Journal of Research in Medical Sciences1735-1995229201709271069210692EN20170724<span class="fontstyle0">Background: </span><span class="fontstyle2">In this study, we aimed to determine comprehensive  maternal characteristics associated with birth weight using Bayesian modeling. </span><span class="fontstyle0">Materials and Methods: </span><span class="fontstyle2">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 e?ective 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. </span><span class="fontstyle0">Results: </span><span class="fontstyle2">Tere 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 fber 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. </span><span class="fontstyle0">Conclusion: </span><span class="fontstyle2">Higher maternal macro? and  micro?nutrient intake during pregnancy was associated with a lower risk of delivering low birth weight infants. Tese fndings support recommendations  to expand intake of nutrients during pregnancy to high level.</span> <br style="font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-align: -webkit-auto; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px;" />http://jrms.mui.ac.ir/index.php/jrms/article/view/10692http://jrms.mui.ac.ir/index.php/jrms/article/download/10692/5549