Neighborhood Walkability as a Predictor of Incident Hypertension in a National Cohort Study

Association between community walkability and hypertension: Evidence from the Wuhan Chronic Disease Cohort Study

While community walkability is recognized as a key environmental factor for health status, evidence linking it specifically to hypertension is rather limited. To fill the knowledge gap, we concluded a cross-sectional study among 6421 eligible participants from the Wuhan Chronic Disease Cohort. A well-developed algorithm was performed to evaluate community walkability across Wuhan, quantified as Walk Score. We then calculated each participant residential Walk Score using the geographic information system. The logistic and linear regression models were conducted to determine the relationship between walkability, hypertension and blood pressure, respectively. We further performed the mediation analysis to explore potential mechanisms. After adjusting for extra confounders, we observed a higher community walk score was associated with a lower hypertension risk (OR = 0.73; 95% CI: 0.63, 0.84), a lower systolic blood pressure (β = -3.152 mmHg; 95% CI: -4.25, -2.05), a lower diastolic blood pressure (β = -2.237 mmHg; 95% CI: -2.95, -2.53) and a lower mean arterial pressure (β = -2.976 mmHg; 95% CI: -3.75, -2.20). The effect of community walkability on hypertension was partially mediated by body fat rate. Our study indicates a positive correlation between high walkability and a reduced odds of hypertension in China. This highlights the potential role of urban design in hypertension prevention, emphasizes the need for walkability-focused planning strategies to foster healthier communities, and guides future interventions and research to mitigate hypertension.

Exploring the impact of the environment on physical activity in patients with chronic obstructive pulmonary disease (EPCOT)-A comparative analysis between suggested and free walking: Protocol study

BACKGROUND

Individuals with chronic obstructive pulmonary disease (COPD) exhibit reduced levels of physical activity, which are associated with poorer outcomes. The number of clinical trials aiming to promote behavioral changes to increase physical activity in this population has grown; therefore, these trials have yet to produce satisfactory results. An ecological model encompassing individual, social, environmental, and political factors represent a potentially more effective approach to promoting physical activity. While favorable urban environments can positively impact physical activity, specifically tailored environmental interventions for individuals with COPD could enhance their engagement in physical activity. Therefore, the aim of this randomized controlled trial (RCT) study was to analyze the effects of walking in a suggested environment and free walking on physical activity levels in individuals with COPD.

METHODS

The environment on physical activity for chronic obstructive disease (EPCOT) is a randomized controlled clinical trial protocol approved by our institution's Ethics Committee and registered with The Brazilian Registry of Clinical Trials (ReBEC) (https://ensaiosclinicos.gov.br, number RBR-4tfwdhp). This protocol will involve 38 volunteers diagnosed with COPD recruited from the pulmonary physiotherapy and rehabilitation service. The volunteers were randomly divided into two walking groups: an experimental group (ERG) with guidance for walking in a suggested environment and an active control group (ACG) instructed to choose their own routes. The intervention consisted of eight consecutive weeks, with progressive walks carried out 3 to 5 times weekly. The primary outcome will be assessing participants' physical activity levels. Secondary outcomes will include exercise capacity, quality of life, dyspnea levels, motivation, anxiety, depression, and perceptions of the environment. All assessments will occur before and after the intervention period, aiming to fill a literature gap by investigating the impact of urban environments on COPD-related physical activity. The results may shed light on the importance of environmental factors in promoting physical activity among individuals with COPD, helping to develop more effective interventions.

Impact of Social Determinants of Health on Hypertension Outcomes: A Systematic Review

Despite ample evidence linking social determinants of health (SDoH) and hypertension outcomes, efforts to address SDoH in the context of hypertension prevention and self-management are not commensurate with the burden and impact of hypertension. To provide valuable insights into the development of targeted and effective strategies for preventing and managing hypertension, this systematic review, guided by the Healthy People 2030 SDoH framework, aims to summarize the inclusion, measurement, and evaluation of SDoH in studies examining hypertension outcomes, with a focus on characterizing SDoH constructs and summarizing the current evidence of their influence on hypertension outcomes. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a comprehensive search of electronic databases identified 10 608 unique records, from which 57 articles meeting inclusion criteria were analyzed. The studies, conducted nationally or regionally across the United States, revealed that higher educational attainment, health insurance coverage, income, and favorable neighborhood characteristics were associated with lower hypertension prevalence and better hypertension control among US adults. The findings underscore the importance of addressing SDoH such as education, health care access, economic stability, neighborhood environments, and social context to reduce hypertension disparities. Multilevel collaboration and community-engaged practices are necessary to tackle these disparities effectively.

