141st APHA Annual Meeting

In This section

283344
Estimation of small-area life expectancy: A comparison of two methods

Monday, November 4, 2013 : 12:30 PM - 12:50 PM

Chungfeng Ren, MPH , Department of Biostatistics, Virginia Commonwealth University, Richmond, VA
Robert Johnson, PhD , VCU Center on Human Needs, Virginia Commonwealth University School of Medicine, Richmond, VA
Laura R. Young, MPH , VCU Center on Human Needs, Virginia Commonwealth University School of Medicine, Richmond, VA
Amber Haley, MPH , VCU Center on Human Needs, Virginia Commonwealth University School of Medicine, Richmond, VA
Steven A. Cohen, DrPH, MPH , Department of Epidemiology and Community Health, Virginia Commonwealth University School of Medicine, Richmond, VA
Steven Woolf, MD , VCU Center on Human Needs, Virginia Commonwealth University School of Medicine, Richmond, VA
Life expectancy (LE) has become increasingly popular as a tool for demonstrating health disparities across countries, across U.S. states, and across small geographic areas where area-level characteristics may, in part, account for variability in health outcomes. Numerous methodological challenges arise when life table methods, which are well suited to larger populations, are applied to smaller populations. In a study funded by the California Endowment, we compared two approaches to estimating LE at the census tract level: the traditional life table method and Poisson modeling. We tabulated all mortality records from California for the period 1999-2001 and combined those with 2000 US Census data to estimate age-specific mortality rates for all populated California census tracts. The LEs produced by these two methods were compared across several characteristics: consistency across point estimates, standard deviation and confidence bounds, and number of census tract estimates marked as unreliable based on extreme population sizes or tabulated deaths. The results, and the respective abilities of the models to predict LE, suggest that the life table approach is more reliable than Poisson modeling. We will discuss our rationale and the strengths and drawbacks of each LE calculation method. Despite these limitations, our study shows that reliable LE estimation is possible when properly applied to small geographic areas.

Learning Areas:
Biostatistics, economics
Public health or related research

Learning Objectives:
Demonstrate the usability of small area life expectancy calculations. Compare and contrast two methods for predicting life expectancy from socioeconomic and demographic determinants on a fine geographic scale. Identify methodological strengths and drawbacks of each life expectancy calculation method.

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been a graduate assistant funded by multiple grants focusing on the epidemiology of mortality rate and social determinants, diabetes prevalence and diabetes cost, childhood obesity prevention, and life expectancy promotion. My scientific interests and experience have been development of strategies for identifying communities with unexpected life expectancies at a fine scale.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.