Spatial scale effects on associations between built environment and cognitive function: Multi-Ethnic Study of Atherosclerosis.

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.

Temporal Patterns in Fruit and Vegetable Intake Among Racially and Ethnically Diverse Children and Adolescents in California.

Introduction: Childhood dietary behaviors, including fruit and vegetable intake, are associated with adult health. Most children do not meet daily recommended servings of fruits and vegetables. Less is known about temporal patterns in fruit and vegetable consumption or if they vary by race and ethnicity. We investigated temporal patterns in fruit and vegetable intake among California school-age children and adolescents overall and by race and ethnicity. Methods: We used 2-year cross-sectional datasets from the child and adolescent samples in the California Health Interview Surveys from 2011-2012 through 2019-2020 and modified Poisson regression models to estimate the likelihood of consuming 5 or more servings of fruits and vegetables in 2013-2016 and 2017-2020 compared with 2011-2012. Models controlled for age, race and ethnicity, gender, citizenship status, family income, and adult education and tested for differences by race and ethnicity. The samples included 16,125 children aged 5 to 11 years and 9,672 adolescents aged 12 to 17 years. Results: Overall, 29.3% of children and 25.9% of adolescents reported intake of 5 or more fruits and vegetables per day. Among children, adjusted prevalence ratios (PR) of fruit and vegetable intake were higher in 2013-2016 (PR,1.25; 95% CI, 1.11-1.42) and 2017-2020 (PR,1.13; 95% CI, 0.99-1.30) compared with 2011-2012. Among adolescents, the adjusted prevalence did not differ significantly over time. We found no evidence of differential associations by race and ethnicity for children and adolescents. Conclusion: We found favorable temporal changes in fruit and vegetable consumption among children, but not among adolescents. Monitoring temporal patterns in fruit and vegetable intake remains critical for planning population-level interventions to increase consumption.

Estimating the effect of latent time-varying count exposures using multiple lists.

A major challenge in longitudinal built-environment health studies is the accuracy of commercial business databases that are used to characterize dynamic food environments. Different databases often provide conflicting exposure measures on the same subject due to different source credibilities. As on-site verification is not feasible for historical data, we suggest combining multiple databases to correct the bias in health effect estimates due to measurement error in any 1 datasource. We propose a joint model for the time-varying health outcomes, observed count exposures, and latent true count exposures. Our model estimates the time-specific quality of sources and incorporates time dependence of true count exposure by Poisson integer-valued first-order autoregressive process. We take a Bayesian nonparametric approach to flexibly account for location-specific exposures. By resolving the discordance between different databases, our method reduces the bias in the longitudinal health effect of the true exposures. Our method is demonstrated with childhood obesity data in California public schools with respect to convenience store exposures in school neighborhoods from 2001 to 2008.

"Competitive" food and beverage policies and weight status: A systematic review of the evidence among sociodemographic subgroups.

Prior studies identified variable associations between competitive food and beverage policies (CF&B) and youth obesity, potentially due to differences across population subgroups. This review summarizes the evidence on associations between CF&B policies and childhood obesity within gender, grade level/ age, race/ethnicity, and/or socioeconomic levels. PubMed, EMBASE, CINAHL, and ERIC database searches identified studies published in English in Canada and the United States between January 1, 2000, and February 28, 2022. Of the 18 selected studies, six were cross-sectional, two correlational, nine were before/after designs, and one study utilized both a cross-sectional and pre-post design. Twelve studies reported findings stratified by a single sociodemographic factor, with grade level/age as the most frequently reported. Although the evidence varied, greater consistency in direction of associations and strengths of evidence were seen among middle school students. Six studies reported findings jointly by multiple sociodemographic subgroups with evidence suggesting CF&B associations with slower rate of increase or plateaus or declines in obesity among multiple subgroups, though the strengths of evidence varied. Over the past two decades, there have been relatively limited subgroup analyses on studies about CF&B policies and childhood obesity. Studies are needed with stronger designs and analyses disaggregated, particularly by race/ethnicities and socioeconomic factors, across places and time.

