Decline of physical activity in early adolescence: A 3-year cohort study.

This study analyses the changes of moderate-to-vigorous physical activity (MVPA) in a cohort of boys and girls aged 11 (n = 50) and 14 (n = 50). Physical activity was assessed with Bodymedia SenseWear Pro Armband monitor for 6 days in October 2013 and October 2016, considering 90% of daily wear time (21h and 40min). The initial sample (n = 160) included the children who wore the monitors at age 11 but the final analyzed sample included only those children from the initial sample (n = 50), whose data fulfilled the inclusion criteria at age 11 and 14. Physical fitness and somatic characteristics of the final sample (n = 50) were compared to a representative sample of Slovenian schoolchildren at ages 11 (n = 385) and 14 (n = 236) to detect possible bias. Changes in MVPA were controlled for maturity using the timing of adolescent growth spurt as its indicator. The average MVPA decreased more than one quarter (34.96 min) from age 11 to age 14. Children were significantly more active at age 11 than at age 14 (p < 0.01, d = 0.39). The timing of puberty onset in girls was significantly earlier (12.01 ± 1.0 years) (p < 0.01) than in boys (13.2 ± 0.75 years) (p < 0.01, d = 1.35). There was a significant gender difference in moderate-to vigorous physical activity at age 14 (p < 0.05, η2 = 0.12) and between moderate-to vigorous physical activity at age 11 and 14 (η2 = 0.11). After controlling for the timing of adolescent growth spurt the girls at age 11 showed significantly higher level of physical activity than at age 14 (p < 0.01, η2 = 0.17). Early adolescence is crucial for the development of physical activity behaviours, which is especially pronounced in girls. The significant decline of MVPA between ages 11 and 14 in Slovenia are likely influenced by environmental changes since the timing of adolescent growth spurt did not prove as a factor underlying the decline of MVPA.

Introduction

Physical activity (PA) is one of the key health determinants in life [1] and is one of the sources of total energy expenditure, which incorporates active energy expenditure, metabolism in resting state, the thermal effects of food digestion and body growth in children and adolescents [2]. Existing evidence shows that PA has positive effects on psychosocial health, and the functional capacity and wellbeing of people [3], whereas physical inactivity increases health risks [4,5]. Research findings indicate that PA in school-age, and moderate-to-vigorous physical activity (MVPA) in particular, positively influence the public health of the adult population, which resulted in the development of recommendations for policymakers to increase PA of the European population [6]. The first Slovenian PA guidelines for children are based on the World Health Organization (WHO) recommendations of at least 60 minutes of MVPA daily [7]. In order to reach the recommendations, children should undertake various types of PA (regular physical education (PE) in school, organized sport practice, active play, active transportation etc.). The guidelines also define the structure of suitable PA (e.g. warm-up, gradual effort, cool-down, and relaxation), as well as suggest appropriate types (exercises improving aerobic and muscular fitness) and frequency of exercise for children and youth [7,8]. The most elaborated national PA guidelines and WHO recommendations are suggesting for PA volume to decrease with age, which is rather unusual since environmental demands for sedentariness actually increase with age from childhood to adolescence and adulthood [9,10].

In both genders, MVPA levels decrease with age [11], especially during adolescence [12]. Most of the existing studies has found the decline of MVPA in children and adolescents [9,10,13-19], but did not take into account the differences in maturity. The decrease of MVPA may extend into adulthood [12,20,21] and seems to be more associated with biological age than with chronological age [22]. In this regard, we aimed to analyse the changes in habitual PA in a group of children in predominantly pre-adolescent period (at age 11) and predominantly early adolescent period (at age 14) also in relation to maturity. Children and adolescents from different countries experience diverse rhythms of everyday life due to different educational systems, social settings and cultural differences [23]. Considering this, it is important to analyse each national setting separately and adjust national recommendations to the actual needs and possibilities of local populations as well as to the most intensive periods of PA behavioural change [13,24-26], which is also reflected in behavioural patterns of PA in adulthood [27-29].

