Disparities in Pedestrian Streetscape Environments by Income and Race/Ethnicity

Disparities in neighborhood food environment and cognitive decline among US older adults: a cohort study

BACKGROUND

Disparities in neighborhood food environments in the United States, attributed to numerous complex economic, social, and political factors, likely to contribute to disparities in access to healthy food and cognitive function in older adults. However, the role of food environment in cognitive function is not well understood. Accordingly, this study examined the association of residing a low food access and low-income neighborhood with changes in cognitive function among older adults in urban areas.

METHODS

This is a cohort study leveraging existing datasets. The 2010 Food Access Research Atlas data was linked to the 2011-2021 National Health and Aging Trends Study (NHATS). A total of 4768 urban-dwelling older adults aged 65 years and older were included in this analysis. Total cognitive function (range: 0-33) was assessed through tests of orientation, executive function, immediate memory, and delayed memory. An unhealthy food environment was defined as residing in census tracts with both low access to healthy food stores and low income. Survey-weighted mixed-effects models were fitted, adjusting for individual- and area-level covariates.

RESULTS

The mean age of participants was 77.1 years (SD = 7.6), and 2779 were women (weighted % = 56.7). A total of 1238 participants (weighted % = 9.9%) were racialized as Black, 365 (weighted % = 9.1%) racialized as Latinx, and 3165 (weighted % = 81.1%) racialized as White. In adjusted models, older urban- and community-dwelling adults living in neighborhoods with low access and low income had faster annual cognitive decline than their peers (β = - 0.19; 95% CI = - 0.32, - 0.05).

CONCLUSIONS

Living in neighborhoods with both low food access and low income may be a risk factor for accelerated cognitive decline among urban-dwelling older adults and contribute to widening disparities in healthy food access and cognitive decline.

Associations of neighbourhood walkability with patterns of device-measured stepping, standing and sitting

BACKGROUND

Neighbourhood walkability is known to be positively associated with self-reported and device-based measures of overall physical activity. However, relations of walkability with specific active and sedentary behaviour patterns are not well understood.

METHODS

We investigated cross-sectional associations of neighbourhood walkability with time spent stepping, standing, sitting, and their pattern metrics using data from 505 participants (mean age 59.2 years) from the AusDiab3 study. Neighbourhood walkability (a composite measure of residential, destination, and intersection densities) was calculated within 1 km street-network buffers around participants' homes. Thigh-worn device data (activPAL, 7-day, 24 h/day protocol) were used to derive stepping, sitting and standing minutes per day and their pattern metrics. Two-level linear mixed models assessed relevant associations, adjusting for potential confounders.

RESULTS

Higher walkability was associated with higher cadences (β [95% CI] = 0.12 [0.04-0.20]), moderate-to-vigorous physical activity (β [95% CI] = 0.17 [0.09-0.26]), longer stepping bouts (β [95% CI] = 0.18 [0.10-0.25]) and time in purposeful (≥ 2 min duration) walking (β [95% CI] = 0.21 [0.13-0.30]). There were no associations with total sitting time, standing time, or their associated pattern metrics. Total stepping time also had no associations, suggesting that participants in neighbourhoods with higher walkability may accumulate similar levels of stepping time to participants in lower walkability neighbourhoods, albeit with higher intensity and in longer bouts.

CONCLUSIONS

By examining activity totals only, relevant walkability relationships may be masked. Further research is needed to understand whether walkability and other built environment attributes are associated with sedentary behaviour patterns, as well as light-intensity physical activities.

Social Deprivation Index and Pediatric Pedestrian-vs-Automobile Collisions in Ohio

BACKGROUND

Social Deprivation Index (SDI) is a composite measurement of disadvantage in which higher SDI indicates worse social deprivation. Previous studies have suggested a relationship between pedestrian-vs-automobile (PVA) collisions and poverty among adults, but a similar association using state-level pediatric data has not previously been shown. We hypothesize that pediatric PVA collision incidence will differ with SDI and urbanicity across Ohio.

METHODS

Coordinates for pediatric PVA collisions between January 2012 through January 2023 from Ohio's Department of Transportation were spatially joined to zip codes. SDI was merged with 5-year American Community Survey population estimates (0-17 years) at the zip code level. Rural-Urban Commuting Area Codes determined urbanicity. Wilcoxon rank-sum tests compared pediatric PVA collision incidence (number of collisions per 10 000 population members aged <18 years) pairwise among SDI quintiles. Zero-inflated negative binomial regression analysis modeled the odds of a zip code being collision-free.

RESULTS

Across 1188 zip codes, 5521 pediatric PVA collisions were identified. Adjusting for population size, PVA incidence was higher in zip codes with very high or high SDI compared with moderate SDI (P < .001), as well as moderate SDI compared with low or very low SDI (P = .02). The odds that a zip code was collision-free decreased by 2% for every unit increase in SDI (P < .001). Rural zip codes had 6.5-times higher odds of being collision-free than urban zip codes (P < .001).

CONCLUSIONS

Children in urban zip codes and zip codes with higher SDI are more vulnerable to PVA collisions. Next steps include identifying opportunities for targeted intervention, including traffic calming measures and traffic safety education programs.

Neighborhood built environment, obesity, and diabetes: A Utah siblings study

Background

This study utilizes innovative computer vision methods alongside Google Street View images to characterize neighborhood built environments across Utah.

Methods

Convolutional Neural Networks were used to create indicators of street greenness, crosswalks, and building type on 1.4 million Google Street View images. The demographic and medical profiles of Utah residents came from the Utah Population Database (UPDB). We implemented hierarchical linear models with individuals nested within zip codes to estimate associations between neighborhood built environment features and individual-level obesity and diabetes, controlling for individual- and zip code-level characteristics (n = 1,899,175 adults living in Utah in 2015). Sibling random effects models were implemented to account for shared family attributes among siblings (n = 972,150) and twins (n = 14,122).

Results

Consistent with prior neighborhood research, the variance partition coefficients (VPC) of our unadjusted models nesting individuals within zip codes were relatively small (0.5%-5.3%), except for HbA1c (VPC = 23%), suggesting a small percentage of the outcome variance is at the zip code-level. However, proportional change in variance (PCV) attributable to zip codes after the inclusion of neighborhood built environment variables and covariates ranged between 11% and 67%, suggesting that these characteristics account for a substantial portion of the zip code-level effects. Non-single-family homes (indicator of mixed land use), sidewalks (indicator of walkability), and green streets (indicator of neighborhood aesthetics) were associated with reduced diabetes and obesity. Zip codes in the third tertile for non-single-family homes were associated with a 15% reduction (PR: 0.85; 95% CI: 0.79, 0.91) in obesity and a 20% reduction (PR: 0.80; 95% CI: 0.70, 0.91) in diabetes. This tertile was also associated with a BMI reduction of -0.68 kg/m2 (95% CI: -0.95, -0.40).

Conclusion

We observe associations between neighborhood characteristics and chronic diseases, accounting for biological, social, and cultural factors shared among siblings in this large population-based study.

