Prevalence Of Undiagnosed Diabetes Research Articles

Optimal Glycated Hemoglobin Cutoff for Diagnosis of Diabetes and Prediabetes in Chinese Breast Cancer Women.

Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies. This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening. Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P<0.001, 95% CI, 0.867-0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P<0.001, 95% CI, 0.632-0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%). The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.

Estimating the Rates of Undiagnosed Prediabetes and Diabetes Among People Experiencing Homelessness

ObjectivesThe rising prevalence of type 2 diabetes (T2D) in Canada poses a significant health challenge. Despite the convenience of screening for diabetes with glycated hemoglobin concentration, people experiencing homelessness (PEH) often face barriers to accessing diabetes screening, potentially leading to underdiagnosis. In this study we aim to assess the prevalence of undiagnosed diabetes among PEH in Calgary, Alberta, and contribute insights for planning health-care services and public health initiatives. MethodsFour screening clinics were held, and participants were recruited through posters and word of mouth. Participants underwent point-of-care glycated hemoglobin (A1C) testing using the Siemens DCA Vantage point-of-care analyzer. Descriptive statistics were used to identify the proportions of prediabetes and diabetes, whereas CanRisk survey scores were used to identify the pre-test probability of diabetes. ResultsThe mean age of participants (n=102) was 47.6 years, and the self-reported causes of homelessness among the participants were diverse, including: housing and financial issues (n=53), interpersonal and family issues (n=35), and health or corrections-related factors (n=27). The average A1C was 5.60% (standard deviation 0.57%), with 5 values in the diabetes range and 12 in the prediabetes range, for a total of 17 participants found to have previously undiagnosed dysglycemia. ConclusionsThe high rate of undiagnosed prediabetes and diabetes among people experiencing homelessness reflects at least what is already seen in the general population in Canada. More resources are required to reduce the barriers to screening for diabetes among this population.

Prevalence of Diabetes by BMI: China Nutrition and Health Surveillance (2015–2017) and U.S. National Health and Nutrition Examination Survey (2015–2018)

IntroductionThe risk of diabetes begins at a lower body mass index (BMI) among Asian adults. This study compares the prevalence of diabetes in the United States and China by BMI. MethodsData from the 2015-2017 China Nutrition and Health Surveillance (n=176,223) and the 2015-2018 US National Health and Nutrition Examination Survey (n=4,464) were used. Diagnosed diabetes was self-reported. Undiagnosed diabetes was no report of diagnosed diabetes and fasting plasma glucose >=126 mg/dL or hemoglobin A1c>=6.5%. Predicted age-adjusted prevalence estimates by BMI were produced using sex- and country-specific logistic regression models. ResultsIn China, the age-adjusted prevalence of total diabetes was 7.8% (95% CI 7.4-8.3%), lower than the 14.6% (95% CI 13.1-16.3%) in the US. The prevalence of diagnosed diabetes was also lower in China than the US. There were no statistically significant differences in the prevalence of undiagnosed diabetes between China and the US. The distribution of BMI in China is lower than in the US and the predicted prevalence of total diabetes is similar in China and the US when comparing adults with the same BMI. The predicted prevalence of undiagnosed diabetes was higher in China than in the US for both men and women and this disparity increased with BMI. When comparing adults at the same BMI there was little difference in prevalence of total diabetes, but diagnosed diabetes was lower in China than the US and undiagnosed was higher. ConclusionWhile differences in BMI appear to explain nearly all of the differences in total diabetes prevalence in the two countries, not all factors that are associated with diabetes risk have been investigated.

Preoperative Glycosylated Haemoglobin Screening to Identify Older Adult Patients with Undiagnosed Diabetes Mellitus-A Retrospective Cohort Study.

