Is the association of type II diabetes with waist circumference or waist-to-hip ratio stronger than that with body mass index?

Proteomic Signature of BMI and Risk of Type 2 Diabetes

ARTICLE HIGHLIGHTS

Environmental mixtures and body mass index in two prospective US-based cohorts of female nurses

We estimated the joint effect of particulate matter ≤ 2.5 µm in diameter (PM2.5), nitrogen dioxide (NO2), seasonal temperature, noise, greenness, light at night, and neighborhood socioeconomic status (NSES) on body mass index (BMI) in a mixture context among 194,966 participants from the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) over 30 years. BMI was calculated from self-reported weight and height. Single- and multi-exposure generalized estimating equations models were used to estimate the difference in BMI per interquartile range (IQR) increase of environmental factors, and quantile g-computation methods were used to estimate joint associations. In both cohorts, we consistently observed positive associations of BMI with PM2.5 and NO2 concentrations as well as negative associations with light at night and NSES regardless modeling approach. A positive association with noise was only observed in NHS. Negative associations with greenness and winter temperature were only observed in NHSII. Overall, the changes in BMI per quintile increase in all eight exposures were -0.11 (-0.13, -0.08) in NHS and -0.39 (-0.41, -0.37) in NHSII, which were largely driven by air pollution and nighttime noise (18-45 %) in the positive direction and NSES (>70 %) in the negative direction. Future intervention on environmental factors, especially reducing PM2.5, NO2 and noise or improving the NSES, might be helpful to lower BMI.

Waist circumference as a parameter in school-based interventions to prevent overweight and obesity - a systematic review and meta-analysis

BACKGROUND

Preventing childhood obesity remains an important public health issue worldwide. Since visceral fat in particular is understood as an important risk factor for many chronic diseases, waist circumference is recommended as a measurement parameter for global obesity surveillance. This systematic review and meta-analysis focused on waist circumference as an outcome parameter for studies of school-based interventions to prevent overweight and obesity.

METHODS

A systematic literature search was conducted at the end of 2019 in nine data bases, including Medline and Embase, in order to identify relevant studies evaluating interventions in schools aimed at preventing obesity. Eligibility criteria admitted randomised and non-randomised controlled trials. After screening titles, abstracts and full texts, the data of the identified studies were systematically extracted. Risk of bias was assessed according to study type with the appropriate Cochrane Risk of Bias Tool. The review gives a qualitative overview over all included studies structured by extracted data. Separate meta-analyses were done for the outcome mean difference in change in waist circumference, measured in cm or reported as z-score value, using an inverse variance random-effects model due to study design.

RESULTS

A total of 2421 publications were screened based on titles, abstracts and full texts. Complemented by results of a former systematic literature search 44 studies were identified for inclusion, comprising a total of 39.837 participants (age range: 6 to 18 years). Nearly half of the studies were conducted in Europe, two-thirds combined diet and exercise-based interventions. Likewise two thirds of the studies were conducted as cluster-randomised trials. Most of the reported effects favoured the experimental groups, indicating the basic effectiveness of school-based measures. Based on reported data, only one third of the studies could be included in the meta-analyses. For the difference in mean change of the outcome parameter waist circumference measured in cm (95% CI), we found a pooled effect estimate of -0.95 (-1.87; -0.46). For the difference in mean change of the outcome parameter waist circumference reported as z-score value (95% CI), the pooled effect estimate was -0.10 (-0.15; -0.05). Both effect estimates were in favour of the experimental group. The overall effect sizes were small with a p-value < 0.05.

CONCLUSIONS

Pooled effect estimates were small but in favour of the experimental groups. The same applies to the majority of the effects reported in the included studies. The included cluster of randomised controlled trials demonstrated an especially sound methodological standard. The possibility of achieving larger effects in studies of preventive interventions and health promotion is limited. Schools can only realise their full potential in preventing overweight and obesity in children and adolescents if they are accompanied by measures in other areas of the obesogenic environment.

The association between body weight indices, behavioral factors, and type 2 diabetes mellitus in Africa: A systematic review and meta-analysis of population-based epidemiological studies

BACKGROUND AND AIM

Type 2 diabetes mellitus (T2DM) is a significant public health concern in Africa. While the associations between modifiable risk factors and T2DM are likely to be Africa-specific, their overall estimations have not been published. This study aimed to use systematic and meta-analytic methods to examine the strength of associations between modifiable risk factors and T2DM in Africa.

METHODS AND RESULTS

A systematic search of literature published between January 2000 to March 2022 was conducted. The review included only population-based studies and data extracted from 57 studies. Of these, unadjusted data from 50 studies were included in meta-analysis. With considerable heterogeneity between studies, random-effect models were calculated to ascertain the odds ratios (OR) and 95% confidence intervals (CI) for the associations between obesity (OB) and overweight (OV), defined by BMI; central obesity (waist circumference (OB-WC), waist-to-hip-ratio (OB-WHR)), alcohol, fruit and vegetable consumption, smoking, physical activity (PA) and T2DM. Moderator effects of age, African regions, and urban/rural location were assessed. Risk factors associated with T2DM include BMI-OB [OR = 3.05, 95% CI: (2.58, 3.61)], BMI-OV [OR = 2.38, 95% CI: (1.51, 3.75)], and BMI-OV/OB [OR = 2.07, 95% CI: (1.82, 2.34)]; OB-WC [OR = 2.58, 95% CI: (2.09, 3.18)] and OB-WHR [OR = 2.22, 95% CI: (1.69, 2.92)]; PA [OR = 1.85, 95% CI: (1.50, 2.30)]. Significant moderator effects were not observed.

CONCLUSION

Obesity defined by BMI and central obesity, but not behavioral risk factors were most strongly associated with T2DM in African populations, emphasizing the need for obesity prevention to limit the rise of T2DM.

REGISTRATION

The PROSPERO registration number is CRD42016043027.

Gender Differences in the Predictive Value of Obesity Indices for Insulin Resistance in Adult Mexican Individuals

BACKGROUND

Obesity-linked insulin resistance (IR) is an important risk factor for metabolic diseases, and anthropometric indices are commonly used for risk assessment.

AIM

The study aimed to assess possible differences between women and men in the predictive value and association of nine obesity indices with IR, as assessed by HOMA-IR, in a nondiabetic adult population.

METHODS

The cross-sectional study included individuals recruited from a hospital in Mexico City. Indices evaluated were waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio, waist-to-height ratio, visceral adiposity index, body adiposity index (BAI), relative fat mass (RFM), and conicity index (CI). Fasting plasma glucose and insulin were measured to calculate HOMA-IR. Correlation analysis was performed between obesity indices and HOMA-IR. Receiver operating characteristics curve analyses were performed to determine predictive accuracy and cut-off values of obesity indices for IR. A binary logistic regression (BLR) analysis with OR calculation was performed to determine the strength of association with HOMA-IR.

RESULTS

We included 378 individuals (59% females, mean age 46.38 ±12.25 years). The highest Pearson coefficient value was observed for BMI among women, while among men, the highest values were found for BMI and BAI. WC among women, and BAI and RFM among men showed the highest sensitivity, while the highest specificity was observed for WHR among women and WC among men with respect to insulin prediction. In the adjusted BLR model, BMI, WC, and WHR among women and WC and RFM and BAI among men were independently associated with IR, showing the highest odds ratio (OR).

CONCLUSION

In Mexican adults, WC, WHR, RFM and BAI could be complementary tools for BMI in screening for IR.

How do sex-specific BMI trajectories shape diabetes risk? A longitudinal analysis of Indonesian adults

Introduction

Sex is a critical predictor of body mass index (BMI) trajectory over the life span, playing a role in disparities in the risk of diabetes. While there is some evidence of the effect of BMI on the risk of diabetes, little is known about sex differences in BMI trajectories over the life span and their later life association with diabetes, especially in low-income and middle-income settings.

Methods

Using panel data from the Indonesian Family Life Survey, this study examines the impact of an individual's BMI trajectory throughout adulthood on diabetes onset. Analysis for men and women were conducted separately. First, growth curve modelling estimates individuals' BMI trajectories over age. Second, the effect of BMI trajectories on diabetes is estimated using logistic regression adjusted for individual socioeconomic status. Finally, we perform relative dominance analysis to test the importance of BMI trajectories as a predictor of diabetes in later life against abdominal obesity measurements.

Results

BMI trajectories over adulthood strongly predict the probability of diabetes in both men and women. A rapidly increasing BMI significantly increases the probability of diabetes in men regardless of individuals' initial BMI. Among women, those who started out with an overweight/obese BMI and experienced a rapid loss in BMI over age had the highest risk of diabetes. Greater educational attainment is associated with an increase in the likelihood of diabetes in men, but higher education level is a protective factor from diabetes in women.

Conclusion

The findings suggest that maintaining BMI at normal cut-off over the life course can lower the likelihood of diabetes onset in later adulthood. This study emphasises that simple monitoring of BMI trajectory over adulthood could be a useful tool to identify the population at risk of diabetes in contexts with substantial underdiagnoses of diabetes.

