Online Program

282605
Community and individual level factors influencing preterm birth: A multilevel analysis


Tuesday, November 5, 2013

Saba Masho, MD, MPH, DrPH, Department of Family Medicine and Population Health, Division of Epidemiology, Virginia Commonwealth University, Richmond, VA
Meaghan Munn, MPH, Department of Epidemiology and Community Health, Virginia Commonwealth University, Richmond, VA
Diane L. Bishop, MPH, Division of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA
Background: Reducing rates of adverse birth outcomes for all mothers is a central focus of public health efforts. Multilevel studies examining adverse birth outcomes have focused on infant mortality and low birth weight. Considering preterm birth is one of the main contributing factors to infant mortality and low birth weight, multilevel factors associated with preterm births should be investigated. The objective of this study is to determine individual-level and community-level factors predicting the rate of preterm birth.

Methods: This study was conducted using vital birth record data for Richmond City, Virginia, violence related ambulance pick up data and population level data obtained from the U.S. Census. Logistic regression was conducted to identify the best predictive model and a combined or hierarchical model was examined using all variables from both levels.

Results: There were 30,591 live births that occurred in Richmond, Virginia between 1997 and 2007. Preterm births occurred in 12.3 per 100 births in this study. Maternal age, race, education, paternal presence, and adequacy of prenatal care, as well as percent black and percent poverty in the block group were significant predictors of preterm birth. Violence related ambulance pick up was not significantly associated with preterm birth.

Conclusions: These results demonstrate the use of multilevel modeling in identifying significant individual and community level factors that are associated with preterm birth. The findings of this study identified modifiable environmental and individual risk factors for future interventions.

Learning Areas:

Epidemiology
Public health or related research

Learning Objectives:
Demonstrate the use of multilevel modeling in identifying significant individual and community level factors that are associated with preterm birth. Identify modifiable risk factors for future interventions to reduce preterm birth rates.

Keyword(s): MCH Epidemiology, Pregnancy Outcomes

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a second-year Master of Public Health student with experience on multiple projects involving epidemiology in the field maternal and child health. One of my scientific interests in this field include pregnancy outcomes in relation to community factors.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.