The relationship between neighbourhood walkability and cardiovascular risk factors in northern France

The association of obesogenic environments with weight status, blood pressure, and blood lipids: A cross-sectional pooled analysis across five cohorts

In this observational cross-sectional study, we investigated the relationship between combined obesogenic neighbourhood characteristics and various cardiovascular disease risk factors in adults, including BMI, systolic blood pressure, and blood lipids, as well as the prevalence of overweight/obesity, hypertension, and dyslipidaemia. We conducted a large-scale pooled analysis, comprising data from five Dutch cohort studies (n = 183,871). Neighbourhood obesogenicity was defined according to the Obesogenic Built-environmental CharacterisTics (OBCT) index. The index was calculated for 1000m circular buffers around participants' home addresses. For each cohort, the association between the OBCT index and prevalence of overweight/obesity, hypertension and dyslipidaemia was analysed using robust Poisson regression models. Associations with continuous measures of BMI, systolic blood pressure, LDL-cholesterol, HDL-cholesterol, and triglycerides were analysed using linear regression. All models were adjusted for age, sex, education level and area-level socio-economic status. Cohort-specific estimates were pooled using random-effects meta-analyses. The pooled results show that a 10 point higher OBCT index score was significantly associated with a 0.17 higher BMI (95%CI: 0.10 to 0.24), a 0.01 higher LDL-cholesterol (95% CI: 0.01 to 0.02), a 0.01 lower HDL cholesterol (95% CI: -0.02 to -0.01), and non-significantly associated with a 0.36 mmHg higher systolic blood pressure (95%CI: -0.14 to 0.65). A 10 point higher OBCT index score was also associated with a higher prevalence of overweight/obesity (PR = 1.03; 95% CI: 1.02 to 1.05), obesity (PR = 1.04; 95% CI: 1.01 to 1.08) and hypertension (PR = 1.02; 95% CI: 1.00 to 1.04), but not with dyslipidaemia. This large-scale pooled analysis of five Dutch cohort studies shows that higher neighbourhood obesogenicity, as measured by the OBCT index, was associated with higher BMI, higher prevalence of overweight/obesity, obesity, and hypertension. These findings highlight the importance of considering the obesogenic environment as a potential determinant of cardiovascular health.

The association between the Canadian active living environments index and glucose metabolism in a Canadian national population study

Biomarkers of glucose metabolism may reflect insulin resistance, a risk factor for diabetes and cardiovascular disease (CVD). Neighborhoods conducive to a physically active lifestyle have the potential to improve these biomarkers. We examined cross-sectional associations between walkability and blood biomarkers of glucose metabolism in 29,649 Canadian Health Measures Survey (CHMS) participants. We used generalized linear mixed models with sampling weights adjusted for province, participants' age, sex, annual household income and educational attainment, cigarette smoking, environmental tobacco smoke, alcohol consumption, and exposure to ambient fine particulate air pollution (PM2.5). A higher value of the Canadian Active Living Environments Index, a measure of neighborhood walkability, equivalent to the magnitude of its interquartile range (IQR) of 2.4 was significantly associated with percentage differences of -0.48 (95% confidence interval (CI): 0.63, -0.32), -3.17 (95%CI: 5.27, -1.08), -3.88 (95%CI: 6.38, -1.38), and -3.36 (95%CI: 5.25, -1.47) in HbA1C, fasting insulin, HOMA-IR, and HOMA-β, respectively, for all CHMS participants. No significant effects were observed in those ≤16 years old. Canadians living in neighborhoods that facilitate active living have more favorable biomarkers of glucose metabolism, suggesting that the built environment has the potential to improve risk factors for diabetes and CVD in adults.