Identifying sex-specific anthropometric measures and thresholds for dysglycemia screening in an HIV-endemic rural South African population

Valid screening and diagnostic algorithms are needed to achieve 2030 targets proposed by the WHO's Global Diabetes Compact. We explored anthropometric thresholds to optimally screen and refer individuals for diabetes testing in rural South Africa. We evaluated screening thresholds for waist circumference (WC), body mass index (BMI), and waist-hip ratio (WHR) to detect dysglycemia based on a glycated hemoglobin (HbA1C) ≥6.5% among adults in a population-based study in South Africa using weighted, non-parametric ROC regression analyses. We then assessed the diagnostic validity of traditional obesity thresholds, explored optimal thresholds for this population, and fit models stratified by sex, age, and HIV status. The prevalence of dysglycemia in the total study population (n = 17,846) was 7.7%. WC had greater discriminatory capacity than WHR to detect dysglycemia in men (p-value<0.001) and women (p<0.001). WC had greater discriminatory capacity than BMI to detect dysglycemia in women (p<0.001). However, BMI and WC performed similarly for men (p = 0.589). Whereas traditional WC thresholds for women (>81cm) performed well (sensitivity 91%, positive predictive value [PPV] 14.9%), substantially lower thresholds were needed to achieve acceptable sensitivity and PPV among men (traditional >94cm, derived >79.5cm). WC outperforms BMI as an anthropometric screening measure for dysglycemia in rural South Africa. Whereas WC guideline thresholds are appropriate for women, male-derived WC cutoffs performed better at lower thresholds. In this rural South African population, thresholds that maximize specificity and PPV for efficient resource allocation may be preferred.

Relevance of body composition in phenotyping the obesities

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

Patients with body mass index ≥25 kg/m2 as a target population for improvement of rate of follow-up duplex venous ultrasound examinations following initial incomplete examinations

OBJECTIVE

Obesity is highly prevalent and a major risk factor for deep vein thrombosis (DVT) and chronic venous disease. It can also technically limit duplex ultrasound evaluations for lower extremity DVT. We compared the rates and results of repeat lower extremity venous duplex ultrasound (LEVDUS) after an initial incomplete and negative (IIN) LEVDUS in overweight (body mass index [BMI] ≤25-30 kg/m2) and obese (BMI ≥30 kg/m2) patients with those of patients with a BMI <25 kg/m2 to evaluate whether increasing the rate of follow-up examinations in overweight and obese patients might facilitate improved patient care.

METHODS

We performed a retrospective review of 617 patients with an IIN LEVDUS study from December 31, 2017 to December 31, 2020. Demographic and imaging data of the patients with an IIN LEVDUS and the frequency of repeat studies performed within 2 weeks were abstracted from the electronic medical records. The patients were divided into three BMI-based groups: normal (BMI <25 kg/m2), overweight (BMI 25-30 kg/m2), and obese (BMI ≥30 kg/m2).

RESULTS

Of the 617 patients with an IIN LEVDUS, 213 (34.5%) were normal weight, 177 (29%) were overweight, and 227 (37%) were obese. The repeat LEVDUS rates were significantly different across the three weight groups (P < .001). After an IIN LEVDUS, the rate of repeat LEVDUS for the normal weight, overweight, and obese groups was 46% (98 of 213), 28% (50 of 227), and 32% (73 of 227), respectively. The overall rates of thrombosis (both DVT and superficial vein thrombosis) in the repeat LEVDUS examinations were not significantly different among the normal weight (14%), overweight (11%), and obese (18%) patients (P = .431).

CONCLUSIONS

Overweight and obese patients (BMI ≥25 kg/m2) received fewer follow-up examinations after an IIN LEVDUS. Follow-up LEVDUS examinations of overweight and obese patients after an IIN LEVDUS study have similar rates of venous thrombosis compared with normal weight patients. Targeting improving usage of follow-up LEVDUS studies for all patients, but especially for those who are overweight and obese, with an IIN LEVDUS through quality improvement efforts could help minimize missed diagnoses of venous thrombosis and improve the quality of patient care.

Arm Circumference, Arm-to-Waist Ratio in Relation to Cardiovascular and All-Cause Mortality among Patients with Diabetes Mellitus

Among patients with diabetes mellitus, limited studies have investigated the relationship between anthropometric parameters and cardiovascular disease (CVD), with all-cause mortality. We examined the associations of arm circumference (AC), arm-to-waist ratio (AC/WC), and CVD, with all-cause mortality among patients with diabetes. This is a cohort study of 5497 diabetic individuals aged 20 or over who were recruited in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014. Cox proportional hazards regression models were used to analyze the associations between AC, AC/WC, and CVD, with all-cause mortality. We also conducted stratified analyses and explored the possible non-linear relation by restricted cubic splines. During a median follow-up of 7.2 years, there were 271 and 1093 cases of CVD and all-cause death. The multivariable adjusted hazard ratios (HRs) with 95% confidence intervals (Cis) of CVD mortality in Q2, Q3, and Q4 groups compared with Q1 group were 0.37 (0.22, 0.62), 0.24 (0.12, 0.48), 0.18 (0.07, 0.46) for AC, and 0.18 (0.07, 0.46), 0.34 (0.20, 0.60), 0.28 (0.15, 0.53) for AC/WC. Similar results were observed in the analysis for all-cause mortality risk. AC and AC/WC were both inversely associated with CVD and all-cause mortality among individuals with diabetes. It is important to pay attention to these anthropometric parameters of diabetic patients.

Sex difference in the associations among obesity-related indices with incidence of diabetes mellitus in a large Taiwanese population follow-up study

Background

Obesity is a major risk factor for diabetes mellitus (DM), which is in turn a major risk factor for cardiovascular diseases such as coronary artery disease and stroke. As few studies have investigated sex differences in the association between obesity and incidence of DM, the aim of this longitudinal study was to explore this issue in a large group of Taiwanese participants.

Methods

A total of 24,346 participants were enrolled in this study, of whom 8,334 (mean age, 50.6 ± 11.0 years) were male and 16,012 (mean age, 50.5 ± 10.1 years) were female. The following obesity-related indices were studied: body mass index, waist-to-height ratio, waist-to-hip ratio (WHR), body roundness index, conicity index (CI), body adiposity index, abdominal volume index, lipid accumulation product (LAP), and visceral adiposity index (VAI).

Results

The analysis showed significant associations between all of these indices with incidence of DM (all p < 0.001). In the male participants, the strongest predictors for incidence of DM were LAP (AUC = 0.692), WHtR (AUC = 0.684), and WHR (AUC = 0.683). In the female participants, the strongest predictors were LAP (AUC = 0.744), WHtR (AUC = 0.710) and VAI (AUC = 0.710), followed by BRI (AUC = 0.708).

Conclusion

Strong associations were found between the studied obesity-related indices and incidence of DM, and sex differences were found. Hence, to better control DM, reducing body weight may be beneficial in addition to lifestyle modifications, diet control, and pharmacological interventions.

Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness

The early prediction of diabetes can facilitate interventions to prevent or delay it. This study proposes a diabetes prediction model based on machine learning (ML) to encourage individuals at risk of diabetes to employ healthy interventions. A total of 38,379 subjects were included. We trained the model on 80% of the subjects and verified its predictive performance on the remaining 20%. Furthermore, the performances of several algorithms were compared, including logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), Cox regression, and XGBoost Survival Embedding (XGBSE). The area under the receiver operating characteristic curve (AUROC) of the XGBoost model was the largest, followed by those of the decision tree, logistic regression, and random forest models. For the survival analysis, XGBSE yielded an AUROC exceeding 0.9 for the 2- to 9-year predictions and a C-index of 0.934, while the Cox regression achieved a C-index of 0.921. After lowering the threshold from 0.5 to 0.25, the sensitivity increased from 0.011 to 0.236 for the 2-year prediction model and from 0.607 to 0.994 for the 9-year prediction model, while the specificity showed negligible changes. We developed a high-performance diabetes prediction model that applied the XGBSE algorithm with threshold adjustment. We plan to use this prediction model in real clinical practice for diabetes prevention after simplifying and validating it externally.

Waist Circumference-Years Construct Analysis and the Incidence of Type 2 Diabetes: China Health and Nutrition Survey, 1997-2015

Background: Few studies have combined the degree and duration of abdominal obesity into a waist circumference-years construct for analysis. The purpose of this study was to investigate the effect of waist circumference-years on the incidence of type 2 diabetes. Methods: A total of 6616 adults from the China Health and Nutrition Survey (CHNS) were enrolled in this study from 1997. The waist circumference-years construct was represented as the sum of the upper and lower area between the waist circumference baseline (men: ≥90 cm, women: ≥85 cm) and the waist circumference line. The correlations in the study were analyzed using logistic regression. Results: The incidence of type 2 diabetes increased with increasing waist circumference-years, with an adjusted risk increase of 38% (95% CI: 31−47%) for each additional 50 waist circumference-years, and this rate was similar across gender and age groups. The area under the curve of waist circumference-years (0.743) was greatest in the receiver operating characteristic curve (ROC) analysis compared to baseline waist circumference (0.731) and the waist-height ratio (0.728) (p < 0.05). Conclusion: The waist circumference-years construct is closely associated with an increased risk of type 2 diabetes and may be a stronger predictor of type 2 diabetes risk than baseline waist circumference or the waist-height ratio.

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.

Prevalence of hyperglycemia in masters athletes

Background

Ageing is associated with decreased physical activity, obesity and subsequently an increased risk of developing type 2 diabetes mellitus (T2dm). Master athletes (MA) have initiated exercise or sport later in life or pursued a physically active lifestyle for an extended period. Subsequently, MAs have been proposed as a model of successful ageing as this active lifestyle is associated with health benefits including decreased health risk of chronic diseases and a reduction in premature mortality. Given long-term physical activity/exercise has previously been shown to be protective against hyperglycemia, a risk factor for T2dm, it is plausible that MA may have protective benefit against developing hyperglycemia. Therefore, the aim of this study was to investigate the prevalence of hyperglycemia via fasting plasma glucose (FPG) in MAs competing at the World Masters Games (WMG).

