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For patients with type 2 diabetes in low-income and middle-income countries (LMICs), access to newer antidiabetic drugs (eg, sodium-glucose co-transporter-2 [SGLT2] inhibitors, glucagon-like peptide-1 [GLP-1] receptor agonists, and insulin analogues) could reduce the incidence of diabetes-related complications. We aimed to estimate price targets to pursue in negotiations for inclusion in national formularies given the addition of these novel agents to WHO's Essential Medicines List.We incorporated individual-level, nationally representative survey data (2006-18) from 23 678 people with diabetes in 67 LMICs into a microsimulation of cardiovascular events, heart failure, end-stage renal disease, vision loss, pressure sensation loss, hypoglycaemia requiring medical attention, and drug-specific side-effects. We estimated price targets for incremental costs of switching to newer treatments to achieve cost-effectiveness (ie,3-times gross domestic product per disability-adjusted life-year averted) or to achieve net cost-savings when including costs of averted complications. We compared switching to SGLT2 inhibitors or GLP-1 receptor agonists in place of sulfonylureas, or insulin analogues in place of human insulin, and also compared a glycaemia-agnostic pathways of adding SGLT2 inhibitors or GLP-1 receptor agonists to existing therapies for people with heart disease, heart failure, or kidney disease.To achieve cost-effectiveness, SGLT2 inhibitors would need to have a median price of $224 per person per year (a 17·4% cost reduction; IQR $138-359, population-weighted across countries; mean price $257); GLP-1 receptor agonists $208 per person per year (98·3% reduction; $129-488; $240); and glargine insulin $20 per vial (31·0% reduction; $16-42; $28). To achieve net cost-savings, price targets would need to reduce by a further $9-10 to a median cost for SGLT2 inhibitors of $214 (21·4% reduction; $148-316; $245) and for GLP-1 receptor agonists to $199 per person per year (98·4% reduction; $138-294; $228); but insulin glargine remained around $20 per vial (32·4% reduction; $15-37; $26). Using SGLT2 inhibitors or GLP-1 receptor agonists in a glycaemia-agnostic pathway produced a 92% reduction (SGLT2 inhibitors) and 72% reduction (GLP-1 receptor agonists) in incremental cost-effectiveness ratios.Among novel agents, SGLT2 inhibitors hold particular promise for reducing complications of diabetes and meeting common price targets, particularly when used among people with established cardiovascular or kidney disease. These findings are consistent with the choice to include SGLT2 inhibitors in the WHO Essential Medicines List.Clinton Health Access Initiative.

Summary 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.

HRQOL in transplant candidates and recipients who are also infected with HIV and are awaiting a kidney, or have received one from a HIV-positive donor, has not been previously investigated. The HRQOL of 47 HIV-positive kidney transplant candidates and 21 recipients from HIV-positive donors was evaluated using the Short Form-36 (SF-36) and face to face interviews at baseline and at 6 months. The correlation between SF-36 scores and sociodemographic, clinical and nutritional factors was determined. 68 patients completed the SF-36 at baseline and 6 months. Transplant candidates: transplant candidates had lower HRQOL than recipients. The main mental stressors were income, employment and waiting for a donor. Physical health complaints were body pain (BP) and fatigue. Pre-albumin and BMI was positively correlated with general health at baseline (r = 0.401, p = 0.031 and r = 0.338, p = 0.025). Besides a positive association with role physical (RP) and BP, albumin was associated with overall physical composite score (PCS) (r = 0.329, p = 0.024) at 6 months. Transplant recipients: Transplant recipients had high HRQOL scores in all domains. PCS was 53.8 ± 10.0 and 56.6 ± 6.5 at baseline and 6 months respectively. MCS was 51.3 ± 11.5 and 54.2 ± 8.5 at baseline and 6 months respectively. Albumin correlated positively with PCS (r = 0.464, p = 0.034) at 6 months and role emotional (RE) (r = 0.492, p = 0.024). Higher pre-albumin was associated with better RE and RP abilities and MCS (r = 0.495, p = 0.034). MAMC was associated with four domains of physical health and strongly correlated with PCS (r = 0.821, p = 0.000). Strategies to improve HRQOL include ongoing social support, assistance with employment issues and optimising nutritional status.

