UC Berkeley

Background

While many studies have found the built environment to be associated with walking, most have used cross-sectional research designs and few have examined more distal cardiometabolic outcomes. This study contributes longitudinal evidence based on changes in walking, body mass index (BMI), and cardiometabolic risk following residential relocation.

Methods

We examined 1,079 participants in the CARDIA study who moved residential locations between 2000 and 2006 (ages 32-46 in 2000, 49% white/51% black, 55% female). We created a walkability index from measures of population density, street connectivity, and food and physical activity resources, measured at participants' pre- and post-move residential locations. Outcomes measured before and after the move included walking, BMI, waist circumference, blood pressure, insulin resistance, triglycerides, cholesterol, atherogenic dyslipidemia, and C-reactive protein. Fixed effects (FE) models were used to estimate associations between within-person change in walkability and within-person change in each outcome. These estimates were compared to those from random effects (RE) models to assess the implications of unmeasured confounding.

Results

In FE models, a one-SD increase in walkability was associated with a 0.81 mmHg decrease in systolic blood pressure [95% CI: (-1.55, -0.07)] and a 7.36 percent increase in C-reactive protein [95% CI: (0.60, 14.57)]. Although several significant associations were observed in the RE models, Hausman tests suggested that these estimates were biased for most outcomes. RE estimates were most commonly biased away from the null or in the opposite direction of effect as the FE estimates.

Conclusions

Greater walkability was associated with lower blood pressure and higher C-reactive protein in FE models, potentially reflecting competing health risks and benefits in dense, walkable environments. RE models tended to overstate or otherwise misrepresent the relationship between walkability and health. Approaches that base estimates on variation between individuals may be subject to bias from unmeasured confounding, such as residential self-selection.