Jennifer Manne-Goehler1, Rifat Atun2, Andrew Stokes3, Alexander Goehler4, Dismand Houinato5, Corine Houehanou5, Mohamed Msaidie Salimani Hambou6, Benjamin Longo Mbenza7, Eugène Sobngwi8, Naby Balde9, Joseph Kibachio Mwangi10, Gladwell Gathecha10, Paul Waweru Ngugi11, C Stanford Wesseh12, Albertino Damasceno13, Nuno Lunet14, Pascal Bovet15, Demetre Labadarios16, Khangelani Zuma16, Mary Mayige17, Gibson Kagaruki17, Kaushik Ramaiya18, Kokou Agoudavi19, David Guwatudde20, Silver K Bahendeka21, Gerald Mutungi22, Pascal Geldsetzer2, Naomi S Levitt23, Joshua A Salomon2, John S Yudkin24, Sebastian Vollmer25, Till Bärnighausen26. 1. Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA. Electronic address: jmanne@post.harvard.edu. 2. Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA. 3. Boston University Center for Global Health and Development, Boston, MA, USA. 4. Department of Radiology, Yale University School of Medicine, New Haven, CT, USA. 5. Faculty of Health Science, University of Abomey-Calavi, Cotonou, Benin. 6. Moroni, Union of Comoros, Walter Sisulu University, Mthatha, South Africa. 7. Department of Family Medicine, Faculty of Health Sciences, Walter Sisulu University, Mthatha, South Africa. 8. Hopital Central de Yaounde Faculte de Medecine et des Sciences Biomedicales et Centre de Biotechnologie, Yaoundé, Cameroon. 9. Department of Endocrinology and Diabetes, Donka University Hospital, Conakry, Guinea; NCD Department, Ministry of Health, Conakry, Guinea. 10. Division of Non-Communicable Diseases, Kenya Ministry of Health, Nairobi, Kenya. 11. Kenya National Bureau of Statistics, Nairobi, Kenya. 12. Liberia Ministry of Health, Monrovia, Liberia. 13. Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique. 14. Department of Clinical Epidemiology, Predictive Medicine and Public Health, Faculty of Medicine of the University of Porto and EpiUnit, Institute of Public Health of the University of Porto, Portugal. 15. Institute of Social and Preventive Medicine, Lausanne, Switzerland; Ministry of Health, Victoria, Seychelles. 16. Human Sciences Research Council, Cape Town, South Africa. 17. National Institute for Medical Research, Dar es Salaam, Tanzania. 18. Hindu Mandal Hospital, Dar es Salaam, Tanzania. 19. Togo Ministry of Health, Lome, Togo. 20. Department of Epidemiology and Biostatistics, Makerere University School of Public Health, Kampala, Uganda. 21. St Francis Hospital Nsambya, Kampala, Uganda. 22. Section on Non-Communicable Disease, Uganda Ministry of Health, Kampala, Uganda. 23. Department of Medicine, University of Cape Town, Cape Town, South Africa. 24. Division of Medicine, University College London, London, UK. 25. Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Economics, University of Göttingen, Göttingen, Germany. 26. Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Africa Health Research Institute, Somkhele, South Africa; Insitute of Public Health, Faculty of Medicine, Heidelberg University, Heidelberg, Germany.
