Association of dietary mineral mixture with depressive symptoms: A combination of Bayesian approaches

Shumin Chen; Jin Liu; Xiao Kang; Kaiwen Cui; Dongfeng Zhang

doi:10.1016/j.ypmed.2023.107661

Association of dietary mineral mixture with depressive symptoms: A combination of Bayesian approaches

Prev Med. 2023 Oct:175:107661. doi: 10.1016/j.ypmed.2023.107661. Epub 2023 Aug 11.

Authors

Shumin Chen¹, Jin Liu¹, Xiao Kang¹, Kaiwen Cui¹, Dongfeng Zhang²

Affiliations

¹ Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, Shandong 266071, People's Republic of China.
² Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, Shandong 266071, People's Republic of China. Electronic address: zhangdongfeng@qdu.edu.cn.

PMID: 37573955
DOI: 10.1016/j.ypmed.2023.107661

Abstract

The relationships between mixtures of multiple minerals and depression have not been explored. Therefore, we analyzed the relationship between the mixture of nine dietary minerals [calcium (Ca), phosphorus, magnesium (Mg), iron (Fe), zinc, copper (Cu), sodium, potassium (K), and selenium (Se)] and depressive symptoms in the general population. We screened 20,342 participants from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. We fitted the general linear regression, Bayesian kernel machine regression (BKMR), and Bayesian semiparametric regression models to explore associations and interactions. We obtained the relative importance of dietary minerals by calculating posterior inclusion probabilities (PIPs). The dietary intakes of minerals were obtained using the 24-h dietary recall interview, and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). The linear analysis showed that nine minerals were negatively associated with PHQ-9 scores. The BKMR analysis showed a negative association between the dietary mineral mixture and PHQ-9 scores, with Se having the largest PIP at 1.0000, followed by K (0.7784). We also observed potential interactions between Ca and Fe, Se and Fe, and K and Mg. Among them, the interaction of Ca and Fe had the largest PIP of 0.986. In addition, the overall effect was more pronounced in females than males, and Cu's PIP (0.8376) was higher in females. Two sensitivity analyses showed that our results were robust. Our study provides a basis for formulating nutritional intervention programs for depression in the future.

Keywords: BKMR; Bayesian semiparametric regression; Depressive symptoms; Dietary mineral intake; Interaction; NHANES.