Health> Vol.4 No.12A, December 2012

The relationship between thermal imaging and waist circumference in young adults

DownloadDownload as PDF (Size:255KB)  HTML    PP. 1485-1491  

ABSTRACT

Technologies such as 3-dimensional body scanners and thermal cameras are currently being investigated to eliminate the traditional means of assessing anthropometrics in the overweight and obese population. The purpose of this study was to determine the potential for thermal imaging to assess the relationship between thermal patterning and anthropometrics in young adults. Participants were 18 - 24 year old men (n = 176) and women (n = 260) with different Body Mass Indices (BMI), somatotypes, and activity levels. Participants were weighed, body scanned and thermally imaged. Statistical treatment included descriptive statistics and ANOVA. Statistically significant differences between mean thermal ratings were found between the normal and abnormal groups as categorized by waist circumference for both males (p < 0.003) and females (p < 0.001). The mean ratings of the contour regions between normal and overweight/ obese groups were also found to be statistically different for both males (p < 0.01) and females (p < 0.004).

Cite this paper

Heuberger, R. , Kinnicutt, P. and Domina, T. (2012) The relationship between thermal imaging and waist circumference in young adults. Health, 4, 1485-1491. doi: 10.4236/health.2012.412A213.

References

[1] Flegal, K.M., Carroll, M.D., Ogden, C. and Curtin, L.R. (2010) Prevalence and trends in obesity among US adults, 1999-2008. Journal of the American Medical Association, 303, 235-241. doi:10.1001/jama.2009.2014
[2] Smith, D.A., Ness, E.M., Herbert, R., Schechter, C.B., Phillips, R.A., Diamond, J.A. and Landrigan, P.A. (2005) Abdominal diameter index: A more powerful anthropom- etric measure for prevalent coronary heart disease risk in adult males. Diabetes Obesity and Metabolism, 7, 370- 380. doi:10.1111/j.1463-1326.2004.00406.x
[3] Yusuf, S., Hawken, S., Ounpuu, S., Bautista, L., Franzosi, M.G., Commerford, P. and Anand, S.S. (2005) Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: A case-control study. The Lancet, 366, 1640-1649. doi:10.1016/S0140-6736(05)67663-5
[4] Ervin, B.R. (2009) Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003- 2006, National Health Statistics Reports, No. 13. www.cdc.gov/nchs/data/nhsr/nhsr013.pdf
[5] Andreassi, M.G. (2009) Metabolic syndrome, diabetes and atherosclerosis: Influence of gene-environment inter-action. Mutation Research, 667, 35-43. doi:10.1016/j.mrfmmm.2008.10.018
[6] Bays, H.E. (2009) “Sick fat”, metabolic disease and atherosclerosis. American Journal of Medicine, 122, S26- S37. doi:10.1016/j.amjmed.2008.10.015
[7] Thalmann, S. and Meier, C.A. (2007) Local adipose tissue depots as cardiovasculardiseaseriskfactors. Cardiovascular Research, 75, 690-701. doi:10.1016/j.cardiores.2007.03.008
[8] Koivistoinen, T., Hutri-K?h?nen, N., Juonala, M., Aatola, H., K??bi, T., Lehtim?ki, T., Viikari, J.S., Raitakari, O.T. and K?h?nen, M. (2011) Metabolic syndrome in child- hood and increased arterial stiffness in adulthood: The cardiovascular risk in young Finns study. Annals of Me- dicine, 43, 312-319. doi:10.3109/07853890.2010.549145
[9] Weiss, R. (2007) Fat distribution and storage: How much, where and how? European Journal of Endocrinology, 157, S39-S45.
[10] Brambilla, P., Bedogni, G., Moreno, L.A., Goran, M.I., Gutin, B., Fox, K.R. and Pietrobelli, A. (2006) Cross- validation of anthropometry against magnetic resonance imaging for the assessment of visceral and subcutaneous adipose tissue in children. International Journal of Obesity, 30, 23-30. doi:10.1038/sj.ijo.0803163