More than 25% of older adults in Europe have diabetes mellitus. It is estimated that 45% of patients with diabetes are currently undiagnosed, which is a known risk factor for perioperative morbidity. We investigated whether routine HbA1c screening in older adult patients undergoing surgery would identify patients with undiagnosed diabetes. We included patients aged ≥65 years without a diagnosis of diabetes who visited the preoperative assessment clinic at the Amsterdam University Medical Center and underwent HbA1c screening within three months before surgery. Patients undergoing cardiac surgery were excluded. We assessed the prevalence of undiagnosed diabetes (defined as HbA1c ≥ 48 mmol·mol-1) and prediabetes (HbA1c 39-47 mmol·mol-1). Using a multivariate regression model, we analysed the ability of HbA1c to predict days alive and at home within 30 days after surgery. From January to December 2019, we screened 2015 patients ≥65 years at our clinic. Of these, 697 patients without a diagnosis of diabetes underwent HbA1c screening. The prevalence of undiagnosed diabetes and prediabetes was 3.7% (95%CI 2.5-5.4%) and 42.9% (95%CI 39.2-46.7%), respectively. Preoperative HbA1c was not associated with days alive and at home within 30 days after surgery. In conclusion, we identified a small number of patients with undiagnosed diabetes and a high prevalence of prediabetes based on preoperative HbA1c screening in a cohort of older adults undergoing non-cardiac surgery. The relevance of prediabetes in the perioperative setting is unclear. Screening for HbA1c in older adult patients undergoing non-cardiac surgery does not appear to help predict postoperative outcome.

Evaluation of Diabetes Risk Score Tool for Detecting Undiagnosed Type 2 Diabetes Mellitus in Attendees of Referral Clinics at Primary Health Care Centers, Sudan

Introduction: The prevalence of diabetes in Sudan is increasing; however, suitable risk assessment and screening tools to identify at-risk individuals are lacking. Objective: To evaluate the Diabetes Risk Score (DRS) tool for detecting Type 2 Diabetes Mellitus among undiagnosed individuals. Methods: In this cross-sectional study, 214 individuals were recruited from Primary Health Care Referral Centers in Khartoum State. Attendees were interviewed to fill out the Diabetes Risk Score (DRS) questionnaire. Random blood glucose and glycosylated hemoglobin (HbA1c) were tested. Descriptive statistics and sensitivity analysis were performed to test the applicability of the DRS in Sudan. Results: The prevalence of undiagnosed diabetes was found to be 14%. Regarding blood tests, Random blood glucose (RBG) was normal in 93% of the participants (cutoff ≤140 mg/dl). The HbA1c result was normal in 86% of the participants (cutoff &lt; 6.4%). The DRS was high in 40.2% (cutoff ≥33), while 59.8% were considered moderate to low risk. The DRS had a sensitivity of 83.33% and a specificity of 66.85%. The positive and negative predictive values were 29.07% and 96.09%, respectively. The Area Under the Curve (AUC) for detecting undiagnosed diabetes was 0.751 (95% CI: 0.662-0.840). Conclusion: The DRS tool was found to be applicable with reference to the HbA1c test for predicting undiagnosed diabetic patients.

A Comparative Analysis of Machine Learning Models for the Detection of Undiagnosed Diabetes Patients

Introduction: Early detection of type 2 diabetes is essential for preventing long-term complications. However, screening the entire population for diabetes is not cost-effective, so identifying individuals at high risk for this disease is crucial. The aim of this study was to compare the performance of five diverse machine learning (ML) models in classifying undiagnosed diabetes using large heterogeneous datasets. Methods: We used machine learning data from several years of the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 to identify people with undiagnosed diabetes. The dataset included 45,431 participants, and biochemical confirmation of glucose control (HbA1c) were used to identify undiagnosed diabetes. The predictors were based on simple and clinically obtainable variables, which could be feasible for prescreening for diabetes. We included five ML models for comparison: random forest, AdaBoost, RUSBoost, LogitBoost, and a neural network. Results: The prevalence of undiagnosed diabetes was 4%. For the classification of undiagnosed diabetes, the area under the ROC curve (AUC) values were between 0.776 and 0.806. The positive predictive values (PPVs) were between 0.083 and 0.091, the negative predictive values (NPVs) were between 0.984 and 0.99, and the sensitivities were between 0.742 and 0.871. Conclusion: We have demonstrated that several types of classification models can accurately classify undiagnosed diabetes from simple and clinically obtainable variables. These results suggest that the use of machine learning for prescreening for undiagnosed diabetes could be a useful tool in clinical practice.

