Browsing by Author "Farshad Farzadfar"
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Item Data Resource Profile: The Global Health and Population Project on Access to Care for Cardiometabolic Diseases (HPACC)(2022-12-13) Jennifer Manne-Goehler; Michaela Theilmann; David Flood; Maja E Marcus; Glennis Andall-Brereton; Kokou Agoudavi; William Andres Lopez Arboleda; Krishna K Aryal; Brice Bicaba; Pascal Bovet; Luisa Campos Caldeira Brant; Garry Brian; Grace Chamberlin; Geoffrey Chen; Albertino Damasceno; Maria Dorobantu; Matthew Dunn; Cara Ebert; Farshad Farzadfar; Mongal Singh Gurung; David Guwatudde; Corine Houehanou; Dismand Houinato; Nahla Hwalla; Jutta M Adelin Jorgensen; Khem B Karki; Demetre Labadarios; Nuno Lunet; Deborah Carvalho Malta; Joao S Martins; Mary T Mayige; Roy Wong McClure; Sahar Saeedi Moghaddam; Kibachio J Mwangi; Omar Mwalim; Bolormaa Norov; Sarah Quesnel-Crooks; Sabrina Rhode; Jacqueline A Seiglie; Abla Sibai; Bahendeka K Silver; Lela Sturua; Andrew Stokes; Adil Supiyev; Lindiwe Tsabedze; Zhaxybay Zhumadilov; Lindsay M Jaacks; Rifat Atun; Justine I DaviesItem Diagnostic testing for hypertension, diabetes, and hypercholesterolaemia in low-income and middle-income countries: a cross-sectional study of data for 994 185 individuals from 57 nationally representative surveys(2023-09) Sophie Ochmann*; Isabelle von Polenz*; Maja-Emilia Marcus; Michaela Theilmann; David Flood; Kokou Agoudavi; Krishna Kumar Aryal; Silver Bahendeka; Brice Bicaba; Pascal Bovet; Luisa Campos Caldeira Brant; Deborah Carvalho Malta; Albertino Damasceno; Farshad Farzadfar; Gladwell Gathecha; Ali Ghanbari; Mongal Gurung; David Guwatudde; Corine Houehanou; Dismand Houinato; Nahla Hwalla; Jutta Adelin Jorgensen; Khem B Karki; Nuno Lunet; Joao Martins; Mary Mayige; Sahar Saeedi Moghaddam; Omar Mwalim; Kibachio Joseph Mwangi; Bolormaa Norov; Sarah Quesnel-Crooks; Negar Rezaei; Abla M Sibai; Lela Sturua; Lindiwe Tsabedze; Roy Wong-McClure; Justine Davies; Pascal Geldsetzer; Till Bärnighausen; Rifat Atun†; Jennifer Manne-Goehler†; Sebastian Vollmer†Background—Testing for the risk factors of cardiovascular disease, which include hypertension, diabetes, and hypercholesterolaemia, is important for timely and effective risk management. Yet few studies have quantified and analysed testing of cardiovascular risk factors in low-income and middle-income countries (LMICs) with respect to sociodemographic inequalities. We aimed to address this knowledge gap. Methods—In this cross-sectional analysis, we pooled individual-level data for non-pregnant adults aged 18 years or older from nationally representative surveys done between Jan 1, 2010, and Dec 31, 2019 in LMICs that included a question about whether respondents had ever had their blood pressure, glucose, or cholesterol measured. We analysed diagnostic testing performance by quantifying the overall proportion of people who had ever been tested for these cardiovascular risk factors and the proportion of individuals who met the diagnostic testing criteria in the WHO package of essential noncommunicable disease interventions for primary care (PEN) guidelines (ie, a BMI >30 kg/m2 or a BMI >25 kg/m2 among people aged 40 years or older). We disaggregated and compared diagnostic testing performance by sex, wealth quintile, and education using two-sided t tests and multivariable logistic regression models. Findings—Our sample included data for 994 185 people from 57 surveys. 19·1% (95% CI 18·5– 19·8) of the 943 259 people in the hypertension sample met the WHO PEN criteria for diagnostic testing, of whom 78·6% (77·8–79·2) were tested. 