Undiagnosed Type 2 Diabetes Mellitus Research Articles

Analysis of Associated Factors Contributing to Type 2 Diabetes Mellitus in the Coastal Community of Bahari Village, Southeast Sulawesi, Indonesia: A Cross-Sectional Study

Background Type 2 diabetes mellitus (T2DM) has become a major lifestyle disease that threatens communities in the world. The lifestyles of undiagnosed T2DM are a major issue in Indonesia. Objective This study aims to analyze the contribution of associated factors to T2DM in Bahari Village. Methods The study was conducted by cross-sectional study. Respondents included 113 men and 157 women were established through simple randomized sampling from March to May 2023. Data analysis using chi-square and logistic regression at p<0.05 using SPSS 25. Results The prevalence of T2DM for women (74.2%), 45-65 years (90.9%), no education (58.7%), overweight (38.2%), heavy drinking sweet tea/coffee (77.5%), never physical activity (87.1%), diabetic father and mother (40.3%), and father’s OR 1.42 (CI 95%:0.73-2.75), significantly associated with T2DM. Gender, age, education, BMI, and occupation simultaneously influence (72.7%), and age partially affects T2DM. Discussion Decreased insulin sensitivity and increased risk of developing diabetes can be influenced by various factors, such as genetics, lifestyle, physical activity, and the environment, either partially or simultaneously. Conclusion The respondents' advanced age, obesity, lack of education, preference for sweet foods, and inactivity all contributed to their type 2 diabetes. These coastal communities need to make lifestyle changes to reduce the burden of diabetes. Classification Epidemiology; Environmental Health; Science of Nutrition MeSH.

Association of Undiagnosed Pre-Diabetes and Type-2 Diabetes Mellitus with Interleukin-2 mRNA Expression Among Adults in Bayelsa State, Nigeria

Many cases of hyperglycemia are undiagnosed in Nigeria due to poverty and inadequate access to health care. Although hyperglycemia and type 2 diabetes mellitus (T2DM) are inflammatory conditions, however, the role of inflammatory mediators such as interleukin-2 in hyperglycemia and T2DM is not fully understood. The aim of the present study was to evaluate the prevalence and association of undiagnosed pre-diabetes and T2DM with IL-2 mRNA level among adults in Bayelsa State, Nigeria. A cross sectional design was employed to randomly select 130 adults and they were grouped into three: normal control, prediabetes, and T2DM. Fasting blood glucose concentration was measured using Accu-answer glucometer, while mRNA level of IL-2 was quantified using real time PCR method. The prevalence of undiagnosed pre-diabetes was 43.07% (males, 19.23%; females, 23.85%) while undiagnosed T2DM was 16.15% (males, 6.92%; females 9.23%). The expression of IL-2 mRNA was significantly upregulated in both pre-diabetes and T2DM subjects compared with normal control (p < 0.05), but was significantly higher among T2DM subjects. Age ≥ 50 years, physical inactivity and marriage was significantly associated with hyperglycemia and T2DM (p < 0.05). The present study found a high prevalence of undiagnosed pre-diabetes and T2DM among adults in Bayelsa State, Nigeria. Association of prediabetes and T2DM with IL-2 mRNA expression was found. IL-2 mRNA level might be a useful biomarker for monitoring diabetes mellitus progression. Directing diabetes survey and interventions to rural communities is highly recommended. Keywords: [Undiagnosed Diabetes, pre-diabetes, IL-2, rural communities, Bayelsa State, Nigeria]

Using HbA1c measurements and the Finnish Diabetes Risk Score to identify undiagnosed individuals and those at risk of diabetes in primary care