Evaluation of Diabetes Risk Score Tool for Detecting Undiagnosed Type 2 Diabetes Mellitus in Attendees of Referral Clinics at Primary Health Care Centers, Sudan

Introduction: The prevalence of diabetes in Sudan is increasing; however, suitable risk assessment and screening tools to identify at-risk individuals are lacking. Objective: To evaluate the Diabetes Risk Score (DRS) tool for detecting Type 2 Diabetes Mellitus among undiagnosed individuals. Methods: In this cross-sectional study, 214 individuals were recruited from Primary Health Care Referral Centers in Khartoum State. Attendees were interviewed to fill out the Diabetes Risk Score (DRS) questionnaire. Random blood glucose and glycosylated hemoglobin (HbA1c) were tested. Descriptive statistics and sensitivity analysis were performed to test the applicability of the DRS in Sudan. Results: The prevalence of undiagnosed diabetes was found to be 14%. Regarding blood tests, Random blood glucose (RBG) was normal in 93% of the participants (cutoff ≤140 mg/dl). The HbA1c result was normal in 86% of the participants (cutoff &lt; 6.4%). The DRS was high in 40.2% (cutoff ≥33), while 59.8% were considered moderate to low risk. The DRS had a sensitivity of 83.33% and a specificity of 66.85%. The positive and negative predictive values were 29.07% and 96.09%, respectively. The Area Under the Curve (AUC) for detecting undiagnosed diabetes was 0.95 with a confidence level (CI 0.92 to 0.98). Conclusion: The DRS tool was found to be applicable with reference to the HbA1c test for predicting undiagnosed diabetic patients.

Factors related to undiagnosed diabetes in Korean adults: a secondary data analysis

Purpose: This study compared health behaviors and health-related clinical characteristics between individuals with normal glucose levels without diabetes and those with undiagnosed diabetes. Factors that were associated with undiagnosed diabetes were identified by sex. Methods: This was an observational study with a cross-sectional design based on data from the eighth Korea National Health and Nutrition Examination Survey, which used a stratified, multi-stage, cluster-sampling design to obtain a nationally representative sample. Multiple logistic regression analysis was employed to compute the odds ratios of health behaviors and clinical characteristics to identify risk factors for undiagnosed diabetes. Results: The overall prevalence of undiagnosed diabetes was 5.2% (weighted %, n = 700, p &lt; .001). Among individuals with undiagnosed diabetes, 58.3% were men. Univariate logistic regression for undiagnosed diabetes identified sex, age, house income, educational level, and triglycerides as influencing factors. In multiple logistic regression by sex, the factors associated with undiagnosed diabetes in men were age, perceived health status, a diagnosis of angina, and triglycerides. Conclusion: Strategies should be targeted to improve health behaviors and clinical characteristics for those in specific age groups, men in bad perceived health status, women with high systolic blood pressure, and high triglycerides. Moreover, healthcare providers should understand the barriers to health behaviors and health-related quality of life to effectively deliver healthcare services.

Changes in the prevalence of diabetes and control of risk factors for diabetes among Chinese adults from 2007 to 2017: An analysis of repeated national cross-sectional surveys.

To examine changes in the prevalence of diabetes and the control of risk factors for diabetes over 10 years among adults in China. Two population-based cross-sectional surveys were used to obtain a nationally representative sample of adults aged 20 years and older in mainland China in 2007 (n = 46 239) and 2017 (n = 73 340). Changes in the prevalence of diabetes, impaired fasting glucose, impaired glucose tolerance, and prediabetes, as diagnosed by the World Health Organization criteria, were assessed over time. The weighted prevalence of diagnosed diabetes (3.8% vs 6.3%, p = .0001) and total diabetes (9.7% vs 11.7%, p = .005) increased among the overall population between 2007 and 2017. The weighted prevalence of undiagnosed diabetes (5.9% vs 5.4%, p = .7), impaired fasting glucose (2.7% vs 2.6%, p = .68), impaired glucose tolerance (12.7% vs 12.5%, p = .95), prediabetes (15.4% vs 15.1%, p = .79), the treatment of diabetes (34.1% vs 32.5%, p = .44), and the control of diabetes (31.1% vs 32.8%, p = .73) did not significantly change over this period. The awareness of diabetes (39.4% vs 53.6%, p = .0004) increased over 10 years among the overall population. The proportion of achieved high-density lipoprotein cholesterol targets increased (p = .005), but the proportion of achieved body mass index (p = .01) and waist circumference (p = .0002) targets decreased significantly. Between 2007 and 2017, the prevalence of total diabetes (diagnosed by the World Health Organization criteria), especially diagnosed diabetes, increased among adults in China. Although awareness of diabetes improved, effective interventions and clinical strategies are urgently required.

