21 results on '"Martins, Joao S."'
Search Results
2. Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults
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Teufel, Felix, Seiglie, Jacqueline A, Geldsetzer, Pascal, Theilmann, Michaela, Marcus, Maja E, Ebert, Cara, Arboleda, William Andres Lopez, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K, Bicaba, Brice Wilfried, Brian, Garry, Bovet, Pascal, Dorobantu, Maria, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta M Adelin, Kagaruki, Gibson B, Karki, Khem B, Labadarios, Demetre, Martins, Joao S, Mayige, Mary T, McClure, Roy Wong, Mwangi, Joseph Kibachio, Mwalim, Omar, Norov, Bolormaa, Crooks, Sarah, Farzadfar, Farshad, Moghaddam, Sahar Saeedi, Silver, Bahendeka K, Sturua, Lela, Wesseh, Chea Stanford, Stokes, Andrew C, Essien, Utibe R, De Neve, Jan-Walter, Atun, Rifat, Davies, Justine I, Vollmer, Sebastian, Bärnighausen, Till W, Ali, Mohammed K, Meigs, James B, Wexler, Deborah J, and Manne-Goehler, Jennifer
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- 2021
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3. Unmet need for hypercholesterolemia care in 35 low- and middle-income countries: A cross-sectional study of nationally representative surveys
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Marcus, Maja E., Ebert, Cara, Geldsetzer, Pascal, Theilmann, Michaela, Bicaba, Brice Wilfried, Andall-Brereton, Glennis, Bovet, Pascal, Farzadfar, Farshad, Singh Gurung, Mongal, Houehanou, Corine, Malekpour, Mohammad-Reza, Martins, Joao S., Moghaddam, Sahar Saeedi, Mohammadi, Esmaeil, Norov, Bolormaa, Quesnel-Crooks, Sarah, Wong-McClure, Roy, Davies, Justine I., Hlatky, Mark A., Atun, Rifat, Bärnighausen, Till W., Jaacks, Lindsay M., Manne-Goehler, Jennifer, and Vollmer, Sebastian
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Developing countries -- Health aspects -- Statistics ,Hypercholesterolemia -- Care and treatment -- International aspects -- Statistics ,Biological sciences - Abstract
Background As the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs. Methods and findings We pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) [greater than or equal to]240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) [greater than or equal to]160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings. Conclusions Cascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs-calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD., Author(s): Maja E. Marcus 1,*, Cara Ebert 2, Pascal Geldsetzer 3,4, Michaela Theilmann 4, Brice Wilfried Bicaba 5, Glennis Andall-Brereton 6, Pascal Bovet 7,8, Farshad Farzadfar 9, Mongal Singh Gurung [...]
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- 2021
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4. Cardiovascular disease risk profile and management practices in 45 low-income and middle-income countries: A cross-sectional study of nationally representative individual-level survey data
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Peiris, David, Ghosh, Arpita, Manne-Goehler, Jennifer, Jaacks, Lindsay M., Theilmann, Michaela, Marcus, Maja E., Zhumadilov, Zhaxybay, Tsabedze, Lindiwe, Supiyev, Adil, Silver, Bahendeka K., Sibai, Abla M., Norov, Bolormaa, Mayige, Mary T., Martins, Joao S., Lunet, Nuno, Labadarios, Demetre, Jorgensen, Jutta M. A., Houehanou, Corine, Guwatudde, David, Gurung, Mongal S., Damasceno, Albertino, Aryal, Krishna K., Andall-Brereton, Glennis, Agoudavi, Kokou, McKenzie, Briar, Webster, Jacqui, Atun, Rifat, Bärnighausen, Till, Vollmer, Sebastian, Davies, Justine I., and Geldsetzer, Pascal
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Developing countries -- Health aspects ,Cardiovascular diseases -- Risk factors -- Care and treatment ,Antihypertensive drugs -- Usage ,Blood pressure -- Regulation ,Biological sciences - Abstract
Background Global cardiovascular disease (CVD) burden is high and rising, especially in low-income and middle-income countries (LMICs). Focussing on 45 LMICs, we aimed to determine (1) the adult population's median 10-year predicted CVD risk, including its variation within countries by socio-demographic characteristics, and (2) the prevalence of self-reported blood pressure (BP) medication use among those with and without an indication for such medication as per World Health Organization (WHO) guidelines. Methods and findings We conducted a cross-sectional analysis of nationally representative household surveys from 45 LMICs carried out between 2005 and 2017, with 32 surveys being WHO Stepwise Approach to Surveillance (STEPS) surveys. Country-specific median 10-year CVD risk was calculated using the 2019 WHO CVD Risk Chart Working Group non-laboratory-based equations. BP medication indications were based on the WHO Package of Essential Noncommunicable Disease Interventions guidelines. Regression models examined