Urban landscape and street-design factors associated with road-traffic mortality in Latin America between 2010 and 2016 (SALURBAL): an ecological study

BACKGROUND

Road-traffic injuries are a key cause of death and disability in low-income and middle-income countries, but the effect of city characteristics on road-traffic mortality is unknown in these countries. The aim of this study was to determine associations between city-level built environment factors and road-traffic mortality in large Latin American cities.

METHODS

We selected cities from Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Panama, and Peru; cities included in the analysis had a population of at least 100 000 people. We extracted data for road-traffic deaths that occurred between 2010 and 2016 from country vital registries. Deaths were grouped by 5-year age groups and sex. Road-traffic deaths were identified using ICD-10 codes, with adjustments for ill-defined codes and incomplete registration. City-level measures included population, urban development, street design, public transportation, and social environment. Associations were estimated using multilevel negative binomial models with robust variances.

FINDINGS

366 cities were included in the analysis. There were 328 408 road-traffic deaths in nearly 3·5 billion person-years across all countries, with an average crude rate of 17·1 deaths per 100 000 person-years. Nearly half of the people who died were younger than 35 years. In multivariable models, road-traffic mortality was higher in cities where urban development was more isolated (rate ratio [RR] 1·05 per 1 SD increase, 95% CI 1·02-1·09), but lower in cities with higher population density (0·94, 0·90-0·98), higher gross domestic product per capita (0·96, 0·94-0·98), and higher intersection density (0·92, 0·89-0·95). Cities with mass transit had lower road mortality rates than did those without (0·92, 0·86-0·99).

INTERPRETATION

Urban development policies that reduce isolated and disconnected urban development and that promote walkable street networks and public transport could be important strategies to reduce road-traffic deaths in Latin America and elsewhere.

FUNDING

Wellcome Trust.

Spatially varying racial inequities in cardiovascular health and the contribution of individual- and neighborhood-level characteristics across the United States: The REasons for geographic and racial differences in stroke (REGARDS) study

Black-White inequities in cardiovascular health (CVH) pose a significant public health challenge, with these disparities also varying geographically across the US. There remains limited evidence of the impact of social determinants of health on these inequities. Using a national population-based cohort from the REasons for Geographic and Racial Differences in Stroke study, we assessed the spatial heterogeneity in Black-White differences in CVH and determined the extent to which individual- and neighborhood-level characteristics explain these inequities. We utilized a Bayesian hierarchical statistical framework to fit spatially varying coefficient models. Results showed overall and spatially varying inequities, where Black participants had significantly poorer CVH. The maps of the state level random effects also highlighted how inequities vary. The evidence produced in this study further highlights the importance of multilevel approaches - at the individual- and neighborhood-levels - that need to be in place to address these geographic and racial differences in CVH.

Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities

BACKGROUND

Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease.

OBJECTIVES

We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities.

METHODS

In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment.

RESULTS

A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18-97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase=1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR=1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase=0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase=1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment.

DISCUSSION

Our results suggest that urban physical environment features-such as fragmentation, mass transit, population density, and intersection density-may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. https://doi.org/10.1289/EHP7870.

Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities

BACKGROUND

Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease.

OBJECTIVES

We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities.

METHODS

In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment.

RESULTS

A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18-97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase=1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR=1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase=0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase=1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment.

DISCUSSION

Our results suggest that urban physical environment features-such as fragmentation, mass transit, population density, and intersection density-may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. https://doi.org/10.1289/EHP7870.

Associations Between Residential Segregation and Incident Hypertension: The Multi-Ethnic Study of Atherosclerosis

