Prescreening tools for diabetes and obesity-associated dyslipidaemia: comparing BMI, waist and waist hip ratio. The D.E.S.I.R. Study

Levels of actigraphy-derived physical activity among Polish nurses: factors associated with the prevalence of selected metabolic disorders

Numerous studies demonstrate a relationship between physical activity and the development of non-communicable diseases. Nurses play a crucial role in the healthcare system, and their demanding work can have an impact on their health. The objective of this cross-sectional study was to assess physical activity in relation to factors predisposing to the occurrence of specific metabolic disorders among Polish nurses. The measurements included physical activity level using ActiGraph GT3X, body weight composition using Tanita MC-980, body mass index, waist circumference, blood pressure using Welch Allyn 4200B, lipid profile, and fasting blood glucose using CardioChek PA. The results indicate that nearly one-third (31.75%) of the total sample of studied nurses do not meet the criteria for the minimum amount of physical activity of at least moderate intensity. Furthermore, over half of the surveyed nurses (55.5%) were classified as overweight or obese based on BMI, and almost half (42.86%) had abdominal obesity. The regression model, employing linear regression, revealed that factors predisposing to selected metabolic disorders were age, engaging in multiple jobs, and the number of steps per day. There is a pressing need to implement comprehensive and supportive initiatives to improve the overall health condition of nurses in Poland through increased physical activity. Activating and supporting this professional group is an investment that benefits not only the nurses themselves but also the healthcare system and the entire nation.

A nomogram for screening sarcopenia in Chinese type 2 diabetes mellitus patients

OBJECTIVE

Diabetes is an important risk factor for sarcopenia and contributes to poor prognosis; it is important for clinicians to identify sarcopenia early in the population with type 2 diabetes mellitus. Our aim was to establish a clinical screening model of sarcopenia in Chinese patients with type 2 diabetes mellitus.

METHODS

A cross-sectional study was conducted involving 1131 hospitalized patients (62.67 ± 11.25 years) with type 2 diabetes mellitus, including 560 men and 571 women. All muscle/fat parameters were measured by dual energy X-ray absorptiometry and the clinical correlation with sarcopenia was evaluated. The least absolute shrinkage and selection operator was used to select optimal variables and build a nomogram chart of the sarcopenic screening model for patients with type 2 diabetes mellitus, respectively. The area under the receiver operating characteristic curve (AUC), the calibration curve, the analysis of the decision curve, the clinical impact curve, and external validations were used to evaluate discriminative ability and clinical applicability.

RESULTS

The prevalence of sarcopenia in patients with type 2 diabetes mellitus was 30.06 % (340/1131). Compared to the non-sarcopenic group, the sarcopenic group was older, more likely to be men, and had a higher heart rate and lower body mass index (BMI), waist-hip ratio (WHR), upper limb muscle mass, lower limb muscle mass and fat paraments (all P < 0.05). Five independent variables (age, sex, BMI, WHR and heart rate) were selected to construct a nomogram prediction model. The AUC was 0.907 (95 % CI: 0.890-0.925). The calibration curve, decision curve analysis, and clinical impact curves showed a wide range of nomograms with good clinical applicability under threshold probability. Additionally, internal validation showed a good AUC of 0.908 (95 % CI: 0.886-0.928) in the training set and 0.904 (95 % CI: 0.868-0.941) in the testing set, as well as an accuracy of 93.2 % for the screening of sarcopenia in the external validation set.

CONCLUSIONS

Age, sex, BMI, WHR, and heart rate were used to detect sarcopenia in patients with type 2 diabetes mellitus. The novel screening model is an accurate, easy-to-implement and low-cost tool for early identification of sarcopenia in Chinese patients with type 2 diabetes mellitus.

Obesity among Sudanese adults with diabetes: a population-based survey

BACKGROUND

The aim of this study was to determine the prevalence of obesity among Sudanese individuals with diabetes.

METHODS

Demographic and clinical data from 1,337 individuals with type 2 diabetes were collected using a pretested, standardized, interviewer administered questionnaire. Subjects were recruited from three states namely Khartoum, Northern and River Nile States. Anthropometric measurements including body weight, height and waist circumference were determined using standardized techniques and calibrated equipment.

RESULTS

Total of 1,337 subjects with type 2 diabetes from Khartoum and North of Sudan were enrolled in this study and completed the questionnaires; the results showed that prevalence of obesity among individuals with diabetes was found to be 24.5%, with a higher rate of obesity in females than males (29.2% versus 18.1%). The prevalence of central obesity was also higher in women (43.6%) than men (21.8%). The prevalence of overweight was 39.9%. The overall prevalence of overweight and obesity was 64.4%. Obesity was associated with age, sex and blood pressure. While central obesity was associated with an increase in age, female sex and hypertension. Logistic regression analysis showed that female sex and hypertension are absolute risk factors for both obesity and central obesity.

