- Author:
Haiyue GUO
1
Author Information
- Publication Type:Journal Article
- Keywords: Influencing factor; Logistic regression; Neonate; Premature birth; Xi'an
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2020;41(2):281-286
- CountryChina
- Language:Chinese
- Abstract: Objective: To analyze the factors influencing the occurrence of preterm birth among single live birth neonates in Xi'an so as to provide theoretical basis for the prevention of premature infants. Methods: From July to December 2013, a questionnaire survey was conducted among the childbearing aged women, selected through multistage stratified random sampling method in Xi'an from 2010 to 2013. All of the childbearing aged women under study had definite pregnancy outcomes. The Logistic regression model was adopted to analyze the influencing factors of premature infants. Results: The incidence of preterm birth among single live birth neonates in the last pregnancy in Xi'an was 2.81%. From 2010 to 2013, the incidence of preterm birth was 3.51%, 3.13%, 3.18% and 2.21%, respectively, without significant difference (P=0.248). The incidence of premature delivery in Baqiao District, Beilin District, Lianhu District, Xincheng District, and Yanta District was 3.10%, 2.41%, 2.14%, 3.70% and 2.64%, respectively. There was no significant difference (P=0.259). The incidence of premature delivery in urban residents and rural residents was 2.96% and 2.69%, respectively, with no significant difference (P=0.581). Logistic regression results showed that the occupation as workers [OR=4.06, 95% CI (1.69,9.75)], the history of abnormal pregnancy and delivery [OR=10.68, 95% CI (6.92,16.48)], occupational exposure to risk factors [OR=1.96, 95% CI (1.08,3.57)], drinking [OR=6.31, 95% CI(1.21, 32.99)], radiological examination [OR=6.13, 95% CI (1.64,22.85)], PIH [OR=4.80, 95% CI(2.17, 10.61)], and having disease[OR=0.64, 95% CI (0.43,0.95)] during periconception were the influencing factors of premature infants. Conclusion: The incidence of premature infants in Xi'an from 2010 to 2013 was lower than the national average. Factors such as occupation as workers, the history of abnormal pregnancy and delivery, occupational exposure to risk factors, drinking, radiological examination and PIH during periconception can increase the risk of preterm birth.