Summary Background Approximately 80% of the 463 million adults worldwide with diabetes live in low-income and middle-income countries (LMICs). A major obstacle to designing evidence-based policies to improve diabetes outcomes in LMICs is the scarce availability of nationally representative data on the current patterns of treatment coverage. The objectives of this study were to estimate the proportion of adults with diabetes in LMICs who receive coverage of recommended pharmacological and non-pharmacological diabetes treatment; and to describe country-level and individual-level characteristics that are associated with treatment. Methods We did 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 on population-level monitoring indicators recommended in the 2020 WHO Package of Essential Noncommunicable Disease Interventions. Surveys were included if they were done in 2008 or after in an LMIC, as classified by the World Bank in the year the survey was done; were nationally representative; had individual-level data; contained a diabetes biomarker (fasting glucose, random glucose, or glycated haemoglobin); and had data on one or more diabetes treatments. Our sample included non-pregnant individuals with an available diabetes biomarker who were at least 25 years of age. 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 geographical region. At the individual level, we used logistic regression models to assess coverage along several key individual characteristics including sex, age, body-mass index, 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% CI 8·7–9·4), with 43·9% (41·9–45·9) reporting a previous diabetes diagnosis. Overall, 4·6% (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% (48·6–52·5); antihypertensive medication was 41·3% (39·3–43·3); cholesterol-lowering medication was 6·3% (5·5–7·2); diet counselling was 32·2% (30·7–33·7); exercise counselling was 28·2% (26·6–29·8); and weight-loss counselling was 31·5% (29·3–33·7). Countries at higher-income levels tended to have greater coverage. Female sex and higher age, body-mass index, 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. Funding National Clinician Scholars Program at the University of Michigan Institute for Healthcare Policy & Innovation, National Institute of Diabetes and Digestive and Kidney Diseases, Harvard Catalyst, and National Center for Advancing Translational Sciences of the National Institutes of Health.

Background: Current hypertension guidelines vary substantially in their definition of who should be offered blood pressure–lowering medications. Understanding the effect of guideline choice on the proportion of adults who require treatment is crucial for planning and scaling up hypertension care in low- and middle-income countries. Methods: We extracted cross-sectional data on age, sex, blood pressure, hypertension treatment and diagnosis status, smoking, and body mass index for adults 30 to 70 years of age from nationally representative surveys in 50 low- and middle-income countries (N = 1 037 215). We aimed to determine the effect of hypertension guideline choice on the proportion of adults in need of blood pressure–lowering medications. We considered 4 hypertension guidelines: the 2017 American College of Cardiology/American Heart Association guideline, the commonly used 140/90 mm Hg threshold, the 2016 World Health Organization HEARTS guideline, and the 2019 UK National Institute for Health and Care Excellence guideline. Results: The proportion of adults in need of blood pressure–lowering medications was highest under the American College of Cardiology/American Heart Association, followed by the 140/90 mm Hg, National Institute for Health and Care Excellence, and World Health Organization guidelines (American College of Cardiology/American Heart Association: women, 27.7% [95% CI, 27.2–28.2], men, 35.0% [95% CI, 34.4–35.7]; 140/90 mm Hg: women, 26.1% [95% CI, 25.5–26.6], men, 31.2% [95% CI, 30.6–31.9]; National Institute for Health and Care Excellence: women, 11.8% [95% CI, 11.4–12.1], men, 15.7% [95% CI, 15.3–16.2]; World Health Organization: women, 9.2% [95% CI, 8.9–9.5], men, 11.0% [95% CI, 10.6–11.4]). Individuals who were unaware that they have hypertension were the primary contributor to differences in the proportion needing treatment under different guideline criteria. Differences in the proportion needing blood pressure–lowering medications were largest in the oldest (65–69 years) age group (American College of Cardiology/American Heart Association: women, 60.2% [95% CI, 58.8–61.6], men, 70.1% [95% CI, 68.8–71.3]; World Health Organization: women, 20.1% [95% CI, 18.8–21.3], men, 24.1.0% [95% CI, 22.3–25.9]). For both women and men and across all guidelines, countries in the European and Eastern Mediterranean regions had the highest proportion of adults in need of blood pressure–lowering medicines, whereas the South and Central Americas had the lowest. Conclusions: There was substantial variation in the proportion of adults in need of blood pressure–lowering medications depending on which hypertension guideline was used. Given the great implications of this choice for health system capacity, policy makers will need to carefully consider which guideline they should adopt when scaling up hypertension care in their country.

Objective: To determine body composition (BC) and the correlation, if any, between indices measured by anthropometry and dual-energy X-ray absorptiometry (DEXA).Design: Cross-sectional descriptive....

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.

Using a systematic review method, the prevalence of anaemia, iron deficiency (ID), and iron deficiency anaemia (IDA) in women of reproductive age (WRA) and children under 5 years of age was obtained to inform priorities in health planning and policy in South Africa. We searched electronic databases for articles published between 1997 and 2021. A total of 713 articles were identified, of which 14 articles comprising 9649 WRA and 4085 children were included. Since most of the included studies were of low quality, we did not pool data in a meta-analysis due to heterogeneity (I2 > 75%). In WRA, anaemia prevalence ranged from 22.0% to 44.0%; ID from 7.7% and 19.0%; and IDA from 10.5% to 9.7%. The prevalence of anaemia in pregnancy was 29.0% to 42.7%; and 60.6% to 71.3% in HIV-infected pregnant women. Three national surveys reported anaemia in children at 28.9%, 10.7%, and 61.3%, respectively. Overall, among the children under 5 years old, anaemia was more prevalent in 1-year-olds (52.0%) compared to the other age groups. Between 2005 and 2012, ID increased by 3.8% and IDA decreased by 83.2% in children. Anaemia in WRA and children under 5 years in South Africa was a moderate public health concern. Therefore, interventions addressing anaemia should be intensified, and policies on iron supplementation and food fortification need to be revised and aligned to the WHO multiple micronutrient supplementation recommendations.

