Mid-level healthcare workers knowledge on non-communicable diseases in Tanzania: a district-level pre-and post-training assessment.

INTRODUCTION: Over the past two decades, Tanzania's burden of non-communicable diseases has grown disproportionately, but limited resources are still prioritized. A trained human resource for health is urgently needed to combat these diseases. However, continuous medical education for NCDs is scarce. This paper reports on the mid-level healthcare workers knowledge on NCDs. We assessed the knowledge to measure the effectiveness of the training conducted during the initiation of a Package for Essential Management of Severe NCDs (PEN Plus) in rural district hospitals in Tanzania. METHODS: The training was given to 48 healthcare employees from Dodoma Region's Kondoa Town Council District Hospital. For a total of five (5) days, a fundamental course on NCDs featured in-depth interactive lectures and practical workshops. Physicians from Tanzania's higher education institutions, tertiary university hospitals, research institutes, and medical organizations served as trainers. Before and after the training, a knowledge assessment comprising 28 questions was administered. Descriptive data analysis to describe the characteristics of the specific knowledge on physiology, diagnosis and therapy of diabetes mellitus, rheumatic fever, heart disease, and sickle cell disease was done using Stata version 17 (STATA Corp Inc., TX, USA). RESULTS: Complete assessment data for 42 out of the 48 participants was available. Six participants did not complete the training and the assessment. The mean age of participants was 36.9 years, and slightly above half (52%) were above 35 years. Two-thirds (61.9%) were female, and about half (45%) were nurses. The majority had the experience of working for more than 5 years, and the average was 9.4 years (+/- 8.4 years). Overall, the trainees' average scores improved after the training (12.79 vs. 16.05, p < 0.0001) out of 28 possible scores. Specifically, trainees' average scores were better in treatment than in diagnosis, except for sickle cell disease (1.26 vs. 1.83). Most were not able to diagnose rheumatic heart disease (47.6% able) compared to diabetes mellitus (54.8% able) or sickle cell disease (64.3% able) at baseline. The proportion of trainees with adequate knowledge of the treatment of sickle cell disease and diabetes mellitus was 35% and 38.1%, respectively, and there was a non-statistical difference after training. Those working for less than 5 years had a higher proportion of adequate knowledge (30.8%) compared to their more experienced colleagues (6.9%). After the training, participants' knowledge of NCDs increased by three times (i.e., aPR 3, 95% CI = 1.1, 1.5, and 6.0). CONCLUSION AND RECOMMENDATIONS: PEN Plus training improved the knowledge of healthcare workers at Kondoa Town Council District Hospital. Training is especially needed among nurses and those with a longer duration of work. Continuing education for human resources for health on the management of NCDs is highly recommended in this setting.

Cost analysis for initiating an integrated package of essential non-communicable disease interventions (PEN-Plus) in Kondoa District Hospital, Tanzania: a time-driven activity-based costing (TDABC) study protocol.

INTRODUCTION: Non-communicable diseases (NCDs) constitute approximately 74% of global mortality, with 77% of these deaths occurring in low-income and middle-income countries. Tanzania exemplifies this situation, as the percentage of total disability-adjusted life years attributed to NCDs has doubled over the past 30 years, from 18% to 36%. To mitigate the escalating burden of severe NCDs, the Tanzanian government, in collaboration with local and international partners, seeks to extend the integrated package of essential interventions for severe NCDs (PEN-Plus) to district-level facilities, thereby improving accessibility. This study aims to estimate the cost of initiating PEN-Plus for rheumatic heart disease, sickle cell disease and type 1 diabetes at Kondoa district hospital in Tanzania. METHODS AND ANALYSIS: We will employ time-driven activity-based costing (TDABC) to quantify the capacity cost rates (CCR), and capital and recurrent costs associated with the implementation of PEN-Plus. Data on resource consumption will be collected through direct observations and interviews with nurses, the medical officer in charge and the heads of laboratory and pharmacy units/departments. Data on contact times for targeted NCDs will be collected by observing a sample of patients as they move through the care delivery pathway. Data cleaning and analysis will be done using Microsoft Excel. ETHICS AND DISSEMINATION: Ethical approval to conduct the study has been waived by the Norwegian Regional Ethics Committee and was granted by the Tanzanian National Health Research Ethics Committee NIMR/HQ/R.8a/Vol.IX/4475. A written informed consent will be provided to the study participants. This protocol has been disseminated in the Bergen Centre for Ethics and Priority Setting International Symposium, Norway and the 11th Muhimbili University of Health and Allied Sciences Scientific Conference, Tanzania in 2023. The findings will be published in peer-reviewed journals for use by the academic community, researchers and health practitioners.

