Comparisons of the strength of associations with future type 2 diabetes risk among anthropometric obesity indicators, including waist-to-height ratio: a meta-analysis

Secular changes in mid-adulthood body mass index, waist circumference, and low HDL cholesterol between 1990, 2003, and 2018 in Great Britain

Objective

To investigate the extent to which 1) secular changes in mid-adulthood WC are independent of BMI and 2) secular changes in low HDL-C are dependent on WC in each sex.

Methods

The sample comprised 19,406 adults (aged 43-47 years) from three birth cohort studies with BMI and WC measured in 1990, 2003, or 2018; 13,239 participants additionally had HDL-C measured in 2003 or 2018. Quantile regression was used to model differences between 1990-2003 and 2003-2018 in 1) BMI and WC internal Z-scores and 2) WC in cm before and after adjustment for BMI. Binary logistic regression was used to model differences between 2003-2018 in low HDL-C, before and after adjustment for BMI or WC.

Results

Secular increases in BMI and WC were larger between 1990-2003 than 2003-2018 and at the upper ends of the distributions. At the 85^th quantile, effect sizes were larger for WC than BMI Z-scores in females but not males. Adjustment for BMI attenuated estimates of secular increases in WC in cm more in males than females. Odds ratios for low HDL-C in 2018 compared to 2003 were 1.73 (95% CI 1.32, 2.28) in males and 1.34 (1.01, 1.78) in females. Adjustment for WC did not substantially change the estimate in males but attenuated the estimate for females to 1.09 (0.81, 1.47).

Conclusions

In women much more so than in men, secular increases in mid-adulthood WC appear to have occurred independently of BMI and largely explain the observed rise in low HDL-C prevalence between 2003-2018.

Joint impact of muscle mass and waist circumference on type 2 diabetes in Japanese middle-aged adults: The Circulatory Risk in Communities Study (CIRCS)

BACKGROUND

Although evidence about skeletal muscle mass loss and type 2 diabetes risk has accumulated, little information is available on the combined effect of skeletal muscle mass and abdominal obesity on type 2 diabetes. We examined whether skeletal muscle mass and abdominal obesity were synergistically associated with the prevalence of type 2 diabetes.

METHODS

Skeletal muscle mass and waist circumference (WC) were measured in 1515 Japanese aged 40 to 69 years. Relative muscle mass was calculated as percentage of total skeletal muscle mass in body weight (SMM%). Type 2 diabetes was identified as fasting serum glucose ≥7.0 mmol/L (126 mg/dL), nonfasting serum glucose ≥11.1 mmol/L (200 mg/dL), glycosylated hemoglobin ≥ 6.5%, and/or diabetes medication use.

RESULTS

The multivariable-adjusted odds ratio (OR) of prevalent diabetes from the lowest to the third quartile of SMM% compared to the highest quartile gradually increased in both sexes. The association between a high WC and prevalent diabetes was similar. The multivariable-adjusted OR (95% confidence intervals) for the prevalence of type 2 diabetes in the low skeletal muscle mass/high WC group was 3.19 (1.78-5.71) for men and 4.46 (2.09-9.51) for women compared with the high skeletal muscle mass/low WC group. The relative excess risk due to interaction was 2.2 (0.5-3.9) in men and 2.8 (0.2-5.3) in women for an excess burden of type 2 diabetes for low skeletal muscle mass and high WC.

CONCLUSIONS

Low skeletal muscle mass and abdominal obesity were synergistically associated with presence of type 2 diabetes.

Home-Based Care, the Missing Link in Caring of Patients Living with HIV/AIDS and Their Family Members: A Narrative Review

Inconsistencies between the number of patients, qualified caregivers and lack of adequate services and resources in the healthcare systems for people living with HIV/AIDS have led to the idea of providing healthcare services for this vulnerable population at home. This study aimed to review the evidence related to the Home-Based Care (HBC) programs in the context of HIV. Literature search was carried out without publication date limit through English databases of Cochrane Library, PubMed, EBSCO, Scopus, Google Scholar, Science Direct, as well as Persian databases including Magiran and SID by the end of July 2019. Out of 1312 studies retrieved from the search of databases, six guidelines and 50 articles met the eligible criteria. The results showed that the overall purpose of HBC is to create hope through providing appropriate care to help the patients and their families to maintain their independence and have the best possible quality of life. The potential benefits of HBC could be discussed in three main categories: 1) patients, including patients’ satisfaction, quality of life, adherence to antiretroviral therapy, preventing mother-to-child transmission, as well as biochemical, social and psychological outcomes, 2) families, consisted of promotinon of family members’ participation, enhancement of family members’ awareness and provision of voluntary counseling and testing, and 3) healthcare systems, containing health care costs, workload at healthcare centers and time spent on services. Given the lessons learnt from the existing HBC programs, developing an alternative approach for providing healthcare at home in the context of HIV seems necessary and could be an agenda for action in health policy making in Iran.

The Relationship between Protein Intake and Source on Factors Associated with Glycemic Control in Individuals with Prediabetes and Type 2 Diabetes

Type 2 diabetes (T2D) is a major contributor to morbidity and mortality largely due to increased cardiovascular disease risk. This study examined the relationships among protein consumption and sources on glycemic control and cardiovascular health in individuals with prediabetes and T2D. Sixty-two overweight or obese participants with prediabetes or T2D, aged 45–75 years were stratified into the following three groups based on protein intake: <0.8 g (gram)/kg (kilogram) body weight (bw), ≥0.8 but <1.0 g/kg bw, and ≥1.0 g/kg bw as below, meeting, and above the recommended levels of protein intake, respectively. Body mass, body mass index (BMI), hip circumference (HC), waist circumference (WC), lean mass, and fat mass (FM) were significantly higher in participants who consumed below the recommended level of protein intake as compared with other groups. Higher animal protein intake was associated with greater insulin secretion and lower triglycerides (TG). Total, low-density, and high-density cholesterol were significantly higher in participants who met the recommended protein intake as compared with the other groups. These data suggest that high protein consumption is associated with lower BMI, HC, WC, and FM, and can improve insulin resistance without affecting lipid profiles in this population. Furthermore, higher intake of animal protein can improve β-cell function and lower plasma TG.

Non-Dietary Factors Associated with Glycemic Status among Adults Diagnosed with Type 2 Diabetes Mellitus in Malawi

We assessed glycemic status and associations with socio-demographic, biomedical, anthropometric, and physical activity (PA) levels among adults with type 2 diabetes mellitus (T2DM) (n = 428; urban n = 288; semi-urban n = 140) using a cross-sectional study. Multivariate linear regression was used to determine factors associated with glycosylated hemoglobin (A1C) . A1C was clinically elevated ≥8% for 60.3% of the participants. Overall, age and PA levels showed a negative association with A1C, and positively with underweight status, duration of diabetes, and participants' view of fluctuating/unstable blood glucose and blood glucose not improved compared to first diagnosed. A significant negative association with A1C was shown with PA levels and additional blood glucose monitoring (BGM) beyond that received at the public clinic in the urban area. Whilst, in the semi-urban area, there was a significant positive association with A1C with regards to duration of diabetes and insulin regimen. Determinants of A1C in this target group are multifactorial, therefore, interventions aiming to improve diabetes clinical outcomes are needed to reduce the likelihood of serious ramifications. Additionally, a team approach from healthcare professionals is needed in conjunction with active patient engagement as well as the development of more comprehensive diabetes care guidelines and policies.

The accuracy of anthropometric measurements of general and central obesity for the prediction of impaired glucose tolerance among the adult population of South India

BACKGROUND

The distribution of body fat and its variation is of great importance in determining the pathogenesis of insulin resistance. Central obesity has been recognized as an independent risk factor for diabetes. The objective of the study was to evaluate the predictive accuracy of various anthropometric measures of body fat in determining impaired glucose tolerance (IGT) or prediabetes among South Indian population.

METHODOLOGY

This was a community-based comparative cross-sectional study where the anthropometric measures of a representative sample of 171 individuals with glycosylated hemoglobin (HbA1c) in the range for IGT were compared with age- and gender-matched controls with HbA1c in the normal range. The predictive accuracy of the various anthropometric measures of obesity to identify individuals with IGT was estimated using the area under the receiver operating characteristic (ROC) curve.

RESULTS

Patients with IGT in both genders had significantly higher BMI, waist circumference (WC), neck circumference (NC), and waist-to-height ratio (WHtR). ROC analysis revealed WHtR in females and NC among males to have the largest area under the curve for predicting IGT. In both genders, WC, WHtR, and NC had better predictive accuracy for prediabetes as compared to BMI and waist-to-hip ratio (WHR).

CONCLUSION

It is suggested that the WHtR and WC are better screening tools for prediabetes in comparison to BMI and WHR among the South Indian population.