Abstract
BACKGROUND: Despite widespread recognition that the burden of diabetes is rapidly growing in many countries in sub-Saharan Africa, nationally representative estimates of unmet need for diabetes diagnosis and care are in short supply for the region. We use national population-based survey data to quantify diabetes prevalence and met and unmet need for diabetes diagnosis and care in 12 countries in sub-Saharan Africa. We further estimate demographic and economic gradients of met need for diabetes diagnosis and care. METHODS: We did a pooled analysis of individual-level data from nationally representative population-based surveys that met the following inclusion criteria: the data were collected during 2005-15; the data were made available at the individual level; a biomarker for diabetes was available in the dataset; and the dataset included information on use of core health services for diabetes diagnosis and care. We first quantified the population in need of diabetes diagnosis and care by estimating the prevalence of diabetes across the surveys; we also quantified the prevalence of overweight and obesity, as a major risk factor for diabetes and an indicator of need for diabetes screening. Second, we determined the level of met need for diabetes diagnosis, preventive counselling, and treatment in both the diabetic and the overweight and obese population. Finally, we did survey fixed-effects regressions to establish the demographic and economic gradients of met need for diabetes diagnosis, counselling, and treatment. FINDINGS: We pooled data from 12 nationally representative population-based surveys in sub-Saharan Africa, representing 38 311 individuals with a biomarker measurement for diabetes. Across the surveys, the median prevalence of diabetes was 5% (range 2-14) and the median prevalence of overweight or obesity was 27% (range 16-68). We estimated seven measures of met need for diabetes-related care across the 12 surveys: (1) percentage of the overweight or obese population who received a blood glucose measurement (median 22% [IQR 11-37]); and percentage of the diabetic population who reported that they (2) had ever received a blood glucose measurement (median 36% [IQR 27-63]); (3) had ever been told that they had diabetes (median 27% [IQR 22-51]); (4) had ever been counselled to lose weight (median 15% [IQR 13-23]); (5) had ever been counselled to exercise (median 15% [IQR 11-30]); (6) were using oral diabetes drugs (median 25% [IQR 18-42]); and (7) were using insulin (median 11% [IQR 6-13]). Compared with those aged 15-39 years, the adjusted odds of met need for diabetes diagnosis (measures 1-3) were 2·22 to 3·53 (40-54 years) and 3·82 to 5·01 (≥55 years) times higher. The adjusted odds of met need for diabetes diagnosis also increased consistently with educational attainment and were between 3·07 and 4·56 higher for the group with 8 years or more of education than for the group with less than 1 year of education. Finally, need for diabetes care was significantly more likely to be met (measures 4-7) in the oldest age and highest educational groups. INTERPRETATION: Diabetes has already reached high levels of prevalence in several countries in sub-Saharan Africa. Large proportions of need for diabetes diagnosis and care in the region remain unmet, but the patterns of unmet need vary widely across the countries in our sample. Novel health policies and programmes are urgently needed to increase awareness of diabetes and to expand coverage of preventive counselling, diagnosis, and linkage to diabetes care. Because the probability of met need for diabetes diagnosis and care consistently increases with age and educational attainment, policy makers should pay particular attention to improved access to diabetes services for young adults and people with low educational attainment. FUNDING: None.
BACKGROUND: Despite widespread recognition that the burden of diabetes is rapidly growing in many countries in sub-Saharan Africa, nationally representative estimates of unmet need for diabetes diagnosis and care are in short supply for the region. We use national population-based survey data to quantify diabetes prevalence and met and unmet need for diabetes diagnosis and care in 12 countries in sub-Saharan Africa. We further estimate demographic and economic gradients of met need for diabetes diagnosis and care. METHODS: We did a pooled analysis of individual-level data from nationally representative population-based surveys that met the following inclusion criteria: the data were collected during 2005-15; the data were made available at the individual level; a biomarker for diabetes was available in the dataset; and the dataset included information on use of core health services for diabetes diagnosis and care. We first quantified the population in need of diabetes diagnosis and care by estimating the