BackgroundPrevalence of prediabetes and type 2 diabetes mellitus (T2DM) is increasing worldwide. The objective of this study was to determine the proportion of people in Northern Iceland with prediabetes, at risk of developing T2DM or with manifest undiagnosed T2DM, as this information is lacking in Iceland.MethodsA cross-sectional study. Clients of the three largest primary health care centres in the Health Care Institution of North Iceland (HSN) were invited to participate if fulfilling the following inclusion criteria: a) aged between 18 and 75 years, b) not diagnosed with diabetes, c) speaking and understanding Icelandic or English fluently and d) living in the included service area.Data collection took place via face-to-face interviews between 1 March 2020 and 15 May 2021. Participation included answering the Finnish Diabetes Risk Score (FINDRISC), measuring the HbA1c levels and background information.ResultsOf the 220 participants, 65.9% were women. The mean age was 52.1 years (SD ± 14.1) and FINDRISC scores were as follows: 47.3% scored ≤8 points, 37.2% scored between 9 and 14 points, and 15.5% scored between 15 and 26 points. The mean HbA1c levels in mmol/mol, were 35.5 (SD ± 3.9) for men and 34.4 (SD ± 3.4) for women, ranging from 24 to 47. Body mass index ≥30 kg/m2 was found in 32% of men and 35.9% of women. Prevalence of prediabetes in this cohort was 13.2%. None of the participants had undiagnosed T2DM. Best sensitivity and specificity for finding prediabetes was by using cut-off points of ≥11 on FINDRISC, which gave a ROC curve of 0.814.ConclusionsThe FINDRISC is a non-invasive and easily applied screening instrument for prediabetes. Used in advance of other more expensive and invasive testing, it can enable earlier intervention by assisting decision making, health promotion actions and prevention of the disease burden within primary health care.Trial registrationThis study is a pre-phase of the registered study “Effectiveness of Nurse-coordinated Follow up Program in Primary Care for People at risk of T2DM” at www.ClinicalTrials.gov (NCT01688359). Registered 30 December 2020.

Efficacy of semaglutide: an evidence-based review

Type 2 diabetes mellitus (T2DM) dominates the chronic non-communicable disease pandemics by its exceptionally rapid expansion into communities all over the world. In many countries diabetes is a socially significant disease. According to the data over the past decade, the number of people with T2DM has more than doubled globally. Equally disturbing is the fact that there are more than 250 million people with undiagnosed T2DM and more than 300 million with prediabetes. For 2045, it was estimated by the International Diabetes Federation that 693 million people will have diabetes. T2DM is a disorder of complex nature that urges further dedicated studies and ingenuity in the search for novel therapeutic approaches and on the pathogenetic links of disease. Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in people with T2DM, and diabetes itself confers a substantial independent risk of coronary heart disease, stroke, and death from other vascular causes. The article discusses an urgent challenge of modern healthcare – the role of new class of sugar-lowering drugs (exogenously administered glucagon-like peptide-1 receptor agonists (arGLP-1)) semaglutide in reducing the risk of developing cardiovascular complications. The authors paid attention to the main results of SUSTAIN clinical program and use as initial treatment for patients with T2DM with very high risk indicated in the new European guidelines with a view to get additional advantages in terms of life prognosis.

Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population.

A diabetes risk score cannot directly be translated and applied in different populations, and its performance should be evaluated in the target population. This study aimed to translate the Finnish Diabetes Risk Score (FINDRISC) instrument and compare its performance with the modified version for detecting undiagnosed type 2 diabetes mellitus (T2DM) and dysglycaemia among the Indonesian adult population. Forward and backward translations were performed and followed by cultural adaptation. In total, 1,403 participants were recruited. The FINDRISC-Bahasa Indonesia (FINDRISC-BI) was scored according to the original FINDRISC instrument, while a Modified FINDRISC-BI was analyzed using a specific body mass index and waist circumference classification for Indonesians. The area under the receiver operating characteristic curve, sensitivity, specificity, and the optimal cut-offs of both instruments were estimated. The area under the receiver operating characteristic curve for detecting undiagnosed T2DM was 0.73 (0.67–0.78) for the FINDRISC-BI with an optimal cut-off score of ≥9 (sensitivity = 63.0%; specificity = 67.3%) and 0.72 (0.67–0.78) for the Modified FINDRISC-BI with an optimal cut-off score of ≥11 (sensitivity = 59.8%; specificity = 74.9%). The area under the receiver operating characteristic curve for detecting dysglycaemia was 0.72 (0.69–0.75) for the FINDRISC-BI instrument with an optimal cut-off score of ≥8 (sensitivity = 66.4%; specificity = 67.0%), and 0.72 (0.69–0.75) for the Modified FINDRISC-BI instrument with an optimal cut-off score ≥9 (sensitivity = 63.8%; specificity = 67.6%). The Indonesian version of the FINDRISC instrument has acceptable diagnostic accuracy for screening people with undiagnosed T2DM or dysglycaemia in Indonesia. Modifying the body mass index and waist circumference classifications in the Modified FINDRISC-BI results in a similar diagnostic accuracy; however, the Modified FINDRISC-BI has a higher optimal cut-off point than the FINDRISC-BI. People with an above optimal cut-off score are suggested to take a further blood glucose test.

