Purpose: To investigate the relationship between changes in neighbourhood walkability and subsequent cardiovascular disease (CVD) risk in Dutch adults.

Methods: We used register data from Statistics Netherlands. The study cohort consisted of all Dutch residents aged 40 or older at baseline (2009), without prior CVD, and who did not move house after baseline (n = 3,570,342). As exposure measure, we used a nationwide, objectively measured walkability index calculated for Euclidean buffers of 500m around the participants’ residential addresses for the years 1996, 2000, 2003, 2006 and 2008. To identify changes in neighbourhood walkability during these years, we applied latent class trajectory modelling. We assessed incident CVD between 2009 and 2019 using the Dutch hospital discharge register and the national cause of death register. Cox proportional hazards modelling was used to analyse associations between walkability trajectories and subsequent CVD incidence, adjusting for individual- and neighbourhood-level confounders.

Results: Most of the study population (88.06%) had a stable but relatively low walkability trajectory. We also identified two groups with a relatively higher initial neighbourhood walkability which decreased moderately (0.75%), and steeply (0.64%), over time. Furthermore, we identified two groups with a relatively lower neighbourhood walkability which increased moderately (2.18%), and steeply (8.37%), over time. We found that steep decreasing walkability was associated with a 10.7% lower risk of CVD compared to stable walkability (HR: 0.893; CI: 0.860 to 0.926). Moderately increasing walkability was associated with a 3.5% lower CVD risk (HR: 0.965; CI: 0.949 to 0.980). We also observed that steep increasing walkability was associated with a 2.1% lower risk of coronary heart disease (HR: 0.979; CI: 0.964 to 0.995). We did not find significant associations for stroke, HF, and CVD mortality in the overall population. Associations were more evident in younger age groups, in urban residents, and for CHD relative to other outcomes. Meijer

Conclusion: This study found evidence for associations of varying trajectories of changes in neighbourhood walkability over time with a lower risk of cardiovascular disease (CVD) in Dutch adults. This dynamic aspect is relevant for urban planners and policymakers to assess the potential of policies regarding neighbourhood walkability.

Purpose: The burden of obesity-related noncommunicable diseases in Asia is on the rise. This study aimed to characterize the neighborhood obesogenic built environment in Singaporeusing composite indicator approach and examine its associationwith obesity-related outcomes in a large cohort study.

Methods: Obesity-related outcomes were measured in the Multiethnic Cohort study 2 (MEC), an island-wide cohort study of adults between 21-75 years old (n = 16,895). For each neighborhood (n=868), built environment variables (n=11including bus stop, subway, green space, park, intersection, footpath and residential density; fast food, general food, fresh produce and convenience store access) were dichotomized, andfurther short-listed based on their univariate association with overweight (BMI >23kg/m2) in the cohort study. Selected components were combined to create a categorical index withhigher levels indicating more obesogenic environment.Multivariate logistic regression was used to examine the cross-sectional association between the index categories anddichotomous obesity-related measures (using specific Asian cut-off values), adjusted for personal sociodemographic characteristics. Effect modification of ethnicity was also tested.

Results: The obesogenic environment index has four components (general food outlet access, park density, subway density and residential density) and five levels, ranging from 0to 4. Most cohort study participants (n=10,487) live in levels 3 and 4, opposed to only 235 in the lowest level of obesogenicity.Compared to level 0, those residing in level 4 have 43% higher odds of overweight (95%CI: 1.08, 1.88), 48% obesity (95%CI: 1.03, 2.13), 30% high waist-to-hip ratio (95%CI: 0.96, 1.77) and27% high waist-to-height ratio (95%CI: 0.96, 1.69). Estimates were similar for other levels of obesogenicity. Stratified analysis showed elevated risks of overweight for the Malays and Indians compared to the Chinese. For the Malays, associations between the index and obesity were inverse and associations with other measures were inconsistent, while for the Chinese and Indians,associations remained consistent with the main analyses. 

Conclusion: Our study reveals a pervasive obesogenic builtenvironment in Singapore, which is consistently associated withobesity-related outcomes among residents. Our obesogenic environment index could be a practical tool for informing targeted health and infrastructure policy to address the increasing burden of obesity.

Purpose: Due to high rates of physical inactivity, social isolation, and obesity, research is needed on policies that increase opportunities for positive health behaviors. Therefore, this study examined relationships between state and local funding for parks and recreation and access to exercise opportunities, physical inactivity, social associations, and obesity.

Methods: This cross-sectional analysis used publicly available data for all U.S. counties (n=3142). State-level data from the U.S. Census Bureau, 2021 Annual Surveys of State and Local Government Finances were used to assess the percentage of state and local expenditures toward parks and recreation. For county-level estimates of access to exercise opportunities, physical inactivity, social associations, and obesity, 2021 County Health Rankings data were used. Access to exercise opportunities measures the percentage of individuals residing in a census block within a half-mile of a park or 1-3 miles (depending on rurality) of a recreational facility. Physically inactivity is the percentage of adults reporting no leisure-time physical activity. Social associations are the number of membership associations per 10,000 population. Obesity is the percentage of adults reporting a body mass index >30 kg/m². Generalized estimating equations in SAS 9.4 (with α=.05) determined relationships between state and local expenditures and four related outcomes.

Results: Parks and recreation expenditures ranged from 0.4 to 2.5% (Mean=1.1, stdev=0.4) of state and local expenditures. After adjustment, 1% increase in parks and recreation expenditures was significantly associated with a 561% increase in the percentage of residents with access to exercise opportunities (p<.0001). A 1% increase in parks and recreation expenditures was significantly associated with a 222% decrease in the percentage of residents who were physically inactive (p<.0001). A 1% increase in parks and recreation expenditures was significantly associated with an 182% decrease in the percentage of residents who were obese (p<.0001). Parks and recreation expenditures were not associated with social associations (p=.123).

Conclusions: This study highlights the importance of state and local expenditures for promoting healthy environments and behaviors at the county level across the United States. Policy measures should increase funding allocated toward parks and recreation resources, given its potential for addressing physical inactivity, social isolation, and obesity.