Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in Greece

Psychosis metabolic risk calculator (PsyMetRiC) in early psychosis: External validation study in Finland

INTRODUCTION

Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).

METHODS

We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18-35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi).

RESULTS

The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59-0.82) compared with partial model (C = 0.70, 95% CI 0.59-0.80) or FINDRISC (C = 0.63, 95% CI 0.54-0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.

CONCLUSION

PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.

Factors affecting continuous participation in follow-up evaluations during a lifestyle intervention programme for type 2 diabetes prevention: The Feel4Diabetes-study

AIMS

Community- and school-based lifestyle interventions are an efficient method of preventing type 2 diabetes in vulnerable populations. Many participants, however, fail to complete the necessary follow-ups. We investigated factors affecting the continuous participation in follow-up evaluations during the Feel4Diabetes-study, a multilevel intervention programme implemented across Europe.

METHODS

Socioeconomic, sociodemographic and clinical factors were assessed for 2702 participants within six participating countries: Bulgaria and Hungary (low-to-middle-income countries, LMIC), Belgium and Finland (high-income countries, HIC) and Greece and Spain (high-income countries under austerity measures, HICAM).

RESULTS

Statistically significant differences were detected with respect to sex, control group, education level, employment status, BMI and blood pressure measurements (systolic and diastolic blood pressure). Post hoc analysis revealed significant differences within socioeconomic regions. Higher levels of education were associated with significantly lower attrition in HIC (p < 0.05) and HICAM (p < 0.001), higher employment status was associated with lower attrition in HICAM (p < 0.001) and being female was associated with lower attrition in LMIC (p < 0.001). Surprisingly, the intervention group exhibited higher-than-expected attrition in HIC (p < 0.001) and HICAM (p = 0.003), and lower attrition in LMIC (p = 0.007). When tested together in the same multivariable predictive model, all sociodemographic and socioeconomic variables along with higher BMI retained their statistical significance, while systolic and diastolic blood pressure failed to remain significant.

CONCLUSIONS

Key socioeconomic and sociodemographic factors along with BMI play a significant role in determining continuous participation in follow-up evaluations during school- and community-based intervention programmes.

Risk of Type 2 Diabetes in University Students at the University of Extremadura: A Cross-Sectional Study

The prevalence of type 2 diabetes is increasing worldwide. The aim of our study was to detect people susceptible to DM among a university population aged 18 to 45 years and analyze the existence of modifiable risk factors in order to implement prevention programs, in addition to analyzing BMI data related to the variables under study. We proposed a descriptive, cross-sectional study following the recommendations of cross-sectional studies (STROBE), with a sample of 341 subjects, students enrolled at the University of Extremadura, carried out by two researchers. The research protocol was approved by the Bioethics Committee of the University of Extremadura (165/2021). The study considered the Findrisk questionnaire in Spanish, validated by the Blackboard Study, a stadiometer to measure height, a bioimpedance meter to evaluate weight and body composition parameters, and a blood pressure monitor to measure blood pressure. The results indicated that the participants had a low risk of suffering T2DM. The highest Findrisk test scores were found in those with a BMI value above 25, lower physical activity, poor dietary intake of fruits and vegetables, and increased fat mass. Our future research will be the implementation of T2DM prevention programs, acting on modifiable factors.

Prevalence and Factors Associated with Metabolic Syndrome among Non-Diabetic Saudi Adults: A Cross-Sectional Study

(1) Introduction: given the high prevalence of metabolic syndrome (MetS) in Saudi Arabia, especially in Jeddah, this study aims to understand the dietary and lifestyle-related risk factors among Jeddah's non-diabetic adults. (2) Material and Methods: Employing a cross-sectional design, non-diabetic adults were sourced from public healthcare centers. Demographics, lifestyle, and dietary habits were surveyed. Blood pressure, anthropometrics, and fasting blood samples measuring plasma glucose, serum triglycerides, and HDL cholesterol were collected. The age cut-off for MetS was ascertained using the receiver operating characteristic curve. Variables influencing MetS were evaluated using univariate logistic regression, and consequential factors underwent multivariate analysis, adjusted for age and sex. (3) Results: Among 1339 participants, 16% had MetS, with age being the strongest predictor (p < 0.001). The optimal age cut-off was 32 years. For those <32, elevated BP in men and waist circumference (WC) in women were most prevalent. For those >32, elevated WC was dominant in both sexes. Univariate logistic regression revealed that higher income and education correlated with lower MetS prevalence, while marriage and smoking were risk factors. Adjusting for age and sex, only very high income had a significant low-risk association (p = 0.034). (4) Conclusion: MetS is notable in the studied group, with age as the pivotal predictor. High income reduces MetS risk, while marital status and smoking could increase it. Since this was a cross-sectional study, cohort studies are needed to validate our findings.

Diabetes and the risk of cirrhosis and HCC: An analysis of the UK Biobank

BACKGROUND

Diabetes increases the risk of cirrhosis and HCC. We aimed to assess such associations given different diabetes statuses.

METHODS

We included 449,497 participants in the UK Biobank cohort (mean age 56.7±8.0 y; 45.5% male) and assessed the association between preclinical diabetes (prediabetes, having a high risk of diabetes), clinical diabetes (presence, duration, or glycemic control of type 2 diabetes), and incident liver cirrhosis and HCC by the Cox regression. Liver diseases were ascertained through inpatient records and national death registration. Gene-environment interaction was examined using the polygenic risk scores of cirrhosis and HCC.

RESULTS

Compared with normoglycemia, having <5 years,≥5 years of diabetes showed adjusted HRs (aHRs) of cirrhosis as 2.85 (2.45-3.32) and 3.43 (2.92-4.02), respectively, which was similarly observed in HCC. In diabetes, a level of hemoglobin A1c ≥ 7.5% showed aHRs of 1.37 (1.07-1.76) and 1.89 (1.10-3.25) for cirrhosis and HCC, respectively, compared with hemoglobin A1c < 6.5%. In non-diabetes, prediabetes presented aHRs of 1.41 (1.14-1.73) and 1.80 (1.06-3.04) of cirrhosis and HCC, respectively. Participants with a high risk of diabetes at baseline showed an aHR of 3.31 (2.65-4.13) for cirrhosis and 2.09 (1.15-3.80) for HCC. In those with a high genetic risk of HCC, having an increased risk of diabetes posed a significantly higher risk of HCC (aHR: 1.93, 1.45-2.58, Pinteraction=0.005), compared with those without a high genetic risk of HCC.

CONCLUSIONS

Not only diabetes but preclinical diabetes, longer diabetes duration, and higher baseline hemoglobin A1c were associated with an increased risk of incident cirrhosis and HCC in the general population.

Risks of obesity and diabetes development in the population of the Ivano-Frankivsk region in Ukraine

The epidemic of obesity that parallels diabetes mellitus and its complications are diseases of major concern to modern societies. Community-based screening is an effective strategy to identify people at high risk of developing overweight, obesity, prediabetes, diabetes, and related health problems. Here, we present the results of screening the population of four locations in the Ivano-Frankivsk region (Western Ukraine). The study group consisted of 400 adults and 252 children. The measured parameters were: (1) main vital signs - body temperature, resting heart rate, blood pressure; (2) anthropometric indicators - body mass and height, body mass index, waist circumference; and (3) metabolic parameters - fasting capillary blood glucose, total body fat, visceral fat, physical activity level and 10-year risk of developing type 2 diabetes. The study found that 23 % of the adults were overweight and 14.8 % obese. Among children, 9.9 % were overweight and 8.7 % obese. Adult body mass index correlated with visceral fat percentage, systolic/diastolic blood pressure and levels of fasting capillary blood glucose. Adults over 18 years of age had fasting capillary blood glucose ≥5.6 mmol/L (14.3 %), including those with undiagnosed pre-diabetes (13.3 %) and suspected diabetes mellitus (1.0 %). The percentage of visceral body fat in adults was positively associated with the 10-year risk of developing type 2 diabetes.

Prevalence of increased risk of type 2 diabetes in general practice: a cross-sectional study in Norway

BACKGROUND

Type 2 diabetes (T2D) is a global public health problem, but the onset can be delayed or prevented with adequate intervention in individuals with increased risk. Therefore, a major challenge in general practice is to identify individuals at risk of diabetes. However, limited knowledge is available about the prevalence of high diabetes risk individuals in a primary care population. In a cohort of consecutive patients in general practice we examined the prevalence of known diabetes and estimated risk of diabetes using The Finnish Diabetes Risk Score (FINDRISC) calculator, by sociodemographic and clinical characteristics.

METHODS

This study was a cross-sectional study conducted in four general practices in Western and Eastern Norway. A total of 1682 individuals, 20-80 years of age, were assessed for eligibility from May to December 2019. We excluded patients who actively declined participation (n = 112), were lost because of various organization challenges (n = 103) and patients who did not fulfil the inclusions criteria (n = 63). Diabetes prevalence and prevalence of individuals at risk of T2D with 95% confidence intervals (CI) were estimated for the total sample, by age group and for men and women separately. We tested for differences between groups using t-test for continuous variables and chi-square test (Pearson Chi-Square) for categorical variables.

RESULTS

Of 1404 individuals, 132 reported known diabetes, yielding a prevalence of 9.9% (95% CI 8.4-11.6). Among participants without a known diagnosis of diabetes, the following estimates of elevated risk assessment scores were found: FINDRISC score ≥ 11 32.8% (95% CI 30.3-35.4) and FINDRISC ≥ 15 10.0% (95% CI 8.6-11.9). Comparable results were found between the sexes.

