ResearchBlogging.orgInequality in mortality is the most poignant reminder of persistent, often multi-generational differences in socioeconomic status (SES). Poor people are more likely to get sick and die than rich people. As a society develops over time, one would hope that this disparity would be reduced, but in fact, it often increases. Recent research published in PLoS Medicine heralds this bad news.

This study is fairly unique in that it examines life expectancy across counties, which are the smallest demographic unit for which the appropriate kind of data are collected. The study examines death rates by county in all US states and D.C. from 1961 to 1999. The data are broken down by sex and disease type.

The following general patterns were noted:

  • Overall US Life Expectancy increased from 67 to 74 for men
  • Overall US Life Expectancy increased from 74 to 80 for women
  • Decreases in cardiovascular disease related mortality decreased death rate for both sexes from 1961 to 1983.
  • During the period 1961 to 1983, differences in death rate across counties fell… the pattern of death rate across the US became more homogeneous with respect to geography.
  • Beginning in the early 1980s, the cross-county variation reversed trend and began to increase. The poorest counties stopped experiencing any reduction in death rate (against the national average) and in many cases, death rate among the poorest counties increased, especailly for women.
  • The primary causes of tehse stagnations or reversals were cardiovascular disease toigether with an increase in a number of other diseases, inlcuding as lung cancer, chronic lung disease, and diabetes, in both men and women, and a rise in HIV/AIDS and homicide in men.

From the PLoS editors summary:

The findings suggest that beginning in the early 1980s and continuing through 1999 those who were already disadvantaged did not benefit from the gains in life expectancy experienced by the advantaged, and some became even worse off. The study emphasizes how important it is to monitor health inequalities between different groups, in order to ensure that everyone–and not just the well-off–can experience gains in life expectancy. Although the “reversal of fortune” that the researchers found applied to only a minority of the population, the authors argue that their study results are troubling because an oft-stated aim of the US health system is the improvement of the health of “all people, and especially those at greater risk of health disparities”…

i-7f7215c470daf2fc7bd8d5509d3885cd-LifeExpAllCompressed.jpg

Composite Graph of Data from This Paper.

Top four graphs are life expectancy and life expectancy gap by male and female. The fifth graph is standard deviation of county life expectancy, showing degree of overall national disparity, for males (top line) and females (bottom line). The bottom chart, not from the present study but added for reference, is the Index of Democratic Party Control over the relevant time period. The index gains one point for having a democrats in charge of the Executive Branch, the Senate and the House, so a year in which there is a Democratic president and democratic control of the house and senate would be valued at a 3.


Ezzati, M., Friedman, A.B., Kulkarni, S.C., Murray, C.J., Novotny, T. (2008). The Reversal of Fortunes: Trends in County Mortality and Cross-County Mortality Disparities in the United States . PLoS Medicine, 5(4), e66. DOI: 10.1371/journal.pmed.0050066

See Also:

The Fall and Rise of US Inequities in Premature Mortality: 1960-2002 Krieger N, Rehkopf DH, Chen JT, Waterman PD, Marcelli E, et al. PLoS Medicine Vol. 5, No. 2, e46 doi:10.1371/journal.pmed.0050046

Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States Murray CJL, Kulkarni SC, Michaud C, Tomijima N, Bulzacchelli MT, et al. PLoS Medicine Vol. 3, No. 9, e260 doi:10.1371/journal.pmed.0030260

Comments

  1. #1 Mary
    April 30, 2008

    I found the figure 3 with the maps and the red areas very compelling. Sad. But compelling.

    Another aspect that bothered me was that they said they couldn’t get the figures since 2000. Why? Is there something the feds don’t want us to know? Does it get worse? I imagine if it was better they’d be sure to tout that….

    It also made me wonder if women were less likely to be insured. I am unencumbered by any data on that, I’m really just curious. I thought it might be possible, though–after death of a spouse, or divorce, or just not having had access to a job with decent insurance, etc….

  2. #2 Mary
    April 30, 2008

    Oh–and if I had any graphics skills I would compare Dave Leip’s voting results atlas data by county with those maps.

    Here: http://uselectionatlas.org/RESULTS/national.php?year=2004&off=0&elect=0&f=0 and click the “counties” button.

    Keep in mind that Dave uses the old color scheme of Red = Dem because he started doing these maps before it switched.

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