Bone health, activity and sedentariness at age 11–12 years: Cross-sectional Australian population-derived study

Osborn, William; Simm, Peter; Olds, Tim; Lycett, Kate; Mensah, Fiona; Muller, Josh; Fraysse, François; Ismail, Najmi; Vlok, Jennifer; Burgner, David; Edwards, Ben; Dwyer, Terence; Azzopardi, Peter; Ranganathan, Sarath; Wake, Melissa

doi:10.1016/j.bone.2018.04.011

Cited by 12 publications

(14 citation statements)

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“…One study showed how that pQCT could introduce systematic error when comparing cross-sectional geometry with bone histomorphometry using different parameter thresholds. For example, threshold differences have been shown to produce variations in total cross-sectional area and bone cortical area ranging between −1%–3.1% and 4.7%–6.5%, respectively 66. SSI is particularly sensitive to overestimations as it is a composite measure that includes cortical bone area 42.…”

Section: Discussionmentioning

confidence: 99%

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

et al. 2019

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ObjectivesTo describe the epidemiology and concordance of bone health in a population-based sample of Australian parent-child dyads at child age 11–12 years.DesignPopulation-based cross-sectional study (the Child Health CheckPoint) nested between waves 6 and 7 of the Longitudinal Study of Australian Children (LSAC).SettingAssessment centres in seven cities around Australia, February 2015–March 2016.Participants: of all participating CheckPoint families (n=1874), bone data were available for 1222 dyads (1271 children, 50% girls; 1250 parents, 86% mothers).Outcome measuresPeripheral quantitative CT (pQCT) of the non-dominant leg scanned at the 4% (distal) and 66% (mid-calf) tibial sites. Stratec XCT 2000 software generated estimates of bone density, geometry and polar stress-strain index.Parent-child concordance were assessed using Pearson’s correlation coefficients and multivariable linear regression models. Percentiles were determined using survey weights. Survey weights and methods accounted for LSAC’s complex sampling, stratification and clustering within postcodes.ResultsConcordances were greater for the geometric pQCT parameters (periosteal circumference 0.38, 95% CI 0.33 to 0.43; endosteal circumference 0.42, 95% CI 0.37 to 0.47; total cross-sectional area 0.37, 95% CI 0.32 to 0.42) than density (cortical density 0.25, 95% CI 0.19 to 0.30). Mother-child and father-child values were similar. Relationships attenuated only slightly on adjustment for age, sex and body mass index. Percentiles and concordance are presented for the whole sample and by sex.ConclusionsThere is strong parent-child concordance in bone geometry and, to a lesser extent, density even before the period of peak adolescent bone deposition. This geometrical concordance suggests that future intergenerational bone studies could consider using pQCT rather than the more commonly used dual X-ray absorptiometry (DXA).

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Section: Discussionmentioning

confidence: 99%

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

et al. 2019

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“…Type of sport, changes (Δ, T1-T0) in maturity offset, stature, BMI, lean mass, fat mass, vertical jump, cardiorespiratory fitness, MVPA, 25(OH)D, calcium, CTX and PINP were selected as predictors based on their relationship with bone outcomes [ 5 , 12 , 31 , 32 ]. Multiple linear regression analyses were used to examine the contribution of the change in each predictor (Δ) on the change in bone outcomes (Δ).…”

Section: Methodsmentioning

confidence: 99%

Longitudinal determinants of 12-month changes on bone health in adolescent male athletes

et al. 2018

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SummaryWe identified the determinants of 12-month changes of areal bone mineral density (aBMD), hip geometry and trabecular bone score (TBS) in adolescent male athletes. Changes in region-specific lean mass and the type of sport are the most consistent determinants in this population.PurposeThis study aims to identify the determinants of 12-month changes of areal bone mineral density (aBMD), hip geometry and trabecular bone score (TBS) in adolescent male athletes.MethodsThe sample was 104 adolescent males aged 12–14 years at baseline that were followed over 12 months: 39 swimmers, 37 footballers (or soccer players) and 28 cyclists. Dual-energy X-ray absorptiometry measured aBMD at the whole body, lumbar spine and dual hip. Hip geometry estimates at the femoral neck were measured using hip structural analysis. Lumbar spine texture was measured by TBS.ResultsMultivariate regression models significantly explained 38–60% of the variance in the aBMD changes, 36–62% in the hip geometry estimates changes and 45% in the TBS changes. Δregion-specific lean mass was the most consistent predictor of changes in aBMD outcomes (β = 0.591 to 0.696), followed by cycling participation (β = − 0.233 to − 0.262), swimming participation (β = − 0.315 to − 0.336) and ΔMVPA (β = 0.165). Cycling participation was the most consistent predictor of changes in hip geometry estimates (β = − 0.174 to − 0.268), followed by Δregion-specific lean mass (β = 0.587) and Δcardiorespiratory fitness (β = 0.253). Finally, cycling and swimming participation (β = − 0.347 to − 0.453), Δregion-specific lean mass (β = 0.848) and Δstature (β = 0.720) were predictors of change in TBS.ConclusionsChanges in region-specific lean mass and the type of sport are the most consistent determinants of 12-month changes in aBMD, hip geometry estimates and TBS in adolescent male athletes.Trial registrationISRCTN17982776

