Maternal greenness exposure and preterm birth in Brazil: A nationwide birth cohort study.

In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%-2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

Short-term exposure to wildfire-related PM2.5 increases mortality risks and burdens in Brazil.

To assess mortality risks and burdens associated with short-term exposure to wildfire-related fine particulate matter with diameter ≤ 2.5 µm (PM2.5), we collect daily mortality data from 2000 to 2016 for 510 immediate regions in Brazil, the most wildfire-prone area. We integrate data from multiple sources with a chemical transport model at the global scale to isolate daily concentrations of wildfire-related PM2.5 at a 0.25 × 0.25 resolution. With a two-stage time-series approach, we estimate (i) an increase of 3.1% (95% confidence interval [CI]: 2.4, 3.9%) in all-cause mortality, 2.6% (95%CI: 1.5, 3.8%) in cardiovascular mortality, and 7.7% (95%CI: 5.9, 9.5) in respiratory mortality over 0-14 days with each 10 µg/m3 increase in daily wildfire-related PM2.5; (ii) 0.65% of all-cause, 0.56% of cardiovascular, and 1.60% of respiratory mortality attributable to acute exposure to wildfire-related PM2.5, corresponding to 121,351 all-cause deaths, 29,510 cardiovascular deaths, and 31,287 respiratory deaths during the study period. In this study, we find stronger associations in females and adults aged ≥ 60 years, and geographic difference in the mortality risks and burdens.

Exposure to wildfire-related PM2.5 and site-specific cancer mortality in Brazil from 2010 to 2016: A retrospective study.

BACKGROUND: Long-term exposure to fine particles ≤2.5 µm in diameter (PM2.5) has been linked to cancer mortality. However, the effect of wildfire-related PM2.5 exposure on cancer mortality risk is unknown. This study evaluates the association between wildfire-related PM2.5 and site-specific cancer mortality in Brazil, from 2010 to 2016. METHODS AND FINDINGS: Nationwide cancer death records were collected during 2010-2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM2.5 concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM2.5 concentration was 2.38 µg/m3, and the annual non-wildfire-related PM2.5 concentration was 8.20 µg/m3. The RR for mortality from all cancers was 1.02 (95% CI 1.01-1.03, p < 0.001) per 1-µg/m3 increase of wildfire-related PM2.5 concentration, which was higher than the RR per 1-µg/m3 increase of non-wildfire-related PM2.5 (1.01 [95% CI 1.00-1.01], p = 0.007, with p for difference = 0.003). Wildfire-related PM2.5 was associated with mortality from cancers of the nasopharynx (1.10 [95% CI 1.04-1.16], p = 0.002), esophagus (1.05 [95% CI 1.01-1.08], p = 0.012), stomach (1.03 [95% CI 1.01-1.06], p = 0.017), colon/rectum (1.08 [95% CI 1.05-1.11], p < 0.001), larynx (1.06 [95% CI 1.02-1.11], p = 0.003), skin (1.06 [95% CI 1.00-1.12], p = 0.003), breast (1.04 [95% CI 1.01-1.06], p = 0.007), prostate (1.03 [95% CI 1.01-1.06], p = 0.019), and testis (1.10 [95% CI 1.03-1.17], p = 0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders. CONCLUSIONS: Exposure to wildfire-related PM2.5 can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM2.5 was higher than for PM2.5 from non-wildfire sources.

High ambient temperature and risk of hospitalization for gastrointestinal infection in Brazil: A nationwide case-crossover study during 2000-2015.

BACKGROUND: The burden of gastrointestinal infections related to hot ambient temperature remains largely unexplored in low-to-middle income countries which have most of the cases globally and are experiencing the greatest impact from climate change. The situation is particularly true in Brazil. OBJECTIVES: Using medical records covering over 78 % of population, we quantify the association between high temperature and risk of hospitalization for gastrointestinal infection in Brazil between 2000 and 2015. METHODS: Data on hospitalization for gastrointestinal infection and weather conditions were collected from 1814 Brazilian cities during the 2000-2015 hot seasons. A time-stratified case-crossover design was used to estimate the association. Stratified analyses were performed by region, sex, age-group, type of infection and early/late study period. RESULTS: For every 5 °C increase in mean daily temperature, the cumulative odds ratio (OR) of hospitalization over 0-9 days was 1.22 [95 % confidence interval (CI): 1.21, 1.23] at the national level, reaching its maximum in the south and its minimum in the north. The strength of association tended to decline across successive age-groups, with infants < 1 year most susceptible. The effect estimates were similar for men and women. Waterborne and foodborne infections were more associated with high temperature than the 'others' and 'idiopathic' groups. There was no substantial change in the association over the 16-year study period. DISCUSSION: Our findings indicate that exposure to high temperature is associated with increased risk of hospitalization for gastrointestinal infection in the hot season, with the strength varying by region, population subgroup and infection type. There was no evidence to indicate adaptation to heat over the study duration.