associations between CVD risk, BP medication use, and socio-demographic characteristics. Our complete case analysis included 600,484 adults from 45 countries. Median 10-year CVD risk (interquartile range [IQR]) for males and females was 2.7% (2.3%-4.2%) and 1.6% (1.3%-2.1%), respectively, with estimates indicating the lowest risk in sub-Saharan Africa and highest in Europe and the Eastern Mediterranean. Higher educational attainment and current employment were associated with lower CVD risk in most countries. Of those indicated for BP medication, the median (IQR) percentage taking medication was 24.2% (15.4%-37.2%) for males and 41.6% (23.9%-53.8%) for females. Conversely, a median (IQR) 47.1% (36.1%-58.6%) of all people taking a BP medication were not indicated for such based on CVD risk status. There was no association between BP medication use and socio-demographic characteristics in most of the 45 study countries. Study limitations include variation in country survey methods, most notably the sample age range and year of data collection, insufficient data to use the laboratory-based CVD risk equations, and an inability to determine past history of a CVD diagnosis. Conclusions This study found underuse of guideline-indicated BP medication in people with elevated CVD risk and overuse by people with lower CVD risk. Country-specific targeted policies are needed to help improve the identification and management of those at highest CVD risk., Author(s): David Peiris 1,*, Arpita Ghosh 2,3, Jennifer Manne-Goehler 4, Lindsay M. Jaacks 5, Michaela Theilmann 4, Maja E. Marcus 6, Zhaxybay Zhumadilov 7, Lindiwe Tsabedze 8, Adil Supiyev 9, [...]
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- 2021
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5. Association between country preparedness indicators and quality clinical care for cardiovascular disease risk factors in 44 lower- and middle-income countries: A multicountry analysis of survey data
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Davies, Justine I., Reddiar, Sumithra Krishnamurthy, Hirschhorn, Lisa R., Ebert, Cara, Marcus, Maja-Emilia, Seiglie, Jacqueline A., Zhumadilov, Zhaxybay, Supiyev, Adil, Sturua, Lela, Silver, Bahendeka K., Sibai, Abla M., Quesnel-Crooks, Sarah, Norov, Bolormaa, Mwangi, Joseph K., Omar, Omar Mwalim, Wong-McClure, Roy, Mayige, Mary T., Martins, Joao S., Lunet, Nuno, Labadarios, Demetre, Karki, Khem B., Kagaruki, Gibson B., Jorgensen, Jutta M. A., Hwalla, Nahla C., Houinato, Dismand, Houehanou, Corine, Guwatudde, David, Gurung, Mongal S., Bovet, Pascal, Bicaba, Brice W., Aryal, Krishna K., Msaidié, Mohamed, Andall-Brereton, Glennis, Brian, Garry, Stokes, Andrew, Vollmer, Sebastian, Bärnighausen, Till, Atun, Rifat, Geldsetzer, Pascal, Manne-Goehler, Jennifer, and Jaacks, Lindsay M.
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Developing countries -- Health aspects ,Cardiovascular diseases -- Risk factors -- Care and treatment ,Biological sciences - Abstract
Background Cardiovascular diseases are leading causes of death, globally, and health systems that deliver quality clinical care are needed to manage an increasing number of people with risk factors for these diseases. Indicators of preparedness of countries to manage cardiovascular disease risk factors (CVDRFs) are regularly collected by ministries of health and global health agencies. We aimed to assess whether these indicators are associated with patient receipt of quality clinical care. Methods and findings We did a secondary analysis of cross-sectional, nationally representative, individual-patient data from 187,552 people with hypertension (mean age 48.1 years, 53.5% female) living in 43 low- and middle-income countries (LMICs) and 40,795 people with diabetes (mean age 52.2 years, 57.7% female) living in 28 LMICs on progress through cascades of care (condition diagnosed, treated, or controlled) for diabetes or hypertension, to indicate outcomes of provision of quality clinical care. Data were extracted from national-level World Health Organization (WHO) Stepwise Approach to Surveillance (STEPS), or other similar household surveys, conducted between July 2005 and November 2016. We used mixed-effects logistic regression to estimate associations between each quality clinical care outcome and indicators of country development (gross domestic product [GDP] per capita or Human Development Index [HDI]); national capacity for the prevention and control of noncommunicable diseases ('NCD readiness indicators' from surveys done by WHO); health system finance (domestic government expenditure on health [as percentage of GDP], private, and out-of-pocket expenditure on health [both as percentage of current]); and health service readiness (number of physicians, nurses, or hospital beds per 1,000 people) and performance (neonatal mortality rate). All models were