The Link Between Geography and Life Expectancy

(This article was provided through The OpEd Project, whose mission is to increase the range of voices and quality of ideas we hear in the world.)

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A recent study of death records across the U.S. by researchers at the University of Washington and the Department of Public Health in the Netherlands found a 20 year difference in life expectancy between counties with the highest life expectancy and the lowest. Cardiovascular risks vary as well, with some counties having a nine to 13 times greater risk of death from cardiovascular disease.

These differences are large and increasing.

The places found to have the lowest life expectancy were parts of North and South Dakota with Native American Reservations; Mississippi; Arkansas; Louisiana and eastern Kentucky. The life expectancy of 66 years in these counties is the same as in countries such as Burma and Ghana.

Counties with the highest life expectancy, an average of 86 years, are in central Colorado, Alaska, along the coast of California and in the mid-Atlantic states.

The good news is this discrepancy can be changed.

Examining life expectancy by county allows for tracking geographic disparities over time and assessing contributing factors. The study authors attribute these differences largely to a combination of socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors as well as health care factors.

The health care related factors used in this study include the percentage of the insured population younger than 65, a quality index of variables related to primary care access and quality based on Medicare data as well as the number of doctors per capita.

Health care is complex. The organization, resources and capacity of health care are local and differ by geography. The Dartmouth Atlas of U.S. maps depicts variations in care across the country.  Studies have shown that only approximately 50 percent of patients get guideline recommended care represented by the Dartmouth Atlas.

In a study reviewing 30 years of interventions to reduce racial and ethnic disparities in health care, differences in care and outcomes were apparent.

The majority of the interventions targeted the patient through education and training, self-management support, communication skills training and decision-making aids. To be sure, it is important to work directly with patients to provide counseling related to behavioral risk factors. But there must be the ability to provide necessary access in order to routinely deliver counseling.

If the care varies due to differences in organization, resources and capacity, patient-centric strategies alone may not affect outcomes. Interventions targeting providers, the care team, organization and policies were less common. Interventions that target the structural and systematic aspects of the health care system can be powerful and improve health and longevity.

For instance, efforts in Cook County in Chicago provide an example of how interventions to address the systems of care locally can lead to a reduction of early unnecessary deaths due to racial and ethnic disparities.

In 2007, Chicago had the highest racial disparities in breast cancer deaths in the U.S.  A decade ago, Chicago's black women were dying of breast cancer at a rate 62 percent higher than white women there.

That year, the Chicago Breast Cancer Task Force was created as a collaboration of the Sinai Urban Health Institute, Avon Foundation for Women, Blue Cross Blue Shield of Illinois, National Institutes for Health, Illinois Department of Public Health, Telligen and a host of other public and private entities.

The Task Force produced a report that focused on the systemic factors related to breast cancer related access to care and the quality of care provided. The three main issues found included lower access to mammography; lower quality mammography services; and less overall access and lower quality treatment.

The Task Force found the city did not have adequate mammography screening capacity, plus there was a shortage in fellowship-trained radiologists and specialized radiology technologists were not available at all providers. The city also had poor mammography technical quality and breast health services in low income communities.

After five years, by addressing these structural issues, there has been a 35 percent reduction in the breast cancer death rate gap between African­-American women and white women in Chicago.

Care measures such as appropriate follow-up after mammography or biopsy, appropriate 12-month follow-up and the search to find cancers when they are small were also processes put into place.

Certainly, life expectancy at birth has increased for both sexes across the board over the last 35 years in the United States. The death rate from heart disease and stroke has also declined 50 percent overall.

Fewer are dying earlier. More are living longer.

Nevertheless, these achievements mask the enormous variation of geographic disparities in health care and ultimately life expectancy. There is substantial unnecessary loss of life in some areas. Too many die too young. But how people are treated can be altered.

From a policy perspective, a review of system and community level health care resources and capacity is necessary. This may provide insight into system level interventions that can improve life expectancy for anyone living in these counties.

As proven in Chicago, strategies for closing the gaps in life expectancy for counties and states with the lowest life expectancies and greatest risk of early death can be successful.

It is a larger moral question to consider and one of enormous importance about who lives and who dies. Because it is preventable, where should not determine when.