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PLOS One logoLink to PLOS One
. 2020 Jun 29;15(6):e0235293. doi: 10.1371/journal.pone.0235293

Profiling the health-related physical fitness of Irish adolescents: A school-level sociodemographic divide

Brendan T O’Keeffe 1,2,*,#, Ciaran MacDonncha 1,2,#, Helen Purtill 2,3,#, Alan E Donnelly 1,2,#
Editor: Kathryn L Weston4
PMCID: PMC7323969  PMID: 32598397

Abstract

Background and aims

Examining factors that may explain disparities in fitness levels among youth is a critical step in youth fitness promotion. The purpose of this study was twofold; 1) to examine the influence of school-level characteristics on fitness test performance; 2) to compare Irish adolescents’ physical fitness to European norms.

Methods

Adolescents (n = 1215, girls = 609) aged 13.4 years (SD .41) from a randomised sample of 20 secondary schools, stratified for gender, location and educational (dis)advantage, completed a series of field-based tests to measure the components of health-related physical fitness. Tests included: body mass index; 20 metre shuttle run test (20 m SRT); handgrip strength; standing broad jump (SBJ); 4 x 10 metre shuttle run; and back-saver sit-and-reach (BSR).

Results

Overall, boys outperformed girls in all tests, aside from the BSR (p < 0.005, t-test, Bonferroni correction). Participants in designated disadvantaged schools had significantly higher body mass index levels (p < 0.001), and significantly lower cardiorespiratory endurance (20 m SRT) (p < 0.001) and muscular strength (handgrip strength) (p = 0.018) levels compared to participants in non-disadvantaged schools. When compared to European norms, girls in this study scored significantly higher in the 20 m SRT, 4 x 10 metre shuttle run and SBJ tests, while boys scored significantly higher in the BSR test (Cohen’s d 0.2 to 0.6, p < 0.001). However, European adolescents had significantly higher handgrip strength scores (Cohen’s d 0.6 to 0.8, p < 0.001).

Conclusion

Irish adolescents compared favourably to European normative values across most components of HRPF, with the exception of muscular strength. School socioeconomic status was a strong determinant of performance among Irish adolescents. The contrasting findings for different fitness components reiterate the need for multi-component testing batteries for monitoring fitness in youth.

Introduction

Physical fitness is a multifaceted construct that can be described as an integrated measure of most, if not all, body functions that are involved in daily physical activity [1]. Health-related physical fitness (HRPF) is made up of multiple components including, cardiorespiratory endurance (CRE), musculoskeletal fitness (muscular strength, endurance, and power) and body composition, which have been identified as powerful markers of future health among children and adolescents [1, 2]. There is a consistent body of evidence supporting the favourable effects of moderate-to-high levels of physical fitness to health-related outcomes, including cardio-metabolic risk factors [3], musculoskeletal [4] and cognitive [5] traits in childhood and adolescence. It has also been reported that positive changes to HRPF during childhood and adolescence can mitigate the impact of negative health outcomes later in life [6].

Declining HRPF levels among youth internationally have been reported. For example, an international analysis of secular trends of CRE among adolescents, involving 11 countries from 1980 to 2000, noted a sample-weighted mean decline of 0.43% per year, and the decline was most prevalent in older adolescent age groups [7]. A meta-analysis of 20 m shuttle run test scores among a sample of 1,142,026 children and youth from 50 countries reported that 67% of boys (CI 95% ± 14%) and 54% (CI 95% ± 17%) of girls had healthy CRE according to Fitnessgram criterion referenced standards, and the numbers achieving healthy standards decreased systematically with age [8]. In contrast, Moliner-Urdiales and colleagues [9] reported significant increases in CRE among Spanish adolescents between 2001 and 2007 (Cohens d 0.2 to 0.4, p < 0.05). In terms of muscular fitness, Cohen et al. [10] reported that English schoolchildren have shown a decrease in upper body muscular strength, measured by handgrip dynamometer over the past decade, a trend also reported in Spain [9], Canada [11] and China [12]. However, Huotari et al. [13] reported that muscular fitness was higher in a cross sectional cohort of Danish adolescents in 2001 than an age-matched cohort from 1976.

Examining variations in HRPF data gathered from multiple countries should be interpreted with caution. Firstly, contrasting methodological approaches used for the measurement and interpretation of results can produce different outcomes [14]. Welsman and Armstrong argue that, in contrast to secular declines in cardio-respiratory fitness estimated from field-based measures such as those presented by Tomkinson et al. [7], lab-based measurement techniques reveal little or no differences in aerobic fitness among youth across time. Furthermore, minor changes to administration protocols, such as the measurement of handspan for handgrip strength as recommended by Ruiz and colleagues [15], could also result in measurement error when comparing scores across regions. The risks associated with criterion values have also been highlighted by Mahar et al. [16] who reported that 35% of 4th- and 5th-grade girls who achieved PACER standards failed to pass the 1-mile run/walk standards. Zhu et al. [17] have proposed the use of test equating statistics to enable two or more tests that measure the same construct in different ways to be compared on the same scale. Encouragingly, a consensus on reliable and valid approaches to monitoring HRPF in field-based settings has emerged in recent years, as reflected in the recent National Academy of Medicine’s report on measurement and health outcomes in youth [18], and the pan-European ALPHA (Assessing Levels of Physical Activity) project [19] that established a standardised test battery for monitoring HRPF throughout Europe.

At an individual level, variations in physical fitness are caused by a network of social, behavioural, physical, psychosocial and physiological factors [20]. Well established determinants of physical fitness among youth include age, gender and physical activity levels [21]. Inverse associations between physical fitness, particularly CRE, and overweight in adolescents have also been reported [21, 22]. The relationship between socioeconomic status and physical fitness has been less examined, with much of the research to date producing inconsistent results [23]. In addition, despite the prominence of fitness testing in schools [24], the influence of school-level sociodemographic characteristics including location and educational (dis)advantage on HRPF are scantly represented in the current literature. In one of the few studies to examine school sociodemographic characteristics and health nationally, Bel-Serrat and colleagues [25] reported that school-level educational (dis)advantage was a strong determinant of overweight and obesity in schoolchildren. Bai et al. [26] also concluded that there was clear evidence showing that school socioeconomic status was the most influential contextual factor for explaining disparities in school fitness outcomes among 157,971 schoolchildren from 675 schools in the US.

