Spatial Analysis of the Relationship between Infant Mortality and Socioeconomic Conditions in Santa Clara, CA
Infant mortality is one of the most important indicators for the overall health of a community. Infant mortality is defined as number of deaths per 1000 live births of children under one year of age. The leading causes of infant mortality include premature births, birth complications, smoking/drinking of mothers while pregnant and environmental conditions. In this project, we explore the relationship between infant mortality rate and such factors as race, income, tobacco/alcohol, and maternal health in Santa Clara County, California, using data acquired from the Santa Clara County Public Health Department. With a population of around 2 million, 53% consisting of white, 3% black, 37% Asian, 25% Hispanic, and 8% living in poverty, Santa Clara is a diverse enough county to perform this study and gain insight on the community health in the area. Previous research has determined that African-American mothers experience infant mortality at a rate 44% higher than average. Lower incomes tend to correlate with higher infant mortality rates, as they do not have the resources to afford medical care. The aim of this project is to find out if these results from previous studies will hold true in Santa Clara County. The external health factors to be analyzed are the number of alcohol and tobacco retailers per square mile in Santa Clara County. Maternal health factors will be evaluated through a Vital Health Statistics dataset obtained from the County Public Health Department. Using GIS, we will also explore how such relationship varies spatially across the county. This information will be useful in gaining a deeper understanding of the rates of varying infant mortality in the county and will highlight zip codes of particular interest regarding infant mortality.
Primary Advisor's Department
Stander Symposium poster
"Spatial Analysis of the Relationship between Infant Mortality and Socioeconomic Conditions in Santa Clara, CA" (2019). Stander Symposium Posters. 1586.