Uncovering physical activity trade-offs in transportation policy: A spatial agent-based model of Bogotá, Colombia.

BACKGROUND: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. METHODS: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. RESULTS: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. CONCLUSIONS: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989-2020.

BACKGROUND: Assessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity. METHODS: We used cross-sectional data from 16 rounds of Mexico's National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity. RESULTS: The mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020. CONCLUSIONS: Our results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Racial and Ethnic Differences in All-Cause and Cardiovascular Disease Mortality: The MESA Study.

BACKGROUND: Despite improvements in population health, marked racial and ethnic disparities in longevity and cardiovascular disease (CVD) mortality persist. This study aimed to describe risks for all-cause and CVD mortality by race and ethnicity, before and after accounting for socioeconomic status (SES) and other factors, in the MESA study (Multi-Ethnic Study of Atherosclerosis). METHODS: MESA recruited 6814 US adults, 45 to 84 years of age, free of clinical CVD at baseline, including Black, White, Hispanic, and Chinese individuals (2000-2002). Using Cox proportional hazards modeling with time-updated covariates, we evaluated the association of self-reported race and ethnicity with all-cause and adjudicated CVD mortality, with progressive adjustments for age and sex, SES (neighborhood SES, income, education, and health insurance), lifestyle and psychosocial risk factors, clinical risk factors, and immigration history. RESULTS: During a median of 15.8 years of follow-up, 22.8% of participants (n=1552) died, of which 5.3% (n=364) died of CVD. After adjusting for age and sex, Black participants had a 34% higher mortality hazard (hazard ratio [HR], 1.34 [95% CI, 1.19-1.51]), Chinese participants had a 21% lower mortality hazard (HR, 0.79 [95% CI, 0.66-0.95]), and there was no mortality difference in Hispanic participants (HR, 0.99 [95% CI, 0.86-1.14]) compared with White participants. After adjusting for SES, the mortality HR for Black participants compared with White participants was reduced (HR, 1.16 [95% CI, 1.01-1.34]) but still statistically significant. With adjustment for SES, the mortality hazards for Chinese and Hispanic participants also decreased in comparison with White participants. After further adjustment for additional risk factors and immigration history, Hispanic participants (HR, 0.77 [95% CI, 0.63-0.94]) had a lower mortality risk than White participants, and hazard ratios for Black participants (HR, 1.08 [95% CI, 0.92-1.26]) and Chinese participants (HR, 0.81 [95% CI, 0.60-1.08]) were not significantly different from those of White participants. Similar trends were seen for CVD mortality, although the age- and sex-adjusted HR for CVD mortality for Black participants compared with White participants was greater than all-cause mortality (HR, 1.72 [95% CI, 1.34-2.21] compared with HR, 1.34 [95% CI, 1.19-1.51]). CONCLUSIONS: These results highlight persistent racial and ethnic differences in overall and CVD mortality, largely attributable to social determinants of health, and support the need to identify and act on systemic factors that shape differences in health across racial and ethnic groups.

Social inequalities and COVID-19 mortality between neighborhoods of Bariloche city, Argentina.

BACKGROUND: The COVID-19 pandemic has shown how intraurban inequalities are likely to reinforce health and social inequalities. Studies at small area level help to visualize social inequialities hidden in large areas as cities or regions. AIM: To describe the spatial patterning of COVID-19 death rates in neighborhoods of the medium-sized city of Bariloche, Argentina, and to explore its relationship with the socioeconomic characteristics of neighborhoods. METHODS: We conducted an ecological study in Bariloche, Argentina. The outcome was counts of COVID-19 deaths between June 2020 and May 2022 obtained from the surveillance system and georeferenced to neighborhoods. We estimated crude- and age-adjusted death rates by neighborhood using a Bayesian approach through a Poisson regression that accounts for spatial-autocorrelation via Conditional Autoregressive (CAR) structure. We also analyzed associations of age-adjusted death rates with area-level socioeconomic indicators. RESULTS: Median COVID-19 death rate across neighborhoods was 17.9 (10th/90th percentile of 6.3/35.2) per 10,000 inhabitants. We found lower age-adjusted rates in the city core and western part of the city. The age-adjusted death rate in the most deprived areas was almost double than in the least deprived areas, with an education-related relative index of inequality (RII) of 2.14 (95% CI 1.55 to 2.96). CONCLUSION: We found spatial heterogeneity and intraurban variability in age-adjusted COVID-19 death rates, with a clear social gradient, and a higher burden in already deprived areas. This highlights the importance of studying inequalities in health outcomes across small areas to inform placed-based interventions.