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.

The Belgian health examination survey: objectives, design and methods

Background

In 2018 the first Belgian Health Examination Survey (BELHES) took place. The target group included all Belgian residents aged 18 years and older. The BELHES was organized as a second stage of the sixth Belgian Health Interview Survey (BHIS). This paper describes the study design, recruitment method and the methodological choices that were made in the BELHES.

Methods

After a pilot period during the first quarter of the BHIS fieldwork, eligible BHIS participants were invited to participate in the BELHES until a predefined number (n = 1100) was reached. To obtain the required sample size, 4918 eligible BHIS participants had to be contacted. Data were collected at the participant’s home by trained nurses. The data collection included: 1) a short set of questions through a face-to-face interview, 2) a clinical examination consisting of the measurement of height, weight, waist circumference, blood pressure and for people aged 50 years and older handgrip strength and 3) a collection of blood and urine samples. The BELHES followed as much as possible the guidelines provided in the framework of the European Health Examination Survey (EHES) initiative. Finally 1184 individuals participated in the BELHES, resulting in a participation rate of 24.1%. Results for all the core BELHES measurements were obtained for more than 90% of the participants.

Conclusion

It is feasible to organize a health examination survey as a second stage of the BHIS. The first successfully organized BELHES provides useful information to support Belgian health decision-makers and health professionals. As the BELHES followed EHES recommendations to a large extent, the results can be compared with those from similar surveys in other EU (European Union) member states.

Effects of waist to height ratio, waist circumference, body mass index on the risk of chronic diseases, all-cause, cardiovascular and cancer mortality

BACKGROUND

Given the fat redistribution in later stages of life, how the associations between abdominal obesity and the risk of morbidity and mortality have changed with age have not been elucidated, especially for waist to height ratio (WHtR).

OBJECTIVE

To compare the strength of association between obesity indices and chronic diseases at baseline, and the subsequent mortality risk among US adults.

METHODS

We included 21 109 participants from National Health and Nutrition Examination Survey 1999-2014. We performed logistic regression and receiver operating curve analysis to examine the discriminatory power of obesity indicators on cardiometabolic diseases and cancer at baseline. Sex-stratified and age-stratified Cox models were constructed to explore the prospective association between obesity indices and all-cause, cardiovascular and cancer mortality.

RESULTS

Elevated WHtR, elevated waist circumference (WC) and body mass index (BMI)-classified obesity are associated with higher odds of hypertension (OR: 1.37-2.13), dyslipidemia (OR: 1.06 to 1.75, all p<0.05) and diabetes (OR: 1.40-3.16, all p<0.05). WHtR had significantly better discriminatory power to predict cardiometabolic health than BMI, especially for diabetes (area under the curve: 0.709 vs 0.654). After multivariable adjustment, all obesity indicators are associated with lower risk of all-cause mortality among females aged ≥65 years (HR: 0.64 to 0.85), but the association was only significant for BMI when obesity indicators were mutually adjusted (HR: 0.79).

CONCLUSIONS

WHtR and WC appeared to be the better indicators for cardiometabolic health than BMI. However, BMI had a stronger and inverse association with a greater risk of all-cause mortality among older females.

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.

Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes

AIM

To develop and validate a model, which combines traditional risk factors and glycosylated hemoglobin A1c (HbA1c) for predicting the risk of type 2 diabetes (T2DM).

MATERIALS AND METHODS

This is a historical cohort study from a collected database, which included 8419 males and 7034 females without diabetes at baseline with a median follow-up of 5.8-years and 5.1-years, respectively. Multivariate cox regression analysis was used to select significant prognostic factors of T2DM. Two nomograms were constructed to predict the 5-year incidence of T2DM based on traditional risk factors (Model 1) and traditional risk factors plus HbA1c (Model 2). C-index, calibration curve, and time-dependent receiver-operating characteristic (ROC) curve were conducted in the training sets and validation sets.

RESULTS

In males, the C-index was 0.824 (95% CI: 0.795-0.853) in Model 1 and 0.867 (95% CI: 0.840-0.894) in Model 2; in females, the C-index was 0.830 (95% CI: 0.770-0.890) in Model 1 and 0.856 (95% CI: 0.795-0.917) in Model 2. The areas under curve (AUC) in Model 2 for prediction of T2DM development were higher than in Model 1 at each time point. The calibration curves showed excellent agreement between the predicted possibility and the actual observation in both models. The results of validation sets were similar to the results of training sets.

CONCLUSION

The proposed nomogram can be used to accurately predict the risk of T2DM. Compared with the traditional nomogram, HbA1c can improve the performance of nomograms for predicting the 5-year incidence of T2DM.

Explaining the Inverse Association between Altitude and Obesity

PURPOSE

To better understand the inverse association between altitude and adult obesity.

METHODS

An ecological study design was used, involving 3,108 counties in the contiguous United States. Data were from several national sources, and assessment involved various statistical techniques, including multiple regression analysis.

RESULTS

Living in counties at higher altitude is associated with lower adult obesity. Compared with counties <500 meters, the percent of adult obesity decreases by 5.18% at 500-999 meters, 9.69% at 1,000-1,499 meters, 16.77% at 1,500-1,999 meters, 24.14% at 2,000-2,499 meters, and 35.28% at ≥2,500 meters. After adjusting for physical inactivity, smoking, and other variables, corresponding decreases in adult obesity with higher altitude groupings are 3.87%, 5.64%, 8.03%, 11.41%, and 17.54%, respectively. Various mechanisms are presented as possible explanations for the association between higher altitude and lower obesity. In addition, altitude may indirectly influence adult obesity, primarily through its relationship with physical inactivity and smoking. In an adjusted regression model, adult obesity was most strongly associated with physical inactivity followed by adult smoking and then altitude. Together they explain 39.04% of the variation in adult obesity. After accounting for these variables, sunlight, precipitation, ambient air temperature, education, income, food insecurity, limited access to healthy foods, race, sex, and rural living explain an additional 4.68% of the variation in adult obesity.

CONCLUSIONS

The inverse association between altitude and adult obesity remains significant after adjustment for several variables.

An anthropometry-based nomogram for predicting metabolic syndrome in the working population

BACKGROUND

Early detection of metabolic syndrome is highly desirable for the prevention and treatment of various diseases. Therefore, this study aimed to develop and validate an anthropometry-based nomogram for predicting metabolic syndrome in a working population.

METHODS

The present study was a secondary analysis of a cross-sectional study. A total of 60,799 workers in Spain were enrolled between 2012 and 2016, of which 50% were randomly assigned to the derivation cohort and the remainder to the validation cohort. Participants' demographics and anthropometric variables were entered into least absolute shrinkage and selection operator (LASSO) regression for the selection of variables. Subsequently, multivariable logistic regression was performed to develop the predictive model and a nomogram. The discrimination ability, calibration curve analysis and decision curve analysis of the nomogram was evaluated. Internal validation of the model was also performed.

RESULTS

There were 2725 (9.0%) participants diagnosed with metabolic syndrome in the derivation cohort and 2762 (9.1%) participants in the validation cohort. Six variables (age, smoking, body fat percentage, waist circumference, systolic blood pressure and diastolic blood pressure were included in the nomogram. The area under the curve was 0.901 (95% confidence interval (CI) 0.895-0.906) and 0.899 (95% CI 0.894-0.905) for the predictive and internal validation, respectively. Furthermore, decision curve analysis showed that if the threshold probability of metabolic syndrome is less than 72.0%, application of this nomogram can benefit more than either the treat-all or treat-none strategies.

CONCLUSIONS

An anthropometry-based nomogram for predicting metabolic syndrome in a working population was developed that incorporates reliable non-invasive anthropometric features to facilitate health counselling and self-risk assessment of developing metabolic syndrome.

Association between Biomarkers of Low-grade Inflammation and Sex Hormones in Women with Polycystic Ovary Syndrome

Objective Women with polycystic ovary syndrome (PCOS) have higher circulating levels of C-reactive protein, but the relationship between inflammation and endocrine function in PCOS remains poorly understood. Thus, this study aimed to investigate the association between low-grade inflammation and sex hormones in women with PCOS.

Design and Patients A comprehensive panel of biomarkers of inflammation was measured in serum of 63 women with PCOS using proximity extension assay technology. Associations of 65 biomarkers with sex hormones were assessed without and with adjustment for age and body mass index (BMI).