Multiple cardiovascular risk factor care in 55 low- and middle-income countries: A cross-sectional analysis of nationally-representative, individual-level data from 280,783 adults.

The prevalence of multiple age-related cardiovascular disease (CVD) risk factors is high among individuals living in low- and middle-income countries. We described receipt of healthcare services for and management of hypertension and diabetes among individuals living with these conditions using individual-level data from 55 nationally representative population-based surveys (2009-2019) with measured blood pressure (BP) and diabetes biomarker. We restricted our analysis to non-pregnant individuals aged 40-69 years and defined three mutually exclusive groups (i.e., hypertension only, diabetes only, and both hypertension-diabetes) to compare individuals living with concurrent hypertension and diabetes to individuals with each condition separately. We included 90,086 individuals who lived with hypertension only, 11,975 with diabetes only, and 16,228 with hypertension-diabetes. We estimated the percentage of individuals who were aware of their diagnosis, used pharmacological therapy, or achieved appropriate hypertension and diabetes management. A greater percentage of individuals with hypertension-diabetes were fully diagnosed (64.1% [95% CI: 61.8-66.4]) than those with hypertension only (47.4% [45.3-49.6]) or diabetes only (46.7% [44.1-49.2]). Among the hypertension-diabetes group, pharmacological treatment was higher for individual conditions (38.3% [95% CI: 34.8-41.8] using antihypertensive and 42.3% [95% CI: 39.4-45.2] using glucose-lowering medications) than for both conditions jointly (24.6% [95% CI: 22.1-27.2]).The percentage of individuals achieving appropriate management was highest in the hypertension group (17.6% [16.4-18.8]), followed by diabetes (13.3% [10.7-15.8]) and hypertension-diabetes (6.6% [5.4-7.8]) groups. Although health systems in LMICs are reaching a larger share of individuals living with both hypertension and diabetes than those living with just one of these conditions, only seven percent achieved both BP and blood glucose treatment targets. Implementation of cost-effective population-level interventions that shift clinical care paradigm from disease-specific to comprehensive CVD care are urgently needed for all three groups, especially for those with multiple CVD risk factors.

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.

Protocol for an evaluation of the initiation of an integrated longitudinal outpatient care model for severe chronic non-communicable diseases (PEN-Plus) at secondary care facilities (district hospitals) in 10 lower-income countries.

INTRODUCTION: The Package of Essential Noncommunicable Disease Interventions-Plus (PEN-Plus) is a strategy decentralising care for severe non-communicable diseases (NCDs) including type 1 diabetes, rheumatic heart disease and sickle cell disease, to increase access to care. In the PEN-Plus model, mid-level clinicians in intermediary facilities in low and lower middle income countries are trained to provide integrated care for conditions where services traditionally were only available at tertiary referral facilities. For the upcoming phase of activities, 18 first-level hospitals in 9 countries and 1 state in India were selected for PEN-Plus expansion and will treat a variety of severe NCDs. Over 3 years, the countries and state are expected to: (1) establish PEN-Plus clinics in one or two district hospitals, (2) support these clinics to mature into training sites in preparation for national or state-level scale-up, and (3) work with the national or state-level stakeholders to describe, measure and advocate for PEN-Plus to support development of a national operational plan for scale-up. METHODS AND ANALYSIS: Guided by Proctor outcomes for implementation research, we are conducting a mixed-method evaluation consisting of 10 components to understand outcomes in clinical implementation, training and policy development. Data will be collected through a mix of quantitative surveys, routine reporting, routine clinical data and qualitative interviews. ETHICS AND DISSEMINATION: This protocol has been considered exempt or covered by central and local institutional review boards. Findings will be disseminated throughout the project's course, including through quarterly M&E discussions, semiannual formative assessments, dashboard mapping of progress, quarterly newsletters, regular feedback loops with national stakeholders and publication in peer-reviewed journals.

