Association between social network structure and physical activity in middle-aged Korean adults

Association between social networks and symptoms of post-traumatic stress during the pandemic: Cohort study in South Korea

BACKGROUND

This study estimated the association between pre-pandemic social network properties and symptoms of posttraumatic stress during the coronavirus disease 2019 (COVID-19) pandemic in South Korea.

METHODS

We conducted four online mental health surveys during COVID-19 (from March 14, 2020, to December 11, 2021) among individuals enrolled in a community-based cohort study (previously recruited from 2013 to 2018). Among 4060 people interviewed at the pre-pandemic baseline, 2652 individuals (men = 951, women = 1701) who responded to at least one of the four surveys conducted were included. At baseline, each individual's social network, including size and average closeness, was measured in an egocentric way. Post Traumatic Stress Disorder Checklist for DSM-5 (PCL-5) was measured at each survey point. A generalized linear model and a generalized linear mixed model were used after stratified by sex.

RESULTS

Among men, network size was negatively associated with total PCL-5 score (b = -0.42, SE = 0.16, p = 0.002). The magnitude of the association increased over time and was maximal by the 4th survey (b = -0.65, SE = 0.31, p = 0.037). Among women, average closeness was negatively associated with the total PCL-5 score (b = -1.16, SE = 0.37, p = 0.002). In analyses disaggregated by symptom clusters, social networks were associated explicitly with symptoms of intrusion and mood but not with avoidance and arousal symptoms.

CONCLUSION

In this cohort of adults followed for more than a year during the outbreak of COVID-19 in South Korea, social networks established before the onset of the COVID-19 pandemic had a protective association against developing symptoms of PTSD during the first two years of the pandemic.

Effect of online and offline social network group clusters on life satisfaction across age groups

Background

Positive social relationships are critical for better subjective well-being across ages. Future research will benefit from examining how to improve life satisfaction by utilizing social groups in new, ever-changing social and technological contexts. This study aimed to evaluate the effect of online and offline social network group clusters on life satisfaction across different age groups.

Methods

Data were derived from the Chinese Social Survey (CSS) (2019), which is a nationally representative survey. We adopted a K-mode cluster analysis algorithm to categorize participants into four clusters according to their online and offline social network groups. ANOVA and chi-square analysis were used to understand the associations among age groups, social network group clusters, and life satisfaction. Multiple linear regression was applied to identify the association between social network group clusters and life satisfaction across age groups.

Results

Younger and older adults had higher life satisfaction than middle-aged adults. Individuals who joined diverse social network groups had the highest life satisfaction, followed by those who joined personal and working social groups, while those who joined restricted social groups had the lowest life satisfaction (F = 81.19, p < 0.001). According to the results of multiple linear regression, individuals who belonged to diverse social groups had higher life satisfaction than those who belonged to restricted social groups among adults aged 18-59 years, except students (p < 0.05). Individuals who joined personal and working social groups had higher life satisfaction than those who joined restricted social groups among adults aged 18-29 and 45-59 years (β = 2.15, p < 0.01; β = 1.45, p < 0.01).

Conclusions

Interventions to promote participation in diverse social network groups among adults aged 18-59 years, except for students, are highly recommended to improve life satisfaction. Health practitioners could provide interventions to encourage young and middle-aged adults to join both personal and working social groups.

Socio-demographics, neighborhood characteristics, time use, and leisure-time physical activity engagement patterns over the life course

Physical inactivity remains a major public health challenge today. Understanding the determinants of changes in habitual leisure-time physical activity patterns by type across the life course is important for developing targeted interventions. This study presents a multiple discrete-continuous extreme value model to examine the determinants of habitual participation in and time allocation to multiple leisure-time physical activities over the life course. A comprehensive set of socio-demographics, life transitions, neighborhood characteristics, and time-related factors are considered as determinants of each activity type, including sports, recreational walking, cycling, outdoor playing, and dog walking. Results estimated on retrospective survey data collected in the Netherlands show significant differences in the determinants of the different types of leisure-time physical activity. Social-demographic factors have a strong influence on sports participation, followed by recreational walking, cycling, outdoor playing, and then dog walking. Life transitions have different effects. A change in marital status appears to be the most important life event for sports participation while changing jobs is the most important event for the other two activities. Neighborhood characteristics primarily affect participation in recreational walking, cycling, outdoor playing, and dog walking. As for time-related factors, they mainly impact sports engagement. The findings of this study could help develop effective interventions to promote leisure-time physical activity participation during life transitions and encourage healthy living.