In addition to the described issues with PA recommendations, also the assessment of PA continues to present a huge research challenge due to multiple research approaches and tools that very often produce incomparable data. In the past, PA of Slovenian children and youth has been assessed predominantly with the use of questionnaires [30-33], but in recent years the development of various wearables [34-38] has enabled the utilization of more objective methods for estimation of PA. Wearable monitors, such as pedometers, load transducers, accelerometers, heart rate (HR) monitors, combined accelerometer/HR monitors and multiple sensor systems [34-36,39], can provide more accurate assessment of mechanical and physiological parameters of PA compared to self-report tools [35]. The most advanced generation of wearable monitors are multisensory devices such as SenseWear Armband Pro (SWA, BodyMedia, Inc., Pittsburgh, PA), used in this study, which provides estimation of EE based on biaxial accelerometer, galvanic skin response and body heat loss [39,40]. SWA has been validated in children [41-43] and adults [44] as well of different intensities of PA [45-47].

Previous studies and comparisons on objectively and subjectively assessed data showed that Slovenian school children and adolescents (6–17 y) are among the most physically active in the world [48-52], with more than 80% reaching the 60 minutes of daily MVPA [49,50]. However, most of the comparisons focused on the preadolescent children [49,50,53,54]. The purpose of this longitudinal study is to analyse the changes in the amount of PA of boys and girls in the early stages of adolescence based on objectively assessed PA data. The monitored period between ages 11 and 14 is characterised by the onset of puberty and intensive somatic development and growth, resulting in increased developmental and behavioural heterogeneity among children within the same chronological age group [12,55]. Namely, differences in PA between pre-adolescent girls and boys can be a result of girls’ typical earlier onset of puberty [56], while at the same time the individual differences in the onset of puberty within boys and girls can very often exceed the mentioned sex differences. We hypothesised that MVPA decreases from age 11 to 14 in boys and girls, that decrease is more pronounced in girls and that maturity negatively affects this decrease.

Methods

Sample

Data for the present study were acquired from a longitudinal cross-sectional study The Analysis of Children’s Development in Slovenia (ACDSi) which has been monitoring physical and motor development of Slovenian children and youth [57,58] and was being carried out every 10 years in the last five decades. The study uses a sentinel approach to provide a nationally representative sample of children from 11 different locations, stratified according to the type of environment (rural, rural-industrial, urban-industrial, urban). The primary sampling unit was school and the secondary one class. In the 2013 ACDSi our sample included 3,476 children and early-adolescents in the 6 to 14 age group. For the purpose of the present study only 11-year-olds (born on October 1, 2002, ± 6 months) of both sexes, who mostly did not yet experience adolescent growth spurt (pre-adolescents), attending primary school Grade 6 at the time of measuring, were included. The total sample of 11-year-olds comprised of 385 children, within which the initial sample of 160 children was invited to wear the SenseWear Pro Armband (SWA). The sample size was dictated by the number of available SWA sensors (n = 50) that still allowed us to monitor their physical activity of children from different localities within one month of the same season and therefore minimise the effects of weather conditions on children’s habitual physical activity. The same schoolchildren wearing SWA at age 11 were measured again at age 14 when the majority already experienced the adolescent growth spurt and were thus considered as early-adolescents. The number of children from the initial sample with sufficient wear time on the required days at age 11 was 141 (boys = 70; girls = 71). The excluded 19 children did not accumulate sufficient wear time due to device malfunction or irregular wearing of the device. The final sample of children at ages 11 and 14 that met the inclusion criteria for both years was 50 (boys = 21). This final sample was included in the final analysis (Fig 1). The average age of the children included in the first round of the PA monitoring at age 11, was 11.3 ± 0.3 years (boys 11.4 ± 0.4; girls 11.3 ± 0.3) and the average age of the children in the second round at age 14 was 14.3 ± 0.3 years (boys 14.3 ± 0.3; girls 14.2 ± 0.3). Due to considerable exclusion and some drop-out from the first to the second round of the PA monitoring, we needed to identify a possible exclusion/drop-out bias (see S1 to S4 Tables) and compared the somatic characteristics and physical fitness of the children in the final sample to the initial sample (see flowchart, Fig 1). In order to investigate possible bias between initial sample and the total sample at age 11 and between the final sample and the non-included children from the initial sample at age 14, we compared their somatic characteristics as well as their physical fitness with the following variables: standing broad jump, obstacle course backwards, 20-s drumming test, flamingo balance test, sit and reach, shoulder circumduction, hand grip strength, bent arm hang, 20-m shuttle-run, height, weight, biceps skinfold, triceps skinfold, subscapular skinfold, suprailiac skinfold, elbow breadth, wrist breadth, calf circumference, mid-thigh circumference, arm length, leg length, shoulder breadth, pelvic breadth, femoral breadth and ankle breadth.