Extracting New Temporal Features to Improve the Interpretability of Undiagnosed Type 2 Diabetes Mellitus Prediction Models.

Type 2 diabetes mellitus (T2DM) often results in high morbidity and mortality. In addition, T2DM presents a substantial financial burden for individuals and their families, health systems, and societies. According to studies and reports, globally, the incidence and prevalence of T2DM are increasing rapidly. Several models have been built to predict T2DM onset in the future or detect undiagnosed T2DM in patients. Additional to the performance of such models, their interpretability is crucial for health experts, especially in personalized clinical prediction models. Data collected over 42 months from health check-up examinations and prescribed drugs data repositories of four primary healthcare providers were used in this study. We propose a framework consisting of LogicRegression based feature extraction and Least Absolute Shrinkage and Selection operator based prediction modeling for undiagnosed T2DM prediction. Performance of the models was measured using Area under the ROC curve (AUC) with corresponding confidence intervals. Results show that using LogicRegression based feature extraction resulted in simpler models, which are easier for healthcare experts to interpret, especially in cases with many binary features. Models developed using the proposed framework resulted in an AUC of 0.818 (95% Confidence Interval (CI): 0.812−0.823) that was comparable to more complex models (i.e., models with a larger number of features), where all features were included in prediction model development with the AUC of 0.816 (95% CI: 0.810−0.822). However, the difference in the number of used features was significant. This study proposes a framework for building interpretable models in healthcare that can contribute to higher trust in prediction models from healthcare experts.

Prevalence of Impaired Fasting Glucose and Type 2 Diabetes in Kazakhstan: Findings From Large Study.

Type 2 diabetes mellitus (T2DM) is a serious public health problem. A large proportion of patients with T2DM are unaware of their condition. People with undiagnosed T2DM are at a greater risk of developing complications, whereas prediabetes has an elevated risk of becoming T2DM. The aim of this study is to estimate the prevalence of impaired fasting glucose (IFG), undiagnosed and prior-diagnosed T2DM in Kazakhstan. A cross-sectional study was conducted in four geographically remote regions using the WHO STEP survey instrument. The status of T2DM of 4,753 participants was determined using the WHO diagnostic criteria based on fasting plasma glucose (FPG) level. As a result, the survey-weighted prevalence of IFG was 1.9% (95% CI 1.1%; 3.5%) and of T2DM was 8.0% (95% CI 3.8; 15.9). A total of 54% of T2DM have been newly diagnosed with T2DM. Being 55–64 years old (OR = 2.71, 95% CI 1.12; 6.60) and having lowered HDL-C level (OR = 3.72, 95% CI 1.68; 8.23) were found to be independent predictors for IFG. Being older than 45 years, a female (OR = 0.57, 95% CI 0.39; 0.83), having high waist circumference, was associated with newly diagnosed T2DM. Whereas, the age older than 45 years, high waist circumference, and family history of diabetes (OR = 2.42, 95% CI 1.64; 3.54) were associated with preexisting T2DM. This study shows a high prevalence of IFG and a high proportion of newly diagnosed T2DM in Kazakhstan. A series of risk factors identified in the study may be used to strengthen appropriate identification of IFG or undiagnosed patients in healthcare settings to deliver either preventive or therapeutic interventions aimed to reduce the incidence of T2DM or the delay of their complications. Further longitudinal studies are needed to confirm these associations in our population.