adjusted for individual-level predictors including age, sex, and education. In an exploratory analysis, we tested whether national-level data on facility preparedness for diabetes were positively associated with outcomes. Associations were inconsistent between indicators and quality clinical care outcomes. For hypertension, GDP and HDI were both positively associated with each outcome. Of the 33 relationships tested between NCD readiness indicators and outcomes, only two showed a significant positive association: presence of guidelines with being diagnosed (odds ratio [OR], 1.86 [95% CI 1.08-3.21], p = 0.03) and availability of funding with being controlled (OR, 2.26 [95% CI 1.09-4.69], p = 0.03). Hospital beds (OR, 1.14 [95% CI 1.02-1.27], p = 0.02), nurses/midwives (OR, 1.24 [95% CI 1.06-1.44], p = 0.006), and physicians (OR, 1.21 [95% CI 1.11-1.32], p < 0.001) per 1,000 people were positively associated with being diagnosed and, similarly, with being treated; and the number of physicians was additionally associated with being controlled (OR, 1.12 [95% CI 1.01-1.23], p = 0.03). For diabetes, no positive associations were seen between NCD readiness indicators and outcomes. There was no association between country development, health service finance, or health service performance and readiness indicators and any outcome, apart from GDP (OR, 1.70 [95% CI 1.12-2.59], p = 0.01), HDI (OR, 1.21 [95% CI 1.01-1.44], p = 0.04), and number of physicians per 1,000 people (OR, 1.28 [95% CI 1.09-1.51], p = 0.003), which were associated with being diagnosed. Six countries had data on cascades of care and nationwide-level data on facility preparedness. Of the 27 associations tested between facility preparedness indicators and outcomes, the only association that was significant was having metformin available, which was positively associated with treatment (OR, 1.35 [95% CI 1.01-1.81], p = 0.04). The main limitation was use of blood pressure measurement on a single occasion to diagnose hypertension and a single blood glucose measurement to diagnose diabetes. Conclusion In this study, we observed that indicators of country preparedness to deal with CVDRFs are poor proxies for quality clinical care received by patients for hypertension and diabetes. The major implication is that assessments of countries' preparedness to manage CVDRFs should not rely on proxies; rather, it should involve direct assessment of quality clinical care., Author(s): Justine I. Davies 1,2,3,4,*, Sumithra Krishnamurthy Reddiar 5, Lisa R. Hirschhorn 6, Cara Ebert 7, Maja-Emilia Marcus 8, Jacqueline A. Seiglie 9, Zhaxybay Zhumadilov 10, Adil Supiyev 11, Lela [...]
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- 2020
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6. Data Resource Profile:The Global Health and Population Project on Access to Care for Cardiometabolic Diseases (HPACC)
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Manne-Goehler, Jennifer, Theilmann, Michaela, Flood, David, Marcus, Maja E., Andall-Brereton, Glennis, Agoudavi, Kokou, Arboleda, William Andres Lopez, Aryal, Krishna K., Bicaba, Brice, Bovet, Pascal, Caldeira Brant, Luisa Campos, Brian, Garry, Chamberlin, Grace, Chen, Geoffrey, Damasceno, Albertino, Dorobantu, Maria, Dunn, Matthew, Ebert, Cara, Farzadfar, Farshad, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Hwalla, Nahla, Jorgensen, Jutta M. Adelin, Karki, Khem B., Labadarios, Demetre, Lunet, Nuno, Malta, Deborah Carvalho, Martins, Joao S., Mayige, Mary T., McClure, Roy Wong, Moghaddam, Sahar Saeedi, Mwangi, Kibachio J., Mwalim, Omar, Norov, Bolormaa, Quesnel-Crooks, Sarah, Rhode, Sabrina, Seiglie, Jacqueline A., Sibai, Abla, Silver, Bahendeka K., Sturua, Lela, Stokes, Andrew, Supiyev, Adil, Tsabedze, Lindiwe, Zhumadilov, Zhaxybay, Jaacks, Lindsay M., Atun, Rifat, Davies, Justine, I, Geldsetzer, Pascal, Vollmer, Sebastian, Baernighausen, Till W., Manne-Goehler, Jennifer, Theilmann, Michaela, Flood, David, Marcus, Maja E., Andall-Brereton, Glennis, Agoudavi, Kokou, Arboleda, William Andres Lopez, Aryal, Krishna K., Bicaba, Brice, Bovet, Pascal, Caldeira Brant, Luisa Campos, Brian, Garry, Chamberlin, Grace, Chen, Geoffrey, Damasceno, Albertino, Dorobantu, Maria, Dunn, Matthew, Ebert, Cara, Farzadfar, Farshad, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Hwalla, Nahla, Jorgensen, Jutta M. Adelin, Karki, Khem B., Labadarios, Demetre, Lunet, Nuno, Malta, Deborah Carvalho, Martins, Joao S., Mayige, Mary T., McClure, Roy Wong, Moghaddam, Sahar Saeedi, Mwangi, Kibachio J., Mwalim, Omar, Norov, Bolormaa, Quesnel-Crooks, Sarah, Rhode, Sabrina, Seiglie, Jacqueline A., Sibai, Abla, Silver, Bahendeka K., Sturua, Lela, Stokes, Andrew, Supiyev, Adil, Tsabedze, Lindiwe, Zhumadilov, Zhaxybay, Jaacks, Lindsay M., Atun, Rifat, Davies, Justine, I, Geldsetzer, Pascal, Vollmer, Sebastian, and Baernighausen, Till W.
