Predicting type 2 diabetes mellitus: a comparison between the FINDRISC score and the metabolic syndrome

Assessment of 1-Hour Postload Plasma Glucose, the Metabolic Syndrome, and the Finish Diabetes Risk Score in the Prediction of Type 2 Diabetes

OBJECTIVE

To compare the 1-hour postload glucose (1h-PG) value of an oral glucose tolerance test (OGTT) with the metabolic syndrome (MetS) and the Finish Diabetes Risk Score (FINDRISC) in patients with impaired fasting glucose (IFG) to predict type 2 diabetes mellitus (T2DM).

METHODS

A cohort study was conducted in patients at a general hospital in Lima, Perú. An OGTT was performed in subjects with IFG who were followed-up for 7 years for T2DM development. The exposure variables were 1h-PG ≥ 155 mg/dL, MetS, and a FINDRISC ≥ 13 points, and the outcome was the presence of T2DM. The relative risk, confidence interval, and area under the curve (AUROC) were also estimated.

RESULTS

Among 324 subjects with IFG, 218 completed the 7-year follow-up. The mean age was 56.2 ± 11.5 years, 64.0% were woman, and 63.8% were overweight/obese. Of these, 36.8% had 1h-PG ≥ 155 mg/dL and normal glucose tolerance, 66.8% had MetS, and 64.5% had FINDRISC ≥ 13 points. After 7 years, 21.1% of participants developed T2DM, with 68.8% of them who had 1h-PG ≥ 155 mg/dL (P < .001), 62.2% had MetS (P = .013), and 67.9% had FINDRISC ≥ 13 (P = .68). After adjusting by age, sex, and body mass index, the relative risk was 3.52 (1.64-7.54; 95% CI), 1.81 (0.96-3.38; 95% CI), and 1.17 (0.51-2.70; 95% CI) for each exposure variable, respectively. Also, the AUROC was 0.72 (0.60-0.83), 0.63 (0.51-0.75), and 0.51 (0.38-0.63) (P = .01), respectively.

CONCLUSION

By performing an OGTT in patients with IFG, an 1h-PG ≥ 155 mg/dL value may be helpful to predict T2DM at 7 years better than the use of MetS or the FINDRISC.

External validation of three diabetes prediction scores in a Spanish cohort: does adding high risk for depression improve the validation of the FINDRISC score (FINDRISC-MOOD)?

OBJECTIVES

To evaluate the external validity of the FINDRISC, DESIR and ADA risk scores for the prediction of diabetes in a Spanish population aged >45 years and to test the possible improvement of FINDRISC by adding a new variable of high risk of depression when Patient Health Questionnaire-9 (PHQ-9) questionnaire score ≥10 (FINDRISC-MOOD).

DESIGN

Prospective population-based cohort study.

SETTING

10 primary healthcare centres in the north of the city of Madrid (Spain).

PARTICIPANTS

A total of 1242 participants without a history of diabetes and with 2-hour oral glucose tolerance test (OGTT) plasma glucose <200 mg/dL (<11.1 mmol/L) were followed up for 7.3 years (median) using their electronic health records (EHRs) and telephone contact.

PRIMARY AND SECONDARY OUTCOME MEASURES

Diabetes risk scores (FINDRISC, DESIR, ADA), PHQ-9 questionnaire and 2-hour-OGTT were measured at baseline. Incident diabetes was defined as treatment for diabetes, fasting plasma glucose ≥126 mg/dL (≥7.0 mmol/L), new EHR diagnosis or self-reported diagnosis. External validation was performed according to optimal cut-off, sensitivity, specificity and Youden Index. Comparison between diabetes risk scores, including FINDRISC-MOOD (original FINDRISC score plus five points if PHQ-9 ≥10), was measured by area under the receiver operating characteristic curve (AUROC).

RESULTS

During follow-up, 104 (8.4%; 95% CI, 6.8 to 9.9) participants developed diabetes and 185 had a PHQ-9 score ≥10. The AUROC values were 0.70 (95% CI, 0.67 to 0.72) for FINDRISC-MOOD and 0.68 (95% CI, 0.65 to 0.71) for the original FINDRISC. The AUROCs for DESIR and ADA were 0.66 (95% CI, 0.63 to 0.68) and 0.66 (95% CI, 0.63 to 0.69), respectively. There were no significant differences in AUROC between FINDRISC-MOOD and the other scores.

