Examinando por Autor "Mushtaha, Maha"

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  • 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
    Acceso abierto
    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.
  • Publicación
    Acceso abierto
    Variations in the financial impact of the COVID-19 pandemic across 5 continents. A cross-sectional, individual level analysis
    (ScienceDirect, 2022-01-28) Khetan, Aditya K.; Yusuf, Salim; Lopez-Jaramillo, Patricio; Szuba, Andrzej; Orlandini, Andres; Mat-Nasir, Nafiza; Oguz, Aytekin; Gupta, Rajeev; Avezum, Alvaro; Rosnah, Ismail; Poirier, Paul; Teo, Koon; Wielgosz, Andreas; Lear, Scott A.; Palileo-Villanueva, Lia M.; Seron, Pamela; Chifamba, Jephat; Rangarajan, Sumathy; Mushtaha, Maha; Mohan, Deepa; Yeates, Karen; McKee, Martin; Mony, Prem; Walli-Attaei, Marjan; Khansaheb, Hamda; Rosengren, Annika; AlHabib, Khalid F.; Kruger, Iolanthe M.; Paucar, María-Jose; Mirrakhimov, Erkin; Assembekov, Batyrbek; Leong, Darryl P.; Masira
    Background COVID-19 has caused profound socio-economic changes worldwide. However, internationally comparative data regarding the financial impact on individuals is sparse. Therefore, we conducted a survey of the financial impact of the pandemic on individuals, using an international cohort that has been well-characterized prior to the pandemic. Methods Between August 2020 and September 2021, we surveyed 24,506 community-dwelling participants from the Prospective Urban-Rural Epidemiology (PURE) study across high (HIC), upper middle (UMIC)-and lower middle (LMIC)-income countries. We collected information regarding the impact of the pandemic on their self-reported personal finances and sources of income. Findings Overall, 32.4% of participants had suffered an adverse financial impact, defined as job loss, inability to meet financial obligations or essential needs, or using savings to meet financial obligations. 8.4% of participants had lost a job (temporarily or permanently); 14.6% of participants were unable to meet financial obligations or essential needs at the time of the survey and 16.3% were using their savings to meet financial obligations. Participants with a post-secondary education were least likely to be adversely impacted (19.6%), compared with 33.4% of those with secondary education and 33.5% of those with pre-secondary education. Similarly, those in the highest wealth tertile were least likely to be financially impacted (26.7%), compared with 32.5% in the middle tertile and 30.4% in the bottom tertile participants. Compared with HICs, financial impact was greater in UMIC [odds ratio of 2.09 (1.88–2.33)] and greatest in LMIC [odds ratio of 16.88 (14.69–19.39)]. HIC participants with the lowest educational attainment suffered less financial impact (15.1% of participants affected) than those with the highest education in UMIC (22.0% of participants affected). Similarly, participants with the lowest education in UMIC experienced less financial impact (28.3%) than those with the highest education in LMIC (45.9%). A similar gradient was seen across country income categories when compared by pre-pandemic wealth status. Interpretation The financial impact of the pandemic differs more between HIC, UMIC, and LMIC than between socio-economic categories within a country income level. The most disadvantaged socio-economic subgroups in HIC had a lower financial impact from the pandemic than the most advantaged subgroup in UMIC, with a similar disparity seen between UMIC and LMIC. Continued high levels of infection will exacerbate financial inequity between countries and hinder progress towards the sustainable development goals, emphasising the importance of effective measures to control COVID-19 and, especially, ensuring high vaccine coverage in all countries.
  • Publicación
    Acceso abierto
    Variations in the financial impact of the COVID-19 pandemic across 5 continents: A cross-sectional, individual level analysis
    (2022-02-05) Khetan, Aditya K.; Yusuf, Salim; Lopez-Jaramillo, Patricio; Szuba, Andrzej; Orlandini, Andres; Mat-Nasir, Nafiza; Oguz, Aytekin; Gupta, Rajeev; Avezum, Álvaro; Rosnah, Ismail; Poirier, Paul; Teo, Koon K.; Wielgosz, Andreas; Lear, Scott A.; Palileo-Villanueva, Lia M.; Serón, Pamela; Chifamba, Jephat; Rangarajan, Sumathy; Mushtaha, Maha; Mohan, Deepa; Yeates, Karen; McKee, Martin; Mony, Prem K.; Walli-Attaei, Marjan; Khansaheb, Hamda; Rosengren, Annika; Alhabib, Khalid F.; Kruger, Iolanthé M.; Paucar, María-José; Mirrakhimov, Erkin; Assembekov, Batyrbek; Leong, Darryl P.; Masira
    Background COVID-19 has caused profound socio-economic changes worldwide. However, internationally comparative data regarding the financial impact on individuals is sparse. Therefore, we conducted a survey of the financial impact of the pandemic on individuals, using an international cohort that has been well-characterized prior to the pandemic. Methods Between August 2020 and September 2021, we surveyed 24,506 community-dwelling participants from the Prospective Urban-Rural Epidemiology (PURE) study across high (HIC), upper middle (UMIC)-and lower middle (LMIC)-income countries. We collected information regarding the impact of the pandemic on their self-reported personal finances and sources of income. Findings Overall, 32.4% of participants had suffered an adverse financial impact, defined as job loss, inability to meet financial obligations or essential needs, or using savings to meet financial obligations. 8.4% of participants had lost a job (temporarily or permanently); 14.6% of participants were unable to meet financial obligations or essential needs at the time of the survey and 16.3% were using their savings to meet financial obligations. Participants with a post-secondary education were least likely to be adversely impacted (19.6%), compared with 33.4% of those with secondary education and 33.5% of those with pre-secondary education. Similarly, those in the highest wealth tertile were least likely to be financially impacted (26.7%), compared with 32.5% in the middle tertile and 30.4% in the bottom tertile participants. Compared with HICs, financial impact was greater in UMIC [odds ratio of 2.09 (1.88 −2.33)] and greatest in LMIC [odds ratio of 16.88 (14.69−19.39)]. HIC participants with the lowest educational attainment suffered less financial impact (15.1% of participants affected) than those with the highest education in UMIC (22.0% of participants affected). Similarly, participants with the lowest education in UMIC experienced less financial impact (28.3%) than those with the highest education in LMIC (45.9%). A similar gradient was seen across country income categories when compared by pre-pandemic wealth status. Interpretation The financial impact of the pandemic differs more between HIC, UMIC, and LMIC than between socio-economic categories within a country income level. The most disadvantaged socio-economic subgroups in HIC had a lower financial impact from the pandemic than the most advantaged subgroup in UMIC, with a similar disparity seen between UMIC and LMIC. Continued high levels of infection will exacerbate financial inequity between countries and hinder progress towards the sustainable development goals, emphasising the importance of effective measures to control COVID-19 and, especially, ensuring high vaccine coverage in all countries. Funding Funding for this study was provided by the Canadian Institutes of Health Research and the International Development Research Centre.