Prevalence Of Undiagnosed Diabetes Research Articles

Indirect estimation of the prevalence of type 2 diabetes mellitus in the sub-population of Tehran: using non-laboratory risk-score models in Iran

BackgroundThe prevalence of type 2 diabetes mellitus (T2DM) in the population covered by the Tehran University of Medical Sciences is unclear but crucial for healthcare programs. This study aims to validate four non-laboratory risk-score models, the American Diabetes Association (ADA) Risk Score, Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK), Finnish Diabetes Risk Score (FINDRISC), and TOPICS Diabetes Screening Score, for identifying undiagnosed diabetes and indirectly estimate the prevalence of T2DM in a subset of the Tehranian population using the selected model.MethodsThis research consisted of two main parts. In the first part, non-laboratory risk-score models to identify undiagnosed T2DM were validated using Iranian data from STEPs 2016 survey. The model performance was evaluated through the Area Under the Curve (AUC) and calibration via the observed-to-expected (O/E) ratio. Additional independent data from STEPs 2011 survey in Iran were utilized to test the model results by comparing indirect prevalence estimates with observed estimates. In the second part, the prevalence of T2DM was estimated indirectly by applying the selected model to a representative random sample from a Tehranian population telephone survey conducted in 2023.ResultsAmong the different models used, AUSDRISK showed the best performance in both discrimination (AUC (95% confidence interval (CI)): 0.80 (0.78, 0.81)) and calibration (O/E ratio = 1.01). After updating the original model, there was no change in the AUC value or calibration. Additionally, our findings indicate that the indirect estimates are nearly identical to the observed values in STEPs 2011 survey. In the second part of the study, by applying the recalibrated model to a subsample, the indirect prevalence of undiagnosed diabetes and T2DM (95% CI) were estimated at 4.18% (3.87, 4.49) and 11.1% (9.34, 13.1), respectively.ConclusionGiven the strong performance of the model, it appears that indirect method can provide a cost-effective and simple approach to assess disease prevalence and intervention effectiveness.Graphical

Investigating the Prevalence of Undiagnosed Diabetes and Its Associated Factors Among Healthcare Workers: A Cross-sectional Study in South of Iran

Abstract Context: Undiagnosed diabetes mellitus (DM) is a hidden aspect of the diabetes epidemic. Globally, over 50% of cases are estimated to be undiagnosed. Undiagnosed DM poses serious public health concerns due to increased risks of complications. Aims: This study aimed to investigate the prevalence and associated factors of undiagnosed diabetes among healthcare workers in southern Iran. Settings and Design: This cross-sectional study analyzed baseline data from the Shiraz University of Medical Sciences Employees Health Cohort Study, involving 5918 healthcare workers aged from 20 to 70 years. Materials and Methods: Participants completed questionnaires, underwent anthropometric measurements, and provided blood samples for clinical laboratory tests. Undiagnosed diabetes was defined as fasting plasma glucose ≥126 mg/dL in those without a previous diagnosis. Statistical Analysis Used: Univariate and multivariate logistic regression analyses were used to determine associated factors. Results: The prevalence of undiagnosed diabetes was 1.2%. Diagnosed diabetes had a prevalence of 3.1%. Together, undiagnosed cases accounted for 27.4% of total cases. Age (odds ratio [OR] = 1.09, 95% confidence interval [CI] [1.05–1.12]), male gender (OR = 1.67, 95% CI [1.01–2.74]), general obesity (OR = 3.64, 95% CI [2.45–5.91]), abdominal obesity (OR = 2.62, 95% CI [1.52–4.52]), hypertension (OR = 1.84, 95% CI [1.06–3.17]), and dyslipidemia were associated factors for undiagnosed diabetes. Conclusions: Although lower than national estimates, over one-quarter of diabetic cases among health workers remained undiagnosed, highlighting the need for improved screening, especially in high-risk groups. Expanding screening programs, raising health literacy, and increasing community access to preventive services are essential steps in addressing the public health issue of undiagnosed diabetes.

Risk factors for cardiometabolic health in Ghana: Cardiometabolic Risks Study Protocol-APTI Project.