Methods

This cross-sectional, observational survey utilized an online survey using open-source web-based software was used to investigate MAs physiological and medical-related parameters. Over 28,000 MAs competed in the WMG, of which 8,072 MAs completed the survey. Of these MAs, a total of 486 (males 277, females 209; range 27 to 91 years, mean age 55.1 ± 10.2 years) attained recent pathology results which included FPG which was subsequently analyzed for this study. FPG and other outcome variables were compared between genders and to the Australian and United States general population.

Results

Mean FPG for MAs was 5.03 mmol (±1.2, 95% CI [4.9-5.1] mmol) with majority (75.5%) of MAs reporting a normal (<5.5 mmol) FPG, followed by pre-diabetes (20.2%, >5.51 to <5.99 mmol) and abnormal (4.3%, >7.0 mmol). There was no significant difference (P = 0.333) in FPG between genders however, males had a slightly higher (+2.1%) FPG as compared to females (5.08 ± 1.2 mmol (95% CI [4.9-5.22] mmol) versus 4.98 ± 1.1 mmol (95% CI 4.8-5.1 mmol)). The majority of males (71.8%) and females (80.3%) were classified with a normal FPG. With regard to an abnormal FPG level, only 4.0% of males and 4.9% of females were classified abnormal which was suggestive of undiagnosed T2dm. With regard to age by decade, there was no significant difference (P = 0.06-1.00) between age groups and no relationship between the MAs' age and FPG (r = .054, P = 0.24). As a group, MAs had a significantly lower FPG as compared to the Australian (-3.2%, P = 0.005) and United States general populations (-13.9%, P < 0.001).

Conclusions

Most, however not all, MAs were found to have normal glycaemia, with only a small percentage indicating a risk of developing T2dm (i.e., impaired fasting glucose) and a smaller percentage identified with an abnormal FPG, suggestive of T2dm. These findings suggest MAs appear to be at low metabolic risk for developing T2dm based upon FPG and the physical activity/exercise they complete as MAs may indeed be protective against hyperglycemia whilst maintaining an active lifestyle.

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model’s goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (β = 0.189−0.373, p < 0.001), fasting glucose (β = 0.168−0.199, p < 0.001) and systolic blood pressure (β = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.

Prevalence of Cardiometabolic Syndrome and its Association With Body Shape Index and A Body Roundness Index Among Type 2 Diabetes Mellitus Patients: A Hospital-Based Cross-Sectional Study in a Ghanaian Population

Cardiometabolic syndrome (MetS) is closely linked to type 2 diabetes mellitus (T2DM) and is the leading cause of diabetes complications. Anthropometric indices could be used as a cheap approach to identify MetS among T2DM patients. We determined the prevalence of MetS and its association with sociodemographic and anthropometric indices among T2DM patients in a tertiary hospital in the Ashanti region of Ghana. A comparative cross-sectional study was conducted among 241 T2DM outpatients attending the Komfo Anokye Teaching Hospital (KATH) and the Kumasi South Hospital for routine check-up. Sociodemographic characteristics, clinicobiochemical markers, namely, systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), and glycated hemoglobin (HbA1C) were measured. Anthropometric indices, namely, body mass index (BMI), Conicity index (CI), body adiposity index (BAI), A body shape index (ABSI), body roundness index (BRI), Waist-to-hip ratio (WHR), and Waist-to-height ratio (WHtR) were computed based on either the Height, Weight, Waist circumference (WC) or Hip circumference (HC) of the patients. Metabolic syndrome (MetS) was classified using the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) criteria. Data entry and analysis were done using Excel 2016 and SPSS version 25.0 respectively. Of the 241 T2DM patients, 99 (41.1%) were males whereas 144 (58.9%) were females. The prevalence of cardiometabolic syndrome (MetS) was 42.7% with dyslipidemia and hypertension recording a prevalence of 6.6 and 36.1%, respectively. Being a female T2DM patient [aOR = 3.02, 95%CI (1.59-5.76), p = 0.001] and divorced [aOR = 4.05, 95%CI (1.22-13.43), p = 0.022] were the independent sociodemographic predictors of MetS among T2DM patients. The 4th quartile for ABSI and 2nd to 4th quartiles for BSI were associated with MetS on univariate logistic regression (p <0.05). Multivariate logistic regression identified the 3rd quartile (aOR = 25.15 (2.02-313.81), p = 0.012) and 4th quartile (aOR = 39.00, 95%CI (2.68-568.49), p = 0.007) for BRI as the independent predictors of MetS among T2DM. The prevalence of cardiometabolic syndrome is high among T2DM patients and this was influenced by female gender, being divorced, and increased BRI. Integration of BRI as part of routine assessment could be used as early indicator of cardiometabolic syndrome among T2DM patients.

Genome-wide association study identifies genetic risk loci for adiposity in a Taiwanese population

Overweight and obese are risk factors for various diseases. In Taiwan, the combined prevalence of overweight and obesity has increased dramatically. Here, we conducted a genome-wide association study (GWAS) on four adiposity traits, including body-mass index (BMI), body fat percentage (BF%), waist circumference (WC), and waist-hip ratio (WHR), using the data for more than 21,000 subjects in Taiwan Biobank. Associations were evaluated between 6,546,460 single-nucleotide polymorphisms (SNPs) and adiposity traits, yielding 13 genome-wide significant (GWS) adiposity-associated trait-loci pairs. A known gene, FTO, as well as two BF%-associated loci (GNPDA2-GABRG1 [4p12] and RNU6-2-PIAS1 [15q23]) were identified as pleiotropic effects. Moreover, RALGAPA1 was found as a specific genetic predisposing factor to high BMI in a Taiwanese population. Compared to other populations, a slightly lower heritability of the four adiposity traits was found in our cohort. Surprisingly, we uncovered the importance of neural pathways that might influence BF%, WC and WHR in the Taiwanese (East Asian) population. Additionally, a moderate genetic correlation between the WHR and BMI (γg = 0.52; p = 2.37×10−9) was detected, suggesting different genetic determinants exist for abdominal adiposity and overall adiposity. In conclusion, the obesity-related genetic loci identified here provide new insights into the genetic underpinnings of adiposity in the Taiwanese population.

Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

BACKGROUND

The accurate assessment of total body and regional body circumferences, volumes, and compositions are critical to monitor physical activity and dietary interventions, as well as accurate disease classifications including obesity, metabolic syndrome, sarcopenia, and lymphedema. We assessed body composition and anthropometry estimates provided by a commercial 3-dimensional optical (3DO) imaging system compared to criterion measures.

METHODS

Participants of the Shape Up! Adults study were recruited for similar sized stratifications by sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and across five ethnicities (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander). All participants received manual anthropometry assessments, duplicate whole-body 3DO (Styku S100), and dual-energy X-ray absorptiometry (DXA) scans. 3DO estimates provided by the manufacturer for anthropometry and body composition were compared to the criterion measures using concordance correlation coefficient (CCC) and Bland-Altman analysis. Test-retest precision was assessed by root mean square error (RMSE) and coefficient of variation.

RESULTS

A total of 188 (102 female) participants were included. The overall fat free mass (FFM) as measured by DXA (54.1 ± 15.2 kg) and 3DO (55.3 ± 15.0 kg) showed a small mean difference of 1.2 ± 3.4 kg (95% limits of agreement -7.0 to +5.6) and the CCC was 0.97 (95% CI: 0.96-0.98). The CCC for FM was 0.95 (95% CI: 0.94-0.97) and the mean difference of 1.3 ± 3.4 kg (95% CI: -5.5 to +8.1) reflected the difference in FFM measures. 3DO anthropometry and body composition measurements showed high test-retest precision for whole body volume (1.1 L), fat mass (0.41 kg), percent fat (0.60%), arm and leg volumes, (0.11 and 0.21 L, respectively), and waist and hip circumferences (all <0.60 cm). No group differences were observed when stratified by body mass index, sex, or race/ethnicity.

CONCLUSIONS

The anthropometric and body composition estimates provided by the 3DO scanner are precise and accurate to criterion methods if offsets are considered. This method offers a rapid, broadly available, and automated method of body composition assessment regardless of body size. Further studies are recommended to examine the relationship between measurements obtained by 3DO scans and metabolic health in healthy and clinical populations.

