1
Accelerometry assessed sedentary behaviour and physical activity levels during the segmented school day
1
in 10-14 year-old children: the HAPPY study 2
3
Daniel P Bailey
1,
Stuart J Fairclough
2
,
Louise A Savory
1
,
Sarah J Denton
1
, Dong Pang
3
, Colleen S Deane
1
, 4
Catherine J Kerr
1
5
6
Corresponding author: Daniel P Bailey. Email: daniel.bailey@beds.ac.uk. Telephone: +441234 793268 7
8
Abstract 9
The school day offers several different time periods that provide varying opportunities for sedentary time (SED) 10
and engagement in physical activity (PA), yet little is known about the PA and sedentary behaviour patterns of 11
boys and girls during these times. The volume, intensity and temporal distribution of SED and PA undertaken 12
by 135 schoolchildren aged 10-14 years, during different segments of the school day: a) school transport, b) 13
morning recess, c) lunch break, d) class time, and e) after school, was explored using tri-axial accelerometry. PA 14
was categorised into SED, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Girls engaged in 15
significantly more SED and LPA than boys during recess and lunch break (p < 0.05), while boys engaged in 16
significantly higher levels of VPA during recess (p < 0.001) and MPA and VPA during lunch break (p < 0.001). 17
PA engagement was similar between sexes during other segments of the day. Conclusion PA patterns appear 18
more beneficial for health in boys during less structured school-based time periods and interventions may 19
therefore target opportunities for girls to be physically active during these times to overcome this observed sex 20
deficit. 21
22
Keywords 23
Children; adolescents; physical activity; sedentary behaviour; accelerometry 24
25
1
Institute for Sport and Physical Activity Research, University of Bedfordshire, Polhill Avenue, Bedford,
Bedfordshire, MK41 9EA, UK.
2
Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Byrom Street,
Liverpool, L3 3AF.
3
Institute for Health Research, University of Bedfordshire, Polhill Avenue, Bedford, Bedfordshire, MK41 9EA,
UK.
2
Introduction
26
The prevalence of childhood obesity has reached epidemic proportions in the UK [39], as well as in other 27
European countries [46] and the US [30]. Despite significant investment in research and changes in policy 28
making, there have been no signs of decline in childhood obesity levels in recent years [30,39]. In children, 29
overweight and obesity may predispose to dyslipidaemia, hypertension, impaired glucose metabolism, and low 30
cardiorespiratory fitness (CRF) [2,7] and each of these risk factors may confer poor cardiometabolic health and 31
associated co-morbidities in later life [27,45]. 32
The causes of overweight and obesity are varied and complex, but at population level, are consistent 33
with sustained positive energy balance that may be a result of sedentary behaviour and low levels of physical 34
activity (PA) [40]. Guidelines for health thus recommend that young people engage in at least 60 minutes per 35
day of moderate-to-vigorous PA (MVPA) and that time spent being sedentary (SED) should be minimised [13]. 36
However, there is debate as to whether children are sufficiently active to benefit their health and prevalence 37
values for sufficiently active youth range between 1% and 100% when assessed using accelerometry [15,32,11] 38
and recent data suggest that only 32% of boys and 24% of girls in England aged 2-15 years typically meet the 39
government’s recommended guidelines [12]. Although variations in reported PA levels may be due in part to 40
discrepancies in methods of accelerometry data analysis [15], these findings advocate the need for a greater 41
insight into young people’s PA patterns to more effectively tailor PA promotion strategies in this population. 42
The school day offers several opportunistic time periods (e.g. school transport, morning recess, lunch 43
break, class time, and after school) for youth to be physically active through informal play, sport, and active 44
commuting. There is considerable evidence that demonstrates sex differences in PA levels, with boys typically 45
engaging in more habitual PA than girls [32,12]. However, little is known about the PA patterns of boys and 46
girls during segments of the school day, and, more specifically, their engagement in different subcomponents of 47
