Statistical Analysis of Socioeconomic Factors Correlating to Caesarean Section Rates 2015-2016Nethra Parasuram* and Mark Martens
Jersey Shore University Medical Center, 1945 Route 33, Neptune, NJ 07753, USA
- *Corresponding Author:
- Nethra Parasuram
Jersey Shore University Medical Center
1945 Route 33, Neptune, NJ 07753, USA
Tel: (217) 402-4906
E-mail: [email protected]
Received November 30, 2016; Accepted date: January 05, 2017; Published date: January 10, 2017
Citation: Parasuram N, Martens M (2017) Statistical Analysis of Socioeconomic Factors Correlating to Caesarean Section Rates 2015-2016. Gynecol Obstet (Sunnyvale) 7:420. doi: 10.4172/2161-0932.1000420
Copyright: © 2017 Parasuram N. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Objective: Caesarean section rates have significantly increased in the past decade in the United States. To make an attempt at lowering these rates, it is important to first understand how states’ rates compare with each other and which factors correlate with these rates. Then, possible ways to impact these rates can be suggested. This investigation sought to determine whether or not there is a significant difference between the rates of caesarean sections in Utah, United States and New Jersey, United States using representative hospitals’ data. Also, we sought to evaluate selected socioeconomic factors and their possible correlation with higher or lower caesarean rates in each United States’ states. Methods: Information collected from various federal and private sources were utilized to collect caesarean section rate data. These data were correlated to selected variables including average birthing age, logarithm of the percent of females in the workforce, median household income, number of hospitals, logarithm of the percent of people who have graduated with a Bachelor’s degree or higher, average number of people in a household, and the standard of living. A Linear Multiple Regression Model and T-Test were utilized to determine significance of each variable. Results: There was a statistical difference between the caesarean section rates of Utah and the caesarean section rates of New Jersey. The p-value obtained from the T-Test was 1.805*10-5. Therefore, there is a significant difference between the two states’ caesarean data. The variables birthing age, logarithm of the percent of females working, and the number of hospitals significantly correlated with caesarean section rates. Median household income, logarithm of the percent of people who have graduated with a Bachelor’s degree or higher and average number of people in a household did not significantly correlate with caesarean section rate data. Conclusion: It appears that there are several economic factors that significantly correlate with caesarean section rates. Other economic factors which did not appear significant may have had several conflicting components, which under estimated any true significance. Understanding these factors may permit us to develop strategies to impact the caesarean section rate.