Cardiometabolic diseases are rapidly becoming primary causes of death in developing countries, including Ghana. However, risk factors for these diseases, including obesity phenotype, and availability of cost-effective diagnostic criteria are poorly documented in an African-ancestry populations in their native locations. The extent to which the environment, occupation, geography, stress, and sleep habits contribute to the development of Cardiometabolic disorders should be examined. The overall goal of this study is to determine the prevalence of undiagnosed diabetes, prediabetes, and associated cardiovascular risks using a multi-sampled oral glucose tolerance test. The study will also investigate the phenotype and ocular characteristics of diabetes and prediabetes subgroups, as well as determine if lifestyle changes over a one-year period will impact the progression of diabetes and prediabetes. The study employs a community-based quasi-experimental design, making use of pre- and post-intervention data, as well as a questionnaire survey of 1200 individuals residing in the Cape Coast metropolis to ascertain the prevalence and risk factors for undiagnosed diabetes and prediabetes. Physical activity, dietary habits, stress levels, sleep patterns, body image perception, and demographic characteristics will be assessed. Glucose dysregulation will be detected using oral glucose tolerance test, fasting plasma glucose, and glycated hemoglobin. Liver and kidney function will also be assessed. Diabetes and prediabetes will be classified using the American Diabetes Association criteria. Descriptive statistics, including percentages, will be used to determine the prevalence of undiagnosed diabetes and cardiovascular risks. Inferential statistics, including ANOVA, t-tests, chi-square tests, ROC curves, logistic regression, and linear mixed model regression will be used to analyze the phenotypic variations in the population, ocular characteristics, glycemic levels, sensitivity levels of diagnostic tests, etiological cause of diabetes in the population, and effects of lifestyle modifications, respectively. Additionally, t-tests will be used to assess changes in glucose regulation biomarkers after lifestyle modifications. Ethics approval was granted by the Institutional Review Board of the University of Cape Coast, Ghana (UCCIRB/EXT/2022/27). The findings will be disseminated in community workshops, online learning platforms, academic conferences and submitted to peer-reviewed journals for publication.

Impact of Gender and Age in HbA1c Levels among Libyan Adults Without Known Diabetes in Zeletin City, Libya: A Cross-Sectional Study

The objective of our study was to examine the correlation between HbA1c levels, gender and age in Libyan adults in Zeletin city who have not been diagnosed with diabetes. In our cross-sectional study, we enrolled a total of 300 participants. Blood samples were collected from each participant and subsequently analyzed to determine their HbA1c levels. Statistical analysis included t-tests, linear regression analysis, and one-way ANOVA. Our results showed a significant positive correlation between HbA1c levels in relation to both age and gender. Furthermore, approximately 58.7% of the individuals had HbA1c levels equal to or exceeding 6.5%, which is commonly used as a threshold for diagnosing diabetes. This indicates that there is a notable occurrence of undiagnosed diabetes within the participants of the study. When examining different age groups, we observed a substantial increase in HbA1c levels with advancing age. Additionally, in the 50-59 and above 60 age groups, males exhibited significantly higher HbA1c levels compared to females (p<0.001). In conclusion, our study validated the previously observed link between elevated HbA1c levels and increasing age in individuals without diabetes. Additionally, our study highlights a high prevalence of undiagnosed diabetes in Zeletin, Libya, suggesting an impending increase in diabetes cases that will pose a significant economic burden on healthcare.

Unmasking the Risk Factors Associated with Undiagnosed Diabetes and Prediabetes in Ghana: Insights from Cardiometabolic Risk (CarMeR) Study-APTI Project.

Undiagnosed diabetes poses significant public health challenges in Ghana. Numerous factors may influence the prevalence of undiagnosed diabetes among adults, and therefore, using a model that takes into account the intricate network of these relationships should be considered. Our goal was to evaluate fasting plasma levels, a critical indicator of diabetes, and the associated direct and indirect associated or protective factors. This research employed a cross-sectional survey to sample 1200 adults aged 25-70 years who perceived themselves as healthy and had not been previously diagnosed with diabetes from 13 indigenous communities within the Cape Coast Metropolis, Ghana. Diabetes was diagnosed based on the American Diabetes Association (ADA) criteria for fasting plasma glucose, and lipid profiles were determined using Mindray equipment (August 2022, China). A stepwise WHO questionnaire was used to collect data on sociodemographic and lifestyle variables. We analyzed the associations among the exogenous, mediating, and endogenous variables using a generalized structural equation model (GSEM). Overall, the prevalence of prediabetes and diabetes in the Cape Coast Metropolis was found to be 14.2% and 3.84%, respectively. In the sex domain, females had a higher prevalence of prediabetes (15.33%) and diabetes (5.15%) than males (12.62% and 1.24%, respectively). Rural areas had the highest prevalence, followed by peri-urban areas, whereas urban areas had the lowest prevalence. In the GSEM results, we found that body mass index (BMI), triglycerides (TG), systolic blood pressure (SBP), gamma-glutamyl transferase (GGT), and female sex were direct predictive factors for prediabetes and diabetes, based on fasting plasma glucose (FPG) levels. Indirect factors influencing diabetes and prediabetes through waist circumference (WC) included childhood overweight status, family history, age 35-55 and 56-70, and moderate and high socioeconomic status. High density lipoprotein (HDL) cholesterol, childhood overweight, low physical activity, female sex, moderate and high socioeconomic status, and market trading were also associated with high BMI, indirectly influencing prediabetes and diabetes. Total cholesterol, increased TG levels, WC, age, low physical activity, and rural dwellers were identified as indirectly associated factors with prediabetes and diabetes through SBP. Religion, male sex, and alcohol consumption were identified as predictive factors for GGT, indirectly influencing prediabetes and diabetes. Diabetes in indigenous communities is directly influenced by blood lipid, BMI, SBP, and alcohol levels. Childhood obesity, physical inactivity, sex, socioeconomic status, and family history could indirectly influence diabetes development. These findings offer valuable insights for policymakers and health-sector stakeholders, enabling them to understand the factors associated with diabetes development and implement necessary public health interventions and personalized care strategies for prevention and management in Ghana.