CONCLUSIONS

Detection of unknown diabetes and individuals with increased risk, is of high public health relevance for early implementation of preventive measures aimed to reduce the risk of diabetes and its complications through lifestyle modification. A simple, non-expensive questionnaire, such as FINDRISC, may be valuable as an initial screening method in general practice to identify those in need for preventive measures.

Large scale application of the Finnish diabetes risk score in Latin American and Caribbean populations: a descriptive study

Background

The prevalence of type 2 diabetes (T2D) continues to increase in the Americas. Identifying people at risk for T2D is critical to the prevention of T2D complications, especially cardiovascular disease. This study gauges the ability to implement large population-based organized screening campaigns in 19 Latin American and Caribbean countries to detect people at risk for T2D using the Finnish Diabetes Risk Score (FINDRISC).

Methods

This cross-sectional descriptive analysis uses data collected in a sample of men and women 18 years of age or older who completed FINDRISC via eHealth during a Guinness World Record attempt campaign between October 25 and November 1, 2021. FINDRISC is a non-invasive screening tool based on age, body mass index, waist circumference, physical activity, daily intake of fruits and vegetables, history of hyperglycemia, history of antihypertensive drug treatment, and family history of T2D, assigning a score ranging from 0 to 26 points. A cut-off point of ≥ 12 points was considered as high risk for T2D.

Results

The final sample size consisted of 29,662 women (63%) and 17,605 men (27%). In total, 35% of subjects were at risk of T2D. The highest frequency rates (FINDRISC ≥ 12) were observed in Chile (39%), Central America (36.4%), and Peru (36.1%). Chile also had the highest proportion of people having a FINDRISC ≥15 points (25%), whereas the lowest was observed in Colombia (11.3%).

Conclusions

FINDRISC can be easily implemented via eHealth technology over social networks in Latin American and Caribbean populations to detect people with high risk for T2D. Primary healthcare strategies are needed to perform T2D organized screening to deliver early, accessible, culturally sensitive, and sustainable interventions to prevent sequelae of T2D, and reduce the clinical and economic burden of cardiometabolic-based chronic disease.

Prediction of hypercholesterolemia using machine learning techniques

Purpose

Hypercholesterolemia is a major risk factor for a wide range of cardiovascular diseases. Developing countries are more susceptible to hypercholesterolemia and its complications due to the increasing prevalence and the lack of adequate resources for conducting screening and/or prevention programs. Using machine learning techniques to identify factors contributing to hypercholesterolemia and developing predictive models can help early detection of hypercholesterolemia, especially in developing countries.

Methods

Data from the nationwide 2016 STEPs study in Iran were used to identify socioeconomic, lifestyle, and metabolic risk factors associated with hypercholesterolemia. Furthermore, the predictive power of the identified risk factors was assessed using five commonly used machine learning algorithms (random forest; gradient boosting; support vector machine; logistic regression; artificial neural network) and 10-fold cross validation in terms of specificity, sensitivity, and the area under the receiver operating characteristic curve.

Results

A total of 14,667 individuals were included in this study, of those 12.8% (n = 1879) had (undiagnosed) hypercholesterolemia. Based on multivariate logistic regression analysis the five most important risk factors for hypercholesterolemia were: older age (for the elderly group: OR = 2.243; for the middle-aged group: OR = 1.869), obesity-related factors including high BMI status (morbidly obese: OR = 1.884; obese: OR = 1.499; overweight: OR = 1.426) and AO (OR = 1.339), raised BP (hypertension: OR = 1.729; prehypertension: OR = 1.577), consuming fish once or twice per week (OR = 1.261), and having risky diet (OR = 1.163). Furthermore, all the five hypercholesterolemia prediction models achieved AUC around 0.62, and models based on random forest (AUC = 0.6282; specificity = 65.14%; sensitivity = 60.51%) and gradient boosting (AUC = 0.6263; specificity = 64.11%; sensitivity = 61.15%) had the optimal performance.

Conclusion

The study shows that socioeconomic inequalities, unhealthy lifestyle, and metabolic syndrome (including obesity and hypertension) are significant predictors of hypercholesterolemia. Therefore controlling these factors is necessary to reduce the burden of hypercholesterolemia. Furthermore, machine learning algorithms such as random forest and gradient boosting can be employed for hypercholesterolemia screening and its timely diagnosis. Applying deep learning algorithms as well as techniques for handling the class overlap problem seems necessary to improve the performance of the models.

Cross-sectional and longitudinal associations between family meals frequency and children's overweight/obesity in families at high risk of type 2 diabetes: The Feel4Diabetes-study

BACKGROUND

The frequency of family meals has been suggested as a protective factor against obesity among children.

OBJECTIVE

This study aimed to investigate the cross-sectional and longitudinal associations between family meals frequency and children's overweight/obesity in families at high risk of type 2 diabetes (T2D) across six European countries.

METHODS

989 parent-child dyads (52% girls and 72% mothers) were included. Participants completed validated measures to assess the frequency of family meals and anthropometrics. Multivariable regression models were applied to examine the longitudinal associations between family meals frequency and overweight/obesity in children. Logistic regression was performed to predict the odds of having overweight/obesity depending on changes in family meals frequency over a two-year follow-up period. Analyses were stratified for children's sex.

RESULTS

High frequency of family breakfasts and/or dinners was inversely associated with children's BMI in boys and girls at T2. Results showed decreased odds of overweight/obesity at follow-up among both boys (OR = 0.65; 95% CI 0.41, 0.96) and girls (OR = 0.53; 95% CI 0.31, 0.87) who consumed minimum of three times family breakfasts and/or family dinners a week at baseline. An increase in family breakfasts and/or dinners frequency was associated with lower odds of overweight/obesity in both boys and girls at follow-up.

CONCLUSION

A high frequency of family breakfasts and/or dinners but not lunch during childhood is associated with lower odds of overweight/obesity development in children from families at high risk of T2D. The promotion of family meals could help in preventing the development of overweight/obesity among children.

Riesgo cardiovascular en pacientes con FINDRISC-C mayor o igual a 12

Introducción: la herramienta FINDRISC permite calcular el riesgo de desarrollar diabetes con punto de corte para Colombia de 12.  Existe evidencia de que el riesgo cardiovascular se incrementa a medida que lo hace el puntaje, pero en Colombia no existe información cuando es ≥ 12. Objetivo: establecer el riesgo cardiovascular (RCV) en pacientes con FINDRISK-C ≥ 12 mediante score Framingham ajustado para Colombia.  Materiales y métodos: subanálisis transversal retrospectivo en 796 pacientes a quienes se les aplicó el cuestionario FINDRISC-C, de ellos 293 con puntaje ≥ 12 y 262 cumplieron los criterios de elegibilidad. Antes se les calculó el RCV mediante análisis uni y multivariado, significancias estadísticas y análisis de correspondencias múltiple. Resultados: 262 pacientes, 63% mujeres, 87% tuvieron sobrepeso y obesidad, promedio de perímetro abdominal 97 cm, 10% eran fumadores y 48% tenían antecedente familiar de diabetes mellitus tipo 2. Se encontró una media de RCV de 8,10 (IC 7,29-8,91), al estratificar por FINDRISC-C la media para cada una de las categorías fue: FINDRISC-C moderado 7,83; FINDRISC-C alto 7,87, FINDRISC-C muy alto 12,61.  La prevalencia de dislipidemia fue de 46,2 % (IC 95%: 40-50) siendo mayor en hombres (53,6%). Conclusión: los pacientes con FINDRISC-C ≥ 12 tienen un RCV entre moderado y alto, existiendo tendencia al incremento del porcentaje de riesgo calculado según score Framingham ajustado para Colombia, a medida que aumenta el puntaje FINDRISC-C.  La prevalencia de dislipidemia en pacientes con FINDRISC-C ≥ 12 fue elevada.

Do parental risk factors for type 2 diabetes predict offspring risk of overweight and obesity? The Feel4Diabetes study

OBJECTIVES

The prevention of children being overweight/obese is of utmost importance. Parental characteristics play a pivotal role in shaping offspring weight status. This study aimed to examine associations between parental obesity and children's overweight/obesity status, and whether other parental type 2 diabetes (T2D) risk factors can predict children's obesity status.

METHODS

Logistic regression and receiver operating characteristic (ROC) analyses were conducted, using cross-sectional data from a European cohort of 20 151 adults (10 967 mothers; 9184 fathers) and children (n = 10 967) participating in the Feel4Diabetes study. Anthropometric measurements were conducted in children, and overweight/obesity was defined according to the International Obesity Task Force criteria. Parents' T2D risk was assessed applying the Finnish Diabetes Risk Score (FINDRISC).

RESULTS

After adjusting for all other FINDRISC variables, region and maternal/parental education, maternal (adjusted odds ratio [aOR]: 2.64; 95% confidence interval [CI], 2.18-3.20) and parental (aOR: 3.21; 95% CI, 2.65-3.91) obesity, maternal (aOR: 1.46; 95% CI, 1.23-1.74) and parental (aOR: 1.59; 95% CI, 1.32-1.92) high waist circumference, as well as maternal (aOR: 1.60; 95% CI, 1.27-2.01) and parental (aOR: 1.87; 95% CI, 1.58-2.21) high FINDRISC score, were associated with child overweight/obesity status. Maternal (area under the curve- ROC: 0.638; 95% CI, 0.628-0.647) and paternal body mass index (BMI; area under the curve-ROC: 0.632; 95% CI, 0.622-0.642) were the most accurate in predicting child overweight/obesity status.