Evaluation of road safety policies and their enforcement in Mexico City, 2015-2019: an interrupted time-series study.

BACKGROUND: Mexico City approved new road safety policies in 2015, which included lower speed limits and higher fines for traffic offences. In 2019, economic fines were replaced by a point penalty system among other changes. This study evaluates these policies on road traffic collisions, injuries and deaths. METHODS: Collisions data came from insurance collision claims (January 2015 to December 2019) and road traffic deaths from vital registrations (January 2013 to December 2019). We conducted an interrupted time series analysis for each outcome using negative binomial regression models with an offset of insured vehicles (collisions) or total population (deaths). Then, we classified the 16 municipalities in the city into enforcement and no-enforcement groups based on presence or absence of automated traffic enforcement devices and conducted a controlled interrupted time series analysis. RESULTS: The 2015 road safety policies had no effect on total collisions and collisions resulting in injury but were associated with a 0.2% (95% CI -0.3 to 0.0) decline in the mortality trend. The 2019 policies had no effect on total collisions but were associated with a 1.5% increase in the trend of collisions resulting in injuries and with a 2.7% (95% CI 1.0 to 4.5) increase in the mortality trend. Postpolicy trends in enforcement versus no-enforcement municipalities were not significantly different. CONCLUSION: Policies that included high economic penalties for speeding and dangerous behaviours were effective in decreasing traffic mortality while removing economic penalties and replacing them with a point penalty system were associated with an increase in collisions, resulting in injury and mortality.

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.

Gender differences in the association of individual and contextual socioeconomic status with hypertension in 230 Latin American cities from the SALURBAL study: a multilevel analysis.

BACKGROUND: Despite global interest in gender disparities and social determinants of hypertension, research in urban areas and regions with a high prevalence of hypertension, such as Latin America, is very limited. The objective of this study was to examine associations of individual- and area-level socioeconomic status with hypertension in adults living in 230 cities in eight Latin America countries. METHODS: In this cross-sectional study, we used harmonized data from 109,184 adults (aged 18-97 years) from the SALURBAL (Salud Urbana en America Latina/Urban Health in Latin America) project. Hypertension was assessed by self-report. Individual-, sub-city- and city-level education were used as proxies of socioeconomic status. All models were stratified by gender. RESULTS: Higher individual-level education was associated with lower odds of hypertension among women (university education or higher versus lower than primary: odds ratio [OR] = 0.67, 95% confidence interval [CI] = 0.61-0.74) but higher odds among men (OR = 1.65; 95%CI 1.47-1.86), although in men an inverse association emerged when measured blood pressure was used (OR = 0.86; 95%CI 0.76-0.97). For both genders, living in sub-city areas with higher educational achievement was associated with higher odds of hypertension (OR per standard deviation [SD] = 1.07, 95%CI = 1.02-1.12; OR = 1.11 per SD, 95%CI = 1.05-1.18, for women and men, respectively). The association of city-level education with hypertension varied across countries. In Peru, there was an inverse association (higher city level education was associated with lower odds of hypertension) in women and men, but in other countries no association was observed. In addition, the inverse association of individual-level education with hypertension became stronger (in women) or emerged (in men) as city or sub-city education increased. CONCLUSION: The social patterning of hypertension differs by gender and by the level of analysis highlighting the importance of context- and gender-sensitive approaches and policies to reduce the prevalence of hypertension in Latin America.