Prevalence and trends of type 2 diabetes mellitus and prediabetes among community-dwelling heart failure patients in the United States

AimsThis study estimated national prevalence and trends of diagnosed and undiagnosed type 2 diabetes mellitus (T2DM) and prediabetes among heart failure (HF) patients in the U.S. MethodsThis cross-sectional study included 527 participants aged 20+ years with a diagnosis of HF, using data from the National Health and Nutrition Examination Survey 2005–2016. We assessed prevalence estimates of diagnosed and undiagnosed T2DM and prediabetes stratified by age-standardized sociodemographic and health characteristics. Trends of T2DM and prediabetes prevalence were examined using logistic regressions. ResultsPrevalence rates of diagnosed and undiagnosed T2DM among HF patients were 34.7% (95% confidence interval (CI), 29.2–40.3%) and 12.8% (95% CI, 9.2–16.9%), respectively. Prediabetes affected 39.1% (95% CI, 33.6–44.9%) of HF patients. Prevalence estimates of diagnosed T2DM were significantly different between non-Hispanic White (20.1% [95% CI, 13.5–27.6%]) and Hispanic participants (52.1% [95% CI, 35.9–68.0%]) (P < 0.001). The prevalence of T2DM and prediabetes did not significantly change between 2005 and 2016. ConclusionsPrevalence rates of T2DM and prediabetes among community-dwelling HF patients in the U.S. remained high between 2005 and 2016. Prevention of and targeted intervention for T2DM among at-risk HF patients is needed, particularly among those of Hispanic origin.

Type 2 diabetes mellitus in sub-Saharan Africa: challenges and opportunities.

Type 2 diabetes mellitus (T2DM), which was once thought to be rare in sub-Saharan Africa (SSA), is now well established in this region. The SSA region is undergoing a rapid but variable epidemiological transition fuelled by the pace of urbanization, with disease burden profiles shifting from communicable diseases to non-communicable diseases (NCDs). Information on the epidemiology of T2DM has increased, but wide variations in study methods, diagnostic biomarkers and criteria hamper analytical comparison, and data from high-quality studies are limited. The prevalence of T2DM is still low in some rural populations but moderate or high rates are reported in many countries/regions, with evidence for an increase in some. In addition, the proportion of undiagnosed T2DM is still high. The prevalence of T2DM is highest in African people living in urban areas, and the gradient between African people living in urban areas and people in the African diaspora is rapidly fading. However, data from longitudinal studies are lacking and there is limited information on chronic complications and the genetics of T2DM. The large unmet needs for T2DM care call for greater investment of resources into health systems to manage NCDs in SSA. Proposed health-system paradigms are being developed in some countries/regions. However, national NCD programmes need to be adequately funded and coordinated to stem the tide of T2DM and its complications.

Association of hepatic steatosis derived from ultrasound and quantitative MRI with prediabetes in the general population

The aim of our study was to investigate the association of hepatic steatosis derived from quantitative ultrasound and magnetic resonance imaging (MRI) with prediabetes in a large population-based study conducted in Northeast Germany. Hepatic steatosis was assessed through transabdominal ultrasound and quantitative MRI. For analysis we included 1622 subjects with MRI who participated in an oral glucose tolerance test and reported no known type 2 diabetes mellitus (T2DM). We classified participants as proposed by the American Diabetes Association: isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), combined IFG and IGT (IFG + IGT), and undiagnosed T2DM. Regression models were adjusted for age, sex body mass index and alcohol consumption. We observed positive associations of hepatic steatosis with glycated hemoglobin, fasting glucose and insulin, 2-h glucose and insulin, as well as homeostasis model assessment-insulin resistance index. Similarly, individuals having hepatic steatosis as defined by MRI had a higher relative risk ratio (RR) to be in the prediabetes groups i-IFG (RR = 1.6; 95% confidence interval (CI) 1.2; 2.2), i-IGT (RR = 3.3, 95% CI 2.0; 5.6) and IFG + IGT (RR = 2.5, 95% CI 1.6; 3.9) or to have undiagnosed T2DM (RR = 4.8, 95% CI 2.6; 9.0). All associations were attenuated when defining hepatic steatosis by ultrasound. Hepatic steatosis is associated with prediabetes and undiagnosed T2DM in the general population. Quantitative liver MRI revealed stronger associations with prediabetes and undiagnosed T2DM compared to ultrasound, which indicates the higher sensitivity and specificity of MRI to determine hepatic steatosis.