Evaluation of a walking school bus program: a cluster randomized controlled trial

BACKGROUND

The purpose of this study was to investigate the effects of a walking school bus intervention on children's active commuting to school.

METHODS

We conducted a randomized controlled trial (RCT) in Houston, Texas (Year 1) and Seattle, Washington (Years 2-4) from 2012 to 2016. The study had a two-arm, cluster randomized design comparing the intervention (walking school bus and education materials) to the control (education materials) over one school year October/November - May/June). Twenty-two schools that served lower income families participated. Outcomes included percentage of days students' active commuting to school (primary, measured via survey) and moderate-to-vigorous physical activity (MVPA, measured via accelerometry). Follow-up took place in May or June. We used linear mixed-effects models to estimate the association between the intervention and outcomes of interest.

RESULTS

Total sample was 418 students [Mage=9.2 (SD = 0.9) years; 46% female], 197 (47%) in the intervention group. The intervention group showed a significant increase compared with the control group over time in percentage of days active commuting (β = 9.04; 95% CI: 1.10, 16.98; p = 0.015) and MVPA minutes/day (β = 4.31; 95% CI: 0.70, 7.91; p = 0.02).

CONCLUSIONS

These findings support implementation of walking school bus programs that are inclusive of school-age children from lower income families to support active commuting to school and improve physical activity.

TRAIL REGISTRATION

This RCT is registered at clinicaltrials.gov (NCT01626807).

Pedestrian crash frequency: Unpacking the effects of contributing factors and racial disparities

In this paper, we unpack the magnitude effects of the determinants of pedestrian crashes using a multivariate analysis approach. We consider four sets of exogenous factors that characterize residential neighborhoods as well as potentially affect pedestrian crashes and the racial composition of such crashes: (1) crash risk exposure (CE) attributes, (2) cultural variables, (3) built environment (BE) features, and (4) sociodemographic (SD) factors. Our investigation uses pedestrian crash and related data from the City of Houston, Texas, which we analyze at the spatial Census Block Group (CBG) level. Our results indicate that social resistance considerations (that is, minorities resisting norms as they are perceived as being set by the majority group), density of transit stops, and road design considerations (in particular in and around areas with high land-use diversity) are the three strongest determinants of pedestrian crashes, particularly in CBGs with a majority of the resident population being Black. The findings of this study can enable policymakers and planners to develop more effective countermeasures and interventions to contain the growing number of pedestrian crashes in recent years, as well as racial disparities in pedestrian crashes. Importantly, transportation safety engineers need to work with social scientists and engage with community leaders to build trust before leaping into implementing planning countermeasures and interventions. Issues of social resistance, in particular, need to be kept in mind.

Understanding the factors affecting the quantity and composition of street litter: Implication for management practices

Some urban areas have more litter than others. Understanding the reason for this is important not only for dealing with urban littering but also for marine water quality because approximately 80% of the world's marine litter originates on land. This study aimed to better understand the quality and quantity of litter on sidewalks along with the sampling site's socio-economic attributes to better discern why some areas have more/different litter than others and what, if any, are the implications for a more tailored waste management strategy. We surveyed twice each of the 35 sites we selected from the Lower Passaic River watershed and the related Harbor Estuary within New Jersey, U.S.A. A total of 28,431 litter items were recorded with a total mass and volume of 245.8 kg and 4.7 m³, respectively. Floatable items accounted for 66% of all objects collected. Cigarette butts were the most numerous among all items (28%) and represented 43% of the total floatable items, the remaining 57% being represented by potentially recyclable items such as plastic, rubber, and Styrofoam. Stepwise linear regression was used to explore the relationship between the litter collected and various predictors. Among others, the results suggest the importance of strategically placing collection bins around properties with relatively lower assessed values, outdoor smoking areas, close to schools, and places where people predominantly walk to their destination. Possible management strategies include prohibiting single use plastic bags, limiting foam food ware, public education, and outreach.

Association of Neighborhood Racial and Ethnic Composition and Historical Redlining With Built Environment Indicators Derived From Street View Images in the US

Importance

Racist policies (such as redlining) create inequities in the built environment, producing racially and ethnically segregated communities, poor housing conditions, unwalkable neighborhoods, and general disadvantage. Studies on built environment disparities are usually limited to measures and data that are available from existing sources or can be manually collected.

Objective

To use built environment indicators generated from online street-level images to investigate the association among neighborhood racial and ethnic composition, the built environment, and health outcomes across urban areas in the US.

Design, Setting, and Participants

This cross-sectional study was conducted using built environment indicators derived from 164 million Google Street View images collected from November 1 to 30, 2019. Race, ethnicity, and socioeconomic data were obtained from the 2019 American Community Survey (ACS) 5-year estimates; health outcomes were obtained from the Centers for Disease Control and Prevention 2020 Population Level Analysis and Community Estimates (PLACES) data set. Multilevel modeling and mediation analysis were applied. A total of 59 231 urban census tracts in the US were included. The online images and the ACS data included all census tracts. The PLACES data comprised survey respondents 18 years or older. Data were analyzed from May 23 to November 16, 2022.

Main Outcomes and Measures

Model-estimated association between image-derived built environment indicators and census tract (neighborhood) racial and ethnic composition, and the association of the built environment with neighborhood racial composition and health.

Results

The racial and ethnic composition in the 59 231 urban census tracts was 1 160 595 (0.4%) American Indian and Alaska Native, 53 321 345 (19.5%) Hispanic, 462 259 (0.2%) Native Hawaiian and other Pacific Islander, 17 166 370 (6.3%) non-Hispanic Asian, 35 985 480 (13.2%) non-Hispanic Black, and 158 043 260 (57.7%) non-Hispanic White residents. Compared with other neighborhoods, predominantly White neighborhoods had fewer dilapidated buildings and more green space indicators, usually associated with good health, and fewer crosswalks (eg, neighborhoods with predominantly minoritized racial or ethnic groups other than Black residents had 6% more dilapidated buildings than neighborhoods with predominantly White residents). Moreover, the built environment indicators partially mediated the association between neighborhood racial and ethnic composition and health outcomes, including diabetes, asthma, and sleeping problems. The most significant mediator was non-single family homes (a measure associated with homeownership), which mediated the association between neighborhoods with predominantly minority racial or ethnic groups other than Black residents and sleeping problems by 12.8% and the association between unclassified neighborhoods and asthma by 24.2%.

Conclusions and Relevance

The findings in this cross-sectional study suggest that large geographically representative data sets, if used appropriately, may provide novel insights on racial and ethnic health inequities. Quantifying the impact of structural racism on social determinants of health is one step toward developing policies and interventions to create equitable built environment resources.

