Concordance in the Health Behaviors of Couples by Age: A Cross-sectional Study

J Prev Med Public Health. 2018 Jan;51(1):6-14. doi: 10.3961/jpmph.17.137.

Abstract

Objectives: To investigate concordance in the health behaviors of women and their partners according to age and to investigate whether there was a stronger correlation between the health behaviors of housewives and those of their partners than between the health behaviors of non-housewives and those of their partners.

Methods: We used data obtained from women participants in the 2015 Korea Community Health Survey who were living with their partners. The outcome variables were 4 health behaviors: smoking, drinking, eating salty food, and physical activity. The main independent variables were the partners' corresponding health behaviors. We categorized age into 4 groups (19-29, 30-49, 50-64, and ≥ 65 years) and utilized multivariate logistic regression analysis, stratifying by age group. Another logistic regression analysis was stratified by whether the participant identified as a housewife.

Results: Data from 64 971 women older than 18 years of age were analyzed. Of the 4 health behaviors, the risk of smoking (adjusted odds ratio [aOR], 4.65; 95% confidence interval [CI], 3.93 to 5.49) was highest when the participant's partner was also a smoker. Similar results were found for an inactive lifestyle (aOR, 2.56; 95% CI, 2.45 to 2.66), eating salty food (aOR, 2.48; 95% CI, 2.36 to 2.62); and excessive drinking (aOR, 1.89; 95% CI, 1.80 to 1.98). In comparison to non-housewives, housewives had higher odds of eating salty food.

Conclusions: The health behaviors of women were positively correlated with those of their partners. The magnitude of the concordance differed by age group.

Keywords: Health behavior; Korea; Spouses; Women’s health.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Cross-Sectional Studies
  • Female
  • Health Behavior*
  • Humans
  • Male
  • Middle Aged
  • Republic of Korea
  • Spouses / psychology*
  • Spouses / statistics & numerical data
  • Young Adult