Greenness and excess deaths from heat in 323 Latin American cities: Do associations vary according to climate zone or green space configuration?

Green vegetation may protect against heat-related death by improving thermal comfort. Few studies have investigated associations of green vegetation with heat-related mortality in Latin America or whether associations are modified by the spatial configuration of green vegetation. We used data from 323 Latin American cities and meta-regression models to estimate associations between city-level greenness, quantified using population-weighted normalized difference vegetation index values and modeled as three-level categorical terms, and excess deaths from heat (heat excess death fractions [heat EDFs]). Models were adjusted for city-level fine particulate matter concentration (PM2.5), social environment, and country group. In addition to estimating overall associations, we derived estimates of association stratified by green space clustering by including an interaction term between a green space clustering measure (dichotomized at the median of the distribution) and the three-level greenness variable. We stratified analyses by climate zone (arid vs. temperate and tropical combined). Among the 79 arid climate zone cities, those with moderate and high greenness levels had modestly lower heat EDFs compared to cities with the lowest greenness, although protective associations were more substantial in cities with moderate versus high greenness levels and confidence intervals (CI) crossed the null (Beta: -0.41, 95% CI: -1.06, 0.25; Beta -0.23, 95% CI: -0.95, 0.49, respectively). In 244 non-arid climate zone cities, associations were approximately null. We did not observe evidence of effect modification by green space clustering. Our results suggest that greenness may offer modest protection against heat-related mortality in arid climate zone Latin American cities.

The pregnancy research on inflammation, nutrition, & city environment: systematic analyses study (PRINCESA) cohort, 2009-2015.

The Pregnancy Research on Inflammation, Nutrition, & City Environment: Systematic Analyses Study (PRINCESA) cohort was set up to evaluate associations between air pollution and birth outcomes among pregnant persons in Mexico City. Specifically, the study was designed to improve air pollution exposure assessment and elucidate biological mechanisms underlying associations between maternal exposures and adverse pregnancy outcomes. Pregnant persons (all women) (N = 935) between ages 18-45 who lived and/or worked in metropolitan Mexico City, Mexico, from 2009 to 2015 and liveborn singleton infants (N = 815) of participants who completed follow-up were enrolled in the cohort. We followed participants monthly from enrollment to delivery and the following categories of data were obtained: demographic, medical and obstetric history, geo-referenced data, repeated measures on daily activity patterns, reported food intake, anthropometric, clinical and obstetric data, 20 serum and 20 cervicovaginal cytokines, and lower reproductive tract infection. Repeated ultrasound measures of fetal parameters and infant birth data are also included in the study's database. In addition, PRINCESA investigators calculated air pollution exposure measures for six pollutants measured by the Mexico City Atmospheric Monitoring System (SIMAT). These estimates utilize participants' addresses to account for spatial variation in exposure (nearest monitor, inverse distance weighting, and kriging) and are available daily during pregnancy for participants. To date, associations between environmental and nutritional impacts on maternal and child health outcomes have been evaluated. PRINCESA has a comprehensive database of maternal and infant data and biological samples and offers collaboration opportunities to study associations between environmental and other factors, including nutrition and pregnancy outcomes.

Association of service facilities and amenities with adolescent birth rates in Mexican cities.