Heterogeneity in Spatial Inequities in COVID-19 Vaccination Across 16 Large US Cities.

Differences in vaccination coverage can perpetuate coronavirus disease 2019 (COVID-19) disparities. We explored the association between neighborhood-level social vulnerability and COVID-19 vaccination coverage in 16 large US cities from the beginning of the vaccination campaign in December 2020 through September 2021. We calculated the proportion of fully vaccinated adults in 866 zip code tabulation areas (ZCTAs) of 16 large US cities: Long Beach, Los Angeles, Oakland, San Diego, San Francisco, and San Jose, all in California; Chicago, Illinois; Indianapolis, Indiana; Minneapolis, Minnesota; New York, New York; Philadelphia, Pennsylvania; and Austin, Dallas, Fort Worth, Houston, and San Antonio, all in Texas. We computed absolute and relative total and Social Vulnerability Index-related inequities by city. COVID-19 vaccination coverage was 0.75 times (95% confidence interval: 0.69, 0.81) or 16 percentage points (95% confidence interval: 12.1, 20.3) lower in neighborhoods with the highest social vulnerability as compared with those with the lowest. These inequities were heterogeneous, with cities in the West generally displaying narrower inequities in both the absolute and relative scales. The Social Vulnerability Index domains of socioeconomic status and of household composition and disability showed the strongest associations with vaccination coverage. Inequities in COVID-19 vaccinations hamper efforts to achieve health equity, as they mirror and could lead to even wider inequities in other COVID-19 outcomes.

Racial Inequities in Self-Rated Health Across Brazilian Cities: Does Residential Segregation Play a Role?

Racial health inequities may be partially explained by area-level factors such as residential segregation. In this cross-sectional study, using a large, multiracial, representative sample of Brazilian adults (n = 37,009 individuals in the 27 state capitals; National Health Survey (Pesquisa Nacional de Saúde), 2013), we investigated 1) whether individual-level self-rated health (SRH) (fair or poor vs. good or better) varies by race (self-declared White, Brown, or Black) and 2) whether city-level economic or racial residential segregation (using dissimilarity index values in tertiles: low, medium, and high) interacts with race, increasing racial inequities in SRH. Prevalence of fair or poor SRH was 31.5% (Black, Brown, and White people: 36.4%, 34.0%, and 27.3%, respectively). Marginal standardization based on multilevel logistic regression models, adjusted for age, gender, and education, showed that Black and Brown people had, respectively, 20% and 10% higher prevalence of fair or poor SRH than did White people. Furthermore, residential segregation interacted with race such that the more segregated a city, the greater the racial gap among Black, Brown, and White people in fair or poor SRH for both income and race segregation. Policies to reduce racial inequities may need to address residential segregation and its consequences for health.

Social Epidemiology: Past, Present, and Future.

In a context where epidemiologic research has been heavily influenced by a biomedical and individualistic approach, the naming of "social epidemiology" allowed explicit emphasis on the social production of disease as a powerful explanatory paradigm and as critically important for interventions to improve population health. This review briefly highlights key substantive areas of focus in social epidemiology over the past 30 years, reflects on major advances and insights, and identifies challenges and possible future directions. Future opportunities for social epidemiology include grounding research in theoretically based and systemic conceptual models of the fundamental social drivers of health; implementing a scientifically rigorous yet realistic approach to drawing conclusions about social causes; using complementary methods to generate valid explanations and identify effective actions; leveraging the power of harmonization, replication, and big data; extending interdisciplinarity and diversity; advancing emerging critical approaches to understanding the health impacts of systemic racism and its policy implications; going global; and embracing a broad approach to generating socially useful research.

Heterogeneity in Disparities in Life Expectancy Across US Metropolitan Areas.