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The determinants of different types of leisure-time physical activity differ significantly.

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Social-demographic factors have a strong impact on sports participation, followed by recreational-WCP, and then dog walking.

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Changes in marital status and work seem to be important events for joining sports and the other two activities, respectively.

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Neighborhood characteristics primarily affect participation in recreational-WCP and dog walking.

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Study-related physical activity time and work-related physical activity time mainly impact sports participation.

The Influence of a School Social Network Intervention on Adolescent's Health Behaviors: A Gender-Specific Agent-Based Model

Introduction

Adolescence is a crucial stage for health behavior development, which is associated with health in adulthood. School closures caused by the coronavirus disease 2019 (COVID-19) pandemic have exposed adolescents to an increased risk of obesity due to a lack of physical activity. Although social network interventions provide an effective approach for promoting health-related behavior, current practices neglect gender differences in adolescent behavioral patterns and emotional preferences. The aim of this study was to examine the effectiveness of centrality-based methods integrated with of gender contexts in a social network intervention to improve adolescent's health behavior.

Methods

We developed an agent-based model (ABM) that supports the small-world characteristics of adolescent social networks. Health-related data for junior middle school students (n = 234, 48% girls) were collected in November 2018, 2019 and 2020 in Tianjin, China. We simulated multiple network-based interventions with different criteria for influential agents (i.e., betweenness centrality, closeness centrality, eigenvector centrality, and PageRank) and a random condition. The rules for generating peer influence and accelerating behavioral changes were based on the diffusion of innovations theory, with gender specifications.

Results

After the school closures, there was a significant increase in the prevalence of overweight and obesity among adolescents, with a greater increase in girls than in boys (+8.85% vs. +1.65%, p < 0.001). Simulations showed that centrality-based network interventions were more effective than the random condition (average 6.17% per tick vs. 5.22% per tick, p < 0.05), with a higher efficiency in girls than boys (average 3.68% vs. 2.99% per tick, p < 0.05). PageRank outperformed other centrality conditions at the population level (6.37% per tick, p < 0.05). In girls, betweenness centrality was the best method (3.85% per tick, p < 0.05), while in boys, PageRank still had the greatest efficiency (3.21% per tick, p < 0.05).

Conclusions

We found evidence for gender differences in the negative impact of COVID-19-related school closures and the potential for centrality-based social network interventions to affect adolescent health behavior. Therefore, we emphasize the importance of gender-specific targeting strategies to further promote health-related school programs in the post-pandemic era.

Association Between Social Network and Cognitive Function: A Cross-Sectional Assessment From the Cardiovascular and Metabolic Diseases Etiology Research Center Cohort (2013-2018)

BACKGROUND

This study aimed to investigate how social networks are associated with cognitive function in the middle-aged and elderly Korean population.

METHODS

A total of 7,704 individuals over the age of 50 were included from the baseline recruitment of the Cardiovascular and Metabolic Diseases Etiology Research Center cohort from the years 2013 to 2018. Egocentric social network characteristics including network size, intimacy, and frequency of face-to-face meetings were measured as exposures, and the Korean version of Mini-Mental State Examination (K-MMSE) score was measured to reflect general cognitive function as an outcome. We also stratified the analysis by income level into tertiles, with income caps of 42,000 thousand won and 72,000 thousand won. A general linear regression model was used, adjusting for age, gender, socioeconomic factors, lifestyle factors, depressive symptoms, and study settings.

RESULTS

Social network properties were positively associated with cognitive function in both men and women. However, the specific estimates varied according to gender and income level. In men, frequency was most significantly associated with cognitive function (standardized β = 0.093, p-value <0 .0001). In women, the strength of the association with cognitive function was found in size (standardized β = 0.055, p-value = 0.001). The effect modification of income level could be seen in the association between frequency and cognitive function. The strongest association between frequency and cognitive function was found in the middle income group in men (standardized β = 0.114, p-value = 0.0063), and the low income group in women (standardized β = 0.076, p-value = 0.0039).

CONCLUSION

There were positive associations between social network properties (i.e., size, intimacy, and frequency of face-to-face meetings) and cognitive function. The degree of association varied according to social network properties, gender, and income level. Overall, among social network properties, social network size was an important factor in the cognition of women, whereas frequency was important in the cognition of men.