Association between country preparedness indicators and quality clinical care for cardiovascular disease risk factors in 44 lower- and middle-income countries: A multicountry analysis of survey data.

BACKGROUND: Cardiovascular diseases are leading causes of death, globally, and health systems that deliver quality clinical care are needed to manage an increasing number of people with risk factors for these diseases. Indicators of preparedness of countries to manage cardiovascular disease risk factors (CVDRFs) are regularly collected by ministries of health and global health agencies. We aimed to assess whether these indicators are associated with patient receipt of quality clinical care. METHODS AND FINDINGS: We did a secondary analysis of cross-sectional, nationally representative, individual-patient data from 187,552 people with hypertension (mean age 48.1 years, 53.5% female) living in 43 low- and middle-income countries (LMICs) and 40,795 people with diabetes (mean age 52.2 years, 57.7% female) living in 28 LMICs on progress through cascades of care (condition diagnosed, treated, or controlled) for diabetes or hypertension, to indicate outcomes of provision of quality clinical care. Data were extracted from national-level World Health Organization (WHO) Stepwise Approach to Surveillance (STEPS), or other similar household surveys, conducted between July 2005 and November 2016. We used mixed-effects logistic regression to estimate associations between each quality clinical care outcome and indicators of country development (gross domestic product [GDP] per capita or Human Development Index [HDI]); national capacity for the prevention and control of noncommunicable diseases ('NCD readiness indicators' from surveys done by WHO); health system finance (domestic government expenditure on health [as percentage of GDP], private, and out-of-pocket expenditure on health [both as percentage of current]); and health service readiness (number of physicians, nurses, or hospital beds per 1,000 people) and performance (neonatal mortality rate). All models were adjusted for individual-level predictors including age, sex, and education. In an exploratory analysis, we tested whether national-level data on facility preparedness for diabetes were positively associated with outcomes. Associations were inconsistent between indicators and quality clinical care outcomes. For hypertension, GDP and HDI were both positively associated with each outcome. Of the 33 relationships tested between NCD readiness indicators and outcomes, only two showed a significant positive association: presence of guidelines with being diagnosed (odds ratio [OR], 1.86 [95% CI 1.08-3.21], p = 0.03) and availability of funding with being controlled (OR, 2.26 [95% CI 1.09-4.69], p = 0.03). Hospital beds (OR, 1.14 [95% CI 1.02-1.27], p = 0.02), nurses/midwives (OR, 1.24 [95% CI 1.06-1.44], p = 0.006), and physicians (OR, 1.21 [95% CI 1.11-1.32], p < 0.001) per 1,000 people were positively associated with being diagnosed and, similarly, with being treated; and the number of physicians was additionally associated with being controlled (OR, 1.12 [95% CI 1.01-1.23], p = 0.03). For diabetes, no positive associations were seen between NCD readiness indicators and outcomes. There was no association between country development, health service finance, or health service performance and readiness indicators and any outcome, apart from GDP (OR, 1.70 [95% CI 1.12-2.59], p = 0.01), HDI (OR, 1.21 [95% CI 1.01-1.44], p = 0.04), and number of physicians per 1,000 people (OR, 1.28 [95% CI 1.09-1.51], p = 0.003), which were associated with being diagnosed. Six countries had data on cascades of care and nationwide-level data on facility preparedness. Of the 27 associations tested between facility preparedness indicators and outcomes, the only association that was significant was having metformin available, which was positively associated with treatment (OR, 1.35 [95% CI 1.01-1.81], p = 0.04). The main limitation was use of blood pressure measurement on a single occasion to diagnose hypertension and a single blood glucose measurement to diagnose diabetes. CONCLUSION: In this study, we observed that indicators of country preparedness to deal with CVDRFs are poor proxies for quality clinical care received by patients for hypertension and diabetes. The major implication is that assessments of countries' preparedness to manage CVDRFs should not rely on proxies; rather, it should involve direct assessment of quality clinical care.

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.

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.

