Decision-making processes for essential packages of health services: experience from six countries.

Many countries around the world strive for universal health coverage, and an essential packages of health services (EPHS) is a central policy instrument for countries to achieve this. It defines the coverage of services that are made available, as well as the proportion of the costs that are covered from different financial schemes and who can receive these services. This paper reports on the development of an analytical framework on the decision-making process of EPHS revision, and the review of practices of six countries (Afghanistan, Ethiopia, Pakistan, Somalia, Sudan and Zanzibar-Tanzania).The analytical framework distinguishes the practical organisation, fairness and institutionalisation of decision-making processes. The review shows that countries: (1) largely follow a similar practical stepwise process but differ in their implementation of some steps, such as the choice of decision criteria; (2) promote fairness in their EPHS process by involving a range of stakeholders, which in the case of Zanzibar included patients and community members; (3) are transparent in terms of at least some of the steps of their decision-making process and (4) in terms of institutionalisation, express a high degree of political will for ongoing EPHS revision with almost all countries having a designated governing institute for EPHS revision.We advise countries to organise meaningful stakeholder involvement and foster the transparency of the decision-making process, as these are key to fairness in decision-making. We also recommend countries to take steps towards the institutionalisation of their EPHS revision process

Diabetes risk and provision of diabetes prevention activities in 44 low-income and middle-income countries: a cross-sectional analysis of nationally representative, individual-level survey data.

The global burden of diabetes is rising rapidly, yet there is little evidence on individual-level diabetes prevention activities undertaken by health systems in low-income and middle-income countries (LMICs). Here we describe the population at high risk of developing diabetes, estimate diabetes prevention activities, and explore sociodemographic variation in these activities across LMICs. We performed a pooled, cross-sectional analysis of individual-level data from nationally representative, population-based surveys conducted in 44 LMICs between October, 2009, and May, 2019. Our sample included all participants older than 25 years who did not have diabetes and were not pregnant. We defined the population at high risk of diabetes on the basis of either the presence of impaired fasting glucose (or prediabetes in countries with a haemoglobin A <sub>1c</sub> available) or overweight or obesity, consistent with the WHO Package of Essential Noncommunicable Disease Guidelines for type 2 diabetes management. We estimated the proportion of survey participants that were at high risk of developing diabetes based on this definition. We also estimated the proportion of the population at high risk that reported each of four fundamental diabetes prevention activities: physical activity counselling, weight loss counselling, dietary counselling, and blood glucose screening, overall and stratified by World Bank income group. Finally, we used multivariable Poisson regression models to evaluate associations between sociodemographic characteristics and these activities. The final pooled sample included 145 739 adults (86 269 [59·2%] of whom were female and 59 468 [40·4%] of whom were male) across 44 LMICs, of whom 59 308 (40·6% [95% CI 38·5-42·8]) were considered at high risk of diabetes (20·6% [19·8-21·5] in low-income countries, 38·0% [37·2-38·9] in lower-middle-income countries, and 57·5% [54·3-60·6] in upper-middle-income countries). Overall, the reach of diabetes prevention activities was low at 40·0% (38·6-41·4) for physical activity counselling, 37·1% (35·9-38·4) for weight loss counselling, 42·7% (41·6-43·7) for dietary counselling, and 37·1% (34·7-39·6) for blood glucose screening. Diabetes prevention varied widely by national-level wealth: 68·1% (64·6-71·4) of people at high risk of diabetes in low-income countries reported none of these activities, whereas 49·0% (47·4-50·7) at high risk in upper-middle-income countries reported at least three activities. Educational attainment was associated with diabetes prevention, with estimated increases in the predicted probability of receipt ranging between 6·5 (3·6-9·4) percentage points for dietary fruit and vegetable counselling and 21·3 (19·5-23·2) percentage points for blood glucose screening, among people with some secondary schooling compared with people with no formal education. A large proportion of individuals across LMICs are at high risk of diabetes but less than half reported receiving fundamental prevention activities overall, with the lowest receipt of these activities among people in low-income countries and with no formal education. These findings offer foundational evidence to inform future global targets for diabetes prevention and to strengthen policies and programmes to prevent continued increases in diabetes worldwide. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program and the EU's Research and Innovation programme Horizon 2020

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.

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. 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/m <sup>2</sup> or a BMI >25 kg/m <sup>2</sup> 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. 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. 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. Harvard McLennan Family Fund, the Alexander von Humboldt Foundation, and the National Heart, Lung, and Blood Institute of the US National Institutes of Health

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

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. 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). 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]). 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

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.

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. 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 <sub>1c</sub> ]); 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 <sub>1c</sub> 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 <sup>2</sup> ], upper-normal [23·0-24·9 kg/m <sup>2</sup> ], overweight [25·0-29·9 kg/m <sup>2</sup> ], or obese [≥30·0 kg/m <sup>2</sup> ]), 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. 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 <sup>2</sup> 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 <sup>2</sup> . 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 <sup>2</sup> among men in east, south, and southeast Asia to 28·3 kg/m <sup>2</sup> among women in the Middle East and north Africa and in Latin America and the Caribbean. 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. Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program

Data Resource Profile: The Global Health and Population Project on Access to Care for Cardiometabolic Diseases (HPACC).

[No abstract available]ach STEPS survey is co-funded by the country’s government and the WHO. DHS are co-funded by the United States Agency for International Development (USAID) and the respective country’s government. The funding of the other surveys are mostly co-funded by a country’s government, universities and international organizations, and sometimes supported by local sponsors. The creation of the final collated data set has been funded by the Harvard McLennan Family Fund and the Alexander von Humboldt Foundation as well as institutional funds from the Universities of Heidelberg and Göttingen