Relationships among Neighborhood Safety, Diabetes rates, and Life Expectancy
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Date
2019-05
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The Ohio State University
Abstract
Diabetes has long been considered one of the primary threats to public health due to its high mortality rate and treatment cost. Many types of research have been done to understand how lifestyles could affect the risk of diabetes. In fact, every detail in daily life, from sleeping to eating, could potentially increase or decrease this risk. And this research pays attention to one of the most discussed factor, physical activity level. Based on the previous research, the physical activity level is negatively related to the risk of diabetes, suggesting that an individual who does more outdoor activities has a lower possibility to be troubled by diabetes. What attributes to a high activity level? Research in 2004 found that a safer neighborhood leads to an increase in physical activity, as residents do more exercise in a safer region. Then what helps make a neighborhood safer? The objective method to identify if a neighborhood is safe or not is by looking at its crime rates, and a low crime rate is an essential symbol of a safe neighborhood. This research is designed to find out the relationship among crime rate, life expectancy, and diabetes prevalence. The whole analysis took a separate look at time series and cross-sectional datasets; the former dataset focuses on Los Angeles County in California in a ten-year time frame and the latter one includes all counties in the United States in 2010. Regression analysis suggested that the crime rate is negatively related to life expectancy, as the residents in a less safe neighborhood tend to live longer; and the crime rate is positively related to the diabetes prevalence since fewer individuals are troubled by diabetes in a safe neighborhood than in a less safe one. The relationships discovered in this research could be utilized by healthcare companies to make regional marketing strategies based on neighborhood crime rates. The government could also apply the models in different neighborhoods to plan on the construction of amenities.