Examinando por Autor "Mohan, Deepa"

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    Associations of Fish Consumption with Risk of Cardiovascular Disease and Mortality among Individuals with or without Vascular Disease from 58 Countries
    (JAMA Network, 2021-03-08) Mohan, Deepa; Mente, Andrew; Dehghan, Mahshid; Rangarajan, Sumathy; O’Donnell, Martin; Hu, Weihong; Dagenais, Gilles; Wielgosz, Andreas; Lear, Scott; Wei, Li; Diaz, Rafael; Avezum, Alvaro; Lopez-Jaramillo, Patricio; Lanas, Fernando; Swaminathan, Sumathi; Kaur, Manmeet; Vijayakumar, K.; Mohan, Viswanathan; Gupta, Rajeev; Szuba, Andrzej; Iqbal, Romaina; Yusuf, Rita; Mohammadifard, Noushin; Khatib, Rasha; Yusoff, Khalid; Gulec, Sadi; Rosengren, Annika; Yusufali, Afzalhussein; Wentzel-Viljoen, Edelweiss; Chifamba, Jephat; Dans, Antonio; Alhabib, Khalid F.; Yeates, Karen; Teo, Koon; Gerstein, Hertzel C.; Yusuf, Salim; The PURE, ONTARGET, TRANSCEND, and ORIGIN investigators; Masira
    Importance Cohort studies report inconsistent associations between fish consumption, a major source of long-chain ω-3 fatty acids, and risk of cardiovascular disease (CVD) and mortality. Whether the associations vary between those with and those without vascular disease is unknown. Objective To examine whether the associations of fish consumption with risk of CVD or of mortality differ between individuals with and individuals without vascular disease. Design, Setting, and Participants This pooled analysis of individual participant data involved 191 558 individuals from 4 cohort studies—147 645 individuals (139 827 without CVD and 7818 with CVD) from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study and 43 413 patients with vascular disease in 3 prospective studies from 40 countries. Adjusted hazard ratios (HRs) were calculated by multilevel Cox regression separately within each study and then pooled using random-effects meta-analysis. This analysis was conducted from January to June 2020. Exposures Fish consumption was recorded using validated food frequency questionnaires. In 1 of the cohorts with vascular disease, a separate qualitative food frequency questionnaire was used to assess intake of individual types of fish. Main Outcomes and Measures Mortality and major CVD events (including myocardial infarction, stroke, congestive heart failure, or sudden death). Results Overall, 191 558 participants with a mean (SD) age of 54.1 (8.0) years (91 666 [47.9%] male) were included in the present analysis. During 9.1 years of follow-up in PURE, compared with little or no fish intake (≤50 g/mo), an intake of 350 g/wk or more was not associated with risk of major CVD (HR, 0.95; 95% CI, 0.86-1.04) or total mortality (HR, 0.96; 0.88-1.05). By contrast, in the 3 cohorts of patients with vascular disease, the HR for risk of major CVD (HR, 0.84; 95% CI, 0.73-0.96) and total mortality (HR, 0.82; 95% CI, 0.74-0.91) was lowest with intakes of at least 175 g/wk (or approximately 2 servings/wk) compared with 50 g/mo or lower, with no further apparent decrease in HR with consumption of 350 g/wk or higher. Fish with higher amounts of ω-3 fatty acids were strongly associated with a lower risk of CVD (HR, 0.94; 95% CI, 0.92-0.97 per 5-g increment of intake), whereas other fish were neutral (collected in 1 cohort of patients with vascular disease). The association between fish intake and each outcome varied by CVD status, with a lower risk found among patients with vascular disease but not in general populations (for major CVD, I2 = 82.6 [P = .02]; for death, I2 = 90.8 [P = .001]). Conclusions and Relevance Findings of this pooled analysis of 4 cohort studies indicated that a minimal fish intake of 175 g (approximately 2 servings) weekly is associated with lower risk of major CVD and mortality among patients with prior CVD but not in general populations. The consumption of fish (especially oily fish) should be evaluated in randomized trials of clinical outcomes among people with vascular disease.
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    The environmental profile of a community’s health : A cross-sectional study on tobacco marketing in 16 countries
    (2015-07) Savell, Emily; Gilmore, Anna B.; Sims, Michelle; Mony, Prem; Koon, Teo; Yusoff, Khalid; Lear, Scott A.; Seron, Pamela; Ismail, Noorhassim; Tumerdem Calik, K Burcu; Rosengren, Annika; Bahonar, Ahmad; Kumar, Rajesh; Vijayakumar, Krishnapillai; Kruger, Annamarie; Swidan, Hany; Gupta, Rajeev; Igumbor, Ehimario; Afridi, Asad; Rahman, Omar; Chifamba, Jephat; Zatonska, Katarzyna; Mohan, Viswanathan; Mohan, Deepa; Lopez-Jaramillo, Patricio
    Objective To examine and compare tobacco marketing in 16 countries while the Framework Convention on Tobacco Control requires parties to implement a comprehensive ban on such marketing. Methods Between 2009 and 2012, a kilometre-long walk was completed by trained investigators in 462 communities across 16 countries to collect data on tobacco marketing. We interviewed community members about their exposure to traditional and non-traditional marketing in the previous six months. To examine differences in marketing between urban and rural communities and between high-, middle- and low-income countries, we used multilevel regression models controlling for potential confounders. Findings Compared with high-income countries, the number of tobacco advertisements observed was 81 times higher in low-income countries (incidence rate ratio, IRR: 80.98; 95% confidence interval, CI: 4.15–1578.42) and the number of tobacco outlets was 2.5 times higher in both low- and lower-middle-income countries (IRR: 2.58; 95% CI: 1.17–5.67 and IRR: 2.52; CI: 1.23–5.17, respectively). Of the 11842 interviewees, 1184 (10%) reported seeing at least five types of tobacco marketing. Self-reported exposure to at least one type of traditional marketing was 10 times higher in low-income countries than in high-income countries (odds ratio, OR: 9.77; 95% CI: 1.24–76.77). For almost all measures, marketing exposure was significantly lower in the rural communities than in the urban communities. Conclusion Despite global legislation to limit tobacco marketing, it appears ubiquitous. The frequency and type of tobacco marketing varies on the national level by income group and by community type, appearing to be greatest in low-income countries and urban communities.
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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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    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.
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    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
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    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.