Lifetime Prevalence of Cervical Cancer Screening in 55 Low- and Middle-Income Countries.

Importance: The World Health Organization is developing a global strategy to eliminate cervical cancer, with goals for screening prevalence among women aged 30 through 49 years. However, evidence on prevalence levels of cervical cancer screening in low- and middle-income countries (LMICs) is sparse. Objective: To determine lifetime cervical cancer screening prevalence in LMICs and its variation across and within world regions and countries. Design, Setting, and Participants: Analysis of cross-sectional nationally representative household surveys carried out in 55 LMICs from 2005 through 2018. The median response rate across surveys was 93.8% (range, 64.0%-99.3%). The population-based sample consisted of 1 136 289 women aged 15 years or older, of whom 6885 (0.6%) had missing information for the survey question on cervical cancer screening. Exposures: World region, country; countries' economic, social, and health system characteristics; and individuals' sociodemographic characteristics. Main Outcomes and Measures: Self-report of having ever had a screening test for cervical cancer. Results: Of the 1 129 404 women included in the analysis, 542 475 were aged 30 through 49 years. A country-level median of 43.6% (interquartile range [IQR], 13.9%-77.3%; range, 0.3%-97.4%) of women aged 30 through 49 years self-reported to have ever been screened, with countries in Latin America and the Caribbean having the highest prevalence (country-level median, 84.6%; IQR, 65.7%-91.1%; range, 11.7%-97.4%) and those in sub-Saharan Africa the lowest prevalence (country-level median, 16.9%; IQR, 3.7%-31.0%; range, 0.9%-50.8%). There was large variation in the self-reported lifetime prevalence of cervical cancer screening among countries within regions and among countries with similar levels of per capita gross domestic product and total health expenditure. Within countries, women who lived in rural areas, had low educational attainment, or had low household wealth were generally least likely to self-report ever having been screened. Conclusions and Relevance: In this cross-sectional study of data collected in 55 low- and middle-income countries from 2005 through 2018, there was wide variation between countries in the self-reported lifetime prevalence of cervical cancer screening. However, the median prevalence was only 44%, supporting the need to increase the rate of screening.

The Association Between Depressive Symptoms, Access to Diabetes Care, and Glycemic Control in Five Middle-Income Countries.

OBJECTIVE: The relationship between depression, diabetes, and access to diabetes care is established in high-income countries (HICs) but not in middle-income countries (MICs), where contexts and health systems differ and may impact this relationship. In this study, we investigate access to diabetes care for individuals with and without depressive symptoms in MICs. RESEARCH DESIGN AND METHODS: We analyzed pooled data from nationally representative household surveys across Brazil, Chile, China, Indonesia, and Mexico. Validated survey tools Center for Epidemiologic Studies Depression Scale Revised, Composite International Diagnostic Interview, Short Form, and Patient Health Questionnaire identified participants with depressive symptoms. Diabetes, defined per World Health Organization Package of Essential Noncommunicable Disease Interventions guidelines, included self-reported medication use and biochemical data. The primary focus was on tracking diabetes care progression through the stages of diagnosis, treatment, and glycemic control. Descriptive and multivariable logistic regression analyses, accounting for gender, age, education, and BMI, examined diabetes prevalence and care continuum progression. RESULTS: The pooled sample included 18,301 individuals aged 50 years and above; 3,309 (18.1%) had diabetes, and 3,934 (21.5%) exhibited depressive symptoms. Diabetes prevalence was insignificantly higher among those with depressive symptoms (28.9%) compared with those without (23.8%, P = 0.071). Co-occurrence of diabetes and depression was associated with increased odds of diabetes detection (odds ratio [OR] 1.398, P < 0.001) and treatment (OR 1.344, P < 0.001), but not with higher odds of glycemic control (OR 0.913, P = 0.377). CONCLUSIONS: In MICs, individuals aged 50 years and older with diabetes and depression showed heightened diabetes identification and treatment probabilities, unlike patterns seen in HICs. This underscores the unique interplay of these conditions in different income settings.