23·8% (23·4–24·3) of the 225 707 people in the diabetes sample met the WHO PEN criteria for diagnostic testing, of whom 44·9% (43·7– 46·2) were tested. Finally, 27·4% (26·3–28·6) of the 250 573 people in the hypercholesterolaemia sample met the WHO PEN criteria for diagnostic testing, of whom 39·7% (37·1–2·4) were tested. Women were more likely than men to be tested for hypertension and diabetes, and people in higher wealth quintiles compared with those in the lowest wealth quintile were more likely to be tested for all three risk factors, as were people with at least secondary education compared with those with less than primary education. Interpretation—Our study shows opportunities for health systems in LMICs to improve the targeting of diagnostic testing for cardiovascular risk factors and adherence to diagnostic testing guidelines. Risk-factor-based testing recommendations rather than sociodemographic characteristics should determine which individuals are tested.Item Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model(2021-09-22) Sanjay Basu; David Flood; Pascal Geldsetzer; Michaela Theilmann; Maja E Marcus; Cara Ebert; Mary Mayige; Roy Wong-McClure; Farshad Farzadfar; Sahar Saeedi Moghaddam; Kokou Agoudavi; Bolormaa Norov; Corine Houehanou; Glennis Andall-Brereton; Mongal Gurung; Garry Brian; Pascal Bovet; Joao Martins; Rifat Atun; Till Bärnighausen; Sebastian Vollmer; Jen Manne-Goehler; Justine DaviesBackground Given the increasing prevalence of diabetes in low-income and middle-income countries (LMICs), we aimed to estimate the health and cost implications of achieving different targets for diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among LMICs. Methods We constructed a microsimulation model to estimate disability-adjusted life-years (DALYs) lost and healthcare costs of diagnosis, treatment, and control of blood pressure, dyslipidaemia, and glycaemia among people with diabetes in LMICs. We used individual participant data—specifically from the subset of people who were defined as having any type of diabetes by WHO standards—from nationally representative, cross-sectional surveys (2006–18) spanning 15 world regions to estimate the baseline 10-year risk of atherosclerotic cardiovascular disease (defined as fatal and non-fatal myocardial infarction and stroke), heart failure (ejection fraction of <40%, with New York Heart Association class III or IV functional limitations), end-stage renal disease (defined as an estimated glomerular filtration rate <15 mL/min per 1∙73 m² or needing dialysis or transplant), retinopathy with severe vision loss (<20/200 visual acuity as measured by the Snellen chart), and neuropathy with pressure sensation loss (assessed by the Semmes-Weinstein 5∙07/10 g monofilament exam). We then used data from meta-analyses of randomised controlled trials to estimate the reduction in risk and the WHO OneHealth tool to estimate costs in reaching either 60% or 80% of diagnosis, treatment initiation, and control targets for blood pressure, dyslipidaemia, and glycaemia recommended by WHO guidelines. Costs were updated to 2020 International Dollars, and both costs and DALYs were computed over a 10-year policy planning time horizon at a 3% annual discount rate. Findings We obtained data from 23 678 people with diabetes from 67 countries. The median estimated 10-year risk was 10∙0% (IQR 4∙0–18∙0) for cardiovascular events, 7∙8% (5∙1–11∙8) for neuropathy with pressure sensation loss, 7∙2% (5∙6–9∙4) for end-stage renal disease, 6∙0% (4∙2–8∙6) for retinopathy with severe vision loss, and 2∙6% (1∙2–5∙3) for congestive heart failure. A target of 80% diagnosis, 80% treatment, and 80% control would be expected to reduce DALYs lost from diabetes complications from a median population-weighted loss to 1097 DALYs per 1000 population over 10 years (IQR 1051–1155), relative to a baseline of 1161 DALYs, primarily from reduced cardiovascular events (down from a median of 143 to 117 DALYs per 1000 population) due to blood pressure and statin treatment, with comparatively little effect from glycaemic control. The target of 80% diagnosis, 80% treatment, and 80% control would be expected to produce an overall incremental cost-effectiveness ratio of US$1362 per DALY averted (IQR 1304–1409), with the majority of decreased costs from reduced cardiovascular event management, counterbalanced by increased costs for blood pressure and statin treatment, producing an overall incremental costeffectiveness ratio of $1362 per DALY averted (IQR 1304–1409). Interpretation Reducing complications from diabetes in LMICs is likely to require a focus on scaling up blood pressure and statin medication treatment initiation and blood pressure medication titration rather than focusing on increasing screening