Tourist Landscape Preferences in a Historic Block Based on Spatiotemporal Big Data-A Case Study of Fuzhou, China

Historic blocks are valuable architectural and landscape heritage, and it is important to explore the distribution characteristics of tourists to historic blocks and their landscape preferences to realize the scientific construction and conservation of historic blocks and promote their sustainable development. At present, few studies combine the analysis of tourist distribution characteristics with landscape preferences. This study takes the historic block of Three Lanes and Seven Alleys in Fuzhou as an example, combines field research and questionnaires to construct a landscape preference evaluation indicator system for the historic block, measures the distribution characteristics of tourists in the block through the heat value of tourist flow obtained from the Tencent regional heat map, and analyses the influence of landscape preference indicators on the heat value of tourist flow in the block through stepwise multiple linear regression. The research shows that: (1) the spatial and temporal variation in the heat value of tourist flow tends to be consistent throughout the block, from 7 a.m. to 6 p.m., showing a "rising, slightly fluctuating and then stabilizing" state, both on weekdays and on weekends. (2) The factors influencing the heat value of tourist flow in the different spatial samples are various, with commercial atmosphere, plant landscape, accessibility of the road space, architecture, and the surrounding environment having a significant impact on the heat value of tourist flow. Based on the analysis of the landscape preferences of tourists in the historic block, a landscape optimization strategy is proposed to provide a reference for the management and construction of the block.

Micro-scale pedestrian streetscapes and physical activity in Hispanic/Latino adults: Results from HCHS/SOL

We examined associations of micro-scale environment attributes (e.g., sidewalks, street crossings) with three physical activity (PA) measures among Hispanic/Latino adults (n = 1776) living in San Diego County, CA. Systematic observation was used to quantify micro-scale environment attributes near each participant's home. Total PA was assessed with accelerometers, and PA for transportation and recreation were assessed by validated self-report. Although several statistically significant interactions between individual and neighborhood characteristics were identified, there was little evidence micro-scale attributes were related to PA. An important limitation was restricted environmental variability for this sample which lived in a small area of a single county.

Behavioral Counseling Interventions to Promote a Healthy Diet and Physical Activity for Cardiovascular Disease Prevention in Adults Without Cardiovascular Disease Risk Factors: US Preventive Services Task Force Recommendation Statement

IMPORTANCE

Cardiovascular disease (CVD), which includes heart disease, myocardial infarction, and stroke, is the leading cause of death in the US. A large proportion of CVD cases can be prevented by addressing modifiable risk factors, including smoking, obesity, diabetes, elevated blood pressure or hypertension, dyslipidemia, lack of physical activity, and unhealthy diet. Adults who adhere to national guidelines for a healthy diet and physical activity have lower rates of cardiovascular morbidity and mortality than those who do not; however, most US adults do not consume healthy diets or engage in physical activity at recommended levels.

OBJECTIVE

To update its 2017 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a review of the evidence on the benefits and harms of behavioral counseling interventions to promote healthy behaviors in adults without CVD risk factors.

POPULATION

Adults 18 years or older without known CVD risk factors, which include hypertension or elevated blood pressure, dyslipidemia, impaired fasting glucose or glucose tolerance, or mixed or multiple risk factors such as metabolic syndrome or an estimated 10-year CVD risk of 7.5% or greater.

EVIDENCE ASSESSMENT

The USPSTF concludes with moderate certainty that behavioral counseling interventions have a small net benefit on CVD risk in adults without CVD risk factors.

RECOMMENDATION

The USPSTF recommends that clinicians individualize the decision to offer or refer adults without CVD risk factors to behavioral counseling interventions to promote a healthy diet and physical activity. (C recommendation).

Analyzing pediatric bicycle injuries using geo-demographic data

PURPOSE

Bicycle accidents are potentially preventable, and helmets can mitigate the severity of injuries. The purpose of the study it to investigate geo-demographic areas to establish prevention policies and targeted programs.

METHODS

From October 2013 to March 2020 all bicycle injuries at a Level 1 trauma center were collected for ages ≤18 years. Demographics, injuries, and outcomes were analyzed. Incidents were aggregated to zip codes and the Local Indicators of Spatial Association (LISA) statistic was used to test for spatial clustering of injury rates per 10,000 children.

RESULTS

Over the 8-year time period, 77 cases were identified with an average age of 13±4 years, 83% male and 48% non-Hispanic white. The majority of patients (98%) were not wearing a helmet. Loss of consciousness was reported in 44% and 21% sustained a traumatic brain injury. Twenty-eight percent required ICU care and 36% required operative interventions. There was only 1 mortality in the cohort (<1%).Injuries were more common in lower household income zip codes (Figure 1). Six zip codes encompassing several interstate exits and the connected heavy-traffic roadways comprise a statistically significant cluster of pediatric bicycle accidents (Figure 1).

CONCLUSION

Low-income neighborhoods and those near major roadways held the highest risk for pediatric bicycle accidents. Use of helmets was extremely low in the patient population, with high rates of traumatic brain injury. With this information, targeted programs to address high-risk intersections, helmet access, and safety education can be implemented locally.

Exploring Disparities in Youth Physical Activity Environments by Income and Non-Hispanic White Population Across the United States

This study investigated relationships between youth physical activity (PA) environments and income and non-Hispanic White population across the United States, stratified by US Census region and urban-rural designation. For all counties (n = 3142), publicly accessible data were used for sociodemographic indicators (ie, median household income and percent non-Hispanic White population) and a composite PA environment index (including exercise opportunities, violent crime incidence, walkability, and access to public schools). One-way analysis of variance was used to examine differences in PA environment index values according to income and non-Hispanic White population tertiles. There were significant differences in PA environments according to tertiles of income (F = 493.5, P < .001) and non-Hispanic White population (F = 58.6, P < .001), including variations by region and urban-rural designation. Public health practice and policy initiatives, such as joint use agreements, Safe Routes to School programs, and targeted funding allocations, should be used to address more pronounced income-based disparities in Southern and metropolitan counties and race-based disparities in rural and micropolitan counties.

Socioeconomic and racial disparities of sidewalk quality in a traditional rust belt city

Neighborhood walkability is key to promoting health, accessibility, and pedestrian safety. The Accessible, Connected Communities Encouraging Safe Sidewalks (ACCESS) project was developed to assess sidewalks throughout an urban community in Pontiac, Michigan. Data were collected from 2016 to 2018 along eighty miles of sidewalk for tripping hazards, cracking, vegetation, obstructions, overhead coverage, street lighting, buffers, and crosswalks. Data were mapped in ArcGIS with sociodemographic characteristics by U.S. Census block group. The majority of sidewalks had moderate (57.6%) or major (29.4%) sidewalk quality issues, especially maintenance-related impediments (68.6%) and inadequate street lighting or shade coverage (87.2%). The majority of crosswalks had a curb ramp to improve access for people with disabilities (84.4%), however over half lacked a detectable warning strip (55.8%). Degraded sidewalk quality was associated with lower neighborhood socioeconomic status and a higher proportion of Black and Latinx residents. Equity-centered pedestrian infrastructure improvement plans can address these disparities by increasing accessible, safe active transport options that promote physical activity and reduce health disparities. Evaluations like ACCESS can connect public health professionals with municipal planners to advance Complete Streets plans and promote healthy living.

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Rectify decades of sidewalk infrastructure disinvestment to improve walkability.

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Economic, racial, and ethnic disparities in pedestrian infrastructure.

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Pedestrian walking environment and accessibility assessment.

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Equitable distribution of pedestrian infrastructure in auto-centric cities.

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Local planning initiatives study nanoscale sidewalk accessibility.