It has been projected that the Republic of Ireland is on course to become the most obese nation in Europe by the year 2030 [27]. Despite World Health Organisation recommendations [28], the Republic of Ireland lacks a clearly specified strategy for monitoring HRPF in youth. Consequently, there is a paucity of data on objectively measured fitness levels of Irish youth, with much of the health and activity surveillance surveys to date utilising self-reported measures [29]. To the authors’ knowledge, the Children Sport Participation and Physical Activity study [30] is the only study to measure HRPF among a nationally representative sample of adolescents in the Republic of Ireland. Woods and colleagues [30] reported no significant changes in CRE levels between 2010 and 2018, with 76% and 77% of participants, respectively, meeting established criterion referenced standards [31]. The collection of objective measures of health and physical fitness from population-based samples over pre-defined time periods is a crucial resource that can inform policy-makers and the public, and is vital for healthcare and education authorities for timely planning of prevention programs [32]. In light of the scarcity of research specific to the Irish context, the aim of the current study was twofold. Firstly, to examine the influence of school-level characteristics on fitness test performance of Irish adolescents from a randomised and stratified sample of schools, and secondly, to compare these data to established European normative values [33].

Methods

Sampling and recruitment

Research ethics approval for this study and the associated protocols was granted by the Institution Review Board of the Faculty of ****, ***, *** (***). All secondary schools with access to an indoor hall space of ≥ 25 metres and students in year one of secondary school with no inhibiting health conditions were eligible to participate. A randomised sample of 20 schools, stratified for gender (boys’ schools, girls’ schools and mixed-gender schools), location (urban and rural categorised by population density), and educational (dis)advantage, participated in the study. Designated disadvantaged schools were selected based on Department of Education and Skills categorisations as part of the Government of Ireland’s Delivering Equality of opportunity in Schools (DEIS) scheme [34]. This classification is based on a ‘Deprivation Index Scale’ which accounts for demographic growth, social class composition and employment status, in addition to centrally held Department of Education and Skills pupil data. There are currently 185 designated disadvantaged secondary schools in Ireland, representing just over one quarter of all secondary schools [34]. The procedure for generating a randomised sample was conducted using a special computerized code system in which all secondary schools in the mid-west and south-west region of Ireland were assigned a code and categorised according to the aforementioned strata. Due to the geographical spread of schools, and the need to visit each school individually, 20 schools was considered to be the maximum sample size achievable from a logistical viewpoint, and the minimum required to obtain a sufficient number of schools in each of the chosen strata. Although, the randomised and stratified sample represented the largest review of HRPF among Irish adolescents undertaken to date, participants were generated from schools in the mid-west and south-west regions of Ireland only due to logistical constraints, and thus, findings cannot be generalised for the entire country.

School and participant recruitment

Of the initial sample of 20 schools, two schools were deemed ineligible to participate due to insufficient indoor hall space, and two schools declined to participate due to time constraints. In each case, the next school on a randomised reserve list was recruited. Approval from the principal and cooperating physical education teacher in each school was granted following an initial email and telephone conversation. Study information sheets and consent forms were provided by cooperating teachers to all students and their parents. Cooperating physical education teachers were responsible for gathering consent forms. This study focused specifically on students in year one of secondary school education (ages 13 to 14), and was open to all students in the selected year group in each participating school who provided informed consent to participate and fulfilled the physical activity readiness questionnaire (PAR-Q) [35] pre-test requirements. A total of 27 students were deemed ineligible to participate due to underlying health conditions recorded on the PAR-Q. A minimum participation rate threshold of 70%, as used in other similar studies [36], was set for a school to be considered eligible. Reasons for non-participation were recorded on a non-participant form. The most commonly cited reasons were absenteeism, injury/sickness, and/or the students or parents deciding not to provide consent to participate in the study. Participation rates in the final sample were ≥ 75% in each school, with a mean participation rate of 61 students per school. Testing took place over a three month period between November 2018 and January 2019. A demographic profile of participants is provided in Table 1.

Table 1. Demographic profile of participants.
Category Sub category Number of schools Participants (%)
Gender (participants) Girls (Age: 13.4, SD .40) - 609 (50.1%)
Boys (Age: 13.5, SD .43) - 606 (49.9%)
School gender Boys 4 47 (14.4%)
Girls 4 67 (20.5%)
Mixed-gender 12 213 (65.1%)
Educational (dis)advantage a Non-disadvantaged 14 994 (81.8%)
Designated disadvantaged 6 221 (18.2%)
Location b Rural 8 390 (32.1%)
Urban 12 825 (67.9%)

a This classification is based on a ‘Deprivation Index Scale’ which accounts for demographic growth, social class composition and employment status, in addition to centrally held Department of Education and Skills pupil data.

b Categorised by population density: Urban, the cities of Cork and Limerick; Rural, all other areas of the mid and south west of the Republic of Ireland

Testing procedures

The cooperating physical education teacher in each school selected eight senior students (final two years of secondary education) to facilitate the administration of the test battery. Tests were delivered in a station format to small groups of five students or less, and each administrator was responsible for one test item on the test battery. A manual detailing standard operating procedures for each test item was designed for and read by both cooperating teachers and senior student administrators. Cooperating physical education teachers and student facilitators participated in a three hour workshop in which each administrator was assigned one test, and trained in the assigned test only. A comprehensive examination of students responses to the senior peer-facilitated approach has been provided elsewhere [37]. It reveals the vast majority (86.8%) of participants agreed or strongly agreed that the senior student facilitator made it easier for them to perform the tests. When asked to rank who they would like to administer fitness tests from most preferred to least preferred, 52.8% of students indicated that they would be in favour of the peer-assessed format used in the Youth-fit test battery, in comparison to an external expert (27.0%) or their teacher (20.2%) recording test scores [37].

Test administrators conducted several familiarisation trials, and examples of correct and incorrect trials were demonstrated. Test items included; body mass index (BMI); 20 m shuttle run test (20 m SRT); handgrip strength; standing broad jump (SBJ); 4 x 10 m shuttle run. The scientific rationale for the selection of the tests was based on their feasibility and reliability for administration in a school setting [38], and their established criterion-related validity [39]. Four additional tests of physical fitness and health commonly administered in school-based HRPF test batteries and large-scale health surveys, were also included, namely: 90° push-up; isometric plank-hold; back-saver sit-and-reach (BSR); and blood pressure. O’Keeffe and colleagues [40] confirmed the test-retest reliability of the administration protocol outlined above for each test item, reporting intra-class correlation coefficients of ≥ .797 and mean coefficient of variation values of 6.5% across all test items. Detailed test administration protocols for each test item are available in this study [40].

