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Background: Diabetes mellitus (DM) is associated with severe outcomes of coronavirus disease (COVID-19), including death. COVID-19 vaccination is crucial for preventing infection and severe disease in the general population, but most importantly, among high-risk populations such as persons with DM. However, while COVID-19 vaccination uptake in the general population is regularly tracked, information on vaccination behavior specific to persons with DM is scarce. This study aimed to identify factors associated with the uptake of full COVID-19 vaccination among persons living with DM at Kiruddu National Referral Hospital (KRH)., Methods: We employed a cross-sectional study design and administered a structured questionnaire on a systematically selected random sample of 340 people with DM attending Kiruddu National Referral Hospital from March 08 to May 25, 2023. We used a Modified Poisson Regression model to identify the factors associated with full COVID-19 vaccination and present adjusted prevalence ratios, along with their 95% confidence intervals. Full COVID-19 vaccination in this study was defined as having completed the last dose in the primary series of a COVID-19 vaccine., Results: We administered the questionnaire to 340 participants, with 75% (255 of 340) being female. The mean age of the participants was 52 years (± 12 years) and their median duration with diabetes mellitus was 5 years (± 7.3 years). Overall, 195 out of 340 participants (57.35%, 95% CI: 52-63%) completed the last dose in the primary series of a COVID-19 vaccine. The likelihood of receiving full vaccination was higher when a health provider advised one to receive a vaccine (aPR = 1.91, 95% CI: 1.20-3.02), when one reported having a comorbidity (aPR = 1.26, 95% CI: 1.06-1.53), and when one had a strong perceived benefit of vaccination (aPR = 1.76, 95% CI: 1.23-2.53). However, having a strong perceived barrier to vaccination was negatively associated with the likelihood of being fully vaccinated (aPR = 0.71, 95% CI: 0.60-0.84)., Conclusion: The uptake of COVID-19 vaccines among persons with DM at KRH is low, with only 57% having a full COVID-19 vaccination status. This underscores the progress in meeting the WHO recommendation of having a 100% COVID-19 vaccination uptake among people with underlying health conditions, including diabetes mellitus. At the policy level, the Ugandan Ministry of Health (MoH) may implement a provider-initiated vaccination strategy where healthcare providers who attend to DM patients during their routine clinic visits initiate the idea of vaccinating, sensitize, and spearhead myth-bursting around COVID-19 vaccines., (© 2024. The Author(s).)

Background: Testing for the risk factors of cardiovascular disease, which include hypertension, diabetes, and hypercholesterolaemia, is important for timely and effective risk management. Yet few studies have quantified and analysed testing of cardiovascular risk factors in low-income and middle-income countries (LMICs) with respect to sociodemographic inequalities. We aimed to address this knowledge gap., Methods: In this cross-sectional analysis, we pooled individual-level data for non-pregnant adults aged 18 years or older from nationally representative surveys done between Jan 1, 2010, and Dec 31, 2019 in LMICs that included a question about whether respondents had ever had their blood pressure, glucose, or cholesterol measured. We analysed diagnostic testing performance by quantifying the overall proportion of people who had ever been tested for these cardiovascular risk factors and the proportion of individuals who met the diagnostic testing criteria in the WHO package of essential noncommunicable disease interventions for primary care (PEN) guidelines (ie, a BMI >30 kg/m 2 or a BMI >25 kg/m 2 among people aged 40 years or older). We disaggregated and compared diagnostic testing performance by sex, wealth quintile, and education using two-sided t tests and multivariable logistic regression models., Findings: Our sample included data for 994 185 people from 57 surveys. 19·1% (95% CI 18·5-19·8) of the 943 259 people in the hypertension sample met the WHO PEN criteria for diagnostic testing, of whom 78·6% (77·8-79·2) were tested. 23·8% (23·4-24·3) of the 225 707 people in the diabetes sample met the WHO PEN criteria for diagnostic testing, of whom 44·9% (43·7-46·2) were tested. Finally, 27·4% (26·3-28·6) of the 250 573 people in the hypercholesterolaemia sample met the WHO PEN criteria for diagnostic testing, of whom 39·7% (37·1-2·4) were tested. Women were more likely than men to be tested for hypertension and diabetes, and people in higher wealth quintiles compared with those in the lowest wealth quintile were more likely to be tested for all three risk factors, as were people with at least secondary education compared with those with less than primary education., Interpretation: Our study shows opportunities for health systems in LMICs to improve the targeting of diagnostic testing for cardiovascular risk factors and adherence to diagnostic testing guidelines. Risk-factor-based testing recommendations rather than sociodemographic characteristics should determine which individuals are tested., Funding: Harvard McLennan Family Fund, the Alexander von Humboldt Foundation, and the National Heart, Lung, and Blood Institute of the US National Institutes of Health., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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., (© 2022 by the American Diabetes Association.)