Neighborhood Walkability Is Associated With Lower Burden of Cardiovascular Risk Factors Among Cancer Patients

Background

Modifiable cardiovascular risk factors constitute a significant cause of cardiovascular disease and mortality among patients with cancer. Recent studies suggest a potential link between neighborhood walkability and favorable cardiovascular risk factor profiles in the general population.

Objectives

This study aimed to investigate whether neighborhood walkability is correlated with favorable cardiovascular risk factor profiles among patients with a history of cancer.

Methods

We conducted a cross-sectional study using data from the Houston Methodist Learning Health System Outpatient Registry (2016-2022) comprising 1,171,768 adults aged 18 years and older. Neighborhood walkability was determined using the 2019 Walk Score and divided into 4 categories. Patients with a history of cancer were identified through International Classification of Diseases-10th Revision-Clinical Modification codes (C00-C96). We examined the prevalence and association between modifiable cardiovascular risk factors (hypertension, diabetes, smoking, dyslipidemia, and obesity) and neighborhood walkability categories in cancer patients.

Results

The study included 121,109 patients with a history of cancer; 56.7% were female patients, and 68.8% were non-Hispanic Whites, with a mean age of 67.3 years. The prevalence of modifiable cardiovascular risk factors was lower among participants residing in the most walkable neighborhoods compared with those in the least walkable neighborhoods (76.7% and 86.0%, respectively). Patients with a history of cancer living in very walkable neighborhoods were 16% less likely to have any risk factor compared with car-dependent-all errands neighborhoods (adjusted OR: 0.84, 95% CI: 0.78-0.92). Sensitivity analyses considering the timing of events yielded similar results.

Conclusions

Our findings demonstrate an association between neighborhood walkability and the burden of modifiable cardiovascular risk factors among patients with a medical history of cancer. Investments in walkable neighborhoods may present a viable opportunity for mitigating the growing burden of modifiable cardiovascular risk factors among patients with a history of cancer.

Spatial Vision Inequalities: A Literature Review of the Impact of Place on Vision and Eye Health Outcomes

"Neighborhood and built environment" is one of the five domains of social determinants of health that has been outlined by Healthy People 2030, and this domain impacts an individual's well-being, health, and quality of life. Social risk factors (SRFs) in the neighborhood and built environment domain include unstable or unsafe housing, poor access to transportation, lack of green spaces, pollution, safety concerns, and neighborhood measures of inequity. In this narrative literature review, we assess the relationship between neighborhood and built environment SRFs and eye health and vision outcomes. We explain how mapping neighborhood-level SRFs may be used to advance health equity in the field of eye health and vision care.

Association between racial residential segregation and walkability in 745 U.S. cities

Despite higher chronic disease prevalence, minoritized populations live in highly walkable neighborhoods in US cities more frequently than non-minoritized populations. We investigated whether city-level racial residential segregation (RRS) was associated with city-level walkability, stratified by population density, possibly explaining this counterintuitive association. RRS for Black-White and Latino-White segregation in large US cities was calculated using the Index of Dissimilarity (ID), and walkability was measured using WalkScore. Median walkability increased across increasing quartiles of population density, as expected. Higher ID was associated with higher walkability; associations varied in strength across strata of population density. RRS undergirds the observed association between walkability and minoritized populations, especially in higher population density cities.

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.

Neighborhood Walkability and Cardiovascular Risk in the United States

Neighborhood walkability may be associated with increased physical activity and thus may confer protection against cardiovascular disease and associated risk factors. We sought to characterize the association between neighborhood-level cardiovascular diseases and risk factors with neighborhood walkability across US census tracts.We linked the Centers for Disease Control and Prevention (CDC) PLACES dataset which provided census-tract level prevalence of coronary artery disease (CAD) and cardiovascular risk factors (hypertension, high cholesterol, obesity, and diabetes), with census tract population-weighted national walkability index (NWI) from the US Environmental Protection Agency (EPA). We calculated the mean prevalence of each cardiovascular health indicator per quartile of the walkability score. We also fit a multivariable linear regression model to estimate the association between walkability index and the prevalence of CAD adjusting for age, sex, race, and the CDC'S social vulnerability index, an integrated metric of socioeconomic position. We additionally performed mediation analyses to understand the mediating effects of CAD risk factors on the relationship between NWI and CAD prevalence. A total of 70,123 census tracts were analyzed nationwide. Across walkability quartiles Q1 (least walkable) through Q4 (most walkable), we found statistically significant decrease in the prevalence of CAD (7.0% to 5.4%), and risk factors including hypertension (35.5% to 29.7%), high cholesterol (34.5% to 29.2%), obesity (35.0% to 30.2%), and diabetes (11.6% to 10.6%). After multivariable adjustment, continuous walkability index was negatively and significantly associated with the prevalence of CAD (β = -0.09, P<0.0001). The relationship between NWI and CAD is partially mediated by the risk factors. High cholesterol accounted for 45%, high blood pressure 41% and diabetes 10% of the total effect of walkability on CAD. While direct relationship between walkability and CAD accounted for 9% of the total effect. This nationwide analysis demonstrates that neighborhood walkability is associated with a lower prevalence of cardiovascular risk factors and CAD. The association between NWI and CAD seems to be partly mediated by prevalence of traditional risk factors.

