Examinando por Autor "Mohan, Indu"

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    Association of estimated sleep duration and naps with mortality and cardiovascular events
    (European Society of Cardiology, 2019-05-21) Wang, Chuangshi; Bangdiwala, Shrikant I.; Rangarajan, Sumathy; Lear, Scott A.; AlHabib, Khalid F.; Mohan, Viswanathan; Koon, Teo; Poirier, Paul; Tse, Lap Ah; Liu, Zhiguang; Rosengren, Annika; Kumar, Rajesh; Lopez-Jaramillo, Patricio; Yusoff, Khalid; Monsef, Nahed; Krishnapillai, Vijayakumar; Ismail, Noorhassim; Seron, Pamela; Dans, Antonio; Kruger, Lanthé; Yeates, Karen; Leach, Lloyd; Yusuf, Rita; Orlandini, Andres; Wolyniec, Maria; Bahonar, Ahmad; Mohan, Indu; Khatib, Rasha; Temizhan, Ahmet; Li, Wei; Yusuf, Salim; On behalf of the Prospective Urban Rural Epidemiology (PURE) study investigators; Everest
    Aims To investigate the association of estimated total daily sleep duration and daytime nap duration with deaths and major cardiovascular events. Methods and results We estimated the durations of total daily sleep and daytime naps based on the amount of time in bed and self-reported napping time and examined the associations between them and the composite outcome of deaths and major cardiovascular events in 116 632 participants from seven regions. After a median follow-up of 7.8 years, we recorded 4381 deaths and 4365 major cardiovascular events. It showed both shorter (≤6 h/day) and longer (>8 h/day) estimated total sleep durations were associated with an increased risk of the composite outcome when adjusted for age and sex. After adjustment for demographic characteristics, lifestyle behaviours and health status, a J-shaped association was observed. Compared with sleeping 6–8 h/day, those who slept ≤6 h/day had a non-significant trend for increased risk of the composite outcome [hazard ratio (HR), 1.09; 95% confidence interval, 0.99–1.20]. As estimated sleep duration increased, we also noticed a significant trend for a greater risk of the composite outcome [HR of 1.05 (0.99–1.12), 1.17 (1.09–1.25), and 1.41 (1.30–1.53) for 8–9 h/day, 9–10 h/day, and >10 h/day, Ptrend < 0.0001, respectively]. The results were similar for each of all-cause mortality and major cardiovascular events. Daytime nap duration was associated with an increased risk of the composite events in those with over 6 h of nocturnal sleep duration, but not in shorter nocturnal sleepers (≤6 h). Conclusion Estimated total sleep duration of 6–8 h per day is associated with the lowest risk of deaths and major cardiovascular events. Daytime napping is associated with increased risks of major cardiovascular events and deaths in those with >6 h of nighttime sleep but not in those sleeping ≤6 h/night.
  • Publicación
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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.