Cardiovascular disease (CVD) continues to be the leading cause of death and a major source of health disparities in the Unites States and globally. Efforts to reduce CVD risk and eliminate cardiovascular health disparities have increasingly emphasized the importance of the social determinants of health. Neighborhood environments have emerged as a possible target for prevention and policy efforts. Hence there is a need to better understand the role of neighborhood environments in shaping cardiovascular risk. The MESA (Multi-Ethnic Study of Atherosclerosis) Neighborhood Study provided a unique opportunity to build a comprehensive place-based resource for investigations of associations between specific features of neighborhood physical and social environments and cardiovascular risk factors and outcomes. This review summarizes the approaches used to characterize residential neighborhood environments in the MESA cohort, provides an overview of key findings to date, and discusses challenges and opportunities in neighborhood health effects research. Results to date suggest that neighborhood physical and social environments are related to behavioral and biomedical risk factors for CVD and that cardiovascular prevention efforts may benefit from taking neighborhood context into account.

Measuring mobility is critical for understanding neighborhood influences on older adults' health and functioning. Global Positioning Systems (GPS) may represent an important opportunity to measure, describe, and compare mobility patterns in older adults.

Lack of longitudinal research hinders causal inference on the association between the built environment and walking. In the present study, we used data from 6,027 adults in the Multi-Ethnic Study of Atherosclerosis who were 45–84 years of age at baseline to investigate the association of neighborhood built environment with trends in the amount of walking between 2000 and 2012. Walking for transportation and walking for leisure were assessed at baseline and at 3 follow-up visits (median follow-up = 9.15 years). Time-varying built environment measures (measures of population density, land use, number of destinations, bus access, and street connectivity) were created using geographic information systems. We used linear mixed models to estimate the associations between baseline levels of and a change in each built environment feature and a change in the frequency of walking. After adjustment for potential confounders, we found that higher baseline levels of population density, area zoned for retail, social destinations, walking destinations, and street connectivity were associated with greater increases in walking for transportation over time. Higher baseline levels of land zoned for residential use and distance to buses were associated with less pronounced increases (or decreases) in walking for transportation over time. Increases in the number of social destinations, the number of walking destinations, and street connectivity over time were associated with greater increases in walking for transportation. Higher baseline levels of both land zoned for retail and walking destinations were associated with greater increases in leisure walking, but no changes in built environment features were associated with leisure walking. The creation of mixed-use, dense developments may encourage adults to incorporate walking for transportation into their everyday lives.

Objectives. We investigated whether moving to neighborhoods with closer proximity of destinations and greater street connectivity was associated with more walking, a greater probability of meeting the “Every Body Walk!” campaign goals (≥ 150 minutes/week of walking), and reductions in body mass index (BMI). Methods. We linked longitudinal data from 701 participants, who moved between 2 waves of the Multi-Ethnic Study of Atherosclerosis (2004–2012), to a neighborhood walkability measure (Street Smart Walk Score) for each residential location. We used fixed-effects models to estimate if changes in walkability resulting from relocation were associated with simultaneous changes in walking behaviors and BMI. Results. Moving to a location with a 10-point higher Walk Score was associated with a 16.04 minutes per week (95% confidence interval [CI] = 5.13, 29.96) increase in transport walking, 11% higher odds of meeting Every Body Walk! goals through transport walking (adjusted odds ratio = 1.11; 95% CI = 1.02, 1.21), and a 0.06 kilogram per meters squared (95% CI = −0.12, −0.01) reduction in BMI. Change in walkability was not associated with change in leisure walking. Conclusions. Our findings illustrated the potential for neighborhood infrastructure to support health-enhancing behaviors and overall health of people in the United States.