Examinando por Autor "Brauer, Michael"

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    Associations of outdoor fine particulate air pollution and cardiovascular disease in 157 436 individuals from 21 high-income, middle-income, and low-income countries (PURE)
    (Elsevier, 2020-06-01) Hystad, Perry; Larkin, Andrew; Rangarajan, Sumathy; AlHabib, Khalid F; Avezum, Alvaro; Tumerdem Calik, Kevser Burcu; Chifamba, Jephat; Dans, Antonio; Diaz, Rafael; Du Plessis, Johan L; Gupta, Rajeev; Iqbal, Romaina; Khatib, Rasha; Kelishadi, Roya; Lanas, Fernando; Liu, Zhiguang; Lopez-Jaramillo, Patricio; Nair, Sanjeev; Poirier, Paul; Rahman, Omar; Rosengren, Annika; Swidan, Hany; Tse, Lap Ah; Wei, Li; Wielgosz, Andreas; Yeates, Karen; Yusoff, Khalid; Zatoński, Tomasz; Burnett, Rick; Yusuf, Salim; Brauer, Michael; Everest
    Background: Most studies of long-term exposure to outdoor fine particulate matter (PM2·5) and cardiovascular disease are from high-income countries with relatively low PM2·5 concentrations. It is unclear whether risks are similar in low-income and middle-income countries (LMICs) and how outdoor PM2·5 contributes to the global burden of cardiovascular disease. In our analysis of the Prospective Urban and Rural Epidemiology (PURE) study, we aimed to investigate the association between long-term exposure to PM2·5 concentrations and cardiovascular disease in a large cohort of adults from 21 high-income, middle-income, and low-income countries. Methods: In this multinational, prospective cohort study, we studied 157 436 adults aged 35-70 years who were enrolled in the PURE study in countries with ambient PM2·5 estimates, for whom follow-up data were available. Cox proportional hazard frailty models were used to estimate the associations between long-term mean community outdoor PM2·5 concentrations and cardiovascular disease events (fatal and non-fatal), cardiovascular disease mortality, and other non-accidental mortality. Findings: Between Jan 1, 2003, and July 14, 2018, 157 436 adults from 747 communities in 21 high-income, middle-income, and low-income countries were enrolled and followed up, of whom 140 020 participants resided in LMICs. During a median follow-up period of 9·3 years (IQR 7·8-10·8; corresponding to 1·4 million person-years), we documented 9996 non-accidental deaths, of which 3219 were attributed to cardiovascular disease. 9152 (5·8%) of 157 436 participants had cardiovascular disease events (fatal and non-fatal incident cardiovascular disease), including 4083 myocardial infarctions and 4139 strokes. Mean 3-year PM2·5 at cohort baseline was 47·5 μg/m3 (range 6-140). In models adjusted for individual, household, and geographical factors, a 10 μg/m3 increase in PM2·5 was associated with increased risk for cardiovascular disease events (hazard ratio 1·05 [95% CI 1·03-1·07]), myocardial infarction (1·03 [1·00-1·05]), stroke (1·07 [1·04-1·10]), and cardiovascular disease mortality (1·03 [1·00-1·05]). Results were similar for LMICs and communities with high PM2·5 concentrations (>35 μg/m3). The population attributable fraction for PM2·5 in the PURE cohort was 13·9% (95% CI 8·8-18·6) for cardiovascular disease events, 8·4% (0·0-15·4) for myocardial infarction, 19·6% (13·0-25·8) for stroke, and 8·3% (0·0-15·2) for cardiovascular disease mortality. We identified no consistent associations between PM2·5 and risk for non-cardiovascular disease deaths. Interpretation: Long-term outdoor PM2·5 concentrations were associated with increased risks of cardiovascular disease in adults aged 35-70 years. Air pollution is an important global risk factor for cardiovascular disease and a need exists to reduce air pollution concentrations, especially in LMICs, where air pollution levels are highest. Funding: Full funding sources are listed at the end of the paper (see Acknowledgments).
