Risk factors for C-section delivery and population attributable risk for C-section risk factors in Southwest of Iran: a prospective cohort study.

Med J Islam Repub Iran

PhD Candidate of Epidemiology, Department of Epidemiology, School of Health, Iran University of Medical Sciences, Tehran, & Departmentof Public Health, Neyshabur University of Medical Sciences, Neyshabur, Iran.

Published: February 2016

Background: Iran has a high C-section rate (40.6% in 2005). The objective of this study was to assess the associations and population-attributable risks (PAR) of risk factors combinations and Csection in the Southwest Iran.

Methods: We performed a population-based cohort study using the reports provided by Shiraz University of Medical Sciences. The cohort included pregnant women within September 2012 and February 2013 (n=4229), with follow-up until delivery. Then, the actual delivery was recorded; i.e., C-section delivery, vaginal delivery, and miscarriage. A multiple logistic regression model was used to estimate the point and the interval probability. The adjusted population attributable risks (aPARs) were calculated through adjusted odds ratio from the final multiple logistic regression models for each variable.

Results: Of 4,217 deliveries, 2,624 ones were C-section (62.2%). The rate of C-section was significantly higher in healthcare departments of private clinics compared to governmental clinics. The rate increased steadily with the mother's age, marriage age, family income and education. The multiple logistic regression analysis showed that local healthcare, supplementary insurance, maternal age, age of marriage, place of birth, family income, maternal education, education of husband and occupation were the key contributing factors to choose the mode of delivery. The multiple logistic regression analysis for reproductive factors showed that parity, previous abortion and stillbirth, previous infertility, birth weight (g) and number of live births were selected risk factors for C-section. Among the exposures, family income, location of healthcare and place of birth showed the highest population attributable risks: 43.86%, 19.2% and 18.53%; respectively.

Conclusion: In this survey, a relatively large contribution of non-medical factors was identified against the background of C-section. All of these factors influence the knowledge, attitudes and norms of the society. Thus, the attention of policymakers should be drawn to the factors associated with this mode of delivery.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4764292PMC

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