Prevalence of Prediabetes and Undiagnosed Diabetes Among Kuwaiti Adults: A Cross-Sectional Study.

PurposeThis study aimed to estimate the prevalence of prediabetes and undiagnosed type 2 diabetes mellitus (T2DM) according to fasting plasma glucose (FPG), 2-h plasma glucose (PG) during oral glucose tolerance test (OGTT), and glycated hemoglobin (HbA1c) among a sample of Kuwaiti adults. In addition, associations of prediabetes and undiagnosed T2DM with sex, age, and body mass index (BMI) were assessed.MethodsA cross-sectional study enrolled 1238 subjects aged 18–65 years who reported no prior history of DM. After overnight fasting, FPG and HbA1c were measured in the total study sample, and 2-h PG during a 75-g OGTT was measured in a subsample of 155 subjects. Prediabetes and undiagnosed T2DM were defined according to the American Diabetes Association criteria. Associations were assessed using Poisson regression with robust variance estimation, and adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) were estimated.ResultsWe enrolled a total of 618 males and 620 females, with an average age of 43.0 years. The prevalence of prediabetes was estimated to be 47.9% (588/1228) by FPG, 36.8% (57/155) by 2-h PG OGTT, and 31.0% (355/1144) by HbA1c. The prevalence of undiagnosed T2DM was 6.9% (85/1228) by FPG, 11.0% (17/155) by 2-h PG OGTT, and 4.9% (56/1144) by HbA1c. Sex-related differences in the prevalence of prediabetes and undiagnosed T2DM were observed. Prediabetes and undiagnosed T2DM prevalence estimates showed increasing trends as age and BMI increased. For instance, obese subjects compared to under/normal weight subjects had an increased HbA1c-defined prediabetes prevalence (aPR = 1.62, 95% CI: 1.21–2.16).ConclusionPrediabetes and undiagnosed T2DM affect a considerable proportion of Kuwaiti adults, and variations across sex, age, and BMI exist. Hence, early identification and management of affected individuals may help reduce the public health burden.

Prevalence of undiagnosed pre-diabetes or diabetes in patients with HFpEF presenting in the emergency department

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Heart failure with preserved ejection fraction (HFpEF) has become a common cause of visiting the emergency department (ED). Type 2 diabetes mellitus (T2DM) is one of the important predisposing factors. Purpose To study the prevalence of undiagnosed pre-diabetes or T2DM in the patients visiting the ED due to HFpEF. Methods 93 consecutive patients without known history of T2DM visited the ED with signs and symptoms of heart failure. Left ventricular ejection fraction (LVEF) was calculated using bedside ECHO. LVEF &amp;gt; 50% was used to classify HFpEF patients. HbA1c was measured to all patients and the cutoff for T2DM was HbA1c &amp;gt; 6.5% and for pre-diabetes 5.7-6.4%. Body mass index (BMI), brain natriuretic peptide (BNP) , creatinine and hemoglobin (Hb) were also recorded. Results are interpreted as mean ± SD. Results Mean age was 56 ± 11.8 years. 64/93 (68.8%) were female and 29/93(26.97%) male. Mean BMI was 36.52 ± 7.34 kg/m2 and mean Hb 13.51 ± 3.45 g/dl. Mean BNP was 584.82 ± 212.97 pg/ml. Mean creatinine was 1.11 ± 0.36mg/dl. 19/93 (17.67%) patients had HbA1c &amp;gt; 5.7-6.4% and were classified as pre-diabetics and 23/93(21.93%) had HbA1c &amp;gt; 6.5% and were classified as diabetics. We did not identify any correlation between the rest of the parameters. Coclusion 44.64% of the patients that visited ED due to signs or symptoms of HFpEF were identified as having either pre-diabetes or T2DM. Taking into consideration the importance of the presence of T2DM in the prognosis of the patients with HFpEF, it would be reasonable to screen all patients with HFpEF for T2DM and suggest specialized treatment.