Loss of life expectancy from PM2.5 in Brazil: A national study from 2010 to 2018.

BACKGROUND: Long-term exposure to PM2.5 is proved to be linked with mortality. However, limited studies have estimated the PM2.5 related loss of life expectancy (LLE) and its changing trends. How much life expectancy would be improved if PM2.5 pollution is reduced to the new WHO air quality guideline (AQG) level is unclear. METHODS: Data on deaths from all-causes, cancer, cardiovascular and respiratory diseases were collected from 5,565 Brazilian municipalities during 2010-2018. A difference-in-differences approach with quasi-Poisson regression was applied to examine the PM2.5-years of life lost (YLL) associations and PM2.5 associated LLE. RESULTS: The annual PM2.5 concentration in each municipality from 2010 to 2018 was 7.7 µg/m3 in Brazil. Nationally, with each 10 µg/m3 increase in five-year-average (current and previous four years) concentrations of PM2.5, the relative risks (RRs) were 1.18 (95% CI: 1.15-1.21) for YLL from all-causes, 1.22 (1.16-1.28) from cancer, 1.12 (1.08-1.17) from cardiovascular and 1.17 (1.10-1.25) from respiratory diseases. Life expectancy could be improved by 1.09 (95% CI: 0.92-1.25) years by limiting PM2.5 concentration to the national lowest level (2.9 µg/m3), specifically, 0.20 (0.15-0.24) years for cancer, 0.16 (0.11-0.22) years for cardiovascular and 0.09 (0.05-0.13) years for respiratory diseases, with significant disparities across regions and municipalities. Life expectancy would be improved by 0.78 (0.66-0.90) years by setting the new WHO AQG PM2.5 concentration level of 5 µg/m3 as an acceptable threshold. CONCLUSIONS: Using nationwide death records in Brazil, we found that long-term exposure to PM2.5 was associated with reduced life expectancy from all-causes, cancer, cardiovascular and respiratory diseases with regional inequalities and different trends. PM2.5 pollution abatement to below the WHO AQG level would improve this loss of life expectancy in Brazil.

Associations between long-term exposure to PM2.5 and site-specific cancer mortality: A nationwide study in Brazil between 2010 and 2018.

Long-term exposure to PM2.5 has been linked to lung cancer incidence and mortality, but limited evidence existed for other cancers. This study aimed to assess the association between PM2.5 on cancer specific mortality. An ecological study based on the cancer mortality data collected from 5,565 Brazilian cities during 2010-2018 using a difference-in-differences approach with quasi-Poisson regression, was applied to examine PM2.5-cancer mortality associations. Globally gridded annual average surface PM2.5 concentration was extracted and linked with the residential municipality of participants in this study. Sex, age stratified and exposure-response estimations were also conducted. Totalling 1,768,668 adult cancer deaths records of about 208 million population living across 5,565 municipalities were included in this study. The average PM2.5 concentration was 7.63 µg/m3 (standard deviation 3.32) with range from 2.95 µg/m3 to 28.5 µg/m3. With each 10 µg/m3 increase in three-year-average (current year and previous two years) concentrations of PM2.5, the relative risks (RR) of cancer mortality were 1.16 (95% confidence interval [CI]: 1.11-1.20) for all-site cancers. The PM2.5 exposure was significantly associated with several cancer-specific mortalities including oral, nasopharynx, oesophagus, and stomach, colon rectum, liver, gallbladder, larynx, lung, bone, skin, female breast, cervix, prostate, brain and leukaemia. No safe level of PM2.5 exposure was observed in the exposure-response curve for all types of cancer. In conclusion, with nationwide cancer death records in Brazil, we found that long-term exposure to ambient PM2.5 increased risks of mortality for many cancer types. Even low level PM2.5 concentrations had significant impacts on cancer mortality.

The impacts of long-term exposure to PM2.5 on cancer hospitalizations in Brazil.

