Publications by authors named "Kokou Agoudavi"

9 Publications

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Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model.

Lancet Glob Health 2021 Sep 22. Epub 2021 Sep 22.

Institute for Applied Health Research, University of Birmingham, Birmingham, UK; Centre for Global Surgery, Department of Global Health, Stellenbosch University, Cape Town, South Africa; Medical Research Council-Wits University Rural Public Health and Health Transitions Research Unit, Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.

Background: Given the increasing prevalence of diabetes in low-income and middle-income countries (LMICs), we aimed to estimate the health and cost implications of achieving different targets for diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among LMICs.

Methods: We constructed a microsimulation model to estimate disability-adjusted life-years (DALYs) lost and health-care costs of diagnosis, treatment, and control of blood pressure, dyslipidaemia, and glycaemia among people with diabetes in LMICs. We used individual participant data-specifically from the subset of people who were defined as having any type of diabetes by WHO standards-from nationally representative, cross-sectional surveys (2006-18) spanning 15 world regions to estimate the baseline 10-year risk of atherosclerotic cardiovascular disease (defined as fatal and non-fatal myocardial infarction and stroke), heart failure (ejection fraction of <40%, with New York Heart Association class III or IV functional limitations), end-stage renal disease (defined as an estimated glomerular filtration rate <15 mL/min per 1·73 m or needing dialysis or transplant), retinopathy with severe vision loss (<20/200 visual acuity as measured by the Snellen chart), and neuropathy with pressure sensation loss (assessed by the Semmes-Weinstein 5·07/10 g monofilament exam). We then used data from meta-analyses of randomised controlled trials to estimate the reduction in risk and the WHO OneHealth tool to estimate costs in reaching either 60% or 80% of diagnosis, treatment initiation, and control targets for blood pressure, dyslipidaemia, and glycaemia recommended by WHO guidelines. Costs were updated to 2020 International Dollars, and both costs and DALYs were computed over a 10-year policy planning time horizon at a 3% annual discount rate.

Findings: We obtained data from 23 678 people with diabetes from 67 countries. The median estimated 10-year risk was 10·0% (IQR 4·0-18·0) for cardiovascular events, 7·8% (5·1-11·8) for neuropathy with pressure sensation loss, 7·2% (5·6-9·4) for end-stage renal disease, 6·0% (4·2-8·6) for retinopathy with severe vision loss, and 2·6% (1·2-5·3) for congestive heart failure. A target of 80% diagnosis, 80% treatment, and 80% control would be expected to reduce DALYs lost from diabetes complications from a median population-weighted loss to 1097 DALYs per 1000 population over 10 years (IQR 1051-1155), relative to a baseline of 1161 DALYs, primarily from reduced cardiovascular events (down from a median of 143 to 117 DALYs per 1000 population) due to blood pressure and statin treatment, with comparatively little effect from glycaemic control. The target of 80% diagnosis, 80% treatment, and 80% control would be expected to produce an overall incremental cost-effectiveness ratio of US$1362 per DALY averted (IQR 1304-1409), with the majority of decreased costs from reduced cardiovascular event management, counterbalanced by increased costs for blood pressure and statin treatment, producing an overall incremental cost-effectiveness ratio of $1362 per DALY averted (IQR 1304-1409).

Interpretation: Reducing complications from diabetes in LMICs is likely to require a focus on scaling up blood pressure and statin medication treatment initiation and blood pressure medication titration rather than focusing on increasing screening to increase diabetes diagnosis, or a glycaemic treatment and control among people with diabetes.

Funding: None.
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http://dx.doi.org/10.1016/S2214-109X(21)00340-5DOI Listing
September 2021

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.

Lancet 2021 07;398(10296):238-248

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

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]); 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 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], upper-normal [23·0-24·9 kg/m], overweight [25·0-29·9 kg/m], or obese [≥30·0 kg/m]), 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, stratified by sex and geographical region.

Findings: Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m among men in east, south, and southeast Asia to 28·3 kg/m among women in the Middle East and north Africa and in Latin America and the Caribbean.