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“…(17,18) Polar SSI has been positively associated with MVPA but not sedentary time in Australian school-aged children. (12) This study aimed to use a 24-hour time-use approach to explore the associations between MVPA, LPA, sedentary time, and sleep with pQCT-derived measures of bone density, geometry, and strength among a large, population-based sample of Australian school-aged children. It aimed to describe the best day-the "Goldilocks Day"-for bone health, where the mix of these four behaviors is "just right" using novel analytical methods based on compositional data analysis.…”

Section: Introductionmentioning

confidence: 99%

“…( 17,18 ) Polar SSI has been positively associated with MVPA but not sedentary time in Australian school‐aged children. ( 12 )…”

Section: Introductionmentioning

confidence: 99%

The “Goldilocks Day” for Children's Skeletal Health: Compositional Data Analysis of 24-Hour Activity Behaviors

Dumuid

Simm

Wake

et al. 2020

Journal of Bone and Mineral Research

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Optimization of children's activity behaviors for skeletal health is a key public health priority, yet it is unknown how many hours of moderate to vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior, or sleep constitute the best daythe "Goldilocks Day"-for children's bone structure and function. To describe the best day for children's skeletal health, we used data from the cross-sectional Child Health CheckPoint. Included participants (n = 804, aged 10.7 to 12.9 years, 50% male) underwent tibial peripheral quantitative CT to assesses cross-sectional area, trabecular and cortical density, periosteal and endosteal circumference, polar moment of inertia, and polar stress-strain index. Average daily time-use composition (MVPA, LPA, sedentary time, and sleep) was assessed through 8-day, 24-hour accelerometry. Skeletal outcomes were regressed against time-use compositions expressed as isometric log-ratios (with quadratic terms where indicated), adjusted for sex, age, pubertal status, and socioeconomic position. The models were used to estimate optimal time-use compositions (associated with best 5% of each skeletal outcome), which were plotted in three-dimensional quaternary figures. The center of the overlapping area was considered the Goldilocks Day for skeletal health. Children's time-use composition was associated with all skeletal measures (all p ≤ 0.001) except cross-sectional area (p = 0.72). Days with more sleep and MVPA, less sedentary time, and moderate LPA were beneficially associated with skeletal measures, except cortical density, which was adversely associated. The Goldilocks daily time-use composition for overall skeletal health was center (range): 10.9 (10.5 to 11.5) hours sleep; 8.2 (7.8 to 8.8) hours sedentary time; 3.4 (2.8 to 4.2) hours LPA, and 1.5 (1.3 to 1.5) hours MVPA. Estimated optimal sleep duration is consistent with current international guidelines (9 to 11 hours), while estimated optimal MVPA exceeds recommendations of at least 60 min/d. This first study to describe optimal durations of daily activities for children's skeletal health provides evidence to underpin guidelines.

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Bone health, activity and sedentariness at age 11–12 years: Cross-sectional Australian population-derived study

Abstract: In early adolescence, MVPA duration showed associations with better bone health that, while modest, could be of population-level importance. MVPA fragmentation and sedentary behaviour duration and fragmentation seemed less important.

Cited by 12 publications

References 51 publications

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

Longitudinal determinants of 12-month changes on bone health in adolescent male athletes

The “Goldilocks Day” for Children's Skeletal Health: Compositional Data Analysis of 24-Hour Activity Behaviors

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Bone health, activity and sedentariness at age 11–12 years: Cross-sectional Australian population-derived study

Abstract: In early adolescence, MVPA duration showed associations with better bone health that, while modest, could be of population-level importance. MVPA fragmentation and sedentary behaviour duration and fragmentation seemed less important.

Cited by 12 publications

References 51 publications

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

pQCT bone geometry and strength: population epidemiology and concordance in Australian children aged 11–12 years and their parents

Longitudinal determinants of 12-month changes on bone health in adolescent male athletes

The “Goldilocks Day” for Children's Skeletal Health: Compositional Data Analysis of 24-Hour Activity Behaviors

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Product

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Bone health, activity and sedentariness at age 11–12 years: Cross-sectional Australian population-derived study