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.

Health-related quality of life and associated factors in HIV-positive transplant candidates and recipients from a HIV-positive donor.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSION: Strategies to improve HRQOL include ongoing social support, assistance with employment issues and optimising nutritional status.

Prevalence of Anaemia, Iron Deficiency, and Iron Deficiency Anaemia in Women of Reproductive Age and Children under 5 Years of Age in South Africa (1997-2021): A Systematic Review.

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.

Targeting Hypertension Screening in Low- and Middle-Income Countries: A Cross-Sectional Analysis of 1.2 Million Adults in 56 Countries.

Background As screening programs in low- and middle-income countries (LMICs) often do not have the resources to screen the entire population, there is frequently a need to target such efforts to easily identifiable priority groups. This study aimed to determine (1) how hypertension prevalence in LMICs varies by age, sex, body mass index, and smoking status, and (2) the ability of different combinations of these variables to accurately predict hypertension. Methods and Results We analyzed individual-level, nationally representative data from 1 170 629 participants in 56 LMICs, of whom 220 636 (18.8%) had hypertension. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or reporting to be taking blood pressure-lowering medication. The shape of the positive association of hypertension with age and body mass index varied across world regions. We used logistic regression and random forest models to compute the area under the receiver operating characteristic curve in each country for different combinations of age, body mass index, sex, and smoking status. The area under the receiver operating characteristic curve for the model with all 4 predictors ranged from 0.64 to 0.85 between countries, with a country-level mean of 0.76 across LMICs globally. The mean absolute increase in the area under the receiver operating characteristic curve from the model including only age to the model including all 4 predictors was 0.05. Conclusions Adding body mass index, sex, and smoking status to age led to only a minor increase in the ability to distinguish between adults with and without hypertension compared with using age alone. Hypertension screening programs in LMICs could use age as the primary variable to target their efforts.

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.

Variation in the Proportion of Adults in Need of Blood Pressure-Lowering Medications by Hypertension Care Guideline in Low- and Middle-Income Countries: A Cross-Sectional Study of 1 037 215 Individuals From 50 Nationally Representative Surveys.

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.

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.

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

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

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

OBJECTIVE: The prevalence of type 2 diabetes is rising rapidly in low-income and middle-income countries (LMICs), but the factors driving this rapid increase are not well understood. Adult height, in particular shorter height, has been suggested to contribute to the pathophysiology and epidemiology of diabetes and may inform how adverse environmental conditions in early life affect diabetes risk. We therefore systematically analyzed the association of adult height and diabetes across LMICs, where such conditions are prominent. RESEARCH DESIGN AND METHODS: We pooled individual-level data from nationally representative surveys in LMICs that included anthropometric measurements and diabetes biomarkers. We calculated odds ratios (ORs) for the relationship between attained adult height and diabetes using multilevel mixed-effects logistic regression models. We estimated ORs for the pooled sample, major world regions, and individual countries, in addition to stratifying all analyses by sex. We examined heterogeneity by individual-level characteristics. RESULTS: Our sample included 554,122 individuals across 25 population-based surveys. Average height was 161.7 cm (95% CI 161.2-162.3), and the crude prevalence of diabetes was 7.5% (95% CI 6.9-8.2). We found no relationship between adult height and diabetes across LMICs globally or in most world regions. When stratifying our sample by country and sex, we found an inverse association between adult height and diabetes in 5% of analyses (2 out of 50). Results were robust to alternative model specifications. CONCLUSIONS: Adult height is not associated with diabetes across LMICs. Environmental factors in early life reflected in attained adult height likely differ from those predisposing individuals for diabetes.

Body Image and the Double Burden of Nutrition among South Africans from Diverse Sociodemographic Backgrounds: SANHANES-1.

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.

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

OBJECTIVE: Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship of education, household wealth, and BMI with diabetes risk. RESEARCH DESIGN AND METHODS: We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall and by country, World Bank income group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR). RESULTS: Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI 7.1-8.0) and of undiagnosed diabetes 4.9% (4.6-5.3). Diabetes prevalence increased with increasing WBIG: countries with low-income economies (LICs) 6.7% (5.5-8.1), lower-middle-income economies (LMIs) 7.1% (6.6-7.6), and upper-middle-income economies (UMIs) 8.2% (7.5-9.0). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, after adjusting for BMI (LICs RR 1.47 [95% CI 1.22-1.78], LMIs 1.14 [1.06-1.23], and UMIs 1.28 [1.02-1.61]). CONCLUSIONS: Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk.

Social and Psychological Predictors of Body Mass Index among South Africans 15 Years and Older: SANHANES-1.

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] 3.94-5.50). The gender effect on BMI was smaller in non-African participants (AOR 3.02; 95% CI 2.41-3.79; 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.

Psychological distress and C-reactive protein in a South African national survey.

