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Built environments have the potential to favorably support cognitive function. Despite growing work on this topic, most of the work has ignored variation in the spatial scale of the effect. The issue with spatial scale effects is that the size and shape of the areal unit within which built environment characteristics are measured naturally influence the built environment exposure metric and thus the estimated associations with health. We used spatial distributed lag modeling (DLM) to estimate how associations between built environment exposures (walkable destinations [WD], social destinations [SD]) and change in cognition varied across distance of these destinations from participants' residences. Cognition was assessed as maintained/improved processing speed (PS) and global cognition (GC). Person-level data from Exam 5 (2010-2012) and Exam 6 (2016-2018) of the Multi-Ethnic Study of Atherosclerosis was used (N = 1380, mean age 67). Built environment data were derived from the National Establishment Time Series. Higher availability of walkable and social destinations at closer distance from participants' residence was associated with maintained/improved PS. The adjusted associations between maintained/improved PS and destinations waned with increasing distance from the residence; associations were evident until approximately 1.9-km for WD and 1.5-km for SD. Associations were most apparent for participants living in areas with high population density. We found little evidence for associations between change in GC and built environment at any distance. These results highlight the importance of identifying appropriate spatial scale to understand the mechanisms for built environment-cognition associations., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts., Methods: We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers., Results: Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers., Conclusion: This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem., (© 2022. The Author(s).)

Introduction: Research examining the influence of neighborhood healthy food environment on diet has been mostly cross-sectional and has lacked robust characterization of the food environment. We examined longitudinal associations between features of the local food environment and healthy diet, and whether associations were modified by race/ethnicity., Methods: Data on 3634 adults aged 45-84 followed for 10 years were obtained from the Multi-Ethnic Study of Atherosclerosis. Diet quality was assessed using the Alternative Healthy Eating Index at Exam 1 (2000-2002) and Exam 5 (2010-2012). We assessed four measures of the local food environment using survey-based measures (e.g. perceptions of healthier food availability) and geographic information system (GIS)-based measures (e.g. distance to and density of healthier food stores) at Exam 1 and Exam 5. Random effects models adjusted for age, sex, education, moving status, per capita adjusted income, and neighborhood socioeconomic status, and used interaction terms to assess effect measure modification by race/ethnicity., Results: Net of confounders, one standard z-score higher average composite local food environment was associated with higher average AHEI diet score (β=1.39, 95% CI: 1.05, 1.73) over the follow-up period from Exam 1 to 5. This pattern of association was consistent across both GIS-based and survey-based measures of local food environment and was more pronounced among minoritized racial/ethnic groups. There was no association between changes in neighborhood environment and change in AHEI score, or effect measure modification by race/ethnicity., Conclusion: Our findings suggest that neighborhood-level food environment is associated with better diet quality, especially among racially/ethnically minoritized populations., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: To examine whether the density of neighbourhood restaurants affected the frequency of eating restaurant meals and subsequently affected diet quality., Design: Cross-sectional and longitudinal designs. Structural equation models assessed the indirect relationship between restaurant density (≤3 miles (4·8 km) of participant addresses) and dietary quality (Healthy Eating Index 2010 (HEI)) via the frequency of eating restaurant meals, after adjustment for sociodemographics, select health conditions, region, residence duration and area-level income., Setting: Urbanised areas in multiple regions of the USA, years 2000-2002 and 2010-2012., Participants: Participants aged 45-84 years were followed for 10 years (n 3567)., Results: Median HEI (out of 100) was fifty-nine at baseline and sixty-two at follow-up. The cross-sectional analysis found that residing in areas with a high density of restaurants (highest-ranked quartile) was associated with 52 % higher odds of frequently eating restaurant meals (≥3 times/week, OR: 1·52, 95 % CI 1·18, 1·98) and 3 % higher odds of having lower dietary quality (HEI lowest quartile < 54, OR: 1·03, 95 % CI 1·01, 1·06); associations were not sustained in longitudinal analyses. The cross-sectional analysis found 34 % higher odds of having lower dietary quality for those who frequently ate at restaurants (OR: 1·34, 95 % CI 1·12, 1·61), and more restaurant meals (over time increase ≥ 1 time/week) were associated with higher odds of having worse dietary quality at follow-up (OR: 1·21, 95 % CI 1·00, 1·46)., Conclusions: Restaurant density was associated with frequently eating out in cross-sectional and longitudinal analyses but was associated with the lower dietary quality only in cross-sectional analyses. Frequent restaurant meals were negatively related to dietary quality. Interventions that encourage less frequent eating out may improve population dietary quality.