BACKGROUND: Life expectancy in the United States has declined since 2014 but characterization of disparities within and across metropolitan areas of the country is lacking. METHODS: Using census tract-level life expectancy from the 2010 to 2015 US Small-area Life Expectancy Estimates Project, we calculate 10 measures of total and income-based disparities in life expectancy at birth, age 25, and age 65 within and across 377 metropolitan statistical areas (MSAs) of the United States. RESULTS: We found wide heterogeneity in disparities in life expectancy at birth across MSAs and regions: MSAs in the West show the narrowest disparities (absolute disparity: 8.7 years, relative disparity: 1.1), while MSAs in the South (absolute disparity: 9.1 years, relative disparity: 1.1) and Midwest (absolute disparity: 9.8 years, relative disparity: 1.1) have the widest life expectancy disparities. We also observed greater variability in life expectancy across MSAs for lower income census tracts (coefficient of variation [CoV] 3.7 for first vs. tenth decile of income) than for higher income census tracts (CoV 2.3). Finally, we found that a series of MSA-level variables, including larger MSAs and greater proportion college graduates, predicted wider life expectancy disparities for all age groups. CONCLUSIONS: Sociodemographic and policy factors likely help explain variation in life expectancy disparities within and across metro areas.

The Impact of Keeping Indoor Dining Closed on COVID-19 Rates Among Large US Cities: A Quasi-Experimental Design.

BACKGROUND: Indoor dining is one of the potential drivers of COVID-19 transmission. We used the heterogeneity among state government preemption of city indoor dining closures to estimate the impact of keeping indoor dining closed on COVID-19 incidence. METHODS: We obtained case rates and city or state reopening dates from March to October 2020 in 11 US cities. We categorized cities as treatment cities that were allowed by the state to reopen but kept indoor dining closed or comparison cities that would have kept indoor dining closed but that were preempted by their state and had to reopen indoor dining. We modeled associations using a difference-in-difference approach and an event study specification. We ran negative binomial regression models, with city-day as the unit of analysis, city population as an offset, and controlling for time-varying nonpharmaceutical interventions, as well as city and time fixed effects in sensitivity analysis and the event study specification. RESULTS: Keeping indoor dining closed was associated with a 55% (IRR = 0.45; 95% confidence intervals = 0.21, 0.99) decline in the new COVID-19 case rate over 6 weeks compared with cities that reopened indoor dining, and these results were consistent after testing alternative modeling strategies. CONCLUSIONS: Keeping indoor dining closed may be directly or indirectly associated with reductions in COVID-19 spread. Evidence of the relationship between indoor dining and COVID-19 case rates can inform policies to restrict indoor dining as a tailored strategy to reduce COVID-19 incidence. See video abstract at, http://links.lww.com/EDE/B902.

Tracking COVID-19 Inequities Across Jurisdictions Represented in the Big Cities Health Coalition (BCHC): The COVID-19 Health Inequities in BCHC Cities Dashboard.

Objectives. To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of the Big Cities Health Coalition (BCHC). Methods. We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities. Results. We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities. Conclusions. This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. (Am J Public Health. 2022;112(6):904-912. https://doi.org/10.2105/AJPH.2021.306708).

Urban Scaling of Health Outcomes: a Scoping Review.

Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. We found several historical studies that examined the dynamic relationships between city size and mortality occurring during the nineteenth and early twentieth centuries. In more recent years, we documented heterogeneity in the relation between city size and health. Measles and influenza are influenced by city size in conjunction with other factors like geographic proximity, while STIs, HIV, and dengue tend to occur more frequently in larger cities. NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.

Does Living near Trees and Other Vegetation Affect the Contemporaneous Odds of Asthma Exacerbation among Pediatric Asthma Patients?