BACKGROUND: Long-term exposure to PM2.5 has been linked to cancer incidence and mortality. However, it was unknown whether there was an association with cancer hospitalizations. METHODS: Data on cancer hospitalizations and annual PM2.5 concentrations were collected from 1,814 Brazilian cities during 2002-2015. A difference-in-difference approach with quasi-Poisson regression was applied to examine State-specific associations. The State-specific associations were pooled at a national level using random-effect meta-analyses. PM2.5 attributable burden were estimated for cancer hospitalization admissions, inpatient days and costs. RESULTS: We included 5,102,358 cancer hospitalizations (53.8% female). The mean annual concentration of PM2.5 was 7.0 µg/m3 (standard deviation: 4.0 µg/m3). With each 1 µg/m3 increase in two-year-average (current year and previous one year) concentrations of PM2.5, the relative risks (RR) of hospitalization were 1.04 (95% confidence interval [CI]: 1.02 to 1.07) for all-site cancers from 2002 to 2015 without sex and age differences. We estimated that 33.82% (95%CI: 14.97% to 47.84%) of total cancer hospitalizations could be attributed to PM2.5 exposure in Brazil during the study time. For every 100,000 population, 1,190 (95%CI: 527 to 1,836) cancer hospitalizations, 8,191 (95%CI: 3,627 to 11,587) inpatient days and US$788,775 (95%CI: $349,272 to $1,115,825) cost were attributable to PM2.5 exposure. CONCLUSIONS: Long-term exposure to ambient PM2.5 was positively associated with hospitalization for many cancer types in Brazil. Inpatient days and cost would be saved if the annual PM2.5 exposure was reduced.

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities.

BACKGROUND: Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. METHODS: In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. FINDINGS: We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV0-1) increased by 0·52% (95% CI 0·50-0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58-0·69), for upper-middle-income cities it was 0·50% (0·47-0·53), and for high-income cities it was 0·39% (0·33-0·46). The socioeconomic inequality in vulnerability to TV0-1 was especially evident for people aged 0-19 years (effect estimate 1·21% [1·11-1·31] for lower-middle income vs 0·52% [0·41-0·63] for high income) and people aged 60 years or older (0·60% [0·50-0·70] vs 0·43% [0·31-0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46-1·78] vs 0·56% [0·30-0·82]), respiratory diseases (1·32% [1·20-1·44] vs 0·55% [0·37-0·74]), and endocrine diseases (1·21% [0·99-1·43] vs 0·32% [0·02-0·62]). INTERPRETATION: People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations. FUNDING: None.

Socioeconomic level and associations between heat exposure and all-cause and cause-specific hospitalization in 1,814 Brazilian cities: A nationwide case-crossover study.

BACKGROUND: Heat exposure, which will increase with global warming, has been linked to increased risk of a range of types of cause-specific hospitalizations. However, little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities. METHODS AND FINDINGS: We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000-2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat-hospitalization association. Then meta-analysis was used to synthesize city-specific estimates according to different socioeconomic quartiles or levels. We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8-55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank's classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%-5.7%, P < 0.001), 3.7% (3.3%-4.0%, P < 0.001), and 2.6% (1.7%-3.4%, P < 0.001) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0-19 years) (increased all-cause hospitalization risk with every 5°C increase [95% CI]: 9.9% [8.7%-11.1%], P < 0.001, in LMI cities versus 5.2% [4.1%-6.3%], P < 0.001, in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (increase in cause-specific hospitalization risk with every 5°C increase [95% CI]: 5.6% [-0.2% to 11.8%], P = 0.060, in LMI cities versus 0.5% [-2.1% to 3.1%], P = 0.717, in HI cities), asthma (3.7% [0.3%-7.1%], P = 0.031, versus -6.4% [-12.1% to -0.3%], P = 0.041), pneumonia (8.0% [5.6%-10.4%], P < 0.001, versus 3.8% [1.1%-6.5%], P = 0.005), renal diseases (9.6% [6.2%-13.1%], P < 0.001, versus 4.9% [1.8%-8.0%], P = 0.002), mental health conditions (17.2% [8.4%-26.8%], P < 0.001, versus 5.5% [-1.4% to 13.0%], P = 0.121), and neoplasms (3.1% [0.7%-5.5%], P = 0.011, versus -0.1% [-2.1% to 2.0%], P = 0.939). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). The main limitations were lack of data on personal exposure to temperature, and that our city-level analysis did not assess intra-city or individual-level socioeconomic disparities and could not exclude confounding effects of some unmeasured variables. CONCLUSIONS: Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate.