Results In the unadjusted analysis, 20 biomarkers were positively correlated with 17-OH-progesterone (17-OH-P), 14 with prolactin and 6 with free testosterone, whereas inverse associations were found for 16 biomarkers with sex hormone-binding globulin (SHBG), 6 with luteinizing hormone (LH) and 6 with estrogen (all p<0.05). Among the positive associations, correlations were mainly found for five chemokines (CXCL11, CCL4, MCP-4/CCL13, CXCL5, CXCL6) and for VEGF-A, LAP-TGFβ1, TNFSF14 and MMP-1. Inverse associations with sex hormones were mainly present for two chemokines (CXCL1, MCP-2/CCL8), CDCP1, CST5 and CSF-1. Adjustment for age and BMI reduced the number of biomarker associations for SHBG and estrogen, but had hardly any impact on associations with 17-OH-P, prolactin, free testosterone and LH.

Conclusion Women with PCOS feature BMI-independent associations between biomarkers of inflammation and certain sex steroid and hypophyseal hormones. Most of these inflammation-related biomarkers were chemokines, which may be relevant as potential mediators of the increased cardiometabolic risk of women with PCOS.

Association of type 2 diabetes with anthropometrics, bone mineral density, and body composition in a large-scale screening study of Korean adults

OBJECTIVES

Type 2 diabetes mellitus (T2DM) is a common, chronic disease that is closely associated with anthropometric indices related to obesity. However, no study published to date has simultaneously examined the associations of T2DM with anthropometrics, bone mineral density (BMD), and body composition variables. The present study aimed to evaluate the associations of T2DM with anthropometrics, BMD and body composition variables and to identify the best indicator of T2DM in Korean adults.

METHODS

The data used in this study were obtained from the Korea National Health and Nutrition Examination Survey conducted from 2008 to 2011. A total of 7,835 participants aged from 40 to 90 years were included in this study. A binary logistic regression analysis was performed to examine the significance of differences between the groups with and without T2DM, and the areas under the receiver operating characteristic (AUCs) curves were calculated to compare the predictive power of all variables.

RESULTS

In men, waist-to-height ratio (WHtR) displayed the strongest association with T2DM (adjusted odds ratio (OR) = 1.838 [1.513-2.233], adjusted p<0.001), and waist circumference (WC) and WHtR were the best indicators (WC: AUC = 0.662 [0.639-0.685], WHtR: AUC = 0.680 [0.658-0.703]) of T2DM among all the variables. In women, left leg (LL) and right leg (RL) fat displayed strong negative associations with T2DM (LL fat: adjusted OR = 0.367 [0.321-0.419], adjusted p<0.001, RL fat: adjusted OR = 0.375 [0.329-0.428], adjusted p<0.001), and WC and WHtR were excellent indicators (WC: AUC = 0.730 [0.709-0.750], WHtR: AUC = 0.747 [0.728-0.766]) of T2DM among all the variables. In particular, the WHtR in men and LL and RL fat in women exhibited the strongest associations with T2DM, and the predictive power of the WC and WHtR was stronger than BMD, fat, and muscle mass variables in both men and women. Additionally, the predictive power of the WC and WHtR was stronger in women than in men.

DISCUSSION

Of the anthropometric indices, BMD, and body fat and muscle variables, the best indicators of T2DM were WC and WHtR in both Korean men and women. The results of the present investigation will provide basic information for clinical studies of patients with T2DM and evidence for the prevention and management of T2DM.

Protocol: investigating the effectiveness and cost benefit of a lifestyle intervention targeting type 2 diabetes in Australia

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) has become an endemic disease. A number of interrelated factors increase the risk of the onset of T2DM, however much of the pathogenesis of the disease is associated with lifestyle. A number of studies have indicated that adopting positive lifestyle changes can successfully prevent or delay the onset of T2DM in a number of different population groups. The CHIP intervention is a lifestyle program that has been shown in over more than 30 published papers have indicated that the CHIP intervention leads to dramatic improvement in the indicators of T2DM these diseases of lifestyle.

METHODS

A randomized control trial will be conducted involving 150 individuals with an established diagnosis of T2DM. All participants will continue to receive usual ongoing diabetes care, however, the intervention group (75 individuals) will in addition participate in a 12-week CHIP lifestyle intervention programme followed by a further 9 months of monthly follow-up appointments. Approval for funding was obtained on 30 June 2017.

DISCUSSION

The outcomes of this study have the potential to inform decisions about patient treatment and potentially provide incentive for the provision of funded lifestyle-based preventive and restorative programs for patients diagnosed with T2DM.

TRIAL REGISTRATION

This trial is registered as an initial version with the Australia New Zealand Clinical Trials Registry ( http://www.anzctr.org.au/ ), registration number ACTRN12617001233314. Registered on 23/08/2017. No enrollments in the study to date.

The Prevalence of Overweight and Obesity in an Adult Kuwaiti Population in 2014

Background: According to World Health Organization (WHO) estimates, Kuwait is ranked amongst the top countries in the world in obesity prevalence. This study aims to describe the prevalence of overweight, obesity, and various types of adiposity in Kuwaiti adults. Methods: This cross-sectional study of 3,915 Kuwaiti adults aged 18-69 years used the STEP-wise approach to surveillance of non-communicable diseases, a WHO Instrument for Chronic Disease Risk Factor Surveillance. We assessed demographic information, lifestyle, personal and family history of diseases and physical measurements (height, weight, waist, and hip circumferences). All participants with valid height and weight measurements (n = 3,589) were included in the present analysis. Overweight was defined as BMI 25-29.9 kg/m2 and obesity as BMI ≥30 kg/m2. Results: Obesity prevalence was 40.3% [95% confidence interval, 38.6-42.0%] (men, 36.5%; women, 44.0%); and overweight prevalence was 37% [35.4-38.7%] (men, 42%; women, 32.1%). The median BMI was 28.4 kg/m2 among men and 29.1 kg/m2 among women. Obesity prevalence was directly associated with female sex, age, history of diabetes, and being married in both men and women; and was inversely associated with education level in women. The prevalence of elevated waist-to-hip ratio was 46.9% among men and 37.9% among women. Waist circumference, waist-hip and waist-height ratios were directly associated with diabetes in both men and women, and inversely associated with education level in women. Conclusion: Almost eight in ten Kuwaiti adults were overweight or obese. Urgent public health action is warranted to tackle the obesity epidemic in Kuwait.

Unpacking the heritability of body mass index and other ratios

OBJECTIVES

Ratios of weight to height, especially body mass index (BMI = kg/m² ), are often used in epidemiological and genetic studies of health, but the limitations of quantitative genetic analysis of ratios are not widely known. The heritability of these ratios can be closely approximated from a bivariate quantitative genetic model of weight and height which clarifies how BMI heritabilities change.

METHODS

I explored this bivariate approximation and alternative measures through simulated datasets fit with linear mixed models. Simulated data were based on published heritabilities and other statistics for BMI and related anthropometric dimensions from four human samples.

RESULTS

Inspection of the bivariate approximation and analysis of simulated data show the heritability of weight/height crucially depends on the phenotypic (r_P ) and genetic correlations (r_A ) between weight and height. Changes in these correlations can have dramatic effects on the heritability of BMI. For example, when r_P  ≪ r_A heritability of BMI is reduced to 35-50% of its value when the correlations are equal.

DISCUSSION

Increasing adiposity likely decreases the phenotypic correlations more than the genetic correlation resulting in reduced heritability of the ratio. This contrasts with the commonly reported stability or increase of BMI heritability and implies it may result from increased genetic variance in weight in obesogenic environments. The bivariate model offers other advantages over ratios, including estimating the conditional genetic variance or heritability of weight that is unassociated with height, which may prove useful in quantitative and molecular genetic studies.

Accurate GFR in obesity-protocol for a systematic review

BACKGROUND

Obesity is increasing globally. Chronic kidney disease (CKD) is strongly associated with obesity. Kidney function is commonly estimated with equations using creatinine (such as CKD-EPI equation) which is a product of muscle metabolism. Decisions about categorizing CKD, planning modality of renal replacement therapies, and adjusting dosages of medications excreted by the kidneys are done using these equations. However, it is not well appreciated that creatinine-based equations may not accurately estimate kidney function in obese individuals. We plan a systematic review of diagnostic studies which will compare estimating equations to actual measured kidney function.

METHODS

We will systematically search electronic bibliographic databases including MEDLINE, EMBASE, and the Cochrane Library with no restrictions on language or specific dates. The search terms will be adapted for the different databases using a combination of Medical Subject Heading and relevant keywords contained in titles and abstracts. Our preliminary search strategy using Cochrane, MEDLINE, and EMBASE databases have identified 190, 1246, and 1660 citations, respectively. For all studies selected, we will extract information on general study characteristics, study participant (age, sex, ethnicity, weight, height, BMI, BSA), type and protocol of reference standard utilized, the index test studied, the methodology of measurement of index test, categories of GFR, the proportion of eGFR within 10, 20, 30, 40, and 50% of measured GFR, and bias between eGFR and measured GFR. If the quality of methods and risk of bias are adequate, we will perform a meta-analysis. We will assess the heterogeneity using the χ 2 and the I 2 statistics to examine whether the estimates from studies included could be pooled. Sensitivity and multivariate meta-regression analyses will be performed to assess the effects of clinical factors and socio-demographic characteristics reported in included studies on the meta-analytic estimates. All analysis will be performed using the Comprehensive Meta-analysis software.

