Analysis of incidence and associated factors of preterm birth based on pre-pregnancy body mass index stratification.
10.3760/cma.j.cn112150-20221008-00968
- Author:
Shao Fei SU
1
;
Shen GAO
1
;
En Jie ZHANG
1
;
Rui Xia LIU
1
;
Wen Tao YUE
2
;
Jian Hui LIU
1
;
Shuang Hua XIE
1
;
Yue ZHANG
2
;
Cheng Hong YIN
1
Author Information
1. Department of Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
2. Department of Research Management, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100026, China.
- Publication Type:Journal Article
- MeSH:
Pregnancy;
Infant, Newborn;
Female;
Humans;
Body Mass Index;
Overweight/epidemiology*;
Premature Birth/epidemiology*;
Pre-Eclampsia/epidemiology*;
Cohort Studies;
Eclampsia;
Incidence;
Risk Factors;
Thinness/epidemiology*
- From:
Chinese Journal of Preventive Medicine
2023;57(6):899-904
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To analyze the incidence of preterm birth based on pre-pregnancy body mass index (BMI) stratification and explore the associated factors of preterm birth among pregnant women at different BMI stratifications. Methods: From February 2018 to December 2020, pregnant women who participated in China Birth Cohort Study (CBCS) and gave birth at Beijing Obstetrics and Gynecology Hospital were enrolled as the study subjects. Electronic Data Capture System and standard structured questionnaires were used to collect data related to pre-pregnancy, pregnancy, and delivery for pregnant women. Pregnant women were divided into the low-weight group, normal-weight group and overweight group based on their pre-pregnancy BMI. A Cox proportional hazards model was used to analyze the associated factors of preterm birth among pregnant women with different BMI before pregnancy. Results: A total of 27 195 singleton pregnant women were included, with a preterm birth rate of 5.08% (1 381/27 195). The preterm birth rates in the low-weight group, normal-weight group and overweight group were 4.29% (138/3 219), 4.63% (852/18 390) and 7.00% (391/5 586) respectively (P<0.001). After adjusting for relevant factors, the Cox proportional hazards model showed that the risk of preterm birth in the overweight group was 1.457 times higher than that in the normal-weight group (95%CI: 1.292-1.643). Preeclampsia-eclampsia (HR=2.701, 95%CI: 1.318-5.537) was the associated factor for preterm birth in the low-weight group. Advanced maternal age (HR=1.232, 95%CI: 1.054-1.441), history of preterm birth (HR=4.647, 95%CI: 3.314-6.515), vaginal bleeding in early pregnancy (HR=1.613, 95%CI: 1.380-1.884), and preeclampsia-eclampsia (HR=3.553, 95%CI: 2.866-4.404) were associated factors for preterm birth in the normal-weight group. Advanced maternal age (HR=1.473, 95%CI: 1.193-1.818), history of preterm birth (HR=3.209, 95%CI: 1.960-5.253), vaginal bleeding in early pregnancy (HR=1.636, 95%CI: 1.301-2.058), preeclampsia-eclampsia (HR=2.873, 95%CI:2.265-3.643), and pre-gestational diabetes mellitus (HR=1.867, 95%CI: 1.283-2.717) were associated factors for preterm birth in the overweight group. Conclusion: Pre-pregnancy overweight is an associated factor for preterm birth, and there are significant differences in the associated factors of preterm birth among pregnant women with different BMI before pregnancy.