The effect of metformin on body mass index and metabolic parameters in non-diabetic HIV-positive patients: a meta-analysis

We sought to evaluate the effetc of metformin on body mass index (BMI) and metabolic parameters in HIV-positive patients. We performed a comprehensive search through five major indexing databases, using keywords ("metformin" OR "dimethylguanylguanidine" OR "biguanide" OR "Glucophage") AND ("HIV" OR "human immunodeficiency virus" OR "AIDS" OR "Acquired immunodeficiency syndrome"), and all possible combinations until January 15, 2021. We measured standardized mean differences (SMD) and 95% confidence intervals (CI) for each outcome. We finally included 12 RCTs (577 participants, 274 in the metformin group and 303 in the comparators). Metformin did not significantly change BMI index compared to various comparators. Metformin generally improve LDL levels (SMD = 0.29, 95% CI: - 1.00 1.57, P = 0.01), HDL levels (SMD = - 0.15, 95% CI: - 0.72 0.41, P = 0.001), triglycerides values (SMD = 0.46, 95% CI: - 0.36 1.27, P < 0.00001), fasting glucose (SMD = - 0.82, 95% CI: - 1.80 0.15, P < 0.00001), insulin 120 min (SMD = - 0.82, 95% CI: - 1.59-0.04, P = 0.02), and glucose 120 min (SMD = - 1.24, 95% CI: - 2.57 0.10, P < 0.0001), but worsened total cholesterol values (SMD = 1.24, 95% CI: - 0.98 3.46, P = 0.0001). Metformin is safe for weight loss in obese people; however, this drug may not be suitable for everyone, especially those who are not overweight. Nevertheless the body of evidences may suggest that metformin had promising impacts on metabolic parameters in patients with both HIV, it is still unknown that such surrogate changes will translate to long-standing clinical advantages.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00869-1.

Obesity Measures as Predictors of Type 2 Diabetes and Cardiovascular Diseases among the Jordanian Population: A Cross-Sectional Study

Obesity is strongly associated with cardiovascular diseases (CVD) and type 2 diabetes (T2D). This study aimed to use obesity measures, body mass index (BMI) and waist circumference (WC) to predict the CVD and T2D risk and to determine the best predictor of these diseases among Jordanian adults. A cross-sectional study was conducted at the governmental and military hospitals across Jordan. The study participants were healthy or previously diagnosed with CVD or T2D. The continuous variables were compared using ANOVA, and the categorical variables were compared using the X2 test. The multivariate logistic regression was used to predict CVD and T2D risk through their association with BMI and WC. The final sample consisted of 6000 Jordanian adults with a mean age of 41.5 ± 14.7 years, 73.6% females. The BMI (OR = 1.7, CI: 1.30-2.30, p < 0.001) was associated with a higher risk of T2D compared to WC (OR = 1.3, CI: 1.04-1.52, p = 0.016). However, our results showed that BMI was not associated with CVD risk, while the WC was significantly and positively associated with CVD risk (OR = 1.9, CI: 1.47-2.47, p < 0.001). In conclusion, an elevated BMI predicts a higher risk of T2D, while WC is more efficient in predicting CVD risk. Our results can be used to construct a population-specific intervention to reduce the risk of CVD and T2D among adults in Jordan and other countries with similar backgrounds.

Adiposity and Long-Term Adiposity Change Are Associated with Incident Diabetes: A Prospective Cohort Study in Southwest China

In order to estimate the associations of different adiposity indicators and long-term adiposity changes with risk of incident type 2 diabetes (T2DM), we conducted a 10-year prospective cohort study of 7441 adults in Guizhou, China, from 2010 to 2020. Adiposity was measured at baseline and follow-up. Cox proportional hazard models were used to estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs). A total of 764 new diabetes cases were identified over an average follow-up of 7.06 years. Adiposity indicators, body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), and long-term adiposity changes (both weight change and WC change) were significantly associated with an increased risk of T2DM (adjusted HRs: 1.16–1.48). Significant non-linear relationships were found between weight/WC change and incident T2DM. Compared with subjects with stable WC from baseline to follow-up visit, the subjects with WC gain ≥9 cm had a 1.61-fold greater risk of T2DM; those with WC loss had a 30% lower risk. Furthermore, the associations were stronger among participants aged 40 years or older, women, and Han Chinese. Preventing weight or WC gain and promoting maintenance of normal body weight or WC are important approaches for diabetes prevention, especially for the elderly, women, and Han Chinese.

The Link between Type 2 Diabetes Mellitus and the Polymorphisms of Glutathione-Metabolizing Genes Suggests a New Hypothesis Explaining Disease Initiation and Progression

The present study investigated whether type 2 diabetes (T2D) is associated with polymorphisms of genes encoding glutathione-metabolizing enzymes such as glutathione synthetase (GSS) and gamma-glutamyl transferase 7 (GGT7). A total of 3198 unrelated Russian subjects including 1572 T2D patients and 1626 healthy subjects were enrolled. Single nucleotide polymorphisms (SNPs) of the GSS and GGT7 genes were genotyped using the MassArray-4 system. We found that the GSS and GGT7 gene polymorphisms alone and in combinations are associated with T2D risk regardless of sex, age, and body mass index, as well as correlated with plasma glutathione, hydrogen peroxide, and fasting blood glucose levels. Polymorphisms of GSS (rs13041792) and GGT7 (rs6119534 and rs11546155) genes were associated with the tissue-specific expression of genes involved in unfolded protein response and the regulation of proteostasis. Transcriptome-wide association analysis has shown that the pancreatic expression of some of these genes such as EDEM2, MYH7B, MAP1LC3A, and CPNE1 is linked to the genetic risk of T2D. A comprehensive analysis of the data allowed proposing a new hypothesis for the etiology of type 2 diabetes that endogenous glutathione deficiency might be a key condition responsible for the impaired folding of proinsulin which triggered an unfolded protein response, ultimately leading to beta-cell apoptosis and disease development.

Associations between obesity indices and both type 2 diabetes and impaired fasting glucose among West African adults: Results from WHO STEPS surveys

BACKGROUND AND AIM

Various obesity indices such as BMI, waist circumference (WC), waist-hip ratio, (WHR) and waist-to-height ratio (WHtR) are associated with the risk of type 2 Diabetes Mellitus (T2DM). Given few studies examining the strength of the association in this population, we aimed to identify which obesity indices are most strongly associated with T2DM and impaired fasting glucose (IFG) among adults from five West African countries.

METHODS AND RESULTS

Data from 15,520 participants from the World Health Organisation (WHO) STEPs surveys in Burkina Faso, Benin, Mali, Liberia, and Ghana were included in analyses. Multinomial logistic regression was used to calculate the relative risk (RR) per standard deviation (SD) of each anthropometric measure, modelled as both continuous variables and as categorical variables based on established cut-points. In the analyses with continuous variables, the unadjusted RRs for T2DM per SD were 1.30 (1.23, 1.37) for body mass index (BMI); 1.56 (1.46, 1.67) for WC; 2.57 (2.15, 3.09) for WHtR and 1.16 (1.03, 1.31) for WHR. WHtR showed the strongest association with T2DM in all adjusted analyses. For models using categorical variables based on established cut-points, obesity defined using waist circumference (OB-WC) and OB-BMI showed the strongest associations with T2DM, and OB-WHR, the weakest association in all adjusted analyses.

CONCLUSION

WHtR and WC appear to be the indices most strongly associated with T2DM and IFG respectively. Given its simplicity, WC may be the metric that most usefully conveys risk for T2DM in West African adults.

Relevance of anthropometric measurements as predictors of prevalent diabetes type 2: a cross-sectional study on a Norwegian population

OBJECTIVES

The objective was to determine the predictive potential of anthropometric indices to screen prevalent diabetes mellitus type 2 in a Norwegian population.

DESIGN

This is a cross-sectional design to determine the potential association of waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), waist circumference (WC) and body mass index (BMI) with prevalent diabetes mellitus type 2 through logistic regression analysis. Receiver operating characteristic (ROC) curves were used to determine the predictive potential of the anthropometric indices. Youden's index was applied to determine the optimal cut-off points for each anthropometric index.

SETTING

This study used cross-sectional data from the populations-based Health Study in Nord-Trøndelag which invited all citizens in the county above 20 years of age.

PARTICIPANTS

This study included all those who were non-pregnant and had complete data (N=50 042), 98.5% of the participants. The sample is to be considered representative for the population of Norway.

PRIMARY AND SECONDARY OUTCOME MEASURES

OR and ROC of the potential association between diabetes mellitus type 2 and anthropometric indices were the main planned and performed outcome measures.

RESULTS

The results suggest that the anthropometric indices performed differently within the Norwegian population with WHR and WHtR being the stronger predictor with (ROC) of 0.746 (0.735 to 0.757) and 0.741 (0.730 to 0.752). The predictive potential for the investigated anthropometric indices was generally stronger for women than men.

CONCLUSION

Anthropometric indices of size BMI and the highly correlated WC are less associated with prevalent diabetes mellitus type 2 than WHR (WC adjusted for hip circumference) or WHtR (WC adjusted for height) in a Norwegian population.

A 16-year prospective cohort study to evaluate effects of long-term fluctuations in obesity indices of prediabetics on the incidence of future diabetes

This study aimed to evaluate the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in the future. This study was conducted among 1228 prediabetics. The patterns of changes in obesity indices based on three measurements including first, mean values during the follow-up period, and last visit from these indices were evaluated by using the latent Markov model (LMM). The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities. Based on a long-term evaluation of patterns of changes in obesity indices, our results reemphasized the values of all five obesity indices in clinical settings for identifying high-risk prediabetic subjects for developing diabetes in future and the need for more effective obesity prevention strategies.

Epidemiology and risk factors for diabetes in the suburbs of Beijing: a retrospective cohort study

OBJECTIVE

We aimed to detect the incidence and risk factors of type 2 diabetes mellitus (T2DM) development in the suburbs of Beijing.

DESIGN

Cohort study with record linkage to incidence data.

SETTING

We performed a 5-year follow-up study in a randomly selected suburban population including 1114 subjects aged ≥18 years living in the suburbs of Beijing.

