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)

Abstract

ObjectivesTo 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.DesignA 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.SettingData were obtained from the Fifth Korea National Health and Nutrition Examination Survey (2010–2012).ParticipantsThe sample included 7337 male and 9908 female participants aged ≥19 years.Outcome measureObesity was defined as body mass index of ≥25, according to a guideline for Asians.ResultsIn 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%.ConclusionsThe 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.

The Intersectionality of Gender and Wealth in Adolescent Health and Behavioral Outcomes in Brazil: The 1993 Pelotas Birth Cohort

“…Regarding overweight and obesity, other studies carried out in adolescents also showed a higher prevalence in boys compared with girls [[34], [35], [36], [37]]. Most of the literature from high-income countries shows that socioeconomic position is inversely correlated with obesity in both sexes, the findings being more consistent in women than in men [27,[38], [39], [40], [41]]. The situation in Brazil is somewhat different, as studies on adults [42,43] show a direct association with income in men—similar to what we report—but an inverse association among women, which we did not document.…”

“…Less attention is given to the intersectionality between these two stratifiers. Few studies have addressed how socioeconomic position intersects with sex and reflected on the influence of gender norms to shape health inequalities, particularly during adolescence [7,[27], [28], [29]].…”

Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults

“…In developing countries, the SES-obesity relationship was found to be more complex: in low-income developing countries, those living in more affluent circumstances are more likely to experience overweight and obesity for both men and women, whereas in middle-income countries, the relationship between SES and obesity is largely mixed for men and predominantly negative for women ( 15 ). Notably, gender appears to play an important role in the SES-obesity relationship, and it was said that ignoring gender differences when examining the SES-obesity association may lead to targeting of wrong populations for reducing obesity prevalence and its resultant socioeconomic gradients ( 17 ). Additionally, researches on the SES-obesity association were mainly concentrated in developed countries and developing urban cities, with very limited research in rural areas of developing countries.…”

A Reversal of the Association between Education Level and Obesity Risk during Ageing: A Gender-Specific Longitudinal Study in South Korea

“…Model 1 was a cross-sectional model that considered only participants at baseline (Wave 1). Model 2 was a longitudinal model with no covariates for all observations of all considered waves (1)(2)(3)(4)(5)(6). As this is a longitudinal dataset, it is likely for observations to be temporally correlated within the same participant; hence, we employed a mixed logistic regression model with two levels: level 1 with observations and level 2 with participants.…”

“…Personal characteristics such as demographic factors, socioeconomic status, lifestyle, and health conditions can determine eating and physical behaviours that lead to a greater risk of being overweight or obese. These obesity risk factors include low levels of education [6], blue-collar occupation [7], residing in urban areas [7], smoking [8], alcohol intake [9], routine physical exercise [10], psychosocial stress [11], and chronic diseases [12].…”