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

Effect of a physical activity intervention on lower body bone health in childhood cancer survivors: A randomized controlled trial (SURfit)

It remains controversial whether physical activity promotes bone health in childhood cancer survivors (CCS). We aimed to assess the effect of a one-year general exercise intervention on lower body bone parameters of CCS. CCS ≥16 years at enrollment, <16 years at diagnosis and ≥5 years in remission were identified from the national Childhood Cancer Registry. Participants randomized to the intervention group were asked to perform an additional ≥2.5 hours of intense physical activity/week, controls continued exercise as usual. Bone health was assessed as a secondary trial endpoint at baseline and after 12-months. We measured tibia bone mineral density (BMD) and morphology by peripheral quantitative computed tomography and lumbar spine, hip and femoral neck BMD by dual-energy x-ray absorptiometry. We performed intention-to-treat, per protocol, and an explorative subgroup analyses looking at low BMD using multiple linear regressions. One hundred fifty-one survivors (44% females, 7.5 ± 4.9 years at diagnosis, 30.4 ± 8.6 years at baseline) were included. Intention-to-treat analysis revealed no differences in changes between the intervention and control group. Per protocol analyses showed evidence for an improvement in femoral neck and trabecular BMD between 1.5% and 1.8% more in participants being compliant with the exercise program. Trabecular BMD increased 2.8% more in survivors of the intervention group with BMD z-score ≤-1 compared to those starting at z-score >-1. A nonstandardized personalized exercise programs might not be specific enough to promote bone health in CCS, although those compliant and those most in need may benefit. Future trials should include bone stimulating exercise programs targeting risk groups with reduced bone health and motivational features to maximize compliance.

Goldilocks Days: optimising children's time use for health and well-being

BACKGROUND

One size rarely fits all in population health. Differing outcomes may compete for best allocations of time. Among children aged 11-12 years, we aimed to (1) describe optimal 24-hour time use for diverse physical, cognitive/academic and well-being outcomes, (2) pinpoint the 'Goldilocks Day' that optimises all outcomes and (3) develop a tool to customise time-use recommendations.

METHODS

In 2004, the Longitudinal Study of Australian Children recruited a nationally-representative cohort of 5107 infants with biennial follow-up waves. We used data from the cross-sectional Child Health CheckPoint module (2015-2016, n=1874, 11-12 years, 51% males). Time use was from 7-day 24-hour accelerometry. Outcomes included life satisfaction, psychosocial health, depressive symptoms, emotional problems, non-verbal IQ; vocabulary, academic performance, adiposity, fitness, blood pressure, inflammatory biomarkers, bone strength. Relationships between time use and outcomes were modelled using compositional regression.

RESULTS

Optimal daily durations varied widely for different health outcomes (sleep: 8.3-11.4 hours; sedentary: 7.3-12.2 hours; light physical activity: 1.7-5.1 hours; moderate-to-vigorous physical activity (MVPA): 0.3-2.7 hours, all models p≤0.04). In general, days with highest physical activity (predominantly MVPA) and low sedentary time were optimal for physical health, while days with highest sleep and lowest sedentary time were optimal for mental health. Days with highest sedentary time and lowest physical activity were optimal for cognitive health. The overall Goldilocks Day had 10 hours 21 min sleep, 9 hours 44 min sedentary time, 2 hours 26 min light physical activity and 1 hour 29 min MVPA. Our interactive interface allows personalisation of Goldilocks Days to an individual's outcome priorities.

CONCLUSION

'Goldilocks Days' necessitate compromises based on hierarchies of priorities for health, social and economic outcomes.

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

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 day-the "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. © 2020 American Society for Bone and Mineral Research (ASBMR).

Analysing body composition as compositional data: An exploration of the relationship between body composition, body mass and bone strength

Human body composition is made up of mutually exclusive and exhaustive parts (e.g. %truncal fat, %non-truncal fat and %fat-free mass) which are constrained to sum to the same total (100%). In statistical analyses, individual parts of body composition (e.g. %truncal fat or %fat-free mass) have traditionally been used as proxies for body composition, and have been linked with a range of health outcomes. But analysis of individual parts omits information about the other parts, which are intrinsically co-dependent because of the constant sum constraint of 100%. Further, body mass may be associated with health outcomes. We describe a statistical approach for body composition based on compositional data analysis. The body composition data are expressed as logratios to allow relative information about all the compositional parts to be explored simultaneously in relation to health outcomes. We describe a recent extension to the logratio approach to compositional data analysis which allows absolute information about the total of the compositional parts (body mass) to be considered alongside relative information about body composition. The statistical approach is illustrated by an example that explores the relationships between adults' body composition, body mass and bone strength.

Population health bio-phenotypes in 11-12 year old children and their midlife parents: Growing Up in Australia's Child Health CheckPoint

In an ambitious undertaking, Growing Up in Australia's Child Health CheckPoint streamlined and implemented wide-ranging population phenotypes and biosamples relevant to non-communicable diseases in nearly 1900 parent-child dyads throughout Australia at child aged 11-12 years. This BMJ Open Special Issue describes the methodology, epidemiology and parent-child concordance of 14 of these phenotypes, spanning cardiovascular, respiratory, bone, kidney, hearing and language, body composition, metabolic profiles, telomere length, sleep, physical activity, snack choice and health-related quality of life. The Special Issue also includes a cohort summary and study methodology paper.

Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children

OBJECTIVES

'Growing Up in Australia: The Longitudinal Study of Australian Children' (LSAC) is Australia's only nationally representative children's longitudinal study, focusing on social, economic, physical and cultural impacts on health, learning, social and cognitive development. LSAC's first decade collected wide-ranging repeated psychosocial and administrative data; here, we describe the Child Health CheckPoint, LSAC's dedicated biophysical module.

DESIGN, SETTING AND PARTICIPANTS

LSAC recruited a cross-sequential sample of 5107 infants aged 0-1 year and a sample of 4983 children aged 4-5 years in 2004, since completing seven biennial visits. CheckPoint was a cross-sectional wave that travelled Australia in 2015-2016 to reach LSAC's younger cohort at ages 11-12 years between LSAC waves 6 and 7. Parent-child pairs participated in comprehensive assessments at 15 Assessment Centres nationwide or, if unable to attend, a shorter home visit.

MEASURES

CheckPoint's intergenerational, multidimensional measures were prioritised to show meaningful variation within normal ranges and capture non-communicable disease (NCD) phenotype precursors. These included anthropometry, physical activity, fitness, time use, vision, hearing, and cardiovascular, respiratory and bone health. Biospecimens included blood, saliva, buccal swabs (also from second parent), urine, hair and toenails. The epidemiology and parent-child concordance of many measures are described in separate papers.

RESULTS

1874 (54% of eligible) parent-child pairs and 1051 second parents participated. Participants' geographical distribution mirrored the broader Australian population; however, mean socioeconomic position and parental education were higher and fewer reported non-English-speaking or Indigenous backgrounds. Application of survey weights partially mitigates that the achieved sample is less population representative than previous waves of LSAC due to non-random attrition. Completeness was uniformly high for phenotypic data (>92% of eligible), biospecimens (74%-97%) and consent (genetic analyses 98%, accessing neonatal blood spots 97%, sharing 96%).

CONCLUSIONS

CheckPoint enriches LSAC to study how NCDs develop at the molecular and phenotypic levels before overt disease emerges, and clarify the underlying dimensionality of health in childhood and mid-adulthood.