PARTICIPANTS

118 subjects with T2DM at baseline according to the 1999 WHO criteria were excluded, and 895 subjects attended the follow-up assessment in 2012. The non-diabetic subjects at baseline were classified into two groups: normal glucose tolerance (NGT) group (n=673) and impaired glucose regulation (IGR) group(n=222).The incidence and risk factors of diabetes development in each group were investigated.

OUTCOME MEASURES

A structured questionnaire about sociodemographic characteristics, height, weight, waist circumference, hip circumference, blood pressure, oral glucose tolerance test and serum lipid levels.

RESULTS

Out of the 895 non-diabetic subjects, 67 developed diabetes with 29 in the NGT group and 38 in the IGR group, respectively, after a 5-year follow-up, producing an overall 5-year cumulative incidence of diabetes of 13%. The incidence of diabetes was 15.5 cases per 1000 person-years, 8.9 cases per 1000 person-years in the NGT group and 35.7 cases per 1000 person-years in the IGR group (p<0.01; RR 4.03; 95% CI 2.58 to 9.29). Binary logistic regression analysis showed that the risk factors for diabetes development included fasting plasma glucose (FPG) in the NGT group, and sex, the waist-to-hip ratio, FPG and diastolic blood pressure (DBP) in the IGR group.

CONCLUSIONS

During a mean follow-up of 5.0 years, the incidence of T2DM in the suburbs of Beijing was 15.5 per 1000 person-years. Early prevention of diabetes should focus on IGR subjects. Elevated FPG predicted diabetes development for both NGT and IGR subjects. Female sex, overweight/obesity and DBP are risk factors for diabetes development in IGR subjects.

Predicting the risk of type 2 diabetes through anthropometric indices in Pakistani adults- A sub-analysis of second National diabetes survey of Pakistan 2016-2017 (NDSP-07)

BACKGROUND AND AIM

Excess adiposity is associated with an increased risk of diabetes. Amongst the various measures of adiposity, the most appropriate one to predict the risk of diabetes remains debatable. Therefore, the aim of this study was to compare the ability of body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) in predicting type 2 diabetes mellitus (DM) among Pakistani adults.

SUBJECTS AND METHODS

This was the sub-analysis of a large population based Second National Diabetes Survey of Pakistan (NDSP) 2016-2017. With this survey, 10834 individuals were recruited and 4788 individuals fulfilled the inclusion criteria for this sub-analysis (subjects with missing anthropometric details were excluded). Participants were categorized into two groups; subjects with type 2 DM and subjects without DM. Data of participants was collected via pre-designed detailed questionnaire. Clinical and anthropometric measurements were measured using standardized techniques.

RESULTS

Out of 4788 individuals, 3085(64.4%) were non-DM subjects and 1703(35.6%) were type 2 DM subjects with mean age of 39.78 ± 13.79 and 50.38 ± 11.33 years, respectively. Logistic regression analysis revealed a significant association of WC with type 2 diabetes after adjustment for possible confounders. Area under the curve (AUC) of WC was found higher than AUC of BMI and WHR.

CONCLUSION

The findings from second NDSP (2016-2017) demonstrated that WC is a better marker than WHR and BMI in predicting type 2 DM for Pakistani population.

Strong Association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with Diabetes: A Population-Based Cross-Sectional Study in Jilin Province, China

BACKGROUNDS

The prevalence of diabetes has increased with the increase of obesity, and finding indicators to predict diabetes risk has become an urgent need. The purpose of this study is to compare the correlation between four anthropometric indices and the prevalence of diabetes.

METHODS

A total of 4052 participants aged 40 years and above were selected in Dehui City, Jilin Province, using a multistage stratified whole group sampling method. Face-to-face interviews and physical examinations were conducted. Multivariate logistic analysis was used. The values of BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were divided into quartiles (Q1: <25%; Q2: ~25%; Q3: ~50%; and Q4: ~75%). The median of each quartile was used for a linear trend test.

RESULTS

For all four body fat-measuring indices of body mass index (adjusted OR: 3.300, 95% CI: 2.370, 4.595), WC (adjusted OR: 5.131, 95% CI: 3.433, 7.669), WHR (adjusted OR: 3.327, 95% CI: 2.386, 4.638), and WHtR (adjusted OR: 5.959, 95% CI: 3.922, 9.054), patients in the highest quartile were more likely to have diabetes than those in the lowest quartile. The areas under the curve of WHtR, WC, WHR, and BMI for diabetes were 0.683, 0.669, 0.654, and 0.629, respectively. In female participants, the areas under the curve of the waist-height ratio and WC were 0.710 (95% CI: 0.679-0.741) and 0.701 (95% CI: 0.670-0.732), respectively.

CONCLUSIONS

The WC and WHtR were more closely related to diabetes than BMI and WHR among study participants ≥ 40 years of age, especially in females.

Interaction of General or Central Obesity and Hypertension on Diabetes: Sex-Specific Differences in a Rural Population in Northeast China

PURPOSE

Some studies have established an association between hypertension or obesity and the risk of diabetes. This study aimed to examine the interaction of hypertension and obesity on diabetes.

PARTICIPANTS AND METHODS

The data of 11,731 Chinese men and women were analyzed from the 2012-2013 Northeast China Rural Cardiovascular Health Study. The interaction was examined by both additive and multiplicative scales. General obesity was measured by body mass index (BMI); central obesity was defined by waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHpR).

RESULTS

After controlling for potential confounders, the odds ratios for diabetes were 3.864 (3.205-4.660), 4.500 (3.673-5.514), 4.932 (3.888-6.255) and 4.701 (3.817-5.788) for the combinations of hypertension and BMI, WC, WHtR or WHpR, respectively, which had the highest risk of diabetes among the four combinations. Notwithstanding the multiplicative interactions showed statistically significant in all analyses, the results of additive interactions were not consistent, suggesting the diabetes risk from female BMI (relative excess risk due to interaction (RERI): 1.136, 95% CI: 0.127-2.146, attributable proportion due to interaction (AP): 0.267, 95% CI: 0.057-0.477, synergy index (S):1.536, 95% CI: 1.017-2.321) or female WHpR (RERI: 1.076, 95% CI: 0.150-2.002, AP:0.205, 95% CI: 0.037-0.374, S:1.340, 95% CI: 1.012-1.775) was additive to the risk from hypertension.

CONCLUSION

The findings suggest that high BMI and high WHpR have synergistic interactions with hypertension on the risk of diabetes for females. The results of this study also suggest that BMI and WHpR, rather than WC, should be used for the diagnosis of metabolic syndrome in Chinese population.

Magnitude of missed opportunities for prediabetes screening among non-diabetic adults attending the family practice clinic in Western Nigeria: Implication for diabetes prevention

BACKGROUND

For many decades, hypertension guidelines recommended dual-arm blood pressure measurement. However, this practice is poor in Nigeria and its significance is largely unidentified. Hence, this study was done to determine the point prevalence of inter-arm blood pressure difference and its relationship with hypertension and diabetes mellitus.

METHODS

A cross-sectional study was conducted among 214 respondents at the general outpatient clinic of a tertiary hospital in Nigeria. Demographic characteristics and anthropometric indices were obtained. Blood pressure readings were obtained through sequentially repeated measurements in respondents' arms.

RESULTS

One-hundred and eighty-six respondents had complete data given a completion rate of 86.9%. Systolic blood pressure was higher on the right and left arm in 102 (54.8%) and 56 (30.1%) of the respondents, respectively. Diastolic blood pressure was higher on the right and left arm in 73 (39.2%) and 63 (33.9%) of the respondents, respectively. The overall prevalence of significant systolic inter-arm difference (≥ 10 mmHg) and diastolic inter-arm difference (≥ 10 mmHg) were 24.2% and 18.8%, respectively. Significant systolic inter-arm difference (p = 0.033) and diastolic inter-arm difference (p = 0.01) were significantly more among respondents with hypertension and/or diabetes mellitus.

CONCLUSION

The blood pressure readings in both arms were different among the majority of the respondents, being higher on the right arm in many of them. The prevalence of significant inter-arm difference was high in the unselected primary care patients studied especially among patients with hypertension and/or diabetes mellitus. Blood pressure measurement in both arms should become a routine practice during initial patients' visits in primary care.

The added value of periodontal measurements for identification of diabetes among Saudi adults

BACKGROUND

The aims of this study were to develop a prediction model for identification of individuals with diabetes based on clinical and perceived periodontal measurements; and to evaluate its added value when combined with standard diabetes screening tools.

METHODS

The study was carried out among 250 adults attending primary care clinics in Riyadh (Saudi Arabia). The study adopted a case-control approach, where diabetes status was first ascertained, and the Finnish Diabetes Risk Score (FINDRISC), Canadian Diabetes Risk questionnaire (CANRISK), and periodontal examinations were carried out afterward.

RESULTS

A periodontal prediction model (PPM) including three periodontal indicators (missing teeth, percentage of sites with pocket probing depth ≥6 mm, and mean pocket probing depth) had an area under the curve (AUC) of 0.694 (95% Confidence Interval: 0.612-0.776) and classified correctly 62.4% of participants. The FINDRISC and CANRISK tools had AUCs of 0.766 (95% CI: 0.690-0.843) and 0.821 (95% CI: 0.763-0.879), respectively. The addition of the PPM significantly improved the AUC of FINDRISC (P = 0.048) but not of CANRISK (P = 0.144), with 26.8% and 9.8% of participants correctly reclassified, respectively. Finally, decision curve analysis showed that adding the PPM to both tools would result in net benefits among patients with probability scores lower than 70%.