the PA intensity continuum i.e. SED, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Given that 48
the magnitude of the association between PA and some health outcomes are intensity driven [13], it is of 49
paramount importance to gain an insight into which segments of the day may benefit from strategies to reduce 50
sedentary behaviour and increased engagement in MPA and VPA. 51
Accelerometers may permit greater accuracy and precision than self-report measures and pedometers 52
[16,1] and allow analysis and interpretation of PA patterns and intensity across various segments of the day. 53
Accelerometry-based studies to date investigating PA patterns typically report on total PA [34], combined 54
MVPA [19], or only selected PA subcomponents e.g. only SED and VPA [41]. In addition, these studies have 55
3
also focused on average weekday and weekend day PA [34], hourly patterns [41], or in- and out-of-school time
56
periods [19] as opposed to specific segments of the day. These investigations have suggested that both in- and 57
out-of-school hours are important times for youths to engage in PA. However, the patterns of children’s 58
engagement in different PA intensities during specific segments of the school day remains unclear, nor is it 59
understood which segments of the day boys and girls differ in their PA intensity engagement. Furthermore, PA 60
levels may be influenced by cardiorespiratory fitness (CRF) [21] and adiposity [5] and many past studies have 61
failed to adjust for these important covariates when investigating the pattern and volume of boys and girls PA 62
levels during the school day [29,44]. Quantifying and adjusting for the potential effects of these variables would 63
strengthen our understanding of any observed sex differences in PA levels. 64
The primary aim of this study was therefore to utilise accelerometry to explore the volume and patterns 65
of 10-14 year-old boys’ and girls’ engagement in SED, LPA, MPA, and VPA during different segments of the 66
school day: a) school transport, b) morning recess, c) lunch break, d) class time, and e) after school. The 67
secondary aim of this study was to explore boys’ and girls’ compliance with recommendations for MVPA 68
during recess and lunch breaks. 69
70
71
Methodology 72
Sample 73
The 135 participants (78 girls) included were part of the HAPPY (Health And Physical activity Promotion in 74
Youth) study. This school-based study explored the effects of three interventions on PA levels and health 75
outcomes in 10-14 year-old schoolchildren. Participants were recruited on a voluntary basis from 11 schools 76
across Bedfordshire, UK and their baseline data used for analyses in the present study. Participants were 77
excluded if they had any contraindications to taking part in physical exercise. The study was approved by the 78
University of Bedfordshire ethics review board. Written informed consent was obtained from participants’ 79
parents and verbal assent from the participants before any testing procedures. 80
81
Measurements 82
Age was recorded as a decimal value for each participant using date of birth. Ethnicity was recorded as white or 83
non-white. A score for socioeconomic status (SES) was attributed to each participant using home postcode and 84
the 2007 Indices of Multiple Deprivation (IMD) [18,26]. Postcodes were converted into IMD scores using the 85
4
GeoConvert application [26]. These scores were categorised into tertiles with the lowest tertile indicating the
86
most deprived. 87
Stature was recorded to the nearest 0.5 cm using the portable Leicester Height Measure (Seca, 88
Birmingham). Body mass was recorded to the nearest 0.1 kg and body fat % (BF%) recorded to the nearest 0.1 89
% using the Tanita BC-418® Segmental Body Composition Analyzer (Tanita Corp., Tokyo). To determine 90
CRF, participants completed an age- and sex-specific all-out progressive cycle ergometer test to exhaustion 91
using a previously validated protocol [31]. Briefly, workloads increased every 3 min until the participant was no 92
longer able to continue. A maximal effort was deemed as a final heart rate ≥ 185 beats per min (bpm) and 93
subjective observation from the researcher that the child could not continue. Power output (watts) was 94
calculated as being equal to W
1
+ (W
2
.