Association of community walkability and glycemic control among pregnant individuals with pregestational diabetes mellitus

BACKGROUND

Neighborhood walkability is a community-level social determinant of health that measures whether people who live in a neighborhood walk as a mode of transportation. Whether neighborhood walkability is associated with glycemic control among pregnant individuals with pregestational diabetes remains to be defined.

OBJECTIVE

This study aimed to evaluate the association between community-level neighborhood walkability and glycemic control as measured by hemoglobin A1c (A1C) among pregnant individuals with pregestational diabetes.

STUDY DESIGN

This was a retrospective analysis of pregnant individuals with pregestational diabetes enrolled in an integrated prenatal and diabetes care program from 2012 to 2016. Participant addresses were geocoded and linked at the census-tract level. The exposure was community walkability, defined by the US Environmental Protection Agency National Walkability Index (score range 1-20), which incorporates intersection density (design), proximity to transit stops (distance), and a mix of employment and household types (diversity). Individuals from neighborhoods that were the most walkable (score, 15.26-20.0) were compared with those from neighborhoods that were less walkable (score <15.26), as defined per national Environmental Protection Agency recommendations. The outcomes were glycemic control, including A1C <6.0% and <6.5%, measured both in early and late pregnancy, and mean change in A1C across pregnancy. Modified Poisson regression and linear regression were used, respectively, and adjusted for maternal age, body mass index at delivery, parity, race and ethnicity as a social determinant of health, insurance status, baseline A1C, gestational age at A1C measurement in early and late pregnancy, and diabetes type.

RESULTS

Among 417 pregnant individuals (33% type 1, 67% type 2 diabetes mellitus), 10% were living in the most walkable communities. All 417 individuals underwent A1C assessment in early pregnancy (median gestational age, 9.7 weeks; interquartile range, 7.4-14.1), and 376 underwent another A1C assessment in late pregnancy (median gestational age, 30.4 weeks; interquartile range, 27.8-33.6). Pregnant individuals living in the most walkable communities were more likely to have an A1C <6.0% in early pregnancy (15% vs 8%; adjusted relative risk, 1.46; 95% confidence interval, 1.00-2.16), and an A1C <6.5% in late pregnancy compared with those living in less walkable communities (13% vs 9%; adjusted relative risk, 1.33; 95% confidence interval, 1.08-1.63). For individuals living in the most walkable communities, the median A1C was 7.5 (interquartile range, 6.0-9.4) in early pregnancy and 5.9 (interquartile range, 5.4-6.4) in late pregnancy. For those living in less walkable communities, the median A1C was 7.3 (interquartile range, 6.2-9.2) in early pregnancy and 6.2 (interquartile range, 5.6-7.1) in late pregnancy. Change in A1C across pregnancy was not associated with walkability.

CONCLUSION

Pregnant individuals with pregestational diabetes mellitus living in more walkable communities had better glycemic control in both early and late pregnancy. Whether community-level interventions to enhance neighborhood walkability can improve glycemic control in pregnancy requires further study.

Higher walkability associated with increased physical activity and reduced obesity among United States adults

OBJECTIVE

This study examined associations among perceived neighborhood walkability, physical activity (PA), and obesity among United States adults.

METHODS

Data from the 2020 National Health Interview Survey were analyzed. Walkability was assessed using a summative scale and was categorized as low, medium, or high. PA was categorized as insufficient (0-149 min/wk) or sufficient (150+ min/wk). Multivariable regressions estimated an association between obesity and BMI and PA/walkability. Mediation analysis was used to partition contribution of PA as a mediator. Effect modification by race and ethnicity in the association between walkability and BMI was explored.