All tests were conducted in participating schools’ physical education halls, and took place during timetabled physical education. The authors were keen for testing to reflect the authenticity of a standard double class period of physical education in the Republic of Ireland school setting, therefore, testing lasted 80 minutes. Tests were administered in small groups of six or less participants at a testing station at any one time. Furthermore, in an effort to address fatigue or test sequencing as potential sources of measurement error, all participants had a minimum rest period of between three and five minutes between each testing station. The 20 m SRT is an estimate of maximal aerobic capacity, therefore, it was conducted on a separate day to all other tests using the Léger et al. protocol [41]. Participants were required to run between two lines 20 metres apart, while keeping pace with audio signals emitted from a pre-recorded CD. The initial speed was 8.5 km/h, and was increased by 0.5 km/h per minute. The test finished when the participant failed to reach the end lines concurrent with the audio signals on two consecutive occasions, or when the subject stopped because of fatigue.

Data collection and quality control

A software platform was developed specifically for the purpose of this study to enable efficient multi-site capture of data from participating schools. Following test administration, cooperating physical education teachers uploaded test results to a web-based application hosted on a secured server at the lead authors’ institution. Cooperating teachers received a tutorial on using the software from the lead author and a user manual outlining the procedure for inputting results. Biologically plausible value limits were assigned to each field to minimise potential inaccuracies during data input. An additional quality control feature included collecting test battery results sheets from participating schools, from which the lead author randomly selected half of the completed results sheets, and cross-referenced each to ensure the accuracy of results inputted.

Statistical analysis

Complete cases (n = 1215; designated disadvantaged, n = 221) were extracted from the software platform and transferred to Statistical Package for Social Sciences (SPSS version 25, Chicago IL) for analysis. The research team defined an incomplete case as missing the BMI recording, or two or more fitness test items. Incomplete responses (n = 66) were excluded from all analyses. A visual inspection of histograms and box plots showed that data were normally distributed, with skewness of ≤ 1.2 and kurtosis of ≤ 1.6. Means (M) and standard deviations (SD) were calculated for all scale scores, with t-tests and ANOVAs testing for differences by selected demographics. A linear mixed model analysis of variance was conducted to examine the differences between designated disadvantaged and non-disadvantaged schools for key health-related fitness outcome variables, controlling for age and gender as fixed effects, and school as a random effect. Results from this analysis were then graphically depicted using clustered error bar graphs.

Following a request, access was provided to the original dataset from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study [33]. This dataset contained gender and age-specific physical fitness normative values among European adolescents from 10 European countries with a similar gender (n = 911, girls = 544) and age (13.5 years, SD .31) profile to participants in the current study. Data collection for the HELENA study took place from 2006 to 2008. Administration protocols for the five field-based tests compared, namely, the 20 m SRT, SBJ, handgrip strength, BSR, and 4 x 10 m shuttle run, were the same for both studies, as detailed in Ortega et al. [33]. Cohen’s d was used to compare differences between participants in this study and age-matched European normative values by calculating the mean difference between the two groups, and dividing the result by the pooled standard deviation [33]. Cohen suggested that d = 0.2 be considered a ‘small’ effect size, 0.5 represents a ‘medium’ effect size and 0.8 a ‘large’ effect size. Correction for multiple comparisons was made via the Bonferroni correction. Participants physical fitness scores were also expressed using a quintile classification framework based on European normative values [33], corresponding to “very low”, “low”, “moderate”, “high”, and “very high” levels as recommended by Tomkinson et al. [42].

Results

Anthropometric characteristics and HRPF levels of the study sample are shown in Table 2. Overall, boys had significantly higher cardiorespiratory endurance (CRE) (20 m shuttle run test), muscular fitness (handgrip strength, standing broad jump (SBJ), 90° push-up and isometric plank hold) levels compared to girls, while girls had significantly higher flexibility (back-saver sit-and-reach (BSR)) (p < 0.001, t-test, with Bonferroni correction for multiple comparisons). Girls had significantly lower mean systolic blood pressure in comparison to boys, however, despite reaching statistical significance, the total difference in mean values was small (< 1.5 mmHg). The prevalence of overweight and obesity was estimated as per the criteria published by Cole et al. [43]. Over one quarter (25.8%) of girls and 23.9% of boys were overweight, of which 12.2% of girls and 9.2% of boys were obese. An inverse relationship between performance in the 20 m SRT (r = -.32, p < 0.001) and SBJ (r = -.29, p < 0.001) tests and overweight and/or obesity was observed. Boys and girls categorised as overweight or obese ran an average of 17 fewer shuttles (20 m SRT) and jumped (SBJ), on average, 14 centimetres (cm) less than their peers.

Table 2. Descriptive characteristics of the study sample, by gender.

Variable Total Total mean (SD) Boys Boys mean (SD) Girls Girls mean (SD) p value
Age 1215 13.4 (0.4) 606 13.5 (0.4) 609 13.4 (0.4) NS
BMI 1215 20.3 (3.6) 606 20.1 (3.6) 609 20.4 (3.7) NS
BSR (cm) a 1177 23.5 (9.3) 591 22.0 (8.7) 586 25.0 (9.7) < 0.001 c
Systolic BP (mmHg) 1189 109.4 (13.3) 595 110.7 (13.3) 594 108.2 (13.1) < 0.001 c
Diastolic BP(mmHg) 1189 74.0 (11.4) 595 73.0 (11.3) 594 75.0 (11.5) < 0.001 b
Standing broad jump (cm) 1206 151.0 (26.1) 601 158.3 (27.3) 605 146.6 (23.7) < 0.001 b
Handgrip strength (kg) a 1201 23.0 (5.1) 598 24.1 (5.7) 603 21.9 (4.3) < 0.001 b
90° push-up (repetitions) 1177 10.9 (8.6) 583 13.3 (8.6) 594 8.5 (8.0) < 0.001 b
Isometric plank-hold (s) 1177 77.7 (49.5) 581 86.7 (54) 596 68.9 (42.8) < 0.001 b
4 x 10 m shuttle run (s) 1174 12.2 (1.4) 588 12.0 (1.1) 586 12.4 (1.7) < 0.001 b
20 m SRT (# shuttles) 1138 47.4 (22.4) 570 53.4 (22.8) 568 41.4 (20.3) < 0.001 b

Abbreviations: BMI, body mass index; BSR, back-saver sit and reach; SD, standard deviation; BP, blood pressure; 20 m SRT, 20 m shuttle run test.

a The average of right and left side scores is shown in the table. Significant differences (p < 0.001, with Bonferroni correction) were found between boys and girls, independent samples t-test.

b Indicates a more favourable HRPF score for boys.

c Indicates a more favourable HRPF score for girls. Due to school absences and/or injury, not all totals amount to 609 (girls) and 606 (boys).