Vegetation may influence asthma exacerbation through effects on aeroallergens, localized climates, air pollution, or children's behaviors and stress levels. We investigated the association between residential vegetation and asthma exacerbation by conducting a matched case-control study based on electronic health records of asthma patients, from the Children's Hospital of Philadelphia (CHOP). Our study included 17,639 exacerbation case events and 34,681 controls selected from non-exacerbation clinical visits for asthma, matched to cases by age, sex, race/ethnicity, public payment source, and residential proximity to the CHOP main campus ED and hospital. Overall greenness, tree canopy, grass/shrub cover, and impervious surface were assessed near children's homes (250 m) using satellite imagery and high-resolution landcover data. We used generalized estimating equations to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between each vegetation/landcover measure and asthma exacerbation, with adjustment for seasonal and sociodemographic factors-for all cases, and for cases defined by diagnosis setting and exacerbation frequency. Lower odds of asthma exacerbation were observed in association with greater levels of tree canopy near the home, but only for children who experienced multiple exacerbations in a year (OR = 0.94 per 10.2% greater tree canopy coverage, 95% CI = 0.90-0.99). Our findings suggest possible protection for asthma patients from tree canopy, but differing results by case frequency suggest that potential benefits may be specific to certain subpopulations of asthmatic children.

Associations between high ambient temperatures and asthma exacerbation among children in Philadelphia, PA: a time series analysis.

OBJECTIVES: High ambient temperatures may contribute to acute asthma exacerbation, a leading cause of morbidity in children. We quantified associations between hot-season ambient temperatures and asthma exacerbation in children ages 0-18 years in Philadelphia, PA. METHODS: We created a time series of daily counts of clinical encounters for asthma exacerbation at the Children's Hospital of Philadelphia linked with daily meteorological data, June-August of 2011-2016. We estimated associations between mean daily temperature (up to a 5-day lag) and asthma exacerbation using generalised quasi-Poisson distributed models, adjusted for seasonal and long-term trends, day of the week, mean relative humidity,and US holiday. In secondary analyses, we ran models with adjustment for aeroallergens, air pollutants and respiratory virus counts. We quantified overall associations, and estimates stratified by encounter location (outpatient, emergency department, inpatient), sociodemographics and comorbidities. RESULTS: The analysis included 7637 asthma exacerbation events. High mean daily temperatures that occurred 5 days before the index date were associated with higher rates of exacerbation (rate ratio (RR) comparing 33°C-13.1°C days: 1.37, 95% CI 1.04 to 1.82). Associations were most substantial for children ages 2 to <5 years and for Hispanic and non-Hispanic black children. Adjustment for air pollutants, aeroallergens and respiratory virus counts did not substantially change RR estimates. CONCLUSIONS: This research contributes to evidence that ambient heat is associated with higher rates of asthma exacerbation in children. Further work is needed to explore the mechanisms underlying these associations.

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.

Potential impacts of policies to reduce purchasing of ultra-processed foods in Mexico at different stages of the social transition: an agent-based modelling approach.

OBJECTIVES: To develop a simulation framework for assessing how combinations of taxes, nutrition warning labels and advertising levels could affect purchasing of ultra-processed foods (UPF) in Latin American countries and to understand whether policies reinforce or reduce pre-existing social disparities in UPF consumption. DESIGN: We developed an agent-based simulation model using international evidence regarding the effect of price, nutrition warning labels and advertising on UPF purchasing. SETTING: We estimated policy effects in scenarios representing two stages of the 'social transition' in UPF purchasing: (1) a pre-transition scenario, where UPF purchasing is higher among high-income households, similar to patterns in Mexico; and (2) a post-transition scenario where UPF purchasing is highest among low-income households, similar to patterns in Chile. PARTICIPANTS: A population of 1000 individual agents with levels of age, income, educational attainment and UPF purchasing similar to adult women in Mexico. RESULTS: A 20 % tax would decrease purchasing by 24 % relative to baseline in both the pre- and post-transition scenarios, an effect that is similar in magnitude to that of a nutrition warning label policy. A 50 % advertising increase or decrease had a comparatively small effect. Nutrition warning labels were most effective among those with higher levels of educational attainment. Labelling reduced inequities in the pre-transition scenario (i.e. highest UPF purchasing among the highest socio-economic group) but widened inequities in the post-transition scenario. CONCLUSIONS: Effective policy levers are available to reduce UPF purchasing, but policymakers should anticipate that equity impacts will differ depending on existing social patterns in UPF purchasing.

