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Prediction of bone health by means of regression equations in children and adolescents living at moderate altitud

Authors

  • Jose Sulla-Torres Universidad Católica Santa Maria de Arequipa
  • Camilo Urra-Albornoz Escuela de Kinesiolología, Facultad de Salud, Universidad Santo Tomás
  • Fernando Alvear-Vvasquez Universidad Católica del Maule
  • Marco Cossio Bolaños
  • Rossana Gomez-Campos Universidad Católica del Maule

DOI:

https://doi.org/10.12873/404sulla

Keywords:

Bone health, regrerssion equation, children, adolescent, Perú

Abstract

Introduction: During childhood and adolescence, the accumulation of bone mass is generated, which is decisive for bone health in adulthood.
Objective: To predict bone health to compare with other geographical regions of the world and to verify the differences in bone density and mineral content of schoolchildren classified with and without risk of bone fragility.
Methods: A descriptive cross-sectional study was carried out in 1224 schoolchildren (573 boys and 651 girls) from the city of Arequipa (Peru). The age range ranges from 6 to 16.9 years. Weight, standing height, sitting height, diameter of the femur, length of the right forearm were evaluated. The weight index (PI), the state of maturity through the growth rate peak (APVC), bone mineral density (BMD) and bone mineral content (CMO) were calculated by regression equations. The sample was classified into a group with risk and without risk of bone fragility.
Results: BMD and CMO were compared with studies from the Netherlands, Chile, and China. Children from the Netherlands presented mean values ​​higher than Peruvian children from ~ 0.10 to 0.90 (g / cm2) in BMD and from ~ 0.28 to 0.94 (g / cm2) in CMO in both sexes. It was observed 9% (n = 52) in men and 12% (n = 78) in women with risk of suffering osteoporosis and 91% (n = 521) of men and 88% (n = 573) of women without risk of osteoporosis . There were differences in the diameter of the femur, length of the forearm, BMD and CMO between both categorized groups (with and without risk) and in both sexes (p <0.05).
Conclusions: There were discrepancies in BMD and CMO with other geographic regions, in addition, schoolchildren classified as risk of bone fragility had decreased bone size and poor bone health compared to their counterparts without risk.

References

Baxter-Jones AD, Faulkner RA, Forwood MR, Mirwald RL, Bailey DA. Bone mineral accrual from 8 to 30 years of age: an estimation of peak bone mass. J Bone Miner Res. 2011; 26(8):1729-1739.

Cooper C, Westlake S, Harvey N, Javaid K, Dennison E, et al. Review: developmental origins of osteoporotic fractures. Osteoporos Int. 2006;17: 337–347.

van der Sluis IM, de Ridder MA, Boot AM, Krenning EP, de Muinck Keizer-Schrama SM. Reference data for bone density and body composition measured with dual energy x ray absorptiometry in white children and young adults. Archives of disease in childhood. 2002; 87(4):341–347.

Kalkwarf HJ, Laor T, Bean JA. Fracture risk in children with a forearm injury is associated with volumetric bone density and cortical area (by peripheral QCT) and areal bone density (by DXA). Osteoporos Int. 2011; 22:607–616

Yi KH, Hwang JS, Kim EY, Lee JA, Kim DH, Lim JS. Reference values for bone mineral density according to age with body size adjustment in Korean children and adolescents. J Bone Miner Metab. 2014;32(3):281-289.

Gómez-Campos R, Sulla-Torres J, Andruske CL, Campos LFCC, Luarte-Rocha C, Cossio-Bolaños W, Cossio-Bolaños M. Ultrasound reference values for the calcaneus of children and adolescents at moderate altitudes in Peru J Pediatr (Rio J). 2020;S0021-7557(19)30577-7.

Miranda V, Muñoz CH, Paolinelli GP, Astudillo AC. Densitometría ósea. Revista Médica Clínica Las Condes.2013; 24 (1):169-173.

