As compared with the control group, the group with a randomly assigned opportunity to use a voucher to move to a neighborhood with a lower poverty rate had lower prevalences of a BMI of 35 or more, a BMI of 40 or more, and a glycated hemoglobin level of 6.5% or more, representing relative reductions of 13.0%, 19.1%, and 21.6%, respectively. The magnitudes of the associations with health were larger still for participants who moved with a voucher that was restricted to use in a low-poverty area than they were for the intention-to-treat estimates for all participants who received the restricted voucher and are consistent with the effect sizes reported in previous observational studies.3
Because we generated estimates for several BMI cutoff points, our estimates for the associations between program participation and extreme obesity may be marginally significant.
Approximately half the participants randomly assigned to receive low-poverty vouchers used these vouchers, and many of the families in the control group subsequently moved to areas with lower poverty rates. Neither imperfect program compliance nor crossover compromises the internal validity of our intention-to-treat estimates, but these factors may reduce the statistical power of the analyses.
Although we could not reject the null hypothesis that the association of the traditional voucher with obesity is equal to zero or that the association is the same as that for the low-poverty voucher, the difference between the prevalence of a glycated hemoglobin level of 6.5% or more in the group that received low-poverty vouchers and the prevalence in the group that received traditional vouchers approached significance. This finding is consistent with that of previous MTO studies in which outcomes not involving health suggested that changes in the neighborhood environment, rather than the act of moving itself, are responsible for these effects32
; it is also consistent with our finding that low-poverty vouchers and traditional vouchers had different associations with neighborhood attributes that may affect health ().
An MTO study published in 2007, which measured self-reported outcomes 4 to 7 years after randomization, showed that the prevalence of obesity (defined as a BMI of 30 or more) among adults assigned to receive low-poverty vouchers was 42.0%, as compared with 46.8% for the control group.32
Use of self-reported measures raises concerns about the Hawthorne effect and the possibility that the neighborhood environment could affect self-reporting. The 2007 study was not informative with regard to long-term health effects because the problem of fade-out (attenuation in the differences in outcomes between treatment groups and control groups) is pervasive in social experiments, and the study did not show results for the most costly condition associated with obesity — diabetes.
The present study has several strengths, including the use of a large social experiment to overcome concerns about selection bias associated with epidemiologic studies and the collection of physical measurements for health outcomes 10 to 15 years after randomization. The study also had the effect of causing a relatively homogeneous group of people to live in a wider range of neighborhoods than is usual for epidemiologic studies. Because the moves led to changes in neighborhoods as defined by the most commonly used markers of neighborhood areas (e.g., tracts and ZIP Codes), the study inherently addresses the potential for measurement error that can result when epidemiologic studies use the wrong geographic proxy for “neighborhood.”34
Our study also has several limitations. First, it is possible that the participants for whom outcomes were not available in our long-term study would have differed systematically across the randomized groups in unobservable attributes. Second, our use of a glycated hemoglobin level of 6.5% or more does not account for people with successfully treated diabetes. Third, the baseline surveys conducted by HUD included little information about health. This restriction limits our ability to determine whether the association between a move to a lower-poverty neighborhood and reductions in the prevalence of obesity and diabetes reflects a change in onset or persistence, but it does not affect the internal validity of our intention-to-treat estimates.
A further limitation of the study is the fact that the participants volunteered. More than 90% of the households in the study were headed by a black or Hispanic woman and included children. Among the 1.2 million households in public housing nationwide, 50% are nonwhite and 38% headed by women with children.35
Our sample also had a higher prevalence of obesity than national samples of all U.S. families.
Although care should be taken in applying these results to populations with different attributes, our finding that neighborhood environments are associated with the prevalence of obesity and diabetes may have implications for understanding trends and disparities in overall health across the United States. The increase in U.S. residential segregation according to income in recent decades36
suggests that a larger proportion of the population is being exposed to distressed neighborhood environments. Minorities are also more likely than whites to live in distressed areas.37
The results of this study, together with those of previous studies documenting the large social costs of obesity38
raise the possibility that clinical or public health interventions that ameliorate the effects of neighborhood environment on obesity and diabetes could generate substantial social benefits. The mechanisms accounting for these associations remain unclear, but further investigation is warranted to provide guidance in designing neighborhood-level interventions to improve health.