CONCLUSIONS

Among parental risk factors for T2D, maternal/parental overweight/obesity status, central obesity, and high FINDRISC score were the main predictors of childhood overweight/obesity status, with BMI the most accurate. Maternal or paternal BMI is simple to use, and might be useful for the early identification of children at risk of being overweight/obese rather than other T2D factors.

Performance of a Finnish Diabetes Risk Score in detecting undiagnosed diabetes among Kenyans aged 18-69 years

BACKGROUND

The application of risk scores has often effectively predicted undiagnosed type 2 diabetes in a non-invasive way to guide early clinical management. The capacity for diagnosing diabetes in developing countries including Kenya is limited. Screening tools to identify those at risk and thus target the use of limited resources could be helpful, but these are not validated for use in these settings. We, therefore, aimed to measure the performance of the Finnish diabetes risk score (FINDRISC) as a screening tool to detect undiagnosed diabetes among Kenyan adults.

METHODS

A nationwide cross-sectional survey on non-communicable disease risk factors was conducted among Kenyan adults between April and June 2015. Diabetes mellitus was defined as fasting capillary whole blood ≥ 7.0mmol/l. The performance of the original, modified, and simplified FINDRISC tools in predicting undiagnosed diabetes was assessed using the area under the receiver operating curve (AU-ROC). Non-parametric analyses of the AU-ROC, Sensitivity (Se), and Specificity (Sp) of FINDRISC tools were determined.

RESULTS

A total of 4,027 data observations of individuals aged 18-69 years were analyzed. The proportion/prevalence of undiagnosed diabetes and prediabetes was 1.8% [1.3-2.6], and 2.6% [1.9-3.4] respectively. The AU-ROC of the modified FINDRISC and simplified FINDRISC in detecting undiagnosed diabetes were 0.7481 and 0.7486 respectively, with no statistically significant difference (p = 0.912). With an optimal cut-off ≥ 7, the simplified FINDRISC had a higher positive predictive value (PPV) (7.9%) and diagnostic odds (OR:6.65, 95%CI: 4.43-9.96) of detecting undiagnosed diabetes than the modified FINDRISC.

CONCLUSION

The simple, non-invasive modified, and simplified FINDRISC tools performed well in detecting undiagnosed diabetes and may be useful in the Kenyan population and other similar population settings. For resource-constrained settings like the Kenyan settings, the simplified FINDRISC is preferred.

Developing a risk assessment tool for insulin resistance in European adolescents: the HELENA-IR score

OBJECTIVES

To develop and validate an easy-to-use screening tool for identifying adolescents at high-risk for insulin resistance (IR).

METHODS

Α total of 1,053 adolescents (554 females), aged 12.5 to 17.5 years with complete data on glucose and insulin levels were included. Body mass index (BMI), fat mass index (FMI) and the homeostasis model assessment for insulin resistance (HOMA-IR) were calculated. VO₂max was predicted using 20 m multi-stage fitness test. The population was randomly separated into two cohorts for the development (n=702) and validation (n=351) of the index, respectively. Factors associated with high HOMA-IR were identified by Spearman correlation in the development cohort; multiple logistic regression was performed for all identified independent factors to develop a score index. Finally, receiver operating characteristic (ROC) analysis was performed in the validation cohort and was used to define the cut-off values that could identify adolescents above the 75th and the 95th percentile for HOMA-IR.

RESULTS

BMI and VO₂max significantly identified high HOMA-IR in males; and FMI, TV watching and VO₂max in females. The HELENA-IR index scores range from 0 to 29 for males and 0 to 43 for females. The Area Under the Curve, sensitivity and specificity for identifying males above the 75th and 95th of HOMA-IR percentiles were 0.635 (95%CI: 0.542-0.725), 0.513 and 0.735, and 0.714 (95%CI: 0.499-0.728), 0.625 and 0.905, respectively. For females, the corresponding values were 0.632 (95%CI: 0.538-0.725), 0.568 and 0.652, and 0.708 (95%CI: 0.559-0.725), 0.667 and 0.617, respectively. Simple algorithms were created using the index cut-off scores.

CONCLUSIONS

Paediatricians or physical education teachers can use easy-to-obtain and non-invasive measures to apply the HELENA-IR score and identify adolescents at high risk for IR, who should be referred for further tests.

An Assessment of the 10-Year Risk of Developing Type 2 Diabetes Among Saudi Adults Based on the Finnish Diabetes Risk Score

Background and objective

Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated blood glucose levels that eventually lead to several acute and chronic complications. Type 2 DM (T2DM) is a major healthcare problem globally as well as in the Kingdom of Saudi Arabia (KSA). Predicting and identifying people at high risk for developing T2DM will help implement preventive measures for these individuals. In light of this, the present study was designed to estimate the 10-year risk of developing T2DM among the Saudi general population.

Methodology

A descriptive, cross-sectional survey involving 15,509 Saudi individuals was undertaken. The participants were selected from all 13 provinces of KSA based on stratified random sampling. The Finnish Diabetes Risk Score (FINDRISC), a validated tool for T2DM risk assessment, was employed. Descriptive and chi-square analyses were used.

Results

The mean age of the participants was 28.33 years. Subjects with a moderate, high, and very high risk of developing T2DM within the next 10 years comprised approximately 18% of the sample. The mean FINDRISC was 7.53 [standard deviation (SD): 4.28], which is considered a level associated with a slightly elevated risk of developing T2DM. Of note, 938 participants (6.05%) among the sample population had a high risk of developing T2DM as predicted by FINDRISC. Education, daily physical activity, high blood glucose, and family history of DM were significantly higher in females compared to males (p<0.001). On the other hand, smoking rates and use of antihypertensive medications were substantially higher among males (p<0.001).

Conclusion

Based on our findings, approximately 18% of the Saudi general population has a moderate to high risk of developing T2DM. T2DM risk assessment should be widely and regularly practiced by general practitioners and internists as part of national programs for diabetes prevention.

Parental food consumption and diet quality and its association with children's food consumption in families at high risk of type 2 diabetes: the Feel4Diabetes-study

OBJECTIVE

To examine the parental food consumption and diet quality and its associations with children's consumption in families at high risk for developing type 2 diabetes mellitus across Europe. Also, to compare food frequency consumption among parents and children from high-risk families to the European Dietary guidelines/recommendations.

DESIGN

Cross-sectional study using Feel4diabetes FFQ.

SETTING

Families completed FFQ and anthropometric measures were obtained. Linear regression analyses were applied to investigate the relations between parental food consumption and diet quality and their children's food consumption after consideration of potential confounders.

PARTICIPANTS

2095 European families (74·6 % mothers, 50·9 % girls). The participants included parent and one child, aged 6-8 years.

RESULTS

Parental food consumption was significantly associated with children's intake from the same food groups among boys and girls. Most parents and children showed under-consumption of healthy foods according to the European Dietary Guidelines. Parental diet quality was positively associated with children's intake of 'fruit' (boys: β = 0·233, P < 0·001; girls: β = 0·134, P < 0·05) and 'vegetables' (boys: β = 0·177, P < 0·01; girls: β = 0·234, P < 0·001) and inversely associated with their 'snacks' consumption (boys: β = -0·143, P < 0·05; girls: β = -0·186, P < 0·01).

CONCLUSION

The present study suggests an association between parental food consumption and diet quality and children's food intake. More in-depth studies and lifestyle interventions that include both parents and children are therefore recommended for future research.

Efficacy of an Online Educational Intervention in Reducing Body Weight in the Pre-Diabetic Population of 18-45 Years Old, a Randomized Trial Protocol

Aim: to analyze the efficacy of an educational online intervention focused on lifestyle changes in reducing body weight from baseline to 6 months in the pre-diabetic population of 18−45 years old in Extremadura (Spain). Methods: a single-blind, multicenter randomized parallel-comparison trial with two intervention groups in a 1:1 ratio will be carried out. Participants will be randomly assigned to intervention A or B with 37 cases in each group according to inclusion criteria of being enrolled or working at Extremadura University, scoring >7 points on the Findrisc test and not having diagnosed diabetes mellitus or physical disabilities. Intervention-A group will have access to online information about healthy diet and exercise. Intervention-B group will have access to a six-session educational program regarding behavioral changes in diet and exercise habits. They will complete follow-up activities and have a personal trainer and motivation. The primary outcome will be identifying changes in body weight from baseline to 1 and 6 months and between groups. The secondary outcomes will be accomplishing regular physical activity (>30 min/day or >4 h/week), decreasing sugary food intake or avoiding it altogether, increasing vegetable/fruit intake and lowering HbA1c levels to non-diabetic status when necessary.

The Feel4Diabetes intervention: effectiveness on 24-hour physical behaviour composition in families at risk for diabetes development

The Feel4Diabetes project conducted a 2-year intervention aiming to encourage healthy behaviours in families in six European countries. Within this paper, the intervention effect was evaluated after the first intervention year on 24-hour physical behaviour composition in Belgian families at risk for type 2 diabetes. Parents’ and children’s levels of physical activity (PA) and sedentary behaviour (SB) were objectively measured and sleep duration was self-reported. Valid data were obtained in 82 children (mean age: 8.2 ± 0.84; 50.0% boys) and 72 parents (mean age: 40.1 ± 5.5; 27.8% fathers). Data were analysed using a compositional data approach, and mixed models were used to take clustering into account. Results showed that for children, the mean baseline composition of the 24-hour day in sleep, SB, light and moderate-to-vigorous PA for the intervention group was (11 hours 18 minutes; 6 hours 33 minutes; 5 hours 02 minutes, 1 hour 08 minutes) and for the control group (11 hours 18 minutes; 6 hours 35 minutes; 5 hours 04 minutes; 1 hour 06 minutes), respectively. For parents, the mean baseline composition was for the intervention group (8 hours 12 minutes; 9 hours 36 minutes; 5 hours 43 minutes; 27 minutes) and for the control group (8 hours 00 minute; 9 hours 00 minute; 6 hours 27 minutes; 33 minutes). No significant intervention effects were found on 24-hour physical behaviour composition of either parents or children (p = 0.19 and p = 0.21, respectively). A relatively small study population and a poor attendance rate among parents could maybe explain the lack of effectiveness. More effective strategies are needed to retain vulnerable families in interventions. Furthermore, future approaches to improve the 24-hour physical behaviour composition should maybe focus more specifically on PA, SB and sleep, and involve teachers, children and parents in the design of the intervention. Trial registration: NCT02393872 in ClinicalTrials.gov.