What predicts how safe people feel in their neighborhoods and does it depend on functional status?

Feeling unsafe in one's neighborhood is related to poor health. Features of the neighborhood environment have been suggested to inform perceptions of neighborhood safety. Yet, the relative contribution of these features (e.g., uneven sidewalks, crime, perceived neighborhood physical disorder) on perceived neighborhood safety, particularly among people with disabilities who may view themselves as more vulnerable, is not well understood. We examined whether sidewalk quality assessed by third party raters, county-level crime rates, and perceived neighborhood disorder would relate to neighborhood safety concerns, and whether functional limitations would exacerbate these links. Using data from the 2012/2014 waves of the Health and Retirement Study (n = 10,653, mean age = 66 years), a national sample of older US adults, we demonstrate that those with and without functional limitations felt less safe in areas with more crime and perceived as more disordered. When considered simultaneously, however, only perceived disorder statistically significantly predicted safety concerns. Living in neighborhoods with better sidewalk quality was statistically significantly related to feeling less safe, but only among those with functional limitations. Sidewalk quality was not statistically significantly related to safety reports among those without functional limitations. To our knowledge, this study is among the first to examine multiple features of the neighborhood environment simultaneously in relation to perceived neighborhood safety. Our findings highlight the relative importance of perceived physical disorder, and that these perceptions relate to safety concerns. Replication of this research is needed to determine the robustness of these patterns, including rich data on pedestrian use and sidewalk proximity to roadways. Community-level interventions that simultaneously target the multifaceted features of the neighborhood environment that shape people's safety reports may be needed to reduce burden of health.

Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods

BACKGROUND

Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples.

OBJECTIVE

We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators among diverse older adults.

METHODS

Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia.

RESULTS

MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants.

CONCLUSION

Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.

Social and Economic Differences in Neighborhood Walkability Across 500 U.S. Cities

INTRODUCTION

Neighborhood walkability has been established as a potentially important determinant of various health outcomes that are distributed inequitably by race/ethnicity and sociodemographic status. The objective of this study is to assess the differences in walkability across major urban centers in the U.S.

METHODS

City- and census tract-level differences in walkability were assessed in 2020 using the 2019 Walk Score across 500 large cities in the U.S.

RESULTS

At both geographic levels, high-income and majority White geographic units had the lowest walkability overall. Walkability was lower with increasing tertile of median income among majority White, Latinx, and Asian American and Native Hawaiian and Pacific Islander neighborhoods. However, this association was reversed within majority Black neighborhoods, where tracts in lower-income tertiles had the lowest walkability. Associations varied substantially by region, with the strongest differences observed for cities located in the South.

CONCLUSIONS

Differences in neighborhood walkability across 500 U.S. cities provide evidence that both geographic unit and region meaningfully influence associations between sociodemographic factors and walkability. Structural interventions to the built environment may improve equity in urban environments, particularly in lower-income majority Black neighborhoods.

Racial differences in physical activity in nursing home residents with cognitive impairment

BACKGROUND

Nursing home (NH) residents with moderate-to-severe cognitive impairment experience mostly sedentary lifestyles.

AIM

Previous research has examined racial differences in physical activity (PA) levels in community-dwelling older adults but not in NH residents with cognitive impairment, and the current study aimed to examine these differences.

METHODS

This was a secondary data analysis of baseline data from the Function and Behavior Focused Care Intervention (FBFC) study. The sample included 247 cognitively impaired residents from 12 NHs who wore an ActiGraph to measure PA.

RESULTS

The residents' mean age was 82.6 (SD = 10.1) and had an average MMSE score of 7.8 (SD = 5.0). The sample (N = 247) was 41% African American and 59% White. African American and White residents engaged in only 50.6 and 46.2 min of light- and 1.5 and 1.1 min of moderate-level PA, respectively. Based on a multivariate analysis of covariance (MANCOVA), there was not a statistically significant difference between African American and White residents on combined dependent PA measures [F (8, 237) = 1.067, p = .387, Wilks' Λ = 0.962]. There was a trend that direct care providers subjectively reported that White residents engaged in more PA than their African American counterparts [F(8, 237) = 2.741, p = .09].

CONCLUSIONS

These findings are not consistent with prior research. However, these findings indicate severely low levels of PA in NH residents, regardless of racial group. Future research should prioritize PA interventions that make accommodations for all NH residents, and especially consider their underlying physical comorbidities and cognitive function.

The Relationship between Physical Activity and the Objectively-Measured Built Environment in Low- and High-Income South African Communities

There is limited data concerning the built environment and physical activity (PA) in a country with a history of sociopolitically motivated, spatial and economic disparities. We explored the extent to which objectively measured attributes of the built environment were associated with self-report or device-measured PA in low- and high-socioeconomic status (SES) communities. Methods: In a convenient sample of residents (n = 52, aged 18–65 years) from four urban suburbs in low- and high-income settings near Cape Town, South Africa, self-reported transport- and leisure-time PA, and device-measured moderate-to-vigorous PA (MVPA) data were collected. Built environment constructs derived from individual-level street network measures (1000 m buffer, ArcGIS, 10.51) were obtained. We assessed PA between four groups, based on income and GIS walkability (derived by a median split, low or high SES and low or high walkable). Results: No relationships between self-reported MVPA and GIS-measured walkability were found. Only intersection density was significantly, inversely associated with moderate and total MVPA (rho = −0.29 and rho = −0.31, respectively, p < 0.05). In the high SES group, vigorous PA was inversely associated with intersection density (rho = −0.39, p < 0.05). Self-report transport PA differed between groups (p < 0.013). Conclusions: Results suggest that the construct of walkability may relate to volitional (leisure) and utilitarian (transport) PA differently, in highly inequitable settings.

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

The built environment (BE) has been associated with health outcomes in prior studies. Few have investigated the association between neighborhood walkability, a component of BE, and hypertension. We examined the association between neighborhood walkability and incident hypertension in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Walkability was measured using Street Smart Walk Score based on participants' residential information at baseline (collected between 2003 and 2007) and was dichotomized as more (score ≥70) and less (score <70) walkable. The primary outcome was incident hypertension defined at the second visit (collected between 2013 and 2017). We derived risk ratios (RR) using modified Poisson regression adjusting for age, race, sex, geographic region, income, alcohol use, smoking, exercise, BMI, dyslipidemia, diabetes, and baseline blood pressure (BP). We further stratified by race, age, and geographic region. Among 6,894 participants, 6.8% lived in more walkable areas and 38% (N = 2,515) had incident hypertension. In adjusted analysis, neighborhood walkability (Walk Score ≥70) was associated with a lower risk of incident hypertension (RR [95%CI]: 0.85[0.74, 0.98], P = 0.02), with similar but non-significant trends in race and age strata. In secondary analyses, living in a more walkable neighborhood was protective against being hypertensive at both study visits (OR [95%CI]: 0.70[0.59, 0.84], P < 0.001). Neighborhood walkability was associated with incident hypertension in the REGARDS cohort, with the relationship consistent across race groups. The results of this study suggest increased neighborhood walkability may be protective for high blood pressure in black and white adults from the general US population.

