Healthy living in hard times
Section snippets
Data and methods
Data are from 1987 to 2000 interview years of the Behavioral Risk Factor Surveillance System, an annual telephone survey of the non-institutionalized adult population administered by the Centers for Disease Control and Prevention. Thirty-four states participated in 1987 and at least 45 throughout the 1990s. Sample sizes are large, exceeding 50,000 in each year analyzed, and increase over time so that the 14-year sample contains almost 1.5 million observations.11
Lifestyles get healthier in bad times
Evidence from a variety of econometric specifications demonstrates that lifestyles become healthier when economic conditions worsen. Table 2 provides initial estimates of the predicted effect of a one point increase in the percent of the state population employed on smoking, obesity, physical inactivity and multiple health risks.28 All specifications control for individual characteristics, month
Population subgroups
Table 4 provides results for subsamples stratified by employment status, education, sex and race/ethnicity. For each group, the first column shows the (weighted) mean of the dependent variable, the second displays marginal effects (with other explanatory variables evaluated at the sample averages) and the third indicates percentage changes.
Despite significant differences in lifestyles, a procyclical pattern of unhealthy behaviors is observed for all groups. The predicted effects are of equal
Mechanisms
Table 5 tests whether changes in incomes or leisure time help to explain the fluctuations in lifestyles. Specification (a) repeats findings of the basic econometric model. Column (b) adds state–age–sex–education group average household incomes and weekly work hours as supplementary regressors. We anticipate obtaining positive parameter estimates for income and hours if these factors account for a portion of the macroeconomic effects, since both increase in good times.40
Adjustment paths
It may seem surprising that the previous econometric specifications, which control for employment rates during only a three-month period, are able to detect effects for lifestyle behaviors that probably respond slowly to changes in macroeconomic conditions. For instance, body weight represents a stock that is determined by the accumulated flows of calorie intake and expenditure, and behaviors like smoking may also change gradually or respond differently in the short-run than in the medium-term.
Discussion
Lifestyle changes provide one mechanism for improvements in physical health during temporary downturns. A one point drop in the percentage of the population employed is estimated to reduce the prevalence of smoking, obesity, physical inactivity and multiple health risks by 0.6, 0.4, 0.7 and 1.1%. The decline in body weight is concentrated among the severely obese and groups with relatively high risk of early death (like males, African–Americans and Hispanics). Increases in exercise largely
Acknowledgements
I thank Peter Bearse, Ken Snowden and seminar participants at IZA, North Carolina State, Rand, Stanford, the Medical University of South Carolina, National Bureau of Economic Research, University California at Santa Barbara, University of California at Santa Cruz, and the Virginia Polytechnic and State University for helpful comments; Olga Khavjou provided superb research assistance. Financial support for this research was provided by the National Science Foundation (SES-9876511). The opinions,
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