PREVALENCE OF TYPE 2 DIABETES MELLITUS AMONG KNOWN HYPERTENSIVES AT THE REGIONAL HOSPITAL BAMENDA, CAMEROON

Objective: To evaluate the prevalence of type 2 diabetes mellitus (T2DM) and the associated risk factors among hypertensive patients with known and or unknown diabetes status. Secondly, to indirectly evaluate the impact of adopting diabetes screening in routine practice for all patients diagnosed with hypertension in the clinical settings. Design and method: This cross-sectional study was conducted on a sample of 150 hypertensive patients attending the diabetes/hypertension clinic of the Regional Hospital Bamenda. Blood pressure and glycemic blood measurements were assessed in all participants. A complete clinical history and physical exam were conducted and a data collection tool was completed. Prevalence of T2DM was obtained from fasting blood sugar, health reports and diabetes medications. Data was entered and analyzed descriptively in the form of frequency and percentage tables with the aid of SPSS 23.0 software. Results: The prevalence of T2DM among hypertensive patients in the was 44.7% (n = 67/150) with gender prevalence rates of 20.6% and 24% among males and females respectively in the studied sample (P = 0.002). T2DM prevalence increases with age, body mass index and duration of being hypertensive. Base on age, the prevalence increases from 9% in those 30–39 years and peak at 31.3% in those over 70 years. T2DM prevalence were 25.3%, 22.4%, 23.4%, and 28.4%, for BMI&lt;18.5 kg/m2, 18.5–24.9 kg/m2, 25.0–29.9 kg/m2, and &gt;30 kg/m2. The prevalence of unrecognized DM was 32.8% in hypertensive patients. Also, more than half of the subjects (56.7%) suffering from DM (38 out of 67 persons) had poorly controlled hypertension, contrasted with only about one third 27.7% (23 out of 83) of the non-diabetic participants with poorly controlled hypertension. Conclusions: The prevalence of DM in patients with hypertension was more than 8times that of the general population. The prevalence of unrecognized DM was equally very high in hypertensive patients. These findings demonstrate that hypertensive patients should regularly submit to T2DM screening for timely DM diagnosis. Therefore, major recommendations would be to adopt strict strategies to improve diabetes screening among hypertensive patients to minimize both the health and economic burdens associated with undiagnosed T2DM.

Prediction Models for Type 2 Diabetes Risk in the General Population: A Systematic Review of Observational Studies.

ObjectivesThis study aimed to provide an overview of prediction models of undiagnosed type 2 diabetes mellitus (U-T2DM) or the incident T2DM (I-T2DM) using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) checklist and the prediction model risk of the bias assessment tool (PROBAST).Data SourcesBoth PUBMED and EMBASE databases were searched to guarantee adequate and efficient coverage.Study SelectionArticles published between December 2011 and October 2019 were considered.Data ExtractionFor each article, information on model development requirements, discrimination measures, calibration, overall performance, clinical usefulness, overfitting, and risk of bias (ROB) was reported.ResultsThe median (interquartile range; IQR) number of the 46 study populations for model development was 5711 (1971 - 27426) and 2457 (2060 - 6995) individuals for I-T2DM and U-T2DM, respectively. The most common reported predictors were age and body mass index, and only the Qrisk-2017 study included social factors (e.g., Townsend score). Univariable analysis was reported in 46% of the studies, and the variable selection procedure was not clear in 17.4% of them. Moreover, internal and external validation was reported in 43% the studies, while over 63% of them reported calibration. The median (IQR) of AUC for I-T2DM models was 0.78 (0.74 - 0.82); the corresponding value for studies derived before October 2011 was 0.80 (0.77 - 0.83). The highest discrimination index was reported for Qrisk-2017 with C-statistics of 0.89 for women and 0.87 for men. Low ROB for I-T2DM and U-T2DM was assessed at 18% and 41%, respectively.ConclusionsAmong prediction models, an intermediate to poor quality was reassessed in several aspects of model development and validation. Generally, despite its new risk factors or new methodological aspects, the newly developed model did not increase our capability in screening/predicting T2DM, mainly in the analysis part. It was due to the lack of external validation of the prediction models.