The effectiveness of interventions to reduce cardio-metabolic risk factors among regular street food consumers in Dar es Salaam, Tanzania: The pre-post findings from a cluster randomized trial (Registered by Pan African clinical trial registry with trial # PACTR202208642850935).

INTRODUCTION: The healthy plate model (HPM) is a practical guide to modulate the portion of staple food in main meals, subsequently affecting the risks associated with Non-communicable Diseases include type2 diabetes mellitus (T2DM). OBJECTIVE: This study investigated the effectiveness of health information and the healthy plate model on cardio-metabolic risk factors, knowledge and attitude towards T2DM prevention measures. METHODS: A pre-post analysis, as part of a cluster randomized trial with street food vendors and their customers, was implemented in three randomly selected districts in Dar es Salaam, Tanzania. Two vendor-customer clusters each with 15 and more vendors from each district were randomly assigned to receive either T2DM health information only (Intervention package1 [IP1]) or IP1 plus a subsidized meal with vegetables and fruits, following the principles of the HPM (Intervention package2 [IP2]). Within the clusters the participants were informed on the importance of the intervention they received. An intervention period lasted for three months from 1st April to 31st June 2019. We applied Generalized Linear Mixed Models and Bayesian Modelling (for sensitivity analysis) to assess the effectiveness of the interventions. RESULTS: Overall, 336 (IP2 = 175 and IP1 = 161) out of 560 (280/arm) previous study participants participated in evaluation. Diastolic BP was lower among IP2 participants in the evaluation than baseline AßC = -4.1mmHg (95%CI:-5.42 to -2.76). After adjusting for the interaction between IP2 and age of the consumers, the BMI was significantly lower among IP2 in the evaluation than baseline AßC = -0.7kg/m2 (95%CI: -1.17 to -0.23). With interaction between IP2 and income, BMI was higher in the IP2 in the evaluation than baseline AßC = 0.73kg/m2 (95%CI: 0.08 to 1.38). Systolic and diastolic BP were significantly lower among IP1 in the evaluation than baseline AßC = -3.5mmHg (95%CI:-5.78 to -1.24) and AßC = -5.9mmHg (95%CI:-7.34 to -4.44) respectively. Both the knowledge scores and positive attitudes towards T2DM prevention measures were higher in the evaluation than baseline in both interventions arms. CONCLUSION: The positive effects on cardio-metabolic risk factors, knowledge and attitude were observed in both intervention arms. Due to interactions between IP2, age and income; designing interventions relating to food and cardio-metabolic risk factors, should consider combining socio-economic factors.

Health service readiness to provide care for HIV and cardiovascular disease risk factors in low- and middle-income countries.

Cardiovascular disease risk factors (CVDRF), in particular diabetes and hypertension, are chronic conditions which carry a substantial disease burden in Low- and Middle-Income Countries. Unlike HIV, they were neglected in the Millenium Development Goals along with the health services required to manage them. To inform the level of health service readiness that could be achieved with increased attention, we compared readiness for CVDRF with that for HIV. Using data from national Service Provision Assessments, we describe facility-reported readiness to provide services for CVDRF and HIV, and derive a facility readiness score of observed essential components to manage them. We compared HIV vs CVDRF coverage scores by country, rural or urban location, and facility type, and by whether or not facilities reported readiness to provide care. We assessed the factors associated with coverage scores for CVDRF and HIV in a multivariable analysis. In our results, we include 7522 facilities in 8 countries; 86% of all facilities reported readiness to provide services for CVDRF, ranging from 77-98% in individual countries. For HIV, 30% reported of facilities readiness to provide services, ranging from 3-63%. Median derived facility readiness score for CVDRF was 0.28 (IQR 0.16-0.50), and for HIV was 0.43 (0.32-0.60). Among facilities which reported readiness, this rose to 0.34 (IQR 0.18-0.52) for CVD and 0.68 (0.56-0.76) for HIV. Derived readiness scores were generally significantly lower for CVDRF than for HIV, except in private facilities. In multivariable analysis, odds of a higher readiness score in both CVDRF or HIV care were higher in urban vs rural and secondary vs primary care; facilities with higher CVDRF scores were significantly associated with higher HIV scores. Derived readiness scores for HIV are higher than for CVDRF, and coverage for CVDRF is significantly higher in facilities with higher HIV readiness scores. This suggests possible benefits from leveraging HIV services to provide care for CVDRF, but poor coverage in rural and primary care facilities threatens Sustainable Development Goal 3.8 to provide high quality universal healthcare for all.

