Physical activity and inactivity trajectories associated with body composition in pre-schoolers

Meredith-Jones, Kim; Haszard, Jillian J.; Moir, Chris; Heath, Anne‐Louise M; Lawrence, Julie; Galland, Barbara; Taylor, Barry; Gray, Andrew; Sayers, Rachel; Taylor, Rachael W.

doi:10.1038/s41366-018-0058-5

Cited by 20 publications

(21 citation statements)

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“…Non-wear time was defined as at least 20 min of consecutive zeros during awake time data only [ 28 ], which provides acceptable estimates of physical activity ( r = 0.70–0.90) in young children [ 29 , 30 ]. As Actical cutoffs for physical activity intensity categories do not exist that span this full age range (1–5 years), we defined sedentary time as 0–25 counts (per 15 s), light physical activity (LPA) as 26–697 counts, and moderate-to-vigorous physical activity (MVPA) as ≥698 counts [ 31 ], based on validation work in toddlers and preschoolers [ 32 – 34 ]. Data from our group shows that Actical accelerometers worn around the waist provide a valid measure of sleep duration in young children when compared against polysomnography (Meredith-Jones, unpublished).…”

Section: Methodsmentioning

confidence: 99%

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health

Taylor

Haszard

Meredith-Jones

et al. 2018

Int J Behav Nutr Phys Act

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BackgroundNew physical activity guidelines for children address all movement behaviors across the 24-h day (physical activity, sedentary behavior, sleep), but how each component relates to body composition when adjusted for the compositional nature of 24-h data is uncertain.AimsTo i) describe 24-h movement behaviors from 1 to 5 years of age, ii) determine cross-sectional relationships with body mass index (BMI) z-score, iii) determine whether movement behaviors from 1 to 5 years of age predict body composition and bone health at 5 years.Methods24-h accelerometry data were collected in 380 children over 5–7 days at 1, 2, 3.5 and 5 years of age to determine the proportion of the day spent: sedentary (including wake after sleep onset), in light (LPA) and moderate-to-vigorous physical activity (MVPA), and asleep (including naps). BMI was determined at each age and a dual-energy x-ray absorptiometry (DXA) scan measured fat mass, bone mineral content (BMC) and bone mineral density (BMD) at 5 years of age. 24-h movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes back-transformed.ResultsAt age 1, children spent 49.6% of the 24-h day asleep, 38.2% sedentary, 12.1% in LPA, and 0.1% in MVPA, with corresponding figures of 44.4, 33.8, 19.8 and 1.9% at 5 years of age. Compositional time use was only related significantly to BMI z-score at 3.5 years in cross-sectional analyses. A 10% increase in mean sleep time (65 min) was associated with a lower BMI z-score (estimated difference, − 0.25; 95% CI, − 0.42 to − 0.08), whereas greater time spent sedentary (10%, 47 min) or in LPA (10%, 29 min) were associated with higher BMI z-scores (0.12 and 0.08 respectively, both p < 0.05). Compositional time use from 1 to 3.5 years was not related to future BMI z-score or percent fat. Although MVPA at 2 and 3.5 years was consistently associated with higher BMD and BMC at 5 years, actual differences were small.ConclusionsConsiderable changes in compositional time use occur from 1 to 5 years of age, but there is little association with adiposity. Although early MVPA predicted better bone health, the differences observed had little clinical relevance.Trial registrationClinicalTrials.gov number NCT00892983.Electronic supplementary materialThe online version of this article (10.1186/s12966-018-0753-6) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health

Taylor

Haszard

Meredith-Jones

et al. 2018

Int J Behav Nutr Phys Act

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“…To date, this body of research [12–14] includes largely studies examining physical-activity trajectories [10–14], with a smaller pool of studies also considering TV-viewing [10] and sedentary-behavior [11] trajectories. For example, a study of 438 children aged 0–5 years in New Zealand identified four prevailing physical-activity trajectories (constantly low, increasing, decreasing and constantly high) and a similar set of trajectories for sedentary behaviors [11]. These trajectories were significantly associated with subsequent adiposity: children who maintained high levels of physical activity since birth had less fat mass by age 5 than children who experienced declining or stable physical-activity levels [11].…”

Section: Introductionmentioning

confidence: 99%

Joint physical-activity/screen-time trajectories during early childhood: socio-demographic predictors and consequences on health-related quality-of-life and socio-emotional outcomes