Gastrointestinal symptoms (GIS) are common in kidney transplant candidates and recipients and may be worsened by HIV. Objective: To determine the frequency and severity of GIS in HIV-positive kidney transplant recipients from HIV-positive donors, and those waiting to receive one. A GIS rating scale (GSRS) was completed by 76 participants at baseline and at 6 months. GIS frequency was defined as having at least one symptom (GSRS > 1). Severity was indicated by the GSRS score. Transplant candidates: GIS frequency was 88.9% and 86.3% at baseline and 6 months respectively. Indigestion was the most frequent (79.6% and 66.7% at baseline and 6 months), and severe GIS (GSRS 2.3). Women reported global mean (p = 0.030) severity significantly more than men. Transplant recipients: GIS frequency was 95.2% and 76.2% at baseline and 6 months respectively. At both assessment points, indigestion occurred most frequently (85.7% and 61.9% respectively). Highest GSRS was reported for indigestion at baseline (2.33) and at 6 months (1.33). Waist circumference (WC) was positively associated with the severity of constipation GSRS. GIS are common in both groups, especially indigestions. WC in transplant recipients should be monitored.

Summary 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.

BACKGROUND The WHO recommends 400 g/d of fruits and vegetables (the equivalent of ∼5 servings/d) for the prevention of noncommunicable diseases (NCDs). However, there is limited evidence regarding individual-level correlates of meeting these recommendations in low- and middle-income countries (LMICs). In order to target policies and interventions aimed at improving intake, global monitoring of fruit and vegetable consumption by socio-demographic subpopulations is required. OBJECTIVES The aims of this study were to 1) assess the proportion of individuals meeting the WHO recommendation and 2) evaluate socio-demographic predictors (age, sex, and educational attainment) of meeting the WHO recommendation. METHODS Data were collected from 193,606 individuals aged ≥15 y in 28 LMICs between 2005 and 2016. The prevalence of meeting the WHO recommendation took into account the complex survey designs, and countries were weighted according to their World Bank population estimates in 2015. Poisson regression was used to estimate associations with socio-demographic characteristics. RESULTS The proportion (95% CI) of individuals aged ≥15 y who met the WHO recommendation was 18.0% (16.6-19.4%). Mean intake of fruits was 1.15 (1.10-1.20) servings per day and for vegetables, 2.46 (2.40-2.51) servings/d. The proportion of individuals meeting the recommendation increased with increasing country gross domestic product (GDP) class (P

HRQOL in transplant candidates and recipients who are also infected with HIV and are awaiting a kidney, or have received one from a HIV-positive donor, has not been previously investigated.The HRQOL of 47 HIV-positive kidney transplant candidates and 21 recipients from HIV-positive donors was evaluated using the Short Form-36 (SF-36) and face to face interviews at baseline and at 6 months. The correlation between SF-36 scores and sociodemographic, clinical and nutritional factors was determined.68 patients completed the SF-36 at baseline and 6 months. Transplant candidates: transplant candidates had lower HRQOL than recipients. The main mental stressors were income, employment and waiting for a donor. Physical health complaints were body pain (BP) and fatigue. Pre-albumin and BMI was positively correlated with general health at baseline (r = 0.401, p = 0.031 and r = 0.338, p = 0.025). Besides a positive association with role physical (RP) and BP, albumin was associated with overall physical composite score (PCS) (r = 0.329, p = 0.024) at 6 months. Transplant recipients: Transplant recipients had high HRQOL scores in all domains. PCS was 53.8 ± 10.0 and 56.6 ± 6.5 at baseline and 6 months respectively. MCS was 51.3 ± 11.5 and 54.2 ± 8.5 at baseline and 6 months respectively. Albumin correlated positively with PCS (r = 0.464, p = 0.034) at 6 months and role emotional (RE) (r = 0.492, p = 0.024). Higher pre-albumin was associated with better RE and RP abilities and MCS (r = 0.495, p = 0.034). MAMC was associated with four domains of physical health and strongly correlated with PCS (r = 0.821, p = 0.000).Strategies to improve HRQOL include ongoing social support, assistance with employment issues and optimising nutritional status.

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., Author summary Why was this study done? CVD burden in low-income and middle-income countries (LMICs) is high and rising. CVD risk estimation using validated risk prediction equations is recommended in most guidelines; however, there are few population-representative analyses of CVD risk and its association with socio-demographic characteristics. Despite guidelines recommending using CVD risk estimates as an essential first step in guiding management practices, the extent to which risk-based approaches are being implemented in LMICs is not well characterised. What did the researchers do and find? We analysed population-representative survey data from 45 LMICs to determine country-specific levels of CVD risk, associations between socio-demographic factors and levels of CVD risk, and adherence to WHO guidelines on use of blood pressure medication. We found high variation in CVD risk profiles, with higher levels of risk in the Europe and the Eastern Mediterranean region and lower levels of risk in sub-Saharan Africa, as well as an inverse association between CVD risk and higher education and employment in most countries. We found an underuse of medicines in people at elevated CVD risk across all countries (only 24.2% of males and 41.6% of females at high CVD risk are taking guideline-recommended BP medication) and an overuse of medicines in people at lower levels of CVD risk, with 47% of all BP medication being used by people at low CVD risk without a guideline indication for use. What do these findings mean? There is large variation in CVD risk across LMICs, and an inverse association between CVD risk and higher education and employment in most countries. There is an overuse of medicines in people at lower levels of CVD risk and an underuse of medicines in people at elevated CVD risk across all countries. The large heterogeneity of the findings in this study reflects varying country contexts. Country-specific targeted policies are needed to improve the identification and management of those at highest CVD risk.