Background Residential segregation, a geospatial manifestation of structural racism, is a fundamental driver of racial and ethnic health inequities, and longitudinal studies examining segregation's influence on cardiovascular health are limited. This study investigates the impact of segregation on hypertension in a multiracial and multiethnic cohort and explores whether neighborhood environment modifies this association. Methods and Results Leveraging data from a diverse cohort of adults recruited from 6 sites in the United States with 2 decades of follow-up, we used race- and ethnicity-stratified Cox models to examine the association between time-varying segregation with incident hypertension in 1937 adults free of hypertension at baseline. Participants were categorized as residing in segregated and nonsegregated neighborhoods using a spatial-weighted measure. We used a robust covariance matrix estimator to account for clustering within neighborhoods and assessed effect measure modification by neighborhood social or physical environment. Over an average follow-up of 7.35 years, 65.5% non-Hispanic Black, 48.1% Chinese, and 53.7% Hispanic participants developed hypertension. Net of confounders, Black and Hispanic residents in segregated neighborhoods were more likely to develop hypertension relative to residents in nonsegregated neighborhoods (Black residents: hazard ratio [HR], 1.33; 95% CI, 1.09-1.62; Hispanic residents: HR, 1.33; 95% CI, 1.04-1.70). Results were similar but not significant among Chinese residents (HR, 1.20; 95% CI, 0.83-1.73). Among Black residents, neighborhood social environment significantly modified this association such that better social environment was associated with less pronounced impact of segregation on hypertension. Conclusions This study underscores the importance of continued investigations of groups affected by the health consequences of racial residential segregation while taking contextual neighborhood factors, such as social environment, into account.

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.

Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Scaling of mortality in 742 metropolitan areas of the Americas

We explored how mortality scales with city population size using vital registration and population data from 742 cities in 10 Latin American countries and the United States. We found that more populated cities had lower mortality (sublinear scaling), driven by a sublinear pattern in U.S. cities, while Latin American cities had similar mortality across city sizes. Sexually transmitted infections and homicides showed higher rates in larger cities (superlinear scaling). Tuberculosis mortality behaved sublinearly in U.S. and Mexican cities and superlinearly in other Latin American cities. Other communicable, maternal, neonatal, and nutritional deaths, and deaths due to noncommunicable diseases were generally sublinear in the United States and linear or superlinear in Latin America. Our findings reveal distinct patterns across the Americas, suggesting no universal relation between city size and mortality, pointing to the importance of understanding the processes that explain heterogeneity in scaling behavior or mortality to further advance urban health policies.

Associations between everyday discrimination and sleep quality and duration among African-Americans over time in the Jackson Heart Study

STUDY OBJECTIVES

African-Americans have a high burden of poor sleep, yet, psychosocial determinants (e.g. discrimination) are understudied. We investigated longitudinal associations between everyday discrimination and sleep quality and duration among African-Americans (N = 3404) in the Jackson Heart Study.

METHODS

At Exam 1 (2000-2004) and Exam 3 (2008-2013), participants completed the Everyday Discrimination Scale, rated their sleep quality (1 = poor to 5 = excellent), and self-reported hours of sleep. A subset of participants (N = 762) underwent 7-day actigraphy to objectively measure sleep duration and sleep quality (Sleep Exam 2012-2016). Changes in discrimination were defined as low stable (reference), increasing, decreasing, and high stable. Within-person changes in sleep from Exam 1 to Exam 3 were regressed on change in discrimination from Exam 1 to Exam 3 while adjusting for age, sex, education, income, employment, physical activity, smoking, body mass index, social support, and stress.

RESULTS

At Exam 1, the mean age was 54.1 (12.0) years; 64% were female, mean sleep quality was 3.0 (1.1) and 54% were short sleepers. The distribution of the discrimination change trajectories were 54.1% low stable, 13.5% increasing, 14.6% decreasing, and 17.7% were high stable. Participants who were in the increasing (vs. low stable) discrimination group had greater decrease in sleep quality. There was no association between change in discrimination and change in sleep duration. Among Sleep Exam participants, higher discrimination was cross-sectionally associated with shorter self-reported sleep duration, independent of stress.

CONCLUSION

Discrimination is a unique stressor for African-Americans; thus, future research should identify interventions to reduce the burden of discrimination on sleep quality.

The role of perceived discrimination in predicting changes in health behaviours among African Americans in the Jackson Heart Study

BACKGROUND

This study examined whether perceived discrimination was associated with health behaviours over time and whether associations of discrimination with behaviours varied by attribution of discrimination.

