Abstract
Background: Approximately 80% of the 463 million adults worldwide with diabetes live in low-income and middle-income countries (LMICs). A major obstacle to designing evidence-based policies to improve diabetes outcomes in LMICs is the scarce availability of nationally representative data on the current patterns of treatment coverage. The objectives of this study were to estimate the proportion of adults with diabetes in LMICs who receive coverage of recommended pharmacological and non-pharmacological diabetes treatment; and to describe country-level and individual-level characteristics that are associated with treatment.
Methods: We did a cross-sectional analysis of pooled, individual data from 55 nationally representative surveys in LMICs. Our primary outcome of self-reported diabetes treatment coverage was based on population-level monitoring indicators recommended in the 2020 WHO Package of Essential Noncommunicable Disease Interventions. Surveys were included if they were done in 2008 or after in an LMIC, as classified by the World Bank in the year the survey was done; were nationally representative; had individual-level data; contained a diabetes biomarker (fasting glucose, random glucose, or glycated haemoglobin); and had data on one or more diabetes treatments. Our sample included non-pregnant individuals with an available diabetes biomarker who were at least 25 years of age. We assessed coverage of three pharmacological and three non-pharmacological treatments among people with diabetes. At the country level, we estimated the proportion of individuals reporting coverage by per-capita gross national income and geographical region. At the individual level, we used logistic regression models to assess coverage along several key individual characteristics including sex, age, body-mass index, wealth quintile, and educational attainment. In the primary analysis, we scaled sample weights such that countries were weighted equally.
Findings: The final pooled sample from the 55 LMICs included 680 102 total individuals and 37 094 individuals with diabetes. Using equal weights for each country, diabetes prevalence was 9·0% (95% CI 8·7–9·4), with 43·9% (41·9–45·9) reporting a previous diabetes diagnosis. Overall, 4·6% (3·9–5·4) of individuals with diabetes self-reported meeting need for all treatments recommended for them. Coverage of glucose-lowering medication was 50·5% (48·6–52·5); antihypertensive medication was 41·3% (39·3–43·3); cholesterol-lowering medication was 6·3% (5·5–7·2); diet counselling was 32·2% (30·7–33·7); exercise counselling was 28·2% (26·6–29·8); and weight-loss counselling was 31·5% (29·3–33·7). Countries at higher-income levels tended to have greater coverage. Female sex and higher age, body-mass index, educational attainment, and household wealth were also associated with greater coverage.
Interpretation: Fewer than one in ten people with diabetes in LMICs receive coverage of guideline-based comprehensive diabetes treatment. Scaling up the capacity of health systems to deliver treatment not only to lower glucose but also to address cardiovascular disease risk factors, such as hypertension and high cholesterol, are urgent global diabetes priorities.
Funding: National Clinician Scholars Program at the University of Michigan Institute for Healthcare Policy & Innovation, National Institute of Diabetes and Digestive and Kidney Diseases, Harvard Catalyst, and National Center for Advancing Translational Sciences of the National Institutes of Health.
Methods: We did a cross-sectional analysis of pooled, individual data from 55 nationally representative surveys in LMICs. Our primary outcome of self-reported diabetes treatment coverage was based on population-level monitoring indicators recommended in the 2020 WHO Package of Essential Noncommunicable Disease Interventions. Surveys were included if they were done in 2008 or after in an LMIC, as classified by the World Bank in the year the survey was done; were nationally representative; had individual-level data; contained a diabetes biomarker (fasting glucose, random glucose, or glycated haemoglobin); and had data on one or more diabetes treatments. Our sample included non-pregnant individuals with an available diabetes biomarker who were at least 25 years of age. We assessed coverage of three pharmacological and three non-pharmacological treatments among people with diabetes. At the country level, we estimated the proportion of individuals reporting coverage by per-capita gross national income and geographical region. At the individual level, we used logistic regression models to assess coverage along several key individual characteristics including sex, age, body-mass index, wealth quintile, and educational attainment. In the primary analysis, we scaled sample weights such that countries were weighted equally.
Findings: The final pooled sample from the 55 LMICs included 680 102 total individuals and 37 094 individuals with diabetes. Using equal weights for each country, diabetes prevalence was 9·0% (95% CI 8·7–9·4), with 43·9% (41·9–45·9) reporting a previous diabetes diagnosis. Overall, 4·6% (3·9–5·4) of individuals with diabetes self-reported meeting need for all treatments recommended for them. Coverage of glucose-lowering medication was 50·5% (48·6–52·5); antihypertensive medication was 41·3% (39·3–43·3); cholesterol-lowering medication was 6·3% (5·5–7·2); diet counselling was 32·2% (30·7–33·7); exercise counselling was 28·2% (26·6–29·8); and weight-loss counselling was 31·5% (29·3–33·7). Countries at higher-income levels tended to have greater coverage. Female sex and higher age, body-mass index, educational attainment, and household wealth were also associated with greater coverage.
Interpretation: Fewer than one in ten people with diabetes in LMICs receive coverage of guideline-based comprehensive diabetes treatment. Scaling up the capacity of health systems to deliver treatment not only to lower glucose but also to address cardiovascular disease risk factors, such as hypertension and high cholesterol, are urgent global diabetes priorities.
Funding: National Clinician Scholars Program at the University of Michigan Institute for Healthcare Policy & Innovation, National Institute of Diabetes and Digestive and Kidney Diseases, Harvard Catalyst, and National Center for Advancing Translational Sciences of the National Institutes of Health.
| Original language | English |
|---|---|
| Pages (from-to) | e340-e351 |
| Number of pages | 12 |
| Journal | The Lancet Healthy Longevity |
| Volume | 2 |
| Issue number | 6 |
| Early online date | 21 May 2021 |
| DOIs | |
| Publication status | Published - Jun 2021 |
Bibliographical note
Funding Information:DF was supported by the National Clinician Scholars Program at the University of Michigan Institute for Healthcare Policy & Innovation. JAS was supported by grant number T32DK007028 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and by grant number 5KL2TR002542–03 (Harvard Catalyst). PG was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number KL2TR003143 . MH was supported by grant number P30DK092926 (Michigan Center for Diabetes Translational Research) from the NIDDK. JMG was supported by grant K23 DK125162 from the NIDDK. The contents of this research are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND license
ASJC Scopus subject areas
- Geriatrics and Gerontology
- Health(social science)
- Psychiatry and Mental health
- Family Practice