CONCLUSIONS

The prevalence of obesity was 24.5% and overweight was 39.9% among Sudanese individuals with diabetes and more among women than men. Obesity and central obesity were significantly associated with female sex and hypertension.

Obesity and Insulin Resistance Screening Tools in American Adolescents: National Health and Nutrition Examination Survey (NHANES) 1999 to 2010

OBJECTIVE

To identify which feasible obesity and insulin resistance (IR) screening tools are most strongly associated in adolescents by using a nationally representative sample.

METHODS

Adolescents aged 12.0 to 18.9 years who were participating in the National Health and Nutrition Examination Survey (NHANES) (n=3584) and who were measured for height, weight, waist circumference (WC), triceps and subscapular skinfold thickness, glycated hemoglobin, fasting glucose (FG) and fasting insulin (FI) level were included. Adolescents were split by gender and grouped by body mass index (BMI) percentile. Age- and gender-specific classifications were constructed for each obesity screening tool measure to account for growth and maturation. General linear models were used to establish groups objectively for analysis based on when IR began to increase. Additional general linear models were used to identify when IR significantly increased for each IR measure as obesity group increased and to identify the variance accounted for among each obesity-IR screening tool relationship.

RESULTS

As the obesity group increased, homeostasis model assessment-insulin resistance (HOMA-IR) and FI significantly increased, while FG increased only (above the referent) in groups with BMI percentiles ≥95.0, and glycated hemoglobin level did not vary across obesity groups. The most strongly associated screening tools were WC and FI in boys (R(2)=0.253) and girls (R(2)=0.257). FI had the strongest association with all of the obesity measures. BMI associations were slightly weaker than WC in each in relation to IR.

CONCLUSIONS

Our findings show that WC and FI are the most strongly associated obesity and IR screening tool measures in adolescents. These feasible screening tools should be utilized in screening practices for at-risk adolescents.

The Prevalence of Diabetes and Prediabetes in the Adult Population of Jeddah, Saudi Arabia--A Community-Based Survey

BACKGROUND

Type 2 (T2DM) is believed to be common in Saudi Arabia, but data are limited. In this population survey, we determined the prevalence of T2DM and prediabetes.

MATERIALS AND METHODS

A representative sample among residents aged ≥ 18 years of the city of Jeddah was obtained comprising both Saudi and non-Saudi families (N = 1420). Data on dietary, clinical and socio-demographic characteristics were collected and anthropometric measurements taken. Fasting plasma glucose and glycated hemoglobin (HbA1c) were used to diagnose diabetes and prediabetes employing American Diabetes Association criteria. Multiple logistic regression analysis was used to identify factors associated with T2DM.

RESULTS

Age and sex standardized prevalence of prediabetes was 9.0% (95% CI 7.5-10.5); 9.4% (7.1-11.8) in men and 8.6% (6.6-10.6) in women. For DM it was 12.1% (10.7-13.5); 12.9% (10.7-13.5) in men and 11.4% (9.5-13.3) in women. The prevalence based on World Population as standard was 18.3% for DM and 11.9% for prediabetes. The prevalence of DM and prediabetes increased with age. Of people aged ≥50 years 46% of men and 44% of women had DM. Prediabetes and DM were associated with various measures of adiposity. DM was also associated with and family history of dyslipidemia in women, cardiovascular disease in men, and with hypertension, dyslipidemia and family history of diabetes in both sexes.

DISCUSSION

Age was the strongest predictor of DM and prediabetes followed by obesity. Of people aged 50 years or over almost half had DM and another 10-15% had prediabetes leaving only a small proportion of people in this age group with normoglycemia. Since we did not use an oral glucose tolerance test the true prevalence of DM and prediabetes is thus likely to be even higher than reported here. These results demonstrate the urgent need to develop primary prevention strategies for type 2 diabetes in Saudi Arabia.

Application and applicability of non-invasive risk models for predicting undiagnosed prevalent diabetes in Africa: A systematic literature search

BACKGROUND AND PURPOSE

Prediction algorithms are increasingly advocated in diabetes screening strategies, particularly in developing countries. We conducted a systematic review to assess the application and applicability of existing non-invasive prevalent diabetes risk models to populations within Africa.

DESIGN

systematic review data sources A systematic search of English literatures in Medline via PubMed from 1999 until June, 2014. Study selection Included studies had to report on the development, validation or implementation of a model that was primarily constructed to predict prevalent undiagnosed diabetes using non-laboratory based predictors.

DATA EXTRACTION

Data were extracted on the type of statistical model, type and range of predictors in the model, performance measures in both internal and external validation, and whether the model was developed from, validated or implemented in an African population.