METHODS

Multinomial logistic regression was used to estimate ORs and CIs for the associations of discrimination (everyday, lifetime, stress from lifetime discrimination) with health behaviours (cigarette smoking, alcohol use) over time among 3050 African Americans in the Jackson Heart Study from visit 1 (2000-2004) to visit 3 (2009-2013). Smoking status was classified as persistent current, persistent former, persistent never, current to former and former/never to current smokers. Alcohol use status was classified as persistent heavy, persistent moderate/none, heavy to moderate/none and moderate/none to heavy alcohol users.

RESULTS

Higher everyday discrimination was associated with persistent current smoking (OR per SD higher discrimination 1.26, 95% CI 1.11,1.43) and with persistent former smoking (high vs low OR 1.32, 95% CI 1.02,1.70) relative to persistent never smoking. Similar findings were observed for lifetime discrimination and persistent current smoking (high vs low OR 1.85, 95% CI 1.15,2.95) and with persistent former smoking (high vs low OR 1.45, 95% CI 1.06,1.98). Participants reporting lifetime discrimination as very stressful compared with not stressful were more likely to be persistent former smokers (OR 1.44, 95% CI 1.04,1.99). Associations did not vary by discrimination attribution.

CONCLUSION

Discrimination did not predict changes in smoking status or alcohol use. Discrimination was associated with persistent current smoking status, which may provide a plausible mechanism through which discrimination impacts the health of African Americans.

The built and social neighborhood environment and child obesity: A systematic review of longitudinal studies

The built and social neighborhood environment where a child lives has been increasingly studied as an exposure that may affect child weight long term. We conducted a systematic review of primary research articles published in 2011 through 2019 that reported results from longitudinal analyses of associations between neighborhood environment characteristics and child obesity or weight. Neighborhood environment measures included proximity to food stores, parks, and recreational facilities, walkability, crime, perceived safety, and social cohesion. Information on study population, exposure and outcome measures, and main results were extracted from 39 studies and results were presented for full cohorts and stratified by sex. Most studies were prospective cohorts (90%) with a median follow-up time of six years. Studies analyzing changes in the neighborhood versus changes in weight were less common than approaches analyzing baseline measures of the neighborhood environment in relation to obesity incidence or weight trajectories. Associations varied by sex, race/ethnicity, and age group. Within the food environment domain, the strongest evidence of adverse impact was for fast food restaurants but the effect was only apparent among girls. Results suggested green space, parks, and recreational facilities may have a beneficial effect on weight. Increased crime and low perceived safety may be risk factors for increased weight although not all studies were consistent. Standardization of measures across studies, investigation of multiple social and physical environment measures simultaneously, effect modification by demographic characteristics, and change in the environment vs change in weight analyses are needed to strengthen conclusions.

The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data

BACKGROUND

Little is known about the effect of changes in mobility at the subcity level on subsequent COVID-19 incidence, which is particularly relevant in Latin America, where substantial barriers prevent COVID-19 vaccine access and non-pharmaceutical interventions are essential to mitigation efforts. We aimed to examine the longitudinal associations between population mobility and COVID-19 incidence at the subcity level across a large number of Latin American cities.

METHODS

In this longitudinal ecological study, we compiled aggregated mobile phone location data, daily confirmed COVID-19 cases, and features of urban and social environments to analyse population mobility and COVID-19 incidence at the subcity level among cities with more than 100 000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico, from March 2 to Aug 29, 2020. Spatially aggregated mobile phone data were provided by the UN Development Programme in Latin America and the Caribbean and Grandata; confirmed COVID-19 cases were from national government reports and population and socioeconomic factors were from the latest national census in each country. We used mixed-effects negative binomial regression for a time-series analysis, to examine longitudinal associations between weekly mobility changes from baseline (prepandemic week of March 2-9, 2020) and subsequent COVID-19 incidence (lagged by 1-6 weeks) at the subcity level, adjusting for urban environmental and socioeconomic factors (time-invariant educational attainment, residential overcrowding, population density [all at the subcity level], and country).