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.

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.

To determine the current vitamin A status of a nationally representative sample of women aged 16–35 years, compare it with previous national data, and determine the impact of sociodemography, diet, and body size on vitamin A status, we performed secondary analysis of data on South African women who participated in the first South African National Health and Nutrition Examination Survey (SANHANES-1). Vitamin A status was assessed by serum retinol, and the findings are reported as means and prevalences with corresponding 95% confidence intervals. Overall, the age-standardized vitamin A deficiency prevalence was 11.7%, a decrease from previous national data, but serum retinol levels remained lower than in other developing countries. Overall, unweighted, multilevel, multivariate logistic regression showed that vitamin A deficiency was influenced by race only (odds ratio (OR) = 1.89, P = 0.031), while weighted multiple logistic regression for 16- to 18-year-olds showed that vitamin A deficiency was influenced by locality (OR = 9.83, P = 0.005) and household income (intermediate (OR = 0.2, P = 0.022) and upper (OR = 0.25, P = 0.049)). Despite the decreased prevalence, vitamin A deficiency remains a moderate public health problem in the country. Opportunities for targeted interventions have been identified.

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., Author summary Why was the study done? Diseases such as high blood pressure and diabetes are becoming increasingly common in low- and middle-income countries (LMICs). Treatment for these conditions is simple and cheap. However, without treatment, sufferers are at high risk of adverse consequences, such as heart attacks and strokes. It is important therefore to be able to measure whether patients who need treatment are getting it. Currently, LMICs’ progress towards being able to treat patients with hypertension and diabetes is measured using proxies, for example, whether policies, guidelines, funding, structures, or human resources are in place. What did the researchers find? We measured whether 187,552 people with hypertension living in 43 LMICs and 40,795 people with diabetes living in 28 LMICs had their high blood pressure or diabetes treated well; i.e., they had these conditions diagnosed, treated, or controlled. We found that most proxy measures were not reflective of whether patients had their condition treated well. What do these findings mean? To judge countries’ progress towards ability to treat hypertension and diabetes requires directly assessing whether people with these diseases are getting the treatment that they need. The main limitation of the study was that a one-time measurement of blood pressure or blood glucose was used to define whether participants had high blood pressure or diabetes. To make a concrete clinical diagnosis requires more detailed investigation.

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., Using individual participant data from a large cohort study, Jennifer Manne-Goehler and colleagues reveal poor healthcare provision for diabetes patients in 28 LMICs., Author summary Why was this study done? Diabetes is a growing problem in low-income and middle-income countries, which already carry about 75% of the global diabetes burden, but there is limited evidence to guide policymaking in these settings. Prior studies have analyzed the cascade of care for diabetes in single-country or subnational contexts, but to our knowledge there have been no prior multi-country analyses on this subject. This study analyzes nationally representative data regarding health system performance for people who have diabetes, as defined by biological criteria, across a spectrum of levels of economic development. What did the researchers do and find? We harmonized nationally representative population-based survey data from 28 low-income and middle-income countries in 4 geographic regions, and used these data to construct the diabetes care cascade stratified by individual factors and national income. In this sample of over 800,000 adults, the overall prevalence of diabetes was 8.8% (95% CI: 8.2%–9.5%), of which 4.8% (95% CI: 4.5%–5.2%) was undiagnosed. In this study, we found that health system performance for diabetes showed large losses to care at the stage of detection (63.4% [95% CI: 56.7%–69.6%]) and low rates of diabetes control (22.8% [95% CI: 20.9%–24.9%]). Total unmet need for diabetes care (defined as the sum of undetected, detected but undiagnosed, diagnosed but untreated, and treated but not controlled diabetes) was 77.0% (95% CI: 74.9%–78.9%). Performance along the care cascade was better in upper-middle-income countries, but across all World Bank income groups, only 16%–25% of those with diabetes achieved diabetes control. Increasing age, educational attainment, and overweight or obesity were associated with higher odds of being tested, treated, and achieving control. What do these findings mean? There is a large unmet need for diabetes care that reflects the need for a greater investment of health resources to strengthen systems of care for this disease. Given that diabetes is considered a tracer condition for examining health systems, these findings also indicate that many countries face challenges in achieving universal health coverage.

This study investigated the associations between underweight, obesity and body image (BI) among 15+ year-old South Africans with diverse socio-demographic backgrounds. A cross-sectional survey and the analyses of data for 6411 15+ year-old participants in the first South African National Health and Nutrition Examination Survey was undertaken. Body image was compared to body mass index (BMI) and socio-demography. Data were analyzed using SPSS versions 25. Results are in percentages, means, 95% confidence intervals, p-values, and odds ratios. Overall, participants who were obese of which majority: were females, earned ZAR 9601+, completed grade 6, were non-Black men, were married and resided in urban formal areas, were more likely to underestimate their BMI and desire to be lighter. Participants who were underweight of which majority: were males, had no form of income or education, were black men, were not married, resided in less urban and farm areas, were younger than 25 years, were more likely to overestimate their BMI and desire to be heavier. While underweight and obesity were strong determinants of BI, BI was differentiated by socio-demography. These findings have a public health implication that requires special attention to curb the irrepressible underweight and obesity in South Africa.