External Validation of Finnish Diabetes Risk Score and Australian Diabetes Risk Assessment Tool Prediction Models to Identify People with Undiagnosed Type 2 Diabetes: A Cross-sectional Study in Iran

BACKGROUND

Noninvasive risk prediction models have been widely used in various settings to identify individuals with undiagnosed diabetes.

OBJECTIVES

We aimed to evaluate the discrimination, calibration, and clinical usefulness of the Finnish Diabetes Risk Score (FINDRISC) and Australian Diabetes Risk Assessment (AUSDRISK) to screen undiagnosed diabetes in Kerman, Iran.

METHODS

We analyzed data from 2014 to 2018 in the second round of the Kerman Coronary Artery Disease Risk Factors Study (KERCADRS), Iran. Participants aged 35 - 65 with no history of confirmed diabetes were eligible. The area under the receiver operating characteristic curve (AUROC) and decision curve analysis were applied to evaluate the discrimination power and clinical usefulness of the models, respectively. The calibration was assessed by the Hosmer-Lemeshow test and the calibration plots.

RESULTS

Out of 3262 participants, 145 (4.44%) had undiagnosed diabetes. The estimated AUROCs were 0.67 and 0.62 for the AUSDRISK and FINDRISC models, respectively (P < 0.001). The chi-square test results for FINDRISC and AUSDRISC were 7.90 and 16.47 for the original model and 3.69 and 14.61 for the recalibrated model, respectively. Based on the decision curves, useful threshold ranges for the original models of FINDRIS and AUSDRISK were 4% to 10% and 3% to 13%, respectively. Useful thresholds for the recalibrated models of FINDRISC and AUSDRISK were 4% to 8% and 4% to 9%, respectively.

CONCLUSIONS

The original AUSDRISK model performs better than FINDRISC in identifying patients with undiagnosed diabetes and could be used as a simple and noninvasive tool where access to laboratory facilities is costly or limited.

Early prediction of diabetes by applying data mining techniques: A retrospective cohort study

BACKGROUND

Saudi Arabia ranks 7th globally in terms of diabetes prevalence, and its prevalence is expected to reach 45.36% by 2030. The cost of diabetes is expected to increase to 27 billion Saudi riyals in cases where undiagnosed individuals are also documented. Prevention and early detection can effectively address these challenges.

OBJECTIVE

To improve healthcare services and assist in building predictive models to estimate the probability of diabetes in patients.

METHODS

A chart review, which was a retrospective cohort study, was conducted at the National Guard Health Affairs in Riyadh, Saudi Arabia. Data were collected from 5 hospitals using National Guard Health Affairs databases. We used 38 attributes of 21431 patients between 2015 and 2019. The following phases were performed: (1) data collection, (2) data preparation, (3) data mining and model building, and (4) model evaluation and validation. Subsequently, 6 algorithms were compared with and without the synthetic minority oversampling technique.

RESULTS

The highest performance was found in the Bayesian network, which had an area under the curve of 0.75 and 0.71.

CONCLUSION

Although the results were acceptable, they could be improved. In this context, missing data owing to technical issues played a major role in affecting the performance of our model. Nevertheless, the model could be used in prevention, health monitoring programs, and as an automated mass population screening tool without the need for extra costs compared to traditional methods.

Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations

BACKGROUND AND OBJECTIVES

Missing data is a ubiquitous problem in longitudinal studies due to the number of patients lost to follow-up. Kernel methods have enriched the machine learning field by successfully managing non-vectorial predictors, such as graphs, strings, and probability distributions, and have emerged as a promising tool for the analysis of complex data stemming from modern healthcare. This paper proposes a new set of kernel methods to handle missing data in the response variables. These methods will be applied to predict long-term changes in glycated haemoglobin (A1c), the primary biomarker used to diagnose and monitor the progression of diabetes mellitus, making emphasis on exploring the predictive potential of continuous glucose monitoring (CGM).

METHODS

We propose a new framework of non-linear kernel methods for testing statistical independence, selecting relevant predictors, and quantifying the uncertainty of the resultant predictive models. As a novelty in the clinical analysis, we used a distributional representation of CGM as a predictor and compared its performance with that of traditional diabetes biomarkers.

RESULTS

The results show that, after the incorporation of CGM information, predictive ability increases from R²=0.61 to R²=0.71. In addition, uncertainty analysis is useful for characterising some subpopulations where predictivity is worsened, and a more personalised clinical follow-up is advisable according to expected patient uncertainty in glucose values.

CONCLUSIONS

The proposed methods have proven to deal effectively with missing data. They also have the potential to improve the results of predictive tasks by including new complex objects as explanatory variables and modelling arbitrary dependence relations. The application of these methods to a longitudinal study of diabetes showed that the inclusion of a distributional representation of CGM data provides greater sensitivity in predicting five-year A1c changes than classical diabetes biomarkers and traditional CGM metrics.

Developing a questionnaire for diabetes mellitus type 2 risk effects and precondition factors – multivariate statistical paths

The primary purpose of the present study is to summarize and explain the results of a questionnaire about diabetes mellitus type 2 (DMT2) endangered individuals. The 275 participants (age between 21 and 76 years) answered 18 questions related to the possible danger of DMT2 disorder. Multivariate statistical methods – cluster analysis, factor and principal components analysis applied for the survey analysis. The final goal was to detect similarity patterns between the variables of interest (questions), to reveal hidden factors regulating the data structure and susceptibility to DMT2 among the participants or between them, to elucidate the health status of the different groups and the similarities within the groups. It was found that five hidden factors regulate the data structure, which are conditionally named “declined general health status”; “metabolic syndrome factor”; “smoking, alcohol abuse and stress factor”; “heredity and sex impact”; “healthy food” impact. The participants could be divided into four similarity patterns, each with probably different susceptibility to DMT2. Thus, the results of the questionnaire could be of use for prophylactic purposes.

Association between anthropometric indices and non-anthropometric components of the metabolic syndrome in Saudi adults

Context

Waist circumference (WC) is used in screening for metabolic syndrome (MetS) based on its association with cardiometabolic risk. This might apply differently in ethnically different populations. Associations with other measures are also unclear.

Objective

This work aimed to investigate the association between neck circumference (NC), WC, WC:hip circumference, WC:height (WC:Ht), NC:Ht, fat percentage, body mass index (BMI), conicity index, abdominal volume index, and weight-adjusted waist index with nonanthropometric components of MetS in nondiabetic Saudi adults.

Methods

This cross-sectional study took place in public health centers in Jeddah, comprising 1365 Saudi adults (772 men and 593 women) aged 18 years or older not previously diagnosed with diabetes.

Main outcome measures included

the presence of 2 or more nonanthropometric components of the MetS were used to define clinical metabolic abnormality (CMA). The predictive ability of studied anthropometric indices for CMA was determined using the area under receiver operating characteristics (AUC) curve and binary logistic regression.

Results

A total of 157 men and 83 women had CMA. NC and NC:Ht had the highest predictive ability for CMA in men (odds ratio [OR]_NC = 1.79, P < .001 and OR_NC:Ht = 1.68, P < .001; AUC_NC = 0.69 [95% CI, 0.64-0.74] and AUC_NC:Ht = 0.69 [95% CI, 0.64-0.73]). In women, WC had the highest predictive ability OR_WC = 1.81, P < .001; AUC_WC = 0.75 [95% CI, 0.69-0.80]).

Conclusion

Upper-body anthropometric indicators that were associated with subcutaneous fat had the highest predictive ability for CMA in men whereas abdominal obesity indictors had the best predictive ability in women, suggesting that fat distribution might contribute to CMA in a sex-specific manner.

Predictors of diabetes risk in urban and rural areas in Colombia

Background

Nutritional habits low in fruits and vegetables and sedentary lifestyle are associated with a higher risk of developing Type 2 Diabetes (T2D). However, it is important to assess differences between urban and rural areas. This study aimed to analyze the associations between the risk of developing T2D and setting in the Colombian north coast in 2017.

Methods

This cross-sectional study included 1,005 subjects. Data was collected by interviewing self-identified members of an urban community and a rural-indigenous population. The interaction terms were evaluated as well as the confounders. Then, adjusted binary logistic regressions were used to estimate the odds ratio (OR) and 95% Confidence Intervals (CI).

Results

subjects with a high risk of T2D are more likely to belong to the urban setting (OR = 1.908; 95%CI = 1.201–2.01) compared with those with lower T2D after adjusting for age, Body Mass Index (BMI), physical activity, history of high levels of glycemia, and diabetes in relatives.

Conclusions

Urban communities are more likely to have T2D compared with rural-indigenous populations. These populations have differences from the cultural context, including personal, and lifestyle factors.

