Height, health, and income in the
US, 1984–2005
Inas Rashad
Georgia State University and NBER, Department of Economics,
Andrew Young School of Policy Studies,
P.O. Box 3992, Atlanta, GA 30302–3992, USA
Received 15 October 2007; accepted 15 October 2007
Abstract
Height has been associated with better physical health when outcomes such as diabetes, heart disease,
and obesity are considered, yet stature is rarely used in predicting comorbidities or as a proxy for physical
health when analyzing outcomes such as income. Since height is a more exogenous measure than variables
likely to be affected by lifestyle changes, such as obesity, observing labor market outcomes based on height
may be revealing. In addition, gender and racial differences must be taken into account when analyzing the
effects of height on physical health and labor market outcomes. This study utilizes the 1984–2005 samples
of the Behavioral Risk Factor Surveillance System in estimating trends in height over time by gender and
race, and in analyzing the relationship between height and physical health and labor market outcomes in the
United States. Trends show that height has not changed substantially at a time when physical health, as
indicated by the incidence of obesity, Type II diabetes, and cholesterol, has deteriorated, and earnings
disparities across racial gaps persist. Results at mean values for males indicate that being 10 cm taller is
associated with a 14–47% increase in obesity, an 8–13% reduction in cholesterol prevalence, and a $1874–
2306 income premium. For females, results indicate that being 10 cm taller is associated with an 8–18%
reduction in cholesterol, a 14% reduction in diabetes for white females, and an $891–2243 earnings
premium.
# 2007 Elsevier B.V. All rights reserved.
JEL classification: I10; I12
Keywords: Height; Income; Health production; USA; Physical stature; Anthropometry
http://www.elsevier.com/locate/ehb
Available online at www.sciencedirect.com
Economics and Human Biology 6 (2008) 108–126
E-mail address: irashad@gsu.edu.
1570-677X/$ – see front matter # 2007 Elsevier B.V. All rights reserved.
doi:10.1016/j.ehb.2007.10.002

1. Introduction
Height is an underutilized variable in predicting health outcomes across populations and yet is
a strong predictor of early-life biological health (Komlos and Lauderdale, 2007; Komlos and
Baur, 2004; Tanner, 1978). Height can be used as a proxy for physical health in analyzing a
variety of outcomes such as those regarding the labor market. One concern when analyzing the
effect of health on income is reverse causality, in that having a lower income may affect health
negatively. Thus the potential issue with having an independent variable that is not completely
independent, or one that is endogenous, may be of concern. To the extent that adult height
remains constant over time until circa age 45, contemporary lifestyle variables do not affect it. It
can therefore be considered an exogenous measure of physical health.
Nutrition and environmental conditions in childhood are determinants of adult stature, yet are
more useful in determining differences across populations than in determining how tall an
individual may become within a country.1 Genetics plays a much greater role in the latter, thus
allowing for an independent factor in predicting subsequent health.
A study by Persico et al. (2004) analyzes the wage premium received by taller white men.
Using data from the 1979 cohort of the National Longitudinal Survey of Youth and Britain’s
National Child Development Survey (NCDS), they find that adolescent height at age 16
affects the wage premium more than adult height. They mainly attribute this to self-esteem
and find that the effect is partially mediated through participation in after-school activities
when in high school. They do not adjust for self-reported height, which is measured to the
nearest inch, raising the spectra of errors in the independent variable as height for younger
individuals may be even more prone to error (Himes and Faricy, 2001). Their findings are
supplemented by those found by Sargent and Blanchflower (1994), who find an effect of
height at age 16 on subsequent labor market outcomes using the British NCDS, and Loh
(1993), who finds a positive effect using the NLSY. A recent study by Case and Paxson
(2006) argues that the wage premium experienced by taller persons is largely due to height’s
correlation with cognitive ability. They use the NCDS in addition to the British Cohort Study
(BCS), the US National Health Interview Survey (NHIS), and the US Panel Study of Income
Dynamics (PSID).
Several studies have investigated the relationship between physical health and income,
using measures of obesity as proxies for physical health or beauty. Averett and Korenman
(1996) use a sample of 23- to 31-year-olds to analyze the effects of the body mass index
(BMI) on income, marital status, and hourly pay differentials. Using the 1979 National
Longitudinal Survey of Youth, they control for family background by comparing same-sex
siblings and find that prior measures of BMI affect income of white but not African-
American females. They find mixed results for males. Additional studies (Cawley, 2004;
Conley and Glauber, 2005) reach similar conclusions using different methods of dealing with
the endogeneity of obesity. On the other hand, some studies (Baum and Ford, 2004) find little
effect of obesity on labor market outcomes.
I. Rashad / Economics and Human Biology 6 (2008) 108–126 109
1 While taller populations tend to be healthier, it should be noted that many other factors determine population health.
Those who argue that individuals in countries such as Japan enjoy higher life expectancies need to control for nutritional
and cultural differences and lifestyle factors that contribute to life expectancy. Comparing differences over time within
populations may thus be useful. Differences in access to health care between the US and European countries may partially
explain differences in height changes between these countries (Komlos and Lauderdale, 2007).