CONCLUSIONS

This study showed that periodontal measurements could play a role in identifying individuals with diabetes, and that addition of clinical periodontal measurements improved the performance of FINDRISC and CANRISK.

Added and Free Sugars Intake and Metabolic Biomarkers in Japanese Adolescents

Reduction in the intakes of added and free sugars is a recommendation to lower cardiometabolic risks. Sugars intake is considered lowest in the Asian-Pacific region, particularly Japan. We examined the association between sugars intake and cardiometabolic risks in Japanese adolescents. We included 3242 students (mean age, 13.56 years) living in Shunan City, Japan, between 2006 and 2010. Sugars intake was estimated using the brief-type self-administered diet history questionnaire. Anthropometrics, serum lipids, fasting plasma glucose, and blood pressure were measured. Metabolic syndrome was determined by the combination of overweight and other risks. Intakes of added and free sugars were 7.6–7.9%E and 8.4–8.8%E of the total energy intake (%E), respectively. Categories based on quintiles of added or free sugars intakes were associated with fasting glucose, systolic blood pressure, and the z-score of metabolic syndrome (P_trend ≤ 0.025). Other than the association between added sugars ≥10%E and high glucose (odds ratio 1.51, 95% confidence interval 1.04–2.19, p = 0.031), non-significantly high intakes of added or free sugars for risks occurred. Association was observed between added or free sugars intake and cardiometabolic biomarkers in Japanese adolescents, and added sugars intake <10%E could prevent glucose intolerance but not metabolic syndrome.

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta-analysis

Body roundness index (BRI) is a new anthropometric index developed to predict both body fat and the percentage of visceral adipose tissue. Our aim was to investigate whether BRI is superior to traditional anthropometric indices in predicting metabolic syndrome (MetS). This systematic review and meta-analysis was conducted using Pubmed, Scopus and Web of Sciences databases. The estimated pooled areas under curve (AUCs) for BRI predicting MetS was higher than body mass index (BMI), waist-to-hip ratio (WHR), body shape index (ABSI) and body adiposity index (BAI), similar to waist circumference (WC) and lower than waist-to-height ratio (WHtR). However, the difference between BRI and BMI, WC and WHtR predicting MetS was statistically non-significant. Similar results were found with the summary receiver operating characteristic curve (AUC-SROC). In addition, the non-Chinese population had pooled AUCs greater than the Chinese population for all indices. Pooled ORs showed that BRI is associated with an increased MetS risk. In conclusion, BRI had good discriminatory power for MetS in adults of both sexes from diverse populations (AUC > 0.7; AUC-SROC>0.7). However, WC and WHtR offer the best performance when screening for MetS, and non-significant differences were found with BRI. In contrast, BRI was superior to BMI, WHR, ABSI and BAI in predicting MetS.

Prevalence and associated risk factors of general and abdominal obesity in rural and urban women in Bangladesh

Background

Obesity is a major public health concern worldwide including Bangladesh. This study aimed to assess the prevalence and associated risk factors of general and abdominal obesity in rural and urban women in Bangladesh.

Methods

A total of 450 adult women aged ≥ 18 years were recruited from rural (n = 210) and urban (n = 240) areas of four administrative regions (Chattagram, Dhaka and Rajshahi and Sylhet) of Bangladesh. Both socio-demographic and anthropometric data were recorded in this study. WHO proposed cut-off values were used for the Asian population for defining general and abdominal obesity. Multinomial logistic regression analysis was applied to evaluate the risk factors of general and abdominal obesity for Bangladeshi women.

Results

Overall, the prevalence of general and abdominal obesity was 28% and 49%, respectively. Urban women had a significantly higher prevalence of both general and abdominal obesity (30.9% and 58.6%, respectively) than in the rural women (26.6% and 38.1%, respectively) (p<0.05 and p<0.01, respectively). As region comparison, the prevalence of general obesity was higher in the Dhaka region (39.3%) compared to the Chattragram (23.3%), Rajshahi (23.9%) and Sylhet (3.5%) regions. On the other hand, abdominal obesity was more frequent among participants in Sylhet (72.4%) and Dhaka regions (61.5%), compared to the Chattagram (27.4%) and Rajshahi (37.3%) regions. A wide variation has been observed on the prevalence of general and abdominal obesity in the different age groups of the four regions. In regression analysis, a high socioeconomic status (ref: low socioeconomic level), low education level (ref: higher education), low physical activity (ref: adequate physical activity) and middle age (ref: ≥ 30 years of age) were significant risk factors for general and abdominal obesity.

Conclusions

The prevalence of general and abdominal obesity was higher among participants living in urban areas. Physical inactivity, middle age, high socioeconomic status and low education level were associated with the increased prevalence of general and abdominal obesity. Such a high prevalence of general and abdominal obesity is a health concern for Bangladeshi women; therefore, public awareness and effective health intervention strategies are needed to address these conditions.

Waist Circumference and its Changes Are More Strongly Associated with the Risk of Type 2 Diabetes than Body Mass Index and Changes in Body Weight in Chinese Adults

BACKGROUND

The associations of different adiposity indicators and short-term adiposity change with diabetes risk are not fully elucidated.

OBJECTIVE

We aimed to assess the independent and joint effects of different baseline adiposity indicators and short-term body adiposity change on the risk of type 2 diabetes.

METHODS

We prospectively followed 10,419 Chinese adults aged 20-80 y in 2008-2012. Incident diabetes was diagnosed based on fasting glucose, 2-h glucose, or glycated hemoglobin (HbA1c) after an oral glucose tolerance test using the American Diabetes Association standard. Cox proportional hazard regression models were used to assess the associations of adiposity indicators and adiposity change with diabetes risk.

RESULTS

During a mean follow-up of 2.8 y, we identified 805 type 2 diabetes cases. Baseline BMI, waist circumference, and waist-height ratio (WHtR) were all positively associated with diabetes risk. The area under the curve was significantly greater for waist circumference (0.624) and WHtR (0.627) than for BMI (0.608) (P <0.05). Compared with subjects with stable adiposity levels (±2 kg or ± 3 cm in changes in body weight or waist circumference) from baseline to Year 1, those subjects with the most weight gain or the most waist circumference gain had a 1.53-fold or 1.37-fold greater risk of diabetes; those with the most weight loss had a 46% lower risk of diabetes. Furthermore, regardless of baseline weight status, weight or waist circumference change in the first year was associated with diabetes risk.

CONCLUSION

Abdominal adiposity indicators, waist circumference and its change, are more strongly associated with the risk of type 2 diabetes than general adiposity indicators, BMI, and changes in body weight among Chinese adults.

A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study

AIMS

Obesity measurement is a vital component of most type 2 diabetes screening tests; while studies had shown that waist circumference (WC) is a better predictor in South Asians, there is evidence that BMI is also effective. Our objective was to evaluate the efficacy of BMI_WC, a composite measure, against BMI and WC.

METHODS

Using data from a nationwide randomized cluster sample survey (NMB-2017), we analyzed 7496 adults at high risk for type 2 diabetes. WC, BMI, and BMI_WC were evaluated using Odds Ratio (OR), and Classification scores (Sensitivity, Specificity, and Accuracy). These were validated using Indian Diabetes Risk Score (IDRS) by replacing WC with BMI and BMI_WC, and calculating Sensitivity, Specificity, and Accuracy.

RESULTS

BMI_WC had higher OR (2·300) compared to WC (1·87) and BMI (2·26). WC, BMI, and BMI_WC were all highly Sensitive (0·75, 0·81, 0·70 resp.). But BMI_WC had significantly higher Specificity (0.36) when compared to WC and BMI (0.27 each). IDRS_WC, IDRS_BMI, and IDRS_BMIWC were all highly Sensitive (0·87, 0·88, 0·82 resp.). But IDRS_BMIWC had significantly higher Specificity (0·39) compared to IDRS_WC and IDRS_BMI (0·30, 0·31 resp.).

CONCLUSIONS

Both WC and BMI are good predictors of risk for T2DM, but BMI_WC is a better predictor, with higher Specificity; this may indicate that Indians with high values of both central (high WC) and general (BMI > 23) obesity carry higher risk for type 2 diabetes than either one in isolation. Using BMI_WC in IDRS improves its performance on Accuracy and Specificity.

Obesity and Body Composition in Man and Woman: Associated Diseases and the New Role of Gut Microbiota

BACKGROUND

Obesity is now recognized as a worldwide health issue and has reached epidemic proportions, affecting both developed and developing countries. The World Obesity Federation stated that "Obesity is a chronic relapsing disease process": as a result, obesity has been recognized internationally as a chronic disease. The primary cause of the metabolic syndrome and increase of the cardiovascular risk have been identified in "sick fat", a condition then defined as adiposopathy. Heart attacks, strokes and renal failures are pathologies that have mid-risk factors such as dyslipidemia, hypertension and diabetes, which in turn are caused by obesity, whose primary risk factor is represented by the diet. The aim of the present review is to consider the importance of body composition, together with chronic inflammation and a new gut microbiota data that may turn out to be crucial elements of some target treatment of human obesity.

METHODS

In this review, we performed research using PubMed database reviewing the evidence in the literature of evidence information regarding the link between obesity and body composition in the development of metabolic disease via inflammation markers and in particular, the new role exerted by gut microbiota.

RESULTS

Several papers were evaluated searching for differences in fat mass and disease risk. We also identified the same papers dealing with differences in body composition and metabolic syndrome. Our attention focuses also on a new frontier of gut microbiota composition in the body weight decrease and anti-inflammatory effects.