t/180), where W
1
is work rate at fully completed stage, W
2
is the work 95
rate increment at final incomplete stage, and t is time in seconds at final incomplete stage. VO
2max
was 96
calculated using previously described formula [31] and expressed relative to body mass (mL/kg/min). 97
RT3® triaxial accelerometers (Stayhealthy, Inc., Monrovia, CA.) were used to measure seven 98
consecutive days of habitual PA using minute-by-minute sampling. Total minutes and proportion of total time 99
(to account for variations in the length of daily wear time between participants) spent in each segment of the 100
school day was determined for SED (< 288 counts per min [cpm]), LPA (288-969 cpm), MPA (970-2332 cpm), 101
and VPA (≥ 2333 cpm). PA intensity cut-off points were based on previously published literature in which the 102
RT3® triaxial accelerometer was validated against oxygen consumption (r = 0.87) in children [37]. Participants 103
were only included for data analysis if they had worn the accelerometer for a minimum of three school days [25] 104
and acquired a minimum daily wear time of nine hours [25]. Sustained 10 min periods of zero counts were 105
removed during the recoding process. 106
The segments of the school day analysed were a) school transport (the 30 min time period prior to 107
school starting time), b) morning recess, which ranged from 15-20 min in duration, c) lunch break, which ranged 108
from 45-65 min in duration, d) class time (typically five to six hours across the school day), and e) after school, 109
which included the time from the end of the last school lesson until 18:30. 110
The secondary aim of this study was to explore boys’ and girls’ compliance with recommendations for 111
MVPA during recess and lunch breaks. The recommendations applied were engagement in MVPA for at least 112
40% of recess and lunch breaks [35]. It is suggested that children should be active for 50% of physical education 113
lesson time [6]. However, when applying this guideline to recess time in previous research, few children met 114
this recommendation [42] and it may thus be an unrealistic target. In light of this, an alternative suggestion of 115
5
40% based on minimum activity recommendations that may be more achievable has been proposed [35] and
116
was thus applied in this study. 117
118
Statistical analysis 119
All analyses were carried out using SPSS version 18.0 (SPSS Inc., Chicago, IL.). Sex differences in descriptive 120
variables were determined by one-way ANOVA. ANCOVA was used to explore sex differences in accumulated 121
minutes and the proportion of time spent in each PA subcomponent during each segment of the school day. 122
Covariates entered into each of the ANCOVA models for school transport and after school segments were BF%, 123
CRF, ethnicity, and SES. Morning recess and lunch break models additionally included morning recess duration 124
and lunch break duration as covariates, respectively, while class time models included both morning recess and 125
lunch break duration as additional covariates. Prior to ANCOVA analysis, tests for homogeneity of regression 126
slopes were conducted and several significant interaction effects between sex (independent variable) and 127
covariates were found. Sub-group analyses were then conducted to explore where sex differences in the 128
dependent variable (PA intensity) varied according to levels of the covariate. Where interaction effects were 129
observed for BF% and CRF, these variables were split into tertiles (lowest tertile representing least fat and least 130
fit, respectively) for sub-group analyses, while for lunch break duration, this variable was split into fertiles with 131
the lowest fertile representing the shortest duration group. The proportion of boys and girls who met the 132
recommendations for PA engagement during recess and lunch break was determined i.e. those who spent 40% 133
of recess and lunch break time in MVPA [35]. Χ
2
tests were used to evaluate associations between sex and 134
achievement of the PA recommendations for recess and lunch break. The level of significance was set at p < 135
0.05. 136
137
Results 138
Table 1 shows the descriptive characteristics of the participants. One-way ANOVA revealed that BF% was 139
significantly higher in girls versus boys, while CRF was significantly higher in boys. The proportion of white 140
and non-white children was similar for both boys and girls. 141
Table 2 shows the percentage of total daily (i.e. school transport to after school hours time period) PA 142
intensity minutes accrued in each segment of the school day. The majority of SED time was accrued during 143
class time (63.9%), while after school hours also contributed substantially (25.8%). The majority of LPA was 144
also accrued during class time (46.3%) and after school hours (30.3). In addition to class time (37.1 and 31.2% 145