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    Household and personal air pollution exposure measurements from 120 communities in eight countries
    (The Lancet Planetary Health, 2020-10-01) Shupler, Matthew; Hystad, Perry; Birch, Aaron; Miller-Lionberg, Daniel; Jeronimo, Matthew; Arku, Raphael E.; Chu, Yen Li; Mushtaha, Maha; Heenan, Laura; Rangarajan, Sumathy; Seron, Pamela; Lanas, Fernando; Cazor, Fairuz; Lopez-Jaramillo, Patricio; Camacho López, Paul Anthony; Perez, Maritza; Yeates, Karen; West, Nicola; Ncube, Tatenda; Ncube, Brian; Chifamba, Jephat; Yusuf, Rita; Khan, Afreen; Hu, Bo; Liu, Xiaoyun; Wei, Li; Tse, Lap Ah; Mohan, Deepa; Kumar, Parthiban; Gupta, Rajeev; Mohan, Indu; Jayachitra, K. G.; Mony, Prem K.; Rammohan, Kamala; Nair, Sanjeev; Lakshmi, P. V. M.; Sagar, Vivek; Khawaja, Rehman; Iqbal, Romaina; Kazmi, Khawar; Yusuf, Salim; Brauer, Michael; thePURE-AIR study; Everest
    Background Approximately 2·8 billion people are exposed to household air pollution from cooking with polluting fuels. Few monitoring studies have systematically measured health-damaging air pollutant (ie, fine particulate matter [PM2·5] and black carbon) concentrations from a wide range of cooking fuels across diverse populations. This multinational study aimed to assess the magnitude of kitchen concentrations and personal exposures to PM2·5 and black carbon in rural communities with a wide range of cooking environments. Methods As part of the Prospective Urban and Rural Epidemiological (PURE) cohort, the PURE-AIR study was done in 120 rural communities in eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Data were collected from 2541 households and from 998 individuals (442 men and 556 women). Gravimetric (or filter-based) 48 h kitchen and personal PM2·5 measurements were collected. Light absorbance (10− ⁵m− ¹) of the PM2·5 filters, a proxy for black carbon concentrations, was calculated via an image-based reflectance method. Surveys of household characteristics and cooking patterns were collected before and after the 48 h monitoring period. Findings Monitoring of household air pollution for the PURE-AIR study was done from June, 2017, to September, 2019. A mean PM2·5 kitchen concentration gradient emerged across primary cooking fuels: gas (45 μg/m³ [95% CI 43–48]), electricity (53 μg/m³ [47–60]), coal (68 μg/m³ [61–77]), charcoal (92 μg/m³ [58–146]), agricultural or crop waste (106 μg/m³ [91–125]), wood (109 μg/m³ [102–118]), animal dung (224 μg/m³ [197–254]), and shrubs or grass (276 μg/m³ [223–342]). Among households cooking primarily with wood, average PM2·5 concentrations varied ten-fold (range: 40–380 μg/m³). Fuel stacking was prevalent (981 [39%] of 2541 households); using wood as a primary cooking fuel with clean secondary cooking fuels (eg, gas) was associated with 50% lower PM2·5 and black carbon concentrations than using only wood as a primary cooking fuel. Similar average PM2·5 personal exposures between women (67 μg/m³ [95% CI 62–72]) and men (62 [58–67]) were observed. Nearly equivalent average personal exposure to kitchen exposure ratios were observed for PM2·5 (0·79 [95% 0·71–0·88] for men and 0·82 [0·74–0·91] for women) and black carbon (0·64 [0·45–0·92] for men and 0·68 [0·46–1·02] for women). Interpretation Using clean primary fuels substantially lowers kitchen PM2·5 concentrations. Importantly, average kitchen and personal PM2·5 measurements for all primary fuel types exceeded WHO’s Interim Target-1 (35 μg/m³ annual average), highlighting the need for comprehensive pollution mitigation strategies.
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    Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study
    (IOP Publishing Ltd, 2019-07-29) Shupler, Matthew; Hystad, Perry; Gustafson, Paul; Rangarajan, Sumathy; Mushtaha, Maha; Jayachtria, K.G.; Mony, Prem K.; Mohan, Deepa; Kumar, Parthiban; Lakshmi, P.V.M.; Sagar, Vivek; Gupta, Rajeev; Mohan, Indu; Nair, Sanjeev; Prasad Varma, Ravi; Li, Wei; Hu, Bo; You, Kai; Ncube, Tatenda; Ncube, Brian; Chifamba, Jephat; West, Nicola; Yeates, Karen; Iqbal, Romaina; Khawaja, Rehman; Yusuf, Rita; Khan, Afreen; Seron, Pamela; Lanas, Fernando; Lopez-Jaramillo, Patricio; Camacho López, Paul Anthony; Puoane, Thandi; Yusuf, Salim; Brauer, Michael; The Prospective Urban Rural Epidemiology (PURE) study; Everest
    Introduction. Switching from polluting (e.g. wood, crop waste, coal) to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions. While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods. We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study. We assessed household-level primary cooking fuel switching during a median of 10 years of follow up (∼2005–2015). We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households (12 369) reported changing their primary cooking fuels between baseline and follow up surveys. Of these, 61% (7582) switched from polluting (wood, dung, agricultural waste, charcoal, coal, kerosene) to clean (gas, electricity) fuels, 26% (3109) switched between different polluting fuels, 10% (1164) switched from clean to polluting fuels and 3% (522) switched between different clean fuels. Among the 17 830 households using polluting cooking fuels at baseline, household-level factors (e.g. larger household size, higher wealth, higher education level) were most strongly associated with switching from polluting to clean fuels in India; in all other countries, community-level factors (e.g. larger population density in 2010, larger increase in population density between 2005 and 2015) were the strongest predictors of polluting-to-clean fuel switching. Conclusions. The importance of community and sub-national factors relative to household characteristics in determining polluting-to-clean fuel switching varied dramatically across the nine countries examined. This highlights the potential importance of national and other contextual factors in shaping large-scale clean cooking transitions among rural communities in low- and middle-income countries.
