ISSN: 2161-0932
Nethra Parasuram and Mark Martens'
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.