빅데이터를 이용한 임신 여성의 식이패턴이 우울감에 미치는 연관성 분석 - 혈중 중금속 농도의 매개효과를 중심으로
Analysis of the Association of Dietary Patterns With Depression in Pregnant Women using Big Data – Mediating Effect of Blood Heavy Metal Concentration
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Abstract
Objectives: This study is to examine the mediating association of blood heavy metal (lead, cadmium, and mercury) concentration on dietary pattern and depression during pregnancy. Methods: From Korean Children’s ENvironmental health Study (Ko-CHENS), a nationwide birth cohort study in Korea, 4,644 mothers in early pregnancy (<20 weeks) during 2015-2018 with normal range of calorie uptake and consequent singleton birth records were included in the analysis. Biological samples including blood heavy metal levels, delivery records, and questionnaire data were collected. Depression symptoms were measured by using the Center for Epidemiologic Studies Depression Scale (CES-D). For mediation regression analysis, 3-step methods proposed by Baron and Kenny were used. The statistical analysis was performed by using R. Results: Three dietary patterns for pregnant women were identified and examined for the effect of heavy metals—pattern 1: vegetables, legumes, mushrooms, and fish-oriented meals, pattern 2: noodles, pizza/hamburger, and meat-oriented meals, and pattern 3: bread, jam, and snack-oriented meals. While lead did not show significant indirect effect on dietary pattern 1 causing depression (B=0.001, 95% confidence interval, CI=0, 0.024), it had significant indirect effect on dietary pattern 2 (B=0.001, 95% CI=0.001, 0.023) and 3 causing depression (B=-0.003, 95% CI=-0.045, -0.006). Conclusions: The mediation effect of lead was confirmed in the relationship between dietary patterns and depression in pregnancy. Therefore, by controlling diet, we can reduce the negative effects of heavy metals on depression during pregnancy.