The magnitude of undiagnosed diabetes mellitus, prediabetes, and associated factors among adults living in Debre Tabor town, northcentral Ethiopia: A community-based cross-sectional study

BackgroundDiabetes mellitus (DM) is a worldwide public health problem. The burden of diabetes has been continuously increasing from day to day, especially in developing countries like Ethiopia. Globally, half of all cases of diabetes mellitus are undiagnosed. Diabetes mellitus can be easily handled if it is detected early. There is limited evidence on the magnitude of undiagnosed diabetics and prediabetes at the community level in Ethiopia, particularly in the study area. ObjectiveTo assess the magnitude of undiagnosed diabetes mellitus, prediabetes, and associated factors among adults living in Debre Tabor town. MethodsA community-based cross-sectional study was conducted in Debre Tabor town from October to December 2021. A total of 407 participants were selected using a multistage sampling technique. A pretested structural questionnaire was used to collect demographic, behavioral, and clinical data. Anthropometric measurements were taken with standardized and calibrated equipment. A fasting venous blood sample was collected for blood glucose level determination. Logistic regression was used to identify risk factors. A P-value ≤0.05 was considered statistically significant. ResultThe magnitude of undiagnosed diabetes mellitus and prediabetes was found to be 4.5% (95% CI: 2.9–7.4) and 14.5% (95% CI: 11.1–18.1), respectively. Older age (AOR: 6.50, 95% CI: 1.82–23.21), abnormal body mass index (AOR: 6.84, 95% CI: 1.91–24.54), systolic hypertension (AOR: 8.74, 95% CI: 2.53–30.19), and family history of diabetes mellitus (FHDM) (AOR: 12.45, 95% CI: 3.63–42.65) were significantly associated with undiagnosed diabetes mellitus. Using saturated oil (AOR: 1.97, 95% CI: 1.09–3.55), having a high waist circumference (AOR: 2.16, 95% CI: 1.20–3.87), and being hypertensive (AOR: 2.26, 95% CI: 1.04–4.96) were all significantly associated with Prediabetes. ConclusionAdults in Debre Tabor town have a high prevalence of undiagnosed diabetes and prediabetes. A variety of modifiable risk factors were also identified. As a result, focusing the prevention strategy on such modifiable risk factors may help to minimize the prevalence of undiagnosed diabetes mellitus and prediabetes as well as future disease complications.

Prevalence and predictive modeling of undiagnosed diabetes and impaired fasting glucose in Taiwan: a Taiwan Biobank study

IntroductionWe investigated the prevalence of undiagnosed diabetes and impaired fasting glucose (IFG) in individuals without known diabetes in Taiwan and developed a risk prediction model for identifying undiagnosed diabetes and...

Prevalence of undiagnosed diabetes and prediabetes related to periodontitis and its risk factors in elderly individuals