Trends in Hospital Admission Rates and Associated Direct Healthcare Costs in Brazil: A Nationwide Retrospective Study between 2000 and 2015.

BACKGROUND: In Brazil, the increase in non-fatal events presents a new, unprecedented challenge for the free and universally accessible public healthcare system (SUS), the size and nature of which has yet to be reliably quantified. We examined the change in all-cause and cause-specific SUS hospital admissions during 2000 to 2015. MATERIALS AND METHODS: Data on hospital admissions across 1,816 cities were collected from the Brazilian Unified Health System. The age-standardized rates of hospital admissions, the associated healthcare costs, and length of hospital stay were quantified. Stratum analyses were performed by age, sex, region, and cause-specific categories. RESULTS: Hospital admission rates decreased by 10.2‰ per decade to 54.2‰ in 2015. For admissions in 2015, healthcare costs per patient equaled US$353 (an increase of $23.5/year since 2000) with an average length of hospital stay of 5 days (a decline of 0.04 days/year since 2000). Circulatory diseases incurred the greatest financial costs. Children and the elderly were most susceptible, especially for pneumonia. Injury and poisoning were the primary reason for admission in adult males, whereas maternal and other female-specific conditions were the highest burden in females. The burden of hospital admission was highest in the south and lowest in the north and northeast. DISCUSSION: Although hospital admission rates and length of stay have decreased in Brazil since 2000, the decline has been offset by an increase in direct healthcare costs. Age-, sex-, and region-specific features of the disease burden should be factored into future plans for healthcare expenditure in Brazil.

Association between Heat Exposure and Hospitalization for Diabetes in Brazil during 2000-2015: A Nationwide Case-Crossover Study.

BACKGROUND: Exposure to excessive heat, which will continue to increase with climate change, is associated with increased morbidity due to a range of noncommunicable diseases (NCDs). Whether this is true for diabetes is unknown. OBJECTIVES: We aimed to quantify the relationship between heat exposure and risk of hospitalization due to diabetes in Brazil. METHODS: Data on hospitalizations and weather conditions were collected from 1,814 cities during the hot seasons from 2000 to 2015. A time-stratified case-crossover design was used to quantify the association between hospitalization for diabetes and heat exposure. Region-specific odds ratios (ORs) were used to calculate the attributable fractions (AFs). RESULTS: A total of 553,351 hospitalizations associated with diabetes were recorded during 2000-2015. Every 5°C increase in daily mean temperature was associated with 6% [OR=1.06; 95% confidence interval (CI): 1.04, 1.07] increase in hospitalization due to diabetes with lag 0-3 d. The association was greatest (OR=1.18; 95% CI: 1.13, 1.23) in those ≥80y of age, but did not vary by sex, and was generally consistent by region and type of diabetes. Assuming a causal association, we estimated that 7.3% (95% CI: 3.5, 10.9) of all hospitalizations due to diabetes in the hot season could be attributed to heat exposure during the study period. DISCUSSION: Short-term heat exposure may increase the burden of diabetes-related hospitalization, especially among the very elderly. As global temperatures continue to rise, this burden is likely to increase. https://doi.org/10.1289/EHP5688.

The association between heat exposure and hospitalization for undernutrition in Brazil during 2000-2015: A nationwide case-crossover study.

BACKGROUND: Global warming is predicted to indirectly result in more undernutrition by threatening crop production. Whether temperature rise could affect undernutrition directly is unknown. We aim to quantify the relationship between short-term heat exposure and risk of hospitalization due to undernutrition in Brazil. METHODS AND FINDINGS: We collected hospitalization and weather data for the hot season (the 4 adjacent hottest months for each city) from 1,814 Brazilian cities during 1 January 2000-31 December 2015. We used a time-stratified case-crossover design to quantify the association between heat exposure and hospitalization due to undernutrition. Region-specific odds ratios (ORs) were used to calculate the attributable fractions (AFs). A total of 238,320 hospitalizations for undernutrition were recorded during the 2000-2015 hot seasons. Every 1°C increase in daily mean temperature was associated with a 2.5% (OR 1.025, 95% CI 1.020-1.030, p < 0.001) increase in hospitalizations for undernutrition across lag 0-7 days. The association was greatest for individuals aged ≥80 years (OR 1.046, 95% CI 1.034-1.059, p < 0.001), 0-4 years (OR 1.039, 95% CI 1.024-1.055, p < 0.001), and 5-19 years (OR 1.042, 95% CI 1.015-1.069, p = 0.002). Assuming a causal relationship, we estimate that 15.6% of undernutrition hospitalizations could be attributed to heat exposure during the study period. The AF grew from 14.1% to 17.5% with a 1.1°C increase in mean temperature from 2000 to 2015. The main limitations of this study are misclassification of different types of undernutrition, lack of individual temperature exposure data, and being unable to adjust for relative humidity. CONCLUSIONS: Our study suggests that global warming might directly increase undernutrition morbidity, by a route other than by threatening food security. This short-term effect is increasingly important with global warming. Global strategies addressing the syndemic of climate change and undernutrition should focus not only on food systems, but also on the prevention of heat exposure.