to increase diabetes diagnosis, or a glycaemic treatment and control among people with diabetes.Item Patterns of tobacco use in low and middle income countries by tobacco product and sociodemographic characteristics: nationally representative survey data from 82 countries(2022-07-01) Michaela Theilmann; Julia M Lemp; Volker Winkler; Jennifer Manne-Goehler; Maja E Marcus; Charlotte Probst; William A Lopez-Arboleda; Cara Ebert; Christian Bommer; Maya Mathur; Glennis Andall-Brereton; Silver K Bahendeka; Pascal Bovet; Farshad Farzadfar; Erfan Ghasemi; Mary T Mayige; Sahar Saeedi Moghaddam; Kibachio J Mwangi; Shohreh Naderimagham; Lela Sturua; Rifat Atun; Justine I Davies; Till Bärnighausen; Sebastian Vollmer; Pascal GeldsetzerObjectives To determine the prevalence and frequency of using any tobacco product and each of a detailed set of tobacco products, how tobacco use and frequency of use vary across countries, world regions, and World Bank country income groups, and the socioeconomic and demographic gradients of tobacco use and use frequency within countries. Design Secondary analysis of nationally representative, crosssectional, household survey data from 82 low and middle income countries collected between 1 January 2015 and 31 December 2020. Setting Population based survey data. Participants 1231068 individuals aged 15 years and older. Main outcome measures Self-reported current smoking, current daily smoking, current smokeless tobacco use, current daily smokeless tobacco use, pack years, and current use and use frequencies of each tobacco product. Products were any type of cigarette, manufactured cigarette, hand rolled cigarette, water pipe, cigar, oral snuff, nasal snuff, chewing tobacco, and betel nut (with and without tobacco). Results The smoking prevalence in the study sample was 16.5% (95% confidence interval 16.1% to 16.9%) and ranged from 1.1% (0.9% to 1.3%) in Ghana to 50.6% (45.2% to 56.1%) in Kiribati. The user prevalence of smokeless tobacco was 7.7% (7.5% to 8.0%) and prevalence was highest in Papua New Guinea (daily user prevalence of 65.4% (63.3% to 67.5%)). Although variation was wide between countries and by tobacco product, for many low and middle income countries, the highest prevalence and cigarette smoking frequency was reported in men, those with lower education, less household wealth, living in rural areas, and higher age. Co nclusions Both smoked and smokeless tobacco use and frequency of use vary widely across tobacco products in low and middle income countries. This study can inform the design and targeting of efforts to reduce tobacco use in low and middle income countries and serve as a benchmark for monitoring progress towards national and international goals.Item Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data(2022-09) David Flood; Pascal Geldsetzer; Kokou Agoudavi; Krishna K. Aryal; Luisa Campos Caldeira Brant; Garry Brian; Maria Dorobantu; Farshad Farzadfar; Oana Gheorghe-Fronea; Mongal Singh Gurung; David Guwatudde; Corine Houehanou; Jutta M. Adelin Jorgensen; Dimple Kondal; Demetre Labadarios; Maja E. Marcus; Mary Mayige; Mana Moghimi; Bolormaa Norov; Gaston Perman; Sarah Quesnel-Crooks; Mohammad-Mahdi Rashidi; Sahar Saeedi Moghaddam; Jacqueline A. Seiglie; Silver K. Bahendeka; Eric Steinbrook; Michaela Theilmann; Lisa J. Ware; Sebastian Vollmer; Rifat Atun; Justine I. Davies; Mohammed K. Ali; Peter Rohloff; Jennifer Manne-GoehlerOBJECTIVE Diabetes prevalence is increasing rapidly in rural areas of low- and middle-income countries (LMICs), but there are limited data on the performance of health systems in delivering equitable and effective care to rural populations. We therefore assessed rural-urban differences in diabetes care and control in LMICs. RESEARCH DESIGN AND METHODS We pooled individual-level data from nationally representative health surveys in 42 countries. We used Poisson regression models to estimate age-adjusted differences in the proportion of individuals with diabetes in rural versus urban areas achieving performance measures for the diagnosis, treatment, and control of diabetes and associated cardiovascular risk factors. We examined differences across the pooled sample, by