Racial disparities in pedestrian-related injury hospitalizations in the United States

BACKGROUND

Racial/ethnic disparity has been documented in a wide variety of health outcomes, and environmental components are contributors. For example, food deserts have been tied to obesity rates. Pedestrian injuries are strongly tied to environmental factors, yet no studies have examined racial disparity in pedestrian injury rates. We examine a nationally-representative sample of pedestrian-related hospitalizations in the United States to identify differences in incidence, severity, and cost by race/ethnicity.

METHODS

Patients with ICD diagnosis E-codes for pedestrian injuries were drawn from the United States Nationwide Inpatient Sample (2009-2016). Rates were calculated using the United States Census. Descriptive statistics and generalized linear regression were used to examine characteristics (age, sex, severity of illness, mortality rates, hospital admissions, length of stay, total costs) associated with hospitalizations for pedestrian injuries.

RESULTS

The annual average of pedestrian-related deaths exceeded 5000 per year and hospitalizations exceeded 47,000 admissions per year. The burden of injury from pedestrian-related hospitalizations was higher among Black, Hispanic, and Multiracial/Other groups in terms of admission rates, costs per capita, proportion of children injured, and length of stay compared to Whites and Asian or Pacific Islander race/ethnicities. Compared to Whites, hospital admission rates were 1.92 (95% CI: 1.89-1.94) and 1.20 (95% CI: 1.19-1.21) times higher for Multiracial/Other and Blacks, respectively. Costs per capita ($USD) were $6.30, $4.14, and $3.22 for Multiracial/Others, Blacks, and Hispanics, compared to $2.88 and $2.32 for Whites and Asian or Pacific Islanders. Proportion of lengths of stay exceeding one week were larger for Blacks (26.4%), Hispanics (22.6%), Asian or Pacific Islanders (23.1%), and Multiracial/Other (24.1%), compared to Whites (18.6%). Extreme and major loss of function proportions were also highest among Black (34.5%) and lowest among Whites (30.2%).

CONCLUSIONS

Results from this study show racial disparities in pedestrian injury hospitalization rates and outcomes, particularly among Black, Hispanic, and Multiracial/Other race/ethnicity groups and support population and system-level approaches to prevention. Access to transportation is an indicator for health disparity, and these results indicate that access to safe transportation also shows inequity by race/ethnicity.

Creating Built Environments That Expand Active Transportation and Active Living Across the United States: A Policy Statement From the American Heart Association

Physical activity is vital for the health and well-being of youth and adults, although the prevalence of physical activity continues to be low. Promoting active transportation or human-powered transportation through policy, systems, and environmental change is one of the leading evidence-based strategies to increase physical activity regardless of age, income, racial/ethnic background, ability, or disability. Initiatives often require coordination across federal, state, and local agencies. To maximize the effectiveness of all types of interventions, it is imperative to establish strong and broad partnerships across professional disciplines, community members, and advocacy groups. Health organizations can play important roles in facilitating these partnerships. This policy statement provides recommendations and resources that can improve transportation systems, enhance land use design, and provide education to support policies and environments to promote active travel. The American Heart Association supports safe, equitable active transportation policies in communities across the country that incorporate consistent implementation evaluation. Ultimately, to promote large increases in active transportation, policies need to be created, enforced, and funded across multiple sectors in a coordinated and equitable fashion. Active transportation policies should operate at 3 levels: the macroscale of land use, the mesoscale of pedestrian and bicycle networks and infrastructure such as Complete Streets policies and Safe Routes to School initiatives, and the microscale of design interventions and placemaking such as building orientation and access, street furnishings, and safety and traffic calming measures. Health professionals and organizations are encouraged to become involved in advocating for active transportation policies at all levels of government.

Development of a national childhood obesogenic environment index in the United States: differences by region and rurality

Background

Diverse environmental factors are associated with physical activity (PA) and healthy eating (HE) among youth. However, no study has created a comprehensive obesogenic environment index for children that can be applied at a large geographic scale. The purpose of this study was to describe the development of a childhood obesogenic environment index (COEI) at the county level across the United States.

Methods

A comprehensive search of review articles (n = 20) and input from experts (n = 12) were used to identify community-level variables associated with youth PA, HE, or overweight/obesity for potential inclusion in the index. Based on strength of associations in the literature, expert ratings, expertise of team members, and data source availability, 10 key variables were identified – six related to HE (# per 1000 residents for grocery/superstores, farmers markets, fast food restaurants, full-service restaurants, and convenience stores; as well as percentage of births at baby (breastfeeding)-friendly facilities) and four related to PA (percentage of population living close to exercise opportunities, percentage of population < 1 mile from a school, a composite walkability index, and number of violent crimes per 1000 residents). Data for each variable for all counties in the U.S. (n = 3142) were collected from publicly available sources. For each variable, all counties were ranked and assigned percentiles ranging from 0 to 100. Positive environmental variables (e.g., grocery stores, exercise opportunities) were reverse scored such that higher values for all variables indicated a more obesogenic environment. Finally, for each county, a total obesogenic environment index score was generated by calculating the average percentile for all 10 variables.

Results

The average COEI percentile ranged from 24.5–81.0 (M = 50.02,s.d. = 9.01) across US counties and was depicted spatially on a choropleth map. Obesogenic counties were more prevalent (F = 130.43,p < .0001) in the South region of the U.S. (M = 53.0,s.d. = 8.3) compared to the Northeast (M = 43.2,s.d. = 6.9), Midwest (M = 48.1,s.d. = 8.5), and West (M = 48.4,s.d. = 9.8). When examined by rurality, there were also significant differences (F = 175.86,p < .0001) between metropolitan (M = 46.5,s.d. = 8.4), micropolitan (M = 50.3,s.d. = 8.1), and rural counties (M = 52.9,s.d. = 8.8) across the U.S.

Conclusion

The COEI can be applied to benchmark obesogenic environments and identify geographic disparities and intervention targets. Future research can examine associations with obesity and other health outcomes.

Analyzing Associations Between Chronic Disease Prevalence and Neighborhood Quality Through Google Street View Images

Deep learning and, specifically, convoltional neural networks (CNN) represent a class of powerful models that facilitate the understanding of many problems in computer vision. When combined with a reasonable amount of data, CNNs can outperform traditional models for many tasks, including image classification. In this work, we utilize these powerful tools with imagery data collected through Google Street View images to perform virtual audits of neighborhood characteristics. We further investigate different architectures for chronic disease prevalence regression through networks that are applied to sets of images rather than single images. We show quantitative results and demonstrate that our proposed architectures outperform the traditional regression approaches.

Crime and Physical Activity: Development of a Conceptual Framework and Measures

BACKGROUND

A common hypothesis is that crime is a major barrier to physical activity, but research does not consistently support this assumption. This article advances research on crime-related safety and physical activity by developing a multilevel conceptual framework and reliable measures applicable across age groups.

METHODS

Criminologists and physical activity researchers collaborated to develop a conceptual framework. Survey development involved qualitative data collection and resulted in 155 items and 26 scales. Intraclass correlation coefficients (ICCs) were computed to assess test-retest reliability in a subsample of participants (N = 176). Analyses were conducted separately by age groups.

