Comprehensive Maternal Characteristics Associated With Birth Weight: Bayesian Modeling in a Prospective Cohort Study From Iran Publisher

Summary: Bayesian modeling links higher maternal nutrient intake (vitamins, minerals, fiber, protein) to reduced risk of low birth weight infants. #MaternalNutrition #BirthWeight

Mansourian M¹ ; Mohammadi R² ; Marateb HR³ ; Yazdani A¹ ; Goodarzikhoigani M⁴ ; Molavi S⁵
Source: Journal of Research in Medical Sciences Published:2017

Abstract

Background: In this study, we aimed to determine comprehensive maternal characteristics associated with birth weight using Bayesian modeling. Materials and Methods: A total of 526 participants were included in this prospective study. Nutritional status, supplement consumption during the pregnancy, demographic and socioeconomic characteristics, anthropometric measures, physical activity, and pregnancy outcomes were considered as effective variables on the birth weight. Bayesian approach of complex statistical models using Markov chain Monte Carlo approach was used for modeling the data considering the real distribution of the response variable. Results: There was strong positive correlation between infant birth weight and the maternal intake of Vitamin C, folic acid, Vitamin B3, Vitamin A, selenium, calcium, iron, phosphorus, potassium, magnesium as micronutrients, and fiber and protein as macronutrients based on the 95% high posterior density regions for parameters in the Bayesian model. None of the maternal characteristics had statistical association with birth weight. Conclusion: Higher maternal macro- and micro-nutrient intake during pregnancy was associated with a lower risk of delivering low birth weight infants. These findings support recommendations to expand intake of nutrients during pregnancy to high level. © 2017 Journal of Research in Medical Sciences.