The prevalence of cardiovascular disease risk factors among adults living in extreme poverty.

Evidence on cardiovascular disease (CVD) risk factor prevalence among adults living below the World Bank's international line for extreme poverty (those with income <$1.90 per day) globally is sparse. Here we pooled individual-level data from 105 nationally representative household surveys across 78 countries, representing 85% of people living in extreme poverty globally, and sorted individuals by country-specific measures of household income or wealth to identify those in extreme poverty. CVD risk factors (hypertension, diabetes, smoking, obesity and dyslipidaemia) were present among 17.5% (95% confidence interval (CI) 16.7-18.3%), 4.0% (95% CI 3.6-4.5%), 10.6% (95% CI 9.0-12.3%), 3.1% (95% CI 2.8-3.3%) and 1.4% (95% CI 0.9-1.9%) of adults in extreme poverty, respectively. Most were not treated for CVD-related conditions (for example, among those with hypertension earning <$1.90 per day, 15.2% (95% CI 13.3-17.1%) reported taking blood pressure-lowering medication). The main limitation of the study is likely measurement error of poverty level and CVD risk factors that could have led to an overestimation of CVD risk factor prevalence among adults in extreme poverty. Nonetheless, our results could inform equity discussions for resource allocation and design of effective interventions.

Diagnostic testing for hypertension, diabetes, and hypercholesterolaemia in low-income and middle-income countries: a cross-sectional study of data for 994 185 individuals from 57 nationally representative surveys.

BACKGROUND: Testing for the risk factors of cardiovascular disease, which include hypertension, diabetes, and hypercholesterolaemia, is important for timely and effective risk management. Yet few studies have quantified and analysed testing of cardiovascular risk factors in low-income and middle-income countries (LMICs) with respect to sociodemographic inequalities. We aimed to address this knowledge gap. METHODS: In this cross-sectional analysis, we pooled individual-level data for non-pregnant adults aged 18 years or older from nationally representative surveys done between Jan 1, 2010, and Dec 31, 2019 in LMICs that included a question about whether respondents had ever had their blood pressure, glucose, or cholesterol measured. We analysed diagnostic testing performance by quantifying the overall proportion of people who had ever been tested for these cardiovascular risk factors and the proportion of individuals who met the diagnostic testing criteria in the WHO package of essential noncommunicable disease interventions for primary care (PEN) guidelines (ie, a BMI >30 kg/m2 or a BMI >25 kg/m2 among people aged 40 years or older). We disaggregated and compared diagnostic testing performance by sex, wealth quintile, and education using two-sided t tests and multivariable logistic regression models. FINDINGS: Our sample included data for 994 185 people from 57 surveys. 19·1% (95% CI 18·5-19·8) of the 943 259 people in the hypertension sample met the WHO PEN criteria for diagnostic testing, of whom 78·6% (77·8-79·2) were tested. 23·8% (23·4-24·3) of the 225 707 people in the diabetes sample met the WHO PEN criteria for diagnostic testing, of whom 44·9% (43·7-46·2) were tested. Finally, 27·4% (26·3-28·6) of the 250 573 people in the hypercholesterolaemia sample met the WHO PEN criteria for diagnostic testing, of whom 39·7% (37·1-2·4) were tested. Women were more likely than men to be tested for hypertension and diabetes, and people in higher wealth quintiles compared with those in the lowest wealth quintile were more likely to be tested for all three risk factors, as were people with at least secondary education compared with those with less than primary education. INTERPRETATION: Our study shows opportunities for health systems in LMICs to improve the targeting of diagnostic testing for cardiovascular risk factors and adherence to diagnostic testing guidelines. Risk-factor-based testing recommendations rather than sociodemographic characteristics should determine which individuals are tested. FUNDING: Harvard McLennan Family Fund, the Alexander von Humboldt Foundation, and the National Heart, Lung, and Blood Institute of the US National Institutes of Health.

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

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.

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

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.