Wildfire-related PM2.5 and cardiovascular mortality: A difference-in-differences analysis in Brazil.

Brazil has experienced unprecedented wildfires recently. We aimed to investigate the association of wildfire-related fine particulate matter (PM2.5) with cause-specific cardiovascular mortality, and to estimate the attributable mortality burden. Exposure to wildfire-related PM2.5 was defined as exposure to annual mean wildfire-related PM2.5 concentrations in the 1-year prior to death. The variant difference-in-differences method was employed to explore the wildfire-related PM2.5-cardiovascular mortality association. We found that, in Brazil, compared with the population in the first quartile (Q1: ≤1.82 µg/m3) of wildfire-related PM2.5 exposure, those in the fourth quartile (Q4: 4.22-17.12 µg/m3) of wildfire-related PM2.5 exposure had a 2.2% (RR: 1.022, 95% CI: 1.013-1.032) higher risk for total cardiovascular mortality, 3.1% (RR: 1.031, 95% CI: 1.014-1.048) for ischaemic heart disease mortality, and 2.0% (RR: 1.020, 95% CI: 1.002-1.038) for stroke mortality. From 2010 to 2018, an estimation of 35,847 (95% CI: 22,424-49,177) cardiovascular deaths, representing 17.77 (95% CI: 11.12-24.38) per 100,000 population, were attributable to wildfire-related PM2.5 exposure. Targeted health promotion strategies should be developed for local governments to protect the public from the risk of wildfire-related cardiovascular premature deaths.

The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study

Background Physical activity has a protective effect against cardiovascular disease (CVD) in high-income countries, where physical activity is mainly recreational, but it is not known if this is also observed in lower-income countries, where physical activity is mainly non-recreational. We examined whether different amounts and types of physical activity are associated with lower mortality and CVD in countries at different economic levels. Methods In this prospective cohort study, we recruited participants from 17 countries (Canada, Sweden, United Arab Emirates, Argentina, Brazil, Chile, Poland, Turkey, Malaysia, South Africa, China, Colombia, Iran, Bangladesh, India, Pakistan, and Zimbabwe). Within each country, urban and rural areas in and around selected cities and towns were identified to reflect the geographical diversity. Within these communities, we invited individuals aged between 35 and 70 years who intended to live at their current address for at least another 4 years. Total physical activity was assessed using the International Physical Activity Questionnaire (IPQA). Participants with pre-existing CVD were excluded from the analyses. Mortality and CVD were recorded during a mean of 6·9 years of follow-up. Primary clinical outcomes during follow-up were mortality plus major CVD (CVD mortality, incident myocardial infarction, stroke, or heart failure), either as a composite or separately. The effects of physical activity on mortality and CVD were adjusted for sociodemographic factors and other risk factors taking into account household, community, and country clustering.

The association between ownership of common householddevices and obesity and diabetes in high, middle and lowincome countries

Household devices (e.g., television,car, computer) are common in highincome countries, and their use has been linked to obesity and type 2 diabetes mellitus.We hypothesized that device ownership is associated with obesity and diabetes and that these effects are explained through reduced physical activity, increased sitting time and increased energy intake.We performed a cross sectional analysis using data from the Prospective UrbanRural Epidemiology study involving 153 996 adults from high, upper-middle, lower-middle and low income countries. We used multilevel regression models to account for clustering at the community and country levels.Ownership of a household deviceincreased from low to high income countries (4% to 83% for all 3 devices) and was associated with decreased physical activity and increased sitting, dietary energy intake, body mass indexand waist circumference. There was anincreased odds of obesity and diabetes with the ownership of any 1 household device compared to no device ownership (obesity: odds ratio [OR] 1.43, 95% confidence interval [CI] 1.32–1.55;diabetes: OR 1.38, 95% CI 1.28–1.50). Ownership of a second device increased the odds further but ownership of a third device did not. Subsequentadjustment for lifestyle factors modestlyattenuated these associations. Of the 3 devices, ownership of a television had the strongest association with obesity (OR 1.39, 95% CI 1.29–1.49) and diabetes (OR 1.33, 95% CI 1.23–1.44).When stratified by country income level, the odds of obesity and diabetes when owning all 3 devices was greatest in low income countries (obesity: OR 3.15, 95% CI 2.33-4.25; diabetes: OR1.97, 95% CI 1.53–2.53) and ecreased through country income levels such that we did not detect an association in high income countries...