147270 Using GIS and logistic regression: Mapping the adequacy of prenatal care in Grand Rapids, MI

Monday, November 5, 2007

Stephen Borders, PhD , School of Nonprofit and Public Administration, Grand Valley State University, Grand Rapids, MI
Gustavo Rotondaro, MA , Community Research Institute, Johnson Center for Philanthropy at Grand Valley State University, Grand Rapids, MI
Background: Early prenatal care is often a prerequisite to a healthy baby. The relationship between adequate prenatal care and improved birthing outcomes is well known. Yet access to adequate prenatal care is complicated by a number of socioeconomic factors related to the mother. These factors include education, ethnicity, insurance type, and the age of the mother. When examining a number of these access measures related to prenatal care access and birthing outcomes, Michigan ranks poorly when compared to other states. The 2005 national infant mortality rate was 7.0 per 1,000 births as compared to 8.2 in Michigan. The percent of Michigan mothers having low birthweight babies (8.2%) also exceeds the national average of 7.9%. In Grand Rapids, Michigan, some of these problems are particularly acute. Grand Rapids exceeds the statewide rates in infant mortality, teen pregnancy and mothers receiving less than adequate prenatal care. Objective: Apply GIS to analyze the spatial aspects of inadequate prenatal care access and assist public health officials in identifying among the 32 Grand Rapids neighborhoods where risk factors are the greatest. Methods: Using vital statistics data on 22,004 live births recorded in Grand Rapids between 1998 and 2003, a logistic regression model was employed to determine the significance of various independent variables associated with inadequate prenatal care access as measured by the Kessner Index. Results: A number of variables (maternal smoking, maternal alcohol use, Medicaid as primary insurance type, ethnicity, and education of the mother) were found to be associated with inadequate prenatal care access. A number of maps were then prepared to examine the spatial distribution and relative severity of each variable within the city, uncovering a number of proximal relationships. Conclusions: These maps are being used to identify problem areas and tailored intervention programs to improve prenatal care access in Grand Rapids.

Learning Objectives:
1.Recognize how GIS and vital records data can be used to identify mother’s at risk of low prenatal care utilization. . 2.Identify factors associated with low prenatal care utilization 3.Recognize how to apply GIS techniques to find solutions to local public health problems.

Keywords: Prenatal Care, Access to Health Care

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

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.