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.

BACKGROUND: 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. METHODS: 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 A1c 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: 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.

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.

Measurement of and training for NCD guideline implementation in LMICs: a scoping review protocol.

INTRODUCTION: Globally, non-communicable diseases (NCDs) are the leading causes of morbidity and mortality with an estimated 41 million deaths (74% of all global deaths) annually. Despite the WHO's Global Action Plan for the Prevention and Control of NCDs since 2013, progress on implementation of the guidelines has been slow. Although research has shown success of some NCD prevention and treatment interventions, there is a dearth of research on NCD care delivery approaches, cost-effectiveness and larger implementation research, especially in low/middle-income countries (LMICs). The objective of this scoping review is to identify the existing variation in how, why and by whom implementation of NCD guidelines is measured as part of implementation research or non-research programme improvement. METHODS AND ANALYSIS: Using the methods established by Arksey and O'Malley, the search strategy was developed in consultation with a research librarian together with stakeholder feedback from content experts. We will apply the search to multiple electronic databases and grey literature sources. Two reviewers will independently screen title and abstract for inclusion followed by a full-text screening and all included records will be abstracted using a standardised tool that will be piloted with a sample of articles before application to all records. We will conduct a narrative synthesis of abstracted data and simple quantitative descriptive statistics. DISSEMINATION: The results will enable stakeholders in LMICs to leverage existing tools and resources for implementation and ongoing evaluation of NCD guidelines, to improve education and capacity building, and ultimately NCD care across the lifespan.

Health system capacity to manage diabetic ketoacidosis in nine low-income and lower-middle income countries: A cross-sectional analysis of nationally representative survey data.

Background: There has been increasing awareness about the importance of type 1 diabetes (T1D) globally. Diabetic ketoacidosis (DKA) is a life-threatening complication of T1D in low-income settings. Little is known about health system capacity to manage DKA in low- and lower-middle income countries (LLMICs). As such, we describe health system capacity to diagnose and manage DKA across nine LLMICs using data from Service Provision Assessments. Methods: In this cross-sectional study, we used data from Service Provision Assessment (SPA) surveys, which are part of the Demographic and Health Survey (DHS) Program. We defined an item set to diagnose and manage DKA in higher-level (tertiary or secondary) facilities, and a set to assess and refer patients presenting to lower-level (primary) facilities. We quantified each item's availability by service level in Bangladesh (Survey 1: May 22 2014-Jul 20 2014; Survey 2: Jul 2017-Oct 2017), the Democratic Republic of the Congo (DRC) (Oct 16 2017-Nov 24 2017 in Kinshasha; Aug 08 2018-Apr 20 2018 in rest of country), Haiti (Survey 1: Mar 05 2013-Jul 2013; Survey 2: Dec 16 2017-May 09 2018), Ethiopia (Feb 06 2014-Mar 09 2014), Malawi (Phase 1: Jun 11 2013-Aug 20 2013; Phase 2: Nov 13 2013-Feb 7 2014), Nepal (Phase 1: Apr 20 2015-Apr 25 2015; Phase 2: Jun 04 2015-Nov 05 2015), Senegal (Survey 1: Jan 2014-Oct 2014; Survey 2: Feb 09 2015-Nov 10 2015; Survey 3: Feb 2016-Nov 2016; Survey 4: Mar 13 2017-Dec 15 2017; Survey 5: Apr 15 2018-Dec 31 2018; Survey 6: Apr 15 2019-Feb 28 2020), Tanzania (Oct 20 2014-Feb 21 2015), and Afghanistan (Nov 1 2018-Jan 20 2019). Variation in secondary facilities' capacity and trends over time were also explored. Findings: We examined data from 2028 higher-level and 7534 lower-level facilities. Of these, 1874 higher-level and 6636 lower-level facilities' data were eligible for analysis. Availability of all item sets were low at higher-level facilities, where less than 50% had the minimal set of supplies, less than 20% had the full minimal set, and less than 15% had the ideal set needed to diagnose and manage DKA. Across countries in lower-level facilities, less than 14% had the minimal set of supplies and less than 9% the full set of supplies for diagnosis and transfer of DKA patients. No country had more than 20% of facilities with the minimal set of items needed to assess or manage DKA. Where data were available for more than one survey (Bangladesh, Senegal, and Haiti), changes in availability of the minimal set and ideal set of items did not exceed 15%. Tertiary facilities performed best in Haiti, Ethiopia, Malawi, Nepal, Senegal, Tanzania, and Afghanistan. Secondary facilities that were rural, public, and had fewer staff had lower capacity. Interpretation: Health system capacity to manage DKA was low across these nine LLMICs. Although efforts are underway to strengthen health systems, a specific focus on DKA management is still needed. Funding: Leona M. and Harry B. Helmsley Charitable Trust, and Juvenile Diabetes Research Foundation Ltd.