Association between residential air pollution exposure and cardiovascular risk factors in adults living in northern France

Air pollution is associated with elevated cardiovascular mortality and an increase in cardiovascular risk factors. However, the literature data on associations between air pollution and cardiovascular risk factors are contradictory. To explore the relationship between residential exposure to atmospheric pollutants and cardiovascular risk factors (lipid biomarker and blood pressure levels). We studied a sample of 2339 adult participants in the ELISABET study from the Dunkirk and Lille urban areas of France. The mean annual exposure to atmospheric pollutants (PM10, NO2 and SO2) at the home address was estimated via an air dispersion model. The associations were probed in multivariate linear regression models. The mean NO2 level was 26.05 μg/m3 in Lille and 19.96 µg/m3 in Dunkirk. The mean PM10 level was 27.02 μg/m3 in Lille and 26.53 μg/m3 in Dunkirk. We detected a significant association between exposure to air pollutants and the high-density lipoprotein (HDL) (which is a protective factor against cardiovascular diseases) level: for a 2 µg/m3 increment in PM10, the HDL level decreased by 1.72% (p = 0.0037). None of the associations with other lipid variables or with blood pressure were significant. We didn't find evidence significant associations for most of the risk factors but, long-term exposure of adults to moderate levels of ambient air pollution was associated with a decrement in HDL.

Neighborhood Access to the Built Environment and Allostatic Load: A Systematic Review of the Use of Geographic Information Systems

Objectives: This paper systematically reviews how spatial analysis has been used to measure relationships between access to the built environment and Allostatic Load (AL) or biomarkers relevant to the stress pathway. Geographic Information Systems (GIS) facilitate objective measurement of built environment access that may explain unequal health outcomes linked to living in stressful environments. Methods: Systematic review, search date 13 July 2022 with methods published a priori. Included studies that quantitatively assessed associations between GIS measures of neighborhood attributes and biomarkers of stress. Results: 23 studies from 14 countries were included having used GIS measures to assess relationships between access to the built environment and biomarkers relevant to AL, with 17 being cross-sectional and 6 longitudinal. Just 2 studies explicitly assessed associations between GIS measures and AL, but 21 explored biomarkers relevant to the stress pathway. GIS was used to calculate density (how much of x within y) and proximity (how far from a to b) measures. Conclusion: GIS measures of greenspace, the food environment, area-level demographics, and land-use measures were found to influence biomarkers relevant to the stress pathway, highlighting the utility of this approach. GIS use is extremely limited when measuring the built environment and its influence on AL but has been widely used to consider effects on individual biomarkers of stress. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=348355], identifier [CRD42022348355].

Association between area-level walkability and glycated haemoglobin: a Portuguese population-based study

Diabetes poses a substantial disease burden, prompting preventive interventions. Physical inactivity, a major risk factor for type 2 diabetes, can potentially be mitigated by enhancing area-level walkability. Despite this, limited population-based studies have investigated the link between walkability and objective diabetes measures. Our study aims to estimate the association between area-level walkability and individual glycated haemoglobin levels in the Portuguese adult population without the diagnosis of diabetes. Data from the 2011 census and an updated street map were obtained to construct a walkability index based on residential density, land-use mix, and street connectivity. Individual health data were sourced from The National Health Examination Survey (INSEF) 2015, a representative survey of the Portuguese adult population. Gamma regression was employed for estimation of the main associations, revealing that residing in moderately walkable areas significantly reduced average glycated haemoglobin levels (Exp(β) = 0.906; 95% CI: 0.821, 0.999) compared to the least walkable areas. The association was less pronounced and not statistically significant for the third tertile of walkability (Exp(β) = 0.919; 95% CI: 0.822, 1.028). Our findings highlight a nonlinear protective association between walkability and glycated haemoglobin, emphasizing the potential policy implications for urban planning, diabetes prevention, and health promotion.

Neighbourhood Walkability and Its Influence on Physical Activity and Cardiometabolic Disease: A Cross-Sectional Study in a Caribbean Small Island Developing State