BACKGROUND: The association of the built environment and the structural availability of services/amenities with adolescent birth rates (ABR) has been overlooked in Latin America. We investigated the association of the availability, and changes in the availability, of services/amenities with ABR in 92 Mexican cities. METHODS: We estimated ABR using data on live birth registration linked to municipality of residence at the time of birth from 2008-2017. The number of services/amenities were obtained from the National Statistical Directory of Economic Units in 2010, 2015, and 2020 and grouped as follows: education, health care, pharmacies, recreation, and on- and off-premises alcohol outlets. Data were linearly interpolated to obtain yearly estimates. We estimated densities per square km by municipality. We fitted negative binomial hybrid models, including a random intercept for municipality and city, and adjusted for other social environment variables. RESULTS: After adjustment a 1-unit increase in the density of recreation facilities, pharmacies, and off-premises alcohol outlets within municipalities was associated with a 5%, 4% and 12% decrease in ABR, respectively. Municipalities with higher density of education, recreational and health care facilities had a lower ABR; in contrast, municipalities with a higher density of on-premises alcohol experienced a higher ABR. CONCLUSION: Our findings highlight the importance of economic drivers and the need to invest in infrastructure, such as pharmacies, medical facilities, schools, and recreation areas and limit the availability of alcohol outlets to increase the impact of current adolescent pregnancy prevention programs.

Frailty in Older Adults and Internal and Forced Migration in Urban Neighborhood Contexts in Colombia.

Objective: We investigated the association between the density of internal human migration, in the urban neighborhood, on frailty in the older adult population in Colombia. Methods: The data used in this study are from four Colombian population surveys. We analyzed 633 census tracts with a sample of 2,194 adults 60 years and over for frailty (measured using the Fried criteria). We considered the proportion of inhabitants in a census tract with a history of internal migration as the exposure variable considering three temporalities. For contextual forced migration, we identified two types: 5-year, and 1-year. Poisson multivariable regression models with two hierarchical levels (individual and census tracts) were estimated. Results: The prevalence of pre-fragile/frailty was 80.63% [CI 95%: 77.67, 83.28]. The prevalence ratio were significantly higher for the older adults who live in neighborhoods where a higher proportion of internal migrants reside. Conclusion: We conclude that older adults who lived in neighborhoods with a high proportion of internal migrants experience more frailty. Potential explanations are that neighborhoods with high internal migration could experience social (l increase in cultural heterogeneity, in the perception of insecurity, violence and physical conditions (pressure on local economies and services, leading elderly residents to compete for neighborhood resources), translated into social stress.

Do diurnal salivary cortisol curves carry meaningful information about the regulatory biology of the HPA axis in healthy humans?

Salivary cortisol stress biomarkers have been extensively used in epidemiological work to document links between stress and ill health. There has been little effort to ground field friendly cortisol measures in the hypothalamic-pituitary-adrenal (HPA) axis regulatory biology that is likely relevant to delineating mechanistic pathways leading from stress exposure to detrimental health outcomes. Here, we utilized a healthy convenience sample (n = 140) to examine normal linkages between extensively collected salivary cortisol measures and available laboratory probes of HPA axis regulatory biology. Participants provided 9 saliva samples per day over 6 days within a month, while engaging in usual activities, and also participated in 5 regulatory tests (adrenocorticoptripin stimulation, dexamethasone/corticotropin-releasing-hormone stimulation, metyrapone, dexamethasone suppression, and Trier Social Stress Test). Logistical regression was used to test specific predictions linking cortisol curve components to regulatory variables and to explore widely for non-predicted associations. We found support for 2 of 3 original hypotheses, showing associations (1) between cortisol diurnal decline and feedback sensitivity as measured by dexamethasone suppression, and (2) between morning cortisol levels and adrenal sensitivity. We did not find links between central drive (metyrapone test) and end of day salivary levels. We confirmed an a priori expectation of limited linkage between regulatory biology and diurnal salivary cortisol measures, beyond those predicted. These data support an emerging focus on measures related to diurnal decline in epidemiological stress work. They raise questions about the biological meaning of other curve components, including morning cortisol levels, and perhaps CAR (Cortisol Awakening Response). If morning cortisol dynamics are linked to stress, more work on adrenal sensitivity in stress adaptation and stress-health links may be warranted.

Trends in school-neighbourhood inequalities and youth obesity: Repeated cross-sectional analyses of the public schools in the state of California.