No statistically significant differences between urban and rural schools were found across any of the variables analysed. However, differences were observed between participants in mixed-gender and single-gender schools. An ANOVA was conducted to examine differences in HRPF between boys and girls in single-gender and mixed-gender schools, using a Bonferroni adjusted p value of .01 for the variables listed in Table 3. Boys in mixed-gender schools had significantly higher BSR, SBJ and 20 m SRT, and significantly lower BMI levels, in comparison to participants in boys’ schools. Girls in mixed-gender schools had significantly higher SBJ and handgrip strength scores in comparison to participants in girls’ schools.

Table 3. A comparison of selected health-related physical fitness variables among participants in single-gender and mixed-gender schools.

Variable Mixed-gender, boys (n = 443) Single-gender, boys (n = 163) p value Effect size n2 Mixed-gender, girls (n = 413) Single-gender, girls (n = 196) p value Effect size n2
BMI 19.9 (3.4) 20.9 (4.0) 0.002 .02 20.3 (3.6) 20.6 (3.9) NS .00
BSR (cm) a 23.9 (8.0) 21.3 (8.8) 0.002 .02 26.7 (8.9) 21.5 (10.3) < 0.001 .06
Standing broad jump (cm) 161.7 (27.2) 150.7 (25.7) < 0.001 .03 148.6 (23.8) 142.1 (22.1) 0.001 .02
Handgrip strength (kg) a 24.1 (6.2) 24.3 (5.7) NS .00 22.3 (4.3) 21.2 (4.1) < 0.001b .02
4 x 10 m shuttle run (s) 11.9 (1.0) 12.0 (1.2) NS .00 12.4 (1.2) 12.2 (2.3) NS .00
20 m SRT (# shuttles) 55.4 (21.7) 48.0 (24.9) < 0.001 .02 42.2 (18.4) 39.8 (23.6) NS .00

Data are shown as means with standard deviation in brackets. Abbreviations: BMI, body mass index; BSR, back-saver sit and reach; 20 m SRT, 20 m shuttle run test.

a The average of right and left side scores is shown in the table. Significant differences (p < 0.001, with Bonferroni correction) were found between boys and girls, independent samples t-test.

b Indicates a more favourable HRPF score for boys.

c Indicates a more favourable HRPF score for girls. Due to school absences and/or injury, not all totals amount to 609 (girls) and 606 (boys).

Descriptive characteristics of boys and girls in non-disadvantaged versus designated disadvantaged schools are presented in Table 4. A mixed model analysis of the differences between designated disadvantaged and non-disadvantaged schools for key health-related fitness outcome variables, controlling for age and gender as fixed effects, and school as a random effect, is presented in Table 5. Mean values were significantly higher in designated disadvantaged schools for BMI (p < 0.001, t-test with Bonferroni correction) and significantly lower for the 20 m SRT (p < 0.001), 90° push-up (p = 0.014), SBJ (p = 0.013) and handgrip strength (p = 0.05). Differences were particularly large for the 20 m SRT, with mean values for designated disadvantaged schools 19 shuttles (380 metres) fewer than non-disadvantaged schools. Clustered error mean bar graphs, with 95% confidence intervals, were used to graphically depict the differences in performance at a school-level across key HRPF fitness variables, as displayed in Fig 1.

Table 4. Descriptive characteristics of students in non-disadvantaged and designated disadvantaged schools, by gender.

Boys non-disadvantaged (n = 472) Boys disadvantaged (n = 134) Girls non-disadvantaged (n = 522) Girls disadvantaged (n = 87)
Variable Mean (SD) Mean (SD) Mean (SD) Mean (SD)
BMI 19.8 (3.4) 21.3 (4.0) 20.2 (3.5) 21.8 (4.2)
BSR (cm) a 22.1 (8.5) 21.6 (9.4) 25.5 (9.4) 21.4 (10.6)
Systolic BP (mmHg) 110.8 (13.4) 110.1 (13.1) 108.2 (13.1) 108.4 (13.5)
Diastolic BP (mmHg) 72.8 (11.3) 73.6 (11.5) 75.1 (11.6) 74.3 (10.6)
Standing broad jump (cm) 161.8 (26.7) 148.0 (26.5) 147.6 (23.3) 139.9 (23.5)
Handgrip (kg) a 24.6 (5.5) 22.6 (5.9) 22 (4.1) 21.9 (5)
90° push-up (reps) 14.2 (8.4) 10.2 (8.2) 8.9 (8.2) 6.3 (5.8)
Isometric plank hold (s) 92.2 (54.6) 67.5 (47.4) 70.8 (43.5) 57.5 (36.9)
4 x 10 m shuttle run (s) 11.9 (1.0) 12.3 (1.3) 12.3 (1.7) 12.7 (1.3)
20 m SRT (# shuttles) 57.8 (21.3) 38.0 (21.3) 43.9 (20.3) 26.3 (12.2)

Abbreviations: BMI, body mass index; BSR, back-saver sit and reach; SD, standard deviation; BP, blood pressure; 20 m SRT, 20 m shuttle run test

a The average of right and left side score is shown in the table and was used for all analyses.

Table 5. Adjusted mean differences in non-disadvantaged versus designated disadvantaged schools, controlling for age and gender as fixed effects, and school as a random effect.

Variable Non- Disadvantaged (n = 994) Disadvantaged (n = 221) Mean difference (CI)b p value
BMI 20.0 21.6 -1.6 (-2.2 to -0.97) < 0.001
BSR (cm) a 24.3 20.7 3.5 (-3.6 to 10.7) NS
Systolic BP (mmHg) 109.4 108.9 0.5 (-2.4 to 3.4) NS
Diastolic BP (mmHg) 73.9 73.3 0.6 (-2.5 to 3.7) NS
Standing broad jump (cm) 154.3 142.0 12.3 (2.9 to 21.9) 0.013
Handgrip (kg) a 23.4 22.0 1.4 (0.0 to 2.7) 0.05
90° push-up (reps) 11.5 8.4 3.1 (0.7 to 5.6) 0.014
Isometric plank hold (s) 79.4 60.7 18.7 (-0.5 to 38.0) NS
4 x 10 m Shuttle (s) 12.1 12.7 -0.6 (-1.3 to -0.0) NS
20 m SRT (# shuttles) 51.3 32.2 19.1 (12.3 to 25.9) < 0.001

Abbreviations: BMI, body mass index; BSR, back-saver sit and reach; SD, standard deviation; BP, blood pressure; 20 m SRT, 20 m shuttle run test.

a The average of right and left side score is shown in the table and was used for all analyses.

bMean difference (95% CI) from linear mixed models, controlling for age and gender as fixed effects, and school as a random effect.