ObjectiveThe prevalence of undiagnosed diabetes was estimated to increase with age and can reach 3.5%. The purpose of the study was to evaluate the prevalence of undiagnosed diabetes and prediabetes in the elderly patients who attended a dental clinic and to find common risk factors. MethodsMale patients, older than 50 years, attended their first dental visit to the School of Dentistry for a period of two years, and it was proposed to evaluate undiagnosed type 2 diabetes mellitus. Periodontal, biochemical, microbiological examinations, nutritional profile, and physical activity were performed. ResultsA total of 106 patients were examined, 6 (5.6%) had diabetes, and 37 (34.9%) had prediabetes without prior diagnosis. The severity of periodontitis was greater in patients with diabetes. Most of the patients were overweight and had increased systolic blood pressure. Patients with prediabetes and periodontitis had a low adherence to the Mediterranean diet. Tannerella forsythia was present in more patients with periodontitis, and the prevalence of Aggregatibacter actinomycetemcomitans is practically absent in groups with periodontitis, except for the group with diabetes. ConclusionsIn the population studied, the prevalence of patients without a diagnosis of diabetes and prediabetes was very high and underestimated. The increased severity of periodontitis in patients with diabetes and in conjunction with the high level of cortisol seen in patients with periodontitis, especially those with diabetes, emphasize the dysregulation of the immunoinflammatory system. Clinical significanceIt is essential to add all this data to our dental practice to cover patient health with a broader landscape.

Socio-demographic Characteristics and Nutritional Status of Adults at Risk of Type 2 Diabetes Mellitus in Kuala Nerus, Terengganu

Introduction: In Malaysia, the undiagnosed diabetes prevalence has increased. Socio-demographic characteristics and nutritional status play a crucial role in prediabetes development. Hence, this cross-sectional study aimed to identify the socio-demographic characteristics and nutritional status of adults at risk of T2DM in Kuala Nerus, Terengganu. Methods: A total of 30 participants at risk of T2DM aged 18 to 59 years old were recruited from Kuala Nerus using a convenience sampling method. Information on socio-demographic, anthropometric, fasting plasma glucose (FPG) level, clinical profile, Finnish Type 2 Diabetes Risk Assessment Tool (FINDRISC) score, dietary intake, and physical activity level were obtained. Results: The participants (mean age: 36.1 ± 8.7 years) were mostly female (76.7%), Malay (96.7%), married (43.3%), had a tertiary degree (60.0%), and were working (83.3%) with a monthly salary of less than RM 1000. Half of the participants were from the obese class I category. Their FPG level was 5.6 ± 0.5 mmol/L and half of them were classified as having optimal blood pressure. Also, they had a mean FINDRISC score of 6.3 ± 1.8. The participants consumed 2073 ± 247 kcal/day, which was comprised of 50.8% carbohydrate, 16.1% protein, and 33.1% fat. Most of them (63.3%) were minimally active. Conclusion: The participants had moderate T2DM risk with normal FPG level, blood pressure, and heart rate. They had excessive energy and fat intake with insufficient dietary fibre intake. It is vital to examine the socio-demographic characteristics and nutritional status, which can provide important information for planning future cost-effective T2DM preventive strategies.

Prevalence of Undiagnosed Diabetes Identified by a Novel Electronic Medical Record Diabetes Screening Program in an Urban Emergency Department in the US

This cross-sectional study describes a screening program that was developed to screen for type 2 diabetes in an urban emergency department setting in the US.

Trends in epidemiology of hyperglycemia in pregnancy in Taiwan, 2008-2017.

Hyperglycemia in pregnancy (HIP) increases the risk of adverse pregnancy outcomes. The increasing prevalence of overweight or obesity and the increasing proportion of pregnant women with advanced maternal age (AMA) in the recent decade may affect its prevalence. We analyzed the secular trend of HIP prevalence in 2008-2017 in Taiwan and investigated the impact of AMA in this study. This cross-sectional study used data from Health and Welfare Data Science Center. Pregnant women who registered their data in the Birth Certificate Application in 2008-2017 were recruited. Diagnosis of HIP was defined by ICD-9-CM and ICD-10-CM codes. In 2008-2017, 151,306-211,768 pregnant women were recruited in different years. The proportion of women with AMA increased from 15.8% to 32.1%. Meanwhile, the prevalence increased from 0.5% to 0.9% for preexisting diabetes, 0.2% to 0.4% for undiagnosed diabetes, and 11.4% to 14.5% for GDM. Maternal age was significantly associated with the prevalence of HIP. For women aged <30 years, 30-34 years and ≥35 years, the prevalence of preexisting diabetes were 0.51%, 0.75% and 1.24%, respectively (p<0.05); the prevalence of undiagnosed diabetes were 0.18%, 0.24% and 0.37%, respectively (p<0.05); and the prevalence of GDM were 10.57%, 14.77% and 18.13%, respectively (p<0.05). In all age groups, the prevalence of HIP increased over time in 2008-2017. The prevalence of HIP increased in Taiwan in 2008-2017, which may result from the increasing proportion of pregnant women with AMA and the change in the diagnostic criteria for GDM.