Fig 1

Participants’ flowchart with drop-out and exclusion reasons.

Measuring procedure

PA was measured using a multi-sensor device SWA (Bodymedia SenseWear Pro Armband; BodyMedia Inc., Pittsburgh, USA). SWA device is based on the recognition of energy expenditure patterns and the estimation of PA. It uses several non-invasive biometrical sensors which measure various physical indicators (e.g. thermal conduction rate, galvanic skin response, skin temperature, environmental temperature, and PA measured with 2-axis accelerometer) and calculates energy expenditure via algorithms, which include data from several sensors as well as sex, age, height and weight of a measured subject. SWA was validated against doubly labeled water in children with high correlations for all comparisons (>0.90) [59] and is considered to be a reliable measuring device in children [40,42,47,60]

Children wore the SWA on the triceps of their right arm for one week [61-63], 24 hours per day except when showering, bathing and when practicing sports activities (usually at competitions or swimming), if they were not allowed to wear it due to safety reasons or device limitations (for example water resistance limitations when swimming). Further analysis of PA included only those children who wore the SWA device at least five days in a row (including both weekend days) [61,64,65] and whose wear time exceeded 90%. The SWA device collected data in one-minute epoch intervals. The main reason for our conservative approach was to reduce the error of under- and overestimation of PA due to missing wear-time in a greater extent than in the existing studies.

Body height, sitting height, and body lengths were measured with the use of anthropometers to one-millimetre precision levels (Siber & Hegner, Zurich, Switzerland). Body mass was measured using a portable electronic scale with 100-gram precision (Tanita BWB-800P, Arlington Heights, IL, USA). The precision of measurement was checked every time the scale was moved.

All other anthropometric measurements, physical fitness measurements, protocols, and equipment have been thoroughly described elsewhere [57].

Data collection

All the parents were notified about the purpose and procedures of data collection and their written consent was collected prior to measurements. Data collection was performed in October 2013 and October 2016. A trained team of researchers delivered the SWA devices on a Wednesday morning and collected the device the following Tuesday. The functioning of the SWA was explained to the children prior to the start of the monitoring period. In addition, short written guidelines of the proper use of equipment were prepared and given to the children, their parents, and teachers. Physical fitness tests and anthropometric measurements at ages 11 and 14 were administered by a highly trained team of researchers according to the prescribed protocol [57]. During the measurements, children were barefoot and wore light clothes. Approval of the National Medical Ethics Committee was obtained in June 2013 (ID 138/05/136).

Variables

The analysis of PA included two indicators of PA estimated through the SWA data: total energy expenditure (in calories) and duration of MVPA (in minutes). Although 3 METs (The Metabolic Equivalent of Task) has been widely used as an intensity threshold to distinguish between sedentary and MVPA, there is considerable evidence that 4 MET is a more suitable cut-off point for classifying MVPA in children and adolescents [66,67]; therefore MVPA was defined as a PA ≥ 4 MET. For the assessment of the timing of adolescent growth spurt, we used the anthropometric measurements that included body height, body mass, sitting height, and age at the time of measurement. We used Mirwald’s equation [68] to calculate the timing of adolescent growth spurt of included children. The timing of the adolescent growth spurt provides a benchmark of the maximum growth during early adolescence and provides a common landmark to reflect the occurrence of other body dimension velocities within and between individuals [69]. Adolescent growth spurt typically occurs approximately two years after the onset of puberty [70]. For boys the predictive equation was: maturity offset (years) boys = -9.236 + (0.0002708 * (leg length * sitting height)) + (−0.001663 * (age * leg length)) + (0.007216 * (age * sitting height)) + (0.02292 * (weight ÷ height * 100)). For girls the predictive equation was: maturity offset (years) girls = - 9.376 + (0.0001882 * (leg length * sitting height)) + (0.0022 * (age * leg length)) + (0.005841 * (age * sitting height)) + (- 0.002658 * (age * weight)) + (0.07693 * (weight ÷ height * 100)). The equation estimates the time distance from the adolescent growth spurt at the time of measurement, based on the ratio between the length of the torso and the legs. The growth of leg length precedes the growth of the torso, which changes the body proportions and by subtracting maturity offset from chronological age, age at adolescent growth spurt could be determined. This method was validated in studies of youth PA [71-73] and of young athletes [74-78]. Moreover, this method has been validated in an independent longitudinal samples in boys [79] and girls [80].