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    Long-term exposure to outdoor and household air pollution and blood pressure in the Prospective Urban and Rural Epidemiological (PURE) study
    (Elsevier, 2020-03-24) Arku, Raphael E.; Brauer, Michael; Ahmed, Suad H.; AlHabib, Khalid F.; Avezum, Álvaro; Bo, Jian; Choudhury, Tarzia; Dans, Antonio; Gupta, Rajeev; Iqbal, Romaina; Ismail, Noorhassim; Kelishadi, Roya; Khatib, Rasha; Koon, Teo; Kumar, Rajesh; Lanas, Fernando; Lear, Scott A.; Wei, Li; Lopez-Jaramillo, Patricio; Mohan, Viswanathan; Poirier, Paul; Puoane, Thandi; Rangarajan, Sumathy; Rosengren, Annika; Soman, Biju; Caklili, Ozge Telci; Yang, Shunyun; Yeates, Karen; Yin, Lu; Yusoff, Khalid; Zatoński, Tomasz; Yusuf, Salim; Hystad, Perry; Everest
    Exposure to air pollution has been linked to elevated blood pressure (BP) and hypertension, but most research has focused on short-term (hours, days, or months) exposures at relatively low concentrations. We examined the associations between long-term (3-year average) concentrations of outdoor PM2.5 and household air pollution (HAP) from cooking with solid fuels with BP and hypertension in the Prospective Urban and Rural Epidemiology (PURE) study. Outdoor PM2.5 exposures were estimated at year of enrollment for 137,809 adults aged 35–70 years from 640 urban and rural communities in 21 countries using satellite and ground-based methods. Primary use of solid fuel for cooking was used as an indicator of HAP exposure, with analyses restricted to rural participants (n = 43,313) in 27 study centers in 10 countries. BP was measured following a standardized procedure and associations with air pollution examined with mixed-effect regression models, after adjustment for a comprehensive set of potential confounding factors. Baseline outdoor PM2.5 exposure ranged from 3 to 97 μg/m3 across study communities and was associated with an increased odds ratio (OR) of 1.04 (95% CI: 1.01, 1.07) for hypertension, per 10 μg/m3 increase in concentration. This association demonstrated non-linearity and was strongest for the fourth (PM2.5 > 62 μg/m3) compared to the first (PM2.5 < 14 μg/m3) quartiles (OR = 1.36, 95% CI: 1.10, 1.69). Similar non-linear patterns were observed for systolic BP (β = 2.15 mmHg, 95% CI: −0.59, 4.89) and diastolic BP (β = 1.35, 95% CI: −0.20, 2.89), while there was no overall increase in ORs across the full exposure distribution. Individuals who used solid fuels for cooking had lower BP measures compared to clean fuel users (e.g. 34% of solid fuels users compared to 42% of clean fuel users had hypertension), and even in fully adjusted models had slightly decreased odds of hypertension (OR = 0.93; 95% CI: 0.88, 0.99) and reductions in systolic (−0.51 mmHg; 95% CI: −0.99, −0.03) and diastolic (−0.46 mmHg; 95% CI: −0.75, −0.18) BP. In this large international multi-center study, chronic exposures to outdoor PM2.5 was associated with increased BP and hypertension while there were small inverse associations with HAP.