RESULTS

Test-retest reliability for most scales (63 of 104 ICCs across 4 age groups) was "excellent" or "good" (ICC ≥ .60) and only 18 ICCs were "poor" (ICC < .40). Reliability varied by age group. Adolescents (aged 12-17 y) had ICCs above the .40 threshold for 21 of 26 scales (81%). Young adults (aged 18-39 y) and middle-aged adults (aged 40-65 y) had ICCs above .40 for 24 (92%) and 23 (88%) scales, respectively. Older adults (aged 66 y and older) had ICCs above .40 for 18 of 26 scales (69%).

CONCLUSIONS

The conceptual framework and reliable measures can be used to clarify the inconclusive relationships between crime-related safety and physical activity.

Variation in the physical activity environment according to area-level socio-economic position-A systematic review

Physical inactivity is a major contributing factor to obesity, and both follow a socio-economic gradient. This systematic review aims to identify whether the physical activity environment varies by socio-economic position (SEP), which may contribute to socio-economic patterning of physical activity behaviours, and in turn, obesity levels. Six databases were searched. Studies were included if they compared an objectively measured aspect of the physical activity environment between areas of differing SEP in a high-income country. Two independent reviewers screened all papers. Results were classified according to the physical activity environment analysed: walkability/bikeability, green space, and recreational facilities. Fifty-nine studies met the inclusion criteria. A greater number of positive compared with negative associations were found between SEP and green space, whereas there were marginally more negative than positive associations between SEP and walkability/bikeability and recreational facilities. A high number of mixed and null results were found across all categories. With a high number of mixed and null results, clear socio-economic patterning in the presence of physical activity environments in high-income countries was not evident in this systematic review. Heterogeneity across studies in the measures used for both SEP and physical activity environments may have contributed to this result.

Disentangling Race, Poverty, and Place in Disparities in Physical Activity

Significant racial disparities in physical activity-a key protective health factor against obesity and cardiovascular disease-exist in the United States. Using data from the 1999-2004 National Health and Nutrition Examination Survey and the 2000 United States (US) Census, we estimated the impact of race, individual-level poverty, neighborhood-level poverty, and neighborhood racial composition on the odds of being physically active for 19,678 adults. Compared to whites, blacks had lower odds of being physically active. Individual poverty and neighborhood poverty were associated with decreased odds of being physically active among both whites and blacks. These findings underscore the importance of social context in understanding racial disparities in physical activity and suggest the need for future research to determine specific elements of the social context that drive disparities.

Sampling Methodology and Reliability of a Representative Walkability Audit

Background

Physical inactivity is a public health concern in the US Virgin Islands (USVI). A contributing factor may be a lack of pedestrian infrastructure and other environmental supports for walking. In this manuscript, we describe the methods used to conduct a walkability audit of environmental features related to physical activity in the USVI.

Methods

In 2016, volunteer auditors conducted the audit using a modified version of the Microscale Audit of Pedestrian Streetscapes tool. A two-stage sampling method was developed using publicly available census data to select a sample of estates (n=46) and street segments (n=1,550; 99.2 km) across the USVI. A subset of segments was audited by two independent auditors, and inter-rater reliability was assessed using Cohen's kappa and percent agreement.

Results

Audits were completed on 1,114 segments (94.6 km), and estimates were weighted to represent accessible public street length in the study area (1,155.9 km). Most items on the audit tool (62.7%) demonstrated good to excellent reliability. We found that it was feasible to conduct a reliable audit of environmental features related to physical activity across a large sample of streets in the USVI.

Conclusions

These methods can be replicated in other settings to collect comprehensive data that can be used to guide strategies to improve the walkability of communities.

The potential for walkability to narrow neighbourhood socioeconomic inequalities in physical function: A case study of middle-aged to older adults in Brisbane, Australia

Residents of disadvantaged neighbourhoods have poorer physical function than their advantaged counterparts, although the reasons for this remain largely unknown. We examined the moderating effects of walkability in the relationship between neighbourhood disadvantage and physical function using 2013 cross-sectional data from 5115 individuals aged 46-72 living in 200 neighbourhoods in Brisbane, Australia. The relationship between neighbourhood disadvantage and physical function differed by levels of walkability: positive associations as levels of walkability increased for those living in more disadvantaged neighbourhoods, and no difference for those living in more advantaged neighbourhoods. Further work is required to better understand the underlying mechanisms.

Iniquidades do ambiente construído relacionado à atividade física no entorno de escolas públicas de Curitiba, Paraná, Brasil

Resumo: O objetivo do estudo foi investigar a associação entre as características do ambiente relacionado à atividade física com a renda em áreas de entorno escolar em Curitiba, Paraná. Foram auditados 888 segmentos de rua com um instrumento de observação sistemática em três seções (Rotas, Segmentos e Cruzamentos) no raio de 500 metros ao redor de 30 escolas públicas. O escore total foi a soma das seções. Dados de renda do entorno escolar foram obtidos do Censo Demográfico de 2010, e a distância linear de cada escola até o centro da cidade foi calculada. Modelos multiníveis (nível um segmento e nível dois escola) foram aplicados na análise, com estimativas de médias ponderadas e correlações intraclasse (ICC). Na análise bruta, a maior variabilidade entre as escolas foi observada na seção Segmentos (ICC = 0,41), e a menor, na seção Rotas (ICC = 0,19). Os segmentos de rua localizados no entorno de escolas do primeiro tercil de renda alcançaram uma média ajustada de 15,6 (IC95%: 13,0-18,3) no escore total, quase metade daqueles de renda maior, que atingiram 30,7 (IC95%: 28,0-33,5) pontos, com diferença significativa entre os tercis (p < 0,001). O escore das áreas mais centrais foi 30,1 (IC95%: 26,9-33,4), significativamente maior (p < 0,001) se comparado àquelas mais periféricas em que a pontuação foi 16,3 (IC95%: 12,8-19,8). As características do ambiente avaliadas nas seções Rotas e Segmentos, além do escore total, mostraram-se associadas com a menor renda. Ambiente de pior qualidade em áreas de menor renda é uma das iniquidades que precisa ser enfrentada nas metrópoles brasileiras e que pode contribuir para a melhoria da saúde das pessoas.