Introduction Cities and neighborhoods may provide opportunities for population-level environmental interventions to reduce physical inactivity and cardiometabolic risk. In this study, we describe the association between neighborhood walkability, physical activity (PA), and cardiometabolic outcomes, by linking data from a nationally representative survey of adults (25 years and older) collected in 2012-2013 with spatial data on built environment features in Barbados. Methods We estimated a walkability index for 45 neighborhoods using objectively measured built environment features (residential density, street connectivity, and land use mix). We used the Recent Physical Activity Questionnaire to capture time spent in outdoor walking, active commuting, moderate-to-vigorous PA (MVPA), and total PA. Our primary cardiometabolic outcome was a predicted 10-year cardiovascular risk (CVD) score, estimated using the American College of Cardiology/American Heart Association pooled cohort equation. Our secondary cardiometabolic outcomes were hypertension and diabetes. We explored the effect of neighborhood walkability on PA and cardiometabolic outcomes using several multivariable regression models (tobit and linear and logistic multi-level mixed effects), with the model choice depending on the structure of the outcome.  Results The average time spent walking weekly for any purpose among participants was 75 minutes/week, time spent on active commuting was 15 minutes/week, and MVPA was 221 minutes/week. We estimated that the average 10-year CVD risk in the study population was 11.7% (95%CI 10.9-12.5). Our confounder-adjusted analyses showed positive linear relationships between neighborhood walkability and each PA outcome (p<0.05 in all cases), and a negative relationship between walkability and predicted 10-year CVD risk (p<0.001). Conclusion In our setting, adults residing in higher walkability neighborhoods spent more time engaged in PA, had a lower predicted 10-year CVD risk, and were less likely to have diabetes. Urban planners may consider shorter-term interventions, such as those on a microscale, which may provide additional ways to increase activity in a mostly fixed macroscale environment.

Associations of Urban Built Environment with Cardiovascular Risks and Mortality: a Systematic Review

With rapid urbanization, built environment has emerged as a set of modifiable factors of cardiovascular disease (CVD) risks. We conducted a systematic review to synthesize evidence on the associations of attributes of urban built environment (e.g. residential density, land use mix, greenness and walkability) with cardiovascular risk factors (e.g. hypertension and arterial stiffness) and major CVD events including mortality. A total of 63 studies, including 31 of cross-sectional design and 32 of longitudinal design conducted across 21 geographical locations and published between 2012 and 2023 were extracted for review. Overall, we report moderately consistent evidence of protective associations of greenness with cardiovascular risks and major CVD events (cross-sectional studies: 12 of 15 on hypertension/blood pressure (BP) and 2 of 3 on arterial stiffness; and longitudinal studies: 6 of 8 on hypertension/BP, 7 of 8 on CVD mortality, 3 of 3 on ischemic heart disease mortality and 5 of 8 studies on stroke hospitalization or mortality reporting significant inverse associations). Consistently, walkability was associated with lower risks of hypertension, arterial stiffness and major CVD events (cross-sectional studies: 11 of 12 on hypertension/BP and 1 of 1 on arterial stiffness; and longitudinal studies: 3 of 6 on hypertension/BP and 1 of 2 studies on CVD events being protective). Sixty-seven percent of the studies were rated as "probably high" risk of confounding bias because of inability to adjust for underlying comorbidities/family history of diseases in their statistical models. Forty-six percent and 14% of the studies were rated as "probably high" risk of bias for exposure and outcome measurements, respectively. Future studies with robust design will further help elucidate the linkages between urban built environment and cardiovascular health, thereby informing planning policies for creating healthy cities.

Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments

BACKGROUND

The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understanding contextual determinants, the resources provided by technological advances could become a key factor in obesogenic environment research. This study aims to identify different sources of non-traditional data and their applications, considering the domains of obesogenic environments: physical, sociocultural, political and economic.

METHODS

We conducted a systematic search in PubMed, Scopus and LILACS databases by two independent groups of reviewers, from September to December 2021. We included those studies oriented to adult obesity research using non-traditional data sources, published in the last 5 years in English, Spanish or Portuguese. The overall reporting followed the PRISMA guidelines.

RESULTS

The initial search yielded 1583 articles, 94 articles were kept for full-text screening, and 53 studies met the eligibility criteria and were included. We extracted information about countries of origin, study design, observation units, obesity-related outcomes, environment variables, and non-traditional data sources used. Our results revealed that most of the studies originated from high-income countries (86.54%) and used geospatial data within a GIS (76.67%), social networks (16.67%), and digital devices (11.66%) as data sources. Geospatial data were the most utilised data source and mainly contributed to the study of the physical domains of obesogenic environments, followed by social networks providing data to the analysis of the sociocultural domain. A gap in the literature exploring the political domain of environments was also evident.