The prevalence of diabetes and prediabetes: a population-based study.

Diabetes remains one of the top public health care priorities. Over 6% of the world's population is affected by type 2 diabetes; however, a similar number of individuals may be unaware of this diagnosis. Our population‑basedstudy aimed to investigate the true prevalence of diabetes and prediabetes in the general population of a medium‑sized city in Poland. The analysis included 1051 participants of the Bialystok PLUS population‑based cohort study. In those who did not report a history of diabetes, the oral glucose tolerance test (OGTT) was performed. Medical history data were gathered using standardized questionnaires, and anthropometric as well as body composition measurements were performed. According to the medical history data, a total of 75 participants had diabetes (7.14%). Prediabetes (impaired fasting glycemia [IFG] or impaired glucose tolerance [IGT]) was identified in 410 individuals, including 241 participants with IFG (22.9%) and 169 patients with IGT (16.1%). Moreover, there were 71 individuals (6.75%) who were newly diagnosed with diabetes based on OGTT results. Overall, 146 patients with diabetes (13.8%) were identified. The ratio of lean mass to fat mass differed significantly between the patients with newly diagnosed diabetes and those without impaired glucose metabolism. Our cohort study demonstrated a high prevalence of undiagnosed diabetes in the Białystok population. In addition, we showed that a large group of patients still remains undiagnosed for other hyperglycemic disorders. Abdominal obesity as well as imbalance between the fat and lean mass may predispose to diabetes.

State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states

BackgroundAlthough treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically.MethodsWe analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts.ResultsThe estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states.ConclusionsDespite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care.Trial Registration: Not applicable.

A Cross-Sectional Study on the Health Profile and Nutritional Status of Adults at Risk of Type 2 Diabetes Mellitus in Kuala Nerus, Terengganu

Surprisingly, 541 million people have impaired glucose tolerance (IGT) worldwide[1]. Prediabetes has been associated with an elevated risk of composite cardiovascular disease, coronary heart disease, stroke and all-cause mortality2 as well as an increased risk of type 2 diabetes mellitus (T2DM) than normal glycaemia[1]. In Malaysia, the undiagnosed diabetes prevalence has increased3. Health profile and nutritional status play a crucial role in prediabetes development. However, there is a scarcity of related health profile characteristics and nutritional status data in Kuala Nerus, Terengganu.&#x0D; &#x0D; This cross-sectional study aimed to identify the health profile and nutritional status of adults at risk of T2DM in Kuala Nerus, Terengganu. A total of 30 respondents at moderate and high risk of T2DM (Finnish Type 2 Diabetes Risk Assessment Tool (FINDRISC) score &gt; 4) aged 18 to 59 years old were recruited from Kuala Nerus using a convenience sampling method. Information on socio-demographic, anthropometric, fasting plasma glucose (FPG) level, clinical profile, FINDRISC score, dietary intake, and physical activity level were obtained. The data were analyzed using IBM SPSS system version 21.0 and Nutritionist ProTM software (Version 7.0.0, Axxya Systems). A descriptive statistic was used to present all outcomes. The continuous data were described as mean ± standard deviation (SD) whereas for categorical variables, the data were reported as the number of frequency and percentage.&#x0D; &#x0D; The respondents (mean age: 36.1 ± 8.7 years) were predominantly female (76.7%), Malay (96.7%), married (43.3%), with tertiary education (60.0%), and employed (83.3%) with a monthly income ranging below RM 1000. Half of the respondents were from the obese class I category. However, they had a normal FPG (5.6 ± 0.5 mmol/L) and were normotensive with a normal heart rate. Also, they had an average FINDRISC score of 6.3 ± 1.8. The respondents had excessive energy, fat, vitamin C, and selenium intake with insufficient dietary fibre, vitamin A, E, and K, calcium, and magnesium intake. Most of them (63.3%) were minimally active.&#x0D; The mean energy intake of this study was in accord with Malaysian Adult Nutrition Survey (MANS) 2003 (2097 kcal) and MANS 2014 (2123 kcal) after excluding under-reporters [3]. The National Health Morbidity Survey (NHMS) 2019 stated that 25.1% of Malaysian adults were physically inactive which was slightly higher than the current study finding. On the contrary, a higher percentage (80.0%) of the study respondents were physically active than 74.9% as reported by NHMS (2019) [4].&#x0D; &#x0D; It is vital to determine the health profile and nutritional status, which can provide important information for planning future cost-effective T2DM preventive strategies. This is because a strategic method of primary prevention for T2DM is by managing risk factors through lifestyle modification.