Frequency of family meals and food consumption in families at high risk of type 2 diabetes: the Feel4Diabetes-study

A family meal is defined as a meal consumed together by the members of a family or by having ≥ 1 parent present during a meal. The frequency of family meals has been associated with healthier food intake patterns in both children and parents. This study aimed to investigate in families at high risk for developing type 2 diabetes across Europe the association (i) between family meals' frequency and food consumption and diet quality among parents and (ii) between family meals' frequency and children's food consumption. Moreover, the study aimed to elucidate the mediating effect of parental diet quality on the association between family meals' frequency and children's food consumption. Food consumption frequency and anthropometric were collected cross-sectionally from a representative sample of 1964 families from the European Feel4Diabetes-study. Regression and mediation analyses were applied by gender of children. Positive and significant associations were found between the frequency of family meals and parental food consumption (β = 0.84; 95% CI 0.57, 1.45) and diet quality (β = 0.30; 95% CI 0.19, 0.42). For children, more frequent family meals were significantly associated with healthier food consumption (boys, β = 0.172, p < 0.05; girls, β = 0.114, p < 0.01). A partial mediation effect of the parental diet quality was shown on the association between the frequency of family meals and the consumption of some selected food items (i.e., milk products and salty snacks) among boys and girls. The strongest mediation effect of parental diet quality was found on the association between the frequency of family breakfast and the consumption of salty snacks and milk and milk products (62.5% and 37.5%, respectively) among girls.

CONCLUSIONS

The frequency of family meals is positively associated with improved food consumption patterns (i.e., higher intake of fruits and vegetables and reduced consumption of sweets) in both parents and children. However, the association in children is partially mediated by parents' diet quality. The promotion of consuming meals together in the family could be a potentially effective strategy for interventions aiming to establish and maintain healthy food consumption patterns among children.

TRIAL REGISTRATION

The Feel4Diabetes-study is registered with the clinical trials registry (NCT02393872), http://clinicaltrials.gov , March 20, 2015.

WHAT IS KNOWN

• Parents' eating habits and diet quality play an important role in shaping dietary patterns in children • Family meals frequency is associated with improved diet quality of children in healthy population What is New: • Frequency of family meals was significantly associated with healthier food consumption among parents and children in families at high risk of type 2 diabetes in six European countries. • Parental diet quality mediates the association between family meals frequency and the consumption of some selected food items among children.

Comparison of the Finnish Diabetes Risk Score Model With the Metabolic Syndrome in a Shanghai Population

AIMS

This study aimed to compare the diagnostic accuracy of the metabolic syndrome with the Finnish Diabetes Risk Score (FINDRISC) to screen for type 2 diabetes mellitus (T2DM) in a Shanghai population.

METHODS

Participants aged 25-64 years were recruited from a Shanghai population from July 2019 to March 2020. Each participant underwent a standard metabolic work-up, including clinical examination with anthropometry. Glucose status was tested using hemoglobin A1c (HbAlc), 2h-post-load glucose (2hPG), and fasting blood glucose (FBG). The FINDRISC questionnaire and the metabolic syndrome were examined. The performance of the FINDRISC was assessed using the area under the receiver operating characteristic curve (AUC-ROC).

RESULTS

Of the 713 subjects, 9.1% were diagnosed with prediabetes, whereas 5.2% were diagnosed with T2DM. A total of 172 subjects had the metabolic syndrome. A higher FINDRISC score was positively associated with the prevalence of T2DM and the metabolic syndrome. Multivariable linear regression analysis demonstrated that the FINDRISC had a linear regression relationship with 2hPG levels (b'= 036, p < 0.0001). The AUC-ROC of the FINDRISC to identify subjects with T2DM among the total population was 0.708 (95% CI 0.639-0.776), the sensitivity was 44.6%, and the specificity was 90.1%, with 11 as the cut-off point. After adding FBG or 2hPG to the FINDRISC, the AUC-ROC among the total population significantly increased to 0.785 (95% CI 0.671-0.899) and 0.731 (95% CI 0.619-0.843), respectively, while the AUC-ROC among the female group increased to 0.858 (95% CI 0.753-0.964) and 0.823 (95% CI 0.730-0.916), respectively (p < 0.001). The AUC-ROC of the metabolic syndrome to identify subjects with T2DM among the total and female population was 0.805 (95% CI 0.767-0.844) and 0.830 (95% CI 0.788-0.872), respectively, with seven as the cut-off point.

CONCLUSIONS

The metabolic syndrome performed better than the FINDRISC model. The metabolic syndrome and the FINDRISC with FBG or 2hPG in a two-step screening model are both efficacious clinical practices for predicting T2DM in a Shanghai population.

Health-related quality of life (HRQoL) in a population at risk of type 2 diabetes: a cross-sectional study in two Latin American cities

Purpose

The purpose of this study was to describe the health-related quality of life (HRQoL) characteristics in a population at risk of developing type 2 diabetes in Barranquilla and Bogotá, Colombia.

Methods

A cross-sectional study with 1135 participants older than 30 years-of-age recruited in Bogotá D.C., and Barranquilla by cluster sampling in 2018 to 2019. The Finnish Diabetes Risk Score (FINDRISC) was used to detect participants at risk of developing type 2 diabetes (T2D). HRQoL was assessed using the EQ-5D-3L questionnaire. Unadjusted and adjusted logistic regression models were used to calculate odds ratios (OR) and their corresponding 95% confidence intervals CI).

Results

Moderate or extreme problems appeared more frequently in the dimensions of Pain/Discomfort (60.8%) and Anxiety/Depression (30.8%). The mean score of the EQ-VAS was 74.3 (± 17.3), significantly larger in the state of complete health (11111) compared with those with problems in more than one of the quality-of-life dimensions. Being female and living in Bogota D.C., were associated with greater odds of reporting problems in the Pain (OR 1.6; 95% CI 1.2–2.2) and Discomfort dimensions (OR 1.6; 95% CI 1.2–2.0) respectively and Anxiety/Depression (OR 1.9; 95% CI 1.3–2.7), (OR 9.1; 95% CI 6.6–12.4), respectively.

Conclusions

As living place and sex were associated with dimensions of Pain/Discomfort and Anxiety/Depression in the HRQoL in people at risk of T2D, greater attention should be paid to these determinants of HRQoL to design and reorient strategies with a territorial and gender perspective to achieve better health outcomes.

Plain English summary

Diabetes is one of the four non-communicable diseases with increasing prevalence in the world, which has made it a serious public health problem. In Colombia, in 2019 diabetes affected 8.4% of the Colombian adult population and more than one million Colombian adults of this age group have hidden or undetected diabetes. This disease is not only characterized by increased premature mortality, loss of productivity, and economic impact, but it also involves a deterioration in the quality of life of people with diabetes with their respective families. However, very Little is known about health-related quality of life (HRQoL) in a population at risk or with prediabetes. This study has evaluated the quality of life in patients at risk of diabetes and their behavior with some variables as sociodemographic, lifestyle, history, and established their difference in two territories of the Colombian Caribbean. The results of this study indicate that the HRQoL of people at risk of type 2 diabetes is affected by factors such as gender, city, dysglycemia, medication for hypertension and education level. Therefore, greater attention should be paid to these determinants of HRQL to design and implement strategies that reduce this risk of developing type 2 diabetes, prevent prediabetes and improve the quality of life in prediabetic or diabetic patients.

Bittersweet: How prices of sugar-rich foods contribute to the diet-related disease epidemic in Mexico

I provide new evidence on how price changes of nutritionally similar foods, such as those rich in sugar or fats, change obesity and diet-related diseases in the context of Mexico between 1996-2010. I merge a bar-code level price dataset with product-specific nutritional composition to two datasets with health outcomes: state-level administrative and nationally representative individual-level panel data. Exploiting within-city variation in prices using fixed effects models, I show that decreased prices of sugar-rich foods increase obesity, type 2 diabetes, and hypertension prevalence; yet the prices of foods rich in other nutrients do not. Health responses to price changes are the largest for those abdominally obese or at the highest risk for chronic disease. The association between prices of sugary foods and chronic disease is meaningful: I estimate that in Mexico, price reductions of sugary foods explain roughly 15 percent of the rise in obesity and diabetes during the 15-year study period.

Prediction of a 10-year risk of type 2 diabetes mellitus in the Turkish population: A cross-sectional study

According to the International Diabetes Federation, Turkey will be among the top 10 countries in the world with the highest prevalence of diabetes mellitus (DM) by 2045, with a speculated number of cases of 10.4 million.This study aimed to predict the 10-year risk of type 2 DM in a Turkish population, assess potential factors of the 10-year risk of DM, and assess the outcomes of Turkey's 2015 to 2020 program for DM.Individuals aged 20-64 years were categorized and stratified according to age (in ranges of 5 years), sex, and populations of family medicine centers to reflect the whole population. The Finnish Diabetes Risk Score, sociodemographic characteristics, body fat, muscle, bone ratio, blood pressure, and waist-to-height ratio were evaluated.We found that 9.5% (n = 71) of the population aged 20 to 64 years will have DM within the next 10 years. Low levels of education (odds ratio [OR]: 2.054; 95% confidence interval [CI]: 1.011-4.174), smoking cessation (OR: 2.636; 95% CI: 1.260-5.513), a waist-to-height ratio >0.5 (OR: 6.885; 95% CI: 2.301-20.602), body fat percentage (OR: 1.187; 95% CI: 1.130-1.247), high systolic blood pressure (OR: 1.025; 95% CI: 1.009-1.041), and alcohol consumption (beta-estimation: -0.690; OR: 0.501; 95% CI: 0.275-0.914) affect the 10-year risk of type 2 DM.Individuals at risk for DM can be easily identified using risk assessment tools in primary care; however, there is no active screening program in the healthcare system, and only proposals exist. In addition to screening, preventive measures should focus on raising awareness of DM, reducing body fat percentage and systolic blood pressure, and decreasing the waist-to-height ratio to <0.5.

