Social disparities in flood exposure and associations with the urban environment in 44,698 neighborhoods in 276 cities in eight Latin American countries.

Background: Climate change is expected to greatly increase exposure to flooding, particularly in urban populations in low- and middle-income countries. We examined within-city social disparities in exposure to flooding in 276 Latin American cities and associated features of the neighborhood urban environment. Methods: We used a spatially granular dataset of historical flood events from 2000 to 2018 to describe neighborhood flooding within cities across eight Latin American countries (Argentina, Brazil, Chile, Colombia, Costa Rica, Guatemala, Mexico, and Panama). We estimated the percentage of the population living in flooded neighborhoods, described social disparities in flooding based on neighborhood educational attainment, and compared the magnitude of disparities across and within cities. We used multilevel models to examine how city- and neighborhood-level factors are related to neighborhood flooding. Results: We examined 44,698 neighborhoods in 276 cities from eight countries with a total of 223 million residents and 117 distinct flood events from 2000-2018. One in four residents in neighborhoods in the lowest education quintile lived in neighborhoods with flooding, compared to one in 20 residents of the highest neighborhood education quintile. Greater neighborhood flooding was associated with lower neighborhood-level educational attainment and with neighborhoods that were coastal, less dense (population or intersection), further from the city center, greener, and had steeper slopes. There was no association between city-level educational attainment and flooding. Conclusion: There are large social disparities in neighborhood flooding within Latin American cities. Residents of areas with lower education attainment face substantially higher risks of flooding. Policymakers must prioritize flood adaptation and recovery efforts in neighborhoods with lower socioeconomic position.

Corrigendum to "Health disparities in past influenza pandemics: A scoping review of the literature" [SSM - Population Health (2023) 21C 101314].

[This corrects the article DOI: 10.1016/j.ssmph.2022.101314.].

Impact of an enhanced sobriety checkpoints programme and publicity campaign on motor vehicle collisions, injuries and deaths in Leon, MX: a synthetic control study.

OBJECTIVE: Drunk driving is a major cause of road traffic injuries and deaths in Latin America. We evaluated the impact of a drunk driving intervention in Leon, Mexico on road traffic safety. METHODS: The intervention included increased drunk driving penalties, enhanced sobriety checkpoints and a young adult-focused mass media campaign, beginning 19 December 2018. We created a synthetic control Leon from 12 Mexican municipalities from a pool of 87 based on similarity to Leon using key predictors from 2015 to 2019. We assessed the effect of the intervention on road traffic collisions overall and collisions with injuries, deaths and involving alcohol, using data from police, insurance claims and vital registration. RESULTS: As compared with the synthetic control, Leon experienced significant postintervention lower police-reported total collision rate (17%) and injury collisions (33%). Alcohol-involved collisions were 38% lower than the synthetic control. Fatal collisions reported by police were 28% lower while vital registration road traffic deaths were 12% lower, though these declines were not statistically significant. We found no impact on insurance collision claims. There was heterogeneity in these changes over the evaluation year, with stronger initial effects and weaker effects by the end of the year. CONCLUSIONS: Drunk driving policies in Leon led to fewer traffic collisions and injuries during the first year of implementation, with a weakening of this effect over time, similar to interventions in high-income settings and other Latin American countries. Supporting the expansion of similar policies to other cities in the region could improve road safety.

Development and validation of statewide survey-based measures of livability in Connecticut.

Livability, or how a place and its systems (e.g., housing, transportation) supports the ability to lead a livable life, is a determinant of health. There is a lack of standard, validated measures to assess livability in the US. This study employed factor analytic methods to create measures of livability in Connecticut using data from the DataHaven Community Wellbeing Survey (DCWS) (n = 32,262). Results identified a 3-factor model (safety, opportunity, and infrastructure) as the best fit, explaining 69% of the variance in survey items. Newly created livability measures had high internal consistency, in addition to high convergent validity with other area-level measures.

Spatial Heterogeneity in Fatal Overdose Rate Trends in Mexican Cities: 2005-2021.

Objectives. To describe national and city-level fatal drug overdose trends between 2005 and 2021 in Mexico. Methods. We calculated fatal overdose rates at the city level in 3-year periods from 2005 to 2021 and annually at the national level for people aged 15 to 64 years in Mexico. We calculated rate differences and rate ratios for each city between periods. Results. The national fatal overdose rate was 0.53 overdose deaths per 100 000 population and was almost twice as high in urban than in nonurban areas. The national fatal overdose rate was stable over the period 2005 to 2014 and increased monotonically to a peak in 2021. Fatal overdose rates varied across cities. Cities with the 8 highest fatal overdose rates in the period were all in states along the US-Mexico border. Conclusions. Fatal overdoses have doubled over the past 15 years in Mexico. Overdose rates are particularly high and increasing in cities close to the US-Mexico border. Public Health Implications. There is a need for enhanced overdose surveillance data and coordinated harm reduction strategies, particularly in the northern border region of Mexico. (Am J Public Health. 2024;114(7):705-713. https://doi.org/10.2105/AJPH.2024.307650).

Area-Level Social Vulnerability and Severe COVID-19: A Case-Control Study Using Electronic Health Records from Multiple Health Systems in the Southeastern Pennsylvania Region.