Fig 1. Clustered error bar mean graphs of 20 m shuttle run, body mass index, standing broad jump and handgrip strength tests with 95% confidence intervals, by school.

Fig 1

Designated disadvantaged schools are highlighted red, non-disadvantaged schools are highlighted blue.

When compared to European normative values [33], girls in this study scored significantly better in the 20 m SRT, 4 x 10 m shuttle run and SBJ tests, while boys scored significantly higher in the BSR test (Cohen’s d ranging from 0.2 to 0.6, p < 0.01, Bonferroni correction). However, European adolescents had significantly higher handgrip strength scores (Cohen’s d 0.6 to 0.8, p < 0.01). European boys also had significantly higher SBJ scores (Cohen’s d = 0.5, p < 0.01). Using a quintile classification framework, the authors established the percentage of Irish adolescents from the current study that fell within each quintile of European normative values [33] (Figs 2 and 3). Only 11.1% of boys and 10.0% of girls achieved a very high score > 80th centile) for handgrip strength, with 34.0% of boys and 31.2% of girls classified in the very low quintile (< 20%). SBJ scores were more evenly spread, 19.5% and 9.9% scoring in the very low category, and 17.6% and 17.1% scoring in the very high category, for boys and girls, respectively. With regard to the BSR test, 39.1% of boys and 29.2% of girls achieved a very high score based on European norms. While boys’ scores for the 4 x 10 m shuttle run were relatively evenly distributed in each quintile, 41.1% of girls achieved a score ≥ 80th percentile. Finally, the most significant differences with European normative data were found in the 20 m SRT. Almost two thirds of girls (61.4%) and 41.1% of boys in the current study achieved a very high ranking (≥ 80th percentile), with only 5.6% of boys and 0.9% of girls categorised in the very low category (≤ 20th percentile).

Fig 2. Quintile classification framework for physical fitness components for boys (n = 606), based on European normative values [33].

Fig 2

Fig 3. Quintile classification framework for physical fitness components for girls (n = 609), based on European normative values [33].

Fig 3

Discussion

The aim of the current study was to examine the influence of school-level characteristics on fitness test performance and to compare Irish adolescents’ physical fitness to European norms. Overall, participants in designated disadvantaged schools had significantly poorer HRPF levels in comparison to those in non-disadvantaged schools, participants in mixed-gender settings had significantly lower BMI levels and higher muscular strength levels compared to those in single-gender schools, and although participants in this study had significantly higher CRE levels, European adolescents had significantly higher muscular strength levels. This study represents the first analysis of all components of HRPF among adolescents from the Republic of Ireland, which we hope will form the basis of further examinations of physical fitness variables among youth across a broader range of age groups.

Perhaps unsurprisingly, boys scored higher than girls across all components of HRPF, aside from flexibility. This corroborates the findings of a recent meta-analysis of physical fitness among adolescents internationally [44], which reported that boys consistently scored higher than girls on fitness tests, except on the sit-and-reach test of flexibility in which girls scored higher. A recent national survey of physical activity and sport participation among Irish youth reported that only 7% of girls in secondary schools met the recommended daily activity guidelines of 60 minutes of moderate-to-vigorous physical activity compared to 14% of boys [30]. The authors also reported non-participation levels of 45% in any form of community sport among adolescent girls, in comparison to 31% among boys. Furthermore, in line with research to date, an inverse relationship between performance in the 20 m SRT and SBJ tests and overweight/obesity was found in the current sample. In an investigation of the determinant factors of physical fitness among 13,622 European children, Zaqout and colleagues [21] highlighted the significance of BMI as a physical fitness determinant, independent of physical activity. In an examination of overweight/obesity and physical fitness among 519 Brazilian children and adolescents aged 7 to 15 years, Dumith et al. [22] also reported that higher BMI values were associated with declines in physical fitness, independent of age. The prevalence of overweight, classified according to the same age and sex specific cut points [43], was 25% among a nationally representative sample of Irish adolescents in a recent longitudinal study [45], one percent less than the figure reported from data generated as part of the current study. In addition, age-matched mean 20 m SRT values were similar to those from the most recently reported national representative data [30].

Participants in mixed-gender schools had significantly higher estimated CRE (20 m SRT) and muscular strength (handgrip strength), and significantly lower BMI levels, in comparison to participants in single-gender schools. A recent survey of students attitudes towards fitness testing in school settings [37] reported that participants in mixed-gender settings had significantly more positive attitudes than those in single-gender schools. Ishee and Ward [46] did report that girls in mixed-gender schools achieved higher moderate to vigorous physical activity levels in their physical education lessons in comparison to those in single-gender schools, however, boys did not vary significantly. Van Acker et al. [47] similarly reported that participants in coeducational settings achieved significantly higher moderate to vigorous physical activity levels during physical education lessons in comparison to single-gender schools.

Contrasting findings emerged from comparisons between the current study sample and age-matched European normative values generated from the HELENA study [33]. Girls in this study had significantly higher mean scores in the 4 x 10 m shuttle run and 20 m SRT in comparison to their European peers, while boys in this study scored significantly higher in the back-saver sit-and-reach test. However, as illustrated in Figs 2 and 3, over three quarters of Irish boys and girls were classified as moderate or below average for handgrip strength when compared to European norms using a quintile classification framework. This is a finding of particular concern given the emerging evidence-base linking poor musculoskeletal fitness in adolescence with negative health outcomes later in life [4, 48]. In contrast, 84.3% of girls and 66.5% of boys scored above the 60th percentile in the 20 m SRT when compared to European normative values. Mean 20 m SRT values were similar to those from the most recent nationally representative data [30]. Nationally, research has indicated a significant drop off in sports participation and physical activity rates among young adolescent girls from the age 14 [49]. Although beyond the scope of the current study, an examination of fitness variables across all school-going adolescent age groups is needed confirm if the reported differences between Irish and European adolescents track across all adolescent age groups.

