Skip to main content Skip to site navigation

Minding the Gap in Las Muertes

Staff Perspective Karen Pfister

I lead our Epidemiology program at the San Mateo County Health System and assist with statistical analysis and provide data for policy and program planning. Our Epidemiologists at the Health System help to ensure our policy work is grounded in evidence. Through data reports and requests, we share health information with community members and other stakeholders on the health of San Mateo County.

In the public health and medical communities, we can use many different measures to assess the health status of a population. These include indicators such as infant mortality rate, maternal mortality ratio, total fertility rate, and life expectancy at birth1.  Of these, life expectancy is one of the more commonly used measures across the world to answers one of the most basic questions:  how long are we expected to live? 

Life expectancy is a little more complicated than that, however, because it is actually the average number of years a newborn baby is expected to live if the mortality patterns that exist at the time they are born remain constant in the future. Life expectancy can be used to compare health across geographic areas as well as different educational levels, by race/ethnicity, and income. Quite a bit of work has been done in recent years to assess life expectancy by these socio-demographic factors. An article published in the Journal of the American Medical Association (JAMA) in April of this year found that in the U.S. between 2001 and 2014, having a higher income was associated with greater longevity, as the gap in life expectancy between the richest 1% and poorest 1% was nearly 15 years for men and 10 years for women.3  

Life expectancy also differs by race and education. A 2012 study found that White men and women with higher education (16 years of education or more) had life expectancies much greater than Black men and women who had less than 12 years of education.4  The study showed that the difference in life expectancy between these two groups was as much as 14 years for men and 10 years for women. To make matters worse, just as the JAMA research mentioned, the gaps have widened over time to the point where this article stated that it has led to the development of “at least two different Americas.” 

When examining life expectancy by race/ethnicity in San Mateo County, similar trends are observed with Blacks faring much worse than the other racial/ethnic groups (see Table 1).  Based on mortality data from 2013, Black individuals in the county had a life expectancy of only about 76 years, while all the other groups (with the exception of Pacific Islanders) and the county overall had life expectancies in the 80’s. 

Table 1:  Life Expectancy by Race/Ethnicity, San Mateo County, 2013

Race/Ethnicity

Life Expectancy (in years)

Asian

86.7

Hispanic

86.1

All

84.2

White

83.1

Pacific Islander

76.8

Black

75.6

Data source:  San Mateo County Death Statistical Master File, 2013

What can be done to improve a population’s life expectancy?  Improved economic and educational opportunities for the segments of the population that don’t currently have them would go a long way in reducing life expectancy disparities. Medical advances that reduce disease, public health and environmental health efforts that continue to improve the hygienic and built environments that we live in are also ways that life expectancy could be increased. By building healthy, equitable communities we can prevent many diseases before they ever occur and reduce these health disparities together.

 

Literature Cited:

1http://www.who.int/healthinfo/indicators/2015/100CoreHealthIndicators_2015_infographic.pdf?ua=1

2H.M. Kravitz. Average age at death. Encyclopedia of Biostatistics.  2005.

3R. Chetty, et al.  The association between income and life expectancy in the United States, 2001-2014. JAMA. 2016; 315(16):  1750-1766.

4 S.J. Olshansky, et al. Differences in life expectancy due to race and educational differences are widening, and many may not catch up. Health Affairs. 2012; 21(8):  1803-1813.

Commands