Diagnostic accuracy of the Finnish Diabetes Risk Score for the prediction of undiagnosed type 2 diabetes, prediabetes, and metabolic syndrome in the Lebanese University

BackgroundRisk scores were mainly proved to predict undiagnosed type 2 diabetes mellitus (UT2DM) in a non-invasive manner and to guide earlier clinical treatment. The objective of the present study was to assess the performance of the Finnish Diabetes Risk Score (FINDRISC) for detecting three outcomes: UT2DM, prediabetes, and the metabolic syndrome (MS).MethodsThis was a prospective, cross-sectional study during which employees aged between 30 and 64, with no known diabetes and working within the faculties of the Lebanese University (LU) were conveniently recruited. Participants completed the FINDRISC questionnaire and their glucose levels were examined using both fasting blood glucose (FBG) and oral glucose tolerance tests (OGTT). Furthermore, they underwent lipid profile tests with anthropometry.ResultsOf 713 subjects, 397 subjects (55.2% female; 44.8% male) completed the blood tests and thus were considered as the sample population. 7.6% had UT2DM, 22.9% prediabetes and 35.8% had MS, where men had higher prevalence than women for these 3 outcomes (P = 0.001, P = 0.003 and P = 0.001) respectively. The AUROC value with 95% Confidence Interval (CI) for detecting UT2DM was 0.795 (0.822 in men and 0.725 in women), 0.621(0.648 in men and 0.59 in women) for prediabetes and 0.710 (0.734 in men and 0.705 in women) for MS. The correspondent optimal cut-off point for UT2DM was 11.5 (sensitivity = 83.3% and specificity = 61.3%), 9.5 for prediabetes (sensitivity = 73.6% and specificity = 43.1%) and 10.5 (sensitivity = 69.7%; specificity = 56.5%) for MS.ConclusionThe FINDRISC can be considered a simple, quick, inexpensive, and non-invasive instrument to use in a Lebanese community of working people who are unaware of their health status and who usually report being extremely busy because of their daily hectic work for the screening of UT2DM and MS. However, it poorly screens for prediabetes in this context.

Prevalence of Undiagnosed Diabetes and Prediabetes in the Dental Setting: A Systematic Review and Meta-Analysis.

Background With the close link between diabetes mellitus (DM) and periodontal disease (PD), dentists have an unrealized opportunity to make a chance discovery of a patient's medical condition. Unlike in the medical setting, information on the point of care (PoC) and opportunistic screening for DM in the dental setting is limited. To make a reliable estimate on the prevalence of undiagnosed type 2 diabetes mellitus (T2DM) and prediabetes among dental patients in the dental setting and to assist healthcare planners in making an informed decision, information on the disease frequency and strategies employed to address this issue is of paramount importance. Objectives To summarize the data on the prevalence of undiagnosed T2DM and prediabetes amongst dental patients and further explore the effectiveness of the PoC screening and its implication for use in the dental setting. Methods A MEDLINE-PubMed, EMBASE, Web of Science, and Cochrane Library search was conducted with no time specification. Information on study characteristics and diagnostic parameters was retrieved for meta-analysis. All the studies were assessed for methodological quality using the QUADAS-2 tool. Proportions were presented in tables and forest plots. All statistical analysis was performed using the MedCalc software. Results Nine studies met the inclusion criteria. The proportion of dental patients identified to be at a risk of hyperglycaemia with the PoC screening using random blood glucose (RBG) and HbA1 was 32.47% and 40.10%, whilst the estimated proportion with undiagnosed T2DM and prediabetes was identified as 11.23% and 47.38%. Conclusion A significant proportion of dental patients can be identified as undiagnosed T2DM and prediabetes. Targeted opportunistic screening is a feasible approach and can help reduce the prevalence of undiagnosed T2DM and prediabetes.