The effect of a cluster-randomized controlled trial on lifestyle behaviors among families at risk for developing type 2 diabetes across Europe: the Feel4Diabetes-study

BACKGROUND

This study investigated the effect of the Feel4Diabetes-intervention, a 2-year multilevel intervention, on energy balance-related behaviors among European families at risk for developing type 2 diabetes. Intervention effects on self-reported physical activity, sedentary behavior and eating behaviors were investigated across and within the participating countries: Belgium, Finland, Greece, Spain, Hungary and Bulgaria.

METHODS

Families were recruited through schools, located in low socio-economic status areas. In total, 4484 families at risk for developing type 2 diabetes were selected using the FINDRISC-questionnaire. Parents' and children's energy balance-related behaviors data were collected by questionnaires at three time points (baseline, mid- and post intervention). Families assigned to the intervention group were invited to participate in a 2-year school-, community-, and family-based intervention to promote a healthier lifestyle, including counseling sessions (first intervention year) and text messages (second intervention year). Families assigned to the control group received standard care, including medical check-up results and recommendations and tips regarding a healthy lifestyle. To assess the intervention-effects, Mixed Models were conducted using the R-Package "lmer "with R v3.2.

RESULTS

Significant intervention effects were found on a certain number of families' lifestyle behaviors. Significant favorable intervention effects were detected on parents' water consumption and consumption of fruit and vegetables, and on children's consumption of sweets and moderate-to-vigorous physical activity. Analyses by country revealed significant favorable intervention effects on water consumption and on moderate-to-vigorous physical activity in Belgian parents and on fruit and vegetable consumption among Belgian children, on sweets consumption among Spanish parents and children, and on moderate-to-vigorous physical activity among Finnish children. Unfavorable intervention effects were found on the consumption of soft drinks and sugar-containing juices among Hungarian children and parents, while when examining the intervention effects for the overall population and per country, 10 from the 112 investigated outcome variables were improved in the intervention group compared to the control group (9%).

CONCLUSIONS

The Feel4Diabetes-intervention managed to improve a certain number of targeted lifestyle behaviors while the intervention was not effective on a large number of targeted lifestyle behaviors. The findings of the current study are encouraging, but further research is needed on how we can further improve effectiveness of lifestyle interventions to prevent type 2 diabetes in families at risk.

TRIAL REGISTRATION

The Feel4Diabetes-study is registered with the clinical trials registry http://clinicaltrials.gov , ID: 643708.

Prediabetes, undiagnosed diabetes and diabetes risk in Italy in 2017-2018: results from the first National screening campaign in community pharmacies

BACKGROUND

Effective policies for diabetes prevention remain urgent. We conducted a mass screening campaign in Italy to identify subjects potentially having undiagnosed diabetes, prediabetes or at diabetes risk.

METHODS

This cohort study was conducted in community pharmacies joining the unitary National federation of pharmacy holders (Federfarma) and participating in the 7-day screening campaign 'DiaDay' in 2017-2018. Capillary blood glucose levels and the risk of developing diabetes in 10 years (through the Finnish Diabetes Risk Score) were assessed.

RESULTS

145 651 volunteers aged ≥20 years without known diabetes were screened at 5671 community pharmacies in 2017 and 116 097 at 5112 in 2018. Overall, 3.6% had glucose values suggestive of undiagnosed diabetes; under fasting conditions (N = 94 076), 39.9% and 16.4% had values suggestive of prediabetes by the American Diabetes Association and the World Health Organization criteria, respectively. Of those without diabetes (N = 252 440), 19.2% had scores compatible with a high risk (1:3) and 2.7% with a very high risk (1:2) of developing the disease; in the prediabetes group, the risk rose with higher impaired fasting glucose values.

CONCLUSIONS

DiaDay, the first National screening campaign, highlights the need to screen the population and the key role of the pharmacist both in screening activities and education promotion.

Metabolic Age, an Index Based on Basal Metabolic Rate, Can Predict Individuals That are High Risk of Developing Metabolic Syndrome

INTRODUCTION

Every 10 years, an adult's basal metabolic rate (BMR), independent of their BMI, decreases 1-2% due to skeletal muscle loss, thus decreasing an adult's energy requirement and promoting obesity. Increased obesity augments the risk of developing Metabolic Syndrome (MetS); however, an adult's healthy lifestyle, which increases BMR, can mitigate MetS development. To compare different BMRs for certain ages, Metabolic age (Met-age) was developed.

AIM

To assess the association between Met-age and MetS and to determine if Met-age is an indicator of high-risk individuals for MetS.

METHODS

Four hundred thirty-five attendees at 2 clinics agreed to participate and gave signed informed consent. MetS risk was assessed by the ESF-I questionnaire. Met-age was determined using a TANITA bio-analyzer. Strengthen of association was determined by calculating Spearman's rho and predictability was evaluated by the area-under-a-receiver-operating characteristic curve (AUC). Difference-in-age (DIA) = [chronological age - Met-age].

RESULTS

There was a difference between the low-risk (n = 155) and the high-risk (n = 280) groups' Met-age (37.8±16.7 v. 62.9±17.3) and DIA (1.3±17.4 v. - 10.5±20.8, p < 0.001). There was a positive correlation between the ESF-I questionnaire and Met-age (rho = - 0.624, p < 0.001) and a negative correlation for DIA (rho = - 0.358, p < 0.001). Met-age was strongly predictive (AUC = 0.84, 95% CI 0.80-0.88), suggesting a 45.5 years cutoff (sensitivity = 83.2%, specificity = 72.3%). DIA was a good predictor (AUC = 0.68, 95% CI 0.63-0.74) with a - 11.5 years cutoff (sensitivity = 52.5%, specificity = 82.8%).

CONCLUSION

Met-age highly associated with and is an indicator of high-risk individuals for MetS. This would suggest that increases in Met-age are associated with augmented MetS severity, independent of the individual's chronological age.

Prevalence of diabetes and pre-diabetes in Greece. Results of the First National Survey of Morbidity and Risk Factors (EMENO) study

AIMS

To report the results of the first national Health Examination Survey (HES) on the prevalence of diabetes, its pharmacologic treatment and level of control, as well as pre-diabetes in Greece.

METHODS

Data were derived from the National Survey of Morbidity and Risk Factors (EMENO), in a randomly selected, representative sample of the adult Greek population. Sampling weights were applied to adjust for study design and post-stratification weights to match sample age/sex distribution to the population. Non-response was adjusted by inverse probability weighting. Weighted prevalence estimates are provided.

RESULTS

A total of 4393 persons with HbA1c and/or fasting plasma glucose measurements were included. Total diabetes prevalence was 11.9% (95% CI: 10.9-12.9), known diabetes 10.4% (9.5-11.4), and unknown 1.5% (1.1-1.9), with considerable increase in older age groups and no difference between genders. Pre-diabetes prevalence was 12.4% (11.4-13.6). The majority of persons with known diabetes were receiving metformin. Of those with known diabetes (and measured HbA1c), 70.9% were well controlled (HbA1c <7.0%).

CONCLUSIONS

This first representative national HES showed high prevalence of diabetes in Greece, with low prevalence of unknown diabetes. Pre-diabetes prevalence is also substantial. These results will hopefully enable national authorities develop tailored and efficient strategies for disease prevention and management.

The Finnish Diabetes Risk Score (FINDRISC), incident diabetes and low-grade inflammation

AIMS

The FINDRISC was created to predict the development of type 2 diabetes mellitus (T2DM). Since T2DM associates with inflammation we evaluated if the FINDRISC could predict either current or incident T2DM, and elevated high sensitivity C-reactive protein (hs-CRP).

METHODS

41,880 people (age 41.9 ± 9.7 years; 31% female) evaluated between 2008 and 2016 were included. First, the cross-sectional association between the FINDRISC with presence of either T2DM or hs-CRP ≥ 2.0 mg/L was tested. After a 5 ± 3 years follow-up we tested the score predictive value for incident T2DM and inflammation in respectively 10,559 individuals without diabetes and in a subset of 2,816 individuals having no elevated hs-CRP at baseline.

RESULTS

In the cross sectional analysis the FINDRISC was associated with both T2DM (OR 1.24, 95% CI: 1.23-1.26, P < 0.001) and inflammation (OR 1.10, 95% CI: 1.09-1.11, P < 0.001) per FINDRISC unit, as well as in longitudinal analyses (OR 1.17, 95% CI: 1.14-1.20, P < 0.001; and OR 1.04, 95% CI: 1.02-1.07, P < 0.001; respectively, per FINDRISC unit). The C-statistic for incident T2DM and inflammation was 0.79 (95% CI 0.77-0.82) and 0.55 (95% CI 0.53-0.58), respectively.

CONCLUSION

The FINDRISC shows good discrimination for incident T2DM but less for inflammation.

Prediabetes/diabetes screening strategy at the periodontal clinic

Objective

The aim of the study was to propose an efficient chairside clinical strategy for the identification of undiagnosed hyperglycaemia in periodontal clinics.

Material and methods

Α chairside system was used for assessment of glycated hemoglobin 1c (HbA1c) and active Matrix Metalloproteinase‐8 levels (aMMP‐8) were analyzed by immunotest in patients (n = 150) who fulfilled the criteria for screening of the Centers for Disease Control and Prevention. Full‐mouth periodontal parameters were assessed and various data such as Body Mass Index (BMI), smoking and education were recorded.

