Using the socioecological model to explore factors associated with obesity among reproductive age women
Amanda Gilbert1, Alicia Persaud1, Sarah Farabi2,3
1Prevention Research Center in St. Louis, Brown School at Washington University in St. Louis, St. Louis, MO, United States.
Introduction:
Women of reproductive age (18-44 years) are at an increased risk of developing obesity due to pregnancy, life-transitions, and marginalization. Obesity in women negatively affects women's health and pregnancy outcomes and can increase risk their children will develop obesity. Less is known about obesity risk at the interpersonal and environmental levels for women of reproductive age. This study uses the socioecological model to explore women's obesity risk across ecological levels.
Materials And Methods:
A secondary cross-sectional analysis was conducted using baseline data (March 2019-June 2022) from the cluster-randomized Healthy Eating and Active Living Taught at Home (HEALTH) Dissemination and Implementation study. Descriptive statistics and multivariate logistic regression models were used to determine associations between individual, interpersonal, and environmental level factors with weight status (overweight vs. obesity).
Results:
Among 221 participants (43% Hispanic/Latino, 51% High school or less), 37% were overweight and 63% had obesity. Interpersonal and environmental factors were not statistically significantly associated with obesity relative to overweight in bivariate analyses. In multivariate models, individual level factors of high/moderate physical activity (OR = 0.47, 95% CI: 0.26,0.84, p = 0.01) and food insecurity (OR = 2.51, 95% CI: 1.33,4.71, p = 0.00) were statistically significantly related to risk of having obesity compared to being overweight.
Discussion:
Physical activity and food insecurity were associated with obesity in this study. Associations with interpersonal and environmental level factors were not statistically significant, which may be due to limited sample size or measures available to assess these levels. Future studies should investigate structural determinants (e.g., economic, neighborhood and physical environment), which may drive physical activity and food insecurity.
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