Performance and costs of multiple screening strategies for type 2 diabetes: two population-based studies in Shanghai, China

IntroductionTo compare the performance and the costs of various assumed screening strategies for type 2 diabetes mellitus (T2DM) among Chinese adults, and identify an optimal one for the population.Research design...

Abstract P318: Prevalence and Trends of Type 2 Diabetes Mellitus and Prediabetes Among Community-Dwelling Heart Failure Patients in the U.S. 2005-2016: A National Health and Nutrition Examination Survey (NHANES) Analysis

Introduction: Recent scientific statements highlight the importance of understanding the effects of the coexistence of heart failure (HF) and type 2 diabetes mellitus (T2DM) on disease management decisions and patient outcomes. Various prevalence estimates of the T2DM burden among HF patients have been reported; however, national estimates are not available. The objective of the study was to assess the prevalence and trends of T2DM (total, diagnosed, and undiagnosed) and prediabetes among community-dwelling HF patients using nationally representative data. Methods: We included 473 participants (20+ years) with a diagnosis of HF using data from the 2005-2016 NHANES survey cycles. Diagnosed T2DM was defined by self-report of a previous physician diagnosis. Undiagnosed T2DM was defined by the absence of a physician diagnosis and the presence of ≥ 1 of 3 criteria: 1) Two-hour plasma glucose (2hPG) after oral glucose tolerance test (OGTT) ≥ 200 mg/dL, 2) Hemoglobin A1c (HbA1c) ≥ 6.5%, 3) Fasting plasma glucose (FPG) ≥ 126 mg/dL. Total T2DM was defined as having diagnosed or undiagnosed T2DM. Prediabetes was defined by the absence of T2DM and the presence of ≥ 1 of 3 criteria: 1) 2hPG after OGTT of 140 mg/dL to 199 mg/dL, 2) HbA1c of 5.7% to 6.4%, 3) FPG of 100 mg/dL to 125mg/dL. We stratified estimates by age-standardized socio-demographic characteristics. Trends of the prevalence of T2DM and prediabetes were examined using logistic regressions. Results: The prevalence rates of total, diagnosed, and undiagnosed T2DM and prediabetes among HF patients were 51.4% (95% CI, 46.0%-56.7%), 37.5% (31.7%-43.6%), 13.8% (10.0%-18.2%), and 36.0% (30.2%-42.1%), respectively. The prevalence of T2DM and prediabetes did not significantly change across individual survey cycles. Conclusion: Rates of T2DM and prediabetes among community-dwelling HF patients in the U.S have been persistently high over the past decade. These findings support the need for the prevention and targeted intervention of T2DM in HF patients.

Assessing Diabetes Risk Factors in Rural Dwelling Grandparent Caregivers.

Objective:The purpose of this study is to assess type 2 diabetes mellitus (T2DM) risk factors in grandparent caregivers living in a rural environment.Methods:Clinical measures (hemoglobin A1c [HbA1c], blood pressure, and lipids) and self-reported data on social environment factors were attained. Data were analyzed via Pearson’s correlation and regression models.Results:By clinical definition of diabetes (HbA1c ≥ 6.5%), 21% were prediabetic and 28% had undiagnosed T2DM. There was an association between the number of individuals in the home and triglycerides (r = −.25), high-density lipoproteins (HDL; r = .43), and body mass index (BMI; r = .39). Guardianship status had a significant association with BMI (r = −.38). There was a significant association between low-density lipoprotein (LDL; r = −.32) and access to community shared resources. In the adjusted linear model, the number of grandchildren in the home had a significant relationship with HDL (β = .012, p = .021) whereas the number of individuals living in the home had a statistically significant relationship with HDL (β = .026, p < .000) and BMI (β = .046, p = .02). In addition, 15% of participants reported being food insecure.Discussion:Efforts are needed to identify and screen at-risk populations living in geographically isolated areas. Considerations should be given to leveraging existing community resources for grandparent caregivers via schools, health systems, and government agencies to optimize health and well-being.

Obesity indicators that best predict type 2 diabetes in an Indian population: insights from the Kerala Diabetes Prevention Program.

Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present.