Results

Thirty‐one patients out of 150 tested were found with unknown hyperglycaemia (20.7%). Regarding sex, education, parent with diabetes, normal BMI, smoking, age ≥45 years and prior testing for diabetes, no differences were observed between subjects displaying HbA1c < 5.7 and ≥5.7% (Pearson's Chi‐square test, p > .05). Subgroups differed regarding BMI (kg/m²), tooth count, percentages of 4 and 5 mm pockets (Mann–Whitney and z‐test, p < .05). The diagnostic performance for HbA1c ≥5.7 was tested by Receiving Operator Characteristic curves and Areas Under the Curve (AUC) for the following: age ≥ 45 years and BMI (AUC 0.651, p = .010), the above and aMMP‐8 (AUC 0.660, p = .006), age ≥ 45 years, BMI and Stage of Periodontitis (AUC 0.711, p < .001) and age ≥ 45 years, BMI, aMMP‐8 and stage of periodontitis (AUC 0.713, p < .001).

Conclusions

Findings of the study suggest that the combination of stage of periodontitis, increasing age, BMI and aMMP‐8, without chairside HbA1c assessment appears to be a viable screening strategy for referring dental patients for testing for prediabetes/diabetes.

The Association Between Dietary Habits and Other Lifestyle Indicators and Dysglycemia in Saudi Adults Free of Previous Diagnosis of Diabetes

Objective:

Study the association of dietary habits and other indicators of lifestyle with dysglycemia in Saudi adults.

Methods:

In a cross-sectional design, data were obtained from 1403 Saudi adults (⩾20 years), not previously diagnosed with diabetes. Demographics, lifestyle variables and dietary habits were obtained using a predesigned questionnaire. Fasting plasma glucose, glycated hemoglobin and 1-hour oral glucose tolerance test were used to identify dysglycemia. Regression analysis was performed to determine the associations of dietary factors and other indicators of lifestyle with dysglycemia.

Results:

A total 1075 adults (596 men, and 479 women) had normoglycemia, and 328 (195 men, and 133 women) had dysglycemia. Following adjustment for age, BMI and waist circumference, in men the weekly intake of 5 portions or more of red meat and Turkish coffee were associated with decreased odds of having dysglycemia odds ratio (OR) 0.444 (95% CI: 0.223, 0.881; P = .02) and 0.387 (95% CI: 0.202, 0.74; P = .004), respectively. In women, the intake of fresh juice 1 to 4 portions per week and 5 portions or more were associated with OR 0.603 (95% CI: 0.369, 0.985; P = .043) and OR 0.511 (95% CI: 0.279, 0.935; P = .029) decreased odds of having dysglycemia, respectively compared with women who did not drink fresh juice. The intake of 5 times or more per week of hibiscus drink was associated with increased odds of having dysglycemia, OR 5.551 (95% CI: 1.576, 19.55, P = .008) compared with women not using such a drink. Other lifestyle factors were not associated with dysglycemia.

Conclusion:

Dietary practices by studied Saudis have some impact on risk of dysglycemia, with obvious sex differences.

Chronic Non-Communicable Disease Risk Calculators - An Overview, Part II

The aim of this review was to identify the different risk assessment tools that stratify the individual's risk of four of the eight leading causes of death: stroke, ischaemic heart diseases, type 2 diabetes mellitus, and dementia. It follows part I, which summarized the risk assessment tools for the other four leading causes of death (breast cancer, lung cancer, colorectal cancer and osteoporosis). As in part I, the different tools were compared by their variables and validation criteria and an overview table was designed for each illness. The tables facilitate the choice of the adequate risk assessment tool for the individual patient in order to estimate the risk of developing an NCD. This could guide treating physicians in the decision-making process about completing diagnostics for early detection and, if necessary, treatment, such that the patient's quality of life can be preserved and costs to the health care system are minimal.

Prevalence of people at risk of developing type 2 diabetes mellitus and the involvement of community pharmacies in a national screening campaign: a pioneer action in Brazil

BACKGROUND

Brazil is one of top 10 countries with the highest number of people with diabetes mellitus (DM), affecting 16.8 million peoples. It is estimated that 7.7 million people (20-79 years) in the country have not yet been diagnosed, representing an under-diagnosis rate of 46.0%. Herein we aimed to screen people for high blood glucose or risk for developing type 2 DM (T2DM) through community pharmacies in Brazil.

METHODS

A cross-sectional study was carried out in November 2018, involving 977 pharmacists from 345 municipalities in Brazil. The study evaluated people between 20 and 79 years old without a previous diagnosis of DM. Glycemia was considered high when its value was ≥ 100 mg/dL fasting and ≥ 140 mg/dL in a casual feeding state. The FINDRISC (Finnish Diabetes Risk Score) was used to estimate the risk for developing T2DM. The prevalence of high blood glucose was estimated and the associated factors were obtained using Poisson's multivariate analysis with robust variance.

RESULTS

During the national screening campaign, 17,580 people were tested with the majority of the consultations (78.2%) being carried out in private pharmacies. The population was composed mainly of women (59.5%) and people aged between 20 and 45 years (47.9%). The frequency of participants with high blood glucose was 18.4% (95% CI 17.9-19.0). Considering the FINDRISC, 22.7% of people had a high or very high risk for T2DM. The risk factors associated with high blood glucose were: Body Mass Index > 25 kg/m2, abdominal circumference > 94 cm for men and > 80 cm for women; education level below 15 years of study, no daily intake of vegetables and fruits; previous diagnosis of arterial hypertension; history of high blood glucose and family history of DM.

CONCLUSIONS

This is the largest screening study that evaluated the frequency of high blood glucose and its associated factors in a population without a previous diagnosis ever performed in community pharmacies in Brazil. These results may help to improve public health policies and reinforce the role of pharmacists in screening and education actions aimed at this undiagnosed population in a continent-size country such as Brazil.

Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care

AIMS

To evaluate the performance of FINDRISC and ModAsian FINDRISC for the screening of undiagnosed diabetes and dysglycaemia in primary care. To compare the performance of FINDRISC with the recommendations of the American Diabetes Association (ADA) and US Preventive Services Task Force (USPSTF) guidelines.

METHODS

This cross-sectional study was carried out on 293 patients without a prior history of diabetes at a primary care clinic in Malaysia. Questions on body mass index and waist circumference were modified based on the Asian standard in ModAsian FINDRISC. Haemoglobin A1c of ≥6.5% (48 mmol/mol) was used to diagnose diabetes. Areas under the receiver operating curve (ROC-AUC) for FINDRISC and ModAsian FINDRISC were analyzed.

RESULTS

The prevalence of undiagnosed diabetes was 7.5% and prediabetes was 32.8%. The ROC-AUC of FINDRISC was 0.76 (undiagnosed diabetes) and 0.79 (dysglycaemia). There was no statistical difference between FINDRISC and ModAsian FINDRISC. The recommended optimal FINDRISC cut-off point for undiagnosed diabetes was ≥11 (Sensitivity 86.4%, Specificity 48.7%). FINDRISC ≥11 point has higher sensitivity compared to USPSTF criteria (72.7%) and higher specificity compared to the ADA (9.6%).

CONCLUSIONS

FINDRISC is a useful diabetes screening tool to identify those at risk of diabetes in primary care in Malaysia.

Metabolic Syndrome and Diabetes Risk Among Young Adult Students in the Health Sciences from Kathmandu, Nepal

Background

The widespread dissemination of unhealthy dietary habits, childhood-teenage obesity, and sedentary lifestyle in young adults has paved the way for public health burden metabolic syndrome and early onset of type 2 diabetes mellitus. The aim of this study was to assess the prevalence and risk factors for metabolic syndrome and diabetes among young adult students.

Methods

This cross-sectional study was conducted among students of age group (18 to 25 years) studying at Manmohan Memorial Institute of Health Sciences and Central Institute of Science and Technology. The diabetes risk score of each individual was calculated by the Finnish Diabetes Risk Score (FINDRISC tool). Independent risk factors for diabetes and metabolic syndrome were measured by multivariable logistic regression analysis. The p-value of <0.05 was considered statistically significant in this study.

Results

A total of 825 students were recruited and 739 (89.6%) students completed the study with all the fulfilled criteria. The metabolic syndrome (Harmonized Joint Scientific Statement (HJSS) criteria) was present in 7.1%, and the most prevalent defining component was low HDL-C (78%); 74.8% of students were under low risk, 22.18% were at slightly elevated risk, 2.02% were at moderate risk, and 1.01% were at high risk of diabetes. The cardiometabolic risk factors like BMI, TC, and LDL-C were higher at a significant level (p<0.001) with an increased diabetes risk score. Independent lifestyle risk factor for metabolic syndrome was current smoking (AOR, 4.49, 95% CI 1.38–14.62) whereas, an independent lifestyle risk factor for diabetes was low adherence to physical exercise (AOR, 4.81, 95% CI, 2.90–7.99).

Conclusion

Metabolic syndrome is present, although in low numbers in young adults putting them at risk to develop diabetes in the near future. Early assessment of metabolic syndrome and diabetes risk in young may provide insights for preventive and control plans for risk population.