Racial and ethnic differences in perceived safety barriers to walking, United States National Health Interview Survey - 2015

Barriers to safe walking may prevent people from being physically active, and previous reports have identified differences in barriers to safe walking across racial and ethnic groups. The purpose of this research was to determine the role demographic characteristics play on racial/ethnic differences in perceived barriers to safe walking and determine if racial/ethnic differences vary by urban/rural residence and Census region. Participants in the 2015 National Health Interview Survey Cancer Control Supplement (n = 31,433 adults ≥18 years) reported perceived barriers to safe walking (traffic, crime, and animals) and demographic characteristics. Urban/rural residence and Census region were based on home addresses. We calculated adjusted prevalence of barriers by race/ethnicity using logistic regression; geographic differences in barriers across racial/ethnic groups were examined via interaction terms. After adjustment for demographic characteristics, non-Hispanic blacks (blacks) and Hispanics reported crime and animals as barriers more frequently than non-Hispanic whites (whites) (crime: blacks, 22.2%; Hispanics, 16.7%; whites, 9.0%; animals: blacks, 18.0%; Hispanics, 12.4%; whites, 8.5%). Racial/ethnic differences in perceived crime as a barrier were more pronounced in the Northeast and Midwest than in the South and West. Urban-dwelling blacks (all regions) and Hispanics (Midwest and South) reported animals as barriers more frequently than whites. Racial/ethnic differences in perceived barriers to safe walking remained after adjusting for demographic characteristics and varied by geographic location. Addressing perceived crime and animals as barriers to walking could help reduce racial/ethnic differences in physical activity, and several barriers may need to be assessed to account for geographic variation.

The relationship between urban forests and race: A meta-analysis

There is ample evidence that urban trees benefit the physical, mental, and social health of urban residents. The environmental justice hypothesis posits that environmental amenities are inequitably low in poor and minority communities, and predicts these communities experience fewer urban environmental benefits. Some previous research has found that urban forest cover is inequitably distributed by race, though other studies have found no relationship or negative inequity. These conflicting results and the single-city nature of the current literature suggest a need for a research synthesis. Using a systematic literature search and meta-analytic techniques, we examined the relationship between urban forest cover and race. First, we estimated the average (unconditional) relationship between urban forest cover and race across studies (studies = 40; effect sizes = 388). We find evidence of significant race-based inequity in urban forest cover. Second, we included characteristics of the original studies and study sites in meta-regressions to illuminate drivers of variation of urban forest cover between studies. Our meta-regressions reveal that the relationship varies across racial groups and by study methodology. Models reveal significant inequity on public land and that environmental and social characteristics of cities help explain variation across studies. As tree planting and other urban forestry programs proliferate, urban forestry professionals are encouraged to consider the equity consequences of urban forestry activities, particularly on public land.

The relationship between urban forests and income: A meta-analysis

Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be unequally distributed among poor and minority urban communities, meaning that these communities are potentially being deprived of public environmental benefits, a form of environmental injustice. The evidence of this problem is not uniform however, and evidence of inequity varies in size and significance across studies. This variation in results suggests the need for a research synthesis and meta-analysis. We employed a systematic literature search to identify original studies which examined the relationship between urban forest cover and income (n=61) and coded each effect size (n=332). We used meta-analytic techniques to estimate the average (unconditional) relationship between urban forest cover and income and to estimate the impact that methodological choices, measurement, publication characteristics, and study site characteristics had on the magnitude of that relationship. We leveraged variation in study methodology to evaluate the extent to which results were sensitive to methodological choices often debated in the geographic and environmental justice literature but not yet evaluated in environmental amenities research. We found evidence of income-based inequity in urban forest cover (unconditional mean effect size = 0.098; s.e. = .017) that was robust across most measurement and methodological strategies in original studies and results did not differ systematically with study site characteristics. Studies that controlled for spatial autocorrelation, a violation of independent errors, found evidence of substantially less urban forest inequity; future research in this area should test and correct for spatial autocorrelation.

Neighbourhood looking glass: 360º automated characterisation of the built environment for neighbourhood effects research

Background

Neighbourhood quality has been connected with an array of health issues, but neighbourhood research has been limited by the lack of methods to characterise large geographical areas. This study uses innovative computer vision methods and a new big data source of street view images to automatically characterise neighbourhood built environments.

Methods

A total of 430 000 images were obtained using Google’s Street View Image API for Salt Lake City, Chicago and Charleston. Convolutional neural networks were used to create indicators of street greenness, crosswalks and building type. We implemented log Poisson regression models to estimate associations between built environment features and individual prevalence of obesity and diabetes in Salt Lake City, controlling for individual-level and zip code-level predisposing characteristics.

Results

Computer vision models had an accuracy of 86%–93% compared with manual annotations. Charleston had the highest percentage of green streets (79%), while Chicago had the highest percentage of crosswalks (23%) and commercial buildings/apartments (59%). Built environment characteristics were categorised into tertiles, with the highest tertile serving as the referent group. Individuals living in zip codes with the most green streets, crosswalks and commercial buildings/apartments had relative obesity prevalences that were 25%–28% lower and relative diabetes prevalences that were 12%–18% lower than individuals living in zip codes with the least abundance of these neighbourhood features.

Conclusion

Neighbourhood conditions may influence chronic disease outcomes. Google Street View images represent an underused data resource for the construction of built environment features.

Cross-sectional interactions between quality of the physical and social environment and self-reported physical activity in adults living in income-deprived communities

Background

Understanding the environmental determinants of physical activity in populations at high risk of inactivity could contribute to the development of effective interventions. Socioecological models of activity propose that environmental factors have independent and interactive effects of physical activity but there is a lack of research into interactive effects.

Objectives

This study aimed to explore independent and interactive effects of social and physical environmental factors on self-reported physical activity in income-deprived communities.

Methods

Participants were 5,923 adults in Glasgow, United Kingdom. Features of the social environment were self-reported. Quality of the physical environment was objectively-measured. Neighbourhood walking and participation in moderate physical activity [MPA] on ≥5 days/week was self-reported. Multilevel multivariate logistic regression models tested independent and interactive effects of environmental factors on activity.

Results

‘Social support’ (walking: OR:1.22,95%CI = 1.06–1.41,p<0.01; MPA: OR:0.79,95%CI = 0.67–0.94,p<0.01), ‘social interaction’ (walking: OR:1.25,95%CI = 1.10–1.42,p<0.01; MPA: OR:6.16,95%CI = 5.14–7.37,p<0.001) and ‘cohesion and safety’ (walking: OR:1.78,95%CI = 1.56–2.03,p<0.001; MPA: OR:1.93,95%CI = 1.65–2.27,p<0.001), but not ‘trust and empowerment’, had independent effects on physical activity. ‘Aesthetics of built form’ (OR:1.47,95%CI = 1.22–1.77,p<0.001) and ‘aesthetics and maintenance of open space’ (OR:1.32, 95%CI = 1.13–1.54,p<0.01) were related to walking. ‘Physical disorder’ (OR:1.63,95%CI = 1.31–2.03,p<0.001) had an independent effect on MPA. Interactive effects of social and physical factors on walking and MPA were revealed.

Conclusions

Findings suggest that intervening to create activity-supportive environments in deprived communities may be most effective when simultaneously targeting the social and physical neighbourhood environment.

