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Background: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. Objectives: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. Methods: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM10), PM ≤ 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) from 620 cities in 36 countries in the period 1995–2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. Results: We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM10 was equal to 10 or 90 μg/m3, respectively. Corresponding estimates when daily O3 concentrations were 40 or 160 μg/m3 were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 μg/m3 increment in PM10 was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1st and 99th city-specific percentiles, respectively. Corresponding mortality estimate for O3 across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM2.5 and NO2. Conclusions: Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.

Objectives: To determine the role of the male sex as a risk factor for coronavirus disease deaths in Sao Paulo and to what extent socioeconomic vulnerability and individual health issues can interfere in such risk. Methods: The primary cause of death, age, sex, comorbidities, and code of the Human Development Units of the residence of 37,583 individuals in Sao Paulo, Brazil, were obtained from the records on confirmed coronavirus disease resident hospitalizations of the city of Sao Paulo from the National Influenza Surveillance Information System. A social vulnerability index was assigned to each Human Development Unit. Using “death” as the outcome variable and sex, admission to the intensive care unit, obesity, renal and heart diseases, diabetes, and social vulnerability as confounders, the odds of death for males and females were compared via logistic regression. Results: The odds of death for males were 1.242 (confidence interval 95% = 1.237, 1.247) times the corresponding odds for females with the same values for all confounders. We estimated the odds of death for patients living in regions with high social vulnerability as 2.243 (CI 95% = 2.151, 2.339) times the corresponding odds of patients living in regions with very low social vulnerability with the same values of the remaining variables. Conclusion: The male:female death ratio by severe acute respiratory syndrome coronavirus 2 infection in Sao Paulo cannot be attributed only to comorbidities or social vulnerabilities. Our results suggest that the male sex is an independent biological risk factor for coronavirus disease death. Besides sex-specific factors, further research should focus on crucial biological factors in male sex coronavirus disease mortality.