CONCLUSION

The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.

Built environment and schizophrenia re-hospitalization risk in China: A cohort study

BACKGROUND

Built environment exposure, characterized by ubiquity and changeability, has the potential to be the prospective target of public health policy. However, little research has been conducted to explore its impact on schizophrenia. This study aimed to investigate the association between built environmentand and schizophrenia rehospitalization by simultaneously considering substantial built environmental exposures.

METHODS

We recruited eligible schizophrenia patients from Hefei, Anhui Province, China between 2017 and 2019. The main outcome for this study was the time interval until the first recurrent hospital admission occurred within one year after discharge. For each included subject, we estimated the built environment exposures, including population density, walkability, land use mix, green and blue space, public transportation accessibility and road traffic indicator. Lasso (Least Absolute Shrinkage and Selection Operator) analysis was used to select the key variables. Multivariable Cox regression model was applied to obtain hazard ratio (HR) and its corresponding 95% confidence intervals (CI). Further, we also evaluated the joint effects of built environment characteristics on rehospitalization for schizophrenia by Quantile g-computation model.

RESULTS

A total of 1564 hospitalized schizophrenia patients were enrolled, with 347 patients (22.2%) had a rehospitalization within one-year after discharge. Multivariable Cox regression analysis indicated that the re-hospitalization rate for schizophrenia would be higher in areas with a high population density (HR: 1.10, 95%CI: 1.04-1.16). Nonetheless, compared to the reference (Q1), participants who lived in a neighborhood with the highest walkability and NDVI (Normalized Difference Vegetation Index) (Q4) had a 76% and 47% lower risk of re-hospitalization within one year (HR:0.24, 95%CI: 0.13-0.45; and 0.53, 95%CI:0.32-0.85), respectively. Moreover, quantile-based g-computation analyses revealed that increased walkability and green space significantly eliminated the adverse effects of population density increases on schizophrenia patients, with a HR ratio of 0.61 (95%CI:0.48,0.79) per one quartile change at the same time.

CONCLUSION

Our study provides scientific evidence for the significant role of built environment in schizophrenia rehospitalization, suggesting that optimizing the built environment is required in designing and building a healthy city.

Favorable Neighborhood Walkability is Associated With Lower Burden of Cardiovascular Risk Factors Among Patients Within an Integrated Health System: The Houston Methodist Learning Health System Outpatient Registry

This is the first study to investigate the relationship between neighborhood walkability and cardiovascular (CV) risk factors in the United States using a large population-based database. Cross-sectional study using data from 1.1 million patients over the age of 18 in the Houston Methodist Learning Health System Outpatient Registry (2016-2022). Using the 2019 WalkScore, patients were assigned to one of the 4 neighborhood walkability categories. The burden of CV risk factors (hypertension, diabetes, obesity, dyslipidemia, and smoking) was defined as poor, average, or optimal (>3, 1-2, 0 risk factors, respectively). We included 887,654 patients, of which 86% resided in the two least walkable neighborhoods. The prevalence of CV risk factors was significantly lower among participants in the most walkable neighborhoods irrespective of ASCVD status. After adjusting for age, sex, race/ethnicity, and socioeconomic factors, we found that adults living in the most walkable neighborhoods were more likely to have optimal CV risk profile than those in the least walkable ones (RRR 2.77, 95% CI 2.64-2.91). We observed an inverse association between neighborhood walkability and the burden of CV risk factors. These findings support multilevel health system stakeholder engagements and investments in walkable neighborhoods as a viable tool for mitigating the growing burden of modifiable CV risk factors.

