Improving the Identification of Bone-specific Physical Activity Using Wrist-worn Accelerometry: A Cross-sectional Study in 11-12-year-old Australian Children

Overview

Journal Eur J Sport Sci

Specialties Orthopedics
Physiology

Date 2024 Jul 3

PMID 38956788

Authors

Gemma Brailey

Brad Metcalf

Lisa Price

Sean Cumming

Alex Rowlands

Timothy Olds

Peter Simm

Melissa Wake

Victoria Stiles

Affiliations

Soon will be listed here.

Abstract

Physical activity (PA) during childhood and adolescence is important for the accrual of maximal peak bone mass. The precise dose that benefits bone remains unclear as methods commonly used to analyze PA data are unsuitable for measuring bone-relevant PA. Using improved accelerometry methods, this study identified the amount and intensity of PA most strongly associated with bone outcomes in 11-12-year-olds. Participants (n = 770; 382 boys) underwent tibial peripheral quantitative computed tomography to assess trabecular and cortical density, endosteal and periosteal circumference and polar stress-strain index. Seven-day wrist-worn raw acceleration data averaged over 1-s epochs was used to estimate time accumulated above incremental PA intensities (50 milli-gravitational unit (mg) increments from 200 to 3000 mg). Associations between time spent above each 50 mg increment and bone outcomes were assessed using multiple linear regression, adjusted for age, sex, height, weight, maturity, socioeconomic position, muscle cross-sectional area and PA below the intensity of interest. There was a gradual increase in mean R change across all bone-related outcomes as the intensity increased in 50 mg increments from >200 to >700 mg. All outcomes became significant at >700 mg (R change = 0.6%-1.3% and p = 0.001-0.02). Any further increases in intensity led to a reduction in mean R change and associations became non-significant for all outcomes >1500 mg. Using more appropriate accelerometry methods (1-s epochs; no a priori application of traditional cut-points) enabled us to identify that ∼10 min/day of PA >700 mg (equivalent to running ∼10 km/h) was positively associated with pQCT-derived measures of bone density, geometry and strength in 11-12-year-olds.

References

Stiles V, Pearce M, Moore I, Langford J, Rowlands A . Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load. Med Sci Sports Exerc. 2018; 50(11):2277-2284. PMC: 6195805. DOI: 10.1249/MSS.0000000000001704. View

Fraysse F, Grobler A, Muller J, Wake M, Olds T . Physical activity and sedentary activity: population epidemiology and concordance in Australian children aged 11-12 years and their parents. BMJ Open. 2019; 9(Suppl 3):136-146. PMC: 6624037. DOI: 10.1136/bmjopen-2018-023194. View

van Hees V, Gorzelniak L, Dean Leon E, Eder M, Pias M, Taherian S . Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PLoS One. 2013; 8(4):e61691. PMC: 3634007. DOI: 10.1371/journal.pone.0061691. View

Rowlands A, Yates T, Davies M, Khunti K, Edwardson C . Raw Accelerometer Data Analysis with GGIR R-package: Does Accelerometer Brand Matter?. Med Sci Sports Exerc. 2016; 48(10):1935-41. DOI: 10.1249/MSS.0000000000000978. View

Moyer-Mileur L, Quick J, Murray M . Peripheral quantitative computed tomography of the tibia: pediatric reference values. J Clin Densitom. 2008; 11(2):283-94. DOI: 10.1016/j.jocd.2007.11.002. View

Farr J, Funk J, Chen Z, Lisse J, Blew R, Lee V . Skeletal muscle fat content is inversely associated with bone strength in young girls. J Bone Miner Res. 2011; 26(9):2217-25. PMC: 4414314. DOI: 10.1002/jbmr.414. View

da Silva I, van Hees V, Ramires V, Knuth A, Bielemann R, Ekelund U . Physical activity levels in three Brazilian birth cohorts as assessed with raw triaxial wrist accelerometry. Int J Epidemiol. 2014; 43(6):1959-68. PMC: 4276065. DOI: 10.1093/ije/dyu203. View

Bornstein D, Beets M, Byun W, Welk G, Bottai M, Dowda M . Equating accelerometer estimates of moderate-to-vigorous physical activity: in search of the Rosetta Stone. J Sci Med Sport. 2011; 14(5):404-10. PMC: 3158964. DOI: 10.1016/j.jsams.2011.03.013. View

Baxter-Jones A, Faulkner R, Forwood M, Mirwald R, Bailey D . Bone mineral accrual from 8 to 30 years of age: an estimation of peak bone mass. J Bone Miner Res. 2011; 26(8):1729-39. DOI: 10.1002/jbmr.412. View

10.

Sherk V, Bemben D, Bemben M, Anderson M . Age and sex differences in tibia morphology in healthy adult Caucasians. Bone. 2012; 50(6):1324-31. PMC: 4082662. DOI: 10.1016/j.bone.2012.03.005. View

11.

Bailey R, Olson J, Pepper S, Porszasz J, Barstow T, Cooper D . The level and tempo of children's physical activities: an observational study. Med Sci Sports Exerc. 1995; 27(7):1033-41. DOI: 10.1249/00005768-199507000-00012. View

12.

Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

13.

Rowlands A, Mirkes E, Yates T, Clemes S, Davies M, Khunti K . Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent?. Med Sci Sports Exerc. 2017; 50(2):257-265. DOI: 10.1249/MSS.0000000000001435. View

14.

Johnell O, Kanis J . An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int. 2006; 17(12):1726-33. DOI: 10.1007/s00198-006-0172-4. View

15.

Stiles V, Metcalf B, Knapp K, Rowlands A . A small amount of precisely measured high-intensity habitual physical activity predicts bone health in pre- and post-menopausal women in UK Biobank. Int J Epidemiol. 2017; 46(6):1847-1856. PMC: 5837700. DOI: 10.1093/ije/dyx080. View

16.

Osborn W, Simm P, Olds T, Lycett K, Mensah F, Muller J . Bone health, activity and sedentariness at age 11-12 years: Cross-sectional Australian population-derived study. Bone. 2018; 112:153-160. DOI: 10.1016/j.bone.2018.04.011. View

17.

Baquet G, Stratton G, Van Praagh E, Berthoin S . Improving physical activity assessment in prepubertal children with high-frequency accelerometry monitoring: a methodological issue. Prev Med. 2006; 44(2):143-7. DOI: 10.1016/j.ypmed.2006.10.004. View

18.

Rowlands A, Fairclough S, Yates T, Edwardson C, Davies M, Munir F . Activity Intensity, Volume, and Norms: Utility and Interpretation of Accelerometer Metrics. Med Sci Sports Exerc. 2019; 51(11):2410-2422. DOI: 10.1249/MSS.0000000000002047. View

19.

Bonjour J, Chevalley T, Ferrari S, Rizzoli R . The importance and relevance of peak bone mass in the prevalence of osteoporosis. Salud Publica Mex. 2009; 51 Suppl 1:S5-17. DOI: 10.1590/s0036-36342009000700004. View

20.

Bailey D, McKay H, Mirwald R, Crocker P, Faulkner R . A six-year longitudinal study of the relationship of physical activity to bone mineral accrual in growing children: the university of Saskatchewan bone mineral accrual study. J Bone Miner Res. 1999; 14(10):1672-9. DOI: 10.1359/jbmr.1999.14.10.1672. View