies have been restricted to older populations, have not explored differences by gender, and have not considered online social interaction. We explore how the effects of four mediators (exercise, smoking, in-person and online social interaction) of the two-way relationships between past and future physical and mental health vary across eight age and gender groups. We use data from a representative sample of the UK population consisting of 175,779 observations on 41,995 adults from Understanding Society (UKHLS) between 2009 and 2019. Within a mediation framework, we estimate the percentage of the total effects that can be explained by the proposed mediating factors. We show that exercise, smoking, in-person and online social interaction are significant mediators of the effect of mental health on future physical health. In-person social interaction is the largest of these, accounting for 2.3% of the total effect. Smoking, in-person and online interaction are significant mediators of the effect of physical health on future mental health. Again, in-person interaction is the largest of these, accounting for 3.0% of the total effect. The percentages of the total effects mediated by each factor differ substantially by age and gender. Seeking to avoid the harmful effects of poor physical health on future mental health should focus on increasing physical activity in older men, and on increasing in-person social interaction in both men and women. Seeking to avoid the harmful effects of poor mental health on future physical health should focus on increasing physical activity and in-person social interaction in older men and women, and on reducing smoking in younger men and women.

The Association between Internet Use and Physical Exercise among Middle-Aged and Older Adults-Evidence from China

BACKGROUND

In an aging and digital society, Internet use is significantly associated with residents' physical exercise. This study aimed to explore the association between Internet use and physical exercise among Chinese middle-aged and older adults in two respects: Internet use and the purpose of Internet use.

METHODS

The data used in this study were obtained from the 2018 China Health and Retirement Longitudinal Study (CHARLS) conducted by Peking University. The logit model and the ordered probit model were used to analyze the association between Internet use and physical exercise, and the substitution variable method was used to examine the robustness of the results.

RESULTS

(1) Internet use and the frequency of Internet use significantly increased the probability and frequency of middle-aged and older adults' participation in physical exercise (p < 0.001). (2) "Watching news", "chatting" and "watching videos" via the Internet were positively associated with physical exercise, while "playing games" had no impact. (3) Internet use had a greater impact on physical exercise participation among middle-aged adults and those living in urban areas than among older adults and those living in rural areas.

CONCLUSIONS

This study suggests that Internet use among middle-aged and older adults is positively associated with their participation in physical exercise; the government should try to increase the popularity of Internet use to encourage their participation in physical exercise.

Differences in healthy lifestyle habits in university students as a function of academic area

Background

It is known that the promotion and acquisition of healthy attitudes is a key factor depending on the academic training provided by the university studies on which students are enrolled.The aim of the present research is to analyse and compare lifestyle habits and health-related quality of life (HRQoL) as a function of academic training.

Methods

A cross-sectional study with a volunteer convenience sample of 707 undergraduate participants aged (21.98 ± 3.50 years). Students were divided into four different groups according to their area of academic training. Socio-demographic variables, adherence to the Mediterranean diet (MD), physical activity (PA) engagement and HRQoL were recorded.

Results

PA and sport science students reported better scores in PA (6342.39 ± 2313.99 metabolic equivalents [METs]; P = 0.000), MD adherence (6.33 ± 2.69; P = 0.000) and HRQoL in physical and mental health (MH; 54.85 ± 9.18; 53.70 ± 13.6; P = 0.000). In contrast, non-health-related sciences (NHRS) students reported the lowest scores on assessed items. Students with a medium/high monthly salary reported better MD adherence (6.16 ± 3.07; P = 0.012). In addition, females reported better scores (6.41 ± 2.65; P = 0.000) than males. Further, males indicated better perceptions of MH (46.52 ± 18.84; P = 0.014). Moreover, university students with a high level of MD adherence were revealed to engage in more PA (5181.17 ± 2813.35 METs; P = 0.000) and have better HRQoL with regards to both physical (54.76 ± 8.84; P = 0.000) and MH (48.11 ± 16.73; P = 0.000).

Conclusions

Outcomes point to differences in MD adherence, PA and HRQoL according to academic training. NHRS students who did not know healthy habits reported lower scores for all studied items. This indicates the need for health interventions at universities.

Exploring Mediation Effects of Gait Speed, Body Balance, and Falls in the Relationship between Physical Activity and Health-Related Quality of Life in Vulnerable Older Adults

The present study aimed to examine whether gait speed (GS), body balance (BB), and falls mediated the relationship between physical activity (PA) and health-related quality of life (HRQoL) in community-dwelling older adults. This is a cross-sectional study that included 305 men and 314 women (69.5 ± 5.6 years), residing in the Autonomous Region of Madeira, Portugal. HRQoL and PA were assessed using the SF-36 and Baecke Questionnaires, respectively. While BB was obtained by the Fullerton Advance Balance (FAB) scale, GS by the 50-foot (15 m) walk test, and the frequency of falls was obtained by self-report. According to the analyses, when GS and BB were placed concomitantly as mediators, the direct effect revealed by the model revealed a non-significant relationship between PA and falls. Thus, in the context of falls, GS and BB partially mediated the association between PA and HRQoL in approximately 29.7%, 56%, and 49.2%, respectively. The total HRQoL model explained a variance of 36.4%. The results can help to understand the role that GS, BB, and falls play in the relationship between PA and HRQoL of the vulnerable older adult population.

Exploring the Role of Physical Activity in Mediating the Association between Educational Level and Health-Related Quality of Life in an Adult Lifespan Sample from Madeira Island

Background: People more socioeconomically vulnerable tend to have a poorer health-related quality of life (HRQoL). Studies are trying to analyse the factors that may condition this relationship, including physical activity (PA), which may influence the relationship between socioeconomic status (SES) and HRQoL. This study aimed to analyse the relationship between SES and HRQoL through specific domains of PA. Methods: A total of 381 adults (≥18 years) from the Autonomous Region of Madeira completed the measurements. Mediation analyses using bootstrapping methods adjusted for confounding variables were performed to relate SES and HRQoL; the latter was evaluated using the physical component score (PCS) of the SF-12, the mental component score (MCS) of the SF-12, and the total score in the SF-12 questionnaire (SF-12 score), through physical activity. Results: Educational level was positively related to PCS and SF-12 score. Leisure-time PA (not including sports PA) and PA at work, as single mediating variables, did not mediate the relationship between SES and HRQoL. The total PA suppressed the socioeconomic gradient of HRQoL by 8–10%, 39–46%, and 15–16%, respectively, for the PCS, MCS, and the SF-12 score; sports PA mediated the relationship by 13–16%, 50%, and 15–21%, respectively. Conclusions: The results suggest that sports PA contributes to reducing the socioeconomic gradient of HRQoL.