Associations between greenspace surrounding schools and lipid levels in Chinese children and teenagers

Little evidence exists concerning the associations of greenspace with childhood lipid profiles and dyslipidemias, especially in developing countries and regions. We aimed to investigate the associations of greenspace surrounding schools with lipid levels and dyslipidemia prevalence among Chinese children and teenagers. We obtained baseline information and health data of 10,408 children and teenagers (aged 6-18 years) who studied from 94 schools in China. We measured levels of four blood lipids: triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Dyslipidemias were defined using standard recommendations. Greenness surrounding schools were assessed using two satellite-based greenness indices, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) at 300-, 500-, and 1000-m circular buffers based on each school's latitude and longitude. We used random forest model combined with meteorological and remote sensing data to estimate air pollution levels surrounding each school. We used generalized linear mixed models to estimate the associations of greenness with lipid levels and dyslipidemias prevalence. We also performed sub-group and mediation analyses. An interquartile range (IQR) increase in NDVI_500m was significantly associated with a 0.064 mmol/L (95% confidence interval [CI]: 0.083, -0.045) and 0.049 mmol/L (95% CI: 0.065, -0.033) decreased TC and LDL-C levels, respectively, as well as a 0.13-fold (95% CI: 0.01, 0.23) and 0.17-fold (95% CI: 0.01, 0.30) decreased odds of hypercholesterolemia and hyperbetalipoproteinemia, respectively. Associations were stronger in students aged ≤12 years and born to parents having lower education levels compared to their counterparts. Particle with aerodynamic diameter ≤2.5 μm (PM_2.5) mediated 61.5% and 16.7% of the association of greenness with TG and LDL-C levels, respectively. In summary, higher school-based greenness exposure was beneficially associated with lipid levels among Chinese children and adolescents, and part of the association can be explained by lowed PM_2.5 levels.

Using an Exposome-Wide Approach to Explore the Impact of Urban Environments on Blood Pressure among Adults in Beijing-Tianjin-Hebei and Surrounding Areas of China

Existing studies mostly explored the association between urban environmental exposures and blood pressure (BP) in isolation, ignoring correlations across exposures. This study aimed to systematically evaluate the impact of a wide range of urban exposures on BP using an exposome-wide approach. A multicenter cross-sectional study was conducted in ten cities of China. For each enrolled participant, we estimated their urban exposures, including air pollution, built environment, surrounding natural space, and road traffic indicator. On the whole, this study comprised three statistical analysis steps, that is, single exposure analysis, multiple exposure analysis and a cluster analysis. We also used deletion-substitution-addition algorithm to conduct variable selection. After considering multiple exposures, for hypertension risk, most significant associations in single exposure model disappeared, with only neighborhood walkability remaining negatively statistically significant. Besides, it was observed that SBP (systolic BP) raised gradually with the increase in PM_2.5, but such rising pattern slowed down when PM_2.5 concentration reached a relatively high level. For surrounding natural spaces, significant protective associations between green and blue spaces with BP were found. This study also found that high population density and public transport accessibility have beneficially significant association with BP. Additionally, with the increase in the distance to the nearest major road, DBP (diastolic BP) decreased rapidly. When the distance was beyond around 200 m, however, there was no obvious change to DBP anymore. By cluster analysis, six clusters of urban exposures were identified. These findings reinforce the importance of improving urban design, which help promote healthy urban environments to optimize human BP health.

Walkability Compass—A Space Syntax Solution for Comparative Studies

The ongoing discourse on air quality and climate changes positions walkability as a pivotal point of sustainable urban planning. Urban studies examine a city’s walkability in terms of pedestrian flows, design qualities, and street network topology, leaving walkability comparative frameworks under development. Building on the space syntax theory, this research introduces a “walkability compass”, a four spatial indicator-designed tool for city walkability assessment and comparison. The tools are being tested on eight Baltic region cities: Vilnius, Kaunas (LT), Malmö (SE), Riga (LV), Tallinn (ES), Gdansk, Bialystok, Lublin (PL). The nine-step method framework integrates four indexes: Gravity (Gr), Reach (Re), Straightness (St), and Population density (Pop). The “walkability compass” results reveal significant Re and St correlations; thus, visual and cultural aspects become the main factors in pedestrian-friendly cities. The spatial pattern typology has matched similar cities (Malmö and Kaunas) to work closely on sustainable urban planning development. In all case studies, specific walkability zones were mapped, but the Gr zones turned out to be the most compact ones (the Z-score of Gr was ranged from 355.4 to 584; other indexes oscillated between 209.4 and 542.6). The walkability mapping results are publicly shared via WebMap to stimulate the participatory discussion on case studies cities further development.