DISCUSSION

This systematic review might help to inform clinicians on the best equation to use in patients with obesity and CKD for staging of CKD and for medication dosing. If no equation is deemed suitable, this review will form a basis for future studies of GFR in obese individuals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42018104345.

Different metabolic/obesity phenotypes are differentially associated with development of prediabetes in adults: Results from a 14-year cohort study

BACKGROUND

The risk of developing prediabetes based on the metabolic/obesity phenotypes has been poorly investigated.

AIM

To examine the association of baseline metabolic/obesity phenotypes and their changes over time with the risk of prediabetes development.

METHODS

In a population-based cohort study, 1741 adults (aged > 19 years) with normal blood glucose were followed for 14 years. Anthropometric and biochemical measures were evaluated regularly during the follow-up period. According to body mass index and metabolic health status, participants were categorized into four groups: Metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW) and metabolically unhealthy obese (MUO). Multivariable Cox regression analysis was used to measure the risk of prediabetes according to the baseline metabolic/obesity phenotype and their changes during the follow-up.

RESULTS

In the whole population with a mean (95CCI for mean) follow up duration of 12.7 years (12.6-12.9), all three MUNW, MHO, MUO groups were at higher risk for developing prediabetes compared to the MHNW group (P = 0.022). The MUNW group had the highest risk for developing prediabetes (hazard ratio (HR): 3.84, 95%CI: 1.20, 12.27). In stratified analysis by sex, no significant association was found in men, while women in the MUNW group were at the greatest risk for prediabetes (HR: 6.74, 95%CI: 1.53, 29.66). Transforming from each phenotype to MHNW or MHO was not related to the risk of prediabetes development, whereas transforming from each phenotype to MUO was associated with an increased risk of prediabetes (HR > 1; P < 0.05).

CONCLUSION

Our findings indicate that MHO is not a high risk, unless it transforms into MUO over time. However, people in the MUNW group have the greatest risk for developing prediabetes, and therefore, they should be screened and treated.

Factors associated with glycemic control in community-dwelling elderly individuals with type 2 diabetes mellitus in Zhejiang, China: a cross-sectional study

BACKGROUND

Although exercise seems to be beneficial for type 2 diabetes mellitus (T2DM) patients, there is limited research elucidating the optimal accessible indices of adiposity and insulin resistance for identifying elderly T2DM patients with poor glycemic control, which could be improved by performing regular exercise.

METHODS

A community-based, cross-sectional study was conducted with 918 Chinese elderly individuals with T2DM in Zhejiang. Relevant risk factors for poor glycemic control, as determined using glycated haemoglobin A1c (HbA1c) > 7%, were explored using logistic regression analyses and included body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR), fasting blood glucose (FBG), triglycerides (TGs), total cholesterol (TC), the product of fasting triglycerides and glucose (TyG), visceral adiposity index (VAI), lipid accumulation product (LAP), TyG-BMI, and TyG-WC. Comparisons of the risk factors' ability to discriminate poor glycemic control as well as their optimal cutoff values were determined using receiver operating characteristic (ROC) analyses, and then the extent of poor glycemic control risk reduction through regular exercise was examined using multivariate logistic regression analyses.

RESULTS

The overall poor glycemic control rate was 49.3%. The factors associated with poor glycemic control included FBG > 3.869, TyG > 8.73, TyG-BMI > 222.45, and TyG-WC > 713.48 in logistic regression analyses. The optimal cutoff points of FBG, TyG, TyG-WC, and TyG-BMI in discriminating poor glycemic control were 7.38, 9.22, 813.33, and 227.77, and their corresponding areas under the ROC curves were 0.864(0.840-0.886), 0.684(0.653-0.714), 0.604(0.571-0.635), and 0.574(0.541-0.606), respectively. Occasional and regular exercise reduced the odds ratios (95% confidence interval) of poor glycemic control to 0.187 (0.063-0.557) and 0.183 (0.059-0.571) for subjects with TyG-WC > 813.33 (p = 0.008), to 0.349 (0.156-0.782) and 0.284 (0.123-0.652) for subjects with TyG > 9.22 (p = 0.011), and to 0.390 (0.175-0.869) and 0.300(0.130-0.688) for subjects with TyG-BMI > 227.77 (p = 0.017), respectively, after adjusting for multiple confounding factors.

CONCLUSION

Among elderly individuals with T2DM, poor glycemic control risk might be identified using indices calculated from FBG, TG, BMI, and WC measurements, which are indicative of adiposity and insulin resistance. TyG-WC seems to be an accessible and useful indicator to identify which elderly T2DM patients would benefit from performing regular exercise to achieve good glycemic control.

Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis

BACKGROUND

In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear.

METHODS

We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium.

RESULTS

All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p  =  5.09  ×  10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p  =  4.02  ×  10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p  =  5.05  ×  10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p  =  9.22  ×  10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer.

CONCLUSIONS

We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.

Comparison of Anthropometric Measures for Evaluating the Association Between Hypogonadism and Hypothalamic-Pituitary-Gonadal Hormones in a Taiwanese Population

To investigate the degree of association between levels of sex hormones and anthropometric indices in male population. A cross-sectional survey was conducted between July 2014 and July, 2016, in a men's health polyclinic in Taiwan. Body mass index, waist circumference, waist-to-height ratio (WHtR), and conicity index were tested. Serum total testosterone, free testosterone, and dehydroepiandrosterone sulfate (DHEA-S) were measured. Decreased testosterone levels were correlated with the four indices (r = -0.09 to -0.27, p < 0.01). In hypogonadism group, DHEA-S deficiency was associated with older age, higher anthropometric indices, and chronic illness. The areas under the receiver operating characteristic curves of hypogonadism and DHEA-S deficiency by the four anthropometric indices ranged from 52.5% to 65.9%. Logistic regression analysis revealed that obesity, defined by the four indices, was associated with increased risk of hypogonadism. Moreover, obesity was also associated with increased risk and DHEA-S deficiency. Anthropometric indices analyzed are associated with lower testosterone and DEAH-S deficiency. A WHtR of 0.5 is suggested to be a simple and reliable indicator of hypogonadism and DHEA-S deficiency.

Stronger associations of waist circumference and waist-to-height ratio with diabetes than BMI in Chinese adults

AIMS

To compare the magnitude of associations of the obesity indicators with the risk of prediabetes and diabetes.

METHODS

We performed an individually region-, sex-, and age-matched case and control analysis involving 42 918 Chinese adults aged 20-88 years (6876 matched prediabetes and normal glucose regulation [NGR] groups and 2873 matched newly diagnosed diabetes mellitus [NDM] and NGR groups).

RESULTS

Compared with their respective NGR controls, the participants with prediabetes or NDM had significantly higher mean levels of obesity indices as follows: waist circumference (cm), 85.3 vs. 81.8 and 87.9 vs. 82.9; waist-to-height ratio (WHtR), 0.531 vs. 0.509 and 0.546 vs. 0.514; and body mass index (BMI) (kg/m²), 25.4 vs. 24.1 and 25.9 vs. 24.2 (all P < 0.001). The odds ratios (95% confidence intervals) of NDM with waist circumference, WHtR, and BMI per standard deviation (SD) increase were 1.88 (1.80-1.97), 1.88 (1.80-1.97), and 1.69 (1.62-1.76) in the total population.

CONCLUSIONS

Mean differences in the three obesity indices were around 0.3 SD between matched prediabetes cases and NGR controls, and around 0.5 SD between matched NDM cases and NGR controls. Waist circumference and WHtR were more strongly associated with diabetes than BMI among Chinese adults.

