Trends and attribution analysis of caesarean section ratesin Shanghai Municipality, 2003-2020
ZHOU Feng1, YU Hui-ting1, FAN He-yu2, WANG Chun-fang1
1. Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China; 2. School of Environmental and Biological Science, Rutgers University, New Jersey 08901-8525, USA
Abstract：Objective To analyze the trends of caesarean section (CS) rates and contribution of related influencing factors to CS rates in Shanghai, and to provide a basis for policy-making about controlling cesarean section rate in Shanghai Municipality. Methods Data about the CS rates of permanent residents in Shanghai from 2003 to 2020 were collected, and the changing trends were described by the average annual percent change (AAPC) method. At the same time, the birth registration information of singleton newborns with Shanghai registration household in 2018 was collected based on the maternity-hospital reports. χ2 test and Cox regression model analysis were performed to identify the factors influencing the occurrence of CS, and the relative risk of relevant influencing factors and population attributable risk proportion (PARP) were estimated. Results During the period of 2003- 2020, the CS rates in Shanghai decreased from 54.63% in 2003 to 48.43% in 2020, and their changes showed a slower downward trend, with an average annual decline of 0.78% (the AAPC was -0.78%, 95%CI:-1.42%--0.13%, P=0.018). The CS rate of singleton newborns with Shanghai registration household in 2018 was as high as 46.45%, and the influencing factors that contributed greatly to the rate (the percentage of population attribution risk was larger) included weekday surgery, general hospitals, non-first pregnancies, advanced maternal age and first birth, of which institutional factors (weekday surgery and general hospitals) contributed nearly 50%. Institutional factors in private hospitals contributed less to their institutional CS rates. Conclusion Relevant departments should further conduct investigation and study, explore and establish comprehensive management intervention strategies for CS strictly according to the indications for CS based on the characteristics of different institutions.
2022, Vol. 29 
