Head, Neck, Trunk, and Pelvis Tissue Mass Predictions for Older Adults using Anthropometric Measures and Dual-Energy X-Ray Absorptiometry

Charles A.J. Kahelin, Nicole C. George, Danielle L. Gyemi, David M. Andrews

Abstract


Background: Regression equations using anthropometric measurements to predict soft (fat mass [FM], lean mass [LM], wobbling mass [WM]) and rigid (bone mineral content [BMC]) tissue masses of the extremities and core body segments have been developed for younger adults (16-35 years), but not older adults (36-65 years). Tissue mass estimates such as these would facilitate biomechanical modeling and analyses of older adults following fall or collision-related impacts that might occur during sport and recreational activities. Purpose: The purpose of this study was to expand on the previously established tissue mass prediction equations of the head, neck, trunk, and pelvis for healthy, younger adults by generating a comparable set of equations for an older adult population. Methods: A generation sample (38 males, 38 females) was used to create head, neck, trunk, and pelvis tissue mass prediction equations via multiple linear stepwise regression. A validation sample (13 males, 12 females) was used to assess equation accuracy; actual tissue masses were acquired from manually segmented full body Dual-Energy X-ray Absorptiometry scans. Results: Adjusted R2 values for the prediction equations ranged from 0.326 to 0.949, where BMC equations showed the lowest explained variances overall. Mean relative errors between actual and predicted masses ranged from –2.6% to 6.1% for trunk LM and FM, respectively. All actual tissue masses except head BMC (R2 = 0.092) were significantly correlated to those predicted from the equations (R2 = 0.403 to 0.963). Conclusion: This research provides a simple and effective method for predicting head, neck, trunk, and pelvis tissue masses in older adults that can be incorporated into biomechanical models for analyzing sport and recreational activities. Future work with this population should aim to improve core segment BMC predictions and develop equations for the extremities.

Keywords


Regression Equations, Anthropometry, Core Body Segments, Wobbling Mass, Biomechanical Modeling

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References


Arthurs, K. L., & Andrews, D. M. (2009). Upper extremity soft and rigid tissue mass prediction using segment anthropometric measures and DXA. Journal of Biomechanics, 42(3), 389-394. DOI: 10.1016/j.jbiomech.2008.11.021

Baumgartner, R. N. (2000). Body composition in healthy aging. Annals of the New York Academy of Sciences, 904, 437-438. DOI: 10.1111/j.1749-6632.2000.tb06498.x

Bazrgari, B., Nussbaum, M. A., Madigan, M. L., & Shirazi-Adl, A. (2011). Soft tissue wobbling affects trunk dynamic response in sudden perturbations. Journal of Biomechanics, 44(3), 547-551. https://doi.org/10.1016/j.jbiomech.2010.09.021

Bernsten, G. K. R., Fønnebø, V., Tollan, A., Søgaard, A. J., & Magnus, J. H. (2001). Forearm bone mineral density by age in 7,620 men and women. American Journal of Epidemiology, 153(5), 465-473. https://doi.org/10.1093/aje/153.5.465

Burkhart, T. A., Arthurs, K. L., & Andrews, D. M. (2009). Manual segmentation of DXA scan images results in reliable upper and lower extremity soft and rigid tissue mass estimates. Journal of Biomechanics, 42(8), 1138-1142. https://doi.org/10.1016/j.jbiomech.2009.02.017

Clarys, J. P., Martin, A. D., & Drinkwater, D.T. (1984). Gross tissue weights in the human body by cadaver dissection. Human Biology, 56(3), 459-473. https://www.jstor.org/stable/41463592

Dempster, W. T. (1955). Space requirements of the seated operator. Ohio, IL: Wright-Patterson Air Force Base (WADC TR 55-159). https://doi.org/10.1002/ajpa.1330220412

Gallagher, D., Visser, M., Sepúlveda, D., Pierson, R. N., Harris, T., & Heymsfield, S.B. (1996). How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? American Journal of Epidemiology, 143(3), 228-239. https://doi.org/10.1093/oxfordjournals.aje.a008733

George, N. C., Kahelin, C., Burkhart, T. A., & Andrews, D. M. (2017). Reliability of head, neck and trunk anthropometric measurements used for predicting segment tissue masses in living humans. Journal of Applied Biomechanics, 33(5), 373-378. https://doi.org/10.1123/jab.2016-0122

Gruber, K., Ruder, H., Denoth, J., & Schneider, K. (1998). A comparative study of impact dynamics: wobbling mass model versus rigid body models. Journal of Biomechanics, 31(5), 439-444. https://doi.org/10.1016/S0021-9290(98)00033-5

Gyemi, D. L., Kahelin, C., George, N. C., & Andrews, D. M. (2017). Head, neck, trunk and pelvis tissue mass predictions for young adults using anthropometric measures and DXA. Journal of Applied Biomechanics, 33(5), 366-372. https://doi.org/10.1123/jab.2016-0228

Holmes, J. D., Andrews, D. M., Durkin, J. L., & Dowling, J. J. (2005). Predicting in vivo soft tissue masses of the lower extremity using segment anthropometric measures and DXA. Journal of Applied Biomechanics, 21(4), 371-382. https://doi.org/10.1123/jab.21.4.371

Jackson A. S., & Pollock, M. L. (1978). Generalized equations for predicting body density of men. British Journal of Nutrition, 40(03), 497–504. https://doi.org/10.1079/BJN19780152

Kerlinger, F. N., & Pedhazar, E. S. (1973). Multiple regression in behavioral research. New York: Holt, Reinhart, & Winston.

Pain, M. T., & Challis, J. H. (2006). The influence of soft tissue movement on ground reaction forces, joint torques and joint reaction forces in drop landings. Journal of Biomechanics, 39(1), 119-124. https://doi.org/10.1016/j.jbiomech.2004.10.036

Schmitt, S., & Günther, M. (2010). Human leg impact: energy dissipation of wobbling masses. Archives of Applied Mechanics, 81(7), 887-897. https://doi.org/10.1007/s00419-010-0458-z

Stevens, J. P. (2002). Applied Multivariate Statistics for the Social Sciences. 4th ed. Hillsdale, NJ: Lawrence Erlbaum Associates.

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. 6th ed. Boston, MA: Pearson Education.

Talmage R. V., Stinnett, S. S., Landwehr, J. T., Vincent L. M., & McCartney, W. H. (1986). Age-related loss of bone mineral density in non-athletic and athletic women. Bone and Mineral,1(2), 115-125.

Wishart, J. M., Need, A. O., Horowitz, M., & Nordin, B. E. C. (1995). Effect of age on bone density and bone turnover in men. Clinical Endocrinology, 42(2), 141-146. https://doi.org/10.1111/j.1365-2265.1995.tb01854.x




DOI: http://dx.doi.org/10.7575/aiac.ijkss.v.8n.3p.14

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