Ambient Particulate Air Pollution and Daily Mortality in 652 Cities.

BACKGROUND: The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS: We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 µm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 µm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived. RESULTS: On average, an increase of 10 µg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS: Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

The association between heatwaves and risk of hospitalization in Brazil: A nationwide time series study between 2000 and 2015.

BACKGROUND: To our knowledge, no study has assessed the association between heatwaves and risk of hospitalization and how it may change over time in Brazil. We quantified the heatwave-hospitalization association in Brazil during 2000-2015. METHODS AND FINDINGS: Daily data on hospitalization and temperature were collected from 1,814 cities (>78% of the national population) in the hottest five consecutive months during 2000-2015. Twelve types of heatwaves were defined with daily mean temperatures of ≥90th, 92.5th, 95th, or 97.5th percentiles of year-round temperature and durations of ≥2, 3, or 4 consecutive days. The city-specific association was estimated using a quasi-Poisson regression with constrained distributed lag model and then pooled at the national level using random-effect meta-analysis. Stratified analyses were performed by five regions, sex, 10 age groups, and nine cause categories. The temporal change in the heatwave-hospitalization association was assessed using a time-varying constrained distributed lag model. Of the 58,400,682 hospitalizations (59% women), 24%, 34%, 21%, and 19% of cases were aged <20, 20-39, 40-59, and ≥60 years, respectively. The city-specific year-round daily mean temperatures were 23.5 ± 2.8 °C on average, varying from 26.8 ± 1.8 °C for the 90th percentile to 28.0 ± 1.6 °C for the 97.5th percentile. We observed that the risk of hospitalization was most pronounced for heatwaves characterized by high daily temperatures and long durations across Brazil, except for the minimal association in the north (the hottest region). After controlling for temperature, the association remained for severe heatwaves in the south and southeast (cold regions). Children 0-9 years, the elderly ≥70 years, and admissions for perinatal conditions were most strongly associated with heatwaves. Over the study period, the strength of the heatwave-hospitalization association declined substantially in the south, while an apparent increase was observed in the southeast. The main limitations of this study included the lack of data on individual temperature exposure and measured air pollution. CONCLUSIONS: There are geographic, demographic, cause-specific, and temporal variations in the heatwave-hospitalization associations across the Brazilian population. Considering the projected increase in frequency, duration, and intensity of heatwaves, future strategies should be developed, such as building early warning systems, to reduce the health risk associated with heatwaves in Brazil.

Temperature variability and hospitalization for ischaemic heart disease in Brazil: A nationwide case-crossover study during 2000-2015.

BACKGROUND: Previous studies have suggested a potential relationship between temperature variability (TV) and ischaemic heart disease (IHD) but the nature and strength differ between studies. We quantify the association between TV and risk of hospitalization for IHD across Brazilian regions and examine how the relationship varies across important population subgroups. METHODS: Data on hospitalization for IHD and meteorological parameters were collected from 1814 cities during 2000-2015. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific estimates were quantified using a time-stratified case-crossover approach, and then pooled at the national level using a random-effect meta-analysis. Stratified analyses were performed by region, sex and three age-groups. RESULTS: There were 2,864,904 IHD hospitalizations during 2000-2015. The estimate of TV effect was strongest on 0-1 days' exposure: odds ratio was 1.019 [95% confidence interval (CI): 1.013-1.025] per 5 °C increase in TV. The relationship was stronger in men [1.025 (95%CI: 1.017-1.033)] than in women [1.011 (95%CI: 1.002-1.019)] and in successively older age groups [1.034 (95%CI: 1.018-1.050)]. Regional differences existed, with the association only apparent in the most ageing parts of Brazil. CONCLUSIONS: Exposure to TV is associated with increased risk of hospitalization for IHD, particularly in men and in older age groups. Our findings add to the growing evidence regarding the potential impact of climatic factors on important health outcomes.

