L Song1, L Shen1, H Li1, B Liu1, X Zheng1, L Zhang1, S Xu2, Y Wang1. 1. Department of Maternal and Child Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2. Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract
AIMS: The relationship between socio-economic status and gestational diabetes mellitus has received little attention. The purpose of this study was to investigate the association between socio-economic status and risk of gestational diabetes. METHODS: Data were obtained from the ongoing Healthy Baby Cohort study in Hubei Province, China, in 2012-2014. Information on educational level and household income was collected using standard questionnaires during face-to-face interviews. Gestational diabetes was defined based on the International Association of Diabetes and Pregnancy Study Group's criteria. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for gestational diabetes in relation to socio-economic status. RESULTS: Among 6886 participants, 1005 (14.6%) pregnant women were diagnosed with gestational diabetes. Higher educational level was inversely associated with risk of gestational diabetes (OR, 0.74; 95% CI, 0.58, 0.95 for high school and OR, 0.62; 95% CI, 0.50, 0.76 for college or above). After adjustment for potential confounders, the ORs for gestational diabetes were 0.77 (95% CI, 0.59, 1.00) and 0.65 (95% CI, 0.51, 0.83) for women with high school and college or above education, respectively, compared with women with less than high school education. No significant association between household income and gestational diabetes was observed after adjustment for potential confounders. Subgroup analysis showed that the reduced risk of gestational diabetes with higher educational level was more evident among women with a pre-pregnancy BMI < 24 kg/m2 (P for interaction = 0.022). CONCLUSIONS: Our findings suggested that educational level was a more robust predictor of gestational diabetes than household income among Chinese women.
AIMS: The relationship between socio-economic status and gestational diabetes mellitus has received little attention. The purpose of this study was to investigate the association between socio-economic status and risk of gestational diabetes. METHODS: Data were obtained from the ongoing Healthy Baby Cohort study in Hubei Province, China, in 2012-2014. Information on educational level and household income was collected using standard questionnaires during face-to-face interviews. Gestational diabetes was defined based on the International Association of Diabetes and Pregnancy Study Group's criteria. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for gestational diabetes in relation to socio-economic status. RESULTS: Among 6886 participants, 1005 (14.6%) pregnant women were diagnosed with gestational diabetes. Higher educational level was inversely associated with risk of gestational diabetes (OR, 0.74; 95% CI, 0.58, 0.95 for high school and OR, 0.62; 95% CI, 0.50, 0.76 for college or above). After adjustment for potential confounders, the ORs for gestational diabetes were 0.77 (95% CI, 0.59, 1.00) and 0.65 (95% CI, 0.51, 0.83) for women with high school and college or above education, respectively, compared with women with less than high school education. No significant association between household income and gestational diabetes was observed after adjustment for potential confounders. Subgroup analysis showed that the reduced risk of gestational diabetes with higher educational level was more evident among women with a pre-pregnancy BMI < 24 kg/m2 (P for interaction = 0.022). CONCLUSIONS: Our findings suggested that educational level was a more robust predictor of gestational diabetes than household income among Chinese women.
Authors: Li Jiang; Kun Tang; Laura A Magee; Peter von Dadelszen; Alec Ekeroma; Xuan Li; Enyao Zhang; Zulfiqar A Bhutta Journal: Nat Rev Endocrinol Date: 2022-09-15 Impact factor: 47.564