Introduction: As diabetes increases in LMICs, there is a need for more evidence to guide health systems planning. We used a cascade of care approach to assess health system performance among adults (=15 years) in LMICs. Methods: We pooled individual data from 25 nationally representative surveys. Diabetes was defined as FBG=126 mg/dL, RBG=200 mg/dL, HbA1c=6.5%, or on medication. Stages of the care cascade included: screening, diagnosis, lifestyle advice and/or medication (“treatment”), and control (HbA1c =8.0%). Linear probability models were used to evaluate predictors (age, sex, education, and wealth quintile) of (1) treatment and (2) control. Results: Across all countries, the largest losses to care occur at screening (Table). While health service access increases with increasing country income group, rates of disease control are similar. Prediction models show that treatment is 31.1 percentage points (95% CI: 12.6-49.5) lower in the youngest age group compared to the oldest and that control is 3.9 percentage points (95% CI: 1.8-6.1) lower in men than women. Conclusions: Diabetes prevalence is substantial across LMICs, particularly in Latin America and the Caribbean. Overall rates of screening are low and only 23% of those with diabetes achieve control, which is less than half of that in the U.S. (64%). Policy interventions that link adults with diabetes to care and improve disease control in LMICs are needed. The diabetes cascade of care in 25 LMICS (N=92,141)RegionPrevalence (95% CI)Screened (95% CI)Diagnosed (95% CI)Completed (95% CI)Controlled (95% CI)Sub-Saharan Africa3.9 (3.0 - 5.0)53.1 (46.3 - 60.0)38.7 (32.9 - 45.0)36.0 (30.4 - 42.0)21.2 (16.7 - 26.3)Latin America & the Caribbean28.4 (23.7 - 33.7)79.8 (74.2 - 84.4)63.7 (57.9 - 69.3)48.9 (42.3 - 55.6)33.1 (26.8 - 40.1)South & Southeast Asia7.5 (7.1 - 7.9)57.5 (47.6 - 66.9)46.1 (36.9 - 55.6)45.2 (36.0 - 54.7)29.1 (22.0 - 37.5)Low-income group2.7 (2.1 - 3.5)39.9 (34.4 - 45.6)32.7 (27.2 - 38.5)31.4 (26.0 - 37.3)21.0 (16.0 - 27.1)Lower-middle income group7.7 (6.6 - 8.9)57.1 (46.0 - 67.6)38.2 (27.8 - 49.8)35.2 (25.0 - 47.0)23.9 (15.2 - 35.4)Upper-middle income group9.3 (5.5 - 15.3)68.9 (60.9 - 75.8)47.9 (40.3 - 55.5)41.7 (34.8 - 48.8)24.1 (19.1 - 30.0)Overall8.5 (5.9 - 12.0)57.9 (52.8 - 62.9)41.8 (37.1 - 46.6)37.6 (33.2 - 42.2)23.0 (19.5 - 27.0) Disclosure J. Manne-Goehler: None. P. Geldsetzer: None. D. Houinato: None. C. Houehanou: None. M.S. Gurung: None. G.M. Andall-Brereton: None. S. Crooks: None. K. Joseph: None. C. Wesseh: None. B. Norov: None. K.K. Aryal: None. K.B. Karki: None. P. Bovet: None. D. Labadarios: None. A. Stokes: None. M.T. Mayige: None. G.B. Kagaruki: None. D. Guwatudde: None. B.K. Silver: None. J.M. Jorgensen: None. S. Vollmer: None. J.I. Davies: None. T. Barnighausen: None. L.M. Jaacks: None.

The study compared hemoglobin (Hb) and serum ferritin levels between adolescent and adult women with different body mass indices, dietary intake, and sociodemography. A secondary analysis of data for 3177 South African women ⩾15 years of age who participated in the SANHANES-1 study was undertaken. Abnormal Hb (≤12 g/dL) and serum ferritin (15 μg/mL) were based on the World Health Organization's criteria for nonpregnant women aged ⩾15 years. Data were analyzed using STATA version 11. Overall, anemia was detected in 740 (23.3%) participants. Of the individuals in the subsample (n = 1123, 15-35 years) who had serum ferritin measured, 6.0% presented with iron depletion (ID) and 10.8% presented with iron-deficiency anemia (IDA). The highest prevalences of anemia, ID, and IDA were in 15- to 18-year-olds (11.2%, 8.8%, and 20.2%, respectively). Black young adults (19-24 years) were up to 40 times more likely to present with ID compared with their non-black counterparts. While overweight adolescents were three times more likely to be anemic, overweight and obese young adults, as well as obese older adults (25-35 years), were less likely to be anemic compared with normal-weight women of all age groups. Overconsumption of dietary fat increased ID by up to 54- and 11-fold (adolescents and 25- to 35-year-olds, respectively). In South Africa, anemia is most prevalent in adolescents and black women. Anemia is also an indicator of overconsumption of dietary fat and a marker of socioeconomic disadvantage.