RESULTS

Twenty-three studies reporting on non-invasive prevalent diabetes models were identified. Ten from Europe (some with multiethnic populations), nine models were developed among Asian population, two from the USA and two from the Middle-East. The c-statistics for these models ranged from 0.65 to 0.88 in the development studies, and from 0.63 to 0.80 in the validation studies. Twenty models were validated, and none in Africa. Among predictors commonly included in models, parental/family history of diabetes and personal history of hypertension appear to be more prone to measurement errors in the African context.

CONCLUSION

Existing prevalent diabetes prediction models have not been applied to African populations, and issues with the measurement of key predictors make their applicability likely inaccurate.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Age-related differences in recommended anthropometric cut-off point validity to identify cardiovascular risk factors in ostensibly healthy women

Aim: To investigate validity of widely recommended anthropometric and total fat percentage cut-off points in screening for cardiovascular risk factors in women of different ages. Methods: A population-based sample of 1002 Swedish women aged 38, 50, 75 (younger, middle-aged and elderly, respectively) underwent anthropometry, health examinations and blood tests. Total fat was estimated (bioimpedance) in 670 women. Sensitivity, specificity of body mass index (BMI; ≥25 and ≥30), waist circumference (WC; ≥80 cm and ≥88 cm) and total fat percentage (TF; ≥35%) cut-off points for cardiovascular risk factors (dyslipidaemias, hypertension and hyperglycaemia) were calculated for each age. Cut-off points yielding high sensitivity together with modest specificity were considered valid. Women reporting hospital admission for cardiovascular disease were excluded. Results: The sensitivity of WC ≥80 cm for one or more risk factors was ~60% in younger and middle-aged women, and 80% in elderly women. The specificity of WC ≥80 cm for one or more risk factors was 69%, 57% and 40% at the three ages (p < .05 for age trends). WC ≥80 cm yielded ~80% sensitivity for two or more risk factors across all ages. However, specificity decreased with increasing age (p < .0001), being 33% in elderly. WC ≥88 cm provided better specificity in elderly women. BMI and TF % cut-off points were not better than WC. Conclusions:Validity of recommended anthropometric cut-off points in screening asymptomatic women varies with age. In younger and middle-age, WC ≥80 cm yielded high sensitivity and modest specificity for two or more risk factors, however, sensitivity for one or more risk factor was less than optimal. WC ≥88 cm showed better validity than WC ≥80 cm in elderly. Our results support age-specific screening cut-off points for women.

Central body fat distribution associates with unfavorable renal hemodynamics independent of body mass index

Central distribution of body fat is associated with a higher risk of renal disease, but whether it is the distribution pattern or the overall excess weight that underlies this association is not well understood. Here, we studied the association between waist-to-hip ratio (WHR), which reflects central adiposity, and renal hemodynamics in 315 healthy persons with a mean body mass index (BMI) of 24.9 kg/m(2) and a mean (125)I-iothalamate GFR of 109 ml/min per 1.73 m(2). In multivariate analyses, WHR was associated with lower GFR, lower effective renal plasma flow, and higher filtration fraction, even after adjustment for sex, age, mean arterial pressure, and BMI. Multivariate models produced similar results regardless of whether the hemodynamic measures were indexed to body surface area. Thus, these results suggest that central body fat distribution, independent of BMI, is associated with an unfavorable pattern of renal hemodynamic measures that could underlie the increased renal risk reported in observational studies.

Assessing impaired glucose tolerance and insulin resistance in polycystic ovarian syndrome with a muffin test: an alternative to the glucose tolerance test

OBJECTIVE

To determine the sensitivity of a high-glucose load in a meal as an alternative to the standard oral glucose tolerance test (OGTT) in detecting impaired glucose tolerance and insulin resistance in women with polycystic ovarian syndrome (PCOS) and the relationship of body composition to insulin resistance in the PCOS cohort.

METHODS

In this prospective, single-center study, women with PCOS who were being followed up as out-patients were recruited. The study was performed between November 2007 and March 2008. All participants underwent OGTT before study enrollment. Participants were given a meal including carbohydrates, fat, and protein. Glucose and insulin levels were measured every 30 minutes for 2 hours after completing the meal. Body composition was measured by dual-energy x-ray absorptiometry.

RESULTS

Thirteen of the 15 participants completed the meal tolerance test and the body composition study. Four of 13 participants (31%) had abnormal glucose tolerance with the meal test compared with 2 of 8 participants (25%) who completed the OGTT. Those who had insulin resistance on OGTT were detected with the meal test. The 2-hour insulin levels following the meal were 38% higher than with the OGTT. Of 10 participants with insulin resistance, 9 had a total body fat mass greater than the 90th percentile, whereas 1 of 3 participants (33%) with normal body composition was insulin resistant.

