Unmet need for hypercholesterolemia care in 35 low- and middle-income countries: A cross-sectional study of nationally representative surveys.

BACKGROUND: As the prevalence of hypercholesterolemia is increasing in low- and middle-income countries (LMICs), detailed evidence is urgently needed to guide the response of health systems to this epidemic. This study sought to quantify unmet need for hypercholesterolemia care among adults in 35 LMICs. METHODS AND FINDINGS: We pooled individual-level data from 129,040 respondents aged 15 years and older from 35 nationally representative surveys conducted between 2009 and 2018. Hypercholesterolemia care was quantified using cascade of care analyses in the pooled sample and by region, country income group, and country. Hypercholesterolemia was defined as (i) total cholesterol (TC) ≥240 mg/dL or self-reported lipid-lowering medication use and, alternatively, as (ii) low-density lipoprotein cholesterol (LDL-C) ≥160 mg/dL or self-reported lipid-lowering medication use. Stages of the care cascade for hypercholesterolemia were defined as follows: screened (prior to the survey), aware of diagnosis, treated (lifestyle advice and/or medication), and controlled (TC <200 mg/dL or LDL-C <130 mg/dL). We further estimated how age, sex, education, body mass index (BMI), current smoking, having diabetes, and having hypertension are associated with cascade progression using modified Poisson regression models with survey fixed effects. High TC prevalence was 7.1% (95% CI: 6.8% to 7.4%), and high LDL-C prevalence was 7.5% (95% CI: 7.1% to 7.9%). The cascade analysis showed that 43% (95% CI: 40% to 45%) of study participants with high TC and 47% (95% CI: 44% to 50%) with high LDL-C ever had their cholesterol measured prior to the survey. About 31% (95% CI: 29% to 33%) and 36% (95% CI: 33% to 38%) were aware of their diagnosis; 29% (95% CI: 28% to 31%) and 33% (95% CI: 31% to 36%) were treated; 7% (95% CI: 6% to 9%) and 19% (95% CI: 18% to 21%) were controlled. We found substantial heterogeneity in cascade performance across countries and higher performances in upper-middle-income countries and the Eastern Mediterranean, Europe, and Americas. Lipid screening was significantly associated with older age, female sex, higher education, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Awareness of diagnosis was significantly associated with older age, higher BMI, comorbid diagnosis of diabetes, and comorbid diagnosis of hypertension. Lastly, treatment of hypercholesterolemia was significantly associated with comorbid hypertension and diabetes, and control of lipid measures with comorbid diabetes. The main limitations of this study are a potential recall bias in self-reported information on received health services as well as diminished comparability due to varying survey years and varying lipid guideline application across country and clinical settings. CONCLUSIONS: Cascade performance was poor across all stages, indicating large unmet need for hypercholesterolemia care in this sample of LMICs-calling for greater policy and research attention toward this cardiovascular disease (CVD) risk factor and highlighting opportunities for improved prevention of CVD.

The state of diabetes treatment coverage in 55 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 680 102 adults.

BACKGROUND: Approximately 80% of the 463 million adults worldwide with diabetes live in low- and middle-income countries (LMICs). A major obstacle to designing evidence-based policies to improve diabetes outcomes in LMICs is the limited nationally representative data on the current patterns of treatment coverage. The objectives of this study are (1) to estimate the proportion of adults with diabetes in LMICs who receive coverage of recommended pharmacological and non-pharmacological diabetes treatment and (2) to describe country-level and individual-level characteristics that are associated with treatment. METHODS: We conducted 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 upon population-level monitoring indicators recommended in the 2020 World Health Organization Package of Essential Noncommunicable Disease Interventions. 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 geographic region. At the individual level, we used logistic regression models to assess coverage along several key individual characteristics including sex, age, BMI, 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% confidence interval [CI], 8.7-9.4), with 43.9% (95% CI, 41.9-45.9) reporting a prior diabetes diagnosis. Overall, 4.6% (95% CI, 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% (95% CI, 48.6-52.5); antihypertensive medication, 41.3% (95% CI, 39.3-43.3); cholesterol-lowering medication, 6.3% (95% CI, 5.5-7.2); diet counseling, 32.2% (95% CI, 30.7-33.7); exercise counseling, 28.2% (95% CI, 26.6-29.8); and weight-loss counseling, 31.5% (95% CI, 29.3-33.7). Countries at higher income levels tended to have greater coverage. Female sex and higher age, BMI, 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.

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

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.