Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment

Abstract

BACKGROUND The question of whether neighborhood environment contributes directly to the development of obesity and diabetes remains unresolved. The study reported on here uses data from a social experiment to assess the association of randomly assigned variation in neighborhood conditions with obesity and diabetes. METHODS From 1994 through 1998, the Department of Housing and Urban Development (HUD) randomly assigned 4498 women with children living in public housing in high-poverty urban census tracts (in which ≥40% of residents had incomes below the federal poverty threshold) to one of three groups: 1788 were assigned to receive housing vouchers, which were redeemable only if they moved to a low-poverty census tract (where <10% of residents were poor), and counseling on moving; 1312 were assigned to receive unrestricted, traditional vouchers, with no special counseling on moving; and 1398 were assigned to a control group that was offered neither of these opportunities. From 2008 through 2010, as part of a long-term follow-up survey, we measured data indicating health outcomes, including height, weight, and level of glycated hemoglobin (HbA1c). RESULTS As part of our long-term survey, we obtained data on body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) for 84.2% of participants and data on glycated hemoglobin level for 71.3% of participants. Response rates were similar across randomized groups. The prevalences of a BMI of 35 or more, a BMI of 40 or more, and a glycated hemoglobin level of 6.5% or more were lower in the group receiving the low-poverty vouchers than in the control group, with an absolute difference of 4.61 percentage points (95% confidence interval [CI], −8.54 to −0.69), 3.38 percentage points (95% CI, −6.39 to −0.36), and 4.31 percentage points (95% CI, −7.82 to −0.80), respectively. The differences between the group receiving traditional vouchers and the control group were not significant. CONCLUSIONS The opportunity to move from a neighborhood with a high level of poverty to one with a lower level of poverty was associated with modest but potentially important reductions in the prevalence of extreme obesity and diabetes. The mechanisms underlying these associations remain unclear but warrant further investigation, given their potential to guide the design of community-level interventions intended to improve health. (Funded by HUD and others.)

Social Determinants of Risk and Outcomes for Cardiovascular Disease

“…However, in the only study of its kind, Ludwig and colleagues 109 analyzed data from the Moving to Opportunity Study, in which 4498 women from 5 cities in the United States were randomized to 1 of 3 conditions: a voucher to move to a low-poverty neighborhood, a voucher to move to any neighborhood, or no voucher (control group). After 10 to 15 years of follow-up, women receiving the low-poverty voucher were significantly less likely to have a BMI >35 kg/m 2 , a BMI >40 kg/m 2 , or a glycated hemoglobin >6.5% compared with women in the control group.…”

Low Income and Rural County of Residence Increase Mortality from Bone and Joint Sarcomas

“…Recently, an important 10-15 years long-term study demonstrated that moving patients from low income neighborhoods to higher ones improved their obesity and diabetes (Ludwig et al, 2011;2012). In this study examined three SEFs: i) whether the patients lived in a rural as opposed to urban counties; ii) whether the patients lived in a county with a family income equal or lower than $50000 per year as opposed to a higher one; and iii) whether the patients lived in a low college education attainment county were examined.…”

Preventing Type 2 Diabetes in Communities Across the U.S.

“…As an example, a recent social experiment in which low-income families were randomized to receive vouchers that moved them to healthier neighborhoods found reduced prevalence of obesity and diabetes after 5 years. 33 Such studies are rare, however, and are a reminder of the difficulty of demonstrating impact of policy approaches and the need for a broader spectrum of research to guide policies. 34 …”