To determine the current vitamin A status of a nationally representative sample of women aged 16-35 years, compare it with previous national data, and determine the impact of sociodemography, diet, and body size on vitamin A status, we performed secondary analysis of data on South African women who participated in the first South African National Health and Nutrition Examination Survey (SANHANES-1). Vitamin A status was assessed by serum retinol, and the findings are reported as means and prevalences with corresponding 95% confidence intervals. Overall, the age-standardized vitamin A deficiency prevalence was 11.7%, a decrease from previous national data, but serum retinol levels remained lower than in other developing countries. Overall, unweighted, multilevel, multivariate logistic regression showed that vitamin A deficiency was influenced by race only (odds ratio (OR) = 1.89, P = 0.031), while weighted multiple logistic regression for 16- to 18-year-olds showed that vitamin A deficiency was influenced by locality (OR = 9.83, P = 0.005) and household income (intermediate (OR = 0.2, P = 0.022) and upper (OR = 0.25, P = 0.049)). Despite the decreased prevalence, vitamin A deficiency remains a moderate public health problem in the country. Opportunities for targeted interventions have been identified.

Introduction Hypertension has become a major cause of morbidity and premature mortality in South Africa, but population-wide estimates of prevalence and access to care are scarce. Using data from the South African National Health and Nutrition Examination Survey (2011–2012), this analysis evaluates the national prevalence of hypertension and uses a care cascade to examine unmet need for care. Methods Hypertension was defined as blood pressure over 140/90 mm Hg or use of antihypertensive medication. We constructed a hypertension care cascade by decomposing the population with hypertension into five mutually exclusive and exhaustive subcategories: (1) unscreened and undiagnosed, (2) screened but undiagnosed, (3) diagnosed but untreated, (4) treated but uncontrolled and (5) treated and controlled. Multivariable logistic regression models were used to explore factors associated with hypertension prevalence and diagnosis. Results In South Africans aged 15 and above, the age standardised prevalence of hypertension was 35.1%. Among those with hypertension, 48.7% were unscreened and undiagnosed, 23.1% were screened but undiagnosed, 5.8% were diagnosed but untreated, 13.5% were treated but uncontrolled and 8.9% were controlled. The hypertension care cascade demonstrates that 49% of those with hypertension were lost at the screening stage, 50% of those who were screened never received a diagnosis, 23% of those who were diagnosed did not receive treatment and 48% of those who were treated did not reach the threshold for control. Men and older individuals had increased risks of being undiagnosed after controlling for other factors. Conclusions There is significant unmet need for hypertension care in South Africa; 91.1% of the hypertensive population was unscreened, undiagnosed, untreated or uncontrolled. Data from this study provide insight into where patients are lost in the hypertension care continuum and serve as a benchmark for evaluating efforts to manage the rising burden of hypertension in South Africa.

Background Diabetes is a serious and growing public health concern in South Africa, but its prevalence and distribution in pregnant women is not well known. Women diagnosed with diabetes during pregnancy have a substantially greater risk of adverse health outcomes for both mother and child. This study aims to determine the prevalence and social determinants of diabetes during pregnancy in South Africa. Methods Data used in this study were from the 2012 South African National Nutrition and Health Examination Survey; a nationally representative cross-sectional household survey. The analysis was restricted to girls and women between the ages of 15 to 49 years who self-reported ever being pregnant (n = 4261) Logistic regression models were constructed to analyse the relationship between diabetes during pregnancy and several indicators including race, family history of diabetes, household income, area of residence and obesity. Results The prevalence of diabetes during pregnancy in South Africa was 3% (144 women) of all women who reported ever being pregnant. The majority of the women who had ever had diabetes were African (70%), 51% were unemployed and 76% lived in rural areas. Factors strongly associated with diabetes during pregnancy were age (1.04 [Odds Ratio], 0.01 [Standard Error]), family history of diabetes (3.04; 0.8) and race (1.91; 0.53). Conclusion The analysis will contribute to an understanding of the prevalence of diabetes during pregnancy and its social determinants. This will help in the development of effective interventions targeted at improving maternal and child health for mothers at high risk.

Objectives: The aim of this study was to determine the best dietary diversity indicator to measure dietary diversity and micronutrient adequacy in children. Methods: A national representative cross-sectional survey of children ages 1 to 9 y (N ¼ 2,200) was undertaken in all ethnic groups in South Africa. A 24-h recall was done with the mother or caregiver of each child. A dietary diversity score (DDS), the number of food groups consumed at least once in a period of 24 h, was calculated for each child in accordance with 6-, 9-, 13-, and 21food group (G) indicators and compared with a mean adequacy ratio (MAR). The nutrient adequacy ratio (NAR) was calculated for 11 micronutrients by comparing the distributions of estimated intakes with the Estimated Average Requirements for that micronutrient. The MAR was the average of all NARs. Correlations were done between MAR and DDS and sensitivity and specificity calculated for each group indicator. Results: Pearson’s correlations between food group indicators and MAR indicate that r values were all highly significant (P < 0.0001). There were no consistent or large differences found between the different group indicators although G13 and G21 appeared to be marginally better. Sensitivity and specificity values in the current study lay between DDS of 3 and 5, suggesting one of these as the best indication of (low) micronutrient adequacy. Conclusions: Overall results seem to indicate that any of the four G indicators can be used in dietary assessment studies on children, with G13 and G21 being marginally better. A cut-off DDS of 4 and 5, respectively, appear best.