Patterns of tobacco use in low and middle income countries by tobacco product and sociodemographic characteristics: nationally representative survey data from 82 countries.

OBJECTIVES: To determine the prevalence and frequency of using any tobacco product and each of a detailed set of tobacco products, how tobacco use and frequency of use vary across countries, world regions, and World Bank country income groups, and the socioeconomic and demographic gradients of tobacco use and frequency of use within countries. DESIGN: Secondary analysis of nationally representative, cross-sectional, household survey data from 82 low and middle income countries collected between 1 January 2015 and 31 December 2020. SETTING: Population based survey data. PARTICIPANTS: 1 231 068 individuals aged 15 years and older. MAIN OUTCOME MEASURES: Self-reported current smoking, current daily smoking, current smokeless tobacco use, current daily smokeless tobacco use, pack years, and current use and use frequencies of each tobacco product. Products were any type of cigarette, manufactured cigarette, hand rolled cigarette, water pipe, cigar, oral snuff, nasal snuff, chewing tobacco, and betel nut (with and without tobacco). RESULTS: The smoking prevalence in the study sample was 16.5% (95% confidence interval 16.1% to 16.9%) and ranged from 1.1% (0.9% to 1.3%) in Ghana to 50.6% (45.2% to 56.1%) in Kiribati. The user prevalence of smokeless tobacco was 7.7% (7.5% to 8.0%) and prevalence was highest in Papua New Guinea (daily user prevalence of 65.4% (63.3% to 67.5%)). Although variation was wide between countries and by tobacco product, for many low and middle income countries, the highest prevalence and cigarette smoking frequency was reported in men, those with lower education, less household wealth, living in rural areas, and higher age. CONCLUSIONS: Both smoked and smokeless tobacco use and frequency of use vary widely across tobacco products in low and middle income countries. This study can inform the design and targeting of efforts to reduce tobacco use in low and middle income countries and serve as a benchmark for monitoring progress towards national and international goals.

The Association of Socioeconomic Status With Hypertension in 76 Low- and Middle-Income Countries.

BACKGROUND: Effective equity-focused health policy for hypertension in low- and middle-income countries (LMICs) requires an understanding of the condition's current socioeconomic gradients and how these are likely to change in the future as countries develop economically. OBJECTIVES: This cross-sectional study aimed to determine how hypertension prevalence in LMICs varies by individuals' education and household wealth, and how these socioeconomic gradients in hypertension prevalence are associated with a country's gross domestic product (GDP) per capita. METHODS: We pooled nationally representative household survey data from 76 LMICs. We disaggregated hypertension prevalence by education and household wealth quintile, and used regression analyses to adjust for age and sex. RESULTS: We included 1,211,386 participants in the analysis. Pooling across all countries, hypertension prevalence tended to be similar between education groups and household wealth quintiles. The only world region with a clear positive association of hypertension with education or household wealth quintile was Southeast Asia. Countries with a lower GDP per capita had, on average, a more positive association of hypertension with education and household wealth quintile than countries with a higher GDP per capita, especially in rural areas and among men. CONCLUSIONS: Differences in hypertension prevalence between socioeconomic groups were generally small, with even the least educated and least wealthy groups having a substantial hypertension prevalence. Our cross-sectional interaction analyses of GDP per capita with the socioeconomic gradients of hypertension suggest that hypertension may increasingly affect adults in the lowest socioeconomic groups as LMICs develop economically.

