Measurement of abdominal fat by magnetic resonance imaging, dual-energy X-ray absorptiometry and anthropometry in non-obese men and women

Kamel, Emad G.; McNeill, Geraldine; Han, Thang S.; Fw, Smith; Avenell, Alison; Davidson, Lance E.; Tothill, P.

doi:10.1038/sj.ijo.0800904

Cited by 117 publications

(110 citation statements)

References 19 publications

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“…This can result in misclassification if both waist and hip circumference are determinants of risk [25]. WHR also has lower correlations with visceral fat [26]. In our study, the model containing both waist and hip circumference had stronger associations as well greater explanatory power than the model containing WHR.…”

Section: Resultsmentioning

confidence: 51%

Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

et al. 2010

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Aims/hypotheses We determined: (1) which of BMI, waist circumference, hip circumference and WHR has the strongest association and explanatory power for newly diagnosed type 2 diabetes and glucose status; and (2) the impact of considering two measures simultaneously. We also explored variation in anthropometric associations by sex and ethnicity. Methods We performed cross-sectional analysis of 22,293 men and women who were from five ethnic groups and 21 countries, and at risk of developing type 2 diabetes. Standardised anthropometric associations with type 2 diabetes and AUC of glucose status from OGTT (AUC OGTT ) were determined using multiple regression. Explanatory power was assessed using the c-statistic and adjusted r 2 . Results An increase in BMI, waist circumference or WHR had similar positive associations with type 2 diabetes, AUC OGTT and explanatory power after adjustment for age, sex, smoking and ethnicity (p <0.01). However, using BMI and WHR together resulted in greater explanatory power than with other models (p< 0.01). Associations were strongest when waist circumference and hip circumference were used together, a combination that had greater explanatory power than other models except for BMI and WHR together (p<0.01). Results were directionally similar according to sex and ethnicity; however, significant variations in associations were observed among these subgroups. Conclusions/interpretation The combination of BMI and WHR, or of waist circumference and hip circumference has the best explanatory power for type 2 diabetes and glucose status compared with a single anthropometric measure. Measurement of waist circumference and hip circumference is required to optimally identify people at risk of type 2 diabetes and people with elevated glucose levels.

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Section: Resultsmentioning

confidence: 51%

Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

et al. 2010

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“…[1][2][3][4] Clustering of these CV risk factors in children and adolescents tends to track into adult life. [5][6][7][8][9] CV disease appears to be related specifically to intraabdominal fat (visceral adipose tissue) 10,11 of which waist circumference (WC) provides a good and clinically useful measure, [12][13][14][15][16][17] supporting the growing view that WC is a better measure of CV risk than body mass index (BMI) in both children and adults. [18][19][20][21] Ethnic differences of WC have been described in adults 22,23 but have not been studied in children, although reference data for WC are available from a number of different countries.…”

Section: Introductionmentioning

confidence: 97%

Waist circumference and body mass index in Chinese children: cutoff values for predicting cardiovascular risk factors

et al. 2006

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Background: Body mass index (BMI) and waist circumference (WC) correlate with cardiovascular (CV) risk factors in childhood which track into adulthood. WC provides a measure of central obesity, which has been specifically associated with CV risk factors. Reference standards for WC, and for WC and BMI risk threshold values are not established in Chinese children. Objectives: To construct reference percentile charts of WC, establish relationships between WC, BMI and other risk factors, and propose WC and BMI threshold values predictive of CV risk factors in Hong Kong ethnic Chinese children. Methods: Weight, height, waist and hip circumference were measured in 2593 (52% boys, 47% girls) randomly sampled Hong Kong school children aged 6-12 years. In 958 of these and 97 additional overweight children (n ¼ 1055), the relationships between WC, BMI, waist/hip and waist/height ratio and six age-adjusted CV risk factors (485% percentile levels of blood pressure (BP), fasting triglycerides, low-density lipoprotein (LDL) cholesterol, glucose and insulin levels, and o15% percentile levels of high-density lipoprotein (HDL) cholesterol) were studied. Receiver-operating characteristic analysis was employed to derive optimal age-adjusted sex-specific WC and BMI thresholds for predicting these measures of risk. Results: WC percentiles were constructed. WC correlated slightly more than BMI with CV risk factors and most strongly with insulin and systolic BP, but poorly or not with LDL and glucose. Optimal WC and BMI risk thresholds for predicting four of these six CV risk factors were ca. the 85th percentiles (sensitivities B0.8, specificities B0.87) with age-specific cutoff values in girls/ boys from B57/58 to B71/76 cm and 17/18 to 22/23 kg/m 2 . Conclusion: These are the first set of WC reference data for Chinese children. WC risk cutoff values are proposed which, despite a smaller waist in Chinese children, are similar to those reported for American children. WC percentiles may reflect population risk.