CONCLUSION

To the saving of lean mass, for the prevention of cardiometabolic diseases, also considering the relationship with obesity, it is necessary to reduce the inflammatory state, acting on the gut-microbiota and on the intestinal permeability. To improve the health of the intestinal flora, we propose a 4P medicine and treatment with probiotics, prebiotics, postbiotics, and polyphenols.

Pre-acculturation as a risk factor for obesity: Findings from the Health of Philippine Emigrants Study (HoPES)

Immigrants to the United States may have an advantage in terms of healthier weight, but tend to gain excessive weight after arrival, and may suffer from obesity and related health conditions. Acculturation theory suggests that this increase in obesity risk is due to adoption of unhealthy western dietary behaviors, and assumes that "eastern/traditional" dietary behaviors prior to migration are healthier. While this assumption is supported by studies conducted several decades ago, the phenomenon of globalization that has risen since the 1990s has increased exposure to western ideas and behaviors in communities worldwide. Hence, today's immigrants are more likely to have already adopted less healthy behaviors that increase obesity risk prior to their arrival in the U.S., a phenomenon we term "pre-acculturation." The present study investigates the role of pre-acculturation in obesity development among immigrants from the Philippines. Data come from the Health of Philippine Emigrants Study, fielded in 2017 (n = 1632). Pre-acculturation was measured with English proficiency, preparation to migrate, receiving care packages, texting, telephone, or internet contact with friends/family in the U.S. Outcomes included the body mass index (BMI, kg/m2), waist circumference (WC, cm), waist-to-height ratio (WHtR) and waist-to-hip-ratio (WHR). Covariates included age, gender, education, financial strain, physical activity, and diet. Migrants reported greater English proficiency, preparation, and a slightly lower WHtR than non-migrants, but did not differ on BMI, WC, or WHR. Preparation was associated with greater BMI, WC, and WHtR, and the effects of preparation status differed by migration status. Among migrants, more preparation was associated with greater BMI, WC, and WtHR. Further, among non-migrants, texting and telephone communications was related to lower BMI, WC, and WHR. In summary, pre-acculturation may be a risk factor for obesity in the Philippines, suggesting that binary notions of "Western" versus "eastern/traditional" cultures may be too simplistic.

Physical Activity Indicators, Metabolic Biomarkers, and Comorbidity in Type 2 Diabetes

Purpose: This study aimed (1) to compare physical activity (PA) indicators, metabolic biomarkers, and comorbidity, (2) to investigate the relationship between PA indicators and metabolic biomarkers, comorbidity and (3) to identify barriers to PA in patients with type 2 diabetes (T2DM) who are using oral hypoglycaemic agent (OHA) or combined OHA and insulin (OHAiN). Methods: Sixty-one patients were classified as patients using only OHA or combined OHAiN. Metabolic biomarkers (waist-to-hip ratio, body mass index (BMI), lipid profile, glycosylated haemoglobin (HbA1c), fasting blood glucose, comorbidity and PA indicators (self-reported PA, number of steps (NOS), 6-minute walking distance (6MWD)) were assessed. PA perceptions and reasons for inactivity were questioned. Results: The comorbidity (p = .013), low-density lipoprotein-cholesterol (p = .026), total cholesterol (p = .008) and HbA1c (p = .020) were higher and PA level was lower (p = .007) in the OHAiN group. NOS was positively correlated with high-density lipoprotein-cholesterol (p = .037) and negatively correlated with BMI (p = .007). 6MWD was negatively correlated with BMI (p = .014) and comorbidity (p = .004) in the OHA group. BMI was a significant predictor of NOS (adjusted R² = 0.242) and comorbidity for 6MWD (adjusted R² = 0.250) in the OHA group. The majority of the patients (OHA = 34.3%, OHAiN = 42.3%) reported "lack of time" as the most common barrier to PA. Conclusions: This study showed that patients on OHAiN have lower PA levels, poorer metabolic profiles, and higher comorbidity rates than OHA users. PA indicators were related with some metabolic biomarkers and comorbidity in only OHA users. The most common reason for inactivity was "the lack of time" in both groups.

Patterns of Women's Postpartum Weight Retention and Its Associations with Maternal Obesity-Related Factors and Parity

Background: There is not much data on the effects of the timing of gestational weight gain (GWG), pre-pregnancy waist circumference (WC), pre-pregnancy body mass index (BMI), and parity, with postpartum weight retention (PPWR) trajectories. Methods: This study was based on a longitudinal cohort. Latent growth mixture models were applied to identify the latent trajectories of PPWR and test the effects of the predictors on distinct classes of PPWR trajectories. Results: Three PPWR trajectories were identified. About 2.8% (n = 26) of women were classified into Class 1, with an inverted U-shape trajectory; 6.6% (n = 61) were assigned to Class 2, with a rapid increase trajectory; 90.6% (n = 837) were classified into Class 3, with a significant decrease. Women who had a lower pre-pregnancy BMI (β = −0.279), higher pre-pregnancy WC (β = 0.111) and GWG (β = 0.723) were at a higher risk of retaining more weight at 1 month postpartum. Only GWG, especially GWG during late pregnancy, was associated with the rate of PPWR change. Parity was not associated with the changes in PPWR, while, compared to Class 1 trajectory, multiparous women were protected from having a Class 2 trajectory. Conclusions: Early targeted interventions should be taken to prevent women who were primiparous, and/or had a lower pre-pregnancy BMI and higher pre-pregnancy WC and GWG, from excessive PPWR.

The predictive value of weight gain and waist circumference for gestational diabetes mellitus

Objective:

The first objective of this study was to investigate the relationship between gestational diabetes mellitus (GDM) and gestational weight gain (WG), waist circumference (WC), prepregnancy, and gestational body mass index (BMI). The second aim of our study was to assess the ability of WG, WC, prepregnancy, and gestational BMI with special reference to their cut-off points on predicting the risk of GDM in pregnant women in Turkey.

Materials and Methods:

A total of 261 women who underwent screening for GDM with the 75-g glucose tolerance test (GTT) between 24^th and 28^th gestational weeks were included. According to the 75-g oral GTT results, women were classified into two groups: the GDM group and non-GDM group. The data collected included age, parity, plasma glucose level for fasting, 1- and 2-h tests, WC, prepregnancy and gestational BMI, prepregnancy weight, WG during pregnancy, gestational age at birth, and birth weight.

Results:

WC at 20-24 weeks of gestation, prepregnancy BMI, and gestational BMI had a predictive capacity for GDM. According to our results, optimal cut-off points for the best predictive value of GDM were WC of 100 cm with a sensitivity of 84% and specificity of 70%, prepregnancy BMI of 25 kg/m² with a sensitivity of 81.8% and specificity of 76%, and gestational BMI of 28.3 kg/m² with a sensitivity of 75% and specificity of 77.4%.

Conclusion:

The measurement of prepregnancy BMI, gestational BMI, and WC may be useful in predicting the risk of GDM. Pregnant women with increased prepregnancy BMI, gestational BMI, and WC measurements may be susceptible to the development of GDM.

Effects of obesity and a history of gestational diabetes on the risk of postpartum diabetes and hyperglycemia in Chinese women: Obesity, GDM and diabetes risk

OBJECTIVE

To evaluate the independent or combined effects of gestational diabetes (GDM) and pre-pregnancy and postpartum BMI on the odds of postpartum diabetes and hyperglycemia.

METHODS

The study samples included 1263 women with prior GDM and 705 women without GDM. Postpartum 1-7 years diabetes was diagnosed by the standard oral glucose tolerance test.

RESULTS

The multivariable-adjusted odds ratios among women with prior GDM, compared with those without it, were 7.52 for diabetes and 2.27 for hyperglycemia. The multivariable-adjusted odds ratios at different postpartum BMI levels (<24, 24-27.9, and ≥ 28 kg/m²) were 1.00, 2.80, and 8.08 for diabetes (P_trend < 0.001), and 1.00, 2.10, and 4.42 for hyperglycemia (P_trend < 0.001), respectively. Women with high body fat (≥31.9%) or abdominal obesity (≥85 cm) had a 2.7-6.9-fold higher odds ratio for diabetes or hyperglycemia. Women with both obesity and prior GDM had the highest risk of diabetes or hyperglycemia compared with non-obese women without GDM. Non-obese women with prior GDM had the same risk of diabetes and hyperglycemia as non-GDM women with obesity. When using Cox regression models, the results were very close to those using logistic regression models.

CONCLUSIONS

Maternal prior GDM and pre-pregnancy or postpartum obesity contribute equally to postpartum diabetes and hyperglycemia risk.

Comparative effectiveness trial comparing MyPlate to calorie counting for mostly low-income Latino primary care patients of a federally qualified community health center: study design, baseline characteristics

BACKGROUND

Primary care-based behavior change obesity treatment has long featured the Calorie restriction (CC), portion control approach. By contrast, the MyPlate-based obesity treatment approach encourages eating more high-satiety/high-satiation foods and requires no calorie-counting. This report describes study methods of a comparative effectiveness trial of CC versus MyPlate. It also describes baseline findings involving demographic characteristics and their associations with primary outcome measures and covariates, including satiety/satiation, dietary quality and acculturation.