An important finding to emerge from this study was the disparity in fitness levels between participants in designated disadvantaged and non-disadvantaged schools. Participants in designated disadvantaged schools had significantly higher BMI levels, and significantly lower 20 m SRT and SBJ scores in comparison to those in non-disadvantaged schools. A comprehensive analysis on the influence of socioeconomic status on physical fitness among European adolescents concluded that socioeconomic status was positively associated with physical fitness, independently of total body fat and habitual physical activity [23]. In one of the few empirical studies to investigate the impact of school sociodemographic characteristics on physical fitness variables, Welk et al. [50] reported that physical fitness was consistently higher among students in schools categorized as low diversity and high socioeconomic status. Bai and colleagues (2016) similarly reported clear evidence that school socioeconomic status was the most influential contextual factor for explaining disparities in school fitness outcomes. It has also recently been reported that school socioeconomic status was a strong determinant of overweight and obesity in Irish schoolchildren [25]. This suggests that government funding utilised for the promotion of healthy lifestyle behaviours among youth should provide additional support for designated disadvantaged schools.

This study had some limitations which should be noted. Firstly, although the current study sample represents the largest examination of multiple components of HRPF in the Republic of Ireland to date, due to logistical constraints, participants were only generated from year one of secondary school education, precluding an analysis of fitness variables across all adolescent age groups. Additionally, the sample size of 20 schools is small for the linear mixed model analysis of non-disadvantaged (n = 14) versus designated disadvantaged (n = 6) schools. However, the randomised and stratified nature of the sample, the variety of fitness tests used and the provision of the original HELENA dataset to facilitate more detailed comparisons with participants in the current study, were important strengths.

Conclusion

This study represents the first comprehensive review of multiple components of health-related fitness among a stratified sample of adolescents in the Republic of Ireland. The contrasting findings for different fitness components within our sample reiterate the need for multi-component HRPF test batteries for monitoring physical fitness in youth. Overall, age-matched comparisons of HRPF levels with European norms were broadly positive for all components, aside from muscular fitness in which European adolescents scored significantly higher. Therefore, interventions aimed at improving the physical fitness and activity levels of Irish youth should include a focus on muscular fitness. In terms of school level characteristics specifically, data presented in the current study indicated that adolescents in mixed gender schools outperformed those in single gender schools across most HRPF components. Furthermore, the extent of the disparity in fitness levels between participants in designated disadvantaged and non-disadvantaged schools was a finding of particular concern. Future interventions designed to promote healthy lifestyle behaviours among school-going populations should give special consideration to students in designated disadvantaged schools. The provision of additional support funds to promote healthy lifestyle behaviours could represent an efficient model of funding, targeting those who are most in need.

Supporting information

S1 File

(SAV)

Acknowledgments

The authors would like to acknowledge the assistance of the participants, parents, principals and, in particular, cooperating physical education teachers involved in this study. The authors would also like to acknowledge iMosphere® for their assistance in the development and design of the web-based component.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

Initials: BOK Grant number: GOIPG/2017/789 Grant fund: Government of Ireland Postgraduate Scholarship Grant fund website: http://research.ie/ No role played by funders in any part of the study.

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Decision Letter 0

Kathryn L Weston

2 Apr 2020

PONE-D-20-05075

Profiling the health related fitness of Irish adolescents: A school level socioeconomic status divide.

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Reviewer #1: An interesting paper that is clear and easy to follow. I have a few minor comments:

I think it is usual practice to report actual p values, unless p<0.001, this hasn't been done consistently.

Did you create BMIz-scores to calculate the proportions that were overweight? If so this data should go in the tables and could be used in the analysis.

Discussion, third paragraph "...physical activity rates among young ADOLESCENT girls"... not adolescents, unless you don't mean to have the word 'girls' in the sentence?

Fig 1 and 2 need to have the categories altered slightly, as at the moment the boundaries fall into two categories, ie someone on the 20th centile is currently both 'very low' and 'low'. Ditto 40th/60th/80th. Check which need to be >< or also equals.

Reviewer #2: Many thanks to the authors for their work in preparing this manuscript. I enjoyed reading the manuscript and feel it will make a good contribution to the literature, given the lack of published data for this country, employing more objective methods. I have outlined queries below.

Introduction

The authors have presented a good overview of the literature in adolescents and the different findings across these datasets. I feel this section could be further strengthened by briefly offering explanations for these differences – are these attributed to methodological differences in how outcomes were measured, inconsistencies in reference points applied, or as a result of the samples recruited.

Methods

The authors could provide some further justification to compare with the European dataset. The methodology should make reference to the population in the European dataset (similar age, gender) and if outcomes were measured in the same way or how any differences were accounted for in the analysis.

Data collection and quality control – I was interested if the schools noted or reported any issues with participants being measured by older peers? I feel the authors should consider the rationale for this approach, and whether it may have introduced a bias within the study sample. Is it possible that some participants (perhaps those who were less sporty/fit/overweight) may have been put off from taking part because of this data collection approach, and how this may have impacted upon the results across schools?

The authors note that disadvantaged schools make up ~ 25% of all secondary schools. Given the difference in sample size across non-disadvantaged and disadvantaged within the results, did the authors consider recruiting a higher proportion of disadvantaged schools to provide a more balanced sample across groups.

Results

Lines 231 – 234 – These findings are quite descriptive and the authors should avoid highlighting individual mean scores.

From Table 2, were any other school level factors (mixed-gender / school location) considered in the analysis which may have influenced differences between disadvantaged and non- disadvantaged schools.

Discussion (line numbers missing)

The opening paragraph highlights that the aim was to look at school level characteristics, and first highlighted results discusses males vs females. Was this technically a school level characteristic i.e. did this only compare all male vs all female schools? I feel this could be further clarified, as it is more a characteristic of the overall gender breakdown sample as opposed to a school level characteristic?

Paragraph 2 notes the higher scores for boys across the sample – did the authors consider collecting any additional information on physical activity levels/sports participation. Would suggest including some references here to support the reasoning behind these observed findings.

Minor comments

Manuscript uses males and females in some instances, then boys and girls in others. Would suggest a consistent approach across the manuscript.

Abstract

Background: Include introductory line to provide context to the article before outlining the study aims

Method: Line 21 – Reword to clarify that tests were undertaken to measure components of physical fitness

Main body

Methods

Were all tests performed in the same order by each study participant to control for the potential of some testing to impact upon performance in another outcome?

Results

Of the 20 schools recruited, how many were disadvantaged? Can only see student numbers, not school numbers also.

What was the mean number of students who participated across each school?

