Related Experiment Video
Updated: Aug 9, 2026

Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
Income inequality and mortality in metropolitan areas of the United States
J W Lynch1, G A Kaplan, E R Pamuk
1Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor 48109-2029, USA.
Objectives:
This study examined associations between income inequality and mortality in 282 US metropolitan areas.
Methods:
Income inequality measures were calculated from the 1990 US Census. Mortality was calculated from National Center for Health Statistics data and modeled with weighted linear regressions of the log age-adjusted rate.
Results:
Excess mortality between metropolitan areas with high and low income inequality ranged from 64.7 to 95.8 deaths per 100,000 depending on the inequality measure. In age-specific analyses, income inequality was most evident for infant mortality and for mortality between ages 15 and 64.
Conclusions:
Higher income inequality is associated with increased mortality at all per capita income levels. Areas with high income inequality and low average income had excess mortality of 139.8 deaths per 100,000 compared with areas with low inequality and high income. The magnitude of this mortality difference is comparable to the combined loss of life from lung cancer, diabetes, motor vehicle crashes, human immunodeficiency virus (HIV) infection, suicide, and homicide in 1995. Given the mortality burden associated with income inequality, public and private sector initiatives to reduce economic inequalities should be a high priority.
More Related Videos
06:55Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
09:50Real-World M3-BREATHE: Toward Multimodal Mobile Monitoring of Behaviour, Respiration, and Exposures for Treatment and Health Evaluation
Published on: June 5, 2026
Related Concept Videos
Regression Toward the Mean
Skewness
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency are...
Statistical Methods for Analyzing Epidemiological Data
Life Tables
Kaplan-Meier Approach
Applications of Life Tables