Contribution of Adipose Tissue Inflammation to the Development of Type 2 Diabetes Mellitus

The objective of this comprehensive review is to summarize and discuss the available evidence of how adipose tissue inflammation affects insulin sensitivity and glucose tolerance. Low-grade, chronic adipose tissue inflammation is characterized by infiltration of macrophages and other immune cell populations into adipose tissue, and a shift toward more proinflammatory subtypes of leukocytes. The infiltration of proinflammatory cells in adipose tissue is associated with an increased production of key chemokines such as C-C motif chemokine ligand 2, proinflammatory cytokines including tumor necrosis factor α and interleukins 1β and 6 as well as reduced expression of the key insulin-sensitizing adipokine, adiponectin. In both rodent models and humans, adipose tissue inflammation is consistently associated with excess fat mass and insulin resistance. In humans, associations with insulin resistance are stronger and more consistent for inflammation in visceral as opposed to subcutaneous fat. Further, genetic alterations in mouse models of obesity that reduce adipose tissue inflammation are-almost without exception-associated with improved insulin sensitivity. However, a dissociation between adipose tissue inflammation and insulin resistance can be observed in very few rodent models of obesity as well as in humans following bariatric surgery- or low-calorie-diet-induced weight loss, illustrating that the etiology of insulin resistance is multifactorial. Taken together, adipose tissue inflammation is a key factor in the development of insulin resistance and type 2 diabetes in obesity, along with other factors that likely include inflammation and fat accumulation in other metabolically active tissues. © 2019 American Physiological Society. Compr Physiol 9:1-58, 2019.

Longitudinal association of adiposity with wheezing and atopy at 22 years: the 1993 Birth Cohort, Pelotas, Brazil

Purpose

Asthma is a highly prevalent noncommunicable lung disease. The aim of this study was to evaluate the longitudinal association of obesity/adiposity with wheezing and atopy.

Methods

The population of the study was composed of participants from the 1993 Pelotas (Brazil) Birth Cohort. The following outcome variables were measured at 22 years: wheezing in the last 12 months, wheezing with atopy, wheezing without atopy, only atopy, and persistent wheezing at 18 and 22 years. Exposure variables were obesity body mass index, percent fat mass (FM), and fat mass index, which were obtained by precise methods (BOD POD and dual-energy X-ray absorptiometry [DXA]). Crude and adjusted logistic and multinomial logistic regressions were used in the analyses.

Results

The prevalence of wheezing (with and without atopy), wheezing without atopy, only atopy, and persistent wheezing were 10.6%, 3.9%, 30.9%, and 4.0%, respectively. To be obese or to belong to the highest tertile of obesity/adiposity at two follow-ups showed a cumulative and positive association with wheezing in the adjusted analysis; for atopy there was no significant association. The odds ratio (OR) for wheezing according to the percentage of total FM measured by DXA in the highest tertile at both follow-ups was 1.58 (95% CI: 1.14–2.20) against an OR of 1.16 (95% CI: 0.92–1.47) for atopy. Persistent wheezing was also associated with adiposity, but without statistical significance.

Conclusions

We found a positive longitudinal association between several measures of adiposity and wheezing at 22 years old. The effect was higher for cumulative adiposity; the results for atopy were not consistent.

Body mass index and the risk of mortality among Chinese adults with Type 2 diabetes

AIMS

To examine the associations between BMI and the risks of all-cause, cardiovascular disease (CVD)-specific and cancer-specific mortality among people with Type 2 diabetes, and thus provide recommendations for weight management in the population.

METHODS

This retrospective cohort study was conducted among 52 763 people with newly diagnosed Type 2 diabetes between 1 January 2004 and 31 December 2014 in Shanghai, China. All cases of death were identified by linking to the Shanghai Vital Statistics. Some 52 488 people were included in the analysis. Survival curves for people with different BMI categories were plotted using the Kaplan-Meier method. Cox proportional hazard models within or without restricted cubic spline functions were applied to examine the potential non-linear or linear relationship between BMI and the risk of mortalities respectively.

RESULTS

A total of 4777 deaths were identified during an average of 6-year follow-up. An L-shaped association was observed between BMI and all-cause mortality in men (P for overall association < 0.001 and P for non-linearity < 0.001) while a U-shaped association was found in women (P for overall association < 0.001 and P for non-linearity< 0.001). In men, no significant association was observed for BMI with cancer-specific and CVD-specific mortality. In women, an increased risk of cancer-specific mortality was observed with increasing BMI, whereas decreasing BMI was associated with the increased CVD-specific mortality rate.

CONCLUSION

The increased all-cause mortality in men with low BMI and in women with either low or high BMI indicate the importance of keeping BMI in a normal range for Chinese adults with Type 2 diabetes.

Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population

OBJECTIVES

A non-invasive method for the early detection of metabolic syndrome (NIM-MetS) using only waist-to-height ratio (WHtR) and blood pressure (BP) has recently been published, with fixed cut-off values for gender and age. The aim of this study was to validate this method in a large sample of Spanish workers.

DESIGN

A diagnostic test accuracy to assess the validity of the method was performed.

SETTING

Occupational health services.

PARTICIPANTS

The studies were conducted in 2012-2016 on a sample of 60 799 workers from the Balearic Islands (Spain).

INTERVENTIONS

The NCEP-ATP III criteria were used as the gold standard. NIM-MetS has been devised using classification trees (the χ² automatic interaction detection method).

MAIN OUTCOME MEASURES

Anthropometric and biochemical variables to diagnose MetS. Sensitivity, specificity, validity index and Youden Index were determined to analyse the accuracy of the diagnostic test (NIM-MetS).

RESULTS

With regard to the validation of the method, sensitivity was 54.7%, specificity 94.9% and the Validity Index 91.2%. The cut-off value for WHtR was 0.54, ranging from 0.51 (lower age group) to 0.56 (higher age group). Variables more closely associated with MetS were WHtR (area under the curve (AUC)=0.85; 95% CI 0.84 to 0.86) and systolic BP (AUC=0.79; 95% CI 0.78 to 0.80)). The final cut-off values for the non-invasive method were WHtR ≥0.56 and BP ≥128/80 mm Hg, which includes four levels of MetS risk (very low, low, moderate and high).

CONCLUSIONS

The analysed method has shown a high validity index (higher than 91%) for the early detection of MetS. It is a non-invasive method that is easy to apply and interpret in any healthcare setting. This method provides a scale of MetS risk which allows more accurate detection and more effective intervention.

Estimate of prevalent diabetes from cardiometabolic index in general Chinese population: a community-based study

Background

Cardiometabolic index (CMI) defines adiposity based on triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio and waist-to-height ratio (WHtR). This newly proposed metric has been used to detect multiple cardiovascular risk factors, but data relative to diabetes in the general population are lacking. This study aims to validate CMI’s utility of discriminating diabetes and compares it with other indexes among general Chinese population.

Methods

Analyses were based on a cross-sectional study of 11,478 participants that underwent assessment of metabolic and anthropometric parameters in rural areas of northeastern China in 2013. CMI was calculated by TG/HDL-C × WHtR. Multivariate logistic regressions were performed to clarify CMI’s association with diabetes, ROC analyses were engaged to investigate CMI’s discriminating ability for diabetes.

Results

The prevalence of diabetes was 9.93% in males while 10.76% in females, and increased with CMI’s increment. After full adjustment, each SD increment of CMI had odds ratios (ORs) for diabetes of 1.471 (1.367–1.584) and 1.422 (1.315–1.539) in females and males, respectively. Compared with bottom categories of CMI, the top quartiles had ORs of 3.736 (2.783–5.015) in females and 3.697 (2.757–4.958) in males. The ROC results showed an excellent discriminating power of CMI (AUC: 0.702 for females, 0.664 for males).

Conclusions

An increasing CMI was correlated with higher odds of diabetes, supporting CMI as a useful and economic measure to screen and quantify diabetes in general Chinese population. Monitoring and promoting achievement of dyslipidemia and abdominal obesity based on CMI may improve subclinical and cardiovascular outcomes.

Comparison of anthropometric indices (body mass index, waist circumference, waist to hip ratio and waist to height ratio) in predicting risk of type II diabetes in the population of Yazd, Iran

BACKGROUND AND OBJECTIVES

The purpose of this study was to determine the best anthropometric index and calculate the cut-off point for each anthropometric index in predicting the risk of type II diabetes in the population of Yazd city in Iran.

MATERIALS AND METHODS

The present analytical cross-sectional study was performed using the data from Yazd Health Study (YaHS) with a sample size of 9293. All required data including anthropometric indices BMI, WC, WHR, and WHtR were extracted from the YAHS questionnaire. The ROC curve was employed to compare the predictive power of each anthropometric index in the risk of developing the type II diabetes.

RESULTS

WHtR in both genders had better predictive power for the risk of type II diabetes (AUC = 0.692 for males and AUC = 0.708 for females), and BMI showed a weaker predictive power (AUC = 0.603 for males and AUC = 0.632 for females), WC and WHR also revealed similar predictive power in the risk of type II diabetes. The cut-off point of BMI for predicting the risk of diabetes was almost identical in both genders (26.2 in males and 25.9 in females), the cut-off point of WC (91 cm), and WHtR (0.56) in males was lower than in the females (96 cm for WC and 0.605 for WHtR). The cut-off point of WHR in males (0.939) was higher than in females (0.892).

