Factors increasing the risk for psychosocial stress among Korean adults living in rural areas: using generalized estimating equations and mixed models.
10.1186/s40557-017-0209-5
- Author:
Ju Hyun NAM
1
;
Myeong Seob LIM
;
Hyun Kyeong CHOI
;
Jae Yeop KIM
;
Sung Kyeong KIM
;
Sung Soo OH
;
Sang Baek KOH
;
Hee Tae KANG
Author Information
1. Department of Occupational and Environmental Medicine, Wonju Severance Christian Hospital, Wonju College of Medicine, Yonsei University, Wonju, Korea. oemkang@yonsei.ac.kr.
- Publication Type:Original Article
- Keywords:
Sleep duration;
Exercise;
Sedentary time;
Stress;
Population-based study;
ARIRANG cohort
- MeSH:
Adult*;
Atherosclerosis;
Cohort Studies;
Farmers;
Follow-Up Studies;
Gangwon-do;
Humans;
Korea;
Life Style;
Occupations;
Odds Ratio;
Risk Factors;
Rural Population
- From:Annals of Occupational and Environmental Medicine
2017;29(1):53-
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: This study was conducted to analyze the distribution of the psychosocial well-being index among adults living in two rural communities in Korea and to examine its correlation with lifestyle variables such as sleep duration, regular exercise, and sedentary time. METHODS: Using the cohort data of the Atherosclerosis Risk of a Rural Area Korean General Population, this study examined 3631 participants living in Wonju and Pyeongchang in Gangwon Province; their preliminary data were established from 2005 to 2007 while their follow-up data were collected 3 years later. This study investigated demographic characteristics, lifestyle habits, disease history, Psychosocial Well-being Index-Short Form (PWI-SF) scores, sleep duration, regular exercise, and sedentary time during work. Using repeated measures ANOVA, this study examined how the variables and PWI-SF scores changed over the course of 3 years and identified the correlation between them based on mixed model analysis. Afterwards, using the generalized estimation equation, this study identified each variable's risk towards the PWI-SF high-risk group and performed a stratified analysis by occupation after dividing the participants into farmers and non-farmers. RESULTS: The PWI-SF high-risk group was found to be 18.9% of the participants from preliminary data and 15.5% from follow-up data. The odds ratio towards the PWI-SF high-risk group was 1.503 (95% CI 1.241–1.821) in the short sleep duration group and 1.327 (95% CI 1.136–1.550) in the non-regular exercise group. A stratified analysis by occupation showed that middle and long sedentary time in the white-collar group increased the risk toward the PWI-SF high-risk group. CONCLUSIONS: Short sleep duration, no regular exercise, and long sedentary time in the white-collar group were identified as risk factors toward the PWI-SF high-risk group in the rural communities, and policy interventions are needed to address this issue.