Data analysis

PA patterns were analysed with the Bodymedia SenseWear Professional 8.1 software package while all the statistical analyses were calculated by SPSS 25.0 (IBM Inc., Armonk, USA). Data are presented as mean and standard deviation, t-values, F-ratios and effect size (Cohen’s d and η2). Independent T-test was used to check for statistical differences in multiple physical fitness and anthropometric variables (standing broad jump, obstacle course backwards, 20-s drumming test, flamingo balance test, sit and reach, shoulder circumduction, hand grip strength, bent arm hang, 20-m shuttle-run, height, weight, biceps skinfold, triceps skinfold, subscapular skinfold, suprailiac skinfold, elbow breadth, wrist breadth, calf circumference, mid-thigh circumference, arm length, leg length, shoulder breadth, pelvic breadth, femoral breadth and ankle breadth): a) between boys and girls from the total sample in 2013 (n = 385), who were excluded from (n = 244) or included in (n = 141) the initial sample at age 11, and b) between boys and girls from the total sample in 2016, who were excluded from (n = 160) or included in (n = 50) the final sample at age 14 (Fig 1). In this way we were able to determine if the 11- and 14-year-olds who were included in PA analysis in 2013 and 2016, respectively, differed from their excluded peers. Differences in MVPA between boys and girls were then analysed using a paired sampled T-test. Differences in maturity between boys and girls were considered as proposed in other studies [73,81] and were analysed using Independent samples T-test, while normal distribution was checked with Q-Q plots, and the homogeneity of variances with Levene’s test. Repeated Measures Analysis of Covariance (RM ANCOVA) with Bonferroni correction was used to check for differences in longitudinal measures (2 time points, 3 years apart) between boys and girls, controlling for maturity with time distance from adolescent growth spurt (used as a covariate). ES was calculated using Cohen’s d (when t-test was used) and η2 (when RM ANCOVA was used). Alpha was set at 0.05.

Results

Independent samples T-test revealed that there were no statistical differences in physical fitness or somatic characteristics between boys and girls from the total sample (n = 385), who were included in the initial sample (n = 141) or excluded from it (n = 244) at age 11 (see S1 and S2 Tables).

The only small statistically significant difference at age 11 was observed in sit and reach test among boys, included in the initial sample (17.80 cm) and boys, who were excluded from it (15.82 cm) sample (t(190) = -2.03, p = 0.044). At age 14 no statistical differences in physical fitness or somatic characteristics were observed (see S3 and S4 Tables) between boys and girls from the total sample in 2016, who were included in the final sample (n = 50) or excluded from it (n = 160).

The expressed significant difference in the flexibility of hamstrings muscles and lower back (measured with sit-and-reach test) is probably irrelevant in regard to physical activity and it is unlikely that they influenced the drop-out or irregular wearing of the SWA sensors that lead to exclusion from the analysis of the final sample. Estimated PA values of girls and boys at ages 11 and 14 are shown in Fig 2.

Fig 2

Estimated MVPA of girls and boys at ages 11 and 14.

MVPA–moderate-to-vigorous physical activity; ↑ maximum; ↓ minimum; * p < 0.05; ** p < 0.01; values in the columns as Mean ± SD.

Without controlling for the timing of adolescent growth spurt, total MVPA off boys and girls was significantly higher at age 11 than at age 14 (t(49) = 2.75, p < 0.01, d = 0.39). MVPA in girls at age 11 was statistically higher than three years later (t(28) = 3.18, p < 0.01, d = 0.20), whereas the difference in MVPA between boys at ages 11 and 14 was not statistically significant (t(20) = 0.545, p = 0.592, d = 0.13). MVPA in boys at age 14 was significantly higher than in the girls of the same age (t(32.14) = 3.357, p < 0.05 d = 0.092) by 62.4 min, whereas the differences in MVPA between girls and boys at age 11 was not statistically significant (t(32.14) = 0.935, p = 0.355, d = 0.27).

