305203
Mapping the relationship between low birth weight and neighborhood deprivation in Miami-Dade County, Florida
Methods: Data on the percentage of infants in each census tract who were LBW (< 2,500 grams) from 2006-2010 were obtained from the Florida CHARTS database. Shapefiles and neighborhood data were obtained from the U.S. Census Bureau. The Neighborhood Deprivation Index consists of eight variables, measured as percentages within each tract: households below poverty line; female-headed households; residents earning < $25,000; residents receiving SNAP benefits; adult males without managerial jobs; households with ≥ 1 person per bedroom; unemployed residents; and residents ≥ age 25 without a high school diploma. GIS software was used to calculate LBW and deprivation quintiles and to create nine maps depicting variations in these measures across census tracts. Tracts were then classified into levels of deprivation (e.g., ≥ 80th percentile for 0, 1-2, 3-4, 5-6, and 7-8 indicators). Binary logistic regression was used to quantify the relationship between LBW and deprivation level. A final map was then created to depict this relationship, with LBW percentage shown as a proportional symbol and deprivation shown as a green to red color ramp.
Results: There was a significant association between LBW and deprivation level (β = 1.334, p = 0.04).
Conclusion: This study provided preliminary evidence of a positive association between neighborhood deprivation and LBW and identified specific Miami-Dade neighborhoods in need of prenatal health interventions.
Learning Areas:
EpidemiologyPublic health or related research
Social and behavioral sciences
Learning Objectives:
Define neighborhood deprivation and low birth weight.
Describe how GIS analysis can be used to evaluate and display geographical health data.
Analyze the association between low birth weight and neighborhood deprivation.
Keyword(s): Geographic Information Systems (GIS), Maternal and Child Health
Qualified on the content I am responsible for because: I am an epidemiology PhD candidate with an MPH and experience in geographic information systems (GIS). I have co-authored four peer-reviewed journal articles and have extensive data analysis experience. My research interests include geospatial epidemiology and maternal and child health. I conducted this study — from conceptualization to analysis to interpretation — by myself in a graduate-level GIS course. This project is a precursor to my dissertation research on neighborhood-level risk factors for maternal hypertension.
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.