CONCLUSION

The WHtR showed the best predictor of diabetes risk compared to other indices, and the BMI was the weakest predictor of the risk for diabetes.

Adiposity and Diabetes Risk in Adults with Prediabetes: Heterogeneity of Findings Depending on Age and Anthropometric Measure

OBJECTIVE

The study aimed to evaluate the effect of age on diabetes incidence by general and central adiposity after 3-year follow-up in adults with prediabetes.

METHODS

Data were taken from a cohort of 1,184 subjects with prediabetes included in The Cohort Study in Primary Health Care on the Evolution of Patients with Prediabetes (PREDAPS). General adiposity was defined using body mass index (BMI), and central adiposity was defined with waist circumference and waist to height ratio. Data were analyzed by age groups 30 to 59 and 60 to 74 years. The association between adiposity and diabetes incidence was assessed using hazard ratios (HR).

RESULTS

Adjusting for sociodemographic characteristics, lifestyles, and metabolic parameters, diabetes HR for central adiposity based on the waist circumference clinical cutoff were 2.14 (1.12-4.09) and 1.48 (0.80-2.74) for people aged 30 to 59 and 60 to 74 years, respectively. In the model additionally adjusted for BMI, diabetes HR were 2.65 (1.24-5.65) and 1.33 (0.68-2.59), respectively. The use of a 1-SD increase rather than cutoff points did not alter this pattern. Similar findings were observed with central adiposity based on waist to height ratio.

CONCLUSIONS

The association of central adiposity with type 2 diabetes incidence was lower for people in the older age group than for those in the younger age group.

Comparison of the association of predicted fat mass, body mass index, and other obesity indicators with type 2 diabetes risk: two large prospective studies in US men and women

Obesity, defined by body mass index (BMI), is a well-established risk factor of type 2 diabetes, but BMI has been criticized for its inability to discriminate fat mass and lean body mass. We examined the association between predicted fat mass and type 2 diabetes risk in two large US prospective cohorts, and compared the magnitude of the association with BMI and other obesity indicators. Validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey were used to estimate predicted fat mass and percent fat for 97,111 participants from the Health Professionals Follow-up Study (1987-2012) and the Nurses' Health Study (1986-2012) who were followed up for type 2 diabetes. Multivariable-adjusted hazard ratios for type 2 diabetes across quintiles of predicted fat mass were 1.00, 1.96, 2.96, 3.90, and 8.38 for men and 1.00, 2.20, 3.50, 5.73, and 12.1 for women; of BMI were 1.00, 1.69, 2.45, 3.54, and 6.94 for men and 1.00, 1.76, 2.86, 4.88, and 9.88 for women. Predicted FM showed the strongest association with type 2 diabetes in men followed by waist circumference (WC), waist-to-height ratio (WHtR), predicted percent fat, BMI, Waist-to-hip ratio (WHR), and a body shape index (ABSI). For women, the strongest association was shown for WHtR, followed by WC, predicted percent fat, predicted fat mass, BMI, ABSI, and WHR. Compared to BMI, predicted fat mass demonstrated consistently stronger association with type 2 diabetes risk. However, there was inconclusive evidence to suggest that predicted fat mass is substantially superior to other obesity indicators.

Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes

OBJECTIVES

To compare different anthropometric indices, Body composition analysis and lipid profile markers in terms of their ability to predict prediabetes (PD).

METHODS

We enrolled 83 subjects with PD and 84 normoglycemic subjects who were matched for age and gender. The diagnosis of prediabetes was done according to the American Diabetes Association (ADA) criteria. All subjects were aged between 30-55 years of age and visited the outpatient department of tertiary care hospital. Anthropometric and lipid profile measurements were obtained. Analysis of body composition was done using Bodystat 1500MDD Instrument. Backward logistic regression was performed for detecting the predictors of PD. A receiver operator characteristic curve (ROC) with area under curve (AUC) was utilized for the accuracy of the predictors of PD.

RESULTS

Comparison of anthropometric measurement and body composition analysis parameters between the two groups showed that Waist circumference (WC), Body mass index, Body Fat% were significantly higher whereas Extracellular water and Dry lean weight in percentage (ECW% and DLW%) were found to be lower in PD (p< 0.05). Higher triglyceride (TG) levels and lower high-density cholesterol (HDL-C) with high TG/HDL-C were seen in subjects with PD. Backward logistic regression analysis found the combination of Body Fat % with WC, TG, ECW% and DLW% as strong predictors of PD. In ROC analysis, ECW% (AUC = 0.703) was the most predictive measure, followed by WC (AUC = 0.702).

CONCLUSION

This study demonstrated that estimation of Body Fat % combined with waist circumference, Extracellular water and Dry lean weight in percentage are valuable in screening and diagnosis of prediabetes. Plasma levels of TG in lipid profile measurements can also serve as an additional marker for prediction of prediabetes.

Association between Obesity and Carotid Intima-Media Thickness in Korean Office Workers: The Mediating Effect of Physical Activity

BACKGROUND

Obesity and physical inactivity are associated with higher prevalence of cardiovascular disease (CVD).

OBJECTIVE

This study investigated the association between obesity and carotid intima-media thickness (CIMT) stratified by physical activity (PA) in Korean office workers.

METHODS

Data obtained from 914 office workers aged 21-60 years (347 women) were used. Resting blood pressures, body mass index (BMI), and waist-to-height ratio (WHtR) were measured. PA was assessed using the international physical activity questionnaire. CIMT was assessed with a carotid artery ultrasonography. Logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of obesity stratified by weekly PA for an abnormally increased CIMT.

RESULTS

Logistic regression analyses showed that those who were overall obese (OR=2.50, 95% CI=1.60-3.91, P<0.001) or central obese (OR=2.08, 95% CI=1.29-3.40, P=0.003) had significantly higher estimated risks of having an abnormally increased CIMT even after adjustments for age, sex, smoking, alcohol consumption, resting blood pressures, and history of hypertension, diabetes, and hyperlipidemia, as compared with those who were not overall or central obese (OR=1). A multivariate linear regression suggested that age (P<0.001), sex (P=0.002), hypertension (P=0.014), smoking (P=0.054), BMI (P<0.001), and physical activity (P=0.011) were important determinants of abnormally elevated CIMT in this study population.

CONCLUSION

The current findings suggest that the risk of obesity for an abnormally increased CIMT is significantly modulated by demographics as well as lifestyle-related risk factors including smoking and physical inactivity in Korean office workers.

Risk modeling in prospective diabetes studies: Association and predictive value of anthropometrics

AIMS

This study aimed to introduce and apply modern statistical techniques for assessing association and predictive value of risk factors in first-degree relatives (FDR) of patients with diabetes from repeatedly measured diabetes data.

METHODS

We used data from 1319 FDR's of patients with diabetes followed for 8 years. Association and predictive performance of weight (Wt), body mass index (BMI), waist and hip circumferences (WC and HC) and their ratio (WHR), waist-height ratio (WHtR) and a body shape index (ABSI) in relation to future diabetes were evaluated by using Cox regression and joint longitudinal-survival modeling.

RESULTS

According to Cox regression, in total sample, WC, HC, Wt, WHtR and BMI had significant direct association with diabetes (all p < 0.01) with the best predictive ability for WHtR (concordance probability estimate = 0.575). Joint modeling suggested direct associations between diabetes and WC, WHR, Wt, WHtR and BMI in total sample (all p < 0.05). According to LPML criterion, WHtR was the best predictor in both total sample and females with LPML of -2666.27 and -2185.67, respectively. However, according to AUC criteria, BMI had the best predictive performance with AUC-JM = 0.7629 and dAUC-JM = 0.5883 in total sample. In females, both AUC criteria indicated that WC was the best predictor followed by WHtR.

CONCLUSION

WC, WHR, Wt, WHtR and BMI are among candidate anthropometric measures to be monitored in diabetes prevention programs. Larger multi-ethnic and multivariate research are warranted to assess interactions and identify the best predictors in subgroups.

Optimal cut-points of different anthropometric indices and their joint effect in prediction of type 2 diabetes: results of a cohort study

Background

To determine the anthropometric indices that would predict type 2 diabetes (T2D) and delineate their optimal cut-points.

Methods

In a cohort study, 7017 Iranian adults, aged 20–60 years, free of T2D at baseline were investigated. Using Cox proportional hazard models, hazard ratios (HRs) for incident T2D per 1 SD change in body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR), waist to hip ratio (WHR), and hip circumference (HC) were calculated. The area under the receiver operating characteristics (ROC) curves (AUC) was calculated to compare the discriminative power of anthropometric variables for incident T2D. Cut-points of each index were estimated by the maximum value of Youden’s index and fixing the sensitivity at 75%. Using the derived cut-points, joint effects of BMI and other obesity indices on T2D hazard were assessed.