BACKGROUND: It is currently unknown whether the relationship between affluence of school neighbourhoods and prevalence of youth overweight/obesity is uniform across demographic subgroups and areal context in the United States. METHODS: We examined association between school-neighbourhood income tertiles and school-level overweight/obesity (OVOB) prevalence, using data on body mass index of fifth, seventh, and nineth graders who attended public schools in California in 2001 and 2010 (n = 1 584 768), using multiple logistic regression models. RESULTS: Overall, OVOB prevalence was higher in lower-income school neighbourhoods, with a steeper income-OVOB gradient for girls. Among boys, the gradient became steeper in 2010 than 2000. Among Asian and White girls, the negative gradients were steepest in rural areas. For African-American students in all areas and Latino boys in rural areas, there was less clear evidence of inverse income-OVOB gradients. Addition of fast-food restaurant availability to the models did not change the observed inverse school-neighbourhood income-obesity gradients. CONCLUSIONS: The findings suggest the needs to investigate reasons for this variability with consideration to combinations of sociodemographic, economic, and environmental risk factors that may contribute to disparities in childhood obesity.

Modification of temperature-related human mortality by area-level socioeconomic and demographic characteristics in Latin American cities.

BACKGROUND: In Latin America, where climate change and rapid urbanization converge, non-optimal ambient temperatures contribute to excess mortality. However, little is known about area-level characteristics that confer vulnerability to temperature-related mortality. OBJECTIVES: Explore city-level socioeconomic and demographic characteristics associated with temperature-related mortality in Latin American cities. METHODS: The dependent variables quantify city-specific associations between temperature and mortality: heat- and cold-related excess death fractions (EDF, or percentages of total deaths attributed to cold/hot temperatures), and the relative mortality risk (RR) associated with 1 °C difference in temperature in 325 cities during 2002-2015. Random effects meta-regressions were used to investigate whether EDFs and RRs associated with heat and cold varied by city-level characteristics, including population size, population density, built-up area, age-standardized mortality rate, poverty, living conditions, educational attainment, income inequality, and residential segregation by education level. RESULTS: We find limited effect modification of cold-related mortality by city-level demographic and socioeconomic characteristics and several unexpected associations for heat-related mortality. For example, cities in the highest compared to the lowest tertile of income inequality have all-age cold-related excess mortality that is, on average, 3.45 percentage points higher (95% CI: 0.33, 6.56). Higher poverty and higher segregation were also associated with higher cold EDF among those 65 and older. Large, densely populated cities, and cities with high levels of poverty and income inequality experience smaller heat EDFs compared to smaller and less densely populated cities, and cities with little poverty and income inequality. DISCUSSION: Evidence of effect modification of cold-related mortality in Latin American cities was limited, and unexpected patterns of modification of heat-related mortality were observed. Socioeconomic deprivation may impact cold-related mortality, particularly among the elderly. The findings of higher levels of poverty and income inequality associated with lower heat-related mortality deserve further investigation given the increasing importance of urban adaptation to climate change.

Adolescent birth rates and the urban social environment in 363 Latin American cities.

INTRODUCTION: Latin America has the second-highest adolescent birth rate (ABR) worldwide. Variation between urban and rural areas and evidence linking country development to ABR points towards upstream factors in the causal pathway. We investigated variation in ABR within and between cities, and whether different features of urban social environments are associated with ABR. METHODS: We included 363 cities in 9 Latin American countries. We collected data on social environment at country, city and subcity levels and birth rates among adolescents (ages 15-19). We investigated variation in ABR within and between countries and cities along with associations between social environment and ABR by fitting three-level negative binomial models (subcities nested within cities nested within countries). RESULTS: The median subcity ABR was 58.5 per 1000 women 15-19 (IQR 43.0-75.3). We found significant variability in subcity ABR between countries and cities (37% of variance between countries and 47% between cities within countries). Higher homicide rates and greater population growth in cities were associated with higher ABR (rate ratio (RR) 1.09; 95% CI 1.06 to 1.12 and RR 1.02; 95% CI 1.00 to 1.04, per SD, respectively), while better living conditions and educational attainment in subcities were associated with lower ABR after accounting for other social environment characteristics (RR 0.95; 95% CI 0.92 to 0.98 and 0.78; 95% CI 0.76 to 0.79, per SD, respectively). CONCLUSIONS: The large heterogeneity of ABR found within countries and cities highlights the key role urban areas have in developing local policies. Holistic interventions targeting education inequalities and living conditions are likely important to reducing ABR in cities.