FINDINGS

We included 1031 subcity areas, representing 314 Latin American cities, in Argentina (107 subcity areas), Brazil (416), Colombia (82), Guatemala (20), and Mexico (406). In the main adjusted model, we observed an incidence rate ratio (IRR) of 2·35 (95% CI 2·12-2·60) for COVID-19 incidence per log unit increase in the mobility ratio (vs baseline) during the previous week. Thus, 10% lower weekly mobility was associated with 8·6% (95% CI 7·6-9·6) lower incidence of COVID-19 in the following week. This association gradually weakened as the lag between mobility and COVID-19 incidence increased and was not different from null at a 6-week lag.

INTERPRETATION

Reduced population movement within a subcity area is associated with a subsequent decrease in COVID-19 incidence among residents of that subcity area. Policies that reduce population mobility at the subcity level might be an effective COVID-19 mitigation strategy, although they should be combined with strategies that mitigate any adverse social and economic consequences of reduced mobility for the most vulnerable groups.

FUNDING

Wellcome Trust.

TRANSLATION

For the Spanish translation of the abstract see Supplementary Materials section.

Built environment profiles for Latin American urban settings: The SALURBAL study

The built environment of cities is complex and influences social and environmental determinants of health. In this study we, 1) identified city profiles based on the built landscape and street design characteristics of cities in Latin America and 2) evaluated the associations of city profiles with social determinants of health and air pollution. Landscape and street design profiles of 370 cities were identified using finite mixture modeling. For landscape, we measured fragmentation, isolation, and shape. For street design, we measured street connectivity, street length, and directness. We fitted a two-level linear mixed model to assess the association of social and environmental determinants of health with the profiles. We identified four profiles for landscape and four for the street design domain. The most common landscape profile was the "proximate stones" characterized by moderate fragmentation, isolation and patch size, and irregular shape. The most common street design profile was the "semi-hyperbolic grid" characterized by moderate connectivity, street length, and directness. The "semi-hyperbolic grid", "spiderweb" and "hyperbolic grid" profiles were positively associated with higher access to piped water and less overcrowding. The "semi-hyperbolic grid" and "spiderweb" profiles were associated with higher air pollution. The "proximate stones" and "proximate inkblots" profiles were associated with higher congestion. In conclusion, there is substantial heterogeneity in the urban landscape and street design profiles of Latin American cities. While we did not find a specific built environment profile that was consistently associated with lower air pollution and better social conditions, the different configurations of the built environments of cities should be considered when planning healthy and sustainable cities in Latin America.

Using cause-effect graphs to elicit expert knowledge for cross-impact balance analysis

Cross-impact balance (CIB) analysis leverages expert knowledge pertaining to the nature and strength of relationships between components of a system to identify the most plausible future ‘scenarios’ of the system. These scenarios, also referred to as ‘storylines’, provide qualitative insights into how the state of one factor can either promote or restrict the future state of one or multiple other factors in the system. This paper presents a novel, visually oriented questionnaire developed to elicit expert knowledge about the relationships between key factors in a system, for the purpose of CIB analysis. The questionnaire requires experts to make selections from a series of standardized cause-effect graphical profiles that depict a range of linear and non-linear relationships between factor pairs. The questionnaire and the process of translating the graphical selections into data that can be used for CIB analysis is described using an applied example which focuses on urban health in Latin American cities.•

A questionnaire featuring a set of standardized cause-effect profiles was developed.

•

Cause-effect profiles were used to elicit information about the strength of linear and non-linear bivariate relationships.

•

The questionnaire represents an intuitive visual means for collecting data required for the conduct of CIB analysis.

Mortality amenable to healthcare in Latin American cities: a cross-sectional study examining between-country variation in amenable mortality and the role of urban metrics

Background

This study examined the variation in city-level amenable mortality, i.e. mortality due to conditions that can be mitigated in the presence of timely and effective healthcare, in 363 Latin American cities and measured associations between amenable-mortality rates and urban metrics.

Methods

We used death records from 363 cities with populations of >100 000 people in nine Latin American countries from 2010 to 2016. We calculated sex-specific age-adjusted amenable-mortality rates per 100 000. We fitted multilevel linear models with cities nested within countries and estimated associations between amenable mortality and urban metrics, including population size and growth, fragmentation of urban development and socio-economic status.