This study examined the association between the price of healthier food relative to unhealthy food and type 2 diabetes prevalence, incidence and insulin resistance (IR). Data came from the Multi-Ethnic Study of Atherosclerosis exam 5 administered 2010-2012 (exam 4, five years prior, was used only for diabetes incidence) and supermarket food/beverage prices derived from Information Resources Inc. For each individual, average price of a selection of healthier foods, unhealthy foods and their ratio was computed for supermarkets within 3miles of the person's residential address. Diabetes status was confirmed at each exam and IR was assessed via the homeostasis model assessment index. Multivariable-adjusted logistic, modified Poisson and linear regression models were used to model diabetes prevalence, incidence and IR, respectively as a function of price and covariates; 2353 to 3408 participants were included in analyses (depending on the outcome). A higher ratio of healthy-to-unhealthy neighborhood food price was associated with greater IR (4.8% higher HOMA-IR score for each standard deviation higher price ratio [95% CI -0.2% to 10.1%]) after adjusting for region, age, gender, race/ethnicity, family history of diabetes, income/wealth index, education, smoking status, physical activity, and neighborhood socioeconomic status. No association with diabetes incidence (relative risk=1.11, 95% CI 0.85 to 1.44) or prevalence (odds ratio=0.95, 95% CI 0.81 to 1.11) was observed. Higher neighborhood prices of healthier food relative to unhealthy food were positively associated with IR, but not with either diabetes outcome. This study provides new insight into the relationship between food prices with IR and diabetes., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

It is known that the price of food influences the purchasing and consumption decisions of individuals; however, little work has examined if the price of healthier food relative to unhealthier food in an individual's neighborhood is associated with overall dietary quality while using data from multiple regions in the United States. Cross-sectional person-level data came from The Multi-Ethnic Study of Atherosclerosis (exam 5, 2010-2012 n = 2765); a food frequency questionnaire assessed diet. Supermarket food/beverage prices came from Information Resources Inc. (n = 794 supermarkets). For each individual, the average price of select indicators of healthier foods (vegetables, fruits, dairy) and unhealthier foods (soda, sweets, salty snacks), as well as their ratio, was computed for supermarkets within three miles of the person's residential address. Logistic regression estimated odds ratios of a high-quality diet (top quintile of Healthy Eating Index 2010) associated with healthy-to-unhealthy price ratio, adjusted for individual and neighborhood characteristics. Sensitivity analyses used an instrumental variable (IV) approach. Healthier foods cost nearly twice as much as unhealthier foods per serving on average (mean healthy-to-unhealthy ratio = 1.97 [SD 0.14]). A larger healthy-to-unhealthy price ratio was associated with lower odds of a high-quality diet (OR = 0.76 per SD increase in the ratio, 95% CI = [0.64-0.9]). IV analyses largely confirmed these findings although-as expected with IV adjustment-confidence intervals were wide (OR = 0.82 [0.57-1.19]). Policies to address the large price differences between healthier and unhealthy foods may help improve diet quality in the United States., Competing Interests: The authors declare no conflicts of interest.

