City-Level Travel Time and Individual Dietary Consumption in Latin American Cities: Results from the SALURBAL Study.

There is limited empirical evidence on how travel time affects dietary patterns, and even less in Latin American cities (LACs). Using data from 181 LACs, we investigated whether longer travel times at the city level are associated with lower consumption of vegetables and higher consumption of sugar-sweetened beverages and if this association differs by city size. Travel time was measured as the average city-level travel time during peak hours and city-level travel delay time was measured as the average increase in travel time due to congestion on the street network during peak hours. Vegetables and sugar-sweetened beverages consumption were classified according to the frequency of consumption in days/week (5-7: "frequent", 2-4: "medium", and ≤1: "rare"). We estimate multilevel ordinal logistic regression modeling for pooled samples and stratified by city size. Higher travel time (Odds Ratio (OR) = 0.65; 95% Confidence Interval (CI) 0.49-0.87) and delay time (OR = 0.57; CI 0.34-0.97) were associated with lower odds of frequent vegetable consumption. For a rare SSB consumption, we observed an inverse association with the delay time (OR = 0.65; CI 0.44-0.97). Analysis stratified by city size show that these associations were significant only in larger cities. Our results suggest that travel time and travel delay can be potential urban determinants of food consumption.

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.

Physical Disorders and Poor Self-Rated Health in Adults Living in Four Latin American Cities: A Multilevel Approach.

Considering that urban environments may affect self-rated health through behavioral and psychosocial mechanisms, the aim of this study was to investigate the association between self-rated health and perceived urban environment characteristics among adults living in four Latin American cities. Data is from a population-based survey by Development Bank of Latin America, encompassing adults between 20 and 60 years old in Buenos Aires, Lima, Mexico City, and Panama City. Self-rated health was measured using a single question and the response options were categorized as poor and good. The explanatory variables were empirical Bayes estimates of self-reported area physical disorder, social disorder, access to services, and access to leisure spaces derived from the survey. The covariates were: individual age, sex, education, wealth index, and length of residency in the neighborhood; and an area social environment index. Multilevel logistic regressions with two levels (individual and sub-city areas) were fitted. Poor self-rated health was reported by 34.73% (95% CI: 33.17 to 36.29) of the participants and was associated with physical disorder (OR = 1.16 per SD; 95% CI: 1.02 to 1.32). Our findings suggest that public policies to promote population health should consider area urban environment factors, especially those associated with disorder.