This study investigated how psychological distress and the proxies for social position combine to influence the risk of both underweight and overweight in South Africans aged 15 years and older. This was a cross-sectional study that included 2254 men and 4170 women participating in the first South African National Health and Nutrition Examination Survey (SANHANES-1). An analysis exploring the associations of social and mental health characteristics with body mass index (BMI) was conducted using binary and multinomial logistic regressions. Results suggested that, overall, women had a higher risk of overweight/obesity compared to men (age-adjusted odds ratio [AOR] 4.65, 95% confidence intervals [CI] 3.94&ndash, 5.50). The gender effect on BMI was smaller in non-African participants (AOR 3.02, 95% CI 2.41&ndash, 3.79, p-value for interaction = 0.004). Being employed and having a higher level of education were associated with higher risks of overweight and obesity and a lower risk of underweight. Being single or without a spouse and poor mental health were found to increase the odds of being underweight, especially in men. To conclude, there are strong social gradients and important gender and ethnic differences in how BMI is distributed in the South African population.

South Africa faces an epidemic of chronic non-communicable diseases (NCDs), yet national surveillance is limited due to the lack of recent data. We used data from the first comprehensive national survey on NCDs-the South African National Health and Nutrition Examination Survey (SANHANES-1 (2011-2012))-to evaluate the prevalence of and health system response to diabetes through a diabetes care cascade. We defined diabetes as a Hemoglobin A1c equal to or above 6.5% or currently on treatment for diabetes. We constructed a diabetes care cascade by categorizing the population with diabetes into those who were unscreened, screened but undiagnosed, diagnosed but untreated, treated but uncontrolled, and treated and controlled. We then used multivariable logistic regression models to explore factors associated with diagnosed and undiagnosed diabetes. The age-standardized prevalence of diabetes in South Africans aged 15+ was 10.1%. Prevalence rates were higher among the non-white population and among women. Among individuals with diabetes, a total of 45.4% were unscreened, 14.7% were screened but undiagnosed, 2.3% were diagnosed but untreated, 18.1% were treated but uncontrolled, and 19.4% were treated and controlled, suggesting that 80.6% of the diabetic population had unmet need for care. The diabetes care cascade revealed significant losses from lack of screening, between screening and diagnosis, and between treatment and control. These results point to significant unmet need for diabetes care in South Africa. Additionally, this analysis provides a benchmark for evaluating efforts to manage the rising burden of diabetes in South Africa.

This article presents key findings from the 2012 HIV prevalence, incidence and behaviour survey conducted in South Africa and explores trends in the HIV epidemic. A representative household based survey collected behavioural and biomedical data among people of all ages. Chi-squared test for association and formal trend tests (2002, 2005, 2008 and 2012) were used to test for associations and trends in the HIV epidemic across the four surveys. In 2012 a total of 38 431 respondents were interviewed from 11 079 households; 28 997 (67.5%) of 42 950 eligible individuals provided blood specimens. HIV prevalence was 12.2% [95% CI: 11.4–13.1] in 2012 with prevalence higher among females 14.4% than males 9.9%. Adults aged 25–49 years were most affected, 25.2% [95% CI: 23.2–27.3]. HIV prevalence increased from 10.6% [95%CI: 9.8–11.6] in 2008 to 12.2% [95% CI: 11.4–13.1] in 2012 (p < 0.001). Antiretroviral treatment (ART) exposure doubled from 16.6% in 2008 to 31.2% in 2012 (p < 0.001). HIV incidence in 2012 among persons 2 years and older was 1.07% [95% CI: 0.87–1.27], with the highest incidence among Black African females aged 20–34 years at 4.5%. Sexual debut before 15 years was reported by 10.7% of respondents aged 15–24 years, and was significantly higher among male youth than female (16.7% vs. 5.0% respectively, p < 0.001). Reporting of multiple sexual partners in the previous 12 months increased from 11.5% in 2002 to 18.3% in 2012 (p < 0.001). Condom use at last sex dropped from 45.1% in 2008 to 36.2% in 2012 (p < 0.001). Levels of accurate HIV knowledge about transmission and prevention were low and had decreased between 2008 and 2012 from 31.5% to 26.8%. South Africa is on the right track with scaling up ART. However, there have been worrying increases in most HIV-related risk behaviours. These findings suggest that there is a need to scale up prevention methods that integrate biomedical, behavioural, social and structural prevention interventions to reverse the tide in the fight against HIV.Keywords: antiretroviral treatment, HIV incidence, HIV knowledge, household survey, sexual behaviour

