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Cardiovascular and Metabolic Risk
Associations between social network properties and metabolic syndrome and the mediating effect of physical activity: findings from the Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort
  1. Kwanghyun Kim1,
  2. Sun Jae Jung1,2,
  3. Jong Min Baek1,
  4. Hyeon Woo Yim3,
  5. Hyunsuk Jeong3,
  6. Dae Jung Kim4,
  7. Sungha Park5,
  8. Yoosik Youm6,
  9. Hyeon Chang Kim1
  1. 1Department of Preventive Medicine, Yonsei University College of Medicine, Seodaemun-gu, Republic of Korea
  2. 2Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  3. 3Department of Preventive Medicine, Catholic University of Korea, Seoul, Republic of Korea
  4. 4Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Republic of Korea
  5. 5Yonsei Health System Cardiology Hospital Division of Cardiology, Yonsei University College of Medicine, Seodaemun-gu, Republic of Korea
  6. 6Department of Sociology, Yonsei University, Seodaemun-gu, Republic of Korea
  1. Correspondence to Dr Sun Jae Jung; sunjaejung{at}yuhs.ac

Abstract

Introduction Social isolation and loneliness are positively associated with metabolic syndrome. However, the mechanisms by which social isolation affects metabolic syndrome are not well understood.

Research design and methods This study was designed as a cross-sectional study of baseline results from the Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort. We included 10 103 participants (8097 community-based low-risk participants, 2006 hospital-based high-risk participants) from the CMERC Cohort. Participants aged 65 years or older were excluded. Multiple imputation by chained equations was applied to impute missing variables. The quantitative properties of social networks were assessed by measuring the ‘size of social networks’; qualitative properties were assessed by measuring the ‘social network closeness’. Metabolic syndrome was defined based on the National Cholesterol Education Program Adult Treatment Panel III criteria. Multivariate logistic regression analyses were conducted to assess association between social network properties and metabolic syndrome. The mediating effects of physical inactiveness, alcohol consumption, cigarette smoking and depressive symptoms were estimated. Age-specific effect sizes were estimated for each subgroup.

Results A smaller social network was positively associated with higher prevalences of metabolic syndrome in all subgroups, except the high-risk male subgroup. There was no clear association between social network closeness and metabolic syndrome. In community-based participants, an indirect effect through physical activity was detected in both sexes; however, in hospital-based participants, no indirect effects were detected. Cigarette smoking, alcohol consumption and depression did not mediate the association. Age-specific estimates showed that the indirect effect through physical activity had a greater impact in older participants.

Conclusions A smaller social network is positively associated with metabolic syndrome. This trend could be partially explained by physical inactivity, especially in older individuals.

  • metabolic syndrome
  • physical activity and health
  • social determinants
  • public health
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjdrc-2020-001272

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    Footnotes

    • Correction notice This article has been corrected since it was published. Funding statement has been updated.

    • Contributors Study design and concept: KK and SJJ. Systematic review on previous related studies: KK and JMB. Acquisition, analysis and interpretation of data: KK, SJJ, HCK, DJK, SP and YY. Statistical analysis: KK. Drafting of the manuscript: KK. Critical revision of the manuscript for important intellectual content: SJJ, JMB, HCK, HWY, HJ and YY. Obtained funding: SJJ, HCK, DJK and SP. Study supervision: SJJ.

    • Funding This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Grant number 2018R1C1B5083722 and grant number 2020R1C1C1003502).

    • Patient consent for publication Not required.

    • Ethics approval The study protocols were approved by the institutional review boards of Severance Hospital, Yonsei University Health System, Seoul, Korea (4-2013-0661, 4-2013-0581) and Ajou University Hospital, Suwon, Korea (AJIRB-BMR-SUR-13-272). All procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available on reasonable request. The Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort is a cohort study, which aims to identify novel risk factors of cardiovascular and metabolic diseases and to develop evidence-based prevention strategies for those diseases. The CMERC Cohort consists of two prospective cohorts, a community-based general population cohort and its sister cohort, which is a hospital-based high-risk patient cohort. Baseline study was conducted between 2013 and 2018, and follow-up study is currently in progress. Baseline measurements assessed sociodemographic factors, medical history, health-related behaviors, psychological health, social network and support, anthropometry, body composition and resting blood pressure and comprised electrocardiography, carotid artery ultrasonography, fasting blood analysis and urinalysis. Please contact cmerc@yuhs.ac for access to CMERC data.