IntroductionAlthough travel behavior is expected to influence personal health, few studies have examined associations with mental health. This study examines associations between commute patterns and mental health using survey data in 11 Latin American cities.MethodsUsing a survey conducted by the Development Bank of Latin America in 2016, we measured the presence of depressive symptoms using the 10-item Center for Epidemiologic Studies Depression (CESD-10) screening scale. We used multilevel non-linear models to estimate the magnitude of the associations between commute patterns and depression risk, adjusting for socio-demographic and neighborhood characteristics.ResultsWe found that, on average, every 10 more minutes of commuting time is associated with 0.5% (p = 0.011) higher probability of screening positively for depression. Furthermore, when decomposing commuting time into free-flow time and delay time, we found that delay and not free-flow time, were associated with depression. Specifically, every 10 additional minutes of traffic delay is associated with 0.8% (p = 0.037) higher probability of screening positively for depression. When examining differences by travel mode, we find that users of formal transit (e.g. subway or bus rapid transit) are 4.8% (p = 0.040) less likely to be screened positively for depression than drivers. In addition, not having transit stops within a 10-min walk from home is associated with higher probability of screening positively for depression.ConclusionsOur findings provide preliminary evidence that better access to mass transit systems and less congestion may be linked to better mental health among urban residents.

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Ciclovía Recreativa is a program in which streets are closed off to automobiles so that people have a safe and inclusive space for recreation and for being physically active. The study aims were: (1) to compare participant’s spatial trajectories in four Ciclovía Recreativa programs in Latin America (Bogotá, Mexico City, Santiago de Cali, and Santiago de Chile) according to socioeconomic characteristics and urban segregation of these cities; and (2) to assess the relationship between participants’ physical activity (PA) levels and sociodemographic characteristics. We harmonized data of cross-sectional studies including 3282 adults collected between 2015 and 2019. We found the highest mobility for recreation in Bogotá, followed closely by Santiago de Cali. In these two cities, the maximum SES (socioeconomic status) percentile differences between the neighborhood of origin and the neighborhoods visited as part of the Ciclovía use were 33.58 (p-value < 0.001) and 30.38 (p-value < 0.001), respectively, indicating that in these two cities, participants were more likely to visit higher or lower SES neighborhoods than their average SES-of-neighborhood origin. By contrast, participants from Mexico City and Santiago de Chile were more likely to stay in geographic units similar to their average SES-of-origin, having lower overall mobility during leisure time: maximum SES percentile difference 1.55 (p-value < 0.001) and −0.91 (p-value 0.001), respectively. PA levels of participants did not differ by sex or SES. Our results suggest that Ciclovía can be a socially inclusive program in highly unequal and segregated urban environments, which provides a space for PA whilefacilitat physical proximity, exposure to new communities and environments, and interactions between different socioeconomic groups.

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.

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