Gender-specific interactions between education and income in relation to obesity: a cross-sectional analysis of the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V)

OBJECTIVES To identify gender-specific associations between education and income in relation to obesity in developed countries by considering both the interaction-effect terms of the independent variables and their main-effect terms. DESIGN A cross-sectional study. Education and income levels were chosen as socioeconomic status indicators. Sociodemographics, lifestyles and medical conditions were used as covariates in multivariable logistic regression models. Adjusted ORs and predicted probabilities of being obese were computed and adjusted for a complex survey design. SETTING Data were obtained from the Fifth Korea National Health and Nutrition Examination Survey (2010-2012). PARTICIPANTS The sample included 7337 male and 9908 female participants aged ≥19 years. OUTCOME MEASURE Obesity was defined as body mass index of ≥25, according to a guideline for Asians. RESULTS In models with no interaction-effect terms of independent variables, education was significantly associated with obesity in both men and women, but income was significant only in women. However, in models with the interaction-effect terms, education was significant only in women, but income was significant only in men. The interaction effect between income and education was significant in men but not in women. Participants having the highest predicted probability of being obese over educational and income levels differed between the two types of models, and between men and women. A prediction using the models with the interaction-effect terms demonstrated that for all men, the highest level of formal education was associated with an increase in their probability of being obese by as much as 26%. CONCLUSIONS The well-known, negative association between socioeconomic status and obesity in developed countries may not be valid when interaction effects are included. Ignoring these effects and their gender differences may result in the targeting of wrong populations for reducing obesity prevalence and its resultant socioeconomic gradients.