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  • Author: Kylie D. Hesketh x
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Katherine L. Downing, Trina Hinkley and Kylie D. Hesketh

Background:

There is little current understanding of the influences on sedentary behavior and screen time in preschool children. This study investigated socioeconomic position (SEP) and parental rules as potential correlates of preschool children’s sedentary behavior and screen time.

Methods:

Data from the Healthy Active Preschool Years (HAPPY) Study were used. Participating parents reported their child’s usual weekly screen time and their rules to regulate their child’s screen time. Children wore accelerometers for 8 days to objectively measure sedentary time.

Results:

Children whose parents limited television viewing spent significantly less time in that behavior and in total screen time; however, overall sedentary behavior was unaffected. An association between parents limiting computer/electronic game use and time spent on the computer was found for girls only. SEP was inversely associated with girls’, but not boys’, total screen time and television viewing.

Conclusions:

As parental rules were generally associated with lower levels of screen time, intervention strategies could potentially encourage parents to set limits on, and switch off, screen devices. Intervention strategies should target preschool children across all SEP areas, as there was no difference by SEP in overall sedentary behavior or screen time for boys.

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Gavin Abbott, Jill Hnatiuk, Anna Timperio, Jo Salmon, Keren Best and Kylie D. Hesketh

Background:

Parental modeling has been shown to be important for school-aged children’s physical activity (PA) and television (TV) viewing, yet little is known about its impact for younger children. This study examined cross-sectional and 3-year longitudinal associations between PA and TV viewing behaviors of parents and their preschool children.

Methods:

In 2008–2009 (T1), parents in the Healthy Active Preschool and Primary Years (HAPPY) cohort study (n = 450) in Melbourne, Australia, self-reported their weekly PA and TV viewing and proxy-reported their partner’s PA and TV viewing and their 3- to 5-year-old preschool child’s TV viewing. Children’s PA was assessed via accelerometers. Repeat data collection occurred in 2011–2012 (T2).

Results:

Mothers’ and fathers’ PAs were associated with PA among preschool girls at T1, but not boys. Parents’ TV viewing times were significant correlates of girls’ and boys’ TV viewing at T1. Longitudinally, mothers’ PA at baseline predicted boys’ PA at T2, whereas sex-specific associations were found for TV viewing, with mothers’ and fathers’ TV viewing at T1 associated with girls’ and boys’ TV viewing respectively at T2.

Conclusions:

The PA and TV viewing of both parents are significantly associated with these behaviors in preschool children. The influence of the sex-matched parent appears to be important longitudinally for children’s TV viewing.

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Rachel A. Jones, Annaleise Riethmuller, Kylie Hesketh, Jillian Trezise, Marijka Batterham and Anthony D. Okely

The aim of this study was to assess the feasibility, acceptability and potential efficacy of a physical activity program for preschool children. A 20-week, 2-arm parallel cluster randomized controlled pilot trial was conducted. The intervention comprised structured activities for children and professional development for staff. The control group participated in usual care activities, which included designated inside and outside playtime. Primary outcomes were movement skill development and objectively measured physical activity. At follow-up, compared with children in the control group, children in the intervention group showed greater improvements in movement skill proficiency, with this improvement statically significant for overall movement skill development (adjust diff. = 2.08, 95% CI 0.76, 3.40; Cohen’s d = 0.47) and significantly greater increases in objectively measured physical activity (counts per minute) during the preschool day (adjust diff. = 110.5, 95% CI 33.6, 187.3; Cohen’s d = 0.46). This study demonstrates that a physical activity program implemented by staff within a preschool setting is feasible, acceptable and potentially efficacious.

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Katherine L. Downing, Jo Salmon, Anna Timperio, Trina Hinkley, Dylan P. Cliff, Anthony D. Okely and Kylie D. Hesketh

Background: Although there is increasing evidence regarding children’s screen time, little is known about children’s sitting. This study aimed to determine the correlates of screen time and sitting in 6- to 8-year-old children. Methods: In 2011–2012, parents in the Healthy Active Preschool and Primary Years (HAPPY) study (n = 498) reported their child’s week/weekend day recreational screen time and potential correlates. ActivPALs measured children’s nonschool sitting. In model 1, linear regression analyses were performed, stratified by sex and week/weekend day and controlling for age, clustered recruitment, and activPAL wear time (for sitting analyses). Correlates significantly associated with screen time or sitting (P < .05) were included in model 2. Results: Children (age 7.6 y) spent 99.6 and 119.3 minutes per day on week and weekend days engaging in screen time and sat for 119.3 and 374.6 minutes per day on week and weekend days, respectively. There were no common correlates for the 2 behaviors. Correlates largely differed by sex and week/weekend day. Modifiable correlates of screen time included television in the child’s bedroom and parental logistic support for, encouragement of, and coparticipation in screen time. Modifiable correlates of sitting included encouragement of and coparticipation in physical activity and provision of toys/equipment for physical activity. Conclusions: Interventions may benefit from including a range of strategies to ensure that all identified correlates are targeted.