Knowledge about neighborhood characteristics that predict disease burden can be used to guide equity-based public health interventions or targeted social services. We used a case-control design to examine the association between area-level social vulnerability and severe COVID-19 using electronic health records (EHR) from a regional health information hub in the greater Philadelphia region. Severe COVID-19 cases (n = 15,464 unique patients) were defined as those with an inpatient admission and a diagnosis of COVID-19 in 2020. Controls (n = 78,600; 5:1 control-case ratio) were a random sample of individuals who did not have a COVID-19 diagnosis from the same geographic area. Retrospective data on comorbidities and demographic variables were extracted from EHR and linked to area-level social vulnerability index (SVI) data using ZIP codes. Models adjusted for different sets of covariates showed incidence rate ratios (IRR) ranging from 1.15 (95% CI, 1.13-1.17) in the model adjusted for individual-level age, sex, and marital status to 1.09 (95% CI, 1.08-1.11) in the fully adjusted model, which included individual-level comorbidities and race/ethnicity. The fully adjusted model indicates that a 10% higher area-level SVI was associated with a 9% higher risk of severe COVID-19. Individuals in neighborhoods with high social vulnerability were more likely to have severe COVID-19 after accounting for comorbidities and demographic characteristics. Our findings support initiatives incorporating neighborhood-level social determinants of health when planning interventions and allocating resources to mitigate epidemic respiratory diseases, including other coronavirus or influenza viruses.

Association Between Household Deprivation and Living in Informal Settlements and Incidence of Diarrhea in Children Under 5 in Eleven Latin American Cities.

Diarrhea is a leading cause of death in children globally, mostly due to inadequate sanitary conditions and overcrowding. Poor housing quality and lack of tenure security that characterize informal settlements are key underlying contributors to these risk factors for childhood diarrhea deaths. The objective of this study is to better understand the physical attributes of informal settlement households in Latin American cities that are associated with childhood diarrhea. We used data from a household survey (Encuesta CAF) conducted by the Corporación Andina de Fomento (CAF), using responses from sampled individuals in eleven cities. We created a household deprivation score based on household water and sewage infrastructure, overcrowding, flooring and wall material, and security of tenure. We fitted a multivariable logistic regression model to estimate odds ratios (OR) and 95% confidence intervals (95% CI) to test the association between the deprivation score and its individual components and childhood diarrhea during the prior 2 weeks. We included a total of 4732 households with children, out of which 12.2% had diarrhea in the 2-week period prior to completing the survey. After adjusting for respondent age, gender, and city, we found a higher risk of diarrhea associated with higher household deprivation scores. Specifically, we found that the odds of diarrhea for children living in a mild and severe deprived household were 1.04 (95% CI 0.84-1.28) and 3.19 times (95% CI 1.80-5.63) higher, respectively, in comparison to households with no deprivation. These results highlight the connections between childhood health and deprived living conditions common in informal settlements.

Modifying effect of urban parks on socioeconomic inequalities in diabetes prevalence: a cross-sectional population study of Madrid City, Spain.

BACKGROUND: Evidence has shown contradicting results on how the density of urban green spaces may reduce socioeconomic inequalities in type 2 diabetes (equigenic hypothesis). The aim of this study is to test whether socioeconomic inequalities in diabetes prevalence are modified by park density. METHODS: We designed a population-wide cross-sectional study of all adults registered in the primary healthcare centres in the city of Madrid, Spain (n=1 305 050). We obtained georeferenced individual-level data from the Primary Care Electronic Health Records, and census-tract level data on socioeconomic status (SES) and park density. We modelled diabetes prevalence using robust Poisson regression models adjusted by age, country of origin, population density and including an interaction term with park density, stratified by gender. We used this model to estimate the Relative Index of Inequality (RII) at different park density levels. FINDINGS: We found an overall RII of 2.90 (95% CI 2.78 to 3.02) and 4.50 (95% CI 4.28 to 4.74) in men and women, respectively, meaning that the prevalence of diabetes was three to four and a half times higher in low SES compared with high SES areas. These inequalities were wider in areas with higher park density for both men and women, with a significant interaction only for women (p=0.008). INTERPRETATION: We found an inverse association between SES and diabetes prevalence in both men and women, with wider inequalities in areas with more parks. Future works should study the mechanisms of these findings, to facilitate the understanding of contextual factors that may mitigate diabetes inequalities.

Measuring variation in infant mortality and deaths of despair by US congressional district in Pennsylvania: a methodological case study.

Many ecological studies examine health outcomes and disparities using administrative boundaries such as census tracts, counties, or states. These boundaries help us to understand the patterning of health by place, along with impacts of policies implemented at these levels. However, additional geopolitical units (units with both geographic and political meaning), such as congressional districts (CDs), present further opportunities to connect research with public policy. Here we provide a step-by-step guide on how to conduct disparities-focused analysis at the CD level. As an applied case study, we use geocoded vital statistics data from 2010-2015 to examine levels of and disparities in infant mortality and deaths of despair in the 19 US CDs of Pennsylvania for the 111th-112th (2009-2012) Congresses and 18 CDs for the 113th-114th (2013-2016) Congresses. We also provide recommendations for extending CD-level analysis to other outcomes, states, and geopolitical boundaries, such as state legislative districts. Increased surveillance of health outcomes at the CD level can help prompt policy action and advocacy and, hopefully, reduce rates of and disparities in adverse health outcomes.

A scaling investigation of urban form features in Latin America cities.

This paper examines scaling behaviors of urban landscape and street design metrics with respect to city population in Latin America. We used data from the SALURBAL project, which has compiled and harmonized data on health, social, and built environment for 371 Latin American cities above 100,000 inhabitants. These metrics included total urbanized area, effective mesh size, area in km2 and number of streets. We obtained scaling relations by regressing log(metric) on log (city population). The results show an overall sub-linear scaling behavior of most variables, indicating a relatively lower value of each variable in larger cities. We also explored the potential influence of colonization on the current built environment, by analyzing cities colonized by Portuguese (Brazilian cities) or Spaniards (Other cities in Latin America) separately. We found that the scaling behaviors are similar for both sets of cities.