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    Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE)
    (Elsevier, 2019-09-03) Yusuf, Salim; Joseph, Philip; Rangarajan, Sumathy; Islam, Shofiqul; Mente, Andrew; Hystad, Perry; Brauer, Michael; Raman Kutty, Vellappillil; Gupta, Rajeev; Wielgosz, Andreas; AlHabib, Khalid F.; Dans, Antonio; Lopez-Jaramillo, Patricio; Avezum, Alvaro; Lanas, Fernando; Oguz, Aytekin; Kruger, Iolanthe M.; Diaz, Rafael; Yusoff, Khalid; Mony, Prem; Chifamba, Jephat; Yeates, Karen; Kelishadi, Roya; Yusufali, Afzalhussein; Khatib, Rasha; Rahman, Omar; Zatonska, Katarzyna; Iqbal, Romaina; Wei, Li; Bo, Hu; Rosengren, Annika; Kaur, Manmeet; Mohan, Viswanathan; Lear, Scott A.; Teo, Koon K.; Leong, Darryl; O'Donnell, Martin; McKee, Martin; Dagenais, Gilles; Everest
    Background Global estimates of the effect of common modifiable risk factors on cardiovascular disease and mortality are largely based on data from separate studies, using different methodologies. The Prospective Urban Rural Epidemiology (PURE) study overcomes these limitations by using similar methods to prospectively measure the effect of modifiable risk factors on cardiovascular disease and mortality across 21 countries (spanning five continents) grouped by different economic levels. Methods In this multinational, prospective cohort study, we examined associations for 14 potentially modifiable risk factors with mortality and cardiovascular disease in 155 722 participants without a prior history of cardiovascular disease from 21 high-income, middle-income, or low-income countries (HICs, MICs, or LICs). The primary outcomes for this paper were composites of cardiovascular disease events (defined as cardiovascular death, myocardial infarction, stroke, and heart failure) and mortality. We describe the prevalence, hazard ratios (HRs), and population-attributable fractions (PAFs) for cardiovascular disease and mortality associated with a cluster of behavioural factors (ie, tobacco use, alcohol, diet, physical activity, and sodium intake), metabolic factors (ie, lipids, blood pressure, diabetes, obesity), socioeconomic and psychosocial factors (ie, education, symptoms of depression), grip strength, and household and ambient pollution. Associations between risk factors and the outcomes were established using multivariable Cox frailty models and using PAFs for the entire cohort, and also by countries grouped by income level. Associations are presented as HRs and PAFs with 95% CIs. Findings Between Jan 6, 2005, and Dec 4, 2016, 155 722 participants were enrolled and followed up for measurement of risk factors. 17 249 (11·1%) participants were from HICs, 102 680 (65·9%) were from MICs, and 35 793 (23·0%) from LICs. Approximately 70% of cardiovascular disease cases and deaths in the overall study population were attributed to modifiable risk factors. Metabolic factors were the predominant risk factors for cardiovascular disease (41·2% of the PAF), with hypertension being the largest (22·3% of the PAF). As a cluster, behavioural risk factors contributed most to deaths (26·3% of the PAF), although the single largest risk factor was a low education level (12·5% of the PAF). Ambient air pollution was associated with 13·9% of the PAF for cardiovascular disease, although different statistical methods were used for this analysis. In MICs and LICs, household air pollution, poor diet, low education, and low grip strength had stronger effects on cardiovascular disease or mortality than in HICs. Interpretation Most cardiovascular disease cases and deaths can be attributed to a small number of common, modifiable risk factors. While some factors have extensive global effects (eg, hypertension and education), others (eg, household air pollution and poor diet) vary by a country's economic level. Health policies should focus on risk factors that have the greatest effects on averting cardiovascular disease and death globally, with additional emphasis on risk factors of greatest importance in specific groups of countries. Funding Full funding sources are listed at the end of the paper (see Acknowledgments).
