Bijou R Hunt1, Gary Tran2, Steven Whitman3. 1. Sinai Urban Health Institute, Mount Sinai Hospital, Sinai Health System, 1500 S. California Ave., Room K443, Chicago, IL, 60608, USA. bijou.hunt@sinai.org. 2. Chicago Medical School, Rosalind Franklin University, North Chicago, IL, USA. 3. Sinai Urban Health Institute, Mount Sinai Hospital, Sinai Health System, 1500 S. California Ave., Room K443, Chicago, IL, 60608, USA.
Abstract
OBJECTIVES: Life expectancy in the USA reached a record high of 78.7 years in 2010. However, the racial gap in life expectancy persists. National data, which are readily available, provide averages which mask important local-level differences. Local data are needed to identify the worst off groups, key to reducing disparities and pursuing health equity. METHODS: Using vital records data, we calculated life expectancy for the USA and Chicago by race/ethnicity and gender and for Chicago's 77 community areas. We also examined the correlation between life expectancy and (1) racial/ethnic composition of a community area and (2) median household income. RESULTS: In Chicago, the highest life expectancy was observed among Hispanics at 84.6 and the lowest life expectancy was observed among Blacks at 71.7-a difference of about 13 years. Life expectancy varied substantially across the 77 community areas of Chicago, from a low of 68.2 to a high of 83.3-a difference of 15 years. There were strong correlations between life expectancy and the racial, ethnic, and socioeconomic distributions among the community areas. CONCLUSIONS: The examination of data at the local level provides invaluable insight into which communities are facing the greatest burden in terms of health and well-being. It is only through the examination of local-level data that we can understand the unique needs of these communities and begin to address them.
OBJECTIVES: Life expectancy in the USA reached a record high of 78.7 years in 2010. However, the racial gap in life expectancy persists. National data, which are readily available, provide averages which mask important local-level differences. Local data are needed to identify the worst off groups, key to reducing disparities and pursuing health equity. METHODS: Using vital records data, we calculated life expectancy for the USA and Chicago by race/ethnicity and gender and for Chicago's 77 community areas. We also examined the correlation between life expectancy and (1) racial/ethnic composition of a community area and (2) median household income. RESULTS: In Chicago, the highest life expectancy was observed among Hispanics at 84.6 and the lowest life expectancy was observed among Blacks at 71.7-a difference of about 13 years. Life expectancy varied substantially across the 77 community areas of Chicago, from a low of 68.2 to a high of 83.3-a difference of 15 years. There were strong correlations between life expectancy and the racial, ethnic, and socioeconomic distributions among the community areas. CONCLUSIONS: The examination of data at the local level provides invaluable insight into which communities are facing the greatest burden in terms of health and well-being. It is only through the examination of local-level data that we can understand the unique needs of these communities and begin to address them.
Keywords:
Black; Health disparities; Hispanic; Life expectancy; Race; Socioeconomic status
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