Tuesday, April 19, 2011
Through computer analysis of geographical information, researchers have effectively identified location-specific preterm birth risk factors in Hamilton County, Ohio. This level of detailed information will enable development of targeted strategies for preventing preterm birth in each community.
The study, published online in the Maternal Child Health Journal, analyzed preterm birth risk factors based on geographic coordinates instead of geopolitical boundaries.
“By identifying risk factors for each area that are potentially modifiable, we are able to begin to also identify the right intervention for that specific population of mothers,” says Andrew South, MD, a neonatologist at Cincinnati Children’s Hospital Medical Center and senior author of the study. “The list of risk factors that we used in this study is consistent with what is in published literature, suggesting that preterm birth in Hamilton County is similar in terms of risk factors to preterm births seen elsewhere in the United States, and thus our methods should be applicable for other urban regions.”
The Cincinnati Children’s Hospital Medical Center study included over 41,000 singleton (one baby) births, all of them infants born between 2003 and 2006 whose mothers resided in Hamilton County. Infant demographics, gestational age, complications of pregnancy and latitude and longitude coordinates of mother’s address were determined from state of Ohio Vital Statistics.
The researchers selected five distinct areas with varying levels of preterm birth for further analysis. All births in the five areas were analyzed to determine differences in demographics and potentially modifiable risk factors for preterm birth, including previous preterm birth, chronic or gestational hypertension, education level, diabetes, short intervals between pregnancies, smoking, advanced maternal age and low pre-pregnancy weight.
The researchers used Geographic Information System (GIS) techniques to determine the proportion of preterm births for geographical points throughout the county. In doing this, they removed artificial geopolitical boundaries in favor of allowing the natural disease pattern to identify areas for further evaluation, according to Dr. South.
“While use of political boundaries, such as counties, may be useful in defining the scope of a problem, it is less useful from a public health standpoint because it does not allow for precise identification of specific populations at risk for a poor outcome,” he says.
Researchers have discussed their findings with public health officials and believe the results of this study can be instrumental to initiating targeted interventions for relevant populations.