Background: Social features of neighbourhood environments may influence smoking by creating a stressful environment or by buffering stress through social cohesion. However, the association of the overall neighbourhood social environment (NSE) with smoking, and the association of specific neighbourhood social factors with change in smoking behaviour over time, has rarely been examined., Methods: This study included 5856 adults aged 45-84 years from the Multi-Ethnic Study of Atherosclerosis (2000-2012, average follow-up: 7.8 years). Outcomes included current smoking status and smoking intensity (average number of cigarettes smoked per day among baseline smokers). NSE was assessed as a composite score composed of aesthetic quality, safety and social cohesion scales (derived from neighbourhood surveys). Generalised linear mixed models evaluated the association of baseline NSE (composite score and individual scales) with current smoking (modified Poisson models) and smoking intensity (negative binomial models) cross-sectionally and longitudinally., Results: Each SD increase in baseline NSE composite score was associated with 13% lower prevalence of smoking at baseline (adjusted prevalence ratio (aPR) 0.87 (95% CI 0.78 to 0.98). Neighbourhood safety and aesthetic quality were similarly associated with lower smoking prevalence (aPR 0.87 (0.78 to 0.97) and aPR 0.87 (0.77 to 0.99), respectively) but the association with social cohesion was weaker or null. No significant associations were observed for smoking intensity among baseline smokers. Baseline NSE was not associated with changes in smoking risk or intensity over time., Conclusions: Results suggest that neighbourhood social context influences whether older adults smoke, but does not promote smoking cessation or reduction over time., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Researchers have theorized that social and psychosocial factors increase vulnerability to the deleterious health effects of environmental hazards. We used baseline examination data (2000-2002) from the Multi-Ethnic Study of Atherosclerosis. Participants were 45-84 years of age and free of clinical cardiovascular disease at enrollment (n = 6814). The modifying role of social and psychosocial factors on the association between exposure to air pollution comprising particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) and blood pressure measures were examined using linear regression models. There was no evidence of synergistic effects of higher PM2.5 and adverse social/psychosocial factors on blood pressure. In contrast, there was weak evidence of stronger associations of PM2.5 with blood pressure in higher socioeconomic status groups. For example, those in the 10th percentile of the income distribution (i.e., low income) showed no association between PM2.5 and diastolic blood pressure (b = -0.41 mmHg; 95% confidence interval: -1.40, 0.61), whereas those in the 90th percentile of the income distribution (i.e., high income) showed a 1.52-mmHg increase in diastolic blood pressure for each 10-µg/m(3) increase in PM2.5 (95% confidence interval: 0.22, 2.83). Our results are not consistent with the hypothesis that there are stronger associations between PM2.5 exposures and blood pressure in persons of lower socioeconomic status or those with greater psychosocial adversity.

Background: Although research has shown that low socioeconomic status (SES) and minority communities have higher exposure to air pollution, few studies have simultaneously investigated the associations of individual and neighborhood SES with pollutants across multiple sites., Objectives: We characterized the distribution of ambient air pollution by both individual and neighborhood SES using spatial regression methods., Methods: The study population comprised 6,140 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Year 2000 annual average ambient PM2.5 and NOx concentrations were calculated for each study participant's home address at baseline examination. We investigated individual and neighborhood (2000 U.S. Census tract level) SES measures corresponding to the domains of income, wealth, education, and occupation. We used a spatial intrinsic conditional autoregressive model for multivariable analysis and examined pooled and metropolitan area-specific models., Results: A 1-unit increase in the z-score for family income was associated with 0.03-μg/m3 lower PM2.5 (95% CI: -0.05, -0.01) and 0.93% lower NOx (95% CI: -1.33, -0.53) after adjustment for covariates. A 1-SD-unit increase in the neighborhood's percentage of persons with at least a high school degree was associated with 0.47-μg/m3 lower mean PM2.5 (95% CI: -0.55, -0.40) and 9.61% lower NOx (95% CI: -10.85, -8.37). Metropolitan area-specific results exhibited considerable heterogeneity. For example, in New York, high-SES neighborhoods were associated with higher concentrations of pollution., Conclusions: We found statistically significant associations of SES measures with predicted air pollutant concentrations, demonstrating the importance of accounting for neighborhood- and individual-level SES in air pollution health effects research.

Objective: While behavioral change is necessary to reverse the obesity epidemic, it can be difficult to achieve and sustain in unsupportive residential environments. This study hypothesized that environmental resources supporting walking and a healthy diet are associated with reduced obesity incidence., Design and Methods: Data came from 4,008 adults aged 45-84 at baseline who participated in a neighborhood ancillary study of the Multi-Ethnic Study of Atherosclerosis. Participants were enrolled at six study sites at baseline (2000-2002) and neighborhood scales were derived from a supplementary survey that asked community residents to rate availability of healthy foods and walking environments for a 1-mile buffer area. Obesity was defined as BMI ≥ 30 kg/m(2) . Associations between incident obesity and neighborhood exposure were examined using proportional hazards and generalized linear regression., Results: Among 4,008 nonobese participants, 406 new obesity cases occurred during 5 years of follow-up. Neighborhood healthy food environment was associated with 10% lower obesity incidence per s.d. increase in neighborhood score. The association persisted after adjustment for baseline BMI and individual-level covariates (hazard ratio (HR) 0.88, 95% confidence interval (CI): 0.79, 0.97), and for correlated features of the walking environment but CIs widened to include the null (HR 0.89, 95% CI: 0.77, 1.03). Associations between neighborhood walking environment and lower obesity were weaker and did not persist after adjustment for correlated neighborhood healthy eating amenities (HR 0.98, 95% CI: 0.84, 1.15)., Conclusions: Altering the residential environment so that healthier behaviors and lifestyles can be easily chosen may be a precondition for sustaining existing healthy behaviors and for adopting new healthy behaviors., (Copyright © 2012 The Obesity Society.)