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

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.

Characterizing food environments near schools in California: A latent class approach simultaneously using multiple food outlet types and two spatial scales.

It is challenging to evaluate associations between the food environment near schools with either prevalence of childhood obesity or with socioeconomic characteristics of schools. This is because the food environment has many dimensions, including its spatial distribution. We used latent class analysis to classify public schools in urban, suburban, and rural areas in California into food environment classes based on the availability and spatial distribution of multiple types of unhealthy food outlets nearby. All urban schools had at least one unhealthy food outlet nearby, compared to seventy-two percent of schools in rural areas did. Food environment classes varied in the quantity of available food outlets, the relative mix of food outlet types, and the outlets' spatial distribution near schools. Regardless of urbanicity, schools in low-income neighborhoods had greater exposure to unhealthy food outlets. The direction of associations between food environment classes and school size, type, and race/ethnic composition depends on the level of urbanicity of the school locations. Urban schools attended primarily by African American and Asian children are more likely to have greater exposures to unhealthy food outlets. In urban and rural but not suburban areas, schools attended primarily by Latino students had more outlets offering unhealthy foods or beverages nearby. In suburban areas, differences in the spatial distribution of food outlets indicates that food outlets are more likely to cluster near K-12 schools and high schools compared to elementary schools. Intervention design and future research need to consider that the associations between food environment exposures and school characteristics differ by urbanicity.

Ambient temperature and term birthweight in Latin American cities.

BACKGROUND: Extreme temperatures may lead to adverse pregnancy and birth outcomes, including low birthweight. Studies on the impact of temperature on birthweight have been inconclusive due to methodological challenges related to operationalizing temperature exposure, the definitions of exposure windows, accounting for gestational age, and a limited geographic scope. METHODS: We combined data on individual-level term live births (N≈15 million births) from urban areas in Brazil, Chile, and Mexico from 2010 to 2015 from the SALURBAL study (Urban Health in Latin America) with high-resolution daily air temperature data and computed average ambient temperature for every month of gestation for each newborn. Associations between full-term birthweight and average temperature during gestation were analyzed using multi-level distributed lag non-linear models that adjusted for newborn's sex, season of conception, and calendar year of child's birth; controlled for maternal age, education, partnership status, presence of previous births, and climate zone; and included a random term for the sub-city of mother's residence. FINDINGS: Higher temperatures during the entire gestation are associated with lower birthweight, particularly in Mexico and Brazil. The cumulative effect of temperature on birthweight is mostly driven by exposure to higher temperatures during months 7-9 of gestation. Higher maternal education can attenuate the temperature-birthweight associations. INTERPRETATION: Our work shows that climate-health impacts are likely to be context- and place-specific and warrants research on temperature and birthweight in diverse climates to adequately anticipate global climate change. Given the high societal cost of suboptimal birthweight, public health efforts should be aimed at diminishing the detrimental effect of higher temperatures on birthweight. FUNDING: The Wellcome Trust.

City-level impact of extreme temperatures and mortality in Latin America.

Climate change and urbanization are rapidly increasing human exposure to extreme ambient temperatures, yet few studies have examined temperature and mortality in Latin America. We conducted a nonlinear, distributed-lag, longitudinal analysis of daily ambient temperatures and mortality among 326 Latin American cities between 2002 and 2015. We observed 15,431,532 deaths among ≈2.9 billion person-years of risk. The excess death fraction of total deaths was 0.67% (95% confidence interval (CI) 0.58-0.74%) for heat-related deaths and 5.09% (95% CI 4.64-5.47%) for cold-related deaths. The relative risk of death was 1.057 (95% CI 1.046-1.067%) per 1 °C higher temperature during extreme heat and 1.034 (95% CI 1.028-1.040%) per 1 °C lower temperature during extreme cold. In Latin American cities, a substantial proportion of deaths is attributable to nonoptimal ambient temperatures. Marginal increases in observed hot temperatures are associated with steep increases in mortality risk. These risks were strongest among older adults and for cardiovascular and respiratory deaths.

