Examinando por Autor "Nair, Sanjeev"

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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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    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
    (2017-12) Lear, Scott A.; Hu, Weihong; Rangarajan, Sumathy; Gasevic, Danijela; Leong, Darryl P.; Iqbal, Romaina; Casanova, Amparo; Swaminathan, Sumathi; Anjana, Ranjit Mohan; Kumar, Rajesh; Rosengren, Annika; Wei, Li; Yang, Wang; Chuangshi, Wang; Huaxing, Liu; Nair, Sanjeev; Diaz, Rafael; Swidon, Hany; Gupta, Rajeev; Mohammadifard, Noushin; Lopez-Jaramillo, Patricio; Oguz, Aytekin; Zatonska, Katarzyna; Seron, Pamela; Avezum, Alvaro; Poirier, Paul P.; Teo, Koon; Yusuf, Salim
    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. Findings: Between Jan 1, 2003, and Dec 31, 2010, 168 916 participants were enrolled, of whom 141 945 completed the IPAQ. Analyses were limited to the 130 843 participants without pre-existing CVD. Compared with low physical activity (<600 metabolic equivalents [MET] × minutes per week or <150 minutes per week of moderate intensity physical activity), moderate (600–3000 MET × minutes or 150–750 minutes per week) and high physical activity (>3000 MET × minutes or >750 minutes per week) were associated with graded reduction in mortality (hazard ratio 0·80, 95% CI 0·74–0·87 and 0·65, 0·60–0·71; p<0·0001 for trend), and major CVD (0·86, 0·78–0·93; p<0·001 for trend). Higher physical activity was associated with lower risk of CVD and mortality in high-income, middle-income, and low-income countries. The adjusted population attributable fraction for not meeting the physical activity guidelines was 8·0% for mortality and 4·6% for major CVD, and for not meeting high physical activity was 13·0% for mortality and 9·5% for major CVD. Both recreational and non-recreational physical activity were associated with benefits. Interpretation: Recreational and non-recreational physical activity was associated with a lower risk of mortality and CVD events in individuals from low-income, middle-income, and high-income countries. Increasing physical activity is a simple, widely applicable, low cost global strategy that could reduce deaths and CVD in middle age. Funding: Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Ontario SPOR Support Unit, Ontario Ministry of Health and Long-Term Care, AstraZeneca, Sanofi-Aventis, Boehringer Ingelheim, Servier, GSK, Novartis, King Pharma, and national and local organisations in participating countries that are listed at the end of the Article.
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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.
  • Publicación
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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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    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.