- Abstract
Though more than four in five deaths due to cardiovascular disease (CVD) occur in low-income and middle-income countries, there have been few data sources that allow for empirical estimation of key relationships relevant to the epidemiology, health behaviour and health services of CVD risk factors at the level of the individual. The Global Health and Population Project on Access to Care for Cardiometabolic Diseases (HPACC) is a novel data resource that fills this gap
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- 2022
7. Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys
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Manne-Goehler, Jennifer, Geldsetzer, Pascal, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K., Bicaba, Brice Wilfried, Bovet, Pascal, Brian, Garry, Dorobantu, Maria, Gathecha, Gladwell, Singh Gurung, Mongal, Guwatudde, David, Msaidie, Mohamed, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta Mari Adelin, Kagaruki, Gibson B., Karki, Khem B., Labadarios, Demetre, Martins, Joao S., Mayige, Mary T., McClure, Roy Wong, Mwalim, Omar, Mwangi, Joseph Kibachio, Norov, Bolormaa, Quesnel-Crooks, Sarah, Silver, Bahendeka K., Sturua, Lela, Tsabedze, Lindiwe, Wesseh, Chea Stanford, Stokes, Andrew, Marcus, Maja, Ebert, Cara, Davies, Justine I., Vollmer, Sebastian, Atun, Rifat, Bärnighausen, Till W., and Jaacks, Lindsay M.
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Health care industry -- Surveys -- International aspects ,Diabetes therapy -- Surveys -- International aspects ,Medical care quality -- Surveys -- International aspects ,Developing countries -- Surveys ,Evidence-based medicine ,Glycosylated hemoglobin ,Diabetics ,Epidemics ,Fasting ,Glucose ,Personal income ,Health surveys ,Health care industry ,Biological sciences - Abstract
Background The prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach. Methods and findings We pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose [greater than or equal to] 7.0 mmol/l (126 mg/dl), random plasma glucose [greater than or equal to] 11.1 mmol/l (200 mg/dl), HbA1c [greater than or equal to] 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given ('treated'), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%-9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%-5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%-78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys. Conclusions The study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured., Author(s): Jennifer Manne-Goehler 1,*, Pascal Geldsetzer 2, Kokou Agoudavi 3, Glennis Andall-Brereton 4, Krishna K. Aryal 5, Brice Wilfried Bicaba 6, Pascal Bovet 7,8, Garry Brian 9, Maria Dorobantu 10, [...]
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- 2019
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8. Body-mass index and diabetes risk in 57 low-income and middle-income countries:a cross-sectional study of nationally representative, individual-level data in 685 616 adults
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Teufel, Felix, Seiglie, Jacqueline A., Geldsetzer, Pascal, Theilmann, Michaela, Marcus, Maja E., Ebert, Cara, Arboleda, William Andres Lopez, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K., Bicaba, Brice Wilfried, Brian, Garry, Bovet, Pascal, Dorobantu, Maria, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta M. Adelin, Kagaruki, Gibson B., Karki, Khem B., Labadarios, Demetre, Martins, Joao S., Mayige, Mary T., McClure, Roy Wong, Mwangi, Joseph Kibachio, Mwalim, Omar, Norov, Bolormaa, Crooks, Sarah, Farzadfar, Farshad, Moghaddam, Sahar Saeedi, Silver, Bahendeka K., Sturua, Lela, Wesseh, Chea Stanford, Stokes, Andrew C., Essien, Utibe R., De Neve, Jan-Walter, Atun, Rifat, Davies, Justine I., Vollmer, Sebastian, Barnighausen, Till W., Ali, Mohammed K., Meigs, James B., Wexler, Deborah J., Manne-Goehler, Jennifer, Teufel, Felix, Seiglie, Jacqueline A., Geldsetzer, Pascal, Theilmann, Michaela, Marcus, Maja E., Ebert, Cara, Arboleda, William Andres Lopez, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K., Bicaba, Brice Wilfried, Brian, Garry, Bovet, Pascal, Dorobantu, Maria, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta M. Adelin, Kagaruki, Gibson B., Karki, Khem B., Labadarios, Demetre, Martins, Joao S., Mayige, Mary T., McClure, Roy Wong, Mwangi, Joseph Kibachio, Mwalim, Omar, Norov, Bolormaa, Crooks, Sarah, Farzadfar, Farshad, Moghaddam, Sahar Saeedi, Silver, Bahendeka K., Sturua, Lela, Wesseh, Chea Stanford, Stokes, Andrew C., Essien, Utibe R., De Neve, Jan-Walter, Atun, Rifat, Davies, Justine I., Vollmer, Sebastian, Barnighausen, Till W., Ali, Mohammed K., Meigs, James B., Wexler, Deborah J., and Manne-Goehler, Jennifer