Results

Cities in Mexico, Colombia and Brazil had the highest rates of amenable mortality. Overall, >70% of the variability in amenable mortality was due to between-country heterogeneity. But for preventable amenable mortality, those for which the healthcare system can prevent new cases, most of the variability in rates occurred between cities within countries. Population size and fragmentation of urban development were associated with amenable mortality. Higher fragmentation of urban development was associated with lower amenable mortality in small cities and higher amenable mortality in large cities. Population growth and higher city-level socio-economic status were associated with lower amenable mortality.

Conclusions

Most of the variability in amenable mortality in Latin American cities was due to between-county heterogeneity. However, urban metrics such as population size and growth, fragmentation of urban development and city-level socio-economic status may have a role in the distribution of amenable mortality across cities within countries.

From causal loop diagrams to future scenarios: Using the cross-impact balance method to augment understanding of urban health in Latin America

Urban health is shaped by a system of factors spanning multiple levels and scales, and through a complex set of interactions. Building on causal loop diagrams developed via several group model building workshops, we apply the cross-impact balance (CIB) method to understand the strength and nature of the relationships between factors in the food and transportation system, and to identify possible future urban health scenarios (i.e., permutations of factor states that impact health in cities). We recruited 16 food and transportation system experts spanning private, academic, non-government, and policy sectors from six Latin American countries to complete an interviewer-assisted questionnaire. The questionnaire, which was pilot tested on six researchers, used a combination of questions and visual prompts to elicit participants' perceptions about the bivariate relationships between 11 factors in the food and transportation system. Each participant answered questions related to a unique set of relationships within their domain of expertise. Using CIB analysis, we identified 21 plausible future scenarios for the system. In the baseline model, 'healthy' scenarios (with low chronic disease, high physical activity, and low consumption of highly processed foods) were characterized by high public transportation subsidies, low car use, high street safety, and high free time, illustrating the links between transportation, free time and dietary behaviors. In analyses of interventions, low car use, high public transport subsidies and high free time were associated with the highest proportion of factors in a healthful state and with high proportions of 'healthy' scenarios. High political will for social change also emerged as critically important in promoting healthy systems and urban health outcomes. The CIB method can play a novel role in augmenting understandings of complex urban systems by enabling insights into future scenarios that can be used alongside other approaches to guide urban health policy planning and action.

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.

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.

Urban social determinants of non-communicable diseases risk factors in Argentina

We examined associations of individual-, neighborhood- and city-level education -as proxies of SES at different levels-, with diabetes, hypertension, obesity, smoking and binge drinking (non-communicable disease risk factors -NCD/RF) among Argentinian adults. We estimated mixed models based on 21,415 individuals from the 2013 National Survey of Risk Factors, living in 2,698 neighborhoods and 33 cities. Gradients by individual-level education differed by gender and NCD/RF, and some were modified by city education. In addition, we identified contextual effects of neighborhood and city education on some NCD/RF. Urban efforts to tackle NCD/RF in Argentina should be context- and gender-sensitive, and mainly focused on socially disadvantaged groups.

Effects of ambient air pollution on childhood asthma exacerbation in the Philadelphia metropolitan Region, 2011-2014

Fine particulate matter (PM_2.5) and ozone (O₃) air pollutants are known risk factors for asthma exacerbation. We studied the association of these air pollutants with pediatric asthma exacerbation in the Philadelphia metropolitan region, and evaluated potential effect modification by children's characteristics (e.g., race/ethnicity, atopic conditions) and environmental factors (e.g., neighborhood tree canopy, meteorological factors, aeroallergens). We conducted a time-stratified case-crossover study of 54,632 pediatric (age ≤18 years) asthma exacerbation cases occurring from 2011 to 2014, identified through electronic health records (EHR) of the Children's Hospital of Philadelphia (CHOP) health system. We applied conditional logistic regression to estimate associations between air pollution and asthma exacerbation, using daily census-tract level pollutant concentrations estimated from the EPA Fused Air Quality Surface Using Downscaling (FAQSD) files. The associations were estimated within warm (Apr-Sep) and cold (Oct-Mar) months for unlagged exposure and for cumulative effects up to 5 days after exposure, with adjustment for temperature, relative humidity, and holidays. We found small increases in odds of asthma exacerbation with higher pollutant concentrations, with positive associations (OR, comparing concentrations of 75th to 25th percentile) observed for PM_2.5 during both warm (1.03, 95% CI: 0.98-1.08) and cold months (1.05, 95% CI: 1.02-1.07), and for O₃ during cold months (1.08, 95% CI: 1.02-1.14). The exposure-response relationship with PM_2.5 during the cold months was essentially linear, whereas thresholds of effect were observed for the other associations at low-medium pollutant concentrations. Results were robust to multi-pollutant modeling and adjustment for additional covariates. We found no effect modification by most children's characteristics, while effect sizes were higher on days with detected tree and grass pollens during warm months. Our results suggest that even small decreases in pollutant concentrations could potentially reduce risk of childhood asthma exacerbation - an important finding, given the high burden of childhood asthma and known disparities in asthma control.