CONCLUSIONS

The results of FINDRISC-MOOD were like those of the other risk scores and do not allow it to be recommended for clinical use.

Evaluate the Effects of Different Types of Preoperative Restricted Calorie Diets on Weight, Body Mass Index, Operation Time and Hospital Stay in Patients Undergoing Bariatric Surgery: a Systematic Review and Meta Analysis Study

Previous studies investigated low-calorie diets (LCD), very-low-calorie diets (VLCD), and very-low-calorie ketogenic diets (VLCKD) in relation to weight loss and outcomes for bariatric surgery patients. However, the overall effects of these diets on various outcomes remain unclear. This study aimed to assess the impact of preoperative restricted calorie diets on weight, body mass index (BMI), operation time (OT), and hospital stay (HS) in bariatric surgery patients. Seventeen articles were analyzed, revealing the highest weight loss (-8.62) and BMI reduction (-5.75) with VLCKD. Due to insufficient data, the impact of these diets on OT and HS could not be determined. Further interventional studies are required to determine the ideal preoperative diet that achieves optimal weight loss, patient compliance, tolerance, acceptance, and surgical outcomes.

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.

Association between the Finnish Diabetes Risk Score and cancer in middle-aged and older adults: Involvement of inflammation

BACKGROUND

Diabetes is associated with increased risk of common cancers. However, evidence of cancer risk in individuals with different diabetes risk is still scarce, and the underlying mechanism remains unknown. Therefore, we aimed to evaluate the relationship between the Finnish Diabetes Risk Score (FINDRISC) and risks of cancer incidence and mortality in a prospective study, and to explore whether low-grade inflammation partially mediated the association.

METHODS

A total of 330,384 participants aged 37 to 73 at baseline from the UK Biobank database was included in this study. The Cox proportional hazards model was used to examine the relationship of the FINDRISC and low-grade inflammation with risks of cancer incidence and mortality. Then, we estimated the contribution of higher FINDRISC to risks of overall and site-specific cancers. In addition, the role of low-grade inflammation in the association between FINDRISC and cancer risks was investigated through mediation analysis.

RESULTS

The increased FINDRISC was dose-dependently associated with higher incidence and mortality risks of overall cancer and an overwhelming majority of site-specific cancers. The higher FINDRISC was a strong contributor to incidence of eighteen site-specific cancers and mortality of fourteen site-specific cancers, with a population-attributable risk of 8.1 %-39.1 %, 14.2 %-39.7 %, respectively. Additionally, low-grade inflammation mainly mediated the association between the FINDRISC and risks of incidence and mortality of overall cancer, colorectal cancer, etc. CONCLUSIONS: Our findings highlighted the higher FINDRISC as critical risk factors of cancer incidence and mortality, partially mediated by low-grade inflammation. Individuals with increased risk of diabetes are also needed to be concerned about cancer prevention.

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.

Non-invasive type 2 diabetes risk scores do not identify diabetes when the cause is β-cell failure: The Africans in America study

Background

Emerging data suggests that in sub-Saharan Africa β-cell-failure in the absence of obesity is a frequent cause of type 2 diabetes (diabetes). Traditional diabetes risk scores assume that obesity-linked insulin resistance is the primary cause of diabetes. Hence, it is unknown whether diabetes risk scores detect undiagnosed diabetes when the cause is β-cell-failure.

Aims

In 528 African-born Blacks living in the United States [age 38 ± 10 (Mean ± SE); 64% male; BMI 28 ± 5 kg/m²] we determined the: (1) prevalence of previously undiagnosed diabetes, (2) prevalence of diabetes due to β-cell-failure vs. insulin resistance; and (3) the ability of six diabetes risk scores [Cambridge, Finnish Diabetes Risk Score (FINDRISC), Kuwaiti, Omani, Rotterdam, and SUNSET] to detect previously undiagnosed diabetes due to either β-cell-failure or insulin resistance.