- Abstract
Background The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings.Methods In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA(1c)]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7.0 mmol/L (126.0 mg/dL) or higher; a random plasma glucose concentration of 11.1 mmol/L (200.0 mg/dL) or higher; or a HbA(1c) of 6.5% (48.0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18.5-22.9 kg/m(2)], upper-normal [23.0-24.9 kg/m(2)], overweight [25.0-29.9 kg/m(2)], or obese [>= 30.0 kg/m(2)]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, strati
- Published
- 2021
9. Cardiovascular disease risk profile and management practices in 45 low-income and middle-income countries:A cross-sectional study of nationally representative individual-level survey data
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Peiris, David, Ghosh, Arpita, Manne-Goehler, Jennifer, Jaacks, Lindsay M., Theilmann, Michaela, Marcus, Maja E., Zhumadilov, Zhaxybay, Tsabedze, Lindiwe, Supiyev, Adil, Silver, Bahendeka K., Sibai, Abla M., Norov, Bolormaa, Mayige, Mary T., Martins, Joao S., Lunet, Nuno, Labadarios, Demetre, Jorgensen, Jutta M.A., Houehanou, Corine, Guwatudde, David, Gurung, Mongal S., Damasceno, Albertino, Aryal, Krishna K., Andall-Brereton, Glennis, Agoudavi, Kokou, McKenzie, Briar, Webster, Jacqui, Atun, Rifat, Bärnighausen, Till, Vollmer, Sebastian, Davies, Justine I., Geldsetzer, Pascal, Peiris, David, Ghosh, Arpita, Manne-Goehler, Jennifer, Jaacks, Lindsay M., Theilmann, Michaela, Marcus, Maja E., Zhumadilov, Zhaxybay, Tsabedze, Lindiwe, Supiyev, Adil, Silver, Bahendeka K., Sibai, Abla M., Norov, Bolormaa, Mayige, Mary T., Martins, Joao S., Lunet, Nuno, Labadarios, Demetre, Jorgensen, Jutta M.A., Houehanou, Corine, Guwatudde, David, Gurung, Mongal S., Damasceno, Albertino, Aryal, Krishna K., Andall-Brereton, Glennis, Agoudavi, Kokou, McKenzie, Briar, Webster, Jacqui, Atun, Rifat, Bärnighausen, Till, Vollmer, Sebastian, Davies, Justine I., and Geldsetzer, Pascal
- Abstract
Background Global cardiovascular disease (CVD) burden is high and rising, especially in low-income and middle-income countries (LMICs). Focussing on 45 LMICs, we aimed to determine (1) the adult population’s median 10-year predicted CVD risk, including its variation within countries by socio-demographic characteristics, and (2) the prevalence of self-reported blood pressure (BP) medication use among those with and without an indication for such medication as per World Health Organization (WHO) guidelines. Methods and findings We conducted a cross-sectional analysis of nationally representative household surveys from 45 LMICs carried out between 2005 and 2017, with 32 surveys being WHO Stepwise Approach to Surveillance (STEPS) surveys. Country-specific median 10-year CVD risk was calculated using the 2019 WHO CVD Risk Chart Working Group non-laboratory-based equations. BP medication indications were based on the WHO Package of Essential Noncommunicable Disease Interventions guidelines. Regression models examined associations between CVD risk, BP medication use, and socio-demographic characteristics. Our complete case analysis included 600,484 adults from 45 countries. Median 10-year CVD risk (interquartile range [IQR]) for males and females was 2.7% (2.3%–4.2%) and 1.6% (1.3%–2.1%), respectively, with estimates indicating the lowest risk in sub-Saharan Africa and highest in Europe and the Eastern Mediterranean. Higher educational attainment and current employment were associated with lower CVD risk in most countries. Of those indicated for BP medication, the median (IQR) percentage taking medication was 24.2% (15.4%–37.2%) for males and 41.6% (23.9%–53.8%) for females. Conversely, a median (IQR) 47.1% (36.1%–58.6%) of all people taking a BP medication were not indicated for such based on CVD risk status. There was no association between BP medication use and socio-demographic characteristics in most of the 45 study countries. Study limitations include variation in
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- 2021
10. Lifetime Prevalence of Cervical Cancer Screening in 55 Low- and Middle-Income Countries