Background: Increased arterial stiffness could represent an intermediate subclinical outcome in the mechanistic pathway underlying associations between average long-term pollution exposure and cardiovascular events., Objective: We hypothesized that 20 years of exposure to particulate matter (PM) ≤ 2.5 and 10 μm in aerodynamic diameter (PM2.5 and PM10, respectively) would be positively associated with arterial stiffness in 3,996 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) who were seen at six U.S. study sites., Methods: We assigned pollution exposure during two decades preceding a clinical exam (2000-2002) using observed PM10 from monitors nearest participants' residences and PM10 and PM2.5 imputed from a space-time model. We examined three log-transformed arterial stiffness outcome measures: Young's modulus (YM) from carotid artery ultrasound and large (C1) and small (C2) artery vessel compliance from the radial artery pulse wave. All associations are expressed per 10 μg/m3 increment in PM and were adjusted for weather, age, sex, race, glucose, triglycerides, diabetes, waist:hip ratio, seated mean arterial pressure, smoking status, pack-years, cigarettes per day, environmental tobacco smoke, and physical activity. C1 and C2 models were further adjusted for heart rate, weight, and height., Results: Long-term average particle exposure was not associated with greater arterial stiffness measured by YM, C1, or C2, and the few associations observed were not robust across metrics and adjustment schemes., Conclusions: Long-term particle mass exposure did not appear to be associated with greater arterial stiffness in this study sample.

Although stress is often hypothesized to contribute to the effects of neighborhoods on health, very few studies have investigated associations of neighborhood characteristics with stress biomarkers. This study helps address the gap in the literature by examining whether neighborhood characteristics are associated with cortisol profiles. Analyses were based on data from the Multi-Ethnic Study of Atherosclerosis Stress study, which collected multiple measures of salivary cortisol over three days on a population based sample of approximately 800 adults. Multilevel models with splines were used to examine associations of cortisol levels with neighborhood poverty, violence, disorder, and social cohesion. Neighborhood violence was significantly associated with lower cortisol values at wakeup and with a slower decline in cortisol over the earlier part of the day, after sociodemographic controls. Associations were weaker and less consistent for neighborhood poverty, social cohesion, and disorder. Results revealed suggestive, though limited, evidence linking neighborhood contexts to cortisol circadian rhythms., (Published by Elsevier Ltd.)

Background: Cardiac autonomic dysfunction has been suggested as a possible biologic pathway for the association between fine particulate matter ≤ 2.5 µm in diameter (PM2.5) and cardiovascular disease (CVD). We examined the associations of PM2.5 with heart rate variability, a marker of autonomic function, and whether metabolic syndrome (MetS) modified these associations., Methods: We used data from the Multi-Ethnic Study of Atherosclerosis to measure the standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (rMSSD) of 5,465 participants 45-84 years old who were free of CVD at the baseline examination (2000-2002). Data from the U.S. regulatory monitor network were used to estimate ambient PM2.5 concentrations at the participants' residences. MetS was defined as having three or more of the following criteria: abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol, high blood pressure, and high fasting glucose., Results: After controlling for confounders, we found that an interquartile range (IQR) increase in 2-day average PM2.5 (10.2 µg/m3) was associated with a 2.1% decrease in rMSSD [95% confidence interval (CI), -4.2 to 0.0] and nonsignificantly associated with a 1.8% decrease in SDNN (95% CI, -3.7 to 0.1). Associations were stronger among individuals with MetS than among those without MetS: an IQR elevation in 2-day PM2.5 was associated with a 6.2% decrease in rMSSD (95% CI, -9.4 to -2.9) among participants with MetS, whereas almost no change was found among participants without MetS (p-interaction = 0.005). Similar effect modification was observed in SDNN (p-interaction = 0.011)., Conclusion: These findings suggest that autonomic dysfunction may be a mechanism through which PM exposure affects cardiovascular risk, especially among persons with MetS.