sex, and by country. RESULTS The pooled sample from 42 countries included 840,110 individuals (35,404 with diabetes). Compared with urban populations with diabetes, rural populations had 15–30% lower relative risk of achieving performance measures for diabetes diagnosis and treatment. Rural populations with diagnosed diabetes had a 14% (95% CI 5–22%) lower relative risk of glycemic control, 6% (95% CI 25 to 16%) lower relative risk of blood pressure control, and 23% (95% CI 2–39%) lower relative risk of cholesterol control. Rural women with diabetes had lower achievement of performance measures relating to control than urban women, whereas among men, differences were small. CONCLUSIONS Rural populations with diabetes experience substantial inequities in the achievement of diabetes performance measures in LMICs. Programs and policies aiming to strengthen global diabetes care must consider the unique challenges experienced by rural populations.Item The socioeconomic gradient of alcohol use: an analysis of nationally representative survey data from 55 low-income and middle-income countries(2022-10-22) Yuanwei Xu; Pascal Geldsetzer; Jen Manne-Goehler; Michaela Theilmann; Maja-E Marcus; Zhaxybay Zhumadilov; Sarah Quesnel-Crooks; Omar Mwalim; Sahar Saeedi Moghaddam; Sogol Koolaji; Khem B Karki; Farshad Farzadfar; Narges Ebrahimi; Albertino Damasceno; Krishna K Aryal; Kokou Agoudavi; Rifat Atun; Till Bärnighausen; Justine Davies; Lindsay M Jaacks; Sebastian Vollmer; Charlotte ProbstBackground: Alcohol is a leading risk factor for over 200 conditions and an important contributor to socioeconomic health inequalities. However, little is known about the associations between individuals' socioeconomic circumstances and alcohol consumption, especially heavy episodic drinking (HED; ≥5 drinks on one occasion) in low-income or middle-income countries. We investigated the association between individual and household level socioeconomic status, and alcohol drinking habits in these settings. Methods: In this pooled analysis of individual-level data, we used available nationally representative surveys-mainly WHO Stepwise Approach to Surveillance surveys-conducted in 55 low-income and middle-income countries between 2005 and 2017 reporting on alcohol use. Surveys from participants aged 15 years or older were included. Logistic regression models controlling for age, country, and survey year stratified by sex and country income groups were used to investigate associations between two indicators of socioeconomic status (individual educational attainment and household wealth) and alcohol use (current drinking and HED amongst current drinkers). Findings: Surveys from 336 287 participants were included in the analysis. Among males, the highest prevalence of both current drinking and HED was found in lower-middle-income countries (L-MICs; current drinking 49·9% [95% CI 48·7-51·2] and HED 63·3% [61·0-65·7]). Among females, the prevalence of current drinking was highest in upper-middle-income countries (U-MIC; 29·5% [26·1-33·2]), and the prevalence of HED was highest in low-income countries (LICs; 36·8% [33·6-40·2]). Clear gradients in the prevalence of current drinking were observed across all country income groups, with a higher prevalence among participants with high socioeconomic status. However, in U-MICs, current drinkers with low socioeconomic status were more likely to engage in HED than participants with high socioeconomic status; the opposite was observed in LICs, and no association between socioeconomic status and HED was found in L-MICs. Interpretation: The findings call for urgent alcohol control policies and interventions in LICs and L-MICs to reduce harmful HED. Moreover, alcohol control policies need to be targeted at socially disadvantaged groups in U-MICs. Funding: Deutsche Forschungsgemeinschaft and the National Center for Advancing Translational Sciences of the US National Institutes of Health.Item Use of statins for the prevention of cardiovascular disease in 41 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data(2022-03) Maja E Marcus; Jennifer Manne-Goehler; Michaela Theilmann; Farshad Farzadfar; Sahar Saeedi Moghaddam; Mohammad