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Lemp, Julia M., primary, De Neve, Jan-Walter, additional, Bussmann, Hermann, additional, Chen, Simiao, additional, Manne-Goehler, Jennifer, additional, Theilmann, Michaela, additional, Marcus, Maja-Emilia, additional, Ebert, Cara, additional, Probst, Charlotte, additional, Tsabedze-Sibanyoni, Lindiwe, additional, Sturua, Lela, additional, Kibachio, Joseph M., additional, Moghaddam, Sahar Saeedi, additional, Martins, Joao S., additional, Houinato, Dismand, additional, Houehanou, Corine, additional, Gurung, Mongal S., additional, Gathecha, Gladwell, additional, Farzadfar, Farshad, additional, Dryden-Peterson, Scott, additional, Davies, Justine I., additional, Atun, Rifat, additional, Vollmer, Sebastian, additional, Bärnighausen, Till, additional, and Geldsetzer, Pascal, additional
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- 2020
- Full Text
- View/download PDF
11. Analysis of attained height and diabetes among 554,122 adults across 25 low- and middle-income countries
- Author
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Teufel, Felix, primary, Geldsetzer, Pascal, primary, Manne-Goehler, Jennifer, primary, Karlsson, Omar, primary, Koncz, Viola, primary, Deckert, Andreas, primary, Theilmann, Michaela, primary, Marcus, Maja-Emilia, primary, Ebert, Cara, primary, Seiglie, Jacqueline A., primary, Agoudavi, Kokou, primary, Andall-Brereton, Glennis, primary, Gathecha, Gladwell, primary, Gurung, Mongal S, primary, Guwatudde, David, primary, Houehanou, Corine, primary, Hwalla, Nahla, primary, Kagaruki, Gibson B, primary, Karki, Khem B, primary, Labadarios, Demetre, primary, Martins, Joao S, primary, Msaidie, Mohamed, primary, Norov, Bolormaa, primary, Sibai, Abla M, primary, Sturua, Lela, primary, Tsabedze, Lindiwe, primary, Wesseh, Chea S, primary, Davies, Justine, primary, Atun, Rifat, primary, Vollmer, Sebastian, primary, Subramanian, SV, primary, Bärnighausen, Till, primary, Jaacks, Lindsay M, primary, and Neve, Jan-Walter De, primary
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- 2020
- Full Text
- View/download PDF
12. Diabetes Prevalence and Its Relationship With Education, Wealth, and BMI in 29 Low- and Middle-Income Countries
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Seiglie, Jacqueline A., primary, Marcus, Maja-Emilia, additional, Ebert, Cara, additional, Prodromidis, Nikolaos, additional, Geldsetzer, Pascal, additional, Theilmann, Michaela, additional, Agoudavi, Kokou, additional, Andall-Brereton, Glennis, additional, Aryal, Krishna K., additional, Bicaba, Brice Wilfried, additional, Bovet, Pascal, additional, Brian, Garry, additional, Dorobantu, Maria, additional, Gathecha, Gladwell, additional, Gurung, Mongal Singh, additional, Guwatudde, David, additional, Msaidié, Mohamed, additional, Houehanou, Corine, additional, Houinato, Dismand, additional, Jorgensen, Jutta Mari Adelin, additional, Kagaruki, Gibson B., additional, Karki, Khem B., additional, Labadarios, Demetre, additional, Martins, Joao S., additional, Mayige, Mary T., additional, Wong-McClure, Roy, additional, Mwangi, Joseph Kibachio, additional, Mwalim, Omar, additional, Norov, Bolormaa, additional, Quesnel-Crooks, Sarah, additional, Silver, Bahendeka K., additional, Sturua, Lela, additional, Tsabedze, Lindiwe, additional, Wesseh, Chea Stanford, additional, Stokes, Andrew, additional, Atun, Rifat, additional, Davies, Justine I., additional, Vollmer, Sebastian, additional, Bärnighausen, Till W., additional, Jaacks, Lindsay M., additional, Meigs, James B., additional, Wexler, Deborah J., additional, and Manne-Goehler, Jennifer, additional
- Published
- 2020
- Full Text
- View/download PDF
13. The state of hypertension care in 44 low-income and middle-income countries: a cross-sectional study of nationally representative individual-level data from 1·1 million adults
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Geldsetzer, Pascal, primary, Manne-Goehler, Jennifer, additional, Marcus, Maja-Emilia, additional, Ebert, Cara, additional, Zhumadilov, Zhaxybay, additional, Wesseh, Chea S, additional, Tsabedze, Lindiwe, additional, Supiyev, Adil, additional, Sturua, Lela, additional, Bahendeka, Silver K, additional, Sibai, Abla M, additional, Quesnel-Crooks, Sarah, additional, Norov, Bolormaa, additional, Mwangi, Kibachio J, additional, Mwalim, Omar, additional, Wong-McClure, Roy, additional, Mayige, Mary T, additional, Martins, Joao S, additional, Lunet, Nuno, additional, Labadarios, Demetre, additional, Karki, Khem B, additional, Kagaruki, Gibson B, additional, Jorgensen, Jutta M A, additional, Hwalla, Nahla C, additional, Houinato, Dismand, additional, Houehanou, Corine, additional, Msaidié, Mohamed, additional, Guwatudde, David, additional, Gurung, Mongal S, additional, Gathecha, Gladwell, additional, Dorobantu, Maria, additional, Damasceno, Albertino, additional, Bovet, Pascal, additional, Bicaba, Brice W, additional, Aryal, Krishna K, additional, Andall-Brereton, Glennis, additional, Agoudavi, Kokou, additional, Stokes, Andrew, additional, Davies, Justine I, additional, Bärnighausen, Till, additional, Atun, Rifat, additional, Vollmer, Sebastian, additional, and Jaacks, Lindsay M, additional