METHODS

A comparative effectiveness trial was designed to compare the CC approach (n = 130) versus a MyPlate-based approach (n = 131) to treating patient overweight. Intervenors were trained community health workers. The 11 intervention sessions included two in-home health education sessions, two group education sessions, and seven telephone coaching sessions. Questionnaire and anthropometric assessments occurred at baseline, 6- and 12 months; food frequency questionnaires were administered at baseline and 12 months. Participants were overweight adult primary care patients of a federally qualified health center in Long Beach, California. Two measures of satiety/satiation and one measure of post-meal hunger comprised the primary outcome measures. Secondary outcomes included weight, waist circumference, blood pressure, dietary quality, sugary beverage intake, water intake, fruit and vegetable fiber intake, mental health and health-related quality of life. Covariates included age, gender, nativity status (U.S.-born, not U.S.-born), race/ethnicity, education, and acculturation.

ANALYSIS

Baseline characteristics were compared using chi square tests. Associations between covariates and outcome measures were evaluated using multiple regression and logistic regression.

RESULTS

Two thousand eighty-six adult patients were screened, yielding 261 enrollees who were 86% Latino, 8% African American, 4% White and 2% Other. Women predominated (95%). Mean age was 42 years. Most (82%) were foreign-born; 74% chose the Spanish language option. Mean BMI was 33.3 kg/m2; mean weight was 82 kg; mean waist circumference was 102 cm. Mean blood pressure was 122/77 mm. Study arms on key baseline measures did not differ except on dietary quality and sugary beverage intake. Nativity status was significantly associated with dietary quality.

CONCLUSIONS

The two treatment arms were well-balanced demographically at baseline. Nativity status is inversely related to dietary quality.

TRIAL REGISTRATION

NCT02514889 , posted on 8/4/2015.

Reconsidering the HbA1c Cutoff for Diabetes Diagnosis Based on a Large Chinese Cohort

INTRODUCTION

The HbA1c has been considered as the 'gold standard' in diabetes diagnosis and management, however, age, gender and body mass index (BMI) might have certain effects on HbA1c. We are aiming to further investigate the correlation between age and HbA1c, and whether it was affected by gender and BMI.

METHODS

A cross-sectional survey including 135,893 nondiabetic individuals who took the physical examination between 2013 and 2017 was conducted. The subjects were grouped by gender, age and BMI, and the interactive and independent effects of the 3 factors on the HbA1c were detected. The median and 95% confidence interval (CI) of HbA1c levels were calculated.

RESULTS

The HbA1c levels gradually increased along with age, both in female and male, and there is a positive association between BMI and the HbA1c. The difference on HbA1c in gender was associated with both age and BMI, the age-related increase in HbAlc was accentuated in the subgroup with higher BMI, and there was a marked accentuation of the positive association between BMI and HbA1c as age increased. In almost all the young and middle-aged (aged 20-59) subgroups, the 97.5^th percentiles of HbA1c levels were lower than 6.5%, suggesting that the single HbA1c cutoff value is probably not applicable to the young and middle-aged population.

CONCLUSIONS

We recommend that the effects of age, gender and BMI should be taken into consideration when using HbA1c for the diagnosis and management of diabetes, especially in the young and middle-aged population.

Vegetarians have a lower fasting insulin level and higher insulin sensitivity than matched omnivores: A cross-sectional study

BACKGROUND AND AIMS

Potential associations of vegetarian diet patterns with fasting insulin (FI) and insulin sensitivity remain unclear. We aimed to investigate whether vegetarian diets were associated with FI and insulin sensitivity in a cross-sectional study in Chinese vegetarians and matched omnivores and then to test whether it is independent of body mass index (BMI).

METHODS AND RESULTS

This study included 279 vegetarians (73 vegans, 206 lacto-ovo-vegetarians) and 279 age- and sex-matched omnivores. Fasting blood glucose (FG) and FI concentrations were measured, and β-cell function (HOMA-β) and insulin resistance index (HOMA-IR) were used to evaluate insulin sensitivity. All blood glucose and insulin sensitivity indices were naturally log-transformed, and multiple-linear regression was used to determine the association between vegetarian diet patterns and insulin sensitivity after adjusting for confounders including BMI, visceral fat area, physical activity, sedentary time, income, alcohol consumption, and daily dietary intakes of macronutrients. Compared to omnivores, both vegan diet [β = -0.25, 95% CI: (-0.38, -0.14)] and lacto-ovo-vegetarian diet [β = -0.10, 95% CI: (-0.18, -0.01)] were negatively associated with HOMA-IR after adjusting for BMI. Vegan diet remained negatively associated with FI [β = -0.16, 95% CI: (-0.30, -0.01)] and HOMA-IR [β = -0.17, 95% CI: (-0.32, -0.03)] after adjusting for all confounders.

CONCLUSION

Vegetarian diet, especially vegan diet, is negatively associated with FI and IR, independent of BMI.

Application of a novel sex independent anthropometric index, termed angle index, in relation to type 2 diabetes: a Trinidadian case-control study

OBJECTIVE

To develop a novel sex independent anthropometric index, termed as angle index, related to type 2 diabetes.

DESIGN

Case-control.

PARTICIPANTS

The study comprised 121 participants and were divided into two groups. One group had no form of diabetes and served as controls (n=50). The other group had the condition of type 2 diabetes (n=71). 31% (n=37) of the subjects were male and 69% (n=84) were female. 62% (n=75) of the subjects were of East Indian ethnicity, 28% (n=34) were of African ethnicity and 10% (n=12) were of mixed ethnicity.

SETTING

Participants of the study were from the island of Trinidad, located in the Caribbean. Patients in the study were selected at random from hospital records.

PRIMARY OUTCOME MEASURE

It was hypothesised that the mean angle index of patients with type 2 diabetes would be higher than the mean angle index of patients without type 2 diabetes.

RESULTS

Patients with type 2 diabetes had a significantly higher angle index value as compared with controls (p<0.001). Angle index was the superior sex independent anthropometric index in relation to type 2 diabetes (area under the curve=0.72; p<0.001) as compared with other sex independent variables. Angle index correlated with glycated haemoglobin (rs=0.28, p=0.003) and fasting blood glucose (rs=0.31, p=0.001) levels. Patients with type 2 diabetes were four times more likely to have an angle index greater than 184° (OR 4.2, 95% CI 1.8 to 9.9) as compared with controls.

CONCLUSION

Angle index was a superior sex independent index for discriminating between patients with and without type 2 diabetes, as compared with waist circumference, abdominal volume index, conicity index, blood pressure readings, triglyceride levels and very low-density lipoprotein levels.

Assessment of the validity of multiple obesity indices compared with obesity-related co-morbidities

Objective

The aim of the present study was to compare selected obesity indicators with comprehensive health status.

Design

The study employed a pooled cross-sectional design.

Setting

BMI, waist circumference, waist-to-height ratio (WHtR) and body fat percentage were considered as indirect obesity indicators. The Edmonton Obesity Staging System (EOSS) was used as a composite indicator to comprehensively reflect obesity-related co-morbidities. Cohen’s κ coefficient was used to evaluate inter-measurement agreement for obesity. Conformity of indirect obesity indicators to the EOSS was assessed based on percentage agreement (proportion classified as obese and severely unhealthy as a result of obesity among the total sample), sensitivity (proportion classified as obese among individuals severely unhealthy as a result of obesity) and specificity (proportion classified as non-obese among fairly healthy individuals). Logistic regression analysis was used to identify the sociodemographic factors most strongly associated with conformity.

Participants

The study included 17338 adults from the Korea National Health and Nutrition Examination survey conducted between July 2008 and May 2011.

Results

Level of conformity to the EOSS was highest for WHtR (60·77 %) and lowest for BMI (35·96 %). WHtR and BMI had the highest sensitivity (53·7 %) and specificity (98·4 %), respectively. Predictability of conformity was lower among men for all indirect obesity indicators.

Conclusions

WHtR has the greatest potential to identify individuals at risk of health problems due to obesity. Individual demographic factors must be considered in selecting the most appropriate obesity measurement.

Effect of Natural Honey on Glycemic Control and Anthropometric Measures of Patients with Type 2 Diabetes: A Randomized Controlled Crossover Trial

Background

Due to high content of fructose, honey has been introduced as a suitable natural sweetener for patients with type 2 diabetes. We investigated the effect of honey consumption on glycemic control and anthropometric measures of patients with type 2 diabetes.

Methods

This randomized controlled crossover clinical trial was conducted on 53 patients with type 2 diabetes. The participants were randomly divided into groups of control (weight maintenance diet) or treatment (weight maintenance diet +50 g/day honey) for 8 weeks. After a 4-week washout, the second phase began, in which the role of the groups was interchanged. Blood glycated hemoglobin (HbA1c), glucose, insulin, and anthropometric characteristics were measured. Statistical analysis was performed with SPSS. Repeated measures of ANOVA were used to test differences within- and between the two conditions.

Results

Forty-two patients completed the study. HbA1c significantly decreased in control (-0.22%, P = 0.03) and nonsignificantly increased in honey condition (+0.17%, P = 0.22). There was a significant difference between the two conditions (P = 0.02). Fasting glucose did not significantly change in either honey or control condition but insulin concentrations (-0.85 μU/ml, P = 0.01) and insulin secretion (-10.7%, P = 0.01) decreased significantly in the control condition. There was no significant difference in any of these parameters between the two conditions. Waist circumference decreased by honey treatment with a significant difference between the two conditions (P = 0.02).

Conclusions

Eight weeks consumption of 50 g/day honey increased HbA1c and decreased waist circumference of patients with type 2 diabetes.