Keykhaei; Amirali Hajebi; Scott Tschida; Julia M Lemp; Krishna K Aryal; Matthew Dunn; Corine Houehanou; Silver Bahendeka; Peter Rohloff; Rifat Atun; Till W Bärnighausen; Pascal Geldsetzer; Manuel Ramirez-Zea; Vineet Chopra; Michele Heisler; Justine I Davies; Mark D Huffman; Sebastian Vollmer; David FloodBackground: In the prevention of cardiovascular disease, a WHO target is that at least 50% of eligible people use statins. Robust evidence is needed to monitor progress towards this target in low-income and middle-income countries (LMICs), where most cardiovascular disease deaths occur. The objectives of this study were to benchmark statin use in LMICs and to investigate country-level and individual-level characteristics associated with statin use. Methods: We did a cross-sectional analysis of pooled, individual-level data from nationally representative health surveys done in 41 LMICs between 2013 and 2019. Our sample consisted of non-pregnant adults aged 40-69 years. We prioritised WHO Stepwise Approach to Surveillance (STEPS) surveys because these are WHO's recommended method for population monitoring of non-communicable disease targets. For countries in which no STEPS survey was available, a systematic search was done to identify other surveys. We included surveys that were done in an LMIC as classified by the World Bank in the survey year; were done in 2013 or later; were nationally representative; had individual-level data available; and asked questions on statin use and previous history of cardiovascular disease. Primary outcomes were the proportion of eligible individuals self-reporting use of statins for the primary and secondary prevention of cardiovascular disease. Eligibility for statin therapy for primary prevention was defined among individuals with a history of diagnosed diabetes or a 10-year cardiovascular disease risk of at least 20%. Eligibility for statin therapy for secondary prevention was defined among individuals with a history of self-reported cardiovascular disease. At the country level, we estimated statin use by per-capita health spending, per-capita income, burden of cardiovascular diseases, and commitment to non-communicable disease policy. At the individual level, we used modified Poisson regression models to assess statin use alongside individual-level characteristics of age, sex, education, and rural versus urban residence. Countries were weighted in proportion to their population size in pooled analyses. Findings: The final pooled sample included 116 449 non-pregnant individuals. 9229 individuals reported a previous history of cardiovascular disease (7·9% [95% CI 7·4-8·3] of the population-weighted sample). Among those without a previous history of cardiovascular disease, 8453 were eligible for a statin for primary prevention of cardiovascular disease (9·7% [95% CI 9·3-10·1] of the population-weighted sample). For primary prevention of cardiovascular disease, statin use was 8·0% (95% CI 6·9-9·3) and for secondary prevention statin use was 21·9% (20·0-24·0). The WHO target that at least 50% of eligible individuals receive statin therapy to prevent cardiovascular disease was achieved by no region or income group. Statin use was less common in countries with lower health spending. At the individual level, there was generally higher statin use among women (primary prevention only, risk ratio [RR] 1·83 [95% CI 1·22-2·76), and individuals who were older (primary prevention, 60-69 years, RR 1·86 [1·04-3·33]; secondary prevention, 50-59 years RR 1·71 [1·35-2·18]; and 60-69 years RR 2·09 [1·65-2·65]), more educated (primary prevention, RR 1·61 [1·09-2·37]; secondary prevention, RR 1·28 [0·97-1·69]), and lived in urban areas (secondary prevention only, RR 0·82 [0·66-1·00]). Interpretation: In a diverse sample of LMICs, statins are used by about one in ten eligible people for the primary prevention of cardiovascular diseases and one in five eligible people for secondary prevention. There is an urgent need to scale up statin use in LMICs to achieve WHO targets. Policies and programmes that facilitate implementation of statins into primary health systems in these settings should be investigated for the future.