There was a statistical difference in the timing of adolescent growth spurt between boys and girls. Girls experienced it significantly earlier (12.01 ± 1.0 years old) than boys (13.2 ± 0.75 years old) (t(48) = 4.201, p < 0.01, d = 1.35).

After controlling for the timing of the adolescent growth spurt, results of RM ANCOVA showed that there was a significant difference in average MVPA between boys and girls at age 11(F(1,47) = 6.294, p < 0.05, η2 = 0.12). Total difference of boys’ and girls’ MVPA at age 11 and 14 (F(1,47) = 5.945, p < 0.05, η2 = 0.11) proved to be significant. The amount of MVPA of boys at age 14 did not significantly differ from their MVPA at age 11 (p = 0.60), whereas MVPA of girls at age 14 significantly differed from their MVPA at age 11 (F(1,27) = 9.799, p < 0.01, η2 = 0.17).

Discussion

The aim of this longitudinal study was to analyse the changes in the amount of PA of boys and girls in the early stages of adolescence based on objectively assessed PA data.

The first important finding of the present study is that there is a visible decrease in MVPA between the ages of 11 and 14 which is more pronounced in girls. The average decrease of MVPA in girls was 41% compared to boys, who experienced a 7% decrease. The decrease of MVPA during early adolescence and especially in girls [82,83] was expected since such trends have been observed also in other studies [13,16,84,85]. The findings from the present study concur with a comparative study between Denmark, Portugal, Estonia, and Norway, which discovered decreasing MVPA in pre-adolescents, which was more pronounced in boys (approx. 30%) than in girls (approx. 20%) [86]. Similar findings have also been noticed by Jurak et al. [85] in a comparative study on PA of 11-year-old children from Ljubljana (Slovenia), Zagreb (Croatia) and Ann Arbour (USA). Boys from Ljubljana and Zagreb were physically more active than girls, although more than 90% of adolescents reached the WHO PA recommendations during the weekdays and more than 85% during weekends. Previous studies in Slovenia showed that 86% of the 11-year olds and 66% of 14-year olds is reaching the WHO PA recommendations [49,50,52] which is similar to the findings of the present study, where 84% of 11-year olds (n = 50) and 68% of 14-year olds (n = 50) are reaching the WHO PA recommendations. The significant decrease of MVPA between ages 11 and 14 in Slovenia is likely a combination of several factors. Although some studies found biological development to be related to the drop of PA in adolescence [56], contributing it to various factors such as non-exercise activity thermogenesis [87,88], reduced dopamine release or loss of dopamine receptors [89-91] or influence of biological maturity status, our analysis showed that the drop was evident with or without controlling for the timing of adolescent growth spurt. This leads to the conclusion that in our case the underlying factors of the adolescent drop of PA might not be biological but environmental. In this regard the school environment can be identified as one of the most important factors for this evident change. Namely, between ages 6 and 11 all Slovenian children have 3 classes of PE per week (45 minutes each), while in the last three years of primary school from ages 12 to 14 the number of compulsory PE classes drops to two per week [92] which is a considerable reduction. In the last three years of primary school pupils are also becoming growingly burdened with schoolwork; the number of school subjects increases from 11 to 14 [85] and their weekly workload increases from 25.5 to 28.5 hours, sometimes even to 32 hours [85]. Consequently, the sedentary activities of children at school and at home increase (more homework and studying), which can partly explain the decrease in PA.

As there are no intergenerational comparisons about the objectively evaluated PA of schoolchildren, it is impossible to conclude whether the 14-year-olds today achieve lower levels of PA than their peers in the past in the past. The comparisons of the level of the PA of Slovenian teenagers with their peers from other countries show that the PA of the Slovenian population is higher, particularly during the week [48-51]. Also the comparisons of physical fitness, which is inevitable result of habitual physical activity, show that Slovenian 14-year-old girls today have significantly higher level of physical fitness than the girls of the same age in 1990, whereas the boys still have a slightly lower physical fitness level [93] than their peers from the same year. All of these findings indicate that the decrease of MVPA in this age period is a universal phenomenon [15,86,94,95], although not necessarily influenced by biological changes during the maturation period.

