Low Birth Weight Rates in Two Counties of South Florida: Small-Area Variation and Temporal Trends

Abstract

Low birth weight (LBW) is a primary cause of infant mortality and morbidity. The main hypothesis is that infant LBW rates would decrease annually by 9% to meet Health People 2010 goal of 5% by 2010. Moreover, observed LBW rates would be comparable over geographical areas in the counties and among race/ethnic groups. This study focused on LBW rates over 8 years at the small area level, the zip code, within each county. The purpose is to estimate the trends, quantify the magnitude of the small area variation and identify geographic area with high rates. This study utilized data from Florida Department of Health extracted from birth records for residents of Miami-Dade and Broward counties born in calendar years 1998 to 2005. For each zip code area within the counties, the number of LBW cases and the total number of births were provided yearly. The Poisson approximation to the Binomial distribution was used for statistical analyses and inference. Spatial statistical methods included the spatial scan statistic to detect clusters. Maps were used to highlight geographical variation and clusters of areas with high LBW rates. Descriptive results showed that for Miami-Dade County, LBW rates varied over time from 74.1 ± 26.9 to 100.1 ± 108.2 cases per 1000 births while in Broward County, they varied from 78.1 ± 21.9 to 87.5 ± 29.6 cases per 1000 births. There was no decreasing trend over both counties. For both counties, LBW rates exhibited non-negligible amount of small-area variation as captured by the coefficients of variation (CV). CV values ranged from 34.5% to 124.7% for Miami-Dade, and from 21.0% to 33.8% for Broward, with less variation within Broward County areas. In this multi-ethnic population of South Florida, LBW rates vary significantly at the small-area level and over time. There is no decrease in rates over time as expected. The rationale of this study is to focus further analysis on factors such as poverty, maternal social support, and smoking levels at the zip code level to explain the observed variation and the area-specific temporal trends.