Methods

Diabetes was diagnosed by glucose criteria of the OGTT and/or HbA1c ≥ 6.5%. Insulin resistance was defined by the lowest quartile of the Matsuda index (≤ 2.04). Diabetes due to β-cell-failure required diagnosis of diabetes in the absence of insulin resistance. Demographics, body mass index (BMI), waist circumference, visceral adipose tissue (VAT), family medical history, smoking status, blood pressure, antihypertensive medication, and blood lipid profiles were obtained. Area under the Receiver Operator Characteristics Curve (AROC) estimated sensitivity and specificity of each continuous score. AROC criteria were: Outstanding: >0.90; Excellent: 0.80-0.89; Acceptable: 0.70-0.79; Poor: 0.50-0.69; and No Discrimination: 0.50.

Results

Prevalence of diabetes was 9% (46/528). Of the diabetes cases, β-cell-failure occurred in 43% (20/46) and insulin resistance in 57% (26/46). The β-cell-failure group had lower BMI (27 ± 4 vs. 31 ± 5 kg/m² P < 0.001), lower waist circumference (91 ± 10 vs. 101 ± 10cm P < 0.001) and lower VAT (119 ± 65 vs. 183 ± 63 cm³, P < 0.001). Scores had indiscriminate or poor detection of diabetes due to β-cell-failure (FINDRISC AROC = 0.49 to Cambridge AROC = 0.62). Scores showed poor to excellent detection of diabetes due to insulin resistance, (Cambridge AROC = 0.69, to Kuwaiti AROC = 0.81).

Conclusions

At a prevalence of 43%, β-cell-failure accounted for nearly half of the cases of diabetes. All six diabetes risk scores failed to detect previously undiagnosed diabetes due to β-cell-failure while effectively identifying diabetes when the etiology was insulin resistance. Diabetes risk scores which correctly classify diabetes due to β-cell-failure are urgently needed.

Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards

Background

Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation. Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models.

Methods

In this study, we analyzed data from 44,709 nondiabetic UK Biobank participants aged 40-69, predicting the risk of T2D onset within a selected time frame (mean of 7.3 years with an SD of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one nonlaboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes subcohorts, and compared the results to the results of the general cohort. We established the nonlaboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip ratio, and body mass index. For the laboratory model, we used age and sex together with four common blood tests: high-density lipoprotein (HDL), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

Results

The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77-0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5-66). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85-0.90) and a deciles' OR of ×48 (95% CI 12-109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4-7%); 3% (2-4%); 10% (8-12%); and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74-0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models.

Conclusions

The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

Funding

The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

Lifestyle in adulthood can modify the causal relationship between BMI and islet function: using Mendelian randomization analysis

BACKGROUND

Body mass index was intimately associated with islet function, which was affected by various confounding factors. Among all methods of statistical analysis, Mendelian randomization best ruled out bias to find the causal relationship. In the present study, we explored the relationship between 13 East Asian body mass index-related genes reported previously and islet function using the Mendelian randomization method.

METHODS

A total of 2892 participants residing in northern China were enrolled. Anthropological information, such as sex, age, drinking status, smoking status, weight, height and blood pressure, was recorded for all participants. Fasting glucose and insulin were detected, and the insulin sensitivity index was calculated. 13 single nucleotide polymorphismss in East Asian body mass index -related genes were analysed with the ABI7900HT system.

RESULTS

Five genetic locus mutations, CDKAL1, MAP2K5, BDNF, FTO and SEC16B, were found to be associated with body mass index and were used to estimate the genetic risk score. We found that the genetic risk score was negatively associated with the insulin sensitivity index. Even after adjusted of confounding factors, the relationship showed statistical significance. A subsequent interaction effect analysis suggested that the negative relationship between the genetic risk score and insulin sensitivity index no longer existed in the nondrinking population, and smokers had a stronger negative relationship than nonsmokers.

CONCLUSION

We found a negative causal relationship between body mass index-related genetic locus mutations and insulin resistance, which might be increased by acquired lifestyle factors, such as drinking and smoking status.

