Browsing by Author "Luisa Campos Caldeira Brant"
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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 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.