Results

During a median follow-up of 12 years, 354 men, and 490 women developed T2D. In both sexes, 1 SD increase in anthropometric variables showed significant association with incident T2D, except for HC in multivariate adjusted model in men. In both sexes, WHtR had the highest discriminatory power while HC had the lowest. The derived cut-points for BMI, WC, WHtR, WHR, and HC were 25.56 kg/m², 89 cm, 0.52, 0.91, and 96 cm in men and 27.12 kg/m², 87 cm, 0.56, 0.83, and 103 cm in women, respectively. Assessing joint effects of BMI and each of the obesity measures in the prediction of incident T2D showed that among both sexes, combined high values of obesity indices increase the specificity for the price of reduced sensitivity and positive predictive value.

Conclusions

Our derived cut-points differ between both sexes and are different from other ethnicities.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5611-6) contains supplementary material, which is available to authorized users.

Diabetes mellitus and bone health: epidemiology, etiology and implications for fracture risk stratification

Skeletal fractures can result when there are co-morbid conditions that negatively impact bone strength. Fractures represent an important source of morbidity and mortality, especially in older populations. Diabetes mellitus is a metabolic disorder that has reached worldwide epidemic proportions and is increasingly being recognized as a risk factor for fracture. Type 1 and Type 2 diabetes have different effects on bone mineral density but share common pathways, which lead to bone fragility. In this review, we discuss the available data on diabetes and fractures, bone density and the clinical implications for fracture risk stratification in current practice.

Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a global epidemic associated with increased health expenditure, and low quality of life. Many non-genetic risk factors have been suggested, but their overall epidemiological credibility has not been assessed.

METHODS

We searched PubMed to capture all meta-analyses and Mendelian randomization studies for risk factors of T2DM. For each association, we estimated the summary effect size, its 95% confidence and prediction interval, and the I2 metric. We examined the presence of small-study effects and excess significance bias. We assessed the epidemiological credibility through a set of predefined criteria.

RESULTS

We captured 86 eligible papers (142 associations) covering a wide range of biomarkers, medical conditions, and dietary, lifestyle, environmental and psychosocial factors. Adiposity, low hip circumference, serum biomarkers (increased level of alanine aminotransferase, gamma-glutamyl transferase, uric acid and C-reactive protein, and decreased level of adiponectin and vitamin D), an unhealthy dietary pattern (increased consumption of processed meat and sugar-sweetened beverages, decreased intake of whole grains, coffee and heme iron, and low adherence to a healthy dietary pattern), low level of education and conscientiousness, decreased physical activity, high sedentary time and duration of television watching, low alcohol drinking, smoking, air pollution, and some medical conditions (high systolic blood pressure, late menarche age, gestational diabetes, metabolic syndrome, preterm birth) presented robust evidence for increased risk of T2DM.

CONCLUSIONS

A healthy lifestyle pattern could lead to decreased risk for T2DM. Future randomized clinical trials should focus on identifying efficient strategies to modify harmful daily habits and predisposing dietary patterns.

Recent trends in the prevalence of type 2 diabetes and the association with abdominal obesity lead to growing health disparities in the USA: An analysis of the NHANES surveys from 1999 to 2014

AIM

To assess whether the secular trends in type 2 diabetes prevalence differ between abdominally obese and non-obese individuals.

METHODS

Data from the National Health and Nutrition Examination Surveys (NHANES) were used to estimate the prevalence of type 2 diabetes and abdominal obesity among individuals aged ≥20 years in the USA from 1999/2000 to 2013/2014, after standardization to the age, sex and ethnicity population distribution estimates on January 1, 2014, as published by the US Census Bureau.

RESULTS

The prevalence of abdominal obesity in the US population increased from 47.4% (95% confidence interval [CI] 42.6-52.2) in 1999/2000 to 57.2% (95% CI 55.9-58.5) in 2013/2014. A significant increase was observed in all age groups: 20 to 44, 45 to 64, and ≥65 years. The prevalence of type 2 diabetes has also increased from 8.8% (95% CI 7.2-10.4) in 1999/2000 to 11.7% (95% CI 10.9-12.6) in 2013/2014, with no substantial change in trend over the recent years. However, the increase in the prevalence of type 2 diabetes was limited to individuals with abdominal obesity, and more specifically to individuals aged ≥45 years with abdominal obesity, with no significant change in prevalence in the non-obese group and in individuals aged <45 years.

CONCLUSION

These findings highlight the critical importance of abdominal obesity-both as a likely key contributor to the continuing epidemic of type 2 diabetes in the USA and as a priority target for public health interventions.

Comparison of adiposity indicators associated with fasting-state insulinemia, triglyceridemia, and related risk biomarkers in a nationally representative, adult population

AIMS

We hypothesized that height-corrected abdominal size (supine sagittal abdominal diameter/height ratio [SADHtR] or waist circumference/height ratio [WHtR]) would associate more strongly than body mass index (BMI, weight/height²) with levels of fasting insulin, triglycerides, and three derived biomarkers of insulin resistance.

METHODS

Anthropometry, including SAD by caliper, was collected on 4398 adults in the 2011-2014 National Health and Nutrition Examination Survey. For comparison purposes, each adiposity indicator was scaled to its population-based, sex-specific, interquartile range (IQR). For each biomarker we created four outcome groups based on equal-sized populations with ascending values. Multivariable polytomous logistic regression modeled the relationships between the adiposity indicators and each biomarker.

RESULTS

Highest-group insulin was associated with a one-IQR increment of BMI (RR 4.3 [95% CI 3.9-4.9]), but more strongly with a one-IQR increment of SADHtR (RR 5.7 [5.0-6.6]). For highest-group HOMA-IR the RR for BMI (4.2 [3.7-4.6]) was less than that of SADHtR (6.0 [5.1-7.0]). Similarly, RRs for BMI were smaller than those for SADHtR applying to highest-group triglycerides (RR 1.6 vs 2.1), triglycerides/HDL-cholesterol (RR 1.9 vs 2.4) and TyG index (RR 1.7 vs 2.2) (all p < .001). The RRs for WHtR were consistently between those for SADHtR and BMI. The top 25% of insulin resistance among US adults was estimated to lie above adiposity thresholds of 0.140 for SADHtR, 0.606 for WHtR, or 29.6 kg/m² for BMI.

CONCLUSIONS

Relative abdominal size rather than relative weight may better define adiposity associated with homeostatic insulin resistance. These population-based, cross-sectional findings could improve anthropometric prediction of cardiometabolic risk.

Adiposity cut-off points for cardiovascular disease and diabetes risk in the Portuguese population: The PORMETS study

Objectives

The contribution of adiposity to cardiovascular and diabetes risk justifies the inclusion of an adiposity measure, usually waist circumference, in the definition of metabolic syndrome. However, waist circumference thresholds differ across populations. Our aim was to assess which adiposity measure performs the best in identifying the metabolic syndrome in a sample of Portuguese participants and to estimate cut-off values for these measures.

Methods

Data were obtained from a cross-sectional study (PORMETS study) conducted in Portugal between 2007 and 2009. A representative sample of non-institutionalized adults, comprising 3,956 participants, aged 18 years and older, was evaluated. A structured questionnaire was administered, collecting information on personal medical history, socio-demographics and behavioral characteristics. Anthropometrics, blood pressure and venous blood samples were also obtained. Metabolic syndrome was defined according to the Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology recommended criteria. Elevated cardiometabolic risk was considered when two or more of the four criteria of metabolic syndrome were present, excluding the waist circumference component. A receiver operating characteristic curve was used to estimate cut-off points.

Results

This study found that waist-to-height ratio, waist circumference and body adiposity index performed better than other adiposity measures, such as body mass index. The estimated cut-off points for waist-to-height ratio, waist circumference and body adiposity index in women and men were 0.564 / 89 cm / 27.4 and 0.571 / 93.5 cm / 25.5, respectively.

Conclusion

As waist circumference is currently used as the adiposity measure in the definition of metabolic syndrome and as no relevant differences were observed between this measure and waist-to-height ratio, it is likely that no modification to the metabolic syndrome definition needs to be proposed. Moreover, this study also confirmed the applicability of European cut-off points in the Portuguese population.