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.

Characteristic of FINDRISC Score and Association with Diabetes Development in 6-Year Follow-Up in PURE Poland Cohort Study

Purpose

The aim of the study was to assess if FINDRISC score was associated with diabetes development after 6 years of observation.

Methods

Polish cohort is a part of global PURE study. Hereby analysis presents data from baseline (2007–2010) and 6-year follow-up (2013–2016) and was conducted on 1090 participants (702 women) from urban and rural areas in Lower Silesia region (Poland) without diabetes at the baseline and with complete data throughout course of the study.

Results

At the baseline, women had significantly higher FINDRISC score than men (10.43 vs 8.91; p=0.000) and participants from rural areas had higher score than from urban areas (10.97 vs 9.33; p=0.000). At the baseline, 25.87% of the participants had low risk of diabetes according to FINDRISC score, 38.90% had slightly elevated risk, 16.79% moderate risk, 16.42% high risk and 2.02% very high risk. Participants, who were healthy at baseline, but developed diabetes after 6 years of observation had significantly higher FINDRISC, than those who did not (13.39 vs 9.36; p=0.000). In 6-year follow-up, diabetes was diagnosed in 2.8% of participants, who were ascertained to “low risk” according to FINDRISC score in baseline; in 9.9% of participants of “slightly elevated risk”, 17.5% of participants of “moderate risk”, 26.8% in participants of “high risk” and 50.0% of participants of “very high risk”.

Conclusions

Results of PURE Poland cohort study indicates that higher FINDRISC score at the baseline was associated with higher risk of diabetes development during 6 years of observation.

Predicting type 2 diabetes mellitus among fishermen in Cape Coast: a comparison between the FINDRISC score and the metabolic syndrome

Background

Studies over the past decades have observed a sharp rise in the prevalence and incidence of type 2 diabetes mellitus (T2DM). A highly sensitive and specific predictive tool for risky populations is essential. This study assessed two significant diabetes mellitus predictive tools for effectiveness and accuracy among people living in fishing communities in Cape Coast, Ghana.

Method

In April 2019, we recruited one hundred and thirty-five (135) fishermen from three fishing communities in Cape Coast in the Central Region of Ghana. Each participant underwent a standard metabolic procedure including clinical examination as well as taking of anthropometric variables such as weight, height, waist and hip circumference were also measured. The FINDRISC questionnaire was used to gather data from the respective participants. Serum glucose and lipids were estimated with enzymatic techniques, and metabolic syndrome (MetS) screened with the international diabetes federation (IDF) criteria.

Results

Of the 135 participants, 71 (52.6%) were women. The average age of study participants was 52 ± 16 years with females averagely older (56.6 ± 15.0) than the males (47.3 ± 15.0). This study recorded 31.1% and 8.9% prediabetic and diabetic fishermen respectively. Frequency of both prediabetes and diabetes was significantly predominant among females (71.4% vs 83.3%) than males (26.2% vs 25.0%) (p < 0.001) respectively. Prevalence of MetS according to the IDF criteria was 18.5%, significantly higher among females (92.0%) than recorded among the males (18.5%). The discriminatory accuracy of FINDRISC [aROC = 0.76 (95% CI 0.68 to 0.83); sensitivity = 58.3% and specificity = 86.9%; p = 0.003; optimal cut-off point = 13.50] and the MetS [aROC = 0.74 (95% CI 0.66 to 0.81); sensitivity = 75.0% and specificity = 71.5%; p = 0.002] despite demonstrating a significantly good capacity to detect T2DM were statistically comparable [aROC = 0.018 (95% CI -0.152 to 0.189); p = 0.834] in our study.

Conclusion

Our findings indicate that both FINDRISC (with a suitable cut-off value of 13.5) and MetS screening tools possess a good predictive capacity for the detection of T2DM. Additionally, FINDRISC can be employed to detect MetS in a high-risk population.

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.

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.

The combination of insulin resistance and visceral adipose tissue estimation improves the performance of metabolic syndrome as a predictor of type 2 diabetes

AIMS

To assess the performance of metabolic syndrome as a predictor of type 2 diabetes in a model that also includes both a measure of insulin resistance and a metabolic score for visceral fat, and to propose a novel metabolic syndrome definition.