Pozo-Cruz

Perales

Parker

et al. 2019

Int J Behav Nutr Phys Act

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Background Understanding the early roots of physical activity and sedentary behaviors is critical to developing intervention programs that promote healthy lifestyle habits in infants and children. There is, however, no evidence on how these behaviors cluster and develop together during early childhood. The aim of this study was to identify single and joint longitudinal trajectories in physical activity and screen time amongst children aged 0 to 9 years, their social-demographic predictors and their prospective health-related quality-of-life and socio-emotional outcomes. Methods Three waves of data from The Longitudinal Study of Australian Children , a national study tracking two cohorts every 2 years (B-cohort, 0–5 years, n = 4,164; K-cohort, 4–9 years, n = 3,974) were analysed. Growth mixture modelling was applied to longitudinal time-use diary data to identify joint trajectories in children’s physical activity and screen time over Waves 1–3. Key socio-demographic variables measured at Wave 1 were used to predict membership in different trajectories . The prospective consequences (at Wave 3) of time-use trajectories on health-related quality-of-life and socio-emotional outcomes were assessed. Results Three physical-activity/screen-time trajectories were identified for both cohorts: Cluster-A—children who maintained low levels of physical activity and screen time ( ∽50% of the sample), Cluster-B—children who progressively increased physical activity and maintained low screen-time levels ( ∽25% ), and Cluster-C—children who maintained low physical-activity levels and increased screen time ( ∽25% ). Children in Cluster-B experienced the best health-related quality-of-life and socio-emotional outcomes, while those in Cluster-C experienced the worst. Children who were female, Indigenous, from non-English-speaking backgrounds, not living with two biological parents, in more affluent households and neighbourhoods, without siblings and with parents with poor mental health were at greater risk of falling into Cluster-A or Cluster-C. Conclusion Our findings identified which children are most at-risk of falling into time-use trajectories that lead to poor health-related quality-of-life and socio-emotional outcomes later in life, increasing our ability to monitor, detect and prevent these suboptimal behaviours prior to their onset. Electronic supplementary material The online version of this article (10.1186/s12966-019-0816-3) contains supplementary material, which is available to authorized users.

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“…Children who are inactive at age 5 years tend to remain inactive throughout childhood and adolescence [3]. Recent longitudinal studies have reported that PA behavior tracks at a moderate level from age 1 to 3 years [4], or age 1 to 5 years [5]. Collectively, these findings suggest that PA behaviors could be established at a very young age and sustained over time.…”

Section: Introductionmentioning

confidence: 99%

Daily Physical Activity Among Toddlers: Hip and Wrist Accelerometer Assessments

Kwon

Honegger

Mason

2019

IJERPH

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Physical activity (PA) habits seem to track over time from as young as early childhood. For children under age 3 years, wearable sensor-measured PA levels have begun to be investigated. The aims of this study were to evaluate the feasibility of using hip- vs. wrist-worn accelerometers, and to report accelerometer-derived PA metrics among toddlers. A convenience sample of 22 toddlers aged 13 to 35 months and their mothers were recruited for this study. ActiGraph wGT3X-BT accelerometers were attached to wrist bands and waist belts. The mothers were asked to affix a wrist band and a waist belt to their participating children during waking hours for four days. They also completed an acceptability survey. Of the 22 toddlers, 19 (86%) had ≥ 3 valid days of hip data, while only 14 (64%) did so for wrist data (p = 0.16). In terms of acceptability, 18 mothers (82%) responded that the 4-day hip wear was easy, while only 13 (59%) responded that the 4-day wrist wear was easy (p = 0.19). Daily light-intensity PA (LPA) was on average 161 min, and daily moderate- and vigorous-intensity PA (MVPA) was on average 47 min, as determined using published hip accelerometer cut-points. There were no significant differences in LPA or MVPA by age or by sex. In conclusion, this study suggests that hip placement of an ActiGraph accelerometer is more feasible than wrist placement among toddlers.

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Physical activity and inactivity trajectories associated with body composition in pre-schoolers

Abstract: Physical activity and sedentary behaviour tracking is broadly similar from infancy to early childhood. Children with consistently higher levels of physical activity have reduced body fat at 5 years of age, although differences are relatively small.

Cited by 20 publications

References 45 publications

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health

24-h movement behaviors from infancy to preschool: cross-sectional and longitudinal relationships with body composition and bone health

Joint physical-activity/screen-time trajectories during early childhood: socio-demographic predictors and consequences on health-related quality-of-life and socio-emotional outcomes

Daily Physical Activity Among Toddlers: Hip and Wrist Accelerometer Assessments

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