Short-term intermittent energy restriction interventions for weight management: a systematic review and meta-analysis

This systematic review synthesized the available evidence on the effect of short-term periods of intermittent energy restriction (weekly intermittent energy restriction; ≥7-d energy restriction) in comparison with usual care (daily continuous energy restriction), in the treatment of overweight and obesity in adults. Six electronic databases were searched from inception to October 2016. Only randomized controlled trials of interventions (≥12 weeks) in adults with overweight and obesity were included. Five studies were included in this review. Weekly intermittent energy restriction periods ranged from an energy intake between 1757 and 6276 kJ/d^-1 . The mean duration of the interventions was 26 (range 14 to 48) weeks. Meta-analysis demonstrated no significant difference in weight loss between weekly intermittent energy restriction and continuous energy restriction post-intervention (weighted mean difference: -1.36 [-3.23, 0.51], p = 0.15) and at follow-up (weighted mean difference: -0.82 [-3.76, 2.11], p = 0.58). Both interventions achieved comparable weight loss of >5 kg and therefore were associated with clinical benefits to health. The findings support the use of weekly intermittent energy restriction as an alternative option for the treatment of obesity. Currently, there is insufficient evidence to support the long-term sustainable effects of weekly intermittent energy restriction on weight management.

Anthropometric Indicators of Adiposity Related to Body Weight and Body Shape as Cardiometabolic Risk Predictors in British Young Adults: Superiority of Waist-to-Height Ratio

Frequently reported poor dietary habits of young adults increase their risk of metabolic syndrome (MetS). Excess adiposity is the most established predictor of MetS, and numerous anthropometric measures have been proposed as proxy indicators of adiposity. We aimed to assess prevalence of MetS in young adult population and to make comparison between weight- and shape-oriented measures of adiposity to identify the best index in association with measured body fat and as a risk predictor for MetS. Healthy males and females aged 18-25 years from the Northwest of England were recruited using convenience sampling (n=550). As part of the assessment of the overall health of young adults, the biochemical variables and adiposity measures BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), new BMI, Body Adiposity Index (BAI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), and A Body Shape Index (ABSI) were assessed. Linear regression analysis was used to investigate the association between the proxy indices of adiposity and measured percentage body fat. The odds ratio with 95% confidence interval was used to investigate the relationship between cardiometabolic (CM) risk factors and proxy measures of adiposity. The discriminatory power of these measures for diagnosis of MetS was investigated using area under the receiver operating characteristic curve. Body weight-related indicators of adiposity, particularly CUN-BAE, had stronger association with measured body fat compared with body shape-related indices. In relation with MetS, body shape-related indices, particularly elevated WC and WHtR, had stronger associations with CM risk compared with body weight-related measures. Amongst all indices, the best predictor for CM risk was WHtR, while ABSI had the weakest correlation with body fat, MetS, and CM risk. Indices directly associated with WC and specifically WHtR had greater diagnostic power in detection of CM risk in young adults.

Relationship between Lipid Phenotypes, Overweight, Lipid Lowering Drug Response and KIF6 and HMG-CoA Genotypes in a Subset of the Brisighella Heart Study Population

The existence of genetic traits might explain the susceptibility to develop hypercholesterolemia and the inter-individual differences in statin response. This study was performed to evaluate whether individuals' polymorphisms in HMG-CoA and KIF6 genes are independently associated with hypercholesterolemia, other lipid-associated traits, and statin response in unselected individuals enrolled in the Brisighella heart study (Survey 2012). A total of 1622 individuals, of which 183 under statin medication, were genotyped for a total of five polymorphisms (KIF6 rs20455, rs9471077, rs9462535; HMG-CoA rs3761740, rs3846662). The relationships between the five loci and clinical characteristics were analyzed. The principal basic parameters calculated on 12 h fasting blood included total cholesterol (TC), High Density Lipoprotein Cholesterol (HDL-C), Low-Density Lipoprotein Cholesterol (LDL-C), and triglycerides (TG). Hypercholesterolemia was defined as a TC >200 mg/dL or use of lipid-lowering medication. 965 individuals were characterized by hypercholesterolemia; these subjects were significantly older (p < 0.001), with body mass index (BMI) and waist circumference significantly higher (p < 0.001) compared to the others. HMG-CoA rs3846662 GG genotype was significantly over-represented in the hypercholesterolemic group (p = 0.030). HMG-CoA rs3846662 genotype was associated with the level of TC and LDL-C. Furthermore, in the same subset of untreated subjects, we observed a significant correlation between the KIF6 rs20455 and HDL-C. KIF6 variants were associated with a significantly lower (rs20455) or higher (rs9471077 and rs9462535) risk of obesity, in males only. No association between responsiveness to statins and the polymorphisms under investigation were observed. Our results showed associations between HMG-CoA rs3846662 and KIF6 rs20455 and lipid phenotypes, which may have an influence on dyslipidemia-related events. Moreover, this represents the first study implicating KIF6 variants with obesity in men, and point to the possible involvement of this genetic locus in the known gender-related differences in coronary artery disease.

Prediction of a new body shape index and body adiposity estimator for development of type 2 diabetes mellitus: The Rural Chinese Cohort Study

To compare the ability of a body shape index (ABSI) and body adiposity estimator (BAE) to BMI, waist circumference (WC) and waist:height ratio (WHtR) for predicting development of type 2 diabetes mellitus (T2DM) in rural adult Chinese. The prospective cohort study included 11 687 eligible participants who were free of T2DM at baseline. The risk of new-onset T2DM for ABSI, BAE, BMI, WC and WHtR quintiles was estimated by Cox proportional-hazards regression at follow-up. We also compared the power of ABSI and BAE to BMI, WC and WHtR for predicting the development of T2DM. With increasing ABSI, BAE, BMI, WC and WHtR, T2DM incidence was substantially increased (Ptrend<0·0001). After adjustment for multi-covariates, risk of T2DM was increased from the second to fifth quintile as compared with first quintile for ABSI (1·27; 95 % CI 0·95, 1·69; 1·35; 95 % CI 1·00, 1·82; 1·75; 95 % CI 1·33, 2·32 and 1·87; 95 % CI 1·40, 2·49; Ptrend<0·0001); BAE (1·82; 95 % CI 1·38, 2·41; 1·93; 95 % CI 1·38, 2·68; 2·73; 95 % CI 1·94, 3·84 and 4·18; 95 % CI 2·98, 5·87; Ptrend<0·0001); BMI (1·42; 95 % CI 1·03, 1·97; 1·62; 95 % CI 1·18, 2·23; 2·59; 95 % CI 1·92, 3·50 and 3·90; 95 % CI 2·90, 5·26; Ptrend<0·0001); WC (1·53; 95 % CI 1·08, 2·17; 1·66; 95 % CI 1·18, 2·33; 2·72; 1·97, 3·76 and 4·09; 95 % CI 2·97, 5·62; Ptrend<0·0001); and WHtR (1·40; 95 % CI 0·98, 1·99; 2·06; 95 % CI 1·47, 2·88; 2·90; 95 % CI 2·10, 4·01 and 4·22; 95 % CI 3·05, 5·85; Ptrend<0·0001). ABSI, BAE, BMI, WC and WHR were effective and comparable in discriminating cases from non-cases of T2DM. Risk of T2DM was increased with elevated ABSI and BAE, but the predictive ability for T2DM did not differ than that of BMI, WC and WHtR in a rural Chinese population.

The Serum Level of KL-6 Is Associated with the Risk of Insulin Resistance and New-onset Diabetes Mellitus: The Tanno-Sobetsu Study

Objective Inflammatory cytokines generated in visceral fat have been shown to contribute to the development of insulin resistance. The involvement of pulmonary inflammation in insulin resistance remains unclear, but smoking is known to be a risk factor for diabetes as well as chronic obstructive pulmonary disease. We herein examined the hypothesis that increased serum levels of lung interstitial injury biomarkers [surfactant protein (SP)-A, SP-D and Krebs von den Lungen (KL)-6] are associated with the risk of diabetes development. Methods For cross-sectional and longitudinal analyses, we enrolled 750 apparently healthy non-diabetic subjects who received annual examinations in 2011 or 2012 in the Tanno-Sobetsu cohort. Results A cross-sectional analysis showed that distinct clinical parameters were associated with SP-A, SP-D and KL-6. In a multiple regression analysis, independent explanatory variables were Brinkman index and brain natriuretic peptide (BNP) for SP-A, sex (women), BNP and body mass index (BMI) for SP-D, and age and BMI for KL-6. A longitudinal analysis of 415 subjects who received annual examinations in both 2011 and 2014 showed that 13 (3.1%) of the patients developed type 2 diabetes during the 3-year follow-up. A multiple logistic regression analysis showed the KL-6 levels, systolic blood pressure and homeostasis model assessment of insulin resistance (HOMA-IR) in 2011 to be independently associated with new-onset diabetes. In a multiple regression analysis for HOMA-IR in 2014, the KL-6 level and BMI in 2011 were selected as explanatory variables. Conclusion A modest elevation of the serum KL-6 level is therefore considered to be associated with the risk for insulin resistance development and new-onset diabetes mellitus in a general population.