Interpretation: The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines.

Funding: Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.
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http://dx.doi.org/10.1016/S0140-6736(21)00844-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336025PMC
July 2021

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.

PLoS Med 2021 03 4;18(3):e1003485. Epub 2021 Mar 4.

Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.

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.
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http://dx.doi.org/10.1371/journal.pmed.1003485DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7932723PMC
March 2021

Analysis of Attained Height and Diabetes Among 554,122 Adults Across 25 Low- and Middle-Income Countries.

Diabetes Care 2020 10 6;43(10):2403-2410. Epub 2020 Aug 6.

Department of Economics and Centre for Modern Indian Studies, Georg-August-Universität Göttingen, Göttingen, Germany.

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.
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http://dx.doi.org/10.2337/dc20-0019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646204PMC
October 2020

Sociodemographic inequities associated with participation in leisure-time physical activity in sub-Saharan Africa: an individual participant data meta-analysis.

BMC Public Health 2020 Jun 15;20(1):927. Epub 2020 Jun 15.

Department of Medicine, University of Cambridge, Cambridge, UK.

Background: Leisure-time physical activity (LTPA) is an important contributor to total physical activity and the focus of many interventions promoting activity in high-income populations. Little is known about LTPA in sub-Saharan Africa (SSA), and with expected declines in physical activity due to rapid urbanisation and lifestyle changes we aimed to assess the sociodemographic differences in the prevalence of LTPA in the adult populations of this region to identify potential barriers for equitable participation.

Methods: A two-step individual participant data meta-analysis was conducted using data collected in SSA through 10 population health surveys that included the Global Physical Activity Questionnaire. For each sociodemographic characteristic, the pooled adjusted prevalence and risk ratios (RRs) for participation in LTPA were calculated using the random effects method. Between-study heterogeneity was explored through meta-regression analyses and tests for interaction.

Results: Across the 10 populations (N = 26,022), 18.9% (95%CI: 14.3, 24.1; I = 99.0%) of adults (≥ 18 years) participated in LTPA. Men were more likely to participate in LTPA compared with women (RR for women: 0.43; 95%CI: 0.32, 0.60; P < 0.001; I = 97.5%), while age was inversely associated with participation. Higher levels of education were associated with increased LTPA participation (RR: 1.30; 95%CI: 1.09, 1.55; P = 0.004; I = 98.1%), with those living in rural areas or self-employed less likely to participate in LTPA. These associations remained after adjusting for time spent physically active at work or through active travel.

Conclusions: In these populations, participation in LTPA was low, and strongly associated with sex, age, education, self-employment and urban residence. Identifying the potential barriers that reduce participation in these groups is necessary to enable equitable access to the health and social benefits associated with LTPA.
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http://dx.doi.org/10.1186/s12889-020-08987-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296740PMC
June 2020

Diabetes Prevalence and Its Relationship With Education, Wealth, and BMI in 29 Low- and Middle-Income Countries.

Diabetes Care 2020 04 12;43(4):767-775. Epub 2020 Feb 12.

Non-Communicable Diseases, Caribbean Public Health Agency, Port of Spain, Trinidad and Tobago.

Objective: Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship of education, household wealth, and BMI with diabetes risk.

Research Design And Methods: We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall and by country, World Bank income group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR).

Results: Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI 7.1-8.0) and of undiagnosed diabetes 4.9% (4.6-5.3). Diabetes prevalence increased with increasing WBIG: countries with low-income economies (LICs) 6.7% (5.5-8.1), lower-middle-income economies (LMIs) 7.1% (6.6-7.6), and upper-middle-income economies (UMIs) 8.2% (7.5-9.0). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, after adjusting for BMI (LICs RR 1.47 [95% CI 1.22-1.78], LMIs 1.14 [1.06-1.23], and UMIs 1.28 [1.02-1.61]).

Conclusions: Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.
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http://dx.doi.org/10.2337/dc19-1782DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085810PMC
April 2020

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.