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“…7,8 Dual energy X-ray absorptiometry (DEXA) provides a relatively rapid and accurate assessment of total body fat with relatively low radiation exposure but does not directly quantify VAAT. [9][10][11] Whereas CT provides more accurate estimation of VAAT, subjects are exposed to ionizing radiation, which makes it unsuitable for large-scale research. 12,13 With the advantages of noninvasiveness and excellent soft-tissue contrast by using different imaging parameters, MRI provides a method to measure adipose tissue safely and accurately.…”

Section: Introductionmentioning

confidence: 99%

“…12,13 With the advantages of noninvasiveness and excellent soft-tissue contrast by using different imaging parameters, MRI provides a method to measure adipose tissue safely and accurately. 8,10,[14][15][16][17][18][19][20][21][22][23][24][25]27 However, measuring the fat quantity and distribution in the abdomen by MRI is generally laborious. Two steps are required to identify the volume of VAAT.…”

Section: Introductionmentioning

confidence: 99%

“…It is often timeconsuming to delineate the region of interest (ROI) of VAAT because of the complex structure of the viscera. 26 Almost all the previous studies of this step have reported requiring more or less human interventions, which are either laborious or subject to technical problems 8,10,[14][15][16][17]19,[24][25] (Table 1). For example, Elbers et al 15 measured visceral fat areas using an algorithmic seed-growing procedure.…”

Section: Introductionmentioning

confidence: 99%

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Fully automated large-scale assessment of visceral and subcutaneous abdominal adipose tissue by magnetic resonance imaging

et al. 2006

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Objective: To describe and evaluate a fully automated method for characterizing abdominal adipose tissue from magnetic resonance (MR) transverse body scans. Methods: Four MR pulse sequences were applied: SE, FLAIR, STIR, and FRFSE. On 39 subjects, each abdomen was traversed by 15 contiguous transaxial images. The total abdominal adipose tissue (TAAT) was calculated from thresholds obtained by slice histogram analysis. The same thresholds were also used in the manual volume calculation of TAAT, subcutaneous abdominal adipose tissue (SAAT) and visceral abdominal adipose tissue (VAAT). Image segmentation methods, including edge detection, mathematical morphology, and knowledge-based curve fitting, were used to automatically separate SAAT from VAAT in various 'nonstandard' cases such as those with heterogeneous magnetic fields and movement artefacts. Results: The percentage root mean squared errors of the method for SAAT and VAAT ranged from 1.0 to 2.7% for the four sequences. It took approximately 7 and 15 min to complete the 15-slice volume estimation of the three adipose tissue classes using automated and manual methods, respectively. Conclusion:The results demonstrate that the proposed method is robust and accurate. Although the separation of SAAT and VAAT is not always perfect, this method could be especially helpful in dealing with large amounts of data such as in epidemiological studies.

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Measurement of abdominal fat by magnetic resonance imaging, dual-energy X-ray absorptiometry and anthropometry in non-obese men and women

Cited by 117 publications

References 19 publications

Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

Waist circumference and body mass index in Chinese children: cutoff values for predicting cardiovascular risk factors

Fully automated large-scale assessment of visceral and subcutaneous abdominal adipose tissue by magnetic resonance imaging

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