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中国江西省孕前体重指数对婴儿出生体重的饱和效应:一项回顾性研究

Saturation effects of pre-pregnancy BMI on infant birth weight in Jiangxi Province, China: a retrospective study.

作者信息

Xiong Jun, Li Huan, Tan Xiao-Qing, He Xiao-Ju, Fu Wen-Yan

机构信息

Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China.

Nanchang University, Nanchang, 330006, China.

出版信息

Sci Rep. 2025 May 22;15(1):17866. doi: 10.1038/s41598-025-02677-6.

DOI:10.1038/s41598-025-02677-6
PMID:40404854
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12098974/
Abstract

There were limited analyses on relationship between body mass index (BMI) pre-pregnancy, as well as birth weight. Research aimed to examine the relation between these two, as well as low birth weight (LBW) risk in Jiangxi Province, China. A total of 1193 pregnant subjects from Jiangxi Province, China were enrolled in the final analysis. Standardized questionnaires were administered to the women during childbirth, newborns' medical information was obtained from hospital records. Pre-pregnancy BMI was categorized into underweight, normal, overweight, and obese groups. Multivariate linear regression models were employed to assess connection between pre-pregnancy BMI, birth weight. We utilized generalized additive model and fitted smoothing curve (penalized spline method) to examine relationship between pre-pregnancy BMI and birth weight, as well as LBW risk. The incidence of LBW was 12.1%, with average pre-pregnancy BMI of 20.9 ± 2.5 kg/m. The smoothing curve revealed an L-shaped association between pre-pregnancy BMI, birth weight and LBW risk. The curve indicated that as pre-pregnancy BMI increased, LBW risk initially decreased and then plateaued, while birth weight initially escalated and then plateaued. The inflection point for pre-pregnancy BMI was identified as 22 kg/m. On the left side of inflection point, β (95% CI) for birth weight was 0.04 (0.02, 0.07), and ORs (95% CIs) for LBW risk were 0.78 (0.69, 0.89), on the right side the corresponding values were - 0.00 (-0.03, 0.03) and 1.02 (0.88, 1.19), respectively. All the outcomes presented to be similar in various subgroups. Within a specific range (BMI<22 kg/m), the correlation between pre-pregnancy BMI and birth weight is statistically significant. This research indicated pre-pregnancy BMI demonstrates a saturation effect on birth weight and LBW risk among Jiangxi Province population.

摘要

关于孕前体重指数(BMI)与出生体重之间关系的分析有限。本研究旨在探讨二者之间的关系,以及中国江西省低出生体重(LBW)的风险。最终分析纳入了来自中国江西省的1193名孕妇。在分娩期间对这些女性进行标准化问卷调查,并从医院记录中获取新生儿的医疗信息。孕前BMI被分为体重过轻、正常、超重和肥胖组。采用多元线性回归模型评估孕前BMI与出生体重之间的联系。我们利用广义相加模型并拟合平滑曲线(惩罚样条法)来研究孕前BMI与出生体重以及LBW风险之间的关系。LBW的发生率为12.1%,孕前平均BMI为20.9±2.5kg/m²。平滑曲线显示孕前BMI、出生体重和LBW风险之间呈L形关联。该曲线表明,随着孕前BMI的增加,LBW风险最初降低,然后趋于平稳,而出生体重最初升高,然后趋于平稳。孕前BMI的拐点确定为22kg/m²。在拐点左侧,出生体重的β(95%CI)为0.04(0.02,0.07),LBW风险的ORs(95%CI)为0.78(0.69,0.89),在右侧相应值分别为-0.00(-0.03,0.03)和1.02(0.88,1.19)。所有结果在各个亚组中均相似。在特定范围内(BMI<22kg/m²),孕前BMI与出生体重之间的相关性具有统计学意义。本研究表明,孕前BMI对江西省人群的出生体重和LBW风险具有饱和效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/c365cdf46e18/41598_2025_2677_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/e25178889702/41598_2025_2677_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/455a5d20df24/41598_2025_2677_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/c365cdf46e18/41598_2025_2677_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/e25178889702/41598_2025_2677_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/455a5d20df24/41598_2025_2677_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09d9/12098974/c365cdf46e18/41598_2025_2677_Fig3_HTML.jpg

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本文引用的文献

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Intrauterine growth restriction, prematurity, and low birth weight: risk phenotypes of neonatal death, Rio de Janeiro State, Brazil.宫内生长受限、早产和低出生体重:巴西里约热内卢州新生儿死亡的风险表型。
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BMC Pregnancy Childbirth. 2023 Apr 19;23(1):268. doi: 10.1186/s12884-023-05603-8.
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Maternal anaemia and birth weight: a cross-sectional study from Jiangxi Province, China.
产妇贫血与出生体重:来自中国江西省的一项横断面研究。
Fam Pract. 2023 Dec 22;40(5-6):722-727. doi: 10.1093/fampra/cmac148.
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Front Public Health. 2022 Nov 30;10:1036689. doi: 10.3389/fpubh.2022.1036689. eCollection 2022.
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