Lancet 2019 08 18;394(10199):652-662. Epub 2019 Jul 18.

Division of Non-Communicable Diseases, Ministry of Health, Nairobi, Kenya.

Background: Evidence from nationally representative studies in low-income and middle-income countries (LMICs) on where in the hypertension care continuum patients are lost to care is sparse. This information, however, is essential for effective targeting of interventions by health services and monitoring progress in improving hypertension care. We aimed to determine the cascade of hypertension care in 44 LMICs-and its variation between countries and population groups-by dividing the progression in the care process, from need of care to successful treatment, into discrete stages and measuring the losses at each stage.

Methods: In this cross-sectional study, we pooled individual-level population-based data from 44 LMICs. We first searched for nationally representative datasets from the WHO Stepwise Approach to Surveillance (STEPS) from 2005 or later. If a STEPS dataset was not available for a LMIC (or we could not gain access to it), we conducted a systematic search for survey datasets; the inclusion criteria in these searches were that the survey was done in 2005 or later, was nationally representative for at least three 10-year age groups older than 15 years, included measured blood pressure data, and contained data on at least two hypertension care cascade steps. Hypertension was defined as a systolic blood pressure of at least 140 mm Hg, diastolic blood pressure of at least 90 mm Hg, or reported use of medication for hypertension. Among those with hypertension, we calculated the proportion of individuals who had ever had their blood pressure measured; had been diagnosed with hypertension; had been treated for hypertension; and had achieved control of their hypertension. We weighted countries proportionally to their population size when determining this hypertension care cascade at the global and regional level. We disaggregated the hypertension care cascade by age, sex, education, household wealth quintile, body-mass index, smoking status, country, and region. We used linear regression to predict, separately for each cascade step, a country's performance based on gross domestic product (GDP) per capita, allowing us to identify countries whose performance fell outside of the 95% prediction interval.

Findings: Our pooled dataset included 1 100 507 participants, of whom 192 441 (17·5%) had hypertension. Among those with hypertension, 73·6% of participants (95% CI 72·9-74·3) had ever had their blood pressure measured, 39·2% of participants (38·2-40·3) had been diagnosed with hypertension, 29·9% of participants (28·6-31·3) received treatment, and 10·3% of participants (9·6-11·0) achieved control of their hypertension. Countries in Latin America and the Caribbean generally achieved the best performance relative to their predicted performance based on GDP per capita, whereas countries in sub-Saharan Africa performed worst. Bangladesh, Brazil, Costa Rica, Ecuador, Kyrgyzstan, and Peru performed significantly better on all care cascade steps than predicted based on GDP per capita. Being a woman, older, more educated, wealthier, and not being a current smoker were all positively associated with attaining each of the four steps of the care cascade.

Interpretation: Our study provides important evidence for the design and targeting of health policies and service interventions for hypertension in LMICs. We show at what steps and for whom there are gaps in the hypertension care process in each of the 44 countries in our study. We also identified countries in each world region that perform better than expected from their economic development, which can direct policy makers to important policy lessons. Given the high disease burden caused by hypertension in LMICs, nationally representative hypertension care cascades, as constructed in this study, are an important measure of progress towards achieving universal health coverage.

Funding: Harvard McLennan Family Fund, Alexander von Humboldt Foundation.
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http://dx.doi.org/10.1016/S0140-6736(19)30955-9DOI Listing
August 2019

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

PLoS Med 2019 03 1;16(3):e1002751. Epub 2019 Mar 1.

Liberia Ministry of Health, Monrovia, Liberia.

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.
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http://dx.doi.org/10.1371/journal.pmed.1002751DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396901PMC
March 2019

Diabetes diagnosis and care in sub-Saharan Africa: pooled analysis of individual data from 12 countries.

Lancet Diabetes Endocrinol 2016 11 7;4(11):903-912. Epub 2016 Oct 7.

Division of Medicine, University College London, London, UK.

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.
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http://dx.doi.org/10.1016/S2213-8587(16)30181-4DOI Listing
November 2016
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