The Regeneración Urbana, Calidad de Vida y Salud - RUCAS project: a Chilean multi-methods study to evaluate the impact of urban regeneration on resident health and wellbeing

BACKGROUND

The available evidence of the health effects of urban regeneration is scarce In Latin America, and there are no studies focused on formal housing that longitudinally evaluate the impact of housing and neighborhood interventions on health. The "Regeneración Urbana, Calidad de Vida y Salud" (Urban Regeneration, Quality of Life, and Health) or RUCAS project is a longitudinal, multi-method study that will evaluate the impact of an intervention focused on dwellings, built environment and community on the health and wellbeing of the population in two social housing neighborhoods in Chile.

METHODS

RUCAS consists of a longitudinal study where inhabitants exposed and unexposed to the intervention will be compared over time within the study neighborhoods (cohorts), capitalizing on interventions as a natural experiment. Researchers have developed a specific conceptual framework and identified potential causal mechanisms. Proximal and more distal intervention effects will be measured with five instruments, implemented pre- and post-interventions between 2018 and 2021: a household survey, an observation tool to evaluate dwelling conditions, hygrochrons for measuring temperature and humidity inside dwellings, systematic observation of recreational areas, and qualitative interviews. Survey baseline data (956 households, 3130 individuals) is presented to describe sociodemographics, housing and health characteristics of both cohorts, noting that neighborhoods studied show worse conditions than the Chilean population.

DISCUSSION

RUCAS' design allows for a comprehensive evaluation of the effects that the intervention could have on various dimensions of health and health determinants. RUCAS will face some challenges, like changes in the intervention process due to adjustments of the master plan, exogenous factors -including COVID-19 pandemic and associated lockdowns- and lost to follow-up. Given the stepped wedge design, that the study capitalizes on within household changes over time, the possibility of adjusting data collection process and complementarity of methods, RUCAS has the flexibility to adapt to these circumstances. Also, RUCAS' outreach and retention strategy has led to high retention rates. RUCAS will provide evidence to inform regeneration processes, highlighting the need to consider potential health effects of regeneration in designing such interventions and, more broadly, health as a key priority in urban and housing policies.

Cross-Sectional Associations of Built and Social Neighborhood Environment Variables with Body Mass Index in a Large Sample of Urban Predominantly African American Children

Background and Objectives: Neighborhood environments may play a role in the development of child obesity by providing or limiting opportunities for children to be physically active and access healthy food near the home. This study quantifies associations between the neighborhood built and social environment and age- and sex- standardized body mass index (BMI) z-scores in a predominantly African American urban sample. Methods: Electronic health record data from a pediatric integrated delivery system (N = 26,460 children, 6 to 19 years old in Philadelphia in 2014) were linked to eight built and social neighborhood environment characteristics. Generalized estimating equations were used to obtain adjusted associations between neighborhood features and age- and sex-adjusted BMI Z-score. Interactions between built and social exposures were examined, as well as effect modification by age, sex, neighborhood socioeconomic status, and population density. Results: Of 26,460 children, 17% were overweight and 21% were obese. After adjustment for individual- and neighborhood-level confounders, higher neighborhood greenness and higher walkability were associated with lower BMI z-score [mean difference per standard deviation (SD): -0.069 (95% confidence interval: [-0.108 to -0.031] and -0.051 [-0.085, -0.017], respectively)]. Higher levels of neighborhood food and physical activity resources were associated with higher BMI z-score [mean difference per SD 0.031 (0.012 and 0.050)]. We observed no interaction between the built and social neighborhood measures. Conclusion: Policies to promote walkability and greening of urban neighborhoods may contribute to preventing obesity in children.