Prognostic value of resting heart rate in predicting undiagnosed diabetes in adults: Korean National Health and Nutrition Examination Survey 2008–2018

Background and aimAlthough resting heart rate (RHR) is associated with prevalence and incidence of diabetes, whether it is associated with undiagnosed diabetes is still unclear. We aimed to investigate whether the RHR is associated with the prevalence of undiagnosed diabetes in a large Korean national dataset. Methods and resultsThe Korean National Health and Nutrition Examination Survey data from 2008 to 2018 were used. After screening, 51,637 participants were included in this study. The odds ratios and 95% confidence intervals (CIs) for undiagnosed diabetes were calculated using multivariable-adjusted logistic regression analyses.Analyses showed that participants with a RHR of ≥90 bpm showed a 4.00- (95% CI: 2.77–5.77) and 3.21-times (95% CI: 2.01–5.14) higher prevalence of undiagnosed diabetes for men and women, respectively, than those with a RHR of <60 bpm. The linear dose-response analyses showed that each 10-bpm increment in RHR was associated with a 1.39- (95% CI: 1.32–1.48) and 1.28-times (95% CI: 1.19–1.37) higher prevalence of undiagnosed diabetes for men and women, respectively. In the stratified analyses, the positive association between RHR and the prevalence of undiagnosed diabetes was tended to be stronger among those who were younger (age: <40 years) and lean (BMI: <23 kg/m2). ConclusionsElevated RHR was significantly associated with a higher prevalence of undiagnosed diabetes in Korean men and women, independent of demographic, lifestyle, and medical factors. Accordingly, the value of RHR as a clinical indicator and health marker, especially in reducing the prevalence of undiagnosed diabetes, is suggestible.

Risk of Developing Diabetes in Patients Undergoing Coronary Artery Angiography Based on American Diabetes Association Risk Score: A Cross-Sectional Study

Aims The high prevalence of undiagnosed diabetes and the high risk for diabetes in the general population is alarming. In addition, the frequency of coronary artery diseases (CAD) in patients with undiagnosed diabetes is higher than in non-diabetic patients. This study aimed to investigate the frequency of people at risk of diabetes in patients undergoing coronary artery angiography (CAG) in a university referral hospital in Guilan Province, Iran. Methods &amp; Materials In this cross-sectional study, data from 300 non-diabetic patients who were candidates for CAG were collected using a simple sampling method. The risk of developing diabetes was calculated according to American Diabetes Association (ADA) risk score. ADA scores higher than five were considered high risk, and ADA scores equal to 4 and lower than 4 were as moderate and low risk, respectively. Findings The mean age of the study population was 59.44±15.7 years. Most subjects were male (59.3%). Only 24.3% of patients were in the low-risk group while 32% were in moderate risk and 43.7% were in the high-risk group. The frequency of patients with at least two coronary artery involvement was significantly higher in the high-risk group (43.1%) than in the moderate group (34.4%), and the low-risk (22.5%) group. Conclusion A high proportion of the patients undergoing CAG were at high risk of developing diabetes. Hence, it seems essential to address cardiometabolic risk factors in coronary artery diseases (CAD) after discharge from the hospital.