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Katrina M. Moss, Annette J. Dobson, Kimberley L. Edwards, Kylie D. Hesketh, Yung-Ting Chang and Gita D. Mishra

Background: Play equipment at home could be targeted in interventions to increase children’s physical activity (PA), but evidence is mixed, potentially because current methods do not reflect children’s lived experience. This study investigated associations between combinations of equipment and PA. Methods: Data were from the Mothers and their Children’s Health study and the Australian Longitudinal Study on Women’s Health. Mothers (n = 2409) indicated the types of fixed active (eg, trampolines), portable active (eg, bicycles), and electronic (eg, computers) equipment at home, and the number of days children (n = 4092, aged 5–12 y, 51% boys) met PA guidelines. Latent class analysis was used to identify combinations of equipment, and linear regressions were used to investigate associations with PA. Results: Compared with children with high active (fixed and portable) and medium electronic equipment, children with portable active and medium (B = −0.53; 95% confidence interval, −0.72 to −0.34) or high (B = −0.58; 95% confidence interval, −0.83 to −0.33) electronic equipment met the guidelines on fewer days. Children with similar active equipment (but more electronic equipment) met the PA guidelines on fewer days (mean difference = −0.51, SE = 0.14, P = .002). Conclusion: Having the right combination of play equipment at home may be important for children’s PA.

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Stephen Hunter, Andrei Rosu, Kylie D. Hesketh, Ryan E. Rhodes, Christina M. Rinaldi, Wendy Rodgers, John C. Spence and Valerie Carson

Purpose: Examine objectively measured environmental correlates of physical activity and sedentary behavior in toddlers (12–35 mo). Methods: Participants were recruited at immunization appointments in Edmonton, Canada. Physical activity and sedentary time were objectively measured via accelerometers (n = 149). The parents reported screen time and demographic characteristics via a questionnaire (n = 249). Postal codes were used to link neighborhood data via geographic information systems. Neighborhood data included 4 environmental domains: functional (ie, walkability), safety (ie, crime), esthetic (ie, tree density), and destination (ie, cul-de-sac density, wooded area percentage, green space percentage, recreation density, park density). Weather data (temperature and precipitation) were obtained via historical weather records. Multilevel multiple linear regression models were used to account for clustering of participants within neighborhoods and adjustment of demographic variables. Results: Each additional 10°C of mean temperature was significantly associated with 5.74 (95% confidence interval, 0.96–10.50) minutes per day of higher light-intensity physical activity, though the effect size was small (f 2 = 0.08). No other significant associations were observed. Conclusions: The lack of significant findings for neighborhood environment factors suggests proximal factors (eg, features of the home environment) may be more important in predicting toddlers’ physical activity and sedentary behavior. More indoor physical activity opportunities may be needed on colder days for toddlers.

Open access

Natasha Schranz, Vanessa Glennon, John Evans, Sjaan Gomersall, Louise Hardy, Kylie D. Hesketh, David Lubans, Nicola D. Ridgers, Leon Straker, Michalis Stylianou, Grant R. Tomkinson, Stewart Vella, Jenny Ziviani and Tim Olds

Open access

Natasha K. Schranz, Timothy Olds, Roslyn Boyd, John Evans, Sjaan R. Gomersall, Louise Hardy, Kylie Hesketh, David R. Lubans, Nicola D. Ridgers, Leon Straker, Stewart Vella, Jenny Ziviani and Grant R. Tomkinson

Background:

Two years on from the inaugural Active Healthy Kids Australia (AHKA) Physical Activity Report Card, there has been little to no change with the majority of Australian children still insufficiently active.

Methods:

The 2016 AHKA Report Card was developed using the best available national- and state-based physical activity data, which were evaluated by the AHKA Research Working Group using predetermined weighting criteria and benchmarks to assign letter grades to the 12 Report Card indicators.

Results:

In comparison with 2014, Overall Physical Activity Levels was again assigned a D- with Organized Sport and Physical Activity Participation increasing to a B (was B-) and Active Transport declining to a C- (was C). The settings and sources of influence again performed well (A- to a C+), however Government Strategies and Investments saw a decline (C+ to a D). The traits associated with physical activity were also graded poorly (C- to a D).

Conclusions:

Australian youth are insufficiently active and engage in high levels of screen-based sedentary behaviors. While a range of support structures exist, Australia lacks an overarching National Physical Activity Plan that would unify the country and encourage the cultural shift needed to face the inactivity crisis head on.