Linking Data on Constituent Health with Elected Officials' Opinions: Associations Between Urban Health Disparities and Mayoral Officials' Beliefs About Health Disparities in Their Cities

Policy Points Mayoral officials' opinions about the existence and fairness of health disparities in their city are positively associated with the magnitude of income-based life expectancy disparity in their city. Associations between mayoral officials' opinions about health disparities in their city and the magnitude of life expectancy disparity in their city are not moderated by the social or fiscal ideology of mayoral officials or the ideology of their constituents. Highly visible and publicized information about mortality disparities, such as that related to COVID-19 disparities, has potential to elevate elected officials' perceptions of the severity of health disparities and influence their opinions about the issue.

CONTEXT

A substantive body of research has explored what factors influence elected officials' opinions about health issues. However, no studies have assessed the potential influence of the health of an elected official's constituents. We assessed whether the magnitude of income-based life expectancy disparity within a city was associated with the opinions of that city's mayoral official (i.e., mayor or deputy mayor) about health disparities in their city.

METHODS

The independent variable was the magnitude of income-based life expectancy disparity in US cities. The magnitude was determined by linking 2010-2015 estimates of life expectancy and median household income for 8,434 census tracts in 224 cities. The dependent variables were mayoral officials' opinions from a 2016 survey about the existence and fairness of health disparities in their city (n = 224, response rate 30.3%). Multivariable logistic regression was used to adjust for characteristics of mayoral officials (e.g., ideology) and city characteristics.

FINDINGS

In cities in the highest income-based life expectancy disparity quartile, 50.0% of mayoral officials "strongly agreed" that health disparities existed and 52.7% believed health disparities were "very unfair." In comparison, among mayoral officials in cities in the lowest disparity quartile 33.9% "strongly agreed" that health disparities existed and 22.2% believed the disparities were "very unfair." A 1-year-larger income-based life expectancy disparity in a city was associated with 25% higher odds that the city's mayoral official would "strongly agree" that health disparities existed (odds ratio [OR] = 1.25; P = .04) and twice the odds that the city's mayoral official would believe that such disparities were "very unfair" (OR = 2.24; P <.001).

CONCLUSIONS

Mayoral officials' opinions about health disparities in their jurisdictions are generally aligned with, and potentially influenced by, information about the magnitude of income-based life expectancy disparities among their constituents.

Association of education level with diabetes prevalence in Latin American cities and its modification by city social environment

Background

Diabetes prevalence continues to increase in urban areas of low-income and middle-income countries (LMIC). Evidence from high-income countries suggests an inverse association between educational attainment and diabetes, but research in LMIC is limited. We investigated educational differences in diabetes prevalence across 232 Latin American (LA) cities, and the extent to which these inequities vary across countries/cities and are modified by city socioeconomic factors.

Methods

Using harmonised health survey and census data for 110 498 city dwellers from eight LA countries, we estimated the association between education and diabetes. We considered effect modification by city Social Environment Index (SEI) as a proxy for city-level development using multilevel models, considering heterogeneity by sex and country.

Results

In women, there was an inverse dose–response relationship between education and diabetes (OR: 0.80 per level increase in education, 95% CI 0.75 to 0.85), consistent across countries and not modified by SEI. In men, Argentina, Brazil, Colombia, Chile and Mexico showed an inverse association (pooled OR: 0.92; 95% CI 0.86 to 0.99). Peru, Panama and El Salvador showed a positive relationship (pooled OR 1.24; 95% CI 1.04 to 1.49). For men, these associations were further modified by city-SEI: in countries with an inverse association, it became stronger as city-SEI increased. In countries where the association was positive, it became weaker as city-SEI increased.

Conclusion

Social inequities in diabetes inequalities increase as cities develop. To achieve non-communicable disease-related sustainable development goals in LMIC, there is an urgent need to develop policies aimed at reducing these educational inequities.