OBJECTIVES: To investigate the incidence of preterm birth and risk factors for preterm birth. METHODS: A prospective cohort study was performed for the pregnant women in early pregnancy and their spouses, who underwent prenatal examination for the first time in Hunan Provincial Maternal and Child Health Care Hospital from May 2014 to December 2016 and decided to be hospitalized for delivery. A questionnaire survey was performed to collect exposure information possibly related to preterm birth. The hospital's medical record system was used for information verification and to record the pregnancy outcome. A multivariate logistic regression analysis was used to investigate the risk factors for preterm birth. RESULTS: A total of 6 764 pregnant women with complete data were included, and the incidence rate of preterm birth was 17.09%. The multivariate logistic regression analysis showed that a history of adverse pregnancy outcomes, eating areca nut before pregnancy, a history of pregnancy complications, a history of hepatitis, no folate supplementation during pregnancy, medication during pregnancy, active smoking and passive smoking during pregnancy, drinking during pregnancy, unbalanced diet during pregnancy, high-intensity physical activity during pregnancy, and natural conception after treatment of infertility or assisted conception as the way of conception were risk factors for preterm birth (P<0.05). Additionally, the pregnant women whose spouses were older, had a higher body mass index or smoked had an increased risk for preterm birth (P<0.05). A higher level of education of pregnant women or their spouses and lower gravidity were protective factors against preterm birth (P<0.05). CONCLUSIONS: There are many risk factors for preterm birth. Special attention should be paid to the life behaviors of pregnant women during pregnancy, and health education should be strengthened for pregnant women and their spouses to develop good living habits and reduce the incidence of preterm births.
OBJECTIVES: To investigate the incidence of preterm birth and risk factors for preterm birth. METHODS: A prospective cohort study was performed for the pregnant women in early pregnancy and their spouses, who underwent prenatal examination for the first time in Hunan Provincial Maternal and Child Health Care Hospital from May 2014 to December 2016 and decided to be hospitalized for delivery. A questionnaire survey was performed to collect exposure information possibly related to preterm birth. The hospital's medical record system was used for information verification and to record the pregnancy outcome. A multivariate logistic regression analysis was used to investigate the risk factors for preterm birth. RESULTS: A total of 6 764 pregnant women with complete data were included, and the incidence rate of preterm birth was 17.09%. The multivariate logistic regression analysis showed that a history of adverse pregnancy outcomes, eating areca nut before pregnancy, a history of pregnancy complications, a history of hepatitis, no folate supplementation during pregnancy, medication during pregnancy, active smoking and passive smoking during pregnancy, drinking during pregnancy, unbalanced diet during pregnancy, high-intensity physical activity during pregnancy, and natural conception after treatment of infertility or assisted conception as the way of conception were risk factors for preterm birth (P<0.05). Additionally, the pregnant women whose spouses were older, had a higher body mass index or smoked had an increased risk for preterm birth (P<0.05). A higher level of education of pregnant women or their spouses and lower gravidity were protective factors against preterm birth (P<0.05). CONCLUSIONS: There are many risk factors for preterm birth. Special attention should be paid to the life behaviors of pregnant women during pregnancy, and health education should be strengthened for pregnant women and their spouses to develop good living habits and reduce the incidence of preterm births.
Authors: Chang Chen; Jin Wen Zhang; Hong Wei Xia; Hui Xin Zhang; Ana Pilar Betran; Lin Zhang; Xiao Lin Hua; Li Ping Feng; Dan Chen; Kang Sun; Chun Ming Guo; Hong Bo Qi; Tao Duan; Jun Zhang Journal: Am J Public Health Date: 2019-09-19 Impact factor: 9.308