RESULTS

The sample included N = 31,568 adults. Compared with those in low-walkability neighborhoods, participants in high-walkability neighborhoods had increased odds of sufficient PA (odds ratio [OR] = 1.48; 95% CI: 1.30-1.69) and decreased obesity odds (OR = 0.76; 95% CI: 0.66-0.87). PA partially mediated the association between walkability and BMI (23.4%; 95% CI: 14.6%-62.7%). The association between walkability and BMI was modified by race and ethnicity (F[5,567]  = 2.75; p = 0.018). Among White, Black, Hispanic, and Asian adults, BMI decreased with increasing walkability; among American Indian/Alaska Native and multiracial/other adults, BMI increased with increasing walkability.

CONCLUSIONS

The findings highlight the importance of investing in the built environment to improve perceptions of walkability and promote PA and healthy weight, as well as developing interventions to target racial and ethnic disparities in these outcomes.

Identifying Communities at Risk for COVID-19-Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

BACKGROUND

Although it is well-known that older individuals with certain comorbidities are at the highest risk for complications related to COVID-19 including hospitalization and death, we lack tools to identify communities at the highest risk with fine-grained spatial resolution. Information collected at a county level obscures local risk and complex interactions between clinical comorbidities, the built environment, population factors, and other social determinants of health.

OBJECTIVE

This study aims to develop a COVID-19 community risk score that summarizes complex disease prevalence together with age and sex, and compares the score to different social determinants of health indicators and built environment measures derived from satellite images using deep learning.

METHODS

We developed a robust COVID-19 community risk score (COVID-19 risk score) that summarizes the complex disease co-occurrences (using data for 2019) for individual census tracts with unsupervised learning, selected on the basis of their association with risk for COVID-19 complications such as death. We mapped the COVID-19 risk score to corresponding zip codes in New York City and associated the score with COVID-19-related death. We further modeled the variance of the COVID-19 risk score using satellite imagery and social determinants of health.

RESULTS

Using 2019 chronic disease data, the COVID-19 risk score described 85% of the variation in the co-occurrence of 15 diseases and health behaviors that are risk factors for COVID-19 complications among ~28,000 census tract neighborhoods (median population size of tracts 4091). The COVID-19 risk score was associated with a 40% greater risk for COVID-19-related death across New York City (April and September 2020) for a 1 SD change in the score (risk ratio for 1 SD change in COVID-19 risk score 1.4; P<.001) at the zip code level. Satellite imagery coupled with social determinants of health explain nearly 90% of the variance in the COVID-19 risk score in the United States in census tracts (r²=0.87).

CONCLUSIONS

The COVID-19 risk score localizes risk at the census tract level and was able to predict COVID-19-related mortality in New York City. The built environment explained significant variations in the score, suggesting risk models could be enhanced with satellite imagery.

Identifying Communities at Risk for COVID-19-Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

BACKGROUND

Although it is well-known that older individuals with certain comorbidities are at the highest risk for complications related to COVID-19 including hospitalization and death, we lack tools to identify communities at the highest risk with fine-grained spatial resolution. Information collected at a county level obscures local risk and complex interactions between clinical comorbidities, the built environment, population factors, and other social determinants of health.

OBJECTIVE

This study aims to develop a COVID-19 community risk score that summarizes complex disease prevalence together with age and sex, and compares the score to different social determinants of health indicators and built environment measures derived from satellite images using deep learning.

METHODS

We developed a robust COVID-19 community risk score (COVID-19 risk score) that summarizes the complex disease co-occurrences (using data for 2019) for individual census tracts with unsupervised learning, selected on the basis of their association with risk for COVID-19 complications such as death. We mapped the COVID-19 risk score to corresponding zip codes in New York City and associated the score with COVID-19-related death. We further modeled the variance of the COVID-19 risk score using satellite imagery and social determinants of health.

RESULTS

Using 2019 chronic disease data, the COVID-19 risk score described 85% of the variation in the co-occurrence of 15 diseases and health behaviors that are risk factors for COVID-19 complications among ~28,000 census tract neighborhoods (median population size of tracts 4091). The COVID-19 risk score was associated with a 40% greater risk for COVID-19-related death across New York City (April and September 2020) for a 1 SD change in the score (risk ratio for 1 SD change in COVID-19 risk score 1.4; P<.001) at the zip code level. Satellite imagery coupled with social determinants of health explain nearly 90% of the variance in the COVID-19 risk score in the United States in census tracts (r2=0.87).

CONCLUSIONS

The COVID-19 risk score localizes risk at the census tract level and was able to predict COVID-19-related mortality in New York City. The built environment explained significant variations in the score, suggesting risk models could be enhanced with satellite imagery.