[EQ] The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in USA

The Reversal of Fortunes:
Trends in County Mortality and Cross-County Mortality Disparities in the United States

 

Majid Ezzati1,2*, Ari B. Friedman2, Sandeep C. Kulkarni2,3, Christopher J. L. Murray1,2,4

1 Harvard School of Public Health, Boston, Massachusetts, United States of America, 2 Initiative for Global Health, Harvard University, Cambridge, Massachusetts, United

States of America, 3 University of California, San Francisco, California, United States of America, 4 Institute for Health Metrics and Evaluation, University of Washington,

Seattle, Washington, United States of America

PLoS Medicine | www.plosmedicine.org  -  22 April 2008 - Volume 5 - Issue 4

 

Available online as PDF file [12p.] at:
http://medicine.plosjournals.org/archive/1549-1676/5/4/pdf/10.1371_journal.pmed.0050066-L.pdf

 

Background

Counties are the smallest unit for which mortality data are routinely available, allowing consistent and comparable long-term analysis of trends in health disparities. Average life expectancy has steadily increased in the United States but there is limited information on long term mortality trends in the US counties This study aimed to investigate trends in county mortality and cross-county mortality disparities, including the contributions of specific diseases

to county level mortality trends.

 

Methods and Findings

We used mortality statistics (from the National Center for Health Statistics [NCHS]) and population (from the US Census) to estimate sex-specific life expectancy for US counties for every year between 1961 and 1999. Data for analyses in subsequent years were not provided to us by the NCHS. We calculated different metrics of cross-county mortality disparity, and also grouped counties on the basis of whether their mortality changed favorably or unfavorably relative to the national average. We estimated the probability of death from specific diseases for counties with above- or below-average mortality performance. We simulated the effect of cross-county migration on each county’s life expectancy using a time-based simulation model.

Between 1961 and 1999, the standard deviation (SD) of life expectancy across US counties was at its lowest in 1983, at 1.9 and 1.4 y for men and women,  respectively. Cross-county life expectancy SD increased to 2.3 and 1.7 y in 1999. Between 1961 and 1983 no counties had a statistically significant increase in mortality; the major cause of mortality decline for both sexes was reduction in cardiovascular mortality. From 1983 to 1999, life expectancy declined significantly in 11 counties for men (by 1.3 y) and in 180 counties for women (by 1.3 y); another 48 (men) and 783 (women) counties had non significant life expectancy decline. Life expectancy decline in both sexes was caused by increased mortality from lung cancer, chronic obstructive pulmonary disease (COPD), diabetes, and a range of other noncommunicable diseases, which were no longer compensated for by the decline in cardiovascular mortality. Higher HIV/AIDS and homicide deaths also contributed substantially to life expectancy decline for men, but not for women. Alternative specifications of the effects of migration showed that the rise in cross county life expectancy SD was unlikely to be caused by migration.

 

Conclusions

There was a steady increase in mortality inequality across the US counties between 1983 and 1999, resulting from stagnation or increase in mortality among the worst-off segment of the population. Female mortality increased in a large number of counties, primarily because of chronic diseases related to smoking, overweight and obesity, and high blood pressure….”

 

Supporting Information

Dataset S1. Change in Probability of Dying in Specific Age Ranges, with Counties Grouped on the Basis of Level of Change in Life Expectancy, Divided by Disease (Numerical Data for Figure 4) (33 KB XLS)

Dataset S2. Life Expectancy at Birth by County, 1961–1999 (2.5 MB ZIP)

Figure S1. County Life Expectancy in (A) 1961; (B) 1983; and (C) 1999 (3.5 MB PPT)

Figure S2. Absolute Change in County Life Expectancy in (A) 1961–1983 and (B) 1983–1999

Movie S1. Life Expectancy at Birth by County, 1961–1999 (Males) (14.4 MB AVI)

Movie S2. Life Expectancy at Birth by County, 1961–1999 (Females) (15.8 MB AVI)

 

 

 

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