Body volume index

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The Body Volume Index (BVI) is a new measurement for obesity, proposed as an alternative and enhancement to the body mass index (BMI).

People of different age, gender or ethnicity will have different body shapes, with different weight distribution and recent studies have highlighted the limitations of BMI as an indicator of individual health risk.[1][2][3]

Development of the Body Volume Index (BVI)[edit]

BVI was originally devised in February 2000 and looks at the relationship between mass and volume distribution (i.e. where weight is distributed on the body); a new, modern-day measurement for measuring obesity; an alternative to the BMI, originally conceived between 1830 and 1850.[4][5]

The data needed to calculate a person's BVI originally relied on data collection from 3D Scanners,[6] equipped with several cameras to capture the dimensions of different parts of a person's body. By December 2016, over 400,000 men, women and children had been measured using this 3D technology, originally developed to measure body circumferences for retail clothing fit. The measurement extraction software has now been configured to develop part volume and body composition measurement for healthcare in 3D.[citation needed]

A 10-year program of research and development has been undertaken; the Body Volume Index uses an algorithm based on MRI data and detailed Body Composition data[7] to make an inference as to the body's distribution of weight and the distribution of muscle and fat.

Distinguishing between BVI and BMI[edit]

Based on height and weight, BMI was originally conceived between 1830 and 1850 by a Belgian polymath called Adolphe Quetelet. BMI uses these measurements to determine whether a person is carrying an appropriate amount of weight for an average person of their height. The Body Mass Index or BMI is a measurement that has been used by healthcare professionals to aid diagnosis of obese and under-weight people for many years and has become a standard worldwide for the assessment of risk and for population statistics.

BVI allows for differentiation between people who have been assigned the same BMI rating, but who have a different body shape and weight distribution. Specifically, BVI divides the 3D body image of a person into 7 distinct sections; Chest, Abdomen, Pelvis, Right Arm, Left arm, Right Leg, Left Leg. The Head, Hands and feet are specifically excluded as extra weight or fat in these areas are not considered to be a risk to general health. After primary development, initial validation was undertaken by Heartlands Hospital, an NHS Obesity, Diabetes and Endocrinology Centre in the UK. This was followed by clinical testing in the US by Mayo Clinic in Rochester, Minnesota. Other organisations such as Aston University, University of Hull, the University of Westminster and the Medical Research Council have also been involved in research and development program.[citation needed]

8 women with the same BMI rating (BMI - 30) but with different weight distribution and abdominal volume, so they have different BVI ratings

Measuring Body Volumes[edit]

There has been an awareness in recent years that abdominal fat and weight around the abdomen constitute a greater health risk,[citation needed] commonly known as central obesity. The difference between visceral fat and subcutaneous fat has become more studied in recent years,[8] BVI, though analysis of part volumes provides a way of measuring the amount of fat an individual has in different parts of the body, based upon the volume of that part of the body. An accurate reading of this has until now only been obtainable through either an MRI Scan or autopsy. BVI is based upon the principle that where weight is distributed on the body is perhaps a better indication of risk than the total weight or total fat content of a person.[citation needed]

A Study by The Mayo Clinic in 1995 looked into the effectiveness of measuring and predicting visceral and subcutaneous fat using computed tomography and dual-energy x-ray absorptiometry.[9] It was concluded that "a single-slice CT scan (or other imaging technique) with or without DXA is required for accurate predictions of intraabdominal fat". An initial pilot study highlighted the potential of BVI as a motivational tool for weight loss in patients and a further study aimed to assess the validity and reproducibility of the BVI scanner in measuring anthropometric markers of obesity.[10]

Comparative validation of the reliability of automatic measurement as opposed to manual measurement concluded that the scanner is a reliable, valid and reproducible method to measure waist and hip circumferences.[11]

Development of BVI continued in 2016 by the collaborators involved and this has included further assignment of BVI values for children aged 4–17, collation of 3D data in the US and Europe for normative reference data and development of BVI applications for deployment alongside BMI to augment and provide an enhanced additional measurement.

