Background: Asbestos consumption in Latin America (LA) amounts to 10% of yearly global production. Little is known about the impact of asbestos exposure in the region. Objective: To discuss scientific and socio-economic issues and conflicts of interest and to summarize epidemiological data of asbestos health effects in LA. Discussion: Recent data on chrysotile strengthened the evidence of its carcinogenicity and showed an excessive risk of lung cancer at cumulative exposure levels as low as 1.5 fibre-years/ml. Technology for substitution is available for all asbestos-containing products and ceasing asbestos production and manufacturing will not result in unemployment and loss of income, except for the mining industry. The flawed arguments used by the industry to maintain its market, both to the public and in courtrooms, strongly relies on the lack of local evidence of the ill effects and on the invisibility of asbestos-related diseases in LA, due to the limited number of studies and the exposed workers’ difficulty accessing health services. The few epidemiological studies available show clear evidence of clusters of mesothelioma in municipalities with a history of asbestos consumption and a forecasted rise in its incidence in Argentina and Brazil for the next decade. In Brazil, non-governmental organizations of asbestos workers were pivotal to counterbalance misinformation and inequities, ending recently in a Supreme Court decision backing an asbestos ban. In parallel, continuous efforts should be made to stimulate the growth of competent and ethical researchers to convey adequate information to the scientific community and to the general public.

BackgroundDiabetes 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.MethodsUsing 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.ResultsIn 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.ConclusionSocial 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.

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Background Understanding how urban environments influence people’s health, especially as individuals age, can help identify ways to improve health in the rapidly urbanizing and rapidly aging populations. Objectives To investigate the association between age and self-reported health (SRH) in adults living in Latin-American cities and whether gender and city-level socioeconomic characteristics modify this association. Methods Cross-sectional analyses of 71,541 adults aged 25–97 years, from 114 cities in 6 countries (Argentina, Brazil, Colombia, Chile, El Salvador, and Guatemala), as part of the Salud Urbana en America Latina (SALURBAL) Project. We used individual-level age, gender, education, and self-reported health (SRH) data from harmonized health surveys. As proxies for socioeconomic environment we used a city-level socioeconomic index (SEI) calculated from census data, and gross domestic product (GDP) per-capita. Multilevel Poisson models with a robust variance were used to estimate relative risks (RR), with individuals nested in cities and binary SRH (poor SHR vs. good SRH) as the outcome. We examined effect modification by gender and city-level socioeconomic indicators. Results Overall, 31.4% of the sample reported poor SRH. After adjusting for individual-level education, men had a lower risk of poor SRH (RR = 0.76; CI 0.73–0.78) compared to women, and gender modified the association between age and poor SRH (p-value of interaction < 0.001). In gender stratified models, the association between older age and poor SRH was more pronounced in men than in women, and in those aged 25–65 than among those 65+ (RR/10 years = 1.38 vs. 1.10 for men, and RR/10 years = 1.29 vs. 1.02 for women). Living in cities with higher SEI or higher GDP per-capita was associated with a lower risk of poor SRH. GDP per-capita modified the association between age (25–65) and SRH in men and women, with SEI the interaction was less clear. Conclusions Across cities in Latin America, aging impact on health is significant among middle-aged adults, and among men. In both genders, cities with lower SEI or lower GDP per-capita were associated with poor SRH. More research is needed to better understand gender inequalities and how city socioeconomic environments, represented by different indicators, modify exposures and vulnerabilities associated with aging.

Studies of life expectancy (LE) in small areas of cities are relatively common in high-income countries but rare in Latin American countries. Small-area estimation methods can help to describe and quantify inequities in LE between neighborhoods and their predictors. Our objective was to analyze the distribution and spatial patterning of LE across small areas of Ciudad Autónoma de Buenos Aires (CABA), Argentina, and its association with socioeconomic characteristics. As part of the SALURBAL project, we used georeferenced death certificates in 2015–2017 for CABA, Argentina. We used a spatial Bayesian Poisson model using the TOPALS method to estimate age- and sex-specific mortality rates. We used life tables to estimate LE at birth. We obtained data on neighborhood socioeconomic characteristics from the 2010 census and analyzed their associations. LE at birth was higher for women (median of across neighborhoods = 81.1 years) compared to men (76.7 years). We found a gap in LE of 9.3 (women) and 14.9 years (men) between areas with the highest and the lowest LE. Better socioeconomic characteristics were associated with higher LE. For example, mean differences in LE at birth in areas with highest versus lowest values of composite SES index were 2.79 years (95% CI: 2.30 to 3.28) in women and 5.61 years (95% CI: 4.98 to 6.24) in men. We found large spatial inequities in LE across neighborhoods of a large city in Latin America, highlighting the importance of place-based policies to address this gap.