Health system performance for people with diabetes in 28 low- and middle-income countries: a cross-sectional study of nationally representative surveys

Research output: Contribution to journalArticle

Authors

  • Jennifer Manne-Goehler
  • Pascal Geldsetzer
  • Kokou Agoudavi
  • Glennis Andall-Brereton
  • Krishna K Aryal
  • Brice Wilfried Bicaba
  • Pascal Bovet
  • Garry Brian
  • Maria Dorobantu
  • Gladwell Gathecha
  • Mongal Singh Gurung
  • David Guwatudde
  • Mohamed Msaidie
  • Corine Houehanou
  • Dismand Houinato
  • Jutta Mari Adelin Jorgensen
  • Gibson B Kagaruki
  • Khem B Karki
  • Demetre Labadarios
  • Joao S Martins
  • Mary T Mayige
  • Roy Wong McClure
  • Omar Mwalim
  • Joseph Kibachio Mwangi
  • Bolormaa Norov
  • Sarah Quesnel-Crooks
  • Bahendeka K Silver
  • Lela Sturua
  • Lindiwe Tsabedze
  • Chea Stanford Wesseh
  • Andrew Stokes
  • Maja Marcus
  • Cara Ebert
  • Sebastian Vollmer
  • Rifat Atun
  • Till W Bärnighausen
  • Lindsay M Jaacks

Colleges, School and Institutes

External organisations

  • Divison of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
  • Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.
  • Togo Ministry of Health, Lome, Togo.
  • Non-Communicable Diseases, Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago.
  • Nepal Health Research Council, Kathmandu, Nepal.
  • Direction de la Lutte Contre la Maladie, Ministère de la Santé, Ouagadougou, Burkina Faso.
  • Institute of Social and Preventive Medicine, Lausanne, Switzerland.
  • The Fred Hollows Foundation NZ, Auckland, New Zealand.
  • Cardiology Department, Emergency Hospital of Bucharest, Bucharest, Romania.
  • Division of Non-Communicable Diseases, Kenya Ministry of Health, Nairobi, Kenya.
  • Health Research and Epidemiology Unit, Ministry of Health, Thimphu, Bhutan.
  • Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda.
  • Comoros Ministry of Health, Solidarity, Social Cohesion and Gender, Moroni, Comoros.
  • Laboratory of Epidemiology of Chronic and Neurological Diseases, Faculty of Health Sciences, University of Abomey-Calavi, Cotonou, Benin.
  • Partners in Health, Boston, Massachusetts, United States of America.
  • National Institute for Medical Research, Dar es Salaam, Tanzania.
  • Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa.
  • Faculty of Medicine and Health Sciences, National University of East Timor, Dili, Timor-Leste.
  • Office of Epidemiology and Surveillance, Caja Costarricense de Seguro Social, San Jose, Costa Rica.
  • Zanzibar Ministry of Health, Mnazi Mmoja, Zanzibar.
  • National Center for Public Health, Ulaanbaatar, Mongolia.
  • St. Francis Hospital, Kampala, Uganda.
  • Non-Communicable Disease Department, National Center for Disease Control and Public Health, Tbilisi, Georgia.
  • Swaziland Ministry of Health, Mbabane, Swaziland.
  • Liberia Ministry of Health, Monrovia, Liberia.
  • Boston University Center for Global Health and Development, Boston, Massachusetts, United States of America.
  • Department of Economics and Centre for Modern Indian Studies, University of Göttingen, Göttingen, Germany.
  • MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • Centre for Childhood Cancer Survivor Studies, Institute of Applied Health Research, University of Birmingham, Birmingham, B15 2TT, United Kingdom.
  • Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Institute of Public Health, Heidelberg University, Heidelberg, Germany; Africa Health Research Institute, Mtubatuba, South Africa.
  • Public Health Foundation of India, New Delhi, India.

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 ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 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.

Details

Original languageEnglish
Article numbere1002751
Number of pages21
JournalPLoS Medicine
Volume16
Issue number3
Publication statusPublished - 1 Mar 2019

ASJC Scopus subject areas