Strengths and limitations

In the existing studies, the duration of wear time was ranging from 1h/day to 16.7 h/day [96], while the most common duration period was ≥ 10 h/day [97]. In order to assess as complete picture of the pre-adolescents’ daily PA patterns as possible one of the most important strengths of the present study is the wear time, which was over 90% (21h and 40min) per day. However, this strong criterion was unfortunately also the main reason for omitting a considerable number of data from the analysis. Further strengths of the present study is the use of the same measuring equipment throughout the study and the inclusion of timing of adolescent growth spurt. However, there are also some limitations: i) as in all PA studies, children were aware that they were being measured and monitored, which might have resulted in the changes of their habitual PA patterns; ii) high measurement and equipment costs limited the availability of SWA sensors and did not allow the measurement of PA of all included children during the same week which means that the PA patterns could be affected by other factors such as different weather conditions; iii) due to the short battery life and recording memory, a 1-minute interval for the collection of signal was used; consequently, not all short-burst PA durations could have been recorded, which might have resulted in underestimating the overall duration and intensity of recorded PA; iv) MVPA was measured only for one week, therefore we cannot interpret our results as behavioural PA; v) biomechanical and physical factors could affect the results as increased mass give lower acceleration and the increased height of children produces longer pendulum [98]; vi) arm worn device is more sensitive to arm movement, therefore results could be overrated [99]; vii) external factors could influence PA between the ages of 11 and 14: family problems, friendship problems, dietary habits and changes of environment/school, socioeconomic status, which have not been controlled for; viii) rigorous inclusion criteria regarding the wear time could have resulted in exclusion of some children who intensively practice sport; for example, children had to remove the measurement equipment during the competitions, in contact sports, and swimming activities; ix) total body mass was used in calculation of energy expenditure, thus it could be confounded by adiposity (a more precise choice would be lean mass proportional measures but it could not be used because the algorithms of the PA analysis software are based on actual body mass); x) anthropometry and equation-based methods like Mirwald et al. equation [69] for predicting the timing of adolescent growth spurt are not the most precise tools [100], therefore radiograph-based methods [80,101] would be recommended in future research; xi) the use of the fixed intensity thresholds in assessment of MVPA during pre-adolescence may not be the most suitable approach during adolescence due to changes in body size, composition and physical fitness, therefore the use of specific cut-off points should be used in the future [102].

Conclusion

This study contributes to the understanding of changes in PA among Slovenian pre-adolescents. Similar to other studies our results confirm the decrease of MVPA with age, but the differences between boys and girls in our study are considerably more pronounced. Since the greater drop of MVPA was observed in girls, future research should aim to explore the use of different approaches in encouraging the PA in boys and girls. Future studies should continue prioritizing longitudinal methodologies with bigger implications on gender differences in MVPA, including information about other PA determinants, such as environment, socioeconomic status and parental education.

Independent samples T-test comparison of physical fitness and somatic characteristics between boys from the total sample who were excluded (n = 120) and the ones who were included (n = 81) in the initial sample at age 11.

(DOCX)

Click here for additional data file.

Independent samples T-test comparison of physical fitness and somatic characteristics between girls from the total sample who were excluded (n = 105) and the ones who were included (n = 79) in the initial sample at age 11.

(DOCX)

Click here for additional data file.

Independent samples T-test comparison of physical fitness and somatic characteristics between boys from the original sample who were excluded (n = 84) and the ones who were included (n = 21) in the final sample at age 14.

(DOCX)

Click here for additional data file.

Independent samples T-test comparison of physical fitness and somatic characteristics between girls from the original sample who were excluded (n = 102) and the ones who were included (n = 29) in the final sample at age 14.

(DOCX)

Click here for additional data file.

(XLSX)

Click here for additional data file.

4 Oct 2019

PONE-D-19-20032

Decline of physical activity from childhood to adolescence: A 3-year longitudinal study

PLOS ONE

Dear Prof. Starc,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please see below for extensive and detailed comments from two expert reviewers. While both reviewers see interest and merit in your study, they have comments and concerns about various aspects of the paper, all of which should be addressed fully in your revision.

We would appreciate receiving your revised manuscript by Nov 18 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Kathryn L. Weston, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Additional Editor Comments (if provided):

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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: Partly

Reviewer #2: Partly

**********

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

Reviewer #1: No

Reviewer #2: No

**********

3. 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: Yes

Reviewer #2: Yes

**********

4. 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 #2: Yes

**********

5. 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: Oversell, the results of the study are relevant in determining PA levels of boys and girls in Slovenia. However, the paper requires some major modifications in terms of how the data is reported and interpreted, to ensure clarity to the reader. The discussion and conclusion should support the findings, without overstating or establishing any causal inference.