CONCLUSION

Administration of oral glucose load via a meal is an effective alternative to the OGTT in diagnosing impaired glucose tolerance and insulin resistance and may be more sensitive, without the adverse effects of the oral glucose load in the OGTT. PCOS is an independent risk factor for impaired glucose tolerance and insulin resistance, regardless of body composition.

Optimal cut-off values and population means of waist circumference in different populations

Abdominal obesity is a risk factor for cardiometabolic disease, and has become a major public health problem in the world. Waist circumference is generally used as a simple surrogate marker to define abdominal obesity for population screening. An increasing number of publications solely rely on the method that maximises sensitivity and specificity to define ‘optimal’ cut-off values. It is well documented that the optimal cut-off values of waist circumference vary across different ethnicities. However, it is not clear if the variation in cut-off values is a true biological phenomenon or an artifact of the method for identifying optimal cut-off points. The objective of the present review was to assess the relationship between optimal cut-offs and population waist circumference levels. Among sixty-one research papers, optimal cut-off values ranged from 65·5 to 101·2 cm for women and 72·5 to 103·0 cm for men. Reported optimal cut-off values were highly correlated with population means (correlation coefficient: 0·91 for men and 0·93 for women). Such a strong association was independent of waist circumference measurement techniques or the health outcomes (dyslipidaemia, hypertension or hyperglycaemia), and existed in some homogeneous populations such as the Chinese and Japanese. Our findings raised some concerns about applying the sensitivity and specificity approach to determine cut-off values. Further research is needed to understand whether the differences among populations in waist circumference were genetically or environmentally determined, and to understand whether using region-specific cut-off points can identify individuals with the same absolute risk levels of metabolic and cardiovascular outcomes among different populations.

Predicting diabetes: clinical, biological, and genetic approaches: data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)

OBJECTIVE

To provide a simple clinical diabetes risk score and to identify characteristics that predict later diabetes using variables available in the clinic setting as well as biological variables and polymorphisms.

RESEARCH DESIGN AND METHODS

Incident diabetes was studied in 1,863 men and 1,954 women, 30-65 years of age at baseline, with diabetes defined by treatment or by fasting plasma glucose >or=7.0 mmol/l at 3-yearly examinations over 9 years. Sex-specific logistic regression equations were used to select variables for prediction.

RESULTS

A total of 140 men and 63 women developed diabetes. The predictive clinical variables were waist circumference and hypertension in both sexes, smoking in men, and diabetes in the family in women. Discrimination, as measured by the area under the receiver operating curves (AROCs), were 0.713 for men and 0.827 for women, a little higher than for the Finish Diabetes Risk (FINDRISC) score, with fewer variables in the score. Combining clinical and biological variables, the predictive equation included fasting glucose, waist circumference, smoking, and gamma-glutamyltransferase for men and fasting glucose, BMI, triglycerides, and diabetes in family for women. The number of TCF7L2 and IL6 deleterious alleles was predictive in both sexes, but after including the above clinical and biological variables, this variable was only predictive in women (P < 0.03) and the AROC statistics increased only marginally.

CONCLUSIONS

The best clinical predictor of diabetes is adiposity, and baseline glucose is the best biological predictor. Clinical and biological predictors differed marginally between men and women. The genetic polymorphisms added little to the prediction of diabetes.

Impaired Glucose Tolerance and Impaired Fasting Glucose Share Similar Underlying Pathophysiologies

Both impaired glucose tolerance (IGT) and impaired fasting glucose (IFG) are pre-diabetic states. IGT was defined as having normal fasting plasma glucose (< 6.1 mmol/l) and abnormal 2-hr post-challenge plasma glucose. IFG was defined as having abnormal fasting plasma and normal 2-hr post-challenge plasma glucose (< 7.8 mmol/l). To explore whether these two abnormalities share similar underlying pathophysiologies, we evaluated risk factors of IGT and IFT using the models of factor analysis. The present study included 107 subjects with IGT and 52 with IFG. An oral glucose tolerance test and insulin suppression test, which could quantify insulin resistance, were performed on separate days. The risk factors include waist-to-hip ratio (WHR), triglycerides, high-density lipoprotein (HDL)-cholesterol, blood pressure, and fasting plasma glucose, which are associated with metabolic syndrome and insulin resistance. Factor analysis is a commonly used statistical method that could reduce a large number of risk factors into smaller numbers of groups, also called dimension. Accordingly, the complicated data could be interpreted more easily, since the related risk factors are grouped in one dimension. The results showed that the risk factors of IGT and IFG have similar grouping patterns. Triglyceride, insulin resistance, and HDL-cholesterol were grouped in one dimension (the lipid dimension), while WHR, mean blood pressure and fasting plasma glucose were grouped in another dimension (the metabolic dimension). In conclusion, except for WHR, the grouping patterns of the components in both IGT and IFG were nearly identical. These results suggest that IGT and IFG may share similar pathophysiologies.