Formatting

Appears to be inconsistency in font size across manuscript version

The figures are unclear/blurred and difficult to view

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Reviewer #1: No

Reviewer #2: No

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Jun 29;15(6):e0235293. doi: 10.1371/journal.pone.0235293.r002

Author response to Decision Letter 0


20 Apr 2020

Response to Reviewers

(PONE-D-20-05075)

The authors would like to thank the editor and reviewers for their time in reviewing this manuscript. Each comment is addressed in the comment log below, and highlighted in red font colour on the updated manuscript.

Response to editor comments

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: Formatting updates have been made to ensure the latest submission aligns with style requirements.

2. In your Methods section, please provide additional information about the participant recruitment method and the demographic details of your participants. Please ensure you have provided sufficient details to replicate the analyses such as:

a) The recruitment date range (month and year),

Response: Manuscript updated P.7 L.157-159.

b) A description of any inclusion/exclusion criteria that were applied to participant recruitment,

Response: Manuscript updated. Schools: P.6 L.119-121 and P.7 L.141 -143. Student participants: P.7 L3.147-152.

c) A table of relevant demographic details,

Response: The manuscript has been updated to include a demographic profile of participants, see Table 1 P.8 L.160-164.

d) A statement as to whether your sample can be considered representative of a larger population,

Response: Manuscript updated: P.6 L136-139.

e) A description of how participants were recruited,

Response: The is detailed on P.7 L.144-147.

f) Descriptions of where participants were recruited and where the research took place.

Response: The manuscript has been updated to provide clarification. Where participants were recruited: P.7 L.140-159. Where the research took place: P.9 L.192-198.

3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly.

Response: Following consultation and approval from our Institution’s Research Ethics Review Board, the de-identified dataset will now be made available.

4. Please upload a new copy of Figure 1 as the detail is not clear. Please follow the link for more information: http://blogs.PLOS.org/everyone/2011/05/10/how-to-check-your-manuscript-image-quality-in-editorial-manager/

Response: Figure 1 has been updated using PACE software as recommended.

5. While revising your submission, please upload your figure files to the Pre-flight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Response: All three figures have been updated using PACE software, and are attached on the revised submission.

Response to reviewer one comments

1. An interesting paper that is clear and easy to follow. I have a few minor comments:

Response: The authors would like to thank you for your time in conducting this review. Each comment is addressed in the comment log below, and all edits are highlighted in red font colour on the updated manuscript.

2. I think it is usual practice to report actual p values, unless p<0.001, this hasn't been done consistently.

Response: Thank you for your recommendation. Where appropriate, p values have been updated to actual values throughout the manuscript, unless p <0.001 as you indicate above. Occasionally, where multiple individual variables produced p values of < 0.001, they are referred to as a collective rather than listing all individual p values. e.g. Abstract P.1 L.32-33.

3. Did you create BMI z-scores to calculate the proportions that were overweight? If so this data should go in the tables and could be used in the analysis.

Response: Thank you for your comment. BMI z-scores were not calculated. The prevalence of overweight and obesity was estimated as per the criteria published by Cole et al. (2000) as indicated on P.12 L.254-255. These set threshold values were used by the most recent national survey of health among a national sample, which enabled a direct comparison. See P.18 L.364 -369.

4. Discussion, third paragraph "...physical activity rates among young ADOLESCENT girls"... not adolescents, unless you don't mean to have the word 'girls' in the sentence?

Response: Updated to “adolescent girls”.

5. Fig 1 and 2 need to have the categories altered slightly, as at the moment the boundaries fall into two categories, i.e. someone on the 20th centile is currently both 'very low' and 'low'. Ditto 40th/60th/80th. Check which need to be >< or also equals.

Response: Thank you for recognising this mistake. This was an oversight on the authors’ behalf. Figures 2 and 3 have been updated to include the correct symbols.

Response to reviewer two comments

1. Many thanks to the authors for their work in preparing this manuscript. I enjoyed reading the manuscript and feel it will make a good contribution to the literature, given the lack of published data for this country, employing more objective methods. I have outlined queries below.

Response: The authors would like to thank your time in providing such detailed recommendations and sagacious advice on the manuscript. Each comment is addressed in the comment log below, and all edits are highlighted in red font colour on the updated manuscript.

2. Introduction

The authors have presented a good overview of the literature in adolescents and the different findings across these datasets. I feel this section could be further strengthened by briefly offering explanations for these differences – are these attributed to methodological differences in how outcomes were measured, inconsistencies in reference points applied, or as a result of the samples recruited.

Response: Thank you for your recommendation. The authors agree that this is an important point to address in light of the stated aims of the manuscript. Therefore, the introduction has been updated to include a new paragraph that details the importance of interpreting and comparing datasets with caution. See P.4 L.66-83.

3. Methods

The authors could provide some further justification to compare with the European dataset. The methodology should make reference to the population in the European dataset (similar age, gender) and if outcomes were measured in the same way or how any differences were accounted for in the analysis.

Response: Thank you for your suggestion. The statistical analysis paragraph of the methodology section has been updated to provide a more comprehensive overview of the demographic profile and protocols used in the HELENA study, thus forming a stronger rationale to conduct the comparison. See P.11 L.230-237.

4. Data collection and quality control

I was interested if the schools noted or reported any issues with participants being measured by older peers? I feel the authors should consider the rationale for this approach, and whether it may have introduced a bias within the study sample. Is it possible that some participants (perhaps those who were less sporty/fit/overweight) may have been put off from taking part because of this data collection approach, and how this may have impacted upon the results across schools?

Response: Thank you for your query. A comprehensive examination of students responses to the senior peer-facilitated methodological designed utilised in the current manuscript is provided in a separate peer reviewed article in the European Physical Education Review Journal. This study reveals that the vast majority (86.8%) of students agreed or strongly agreed that the senior student facilitator made it easier for them to perform the tests. When asked to rank who they would like to administer fitness tests from most preferred to least preferred, 52.8% of students indicated that they would be in favour of the senior-peer facilitated format used in the Youth-fit test battery, in comparison to an external expert (27.0%) or their teacher (20.2%) recording test scores. P.8 L.173-179 has been updated to reflect this.

In terms of the potential impact of this approach on participation rates, participation rates in the final sample were ≥75% in all schools, with a mean of 86% per school, and many schools reached maximum participation. It should also be stated, as noted on P.8 L.171-173 that senior peer-facilitators participated in a three hour workshop on test administration protocols. The importance of administering the tests sensitively and in a supportive manner were addressed during this workshop. Finally, as mentioned on P.18 L.364-368, the prevalence of overweight and estimated cardio-respiratory fitness were very similar to most recently reported nationally representative data, further emphasising the potential for this approach to monitoring key health indicators on a larger-scale.