Background South Africa is one of the 22 high tuberculosis burden countries that contribute 80 % of the global tuberculosis cases. Tuberculosis is infectious and due to its rapid and easy transmission route poses a threat to population health. Considering the importance of social and psychological factors in influencing health outcomes, appraising knowledge and awareness of tuberculosis, remain vital for effective tuberculosis control. The main aim of this study was to investigate the factors that predict knowledge about tuberculosis among 18–64 year old adults in South Africa. Methods A cross-sectional survey method was used. Multi-stage disproportionate, stratified cluster sampling was used to select households within enumeration areas stratified by province and locality type. Based on the Human Sciences Research Council 2007 master sample, 500 Enumerator Areas representative of the socio-demographic profile of South Africa were identified and a random sample of 20 households was randomly selected from each Enumerator Area, yielding an overall sample of 10 000 households. The tuberculosis module contained in the South African National Health And Nutrition Examination Survey I was the only module that examined the social determinants of an infectious disease. This module was questionnaire-based with no biomarkers obtained to screen for the presence of tuberculosis disease among the participants. Data was collected by administering a researcher developed individual level questionnaire. Simple and multiple linear regression was used to determine the independent variables associated with tuberculosis knowledge. Results Half the sample (52.6 %) was female and the majority of the respondents were black African (76.5 %). More than two thirds (68.0 %) resided in urban areas, 56.9 % did not complete high school and half were not in formal employment. Significant predictors of tuberculosis knowledge were race, sex, completion of high school, being in employment, having a diagnosis of the disease in ones’ life-time and learning about tuberculosis from television, brochures, health workers, and teachers. Conclusions To reduce the burden of tuberculosis in South Africa, media campaigns targeting both rural and urban communities should include conveying accurate information about the disease. Policy makers should also address structural barriers that vulnerable communities face. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-2951-y) contains supplementary material, which is available to authorized users.

Estimates of the parameters used in the model.docx. Tables displaying parameter estimates used as inputs for the model. (DOCX 24 kb)

Summary Background Despite widespread recognition that the burden of diabetes is rapidly growing in many countries in sub-Saharan Africa, nationally representative estimates of unmet need for diabetes diagnosis and care are in short supply for the region. We use national population-based survey data to quantify diabetes prevalence and met and unmet need for diabetes diagnosis and care in 12 countries in sub-Saharan Africa. We further estimate demographic and economic gradients of met need for diabetes diagnosis and care. Methods We did a pooled analysis of individual-level data from nationally representative population-based surveys that met the following inclusion criteria: the data were collected during 2005–15; the data were made available at the individual level; a biomarker for diabetes was available in the dataset; and the dataset included information on use of core health services for diabetes diagnosis and care. We first quantified the population in need of diabetes diagnosis and care by estimating the prevalence of diabetes across the surveys; we also quantified the prevalence of overweight and obesity, as a major risk factor for diabetes and an indicator of need for diabetes screening. Second, we determined the level of met need for diabetes diagnosis, preventive counselling, and treatment in both the diabetic and the overweight and obese population. Finally, we did survey fixed-effects regressions to establish the demographic and economic gradients of met need for diabetes diagnosis, counselling, and treatment. Findings We pooled data from 12 nationally representative population-based surveys in sub-Saharan Africa, representing 38 311 individuals with a biomarker measurement for diabetes. Across the surveys, the median prevalence of diabetes was 5% (range 2–14) and the median prevalence of overweight or obesity was 27% (range 16–68). We estimated seven measures of met need for diabetes-related care across the 12 surveys: (1) percentage of the overweight or obese population who received a blood glucose measurement (median 22% [IQR 11–37]); and percentage of the diabetic population who reported that they (2) had ever received a blood glucose measurement (median 36% [IQR 27–63]); (3) had ever been told that they had diabetes (median 27% [IQR 22–51]); (4) had ever been counselled to lose weight (median 15% [IQR 13–23]); (5) had ever been counselled to exercise (median 15% [IQR 11–30]); (6) were using oral diabetes drugs (median 25% [IQR 18–42]); and (7) were using insulin (median 11% [IQR 6–13]). Compared with those aged 15–39 years, the adjusted odds of met need for diabetes diagnosis (measures 1–3) were 2·22 to 3·53 (40–54 years) and 3·82 to 5·01 (≥55 years) times higher. The adjusted odds of met need for diabetes diagnosis also increased consistently with educational attainment and were between 3·07 and 4·56 higher for the group with 8 years or more of education than for the group with less than 1 year of education. Finally, need for diabetes care was significantly more likely to be met (measures 4–7) in the oldest age and highest educational groups. Interpretation Diabetes has already reached high levels of prevalence in several countries in sub-Saharan Africa. Large proportions of need for diabetes diagnosis and care in the region remain unmet, but the patterns of unmet need vary widely across the countries in our sample. Novel health policies and programmes are urgently needed to increase awareness of diabetes and to expand coverage of preventive counselling, diagnosis, and linkage to diabetes care. Because the probability of met need for diabetes diagnosis and care consistently increases with age and educational attainment, policy makers should pay particular attention to improved access to diabetes services for young adults and people with low educational attainment. Funding None.

Correct knowledge for the six individual knowledge items by demographic characteristics, TB diagnosis and sources of information on TB. (DOCX 33Â kb)