Association of gestational metabolic syndrome with the Chinese Healthy Eating Index in mid-pregnancy: a cross-sectional study.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS Nutrition & Metabolism Pub Date : 2024-01-26 DOI:10.1186/s12986-024-00780-5

Hui Wu, Min-Hui Yi, Bing-Gang Liu, Yan Xu, Qin Wu, Yu-Hong Liu, Ling-Peng Lu

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Abstract

Background: This study aims to investigate the relationship between gestational metabolic syndrome (GMS) and the Chinese Healthy Eating Index (CHEI) in mid-pregnancy, and to identify potentially beneficial or high-risk dietary habits. We have developed a mid-pregnancy version of CHEI-2022, adapting the Chinese Healthy Eating Index to align with the food quantity recommendations outlined in the 2022 Dietary Guidelines for Chinese Residents for mid-pregnancy.

Methods: Using the inclusion and exclusion criteria, data from 2411 mid-pregnant individuals were collected through interviews. The Total CHEI score and its component scores were determined through analysis of responses from the food frequency questionnaire. GMS diagnosis involved conducting physical examinations and performing blood biochemical tests. A logistic regression model was employed to analyze the relationship between GMS or related indices and both the total CHEI score and its component scores.

Results: The study identified an overall GMS prevalence of 21.65% (522 out of 2411 participants). During mid-pregnancy, participants diagnosed with GMS exhibited higher BMI, FBG, 1hPBG, 2hPBG, TC, TG, HDL, SBP, as well as higher educational levels and daily activity, compared to those without GMS (P < 0.001). After adjusting for potential confounders, participants with higher total CHEI scores (≥ 80) were found to have lower odds of GMS or related indices (P < 0.05). Increasing dietary intake of potatoes, whole grains, beans, dark green vegetables, and fruits, as per the CHEI recommendations, was associated with reduced odds of GMS or related indices (P < 0.05).

Conclusion: A high-quality diet, as indicated by a total CHEI score of 80 or higher, and increased consumption of specific dietary components, namely potatoes, beans, dark green vegetables, and fruits, were found to effectively reduce the odds of GMS or related indices during mid-pregnancy.

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妊娠中期代谢综合征与中国健康饮食指数的关系：一项横断面研究。

研究背景本研究旨在调查妊娠中期妊娠代谢综合征（GMS）与中国人健康饮食指数（CHEI）之间的关系，并找出潜在的有益或高风险饮食习惯。我们根据《中国居民膳食指南（2022年）》中关于孕中期食物量的建议，对中国人健康饮食指数进行了调整，开发了孕中期版本的CHEI-2022：方法：根据纳入和排除标准，通过访谈收集了 2411 名孕中期个体的数据。通过对食物频率调查问卷的回答进行分析，确定了CHEI总分及其组成分数。GMS诊断包括体格检查和血液生化检验。采用逻辑回归模型分析 GMS 或相关指数与 CHEI 总分及其组成部分得分之间的关系：研究发现，GMS 的总患病率为 21.65%（2411 名参与者中有 522 人）。在孕中期，被诊断为 GMS 的参与者与未患 GMS 的参与者相比，BMI、FBG、1hPBG、2hPBG、TC、TG、HDL、SBP 均较高，受教育程度和日常活动量也较高（P 结论：与未患 GMS 的参与者相比，被诊断为 GMS 的参与者BMI、FBG、1hPBG、2hPBG、TC、TG、HDL、SBP 均较高：研究发现，CHEI 总分达到 80 分或以上的优质饮食，以及增加特定饮食成分（即土豆、豆类、深绿色蔬菜和水果）的摄入量，可有效降低孕中期发生 GMS 或相关指数的几率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.