Background: Blood pressure (BP) may be implicated in associations observed between ambient particulate matter and cardiovascular morbidity and mortality. This study examined cross-sectional associations between short-term ambient fine particles (particulate matter

Little is known about environmental determinants of type 2 diabetes. The authors hypothesized that insulin resistance is positively related to distance to a wealthy area and to local neighborhood poverty. Data were derived from The Multi-Ethnic Study of Atherosclerosis, a study of adults aged 45-84 years in six US locales, and the 2000 US Census. The homeostasis model assessment (HOMA) index was used to measure insulin resistance. Linear regression was used to estimate associations between area characteristics and insulin resistance after adjustment for age, sex, income, education, and race/ethnicity and for the potential mediators diet, physical activity, and body mass index (n = 4,821). Among persons not treated for diabetes, distance to a wealthy area was associated with HOMA independent of local poverty and person-level covariates: per 4.4-km change, the relative increase in HOMA was 13% (95% confidence interval: 7%, 19%), similar to the effect of a body mass index increase of 1.7 kg/m(2) on HOMA. This association was reduced after adjustment for physical activity, diet, and body mass index (relative increase = 9%, 95% confidence interval: 3%, 15%). Local neighborhood poverty was also positively, but more weakly associated with insulin resistance, with no association after adjustment for race/ethnicity. This study shows that proximity to resources in high-income areas is related to insulin resistance.

IntroductionResearch examining the influence of neighborhood healthy food environment on diet has been mostly cross-sectional and has lacked robust characterization of the food environment. We examined longitudinal associations between features of the local food environment and healthy diet, and whether associations were modified by race/ethnicity.MethodsData on 3634 adults aged 45-84 followed for 10 years were obtained from the Multi-Ethnic Study of Atherosclerosis. Diet quality was assessed using the Alternative Healthy Eating Index at Exam 1 (2000-2002) and Exam 5 (2010-2012). We assessed four measures of the local food environment using survey-based measures (e.g. perceptions of healthier food availability) and geographic information system (GIS)-based measures (e.g. distance to and density of healthier food stores) at Exam 1 and Exam 5. Random effects models adjusted for age, sex, education, moving status, per capita adjusted income, and neighborhood socioeconomic status, and used interaction terms to assess effect measure modification by race/ethnicity.ResultsNet of confounders, one standard z-score higher average composite local food environment was associated with higher average AHEI diet score (β=1.39, 95% CI: 1.05, 1.73) over the follow-up period from Exam 1 to 5. This pattern of association was consistent across both GIS-based and survey-based measures of local food environment and was more pronounced among minoritized racial/ethnic groups. There was no association between changes in neighborhood environment and change in AHEI score, or effect measure modification by race/ethnicity.ConclusionOur findings suggest that neighborhood-level food environment is associated with better diet quality, especially among racially/ethnically minoritized populations.

Longitudinal associations between neighborhood characteristics and body mass index (BMI; weight (kg)/height (m)2) were assessed from 2000 to 2011 among 5,919 participants in the Multi-Ethnic Study of Atherosclerosis. The perceived availability of healthy food and walking environment were assessed via surveys, and 1-mile (1.6-km) densities of supermarkets, fruit-and-vegetable stores, and recreational facilities were obtained through a commercial database. Econometric fixed-effects models were used to estimate the association between within-person changes in neighborhood characteristics and within-person change in BMI. In fully adjusted models, a 1-standard-deviation increase in the healthy food environment index was associated with a 0.16-kg/m2 decrease in BMI (95% confidence interval (CI): -0.27, -0.06) among participants with obesity at baseline. A 1-standard-deviation increase in the physical activity environment index was associated with 0.13-kg/m2 (95% CI: -0.24, -0.02) and 0.14-kg/m2 (95% CI: -0.27, -0.01) decreases in BMI for participants who were overweight and obese at baseline, respectively. Paradoxically, increases in the physical activity index were associated with BMI increases in persons who were normal-weight at baseline. This study provides preliminary longitudinal evidence that favorable changes in neighborhood physical environments are related to BMI reductions in obese persons, who comprise a substantial proportion of the US population. [ABSTRACT FROM AUTHOR]

The article presents a multi-ethnic atherosclerosis study which investigates the contribution of residential environments in Type 2 diabetes mellitus incidents. It examines the physical activities and healthy diets of neighborhood resources which can lessen diabetes incidents. It adds that people who live in worse environments have lower risk factors and are less associated with the disease. It concludes that health promotion and modification of physical environment should be improved.