Place of residence and blood sugar testing practices among men: insights from the 2021 Madagascar demographic and health survey

BackgroundIn 2021, Madagascar had approximately 13,919 people living with diabetes, with 66.1% of cases being undiagnosed. The implication is that this population are at high risk of developing diabetes complications which will affect their quality of life. However, promoting the uptake of screening practices such as the blood glucose test among the asymptomatic population would offer a chance to reduce the prevalence of undiagnosed diabetes in the country. This study examined the association between place of residence and blood sugar testing practices among men in Madagascar.MethodsSecondary data from the men recode file of the 2021 Madagascar Demographic and Health Survey (MDHS) was used. A sample of 9,035 were used for the analysis. Descriptive and multivariate analyses were performed in STATA version 14. The results are presented in adjusted odds ratio (AOR) with the corresponding 95% confidence interval.ResultsOnly 5.83% reported to have ever had their blood glucose/sugar tested by a health professional. Residing in rural areas was associated in lower likelihood of undergoing a test to check one’s blood sugar level [AOR = 0.23; 95%CI = 0.19–0.28] compared to those in urban areas. This association remained consistent even after adjusting for the effects of covariates [AOR = 0.67; 95%CI = 0.52–0.86].ConclusionWe conclude that place of residence plays a significant role in influencing men’s decision to test their blood glucose level. It is, therefore, imperative for the Madagascar Public Health Department to liaise with the government to bridge the rural-urban disparities in terms of accessibility to blood glucose testing services. Practically, this can be achieved by instituting community-based health services centers in the rural areas of Madagascar to mitigate the rural-urban disparities. Also, health education campaigns to raise men’s awareness about the need to test their blood glucose level must necessarily target older men, those without formal education, those without health insurance, and men who have been diagnosed with hypertension.

Analysis of risk factors and clinical implications for diabetes in first-degree relatives in the northeastern region of China.

The prevalence of diabetes has risen fast with a considerable weighted prevalence of undiagnosed diabetes or uncontrolled diabetes. Then it becomes more necessary to timely screen out and monitor high-risk populations who are likely to be ignored during the COVID-19 pandemic. To classify and find the common risks of undiagnosed diabetes and uncontrolled diabetes, it's beneficial to put specific risk control measures into effect for comprehensive primary care. Especially, there is a need for accurate yet accessible prediction models. Based on a cross-sectional study and secondary analysis on the health examination held in Changchun City (2016), we aimed to evaluate the factors associated with hyperglycemia, analyze the management status of T2DM, and determine the best cutoff value of incidence of diabetes in the first-degree relatives to suggest the necessity of early diagnosis of diabetes after first screening. A total of 5658 volunteers were analyzed. Prevalence of T2DM and impaired fasting glucose were 8.4% (n=477) and 11.5% (n=648), respectively. There were 925 participants (16.3%) with a family history of T2DM in their first-degree relatives. Multivariable analysis demonstrated that family history was associated with hyperglycemia. Among the 477 patients with T2DM, 40.9% had not been previously diagnosed. The predictive equation was calculated with the following logistic regression parameters with 0.71 (95% CI: 0.67-0.76) of the area under the ROC curve, 64.0% of sensitivity and 29% of specificity (P < 0.001): P = \frac{1}{1 + e^{-z}}, where z = -3.08 + [0.89 (Family history-group) + 0.69 (age-group)+ 0.25 (BMI-group)]. Positive family history was associated with the diagnosis of T2DM, but not glucose level in the diagnosed patients. The best cutoff value of incidence of diabetes in the first-degree relatives was 9.55% (P < 0.001). Family history of diabetes was independently associated with glucose dysfunction. Classification by the first-degree relatives with diabetes is prominent for targeting high-risk population. Meanwhile, positive family history of diabetes was associated with diabetes being diagnosed rather than the glycemic control in patients who had been diagnosed. It's necessary to emphasize the linkage between early diagnosis and positive family history for high proportions of undiagnosed T2DM.

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 in Canada poses a significant health challenge. Despite the convenience of screening for diabetes with glycated hemoglobin (A1C) 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 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 PEH 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.