The Association between Dyslipidemia, Dietary Habits and Other Lifestyle Indicators among Non-Diabetic Attendees of Primary Health Care Centers in Jeddah, Saudi Arabia

Diet and other lifestyle habits have been reported to contribute to the development of dyslipidemia in various populations. Therefore, this study investigated the association between dyslipidemia and dietary and other lifestyle practices among Saudi adults. Data were collected from adults (≥20 years) not previously diagnosed with diabetes in a cross-sectional design. Demographic, anthropometric, and clinical characteristics, as well as lifestyle and dietary habits were recorded using a predesigned questionnaire. Fasting blood samples were drawn to estimate the serum lipid profile. Out of 1385 people, 858 (62%) (491 men, 367 women) had dyslipidemia. After regression analysis to adjust for age, body mass index, and waist circumference, an intake of ≥5 cups/week of Turkish coffee, or carbonated drinks was associated with increased risk of dyslipidemia in men (OR (95% CI), 2.74 (1.53, 4.89) p = 0.001, and 1.53 (1.04, 2.26) p = 0.03 respectively), while the same intake of American coffee had a protective effect (0.53 (0.30, 0.92) p = 0.025). Sleep duration <6 h, and smoking were also associated with increased risk in men (1.573 (1.14, 2.18) p = 0.006, and 1.41 (1.00, 1.99) p = 0.043 respectively). In women, an increased intake of fresh vegetables was associated with increased risk (2.07 (1.09, 3.94) p = 0.026), which could be attributed to added salad dressing. Thus, there are sex differences in response to dietary and lifestyle practices.

Diabetes mellitus risk among Jordanians in a dental setting: a cross-sectional study

BACKGROUND

Dental offices can be useful to screen and identify patients at risk of developing diabetes mellitus (DM) using risk prediction tools. The Finnish Diabetes Risk Score (FINDRISC) is a validated, questionnaire-based tool used to predict the 10-year risk of developing type II DM.

OBJECTIVES

To determine the 10-year DM risk among Jordanians using the FINDRISC questionnaire in a dental setting.

MATERIALS AND METHODS

Participants attending two university dental teaching centres between March 2017 and February 2018 were interviewed using an Arabic translated version of the FINDRISC questionnaire. Anthropometrics including weight, height, waist circumference (WC) and body mass index (BMI) were recorded. Random capillary blood glucose level was measured for each participant. Statistical analysis was done using Chi-square and independent t-tests.

RESULTS

A total of 1,247 (436 males and 811 females) participants were included. As defined by BMI, 1,012 (81.2%) participants were either overweight or obese. Abdominal adiposity as determined by WC was seen in 738 (59.2%) participants. The mean (± SD) FINDRISC score for females (11.3 ± 4.3) was significantly higher (P = 0.001) than males (10.4 ± 4.9). After age adjustment, more females were in the high-risk categories (FINDRISC ≥ 15) compared with males. This trend was seen among all age groups, but was statistically significant in the older age groups; 55-64 years (P = 0.037) and ≥ 65 years (P = 0.004).

CONCLUSION

In a developing Middle Eastern country such as Jordan, almost half of Jordanians attending university dental clinics are at a moderate to high risk of developing type II DM in 10 years. The risk of DM should be considered in dental patients, particularly older females.

Dysglycemia risk score in Saudi Arabia: A tool to identify people at high future risk of developing type 2 diabetes

AIMS/INTRODUCTION

To develop a non-invasive risk score to identify Saudis having prediabetes or undiagnosed type 2 diabetes.

METHODS

Adult Saudis without diabetes were recruited randomly using a stratified two-stage cluster sampling method. Demographic, dietary, lifestyle variables, personal and family medical history were collected using a questionnaire. Blood pressure and anthropometric measurements were taken. Body mass index was calculated. The 1-h oral glucose tolerance test was carried out. Glycated hemoglobin, fasting and 1-h plasma glucose were measured, and obtained values were used to define prediabetes and type 2 diabetes (dysglycemia). Logistic regression models were used for assessing the association between various factors and dysglycemia, and Hosmer-Lemeshow summary statistics were used to assess the goodness-of-fit.

RESULTS

A total of 791 men and 612 women were included, of whom 69 were found to have diabetes, and 259 had prediabetes. The prevalence of dysglycemia was 23%, increasing with age, reaching 71% in adults aged ≥65 years. In univariate analysis age, body mass index, waist circumference, use of antihypertensive medication, history of hyperglycemia, low physical activity, short sleep and family history of diabetes were statistically significant. The final model for the Saudi Diabetes Risk Score constituted sex, age, waist circumference, history of hyperglycemia and family history of diabetes, with the score ranging from 0 to 15. Its fit based on assessment using the receiver operating characteristic curve was good, with an area under the curve of 0.76 (95% confidence interval 0.73-0.79). The proposed cut-point for dysglycemia is 5 or 6, with sensitivity and specificity being approximately 0.7.

CONCLUSION

The Saudi Diabetes Risk Score is a simple tool that can effectively distinguish Saudis at high risk of dysglycemia.

Translation, cross-cultural adaptation and validation of the Finnish Diabetes Risk Score (FINDRISC) for use in Brazilian Portuguese: questionnaire validity study

BACKGROUND

The Finnish Diabetes Risk Score (FINDRISC) is a questionnaire that was developed by Finnish researchers to track the risk of diabetes.

OBJECTIVE

To translate, cross-culturally adapt and validate the FINDRISC for use in Brazilian Portuguese.

DESIGN AND SETTING

Questionnaire validity study conducted at a private university.

METHODS

The Brazilian version of the FINDRISC was developed through the processes of translation, back-translation, committee review and pre-testing. Test-retest reliability was measured using the intraclass correlation coefficient (ICC), kappa coefficient, standard error of measurement (SEM) and minimum detectable change (MDC). Internal consistency was measured using Cronbach's alpha. For construct validity, the total score of the FINDRISC was correlated with the Diabetes Knowledge Scale (DKN-A) and Diabetes Mellitus Risk Questionnaire (QRDM). Ceiling and floor effects were also evaluated in the present study.

RESULTS

For construct validity and floor and ceiling effect measurements, a total sample of 107 participants was used. For reliability, a subsample of 51 participants out of the total sample was used. We identified adequate values for reliability (kappa ≥ 0.79 and ICC = 0.98) and internal consistency (Cronbach's alpha = 0.84). Regarding the error inherent in the FINDRISC, we found SEM = 8.02% and MDC = 22.44%. There were significant correlations between the FINDRISC and the QRDM (r = 0.686) and DKN-A (r = -0.216). No ceiling or floor effects were found.

CONCLUSION

The Brazilian version of the FINDRISC has adequate psychometric properties that are in accordance with the best international recommendations.

Development and Validation of Two Self-Reported Tools for Insulin Resistance and Hypertension Risk Assessment in A European Cohort: The Feel4Diabetes-Study

Early identification of type 2 diabetes mellitus (T2DM) and hypertension (HTN) risk may improve prevention and promote public health. Implementation of self-reported scores for risk assessment provides an alternative cost-effective tool. The study aimed to develop and validate two easy-to-apply screening tools identifying high-risk individuals for insulin resistance (IR) and HTN in a European cohort. Sociodemographic, lifestyle, anthropometric and clinical data obtained from 1581 and 1350 adults (baseline data from the Feel4Diabetes-study) were used for the European IR and the European HTN risk assessment index respectively. Body mass index, waist circumference, sex, age, breakfast consumption, alcohol, legumes and sugary drinks intake, physical activity and sedentary behavior were significantly correlated with Homeostatic Model Assessment of IR (HOMA-IR) and/or HTN and incorporated in the two models. For the IR index, the Area Under the Curve (AUC), sensitivity and specificity for identifying individuals above the 75th and 95th of HOMA-IR percentiles were 0.768 (95%CI: 0.721-0.815), 0.720 and 0.691 and 0.828 (95%CI: 0.766-0.890), 0.696 and 0.778 respectively. For the HTN index, the AUC, sensitivity and specificity were 0.778 (95%CI: 0.680-0.876), 0.667 and 0.797. The developed risk assessment tools are easy-to-apply, valid, and low-cost, identifying European adults at high risk for developing T2DM or having HTN.

Methodological procedures followed in a school-and community-based intervention to prevent type 2 diabetes in vulnerable families across Europe: the Feel4Diabetes-study

Feel4Diabetes (standing for: Families across Europe following a hEalthy Lifestyle for Diabetes prevention, http://feel4diabetes-study.eu/) is a school and community based intervention program, aiming to prevent type 2 diabetes (T2D) among families from vulnerable population groups, in six European countries, by promoting healthy lifestyle. In the current issue of BMC Endocrine Disorders, three reviews and three papers providing a detailed description of the methodology used to obtain measurements related to the trial conduction, as well as two papers using original data collected in the Feel4Diabetes-study are presented.

A Deep Learning Model for Estimation of Patients with Undiagnosed Diabetes

A screening model for undiagnosed diabetes mellitus (DM) is important for early medical care. Insufficient research has been carried out developing a screening model for undiagnosed DM using machine learning techniques. Thus, the primary objective of this study was to develop a screening model for patients with undiagnosed DM using a deep neural network. We conducted a cross-sectional study using data from the Korean National Health and Nutrition Examination Survey (KNHANES) 2013–2016. A total of 11,456 participants were selected, excluding those with diagnosed DM, an age < 20 years, or missing data. KNHANES 2013–2015 was used as a training dataset and analyzed to develop a deep learning model (DLM) for undiagnosed DM. The DLM was evaluated with 4444 participants who were surveyed in the 2016 KNHANES. The DLM was constructed using seven non-invasive variables (NIV): age, waist circumference, body mass index, gender, smoking status, hypertension, and family history of diabetes. The model showed an appropriate performance (area under curve (AUC): 80.11) compared with existing previous screening models. The DLM developed in this study for patients with undiagnosed diabetes could contribute to early medical care.