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Journal of Health Economics

Volume 30, Issue 6, December 2011, Pages 1174–1187

# Rising educational gradients in mortality: The role of behavioral risk factors

- David M. Cutler a, 1, ,
- Fabian Lange b, , , ,
- Ellen Meara c, 2, ,
- Seth Richards-Shubik d, 3, ,
- Christopher J. Ruhm e, 4,

- a Department of Economics, Littauer Center, 1875 Cambridge Street, Harvard University, Cambridge, MA 02138, United States
- b Department of Economics, Yale University, New Haven, CT 06520-8268, United States
- c The Dartmouth Institute for Health Policy and Clinical Practice, 35 Centerra Parkway, Lebanon, NH 03766, United States
- d H. John Heinz III College, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213-3890, United States
- e Frank Batten School of Leadership and Public Policy, University of Virginia, 235 McCormick Road, P.O. Box 400893, Charlottesville, VA 22904, United States

  Received 22 October 2010, Revised 24 May 2011, Accepted 13 June 2011, Available online 3 September 2011

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  https://doi.org/10.1016/j.jhealeco.2011.06.009
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Referred to by
  - David M. Cutler, Fabian Lange, Ellen Meara, Seth Richards-Shubik, Christopher J. Ruhm

  - ## Corrigendum to “Rising educational gradients in mortality: The role of behavioral risk factors” [J. Health Econ. 30 (6) (2011) 1174–1187]

  - Journal of Health Economics, Volume 31, Issue 6, December 2012, Page 888
  - - PDF (85 K)

## Abstract

The long-standing inverse relationship between education and mortality strengthened substantially at the end of the 20th century. This paper examines the reasons for this increase. We show that behavioral risk factors are not of primary importance. Smoking declined more for the better educated, but not enough to explain the trend. Obesity rose at similar rates across education groups, and control of blood pressure and cholesterol increased fairly uniformly as well. Rather, our results show that the mortality returns to risk factors, and conditional on risk factors, the return to education, have grown over time.

## JEL classification

- I10;
- I20;
- J11

## Keywords

- Health inequality;
- Risk factors;
- Education and mortality;
- Smoking;
- Obesity

## 1. Introduction

Mortality in the United States has declined by much more among the better educated than among the less educated. Between 1960 and 1986, education-related differences in mortality grew 20% (Pappas et al., 1993). The gap widened further and more rapidly in the decade after 1990, when life expectancy of those attending college increased an additional 1.6 years with no change among those who did not go to college, yielding a 30% growth in life expectancy gaps by education (Meara et al., 2008). By 2000, college-educated 25-year olds could expect to live 7 years longer than their peers with less schooling. These patterns have thrust the issue of health disparities onto the political agenda. Reducing such disparities (by race and ethnicity as well as economic status), along with improving population health, are two major components of the Healthy People 2010 objectives ( U.S. Department of Health and Human Services, 2000).

Sources of the increase in these educational gradients remain poorly understood. Some studies show that advantaged individuals receive better and earlier medical care than their less advantaged counterparts (e.g. Rathore et al., 2000). Other analyses stress behavioral differences: the better educated are less likely to smoke, drink, or (at least among women) to be obese (Cutler and Lleras-Muney, 2008). Still other research suggests the possibility that high status individuals are less exposed to unalleviated stress (Marmot, 2006).

This paper analyzes the extent to which behavioral differences (smoking and obesity), and their immediate medical correlates (hypertension and high cholesterol), explain changes in educational mortality gradients occurring over the past three decades.5 Smoking and obesity are natural to examine because they are the two leading behavioral causes of death in the United States. Tobacco use is responsible for about 435,000 premature deaths annually (Mokdad et al., 2000) and obesity for between 100,000 and 400,000 early deaths per year (Flegal et al., 2005 ; Willett et al., 2005).6 Since the obese often develop high blood pressure (hypertension) and high cholesterol (hypercholesterolemia), and management of these risk factors is itself a behavioral issue, we further examine how disease management varies across education groups. Finally, we separately consider deaths due to cardiovascular disease (CVD, mostly heart disease) and cancer, since these represent major sources of premature mortality and are responsive to changes in modifiable risk factors.

Cutler et al. (2009) show that behavioral risk factors play an important role in understanding changes in overall mortality trends. They estimated the contribution of demographics and risk factors (smoking, drinking, obesity, and blood pressure) to 10-year mortality risk during the last three decades of the 20th century and provide evidence that decreases in smoking and better control of hypertension contribute most to the substantial reductions in age-adjusted deaths rates, while increases in obesity raised mortality risk (also see Olshansky et al., 2005 ; Stewart et al., 2009). We use similar data but, instead of focusing on the entire population, assess the extent to which differential changes in risk factors explain secular increases in education-related mortality gaps.

Our analysis reveals three primary findings. First, education-gradients in mortality are stronger for men than women but have increased over time for both sexes. Second, despite the importance of smoking, obesity, hypertension, and cholesterol as determinants of population health, differential changes in these risk factors do not explain the widening educational gap in death rates since the 1970s. Finally, the mortality returns to risk factors and the return to education, conditioning on them, have grown over time for reasons that are not yet understood. Thus, even if less educated populations were able to achieve risk factor profiles mirroring those with more education, widening mortality differentials would likely persist.

Three explanations seem likely to explain why the impacts of risk factors and education have increased over time. First, access to medical care may have become more important for detecting disease early and treating it appropriately, and the better educated have superior access to care. Second, the living environments (i.e. the exposure to environmental health risks) may have improved more over time for the better educated. Third, the management of chronic health problems may have become more sophisticated in ways that favor those with more schooling. Our data are not adequate to test these theories, which we leave to subsequent research.

Sections 2 ; 3 present the data we analyze and descriptive trends in mortality, and the fourth section our empirical approach. The fifth section reports our mortality regressions, and the sixth section uses these to understand changes in the education-gradient in mortality. Section 7 examines CVD and cancer deaths. The last section concludes.

## 2. Data and key variables

Our analysis utilizes data from various waves of the National Health and Nutrition Examination Surveys (NHANES) and multiple years of the National Health Interview Survey (NHIS). The NHANES and NHIS both provide samples that are nationally representative of the non-institutionalized U.S. population in the specified period, using stratified, multi-stage probability cluster designs. Information on subsequent mortality for selected surveys is used to estimate education-related differences in death rates. The remainder of this section describes the surveys and key explanatory variables.

### 2.1. The National Health and Nutrition Examination Survey

Baseline information for this study was obtained from NHANES I, covering the period 1971–1975. Subsequent descriptive data are from the NHANES II (1976–1980) and NHANES III (1998–1994), and the first six years (1999–2004) of the continuous NHANES survey (hereafter referred to as NHANES IV).7 The NHANES is particularly useful since it includes a physical exam component providing clinical measures of weight, height, blood pressure, and cholesterol. Our analysis is limited to non-Hispanic whites, since the earlier NHANES does not provide adequate size to estimate mortality among non-white or Hispanic populations. All results are age-adjusted and separated by gender, so that trends do not reflect changes in these characteristics.

The absence of persons institutionalized at baseline reduces the estimates of future mortality, since the institutionalized have higher death rates than the rest of the population. However, Meara et al. (2008) demonstrate that, conditional on surviving one year, the mortality rates for adults initially living in the community closely resemble those reported in published statistics for the entire population. Therefore, we limit the sample to individuals surviving at least one year from the baseline interview for all mortality models estimated below.

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