Studies examining urban health and the environment must ensure comparability of measures across cities and countries. We describe a data platform and process that integrates health outcomes together with physical and social environment data to examine multilevel aspects of health across cities in 11 Latin American countries. We used two complementary sources to identify cities with ≥ 100,000 inhabitants as of 2010 in Argentina, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Mexico, Nicaragua, Panama, and Peru. We defined cities in three ways: administratively, quantitatively from satellite imagery, and based on country-defined metropolitan areas. In addition to “cities,” we identified sub-city units and smaller neighborhoods within them using census hierarchies. Selected physical environment (e.g., urban form, air pollution and transport) and social environment (e.g., income, education, safety) data were compiled for cities, sub-city units, and neighborhoods whenever possible using a range of sources. Harmonized mortality and health survey data were linked to city and sub-city units. Finer georeferencing is underway. We identified 371 cities and 1436 sub-city units in the 11 countries. The median city population was 234,553 inhabitants (IQR 141,942; 500,398). The systematic organization of cities, the initial task of this platform, was accomplished and further ongoing developments include the harmonization of mortality and survey measures using available sources for between country comparisons. A range of physical and social environment indicators can be created using available data. The flexible multilevel data structure accommodates heterogeneity in the data available and allows for varied multilevel research questions related to the associations of physical and social environment variables with variability in health outcomes within and across cities. The creation of such data platforms holds great promise to support researching with greater granularity the field of urban health in Latin America as well as serving as a resource for the evaluation of policies oriented to improve the health and environmental sustainability of cities.

Lockdown during the COVID-19 pandemic imposed changes in children’s daily routine that could lead to changes in behavior patterns. Using a survey targeted at children under 17 years of age, we described dietary (adherence to Mediterranean diet, AMD) and sleeping habits (disorders of initiating and maintaining sleep) after the implementation of lockdown, and examined the probability of the inadequate frequency of physical activity (PA) and use of TV and electronic devices (TV-ED) before and after lockdown through generalized estimating equation models, accounting for age and gender differences. From 3464 children included, 53.2% showed optimal AMD; 79.2% referred to delayed bedtime; and 16.3% were suspected of sleeping disorders after the implementation of lockdown. Delay in bedtime was more frequent among children older than 6 years, and inadequate sleeping hours among those younger than 11 years. There were no gender differences in AMD or sleeping habits. The odds of inadequate frequency of PA and TV-ED use were greater after lockdown, with a greater risk for TV-ED use. Boys were at greater risk of inadequate PA frequency and TV-ED use. Odds ratio of inadequate PA was greater at older ages. Lockdown could influence changes in children’s habits that could lead to risk factors for non-communicable diseases during adulthood if such behaviors are sustained over time.

BackgroundUrbanisation in Latin America (LA) is heterogeneous and could have varying implications for infant mortality (IM). Identifying city factors related to IM can help design policies that promote infant health in cities.MethodsWe quantified variability in infant mortality rates (IMR) across cities and examined associations between urban characteristics and IMR in a cross-sectional design. We estimated IMR for the period 2014–2016 using vital registration for 286 cities above 100 000 people in eight countries. Using national censuses, we calculated population size, growth and three socioeconomic scores reflecting living conditions, service provision and population educational attainment. We included mass transit availability of bus rapid transit and subway. Using Poisson multilevel regression, we estimated the per cent difference in IMR for a one SD (1SD) difference in city-level predictors.ResultsOf the 286 cities, 130 had <250 000 inhabitants and 5 had >5 million. Overall IMR was 11.2 deaths/1000 live births. 57% of the total IMR variability across cities was within countries. Higher population growth, better living conditions, better service provision and mass transit availability were associated with 6.0% (95% CI −8.3 to 3.7%), 14.1% (95% CI −18.6 to −9.2), 11.4% (95% CI −16.1 to −6.4) and 6.6% (95% CI −9.2 to −3.9) lower IMR, respectively. Greater population size was associated with higher IMR. No association was observed for population-level educational attainment in the overall sample.ConclusionImproving living conditions, service provision and public transportation in cities may have a positive impact on reducing IMR in LA cities.

Rapid urbanization in low- and middle-income countries (LMIC) is associated with increasing population living in informal settlements. Inadequate infrastructure and disenfranchisement in settlements can create environments hazardous to health. Placed-based physical environment upgrading interventions have potential to improve environmental and economic conditions linked to health outcomes. Summarizing and assessing evidence of the impact of prior interventions is critical to motivating and selecting the most effective upgrading strategies moving forward. Scientific and grey literature were systematically reviewed to identify evaluations of physical environment slum upgrading interventions in LMICs published between 2012 and 2018. Thirteen evaluations that fulfilled inclusion criteria were reviewed. Quality of evaluations was assessed using an adapted Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies. Findings were then pooled with those published prior to 2012. Narrative analysis was performed. Of thirteen evaluations, eight used a longitudinal study design (“primary evaluations”). All primary evaluations were based in Latin America and included two housing, two transportation, and four comprehensive intervention evaluations. Three supporting evaluations assessed housing interventions in Argentina and South Africa; two assessed a comprehensive intervention in India. Effects by intervention-type included improvements in quality of life and communicable diseases after housing interventions, possible improvements in safety after transportation and comprehensive interventions, and possible non-statistically significant effects on social capital after comprehensive interventions. Effects due to interventions may vary by regional context and intervention scope. Limited strong evidence and the diffuse nature of comprehensive interventions suggests a need for attention to measurement of intervention exposure and analytic approaches to account for confounding and selection bias in evaluation. In addition to health improvements, evaluators should consider unintended health consequences and environmental impact. Understanding and isolating the effects of place-based interventions can inform necessary policy decisions to address inadequate living conditions as rapid urban growth continues across the globe.

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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.

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