Interactive effects of gestational diabetes and high pre‐pregnancy body mass index on adverse growth patterns of offspring

后代 怀孕 妊娠期糖尿病 体质指数 优势比 产科 医学 肥胖 妊娠期 内分泌学 内科学 生物 遗传学
作者
Weihan Cao,Ninghua Li,Rui Zhang,Weiqin Li,Ming Gao,Hui Wang,Leishen Wang,Yijuan Qiao,Jing Li,Zhijie Yu,Gang Hu,Junhong Leng,Xilin Yang
出处
期刊:Diabetes-metabolism Research and Reviews [Wiley]
卷期号:40 (3): e3759-e3759 被引量:3
标识
DOI:10.1002/dmrr.3759
摘要

Abstract Aims To examine the independent and interactive effects of maternal gestational diabetes mellitus (GDM) and high pre‐pregnancy body mass index (BMI) on the risk of offspring adverse growth patterns. Materials and Methods One thousand six hundred and eighty one mother‐child pairs were followed for 8 years in Tianjin, China. Group‐based trajectory modelling was used to identify offspring growth patterns. Logistic regression was performed to obtain odds ratios (ORs) and 95% confidence intervals (CIs) of GDM and high pre‐pregnancy BMI for offspring adverse growth patterns. Restricted cubic spline was used to identify cut‐off points. Additive interactions and multiplicative interactions were used to test interactive effects between GDM and high pre‐pregnancy BMI for adverse growth patterns. Results Four distinct growth patterns were identified in offspring, including normal growth pattern, persistent lean growth pattern, late obesity growth pattern (LOGP), and persistent obesity growth pattern (POGP). Maternal high pre‐pregnancy BMI was associated with LOGP and POGP (adjusted OR, 95% CI: 2.38, 1.74–3.25 & 4.92, 2.26–10.73). GDM greatly enhanced the adjusted OR of high pre‐pregnancy BMI for LOGP up to 3.48 (95% CI: 2.25–5.38). Additive interactions and multiplicative interactions between both risk factors were significant for LOGP but not for POGP. Conclusions Maternal high pre‐pregnancy BMI was associated with increased risk of LOGP and POGP, whereas GDM greatly enhanced the risk of high pre‐pregnancy BMI for LOGP.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
天真以菱发布了新的文献求助10
刚刚
害羞的大炮完成签到,获得积分10
刚刚
YAN发布了新的文献求助10
1秒前
1秒前
2秒前
连安阳完成签到,获得积分10
2秒前
lql发布了新的文献求助10
3秒前
慕青应助月亮三分糖采纳,获得10
3秒前
Serena发布了新的文献求助10
3秒前
荻野千寻完成签到,获得积分10
4秒前
典雅代曼应助huihui0914采纳,获得10
5秒前
田様应助huihui0914采纳,获得10
5秒前
LW2026完成签到,获得积分10
6秒前
6秒前
星辰大海应助徐妮采纳,获得10
6秒前
大模型应助京刹而语采纳,获得10
7秒前
J_B_Zhao发布了新的文献求助10
8秒前
zhao发布了新的文献求助10
9秒前
乐观秋荷应助kk采纳,获得10
10秒前
10秒前
SciGPT应助YAN采纳,获得10
11秒前
11秒前
nan11发布了新的文献求助10
11秒前
今后应助小巧南晴采纳,获得10
11秒前
11秒前
12秒前
不太热烈发布了新的文献求助10
12秒前
科研通AI6.2应助leeshho采纳,获得30
13秒前
13秒前
Chali完成签到,获得积分10
13秒前
之南完成签到,获得积分10
14秒前
liguyi完成签到,获得积分10
14秒前
马木木云完成签到,获得积分10
14秒前
hcy发布了新的文献求助10
14秒前
Aliya发布了新的文献求助10
15秒前
乐乐应助再炫一袋砂糖橘采纳,获得30
15秒前
15秒前
15秒前
wulinuan发布了新的文献求助10
16秒前
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Metallurgy at high pressures and high temperatures 2000
Tier 1 Checklists for Seismic Evaluation and Retrofit of Existing Buildings 1000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 1000
The Organic Chemistry of Biological Pathways Second Edition 1000
Signals, Systems, and Signal Processing 610
An Introduction to Medicinal Chemistry 第六版习题答案 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6333054
求助须知:如何正确求助?哪些是违规求助? 8149761
关于积分的说明 17107747
捐赠科研通 5388822
什么是DOI,文献DOI怎么找? 2856801
邀请新用户注册赠送积分活动 1834281
关于科研通互助平台的介绍 1685299