Rural-Urban Differences in Diabetes Care and Control in 42 Low- and Middle-Income Countries: A Cross-sectional Study of Nationally Representative Individual-Level Data.

OBJECTIVE: Diabetes prevalence is increasing rapidly in rural areas of low- and middle-income countries (LMICs), but there are limited data on the performance of health systems in delivering equitable and effective care to rural populations. We therefore assessed rural-urban differences in diabetes care and control in LMICs. RESEARCH DESIGN AND METHODS: We pooled individual-level data from nationally representative health surveys in 42 countries. We used Poisson regression models to estimate age-adjusted differences in the proportion of individuals with diabetes in rural versus urban areas achieving performance measures for the diagnosis, treatment, and control of diabetes and associated cardiovascular risk factors. We examined differences across the pooled sample, by sex, and by country. RESULTS: The pooled sample from 42 countries included 840,110 individuals (35,404 with diabetes). Compared with urban populations with diabetes, rural populations had ∼15-30% lower relative risk of achieving performance measures for diabetes diagnosis and treatment. Rural populations with diagnosed diabetes had a 14% (95% CI 5-22%) lower relative risk of glycemic control, 6% (95% CI -5 to 16%) lower relative risk of blood pressure control, and 23% (95% CI 2-39%) lower relative risk of cholesterol control. Rural women with diabetes had lower achievement of performance measures relating to control than urban women, whereas among men, differences were small. CONCLUSIONS: Rural populations with diabetes experience substantial inequities in the achievement of diabetes performance measures in LMICs. Programs and policies aiming to strengthen global diabetes care must consider the unique challenges experienced by rural populations.

Prioritizing Health-Sector Interventions for Noncommunicable Diseases and Injuries in Low- and Lower-Middle Income Countries: National NCDI Poverty Commissions.

Health sector priorities and interventions to prevent and manage noncommunicable diseases and injuries (NCDIs) in low- and lower-middle-income countries (LLMICs) have primarily adopted elements of the World Health Organization Global Action Plan for NCDs 2013-2020. However, there have been limited efforts in LLMICs to prioritize among conditions and health-sector interventions for NCDIs based on local epidemiology and contextually relevant risk factors or that incorporate the equitable distribution of health outcomes. The Lancet Commission on Reframing Noncommunicable Diseases and Injuries for the Poorest Billion supported national NCDI Poverty Commissions to define local NCDI epidemiology, determine an expanded set of priority NCDI conditions, and recommend cost-effective, equitable health-sector interventions. Fifteen national commissions and 1 state-level commission were established from 2016-2019. Six commissions completed the prioritization exercise and selected an average of 25 NCDI conditions; 15 conditions were selected by all commissions, including asthma, breast cancer, cervical cancer, diabetes mellitus type 1 and 2, epilepsy, hypertensive heart disease, intracerebral hemorrhage, ischemic heart disease, ischemic stroke, major depressive disorder, motor vehicle road injuries, rheumatic heart disease, sickle cell disorders, and subarachnoid hemorrhage. The commissions prioritized an average of 35 health-sector interventions based on cost-effectiveness, financial risk protection, and equity-enhancing rankings. The prioritized interventions were estimated to cost an additional US$4.70-US$13.70 per capita or approximately 9.7%-35.6% of current total health expenditure (0.6%-4.0% of current gross domestic product). Semistructured surveys and qualitative interviews of commission representatives demonstrated positive outcomes in several thematic areas, including understanding NCDIs of poverty, informing national planning and implementation of NCDI health-sector interventions, and improving governance and coordination for NCDIs. Overall, national NCDI Poverty Commissions provided a platform for evidence-based, locally driven determination of priorities within NCDIs.

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.

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 m2 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.

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.

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 [HbA1c]); 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 HbA1c 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/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), 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/m2 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/m2. 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/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 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.

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.

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.

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.