See also[edit]

References[edit]

  1. ^ Romero-Corral, A; Somers, V K; Sierra-Johnson, J; Thomas, R J; Collazo-Clavell, M L; Korinek, J; Allison, T G; Batsis, J A; Sert-Kuniyoshi, F H; Lopez-Jimenez, F (2008). "Accuracy of body mass index in diagnosing obesity in the adult general population". International Journal of Obesity. 32 (6): 959–66. doi:10.1038/ijo.2008.11. PMC 2877506Freely accessible. PMID 18283284. 
  2. ^ Romero-Corral, Abel; Montori, Victor M; Somers, Virend K; Korinek, Josef; Thomas, Randal J; Allison, Thomas G; Mookadam, Farouk; Lopez-Jimenez, Francisco (2006). "Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: A systematic review of cohort studies". The Lancet. 368 (9536): 666–78. doi:10.1016/S0140-6736(06)69251-9. PMID 16920472. 
  3. ^ Tomiyama, A J; Hunger, J M; Nguyen-Cuu, J; Wells, C (2016). "Misclassification of cardiometabolic health when using body mass index categories in NHANES 2005–2012". International Journal of Obesity. 40 (5): 883–6. doi:10.1038/ijo.2016.17. PMID 26841729. 
  4. ^ Romero-Corral, A; Somers, V K; Sierra-Johnson, J; Thomas, R J; Collazo-Clavell, M L; Korinek, J; Allison, T G; Batsis, J A; Sert-Kuniyoshi, F H; Lopez-Jimenez, F (2008). "Accuracy of body mass index in diagnosing obesity in the adult general population". International Journal of Obesity. 32 (6): 959–66. doi:10.1038/ijo.2008.11. PMC 2877506Freely accessible. PMID 18283284. 
  5. ^ Romero-Corral, Abel; Montori, Victor M; Somers, Virend K; Korinek, Josef; Thomas, Randal J; Allison, Thomas G; Mookadam, Farouk; Lopez-Jimenez, Francisco (2006). "Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: A systematic review of cohort studies". The Lancet. 368 (9536): 666–78. doi:10.1016/S0140-6736(06)69251-9. PMID 16920472. 
  6. ^ Treleaven, Philip; Wells, Jonathan (2007). "3D Body Scanning and Healthcare Applications". Computer. 40 (7): 28–34. doi:10.1109/MC.2007.225. 
  7. ^ Tahrani, Abd; Boelaert, Kristien; Barnes, Richard; Palin, Suzanne; Field, Annmarie; Redmayne, Helen; Aytok, Lisa; Rahim, Asad (10 April 2008). "Body volume index: time to replace body mass index?". Endocrine Abstracts. Society for Endocrinology, British Endocrine Societies. 15: 104. 
  8. ^ Tran, Thien T.; Yamamoto, Yuji; Gesta, Stephane; Kahn, C. Ronald (2008). "Beneficial Effects of Subcutaneous Fat Transplantation on Metabolism". Cell Metabolism. 7 (5): 410–20. doi:10.1016/j.cmet.2008.04.004. PMC 3204870Freely accessible. PMID 18460332. Lay summaryJoslin Diabetes Center (May 6, 2008). 
  9. ^ Jensen, M. D.; Kanaley, J. A.; Reed, J. E.; Sheedy, P. F. (1995). "Measurement of abdominal and visceral fat with computed tomography and dual-energy x-ray absorptiometry". The American journal of clinical nutrition. 61 (2): 274–8. PMID 7840063. 
  10. ^ Boelaert, Kristien; Palin, Suzanne; Field, Annmarie; Rahim, Asad; Barnes, Richard (2008). "The impact of 3D body images on motivating weight loss in overweight individuals". Endocrine Abstracts. 
  11. ^ Korenfeld, Y.; Ngwa, T.; Friedman, L.; Romero-Corral, A.; Somers, V; Xu, L.; Albuquerque, F.; Sert-Kuniyoshi, F.; Ockay, A.; Lopez-Jimenez, F. (March 2009). "Validation of a Novel 3D Body Scanner for Obesity Anthropometric Measurements". AHA. 

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