Assessment of Intraseasonal Variation in Hospitalization Associated With Heat Exposure in Brazil.

Importance: The onset of the hot season is known to be adversely associated with a range of health outcomes. However, little is known about whether the association is constant over the course of the hot season. Objective: To quantify the change in the association between heat exposure and hospitalization from the early to late hot season in the Brazilian population. Design, Setting, and Participants: This time-stratified case-crossover study used daily data on hospitalization and weather conditions during the 2000 to 2015 hot seasons in 1814 Brazilian cities. There were 49 145 997 admissions during the study period. Data analysis was conducted between May 12, 2018, and July 2, 2018. Exposures: Increase in daily mean temperature. Main Outcomes and Measures: Daily hospitalizations were recorded. Conditional quasi-Poisson regression with time-varying constrained distributed lag model was used to examine the city-specific association between heat and hospitalization in the early or late hot season. City-specific estimates were then pooled at the national level using random-effect meta-analysis. Stratified analyses were conducted by 5 regions, sex, 10 age groups, and 7 cause-specific categories. Results: Of the 49 145 997 admissions (59% women), the median (interquartile range) age was 33.3 (19.8-55.7) years. At the national level, the risk of hospitalization increased by 4.6% (95% CI, 4.3%-4.9%) and 2.3% (95% CI, 1.9%-2.6%) for every 5°C increase in daily mean temperature in the early and late hot season, respectively. Exposure to early heat was associated with greater risk of hospitalization for residents in the northeast (6.4%; 95% CI, 5.5%-7.3%) and central west (7.1%; 95% CI, 6.1%-8.2%) compared with other regions. Children aged 0 to 9 years and elderly individuals (aged ≥80 years) were most susceptible. Admissions due to endocrine, nutritional, and metabolic diseases were most strongly associated with heat exposure. There was an attenuation in the heat-associated risk of hospitalization from the early to late hot season for all subgroups except young children and patients with hospitalization caused by respiratory illness. Conclusions and Relevance: In this study, the association between heat exposure and hospitalization attenuated temporally for most of the Brazilian population. Preventive strategies to mitigate the association of high temperature with population health should focus in particular on the first few days of heat exposure.

Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015.

BACKGROUND: Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time. OBJECTIVES: This study sought to quantify the geographic, demographic and temporal variations in the heat­hospitalization association in Brazil from 2000­2015. METHODS: Data on hospitalization and meteorological conditions were collected from 1,814 cities during the 2000­2015 hot seasons. Quasi-Poisson regression with constrained lag model was applied to examine city-specific estimates, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, 10 age groups, and 11 cause categories. Meta-regression was used to examine the temporal change in estimates of heat effect from 2000 to 2015. RESULTS: For every 5°C increase in daily mean temperature during the 2000­2015 hot seasons, the estimated risk of hospitalization over lag 0-7 d rose by 4.0% [95% confidence interval (CI): 3.7%, 4.3%] nationwide. Estimated 6.2% [95% empirical CI (eCI): 3.3%, 9.1%] of hospitalizations were attributable to heat exposure, equating to 132 cases (95% eCI: 69%, 192%) per 100,000 residents. The attributable rate was greatest in children [Formula: see text] and was highest for hospitalizations due to infectious and parasitic diseases. Women of reproductive age and those [Formula: see text] had higher heat burden than men. The attributable burden was greatest for cities in the central west and the inland of the northeast; lowest in the north and eastern coast. Over the 16-y period, the estimated heat effects declined insignificantly at the national level. CONCLUSIONS: In Brazil's hot seasons, 6% of hospitalizations were estimated to be attributed to heat exposure. As there was no evidence indicating that thermal adaptation had occurred at the national level, the burden of hospitalization associated with heat exposure in Brazil is likely to increase in the context of global warming. https://doi.org/10.1289/EHP3889.

Temperature variability and hospitalization for cardiac arrhythmia in Brazil: A nationwide case-crossover study during 2000-2015.