METHODS

In a prospective Metabolic Syndrome Cohort (n=6143), we evaluated improvements in type 2 diabetes risk prediction using International Diabetes Federation-defined and Adult Treatment Panel III-defined metabolic syndrome, after inclusion in the model of updated homeostatic model assessment of insulin resistance and a metabolic score for visceral fat. We also developed a modified metabolic syndrome construct, 'MS-METS', which used the metabolic score for visceral fat instead of waist circumference to evaluate improved predictive performance for risk of developing type 2 diabetes.

RESULTS

Participants who had metabolic syndrome as defined by both the Adult Treatment Panel III and the International Diabetes Federation criteria had a higher risk of type 2 diabetes compared to participants who did not meet these criteria. Addition of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat to both metabolic syndrome definitions increased predictive performance for type 2 diabetes risk. Homeostatic model assessment of insulin resistance was the only additional predictor of type 2 diabetes in participants without metabolic syndrome. Conversely, in participants with metabolic syndrome, the use of the metabolic score for visceral fat was the stronger added predictor for type 2 diabetes. When evaluating participants using the MS-METS definition we observed the largest improvement in predictive ability for type 2 diabetes risk and a significant reduction in risk overestimation compared to evaluation using metabolic syndrome defined according to the International Diabetes Federation and Adult Treatment Panel III criteria alone.

CONCLUSION

Inclusion of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat increases performance of metabolic syndrome in prediction of type 2 diabetes. Assessment of insulin resistance could be more useful than conventional metabolic syndrome and assessment of visceral adipose tissue could be more useful in people with metabolic syndrome. Metabolic syndrome as defined using our modified MS-METS construct improved the accuracy of type 2 diabetes prediction.

Translation and cultural adaptation into Brazilian Portuguese of the Finnish Diabetes Risk Score (FINDRISC) and reliability assessment

ABSTRACT: Introduction: The Finnish Diabetes Risk Score (FINDRISC) is a tool that was initially developed to predict the risk of developing type 2 diabetes mellitus in adults. This tool is simple, quick to apply, non-invasive, and low-cost. The aims of this study were to perform a translation and cultural adaptation of the original version of FINDRISC into Brazilian Portuguese and to assess test-retest reliability. Methodology: This work was done following the ISPOR Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes Measures. Once the final Brazilian Portuguese version (FINDRISC-Br) was developed, the reliability assessment was performed using a non-random sample of 83 individuals attending a primary care health center. Each participant was interviewed by trained registered dieticians on two occasions with a mean interval of 14 days. The reliability assessment was performed by analyzing the level of agreement between the test-retest responses of FINDRISC-Br using Cohen’s kappa coefficient and the intraclass correlation coefficient (ICC). Results: The steps of ISPOR guidelines were consecutively followed without major problems. Regarding the reliability assessment, the questionnaire as a whole presented adequate reliability (Cohen’s kappa = 0.82, 95%CI 0.72 - 0.92 and ICC = 0.94, 95%CI 0.91 - 0.96). Conclusion: FINDRISC was translated into Brazilian Portuguese and culturally adapted following standard procedures. FINDRISC-Br has thus become available for use and has potential as a screening tool in different Brazilian settings and applications.

The FINDRISC questionnaire capacity to predict diabetes mellitus II, arterial hypertension and comorbidity in women from low-and-middle-income countries

The Finnish Diabetes Risk Score (FINDRISC) has been implemented to assess diabetes risk. The authors aimed in this study to determine the prediction capacity of FINDRISC for the early detection of cardiovascular diseases in women. A prevalence study was carried out on 441 women of Pueblo Libre (Peru). Anthropometric variables, blood pressure, blood glucose and comorbidity were measured and entered in FINDRISC. 4.8% of the studied women suffered from DM2, 14.3% from AHT, 33% obesity and 8.6% comorbidity. We found that FINDRISC was the best method to discriminate DM, AHT and comorbidity. FINDRISC is an effective non-invasive tool for women from low-and-middle-income countries.