Background: Understanding motivational determinants of physical activity (PA) is essential to guide the implementation of PA at individual and population level. Knowledge about the cross-cultural generalizability of these determinants is lacking and they have mostly been studied as separate factors. This study compares a motivational process model across samples from diverse populations with, or at risk of diabetes., Methods: Measurement invariance of barrier identified regulation, barrier self-efficacy and social support was assessed in a rural Ugandan sample (n = 712) and disadvantaged samples with high proportions of immigrants in urban South Africa (n = 566) and Sweden (n = 147). These motivational determinants were then compared through multigroup structural equation modeling., Results: The studied motivational constructs showed scalar invariance. Latent mean levels of perceived social support and barrier self-efficacy were lower in South Africa and Sweden. Structural models (for different PA outcomes) were not consistent across settings except for the association between perceived social support and identified regulation. Identified regulation was only associated with vigorous PA in Uganda and with moderate PA in South Africa. The association between social support and PA outcomes ranged from weak to not significant and the association between self-efficacy and PA was not significant. Self-reported PA was highest in Uganda and lowest in Sweden. Self-reported vigorous PA was significantly related to lower hemoglobin A1c levels, while moderate PA was not., Conclusions: Findings suggest that: 1) it is feasible to compare a motivational process model across diverse settings; 2) there is lower perceived social support and self-efficacy in the urban, migrant samples; 3) identified regulation is a more promising determinant of PA than self-efficacy or social support in these populations; 4) associations between motivational determinants and PA depend on the perceived type and/or intensity of PA; 5) perceived relatedness functions as a basic psychological need across diverse settings; and 6) people's perception of the PA they perform depends on their perceived level of intensity of PA which would have major implications for health promotion., (© 2022. The Author(s).)

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 [HbA 1c ]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA 1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m 2 ], upper-normal [23·0-24·9 kg/m 2 ], overweight [25·0-29·9 kg/m 2 ], or obese [≥30·0 kg/m 2 ]), 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/m 2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m 2 . Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m 2 among men in east, south, and southeast Asia to 28·3 kg/m 2 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., Competing Interests: Declaration of interests MKA reports receiving a grant from Merck and Co awarded to Emory University, outside the submitted work. DJW reports serving on a data monitoring committee for Novo Nordisk SOUL and FLOW trials. JBM reports serving as an academic associate for the American clinical laboratory, Quest Diagnostics. All other authors declare no competing interests., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of interests D.J.W. reports serving on a data-monitoring committee for Novo Nordisk.

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., (© 2020 by the American Diabetes Association.)

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., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: AS has received research funding from Johnson & Johnson, Inc.

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., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: The increase in prevalence of diabetes and pre-diabetes in sub-Saharan Africa underlines the importance of understanding its magnitude and causes in different population groups. We analyzed data from the Africa/Harvard Partnership for Cohort Research and Training (PaCT) studies to determine the prevalence of diabetes and pre-diabetes and risk factors associated with diabetes., Methodology: Participants were randomly selected from peri-urban (n=297) and rural (n=200) communities in Uganda, and teachers were recruited from schools (n=229) in urban Tanzania. We used a standardized questionnaire to collect socio-demographic and self-reported disease status including diabetes status. Blood glucose was also measured after participants fasted for 8 h. We used standard protocols for anthropometric and blood pressure measurement., Results: The overall prevalence of diabetes was 10.1% and was highest in rural Ugandan residents (16.1%) compared to teachers in Tanzania (8.3%) and peri-urban Ugandan residents (7.6%). The prevalence of pre-diabetes was 13.8%. The prevalence of self-reported diabetes was low across all sites, where 68% of participants with diabetes were not captured by self-report. In multivariable logistic regression analysis, family history (OR 2.5, 95% CI: 1.1, 5.6) and hypertension (OR 2.3, 95% CI: 1.1, 5.2) were significantly associated with diabetes., Conclusions: The prevalence of diabetes and pre-diabetes in Uganda and Tanzania is high, differs markedly between population groups, and remains undiagnosed in an alarmingly high proportion of individuals. These findings highlight the need for large-scale, prospective studies to accurately quantify the burden and identify effective intervention and treatment strategies across diverse African populations.

Objective: We analysed fasting blood glucose (FBG) and other data collected as part of a population-based nationwide non-communicable disease risk factor survey, to estimate the prevalence of impaired fasting glycaemia (IFG) and diabetes mellitus and to identify associated factors in Uganda., Methods: The nationwide cross-sectional survey was conducted between April and July 2014. Participants were adults aged 18-69 years. A multistage stratified sample design was used to produce a national representative sample. Fasting capillary glucose was measured to estimate glycaemia. Data were managed with WHO e-STEPs software and Epi Info. Stata(®) survey procedures were used to account for the sampling design, and sampling weights were used to account for differential probability of selection between strata., Results: Of the 3689 participants, 1467 (39.8%) were males, and 2713 (73.5%) resided in the rural areas. The mean age was 35.1 years (standard deviation = 12.6) for males and 35.8 years (13.2) for females. The overall prevalence of IFG was 2.0% (95% confidence interval (CI) = 1.5-2.5%), whereas that of diabetes mellitus was 1.4% (95% CI 0.9-1.9%). The prevalence of IFG was 2.1% (95% CI 1.3-2.9%) among males and 1.9% (95% CI 1.3-2.6%) among females, whereas that of diabetes mellitus was 1.6% (95% CI 0.8-2.6%) and 1.1% (95% CI 0.6-1.7%), respectively. The prevalence of IFG was 2.6% (95% CI 1.4-3.8%) among urban and 1.9% (95% CI 1.3-2.4%) among rural residents, whereas that of diabetes mellitus was 2.7% (95% CI 1.4-4.1) and 1.0% (95% 0.5-1.6%), respectively. The majority of participants identified with hyperglycaemia (90.5% IFG and 48.9% diabetes) were not aware of their hyperglycaemic status. Factors associated with IFG were region of residence, body mass index and total cholesterol; factors associated with diabetes mellitus were age, sex, household floor finish and abdominal obesity., Conclusion: The prevalence of IFG and of diabetes mellitus is low in the Ugandan population, providing an opportunity for the prevention of diabetes. The majority of persons with hyperglycaemia were not aware of their hyperglycaemic status, which implies a likelihood of presenting late with complications., (© 2016 John Wiley & Sons Ltd.)