Wang Xiao, Zhang Jianming, Du Jing, Zhang Weichunbai, Ma Yan, Yang Yi, Shen Shi
National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, NHC Key Laboratory of Public Nutrition and Health, Beijing 100050, China.
Beijing Center for Disease Control and Prevention, Beijing 100013, China.
Wei Sheng Yan Jiu. 2025 May;54(3):478-494. doi: 10.19813/j.cnki.weishengyanjiu.2025.03.019.
To understand the dietary pattern characteristics of pregnant women in early pregnancy and analyze the association between these dietary patterns and weight changes in early pregnancy.
Using the birth cohort of the China Birth Cohort Study(CBCS), we analyzed the early pregnancy information and food frequency questionnaire data of 3, 540 subjects who met the inclusion and exclusion criteria at the Shenzhen sub-center from July 2018 to January 2021. Dietary patterns were extracted using factor analysis. Logistic regression models were used to analyze the associations between these dietary patterns and weight changes in early pregnancy. Finally, gestational age was divided into three groups using the tertile method, and stratified analyses were conducted for each group.
The low weight change group comprised 914 individuals(25.82%), the moderate weight change group included 1442 individuals(40.73%), and the high weight change group consisted of 1184 individuals(33.45%). The result of the univariate analysis showed that there were statistically significant differences in the distribution of gestational age, age, ethnicity, educational level, occupation, pre-pregnancy body mass index(BMI), presence of early pregnancy reactions, and average annual household income over the past two years among the subjects with low, moderate, and high weight changes in early pregnancy. Factor analysis identified four major dietary patterns: the high-protein dietary pattern, the vegetarian dietary pattern, the legume-nut dietary pattern, and the snack-dairy dietary pattern, with a cumulative variance contribution rate of 42.45%. The result of the Logistic regression analysis showed that, after adjusting for gestational age, age, ethnicity, educational level, occupation, pre-pregnancy BMI, early pregnancy reactions(nausea, vomiting), and average annual household income over the past two years, the high-protein dietary pattern in T3 group(OR=0.635, 95%CI 0.427-0.946) and the legume-nut dietary pattern in T2 group(OR=0.675, 95%CI 0.467-0.975) were both significantly negatively correlated with the low weight change group. After stratification by gestational age, the high-protein dietary pattern in T3 group(OR=0.472, 95%CI 0.211-0.862) in the population at 11-13 weeks of gestation and the legume-nut dietary pattern in T2 group(OR=0.542, 95%CI 0.304-0.965) in the population at 9-11 weeks of gestation remained significantly negatively correlated with the low weight change group.
The high-protein dietary pattern and the legume-nut dietary pattern have a certain positive impact on the rational weight gain of pregnant women in early pregnancy.
了解孕早期孕妇的饮食模式特征,分析这些饮食模式与孕早期体重变化之间的关联。
利用中国出生队列研究(CBCS)的出生队列,我们分析了2018年7月至2021年1月在深圳分中心符合纳入和排除标准的3540名受试者的孕早期信息和食物频率问卷数据。采用因子分析提取饮食模式。使用逻辑回归模型分析这些饮食模式与孕早期体重变化之间的关联。最后,采用三分位数法将孕周分为三组,并对每组进行分层分析。
低体重变化组914人(25.82%),中等体重变化组1442人(40.73%),高体重变化组1184人(33.45%)。单因素分析结果显示,孕早期体重变化低、中、高的受试者在孕周、年龄、种族、教育程度、职业、孕前体重指数(BMI)、早孕反应情况以及过去两年家庭年均收入分布上存在统计学显著差异。因子分析确定了四种主要饮食模式:高蛋白饮食模式、素食饮食模式、豆类-坚果饮食模式和零食-乳制品饮食模式,累积方差贡献率为42.45%。逻辑回归分析结果显示,在调整孕周、年龄、种族、教育程度、职业、孕前BMI、早孕反应(恶心、呕吐)以及过去两年家庭年均收入后,T3组的高蛋白饮食模式(OR=0.635,95%CI 0.427-0.946)和T2组的豆类-坚果饮食模式(OR=0.675,95%CI 0.467-0.975)均与低体重变化组显著负相关。按孕周分层后,孕11-13周人群中T3组的高蛋白饮食模式(OR=0.472,95%CI 0.211-0.862)和孕9-11周人群中T2组的豆类-坚果饮食模式(OR=0.542,95%CI 0.304-0.965)仍与低体重变化组显著负相关。
高蛋白饮食模式和豆类-坚果饮食模式对孕早期孕妇合理增重有一定的积极影响。