Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program

Bray, George A.; Jablonski, Kathleen A.; Fujimoto, Wilfred Y.; Barrett‐Connor, Elizabeth; Haffner, Steven M.; Hanson, Robert L.; Hill, James O.; Hubbard, Van S.; Kriska, Andrea M.; Stamm, Elizabeth R.; Pi‐Sunyer, F. Xavier

doi:10.1093/ajcn/87.5.1212

Cited by 220 publications

(202 citation statements)

References 39 publications

Supporting

Mentioning

187

Contrasting

Unclassified

Order By: Relevance

“…Studies carried out in different ethnicities showed that VAT, but not SAT, was strongly associated with the development of diabetes 16,17 and coronary heart disease. 18 Increased VAT was associated with impaired glucose tolerance 19 or insulin resistance.…”

Section: Discussionmentioning

confidence: 98%

Identification of waist circumference cutoffs for abdominal obesity in the Chinese population: a 7.8-year follow-up study in the Shanghai urban area

Bao

Hou

et al. 2009

Int J Obes

View full text Add to dashboard Cite

Aim: To identify the appropriate visceral adipose tissue (VAT) cutoff values for the diagnosis of abdominal obesity in predicting diabetes and the corresponding waist circumference in the Chinese population. Methods: At baseline, 381 volunteers aged 35-75 years were enrolled without diabetes from the Shanghai urban area. Anthropometry and VAT area determined by magnetic resonance imaging were measured. During the average 7.8 years of follow-up, glucose tolerance was monitored. Receiver operating characteristic (ROC) curve analysis was used to define the optimal cutoff points for abdominal obesity. Results: At the end of the study, 290 participants were followed up, in which 63 participants developed diabetes. Using ROC curve analyses in participants with normal glucose regulation, the appropriate VAT cutoff was 90 cm 2 for both genders to predict diabetes development. In logistic regression models, the relative risks (95% confidence intervals) of VAT value over 90 cm 2 were 3.35 (1.10-10.18, P ¼ 0.033) in men and 4.57 (1.73-12.07, P ¼ 0.002) in women after adjusted for age, impaired glucose regulation, hypertension and dyslipidemia. The optimal waist circumference cutoffs were 88 cm for men and 82 cm for women to indicate VAT value over 90 cm 2 in ROC analyses. Conclusion: VAT cutoff of 90 cm 2 is useful for defining visceral obesity in Chinese individuals. The appropriate waist circumference cutoffs for abdominal obesity are 88 cm for men and 82 cm for women in the Chinese population.

show abstract

Section: Discussionmentioning

confidence: 98%

Identification of waist circumference cutoffs for abdominal obesity in the Chinese population: a 7.8-year follow-up study in the Shanghai urban area

Bao

Hou

et al. 2009

Int J Obes

View full text Add to dashboard Cite

show abstract

“…3. Subcutaneous adipose tissue can be reliably measured by CT scan at the L2-L3 and L4-L5 disc spaces [25].…”

Section: Ligaments Thickness Estimationmentioning

confidence: 99%

“…Quantifying the adjustment of haptic feedback according to BMI can provide simulation of obese patients which are considered to be difficult. The size and shape of ligaments and vertebrae and the force required for the needle to traverse each tissue layer changes according to patient body shape [25].…”

Section: Body Shape Visualisation Using Mesh Deformationmentioning

confidence: 99%

Parametric model of human body shape and ligaments for patient-specific epidural simulation

Vaughan

Dubey

Wee

et al. 2014

Artificial Intelligence in Medicine

View full text Add to dashboard Cite

Objective: This work builds upon the concept of matching a person's weight, height and age to their overall body shape to create an adjustable three-dimensional model. A versatile and accurate predictor of body size and shape and ligament thickness is required to improve simulation for medical procedures. A model which is adjustable for any size, shape, body mass, age or height would provide ability to simulate procedures on patients of various body compositions.Methods: Three methods are provided for estimating body circumferences and ligament thicknesses for each patient. The first method is using empirical relations from body shape and size. The second method is to load a dataset from a magnetic resonance imaging scan (MRI) or ultrasound scan containing accurate ligament measurements. The third method is a developed artificial neural network (ANN) which uses MRI dataset as a training set and improves accuracy using error back-propagation, which learns to increase accuracy as more patient data is added. The ANN is trained and tested with clinical data from 23088 patients. Results:The ANN can predict subscapular skinfold thickness within 3.54mm, waist circumference 3.92cm, thigh circumference 2.00cm, arm circumference 1.21cm, calf circumference 1.40cm, triceps skinfold thickness 3.43mm. Alternative regression analysis method gave overall slightly less accurate predictions for subscapular skinfold thickness within 3.75mm, waist circumference 3.84cm, thigh circumference 2.16cm, arm circumference 1.34cm, calf circumference 1.46cm, triceps skinfold thickness 3.89mm.for male or female patients aged 8-85. These calculations are used to display a 3D graphics model of the patient's body shape using OpenGL and adjusted by 3D mesh deformations. Conclusions:A patient-specific epidural simulator is presented using the developed body shape model, able to simulate needle insertion procedures on a 3D model of any patient size and shape.The developed ANN gave the most accurate results for body shape, size and ligament thickness.The resulting simulator offers the experience of simulating needle insertions accurately whilst allowing for variation in patient body mass, height or age.

show abstract

“…If less radiation exposure is desired, a measurement can be made in L1-L4 single scanning region. Visceral adipose tissue and subcutaneous adipose tissue can be measured at the L2-L3 and L4-L5 disc spaces [27].…”

Section: Ctmentioning

confidence: 99%

Methods for Body Composition Analysis in Adults

Ayvaz¹

2011

TOOBESJ

View full text Add to dashboard Cite

Abstract:Fat and lean components of the body including total body fat, fat-free mass and total body water and ectopic fat accumulation are important constituents that link obesity, aging, and chronic disease to subsequent morbidity and mortality. The methodology of body composition is based on a series of models characterized by progressive levels of anatomical complexity. A commonly used example is five-level model: atomic, molecular, cellular, tissue-system, whole body. Each body composition analysis method targets a component or a subcomponent of the five-level model of body composition. The choice of body composition analysis method greatly depends on the question being asked, the setting where the measurement is performed and the availability of measuring devices. Body composition analysis methods vary in complexity and precision, and range from simple field based methods to more technically challenging, laboratory based methods. Although several methods have been developed to assess body composition, anthropometric indices are simple, safe and cheap measures to quantify obesity. Body mass index, calculated from height and weight, is the most frequently used, quickest and the easiest measure. As body mass index does not differentiate peripheral from abdominal obesity, the use of waist circumference and waist-to-hip ratio was proposed in various guidelines. Waist-to-height ratio is emerging as a new anthropometric index with a potential for global use in different ethnic groups and in adults and children. The minimum measurements to be made in the basal evaluation of overweight patients are weight, height and waist circumference to calculate body mass index and waist-to-height ratio.

show abstract

Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program

Abstract: In the placebo and lifestyle groups, VAT at both cuts, WHR, and WC predicted diabetes. No measure predicted diabetes in the metformin group. CT provided no important advantage over these simple measures. SAT did not predict diabetes.

Cited by 220 publications

References 39 publications

Identification of waist circumference cutoffs for abdominal obesity in the Chinese population: a 7.8-year follow-up study in the Shanghai urban area

Identification of waist circumference cutoffs for abdominal obesity in the Chinese population: a 7.8-year follow-up study in the Shanghai urban area

Parametric model of human body shape and ligaments for patient-specific epidural simulation

Methods for Body Composition Analysis in Adults

Contact Info

Product

Resources

About