- Published
- 2019
- Full Text
- View/download PDF
14. Consumption of Fruits and Vegetables Among Individuals 15 Years and Older in 28 Low- and Middle-Income Countries
- Author
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Frank, Sarah M, primary, Webster, Jacqui, additional, McKenzie, Briar, additional, Geldsetzer, Pascal, additional, Manne-Goehler, Jennifer, additional, Andall-Brereton, Glennis, additional, Houehanou, Corine, additional, Houinato, Dismand, additional, Gurung, Mongal Singh, additional, Bicaba, Brice Wilfried, additional, McClure, Roy Wong, additional, Supiyev, Adil, additional, Zhumadilov, Zhaxybay, additional, Stokes, Andrew, additional, Labadarios, Demetre, additional, Sibai, Abla Mehio, additional, Norov, Bolormaa, additional, Aryal, Krishna K, additional, Karki, Khem Bahadur, additional, Kagaruki, Gibson B, additional, Mayige, Mary T, additional, Martins, Joao S, additional, Atun, Rifat, additional, Bärnighausen, Till, additional, Vollmer, Sebastian, additional, and Jaacks, Lindsay M, additional
- Published
- 2019
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- View/download PDF
15. Understanding HRH recruitment in post-conflict settings: an analysis of central-level policies and processes in Timor-Leste (1999–2018)
- Author
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Bertone, Maria Paola, primary, Martins, Joao S., additional, Pereira, Sara M., additional, Martineau, Tim, additional, and Alonso-Garbayo, Alvaro, additional
- Published
- 2018
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- View/download PDF
16. Malaria control in Timor-Leste during a period of political instability: what lessons can be learned?
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Martins Nelson, Zwi Anthony B, Martins Joao S, and Kelly Paul M
- Subjects
Special situations and conditions ,RC952-1245 ,Medical emergencies. Critical care. Intensive care. First aid ,RC86-88.9 - Abstract
Abstract Background Malaria is a major global health problem, often exacerbated by political instability, conflict, and forced migration. Objectives To examine the impact of political upheaval and population displacement in Timor-Leste (2006) on malaria in the country. Method Case study approach drawing on both qualitative and quantitative methods including document reviews, in-depth interviews, focus group discussions, site visits and analysis of routinely collected data. Findings The conflict had its most profound impact on Dili, the capital city, in which tens of thousands of people were displaced from their homes. The conflict interrupted routine malaria service programs and training, but did not lead to an increase in malaria incidence. Interventions covering treatment, insecticide treated nets (ITN) distribution, vector control, surveillance and health promotion were promptly organized for internally displaced people (IDPs) and routine health services were maintained. Vector control interventions were focused on IDP camps in the city rather than on the whole community. The crisis contributed to policy change with the introduction of Rapid Diagnostic Tests and artemether-lumefantrine for treatment. Conclusions Although the political crisis affected malaria programs there were no outbreaks of malaria. Emergency responses were quickly organized and beneficial long term changes in treatment and diagnosis were facilitated.
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- 2009
- Full Text
- View/download PDF
17. Determinants of health care utilisation: the case of Timor-Leste
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Guinness, Lorna, primary, Paul, Repon C, additional, Martins, Joao S, additional, Asante, Auguste, additional, Price, Jennifer A, additional, Hayen, Andrew, additional, Jan, Stephen, additional, Soares, Ana, additional, and Wiseman, Virginia, additional
- Published
- 2018
- Full Text
- View/download PDF
18. “I go I die, I stay I die, better to stay and die in my house”: understanding the barriers to accessing health care in Timor-Leste
- Author
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Price, Jennifer A., primary, Soares, Ana I. F. Sousa, additional, Asante, Augustine D., additional, Martins, Joao S., additional, Williams, Kate, additional, and Wiseman, Virginia L., additional