prevalence of diabetes across the surveys; we also quantified the prevalence of overweight and obesity, as a major risk factor for diabetes and an indicator of need for diabetes screening. Second, we determined the level of met need for diabetes diagnosis, preventive counselling, and treatment in both the diabetic and the overweight and obese population. Finally, we did survey fixed-effects regressions to establish the demographic and economic gradients of met need for diabetes diagnosis, counselling, and treatment. FINDINGS: We pooled data from 12 nationally representative population-based surveys in sub-Saharan Africa, representing 38 311 individuals with a biomarker measurement for diabetes. Across the surveys, the median prevalence of diabetes was 5% (range 2-14) and the median prevalence of overweight or obesity was 27% (range 16-68). We estimated seven measures of met need for diabetes-related care across the 12 surveys: (1) percentage of the overweight or obese population who received a blood glucose measurement (median 22% [IQR 11-37]); and percentage of the diabetic population who reported that they (2) had ever received a blood glucose measurement (median 36% [IQR 27-63]); (3) had ever been told that they had diabetes (median 27% [IQR 22-51]); (4) had ever been counselled to lose weight (median 15% [IQR 13-23]); (5) had ever been counselled to exercise (median 15% [IQR 11-30]); (6) were using oral diabetes drugs (median 25% [IQR 18-42]); and (7) were using insulin (median 11% [IQR 6-13]). Compared with those aged 15-39 years, the adjusted odds of met need for diabetes diagnosis (measures 1-3) were 2·22 to 3·53 (40-54 years) and 3·82 to 5·01 (≥55 years) times higher. The adjusted odds of met need for diabetes diagnosis also increased consistently with educational attainment and were between 3·07 and 4·56 higher for the group with 8 years or more of education than for the group with less than 1 year of education. Finally, need for diabetes care was significantly more likely to be met (measures 4-7) in the oldest age and highest educational groups. INTERPRETATION:Diabetes has already reached high levels of prevalence in several countries in sub-Saharan Africa. Large proportions of need for diabetes diagnosis and care in the region remain unmet, but the patterns of unmet need vary widely across the countries in our sample. Novel health policies and programmes are urgently needed to increase awareness of diabetes and to expand coverage of preventive counselling, diagnosis, and linkage to diabetes care. Because the probability of met need for diabetes diagnosis and care consistently increases with age and educational attainment, policy makers should pay particular attention to improved access to diabetes services for young adults and people with low educational attainment. FUNDING: None.
Authors: Margaret E Kruk; Anna D Gage; Catherine Arsenault; Keely Jordan; Hannah H Leslie; Sanam Roder-DeWan; Olusoji Adeyi; Pierre Barker; Bernadette Daelmans; Svetlana V Doubova; Mike English; Ezequiel García-Elorrio; Frederico Guanais; Oye Gureje; Lisa R Hirschhorn; Lixin Jiang; Edward Kelley; Ephrem Tekle Lemango; Jerker Liljestrand; Address Malata; Tanya Marchant; Malebona Precious Matsoso; John G Meara; Manoj Mohanan; Youssoupha Ndiaye; Ole F Norheim; K Srinath Reddy; Alexander K Rowe; Joshua A Salomon; Gagan Thapa; Nana A Y Twum-Danso; Muhammad Pate Journal: Lancet Glob Health Date: 2018-09-05 Impact factor: 26.763
Authors: Julian T Hertz; Francis M Sakita; Preeti Manavalan; Deng B Madut; Nathan M Thielman; Blandina T Mmbaga; Catherine A Staton; Sophie W Galson Journal: Ethn Dis Date: 2019-10-17 Impact factor: 1.847
Authors: Kenneth A Fleming; Susan Horton; Michael L Wilson; Rifat Atun; Kristen DeStigter; John Flanigan; Shahin Sayed; Pierrick Adam; Bertha Aguilar; Savvas Andronikou; Catharina Boehme; William Cherniak; Annie Ny Cheung; Bernice Dahn; Lluis Donoso-Bach; Tania Douglas; Patricia Garcia; Sarwat Hussain; Hari S Iyer; Mikashmi Kohli; Alain B Labrique; Lai-Meng Looi; John G Meara; John Nkengasong; Madhukar Pai; Kara-Lee Pool; Kaushik Ramaiya; Lee Schroeder; Devanshi Shah; Richard Sullivan; Bien-Soo Tan; Kamini Walia Journal: Lancet Date: 2021-10-06 Impact factor: 79.321
Authors: 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; Gastón 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-Goehler Journal: Diabetes Care Date: 2022-09-01 Impact factor: 17.152
Authors: Pascal Geldsetzer; Jennifer Manne-Goehler; Michaela Theilmann; Justine I Davies; Ashish Awasthi; Sebastian Vollmer; Lindsay M Jaacks; Till Bärnighausen; Rifat Atun Journal: JAMA Intern Med Date: 2018-03-01 Impact factor: 21.873
Authors: C Bamuya; J C Correia; E M Brady; D Beran; D Harrington; A Damasceno; A M Crampin; Ana Magaia; Naomi Levitt; M J Davies; M Hadjiconstantinou Journal: BMC Public Health Date: 2021-07-08 Impact factor: 3.295