OBJECTIVE: To examine the association of psychological distress with serum C-reactive protein (CRP) in a South African cohort. METHODS: Data were analysed on individuals aged ≥15 years from the South African National Health and Nutrition Examination Survey (SANHANES) of 2012. Psychological distress was evaluated using the Kessler Psychological Distress Scale. Linear regression models assessed the association of psychological distress with serum CRP, adjusting for possible confounding factors. RESULTS: The analytic sample comprised n = 3944 individuals (mean age = 40 and sex = 36% males). Psychological distress was significantly associated with increased serum CRP levels (B = 0.31 and p = 0.001). This association was no longer significant after adjusting for demographic variables, lifestyle factors, cardiac disease, diabetes, hypertension, trauma and anti-inflammatory medication use (B = 0.15 and p = 0.062). CONCLUSION: Psychological distress was associated with elevated levels of CRP among South African adults. However, the association was confounded by a range of factors, with demographic variables (age, sex and population group) having the largest confounding effect. These findings indicate that CRP is not a useful biomarker of psychological distress, and that additional work is needed on the underlying psychobiology of psychological distress.

The state of hypertension care in 44 low-income and middle-income countries: a cross-sectional study of nationally representative individual-level data from 1·1 million adults.

BACKGROUND: Evidence from nationally representative studies in low-income and middle-income countries (LMICs) on where in the hypertension care continuum patients are lost to care is sparse. This information, however, is essential for effective targeting of interventions by health services and monitoring progress in improving hypertension care. We aimed to determine the cascade of hypertension care in 44 LMICs-and its variation between countries and population groups-by dividing the progression in the care process, from need of care to successful treatment, into discrete stages and measuring the losses at each stage. METHODS: In this cross-sectional study, we pooled individual-level population-based data from 44 LMICs. We first searched for nationally representative datasets from the WHO Stepwise Approach to Surveillance (STEPS) from 2005 or later. If a STEPS dataset was not available for a LMIC (or we could not gain access to it), we conducted a systematic search for survey datasets; the inclusion criteria in these searches were that the survey was done in 2005 or later, was nationally representative for at least three 10-year age groups older than 15 years, included measured blood pressure data, and contained data on at least two hypertension care cascade steps. Hypertension was defined as a systolic blood pressure of at least 140 mm Hg, diastolic blood pressure of at least 90 mm Hg, or reported use of medication for hypertension. Among those with hypertension, we calculated the proportion of individuals who had ever had their blood pressure measured; had been diagnosed with hypertension; had been treated for hypertension; and had achieved control of their hypertension. We weighted countries proportionally to their population size when determining this hypertension care cascade at the global and regional level. We disaggregated the hypertension care cascade by age, sex, education, household wealth quintile, body-mass index, smoking status, country, and region. We used linear regression to predict, separately for each cascade step, a country's performance based on gross domestic product (GDP) per capita, allowing us to identify countries whose performance fell outside of the 95% prediction interval. FINDINGS: Our pooled dataset included 1 100 507 participants, of whom 192 441 (17·5%) had hypertension. Among those with hypertension, 73·6% of participants (95% CI 72·9-74·3) had ever had their blood pressure measured, 39·2% of participants (38·2-40·3) had been diagnosed with hypertension, 29·9% of participants (28·6-31·3) received treatment, and 10·3% of participants (9·6-11·0) achieved control of their hypertension. Countries in Latin America and the Caribbean generally achieved the best performance relative to their predicted performance based on GDP per capita, whereas countries in sub-Saharan Africa performed worst. Bangladesh, Brazil, Costa Rica, Ecuador, Kyrgyzstan, and Peru performed significantly better on all care cascade steps than predicted based on GDP per capita. Being a woman, older, more educated, wealthier, and not being a current smoker were all positively associated with attaining each of the four steps of the care cascade. INTERPRETATION: Our study provides important evidence for the design and targeting of health policies and service interventions for hypertension in LMICs. We show at what steps and for whom there are gaps in the hypertension care process in each of the 44 countries in our study. We also identified countries in each world region that perform better than expected from their economic development, which can direct policy makers to important policy lessons. Given the high disease burden caused by hypertension in LMICs, nationally representative hypertension care cascades, as constructed in this study, are an important measure of progress towards achieving universal health coverage. FUNDING: Harvard McLennan Family Fund, Alexander von Humboldt Foundation.

Consumption of Fruits and Vegetables Among Individuals 15 Years and Older in 28 Low- and Middle-Income Countries.

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 < 0.0001) and with decreasing country FAO food price index (FPI; indicating greater stability of food prices; P < 0.0001). At the individual level, those with secondary education or greater were more likely to achieve the recommendation compared with individuals with no formal education: risk ratio (95% CI), 1.61 (1.24-2.09). CONCLUSIONS: Over 80% of individuals aged ≥15 y living in these 28 LMICs consumed lower amounts of fruits and vegetables than recommended by the WHO. Policies to promote fruit and vegetable consumption in LMICs are urgently needed to address the observed inequities in intake and prevent NCDs.

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

BACKGROUND: The prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach. METHODS AND FINDINGS: We pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given ("treated"), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%-9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%-5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%-78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys. CONCLUSIONS: The study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured.

Understanding the determinants of hemoglobin and iron status: adolescent-adult women comparisons in SANHANES-1.

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.

The impact of sociodemography, diet, and body size on serum retinol in women 16-35 years of age: SANHANES-1.

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.