BACKGROUND: There is growing recognition of a potential role for environmental and climatic factors in influencing cardiovascular risk. It has been speculated that temperature variability (TV) is a risk factor for cardiac arrhythmia but evidence is limited. OBJECTIVE: To quantify the geographic and demographic variations in the association between TV and hospitalization for cardiac arrhythmia in Brazil during 2000-2015. METHODS: Data on hospitalization for arrhythmia and weather conditions were collected from 1,814 cities. TV was calculated as the standard deviation of daily maximum and minimum temperatures during exposure days. A time-stratified case-crossover approach was applied to examine the city-specific association between TV and hospitalization for arrhythmia. City-specific estimates were pooled at the national and regional levels using a random-effect meta-analysis. Stratified analyses were conducted by sex, three age-groups (0-64, 65-74 and ≥75 years), and three arrhythmia subtypes (paroxysmal tachycardia, atrial fibrillation and flutter, and other arrhythmias). RESULTS: There were 447,667 arrhythmia-related hospitalizations during 2000-2015. The odds ratio of hospitalization per 1 °C increase in TV peaked on 0-1 days' exposure [1.012 (95% confidence interval: 1.010-1.015)]. There were no substantial differences in effect estimates of TV0-1 by region, age or sex, except for the non-significant association observed in the north. However, women were more affected by prolonged TV exposure than men. For the three arrhythmias subtypes, only paroxysmal tachycardia and other arrhythmias were sensitive to TV. Assuming a causal relationship, 35,813 (95%CI: 18,302-51,665) cases were attributable to TV0-1 in Brazil during 2000-2015, accounting for 8.0% (95%CI: 4.1-11.5%) of hospitalizations for cardiac arrhythmia. CONCLUSIONS: At a population-level exposure to TV was associated with increased risk of arrhythmia-related hospitalization in Brazil, with the relationship equally distributed across most residents but varied by arrhythmia subtypes. Our findings add to the accumulating evidence-base that climatic factors can influence cardiovascular outcomes in populations.

Spatiotemporal and demographic variation in the association between temperature variability and hospitalizations in Brazil during 2000-2015: A nationwide time-series study.

BACKGROUND: Extreme temperature events are known to be adversely associated with a range of health outcomes, but little is known about the effect of less extreme, but more frequent fluctuation in temperature. We examined the spatiotemporal and demographic variation in the effect of temperature variability (TV) on nationwide hospitalizations in Brazil during 2000-2015. METHODS: Data on daily hospitalizations and weather variables were collected from 1814 cities, comprising 78.4% of Brazilian population. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific TV effect was estimated using a quasi-Poisson regression model, and then pooled at the national and regional level using meta-analysis. Stratified analyses were performed by sex, 10 age-groups, and 11 cause categories. Meta-regression was applied to city-year-specific estimates to examine the temporal change. RESULTS: The estimate of TV effect peaked on 0-1 days' exposure, contributing to 3.5% [95% confidence interval (CI): 3.1-3.8%] of hospitalizations nationwide, equalling 221 (95%CI: 200-242) cases per 100,000 population annually. The effect estimate varied across 11 cause categories, which was strongest for respiratory admissions. Males, particular those 10-49 year old were more affected than females but there was no sex difference for the attributable hospitalization rate. The attributable rate for the under-fives was twice as high as for the elderly, and five times higher than in adults. The majority of the most affected cities were located in the central west and the inland of northeast. The risk of hospitalization related to TV showed a significant increase over the 16-year period at the national level. CONCLUSIONS: In Brazil, the effect of TV on hospitalization is acute, and varies by spatial, sex, age, and cause category. Given there is no evidence regarding TV adaptation, hospitalization burden associated with TV is likely to further increase and warrants consideration when developing future public health policies in the context of climate change.

The impact of climate on Leptospirosis in São Paulo, Brazil.

In this work, we correlate the daily number of human leptospirosis cases with several climatic factors. We used a negative binomial model that considers hospital daily admissions due to leptospirosis as the dependent variable, and the climatic variables of daily precipitation pattern, and maximum and minimum temperature as independent variables. We calculated the monthly leptospirosis admission probabilities from the precipitation and maximum temperature variables. The month of February showed the highest probability, although values were also high during the spring months. The month of February also showed the highest number of hospital admissions. Another interesting result is that, for every 20 mm precipitation, there was an average increase of 31.5% in hospital admissions. Additionally, the relative risk of leptospirosis varied from 1.1 to 2.0 when the precipitation varied from 20 to 140 mm.