Racial/ethnic disparities in childhood obesity: The role of school segregation.

OBJECTIVE: Recent studies have observed that racial or ethnic adult health disparities revealed in national data dissipate in racially integrated communities, supporting the theory that "place, not race" shapes the nature and magnitude of racial/ethnic health disparities. This study tested this theory among children. METHODS: In 2020, the racial/ethnic childhood obesity disparities within integrated schools and between segregated schools were estimated using statewide cross-sectional data collected in 2019 on fifth, seventh, and ninth grade students from California public schools. RESULTS: School segregation accounted for a large part of the obesity disparities between White children and children of color (Latino, Black, and Filipino children). In racially integrated schools, obesity disparities were much smaller than those in statewide data, whereas racial or ethnic childhood obesity disparities were larger when comparing children in majority-White schools with those attending schools with a majority enrollment of children of color, except for Asian children, who generally had lower obesity rates than their White peers. CONCLUSIONS: School-level racial segregation is a salient contributor to racial/ethnic childhood obesity disparities. Reducing obesity disparities may be particularly effective if place-level interventions target socioeconomically disadvantaged integrated schools and segregated schools attended primarily by children of color.

Split and combine simulation extrapolation algorithm to correct geocoding coarsening of built environment exposures.

A major challenge in studies relating built environment features to health is measurement error in exposure due to geocoding errors. Faulty geocodes in built environment data introduce errors to exposure assessments that may induce bias in the corresponding health effect estimates. In this study, we examine the distribution of the measurement error in measures constructed from point-referenced exposures, quantify the extent of bias in exposure effect estimates due to geocode coarsening, and extend the simulation extrapolation (SIMEX) method to correct the bias. The motivating example focuses on the association between children's body mass index and exposure to the junk food environment, represented by the number of junk food outlets within a buffer area near their schools. We show, algebraically and through simulation studies, that coarsening of food outlet coordinates results in exposure measurement errors that have heterogeneous variance and nonzero mean, and that the resulting bias in the health effect can be away from the null. The proposed SC-SIMEX procedure accommodates the nonstandard measurement error distribution, without requiring external data, and provides the best bias correction compared to other SIMEX approaches.

Health and Environmental Co-Benefits of City Urban Form in Latin America: An Ecological Study.

We investigated the association of urban landscape profiles with health and environmental outcomes, and whether those profiles are linked to environmental and health co-benefits. In this ecological study, we used data from 208 cities in 8 Latin American countries of the SALud URBana en América Latina (SALURBAL) project. Four urban landscape profiles were defined with metrics for the fragmentation, isolation, and shape of patches (contiguous area of urban development). Four environmental measures (lack of greenness, PM2.5, NO2, and carbon footprint), two cause-specific mortality rates (non-communicable diseases and unintentional injury mortality), and prevalence of three risk factors (hypertension, diabetes, and obesity) for adults were used as the main outcomes. We used linear regression models to evaluate the association of urban landscape profiles with environmental and health outcomes. In addition, we used finite mixture modeling to create co-benefit classes. Cities with the scattered pixels profile (low fragmentation, high isolation, and compact shaped patches) were most likely to have positive co-benefits. Profiles described as proximate stones (moderate fragmentation, moderate isolation, and irregular shape) and proximate inkblots (moderate-high fragmentation, moderate isolation, and complex shape) were most likely to have negative co-benefits. The contiguous large inkblots profile (low fragmentation, low isolation, and complex shape) was most likely to have mixed benefits.

Exploring the spatial scale effects of built environments on transport walking: Multi-Ethnic Study of Atherosclerosis.

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.