Kok-Yong Ch, Ima-Nirwana S. Calcaneal quantitative ultrasound as a determinant of bone health status: what properties of bone does it reflect?. Int J Med Sci. 2013;10:1778-1783

Binkovitz LA, Henwood MJ. Pediatric DXA: technique and interpretation. Pediatric radiology. 2007;37(1): 21–31.

Gómez-Campos R, Andruske CL, Arruda M, Urra Albornoz C, Cossio-Bolaños M. Proposed equations and reference values for calculating bone health in children and adolescent based on age and sex. PloS one. 2017;12(7): e0181918.

Ross WD, Marfell-Jones MJ. Kinanthropometry. In: MacDougall JD, Wenger HA, Geeny HJ. (Eds.), Physiological testing of eliteathlete. London: Human Kinetics. 1991;223:308–314.

Mirwald RL, Baxter-Jones ADG, Bailey DA, Beunen GP. An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc. 2002;34:689–94.

Hao X, Jia-Xuan C, Jian G, Tian-Min Z, Qiu-Lian W, Zhong-Man Y, Jin-Ping W. Normal Reference for Bone Density in Healthy Chinese Children, Journal of Clinical Densitometry. 2007;10, (3): 266-275.

Langsetmo L, Hanley DA, Kreiger N, et al. Geographic variation of bone mineral density and selected risk factors for prediction of incident fracture among Canadians 50 and older. Bone. 2008;43: 672–678.

Rauch F, Bailey DA, Baxter-Jones ADG, Mirwald R, Faulkner RA. The ‘muscle-bone unit’ during the pubertal growth spurt. Bone. 2004;34:771–775.

Bailey DA, Martin AD, McKay HA, Whiting S, Mirwald R. Calcium accretion in girls and boys during puberty: A longitudinal analysis. J Bone Miner Res. 2000;15:2245–2250.

Mikuls TR, Saag KG, Curtis J, Bridges SL Jr, Alarcon GS, Westfall AO, Lim SS, Smith EA, Jonas BL, Moreland LW: Prevalence of osteoporosis and osteopenia among African Americans with early rheumatoid arthritis: the impact of ethnic-specific normative data. J Natl Med Assoc. 2005, 97(8):1155-1160.

Kralick AE, Zemel BS. Evolutionary Perspectives on the Developing Skeleton and Implications for Lifelong Health. Frontiers in endocrinology. 2020;11:99.

Novotny SA, Warren GL, Hamrick MW. Aging and the muscle-bone relationship. Physiology. 2015; 30:8–16.

Osterhoff G, Morgan EF, Shefelbine SJ, Karim L, McNamara LM, Augat P. Bone mechanical properties and changes with osteoporosis. Injury. 2016; 47(Suppl. 2):S11–20.

Krall EA, Dawson-Hughes B. Heritable and life-style determinants of bone mineral density. J Bone Miner Res. 1993;8:1e9.

Abrahamsen B, Brask-Lindemann D, Rubin KH, Schwarz P. Una revisión del estilo de vida, el tabaquismo y otros factores de riesgo modificables para las fracturas osteoporóticas. Informes de BoneKEy Reports. 2014; 3:574.

Weaver CM, Gordon CM, Janz KF, Kalkwarf HJ, Lappe JM, Lewis R, et al. The national osteoporosis foundation's position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations. Osteopor Int. 2016; 27:1281–386.

Gunter KB, Almstedt HC, Janz KF. Physical activity in childhood may be the key to optimizing lifespan skeletal health. Exerc Sport Sci Rev. 2012;40:13–21

Duncan CS, Blimkie CJ, Cowell CT, et al. Bone mineral density in adolescent female athletes: relationship to exercise type and muscle strength. Med Sci Sports Exerc. 2002;34:286–294.

Published

2020-12-15

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How to Cite

Sulla-Torres, J., Urra-Albornoz, C., Alvear-Vvasquez, F., Cossio Bolaños, M., & Gomez-Campos, R. (2020). Prediction of bone health by means of regression equations in children and adolescents living at moderate altitud. Nutrición Clínica Y Dietética Hospitalaria, 40(4). https://doi.org/10.12873/404sulla

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