[11] Wells, J.C.K., Cole, T.J. and Treleaven, P. (2008) Age- variability in body shape associatedwith excess weight: The UK national sizing survey. Obesity, 16, 435-441. doi:10.1038/oby.2007.62
[12] Heuberger, R., Domina, T. and MacGillivray, M. (2008) Body scanning as a new anthropometric measurement tool for health-risk assessment. International Journal of Consumer Studies, 32, 34-40.
[13] Wells, J.C.K., Treleaven, P. and Charoensiriwath, S. (2012) Body shape by 3-D photonic scanning in Thai and UK adults: Comparison of national sizing surveys. International Journal of Obesity, J36, 148-154. doi:10.1038/ijo.2011.51
[14] Gropper, S.S., Simmons, K.P., Gaines, G., Drawdy, K., Saunders, D., Ulrich, P. and Connell, L.J. (2009) The freshman 15—A closer look. The Journal of American College Health, 58, 223-231. doi:10.1080/07448480903295334
[15] Ferreira, J.J., Mendonca, L.C., Nunes, L.A., Filho, A.C., Rebelatto, J.R. and Salvini, T.F. (2008) Exercise-associated thermographic changes in young and elderly subjects. Annals of Biomedical Engineering, 36, 1420-1427. doi:10.1007/s10439-008-9512-1
[16] Galic, S., Oakhill, J.S. and Steinberg, G.R. (2010) Adi-pose tissue as an endocrine organ. Molecular and Cellular Endocrinology, 316, 129-39. doi:10.1016/j.mce.2009.08.018
[17] Savastano, D.M., Gorbach, A.M., Eden, H.S., Brady, S.M., Reynolds, J.C. and Yanovski, J.A. (2009) Adiposity and human regional body temperature. The American Journal of Clinical Nutrition, 90, 1124-1131. doi:10.3945/ajcn.2009.27567
[18] Kinnicutt, P., Domina, T. and MacGillivray, M. (2011) Thermal pattern variations analyzed using 2D/3D mapping techniques among females. Journal of Textile and Apparel, Technology Management, 7, 1-15.
[19] Lindsey, J.C., Jacobson, D.L., Li, H., Houseman, E.A., Aldrovandi, G.M. and Mulligan, K. (2012) Using cluster heat maps to investigate relationships between body composition and laboratory measurements in HIV-infected and HIV-uninfected children and young adults. Journal of Acquired Immune Deficiency Syndromes, 59, 325-328. doi:10.1097/QAI.0b013e31823fdbec
[20] Sivanandam, S., Anburajan, M., Venkatraman, B., Menaka, M. and Sharath, D. (2012) Medical thermography: A diagnostic approach for type 2 diabetes based on non-contact infrared thermal imaging. Endocrine, 42, 343-351. doi:10.1007/s12020-012-9645-8
[21] Al-Nakhli, H.H., Petrofsky, J.S., Laymon, M.S., Arai, D., Holland, K. and Berk, L.S. (2012) The use of thermal infrared imaging to assess the efficacy of a therapeutic exercise program in individuals with diabetes. Diabetes Technology and Therapeutics, 14, 159-67. doi:10.1089/dia.2011.0187
[22] Spalding, S.J., Kwoh, C.K., Boudreau, R., Enama, J., Lunich, J., Huber, D. ... and Hirsch, R. (2008) Three-dimensional and thermal surface imaging produces reliable measures of joint shape and temperature: A potential tool for quantifying arthritis. Arthritis Research and Therapy, 10, e1-10. doi:10.1186/ar2360
[23] Fengzhi, L. and Li, Y. (2005) Effect of clothing material on thermal responses of the human body. Modeling Simulation Materials Science Engineering, 13, 809-827. doi:10.1088/0965-0393/13/6/002
[24] Ritchie, S.A. and Connell, J.M. (2007) The link between abdominal obesity, metabolic syndrome and cardiovascular disease. Nutrition Metabolism and Cardiovascular Diseases, 17, 319-326. doi:10.1016/j.numecd.2006.07.005

comments powered by Disqus

Copyright © 2014 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.