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    Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study
    (Elsevier, 2022-01-15) Shupler, Matthew; Hystad, Perry; Birch, Aaron; Li Chu, Yen; Jeronimo, Matthew; Miller-Lionberg, Daniel; Gustafson, Paul; Rangarajan, Sumathy; Mustaha, Maha; Heenan, Laura; Seron, Pamela; Lanas, Fernando; Cazor, Fairuz; Oliveros, Maria Jose; Lopez-Jaramillo, Patricio; Camacho López, Paul Anthony; Otero, Johanna; Perez, Maritza; Yeates, Karen; West, Nicola; Ncube, Tatenda; Ncube, Brian; Chifamba, Jephat; Yusuf, Rita; Khan, Afreen; Liu, Zhiguang; Wu, Shutong; Wei, Li; Tse, Lap Ah; Mohan, Deepa; Kuma, Parthiban; Gupta, Rajeev; Mohan, Indu; Jayachitra, K.G.; Mony, Prem; Rammohan, Kamala; Nair, Sanjeev; Lakshmi, P.V.M.; Sagar, Vivek; Khawaja, Rehman; Iqbal, Romaina; Kazmi, Khawar; Yusuf, Salim; Brauer, Michael; PURE-AIR study investigators; Masira
    Abstract Introduction Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM2.5 exposure models. Methods The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM2.5 kitchen concentrations (n = 2,365) and male and/or female PM2.5 exposure monitoring (n = 910) in a subset of households in Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania and Zimbabwe. PURE-AIR measurements were combined with survey data on cooking environment characteristics in hierarchical Bayesian log-linear regression models. Model performance was evaluated using leave-one-out cross validation. Predictive models were applied to survey data from the larger PURE cohort (22,480 households; 33,554 individuals) to quantitatively estimate PM2.5 exposures. Results The final models explained half (R2 = 54%) of the variation in kitchen PM2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R2 = 48%; RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM2.5 kitchen concentrations. Average national PM2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20 μg/m3 (Chile); 55 μg/m3 (China)) and 12-fold among households primarily cooking with wood (36 μg/m3 (Chile)); 427 μg/m3 (Pakistan)). Average PM2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile). Conclusion Using survey data to estimate PM2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.
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    Personal and household PM2.5 and black carbon exposure measures and respiratory symptoms in 8 low- and middle-income countries
    (2022-09-01) Wang, Ying; Shupler, Matthew; Birch, Aaron; Li-Chu, Yen; Jeronimo, Matthew; Rangarajan, Sumathy; Mustaha, Maha; Heenan, Laura; Seron, Pamela; Saavedra, Nicolas; Oliveros, Maria Jose; Lopez-Jaramillo, Patricio; Camacho-Lopez, Paul Antony; Otero, Johnna; Perez-Mayorga, Maritza; Yeates, Karen; West, Nicola; Ncube, Tatenda; Ncube, Brian; Chifamba, Jephat; Yusuf, Rita; Khan, Afreen; Liu, Zhiguang; Cheng, Xiaoru; Wei, Li; Tse, L.A.; Mohan, Deepa; Kumar, Parthiban; Gupta, Rajeev; Mohan, Indu; Jayachitra, K.G.; Mony, Prem K.; Rammohan, Kamala; Nair, Sanjeev; Lakshmi, P.V.M.; Sagar, Vivek; Khawaja, Rehman; Iqbal, Romaina; Kazmi, Khawar; Yusuf, Salim; Brauer, Michael; Hystad, Perry; PURE-AIR study investigators; Masira
    Background Household air pollution (HAP) from cooking with solid fuels has been associated with adverse respiratory effects, but most studies use surveys of fuel use to define HAP exposure, rather than on actual air pollution exposure measurements. Objective To examine associations between household and personal fine particulate matter (PM2.5) and black carbon (BC) measures and respiratory symptoms. Methods As part of the Prospective Urban and Rural Epidemiology Air Pollution study, we analyzed 48-h household and personal PM2.5 and BC measurements for 870 individuals using different cooking fuels from 62 communities in 8 countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Self-reported respiratory symptoms were collected after monitoring. Associations between PM2.5 and BC exposures and respiratory symptoms were examined using logistic regression models, controlling for individual, household, and community covariates. Results The median (interquartile range) of household and personal PM2.5 was 73.5 (119.1) and 65.3 (91.5) μg/m3, and for household and personal BC was 3.4 (8.3) and 2.5 (4.9) x10−5 m−1, respectively. We observed associations between household PM2.5 and wheeze (OR: 1.25; 95%CI: 1.07, 1.46), cough (OR: 1.22; 95%CI: 1.06, 1.39), and sputum (OR: 1.26; 95%CI: 1.10, 1.44), as well as exposure to household BC and wheeze (OR: 1.20; 95%CI: 1.03, 1.39) and sputum (OR: 1.20; 95%CI: 1.05, 1.36), per IQR increase. We observed associations between personal PM2.5 and wheeze (OR: 1.23; 95%CI: 1.00, 1.50) and sputum (OR: 1.19; 95%CI: 1.00, 1.41). For household PM2.5 and BC, associations were generally stronger for females compared to males. Models using an indicator variable of solid versus clean fuels resulted in larger OR estimates with less precision. Conclusions We used measurements of household and personal air pollution for individuals using different cooking fuels and documented strong associations with respiratory symptoms.