5. The authors note that disadvantaged schools make up ~ 25% of all secondary schools. Given the difference in sample size across non-disadvantaged and disadvantaged within the results, did the authors consider recruiting a higher proportion of disadvantaged schools to provide a more balanced sample across groups.

Response: The objective was to recruit a sample from the mid-west and south-west region of Ireland that was representative of national demographic characteristics, hence, 6 designated disadvantaged schools were recruited representing 30% of schools in the final sample. It should also be noted that, on average, student numbers in designated disadvantaged schools are significantly lower than non-designated schools.

6. Results

Lines 231 – 234 – These findings are quite descriptive and the authors should avoid highlighting individual mean scores.

Response: Thank you for your recommendation. The authors agree that this is overly descriptive and does not add to the paper. We have removed these lines in the updated manuscript.

7. From Table 2, were any other school level factors (mixed-gender / school location) considered in the analysis which may have influenced differences between disadvantaged and non- disadvantaged schools.

Response: The results section has been updated to indicate that no statistically significant differences were found between urban and rural schools for any of the variables analysed. P.12 L.261-262.

8. Discussion (line numbers missing)

Response: Apologies for this oversight. The updated manuscript includes continuous line numbers for the entire manuscript.

9. Discussion: The opening paragraph highlights that the aim was to look at school level characteristics, and first highlighted results discusses males vs females. Was this technically a school level characteristic i.e. did this only compare all male vs all female schools? I feel this could be further clarified, as it is more a characteristic of the overall gender breakdown sample as opposed to a school level characteristic?

Response: Thank you for your comment. The authors acknowledge that the gender comparison does not specifically address the stated aim (i.e. school characteristics), and thus, have removed reference to this comparison from the opening paragraph of the discussion. The authors do feel that there is merit in the second paragraph of the discussion which provides an overview of male and female participants given the dearth of HRPF data specific to this population. The authors have also updated the results section to provide a comparison between males and females in single-gender and mixed-gender schools. This is a school level characteristic which we feel is of direct relevance to the stated aim, and would be of specific interest to the target readership. See P.12 L.262-268. Also, see Table 3 P.13 L.276-282. The discussion section has also been updated to reference the school gender comparison (P.20 L.365-376).

10. Paragraph 2 notes the higher scores for boys across the sample – did the authors consider collecting any additional information on physical activity levels/sports participation. Would suggest including some references here to support the reasoning behind these observed findings.

Response: Thank you for your comment. The collection of additional information beyond HRPF was not an objective of the current study. However, the authors acknowledge that the inclusion of such data could serve to explain some of the gender disparities. Therefore, the manuscript has been updated to include data from a recent national survey of physical activity and sport participation levels among youth. (P.18 L.369-380)

Minor comments

11. General

Manuscript uses males and females in some instances, then boys and girls in others. Would suggest a consistent approach across the manuscript.

Response: The manuscript has been updated to ensure consistency throughout when referencing participant gender.

12. Abstract

Background: Include introductory line to provide context to the article before outlining the study aims

Response: Thank you for this suggestion. The introductory line of the abstract has been updated to provide context of the article (P.1 L15-16) “Examining factors that may explain disparities in fitness levels among youth is a critical step in youth fitness promotion.”

13. Method: Line 21 – Reword to clarify that tests were undertaken to measure components of physical fitness

Response: The methods section of the abstract has been updated to clarify that tests were undertaken to measure the components of health related physical fitness. (P.1 L.22)

14. Main body

Methods

Were all tests performed in the same order by each study participant to control for the potential of some testing to impact upon performance in another outcome?

Response: P.9 L.192-198 has been updated to reflect test sequencing. Tests were not performed in the same order by all participants due to time constraints. The authors were keen for testing to reflect the authenticity of a standard school environment, therefore, testing lasted 80 minutes, which is a standard double class period of physical education in the Republic of Ireland. Tests were administered in small groups with no more than six students at a testing station at any one time. Furthermore, in an effort to address potential participant fatigue and/or test sequencing as potential sources of error, the test battery was sequenced to ensure participants had a minimum rest period of three to five minutes between each testing station.

15. Results

Of the 20 schools recruited, how many were disadvantaged? Can only see student numbers, not school numbers also.

Response: Table 1 in the updated manuscript provides a full demographic profile of the sample, including the number of schools for each of the chosen strata.

16. What was the mean number of students who participated across each school?

Response: The manuscript has been updated to include the mean number of participants across each school (P.7 L.157-159)

Formatting

17. Appears to be inconsistency in font size across manuscript version

Response: The manuscript has been updated to ensure consistency in font size throughout.

18. The figures are unclear/blurred and difficult to view

Response: In line with the recommendations from the editor, all three figures in the latest manuscript have been updated using PLOS One’s online image quality enhancer tool PACE.

Decision Letter 1

Kathryn L Weston

12 Jun 2020

Profiling the health-related physical fitness of Irish adolescents: A school-level sociodemographic divide.

PONE-D-20-05075R1

Dear Dr. O'Keeffe,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Kathryn L. Weston, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Please note some very small comments from the Reviewers regarding a minor typo in Table 3, spacing throughout the manuscript and the suggestion to remove a sentence from the Discussion. Please ensure these are addressed in the final version of the manuscript. 

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #3: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The additions have really strengthened the paper.

Check the new table 3 as one of the variables has two decimal places (this is the minor revision, as PLOS ONE says it does not correct typos).

Reviewer #3: Thank you for addressing the comments of the reviewer. I have a few minor comments/amendments required. Please check the full manuscript for adherence and consistency to the SI units of reporting. For example, for 20m shuttle run, there should be a space between the number and unit. Please check all numbers and units. Additionally the authors sometimes use N in capitals, other times as n. Please ensure there is a space between n and the equals sign. For example, n = 35. Not n= 35. Finally, within the discussion, the authors state....to the best of the authors knowledge this is the first study.......I would personally consider refraining from using such expressions. Firstly, you cannot be sure. And secondly, I am not sure what this adds to the manuscript and the interpretation of the findings. It may perhaps be better to allow the reader to decide. A short article on why to avoid such phrases can be found here https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(04)17096-7/fulltext

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: No

Acceptance letter

Kathryn L Weston

19 Jun 2020

PONE-D-20-05075R1

Profiling the health-related physical fitness of Irish adolescents: A school-level sociodemographic divide.

Dear Dr. O'Keeffe:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Kathryn L. Weston

Academic Editor

PLOS ONE

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    S1 File

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    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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