- Published
- 2016
- Full Text
- View/download PDF
19. Malaria control in Timor-Leste during a period of political instability: what lessons can be learned?
- Author
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Martins, Joao S, Zwi, Anthony B, Martins, Nelson, Kelly, Paul M, Martins, Joao S, Zwi, Anthony B, Martins, Nelson, and Kelly, Paul M
- Abstract
BACKGROUND Malaria is a major global health problem, often exacerbated by political instability, conflict, and forced migration. OBJECTIVES To examine the impact of political upheaval and population displacement in Timor-Leste (2006) on malaria in the country. METHOD Case study approach drawing on both qualitative and quantitative methods including document reviews, in-depth interviews, focus group discussions, site visits and analysis of routinely collected data. FINDINGS The conflict had its most profound impact on Dili, the capital city, in which tens of thousands of people were displaced from their homes. The conflict interrupted routine malaria service programs and training, but did not lead to an increase in malaria incidence. Interventions covering treatment, insecticide treated nets (ITN) distribution, vector control, surveillance and health promotion were promptly organized for internally displaced people (IDPs) and routine health services were maintained. Vector control interventions were focused on IDP camps in the city rather than on the whole community. The crisis contributed to policy change with the introduction of Rapid Diagnostic Tests and artemether-lumefantrine for treatment. CONCLUSIONS Although the political crisis affected malaria programs there were no outbreaks of malaria. Emergency responses were quickly organized and beneficial long term changes in treatment and diagnosis were facilitated.
- Published
- 2009
20. Changing the malaria treatment protocol policy in Timor-Leste: an examination of context, process, and actors' involvement.
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Martins, Joao S, Zwi, Anthony B, Hobday, Karen, Bonaparte, Fernando, Kelly, Paul M, and Martins, João S
- Abstract
In 2007 Timor-Leste, a malaria endemic country, changed its Malaria Treatment Protocol for uncomplicated falciparum malaria from sulphadoxine-pyrimethamine to artemether-lumefantrine. The change in treatment policy was based on the rise in morbidity due to malaria and perception of increasing drug resistance. Despite a lack of nationally available evidence on drug resistance, the Ministry of Health decided to change the protocol. The policy process leading to this change was examined through a qualitative study on how the country developed its revised treatment protocol for malaria. This process involved many actors and was led by the Timor-Leste Ministry of Health and the WHO country office. This paper examines the challenges and opportunities identified during this period of treatment protocol change. [ABSTRACT FROM AUTHOR]
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- 2013
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21. Analysis of Attained Height and Diabetes Among 554,122 Adults Across 25 Low- and Middle-Income Countries.
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Teufel F, Geldsetzer P, Manne-Goehler J, Karlsson O, Koncz V, Deckert A, Theilmann M, Marcus ME, Ebert C, Seiglie JA, Agoudavi K, Andall-Brereton G, Gathecha G, Gurung MS, Guwatudde D, Houehanou C, Hwalla N, Kagaruki GB, Karki KB, Labadarios D, Martins JS, Msaidie M, Norov B, Sibai AM, Sturua L, Tsabedze L, Wesseh CS, Davies J, Atun R, Vollmer S, Subramanian SV, Bärnighausen T, Jaacks LM, and De Neve JW
- Subjects
- Adult, Cross-Sectional Studies, Female, Humans, Income statistics & numerical data, Male, Middle Aged, Poverty statistics & numerical data, Prevalence, Socioeconomic Factors, Body Height, Developing Countries statistics & numerical data, Diabetes Mellitus, Type 2 epidemiology
- Abstract
Objective: The prevalence of type 2 diabetes is rising rapidly in low-income and middle-income countries (LMICs), but the factors driving this rapid increase are not well understood. Adult height, in particular shorter height, has been suggested to contribute to the pathophysiology and epidemiology of diabetes and may inform how adverse environmental conditions in early life affect diabetes risk. We therefore systematically analyzed the association of adult height and diabetes across LMICs, where such conditions are prominent., Research Design and Methods: We pooled individual-level data from nationally representative surveys in LMICs that included anthropometric measurements and diabetes biomarkers. We calculated odds ratios (ORs) for the relationship between attained adult height and diabetes using multilevel mixed-effects logistic regression models. We estimated ORs for the pooled sample, major world regions, and individual countries, in addition to stratifying all analyses by sex. We examined heterogeneity by individual-level characteristics., Results: Our sample included 554,122 individuals across 25 population-based surveys. Average height was 161.7 cm (95% CI 161.2-162.3), and the crude prevalence of diabetes was 7.5% (95% CI 6.9-8.2). We found no relationship between adult height and diabetes across LMICs globally or in most world regions. When stratifying our sample by country and sex, we found an inverse association between adult height and diabetes in 5% of analyses (2 out of 50). Results were robust to alternative model specifications., Conclusions: Adult height is not associated with diabetes across LMICs. Environmental factors in early life reflected in attained adult height likely differ from those predisposing individuals for diabetes., (© 2020 by the American Diabetes Association.)
- Published
- 2020
- Full Text
- View/download PDF
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