Aging and self-reported health in 114 Latin American cities: gender and socio-economic inequalities.

BACKGROUND: Understanding how urban environments influence people's health, especially as individuals age, can help identify ways to improve health in the rapidly urbanizing and rapidly aging populations. OBJECTIVES: To investigate the association between age and self-reported health (SRH) in adults living in Latin-American cities and whether gender and city-level socioeconomic characteristics modify this association. METHODS: Cross-sectional analyses of 71,541 adults aged 25-97 years, from 114 cities in 6 countries (Argentina, Brazil, Colombia, Chile, El Salvador, and Guatemala), as part of the Salud Urbana en America Latina (SALURBAL) Project. We used individual-level age, gender, education, and self-reported health (SRH) data from harmonized health surveys. As proxies for socioeconomic environment we used a city-level socioeconomic index (SEI) calculated from census data, and gross domestic product (GDP) per-capita. Multilevel Poisson models with a robust variance were used to estimate relative risks (RR), with individuals nested in cities and binary SRH (poor SHR vs. good SRH) as the outcome. We examined effect modification by gender and city-level socioeconomic indicators. RESULTS: Overall, 31.4% of the sample reported poor SRH. After adjusting for individual-level education, men had a lower risk of poor SRH (RR = 0.76; CI 0.73-0.78) compared to women, and gender modified the association between age and poor SRH (p-value of interaction < 0.001). In gender stratified models, the association between older age and poor SRH was more pronounced in men than in women, and in those aged 25-65 than among those 65+ (RR/10 years = 1.38 vs. 1.10 for men, and RR/10 years = 1.29 vs. 1.02 for women). Living in cities with higher SEI or higher GDP per-capita was associated with a lower risk of poor SRH. GDP per-capita modified the association between age (25-65) and SRH in men and women, with SEI the interaction was less clear. CONCLUSIONS: Across cities in Latin America, aging impact on health is significant among middle-aged adults, and among men. In both genders, cities with lower SEI or lower GDP per-capita were associated with poor SRH. More research is needed to better understand gender inequalities and how city socioeconomic environments, represented by different indicators, modify exposures and vulnerabilities associated with aging.

Spatial Inequities in COVID-19 Testing, Positivity, Confirmed Cases, and Mortality in 3 U.S. Cities : An Ecological Study.

BACKGROUND: Preliminary evidence has shown inequities in coronavirus disease 2019 (COVID-19)-related cases and deaths in the United States. OBJECTIVE: To explore the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York, Philadelphia, and Chicago during the first 6 months of the pandemic. DESIGN: Ecological, observational study at the ZIP code tabulation area (ZCTA) level from March to September 2020. SETTING: Chicago, New York, and Philadelphia. PARTICIPANTS: All populated ZCTAs in the 3 cities. MEASUREMENTS: Outcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September 2020. Predictors were the Centers for Disease Control and Prevention Social Vulnerability Index and its 4 domains, obtained from the 2014-2018 American Community Survey. The spatial autocorrelation of COVID-19 outcomes was examined by using global and local Moran I statistics, and estimated associations were examined by using spatial conditional autoregressive negative binomial models. RESULTS: Spatial clusters of high and low positivity, confirmed cases, and mortality were found, co-located with clusters of low and high social vulnerability in the 3 cities. Evidence was also found for spatial inequities in testing, positivity, confirmed cases, and mortality. Specifically, neighborhoods with higher social vulnerability had lower testing rates and higher positivity ratios, confirmed case rates, and mortality rates. LIMITATIONS: The ZCTAs are imperfect and heterogeneous geographic units of analysis. Surveillance data were used, which may be incomplete. CONCLUSION: Spatial inequities exist in COVID-19 testing, positivity, confirmed cases, and mortality in 3 large U.S. cities. PRIMARY FUNDING SOURCE: National Institutes of Health.