Supportive environments for physical activity in deprived communities in the United Kingdom: A qualitative study using photo elicitation

The health benefits of regular physical activity are substantial and well-established. However, population activity levels are insufficient to obtain health benefits in the United Kingdom (UK), and strategies to increase activity, particularly in income-deprived communities, are sought. Socioecological models of physical activity posit that activity levels are influenced by social, physical and wider environmental factors. In line with a growing evidence base, there is a need to understand the factors that contribute to an activity-supportive neighbourhood within deprived settings within the UK. This study used photo-elicitation qualitative interviews to explore environmental facilitators and barriers to neighbourhood-based, outdoor physical activity in 23 adults living in two income-deprived neighbourhoods in Glasgow, UK. Data were collected between June and October 2015, and were explored using thematic analysis. Five themes were identified: 'diversity of destinations in the neighbourhood', 'provision of services to support healthy environments', 'ownership of public space and facilities to encourage physical activity', 'collective control of public space to prevent disorder' and 'perceived value of the neighbourhood'. Findings highlighted the close interaction between these themes and more broadly between social and physical facets of neighbourhood environments that were unsupportive of physical activity. Discourse about economic aspects was pervasive and emerged as deeply affecting characteristics of the social and physical environment and upstream influences on physical activity. This study supports evidence that multi-faceted interventions addressing aspects of the social, physical and economic environment may be needed to support outdoor physical activity in deprived communities.

Examining Sociodemographic Differences in Playground Availability and Quality and Associations with Childhood Obesity

BACKGROUND

Parks and playgrounds are important environmental components for promoting healthy weight among children. The purposes of this study were to examine disparities in access to playgrounds and playground quality by multiple sociodemographic characteristics and the association of playground access and quality with youth weight status.

METHODS

Objectively measured height and weight were collected for all third to fifth grade youth (n = 13,469) in a southeastern US County. Detailed audits of all park playgrounds (n = 95) were concurrently conducted. Playground quality was measured by the presence of eight playground attributes (e.g., good condition and shade). Spatial (GIS) and statistical (multilevel logistic regression) analyses were used to determine access to playgrounds within a ½ mile network buffer, whether playground access and quality varied by the individual's gender, socioeconomic status (SES), and race/ethnicity, and the association between playground access and quality with youth being a healthy weight vs. overweight or obese.

RESULTS

Higher SES youth were half as likely to have a playground within ½ mile. No disparities were found for playground quality by gender, SES, or race/ethnicity. In unadjusted models, youth with lower quality playgrounds nearby were more likely to be overweight/obese than children with no playground access. However, there were no significant associations for playground access/quality and weight status after adjusting for sociodemographic variables.

CONCLUSION

Future research should continue to monitor disparities in diverse metrics of access to and quality of playgrounds and how these are related to weight status and other outcomes among children of different age, income, and racial/ethnic groups.

Intersection of neighborhood dynamics and socioeconomic status in small-area walkability: the Heart Healthy Hoods project

Background

Previous studies found a complex relationship between area-level socioeconomic status (SES) and walkability. These studies did not include neighborhood dynamics. Our aim was to study the association between area-level SES and walkability in the city of Madrid (Spain) evaluating the potential effect modification of neighborhood dynamics.

Methods

All census sections of the city of Madrid (n = 2415) were included. Area-level SES was measured using a composite index of 7 indicators in 4 domains (education, wealth, occupation and living conditions). Two neighborhood dynamics factors were computed: gentrification, proxied by change in education levels in the previous 10 years, and neighborhood age, proxied by median year of construction of housing units in the area. Walkability was measured using a composite index of 4 indicators (Residential Density, Population Density, Retail Destinations and Street Connectivity). We modeled the association using linear mixed models with random intercepts.

Results

Area-level SES and walkability were inversely and significantly associated. Areas with lower SES showed the highest walkability. This pattern did not hold for areas with an increase in education level, where the association was flat (no decrease in walkability with higher SES). Moreover, the association was attenuated in newly built areas: the association was stronger in areas built before 1975, weaker in areas built between 1975 and 1990 and flat in areas built from 1990 on.

Conclusion

Areas with higher neighborhood socioeconomic status had lower walkability in Madrid. This disadvantage in walkability was not present in recently built or gentrified areas.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-017-0095-7) contains supplementary material, which is available to authorized users.

Developing and Validating an Abbreviated Version of the Microscale Audit for Pedestrian Streetscapes (MAPS-Abbreviated)

PURPOSE

Macroscale built environment factors (e.g., street connectivity) are correlated with physical activity. Less-studied but more modifiable microscale elements (e.g., sidewalks) may also influence physical activity, but shorter audit measures of microscale elements are needed to promote wider use. This study evaluated the relation of an abbreviated 54-item streetscape audit tool with multiple measures of physical activity in four age groups.

METHODS

We developed a 54-item version from the original 120-item Microscale Audit of Pedestrian Streetscapes (MAPS). Audits were conducted on 0.25-0.45 mile routes from participant residences toward the nearest nonresidential destination for children (N=758), adolescents (N=897), younger adults (N=1,655), and older adults (N=367). Active transport and leisure physical activity were measured with surveys, and objective physical activity was measured with accelerometers. Items to retain from original MAPS were selected primarily by correlations with physical activity. Mixed linear regression analyses were conducted for MAPS-Abbreviated summary scores, adjusting for demographics, participant clustering, and macroscale walkability.

RESULTS

MAPS-Abbreviated and original MAPS total scores correlated r=.94 The MAPS-Abbreviated tool was related similarly to physical activity outcomes as the original MAPS. Destinations and land use, streetscape and walking path characteristics, and overall total scores were significantly related to active transport in all age groups. Street crossing characteristics were related to active transport in children and older adults. Aesthetics and social characteristics were related to leisure physical activity in children and younger adults, and cul-de-sacs were related with physical activity in youth. Total scores were related to accelerometer-measured physical activity in children and older adults.

CONCLUSION

MAPS-Abbreviated is a validated observational measure for use in research. The length and related cost of implementation has been cited as a barrier to use of microscale instruments, so availability of this shorter validated measure could lead to more widespread use of streetscape audits in health research.

Racial and Ethnic Disparities in Health and Health Care

A health disparity is defined as an increased burden of an adverse health outcome or health determinant within a specific subset of the population. There are well-documented racial and ethnic disparities throughout health care at the patient, provider, and health care system levels. As the minority populations within the United States grow to record numbers, it is increasingly important to invest in efforts to characterize, understand, and end racial and ethnic disparities in health care. Inequities in health outcomes and care pose real threats to the entire nation's well-being. Eliminating health disparities is fundamental to the well-being, productivity, and viability of the entire nation.

Examining associations between area-level spatial measures of housing with selected health and wellbeing behaviours and outcomes in an urban context

Adequate and affordable housing is a major social determinant of health; yet no work has attempted to conceptually map and spatially test area-level measures of housing with selected health and wellbeing outcomes. Sourcing data from 7,753 adults from Melbourne, Australia, we tested associations between area-level measures of housing density, tenure, and affordability with individual-level measures of neighbourhood safety, community satisfaction, and self-rated health. Compared with the reference groups, the odds of: feeling unsafe was higher for residents living in areas with less affordable housing; community dissatisfaction was ~30% higher in those living in areas with >36% residential properties assigned as rentals, and was significantly higher in the least affordable areas (OR =1.57). Compared with the reference groups, as dwelling density, proportion of rental properties, and housing unaffordability increased, the odds of reporting poorer self-rated health increased; however these associations did not always reach statistical significance. This work highlights the benefits of evidenced-based planning spatial measures to support health and wellbeing.