Abstract

Line 17: please change ‘The study’ to ‘This study’

Line 18: please change to ‘boys and girls aged 11 and 14’. Please state n = for each age. From this sentence, it is not clear if the 11 year olds and 14 year olds were the same children (i.e. you analyzed their PA at aged 11, and then followed up 3 years later by analyzing their PA levels again at aged 14). Please make this clear to the reader. Also, can you please state how long they wore the Bodymedia for (i.e. how many days), and if the measurements were taken at the same time of year (please provide month and date)

Line 20-21: It is not clear about when PA was measured, and what you mean by subsample at the age 11, and final subsample at age 11 and 14. Can you please re-word to clarify this for the reader

Line 21: please use abbreviation (MVPA)

Line 22: please clarify what you mean by ‘longitudinally measured’ and provide n =. What ages are you referring to? Both 11 and 14 years? Or just 11 years? And how did you compare?

Line 23: please add ‘a’ before representative, and delete ‘the’ before age 11

Line 24: please use abbreviation (MVPA)

Line 24 – 24: compared to what?

Lines 24-26: please provide p values. The results section is not clear for the reader. You have ES, the eta squared symbol, and p values. Can you please provide a concise statement about the results, and use consistent reporting values (i.e. p values, ES, t values, f ratios etc)

Line 28: please use abbreviation (MVPA)

Line 28-29: please use abbreviation (MVPA)

Lines 30-32: The conclusions do not match the aim or findings. Can you please reword to include an appropriate conclusion based on the findings, as you do not directly measure schoolwork, participation in PE lessons, or extracurricular PA/PA outside the school environment

Introduction

Line 35: please delete the full stop and ‘it’, and replace with ‘and’ is one of the …..

Line 41: please add ‘the’ before adult

Line 42: please insert a comma before which

Line 43: please write World Health Organization in full before abbreviating

Line 48: ‘suitable contents’ is not clear for the reader. Can you please define

Lines 49 – 52: is there any evidence that the guidelines should differentiate between childhood and adolescence? Could you please clarify what you mean by childhood and adolescence (i.e. provide the ages in years). Is there any evidence that you can provide to support increased sedentary behavior in adolescence?

Lines 52-54: can you please provide the specific ages of childhood and adolescence (see comment above), and also provide evidence to support why it is important to analyse these changes. What does the literature state in terms of the transition from childhood and adolescence? How does this impact PA in adulthood etc.

Lines 54-56: I am not sure that ‘the matter is further complicated’ in relation to your study, as you are not comparing children from different countries, only Slovenia. So I would delete ‘the matter is further complicated’. You also use the word ‘different’ three times in this sentence. Could you please reword to allow the sentence to flow better for the reader

Line 59: please provide evidence that the age groups you are referring to are the ‘most problematic’

Line 63 delete ‘the’ before recent

Paragraph two (lines 60 – 78): I am not sure on the relevance of the paragraph to your study. You discuss advantages and limitations of questionnaires, DLW and accelerometers (none of which are utilized in your study). But you do not mention wearable technologies. And then the paragraph suddenly finishes, and moves on to discuss PA in Slovenia, which does not flow. As you are not comparing these methods (i.e. questionnaires, DLW or accelerometers) in your study I would remove this paragraph, and include pertinent and relevant information on wearable technologies and the use of the Body Media Sense wear armband to assess PA in children

Line 79: please specify the ages of the school children

Lines 81-86: Here you define preadolescents, and puberty. However, in the first paragraph (lines 50-51) you talk about the difference between childhood and adolescence. As you are only looking at PA in children aged 11 and 14, I do not think you can refer to ‘issues/problems’ between childhood and adolescence (in the first paragraph), as you are not actually measuring this in your study. The world health organization defines adolescence as between the ages of 10 and 19. Early adolescence (i.e. puberty) may be defined as ages 10-14. I would suggest therefore, that you temper your introduction (particularly the first paragraph), as you are not really examining differences in PA between childhood and adolescence, but looking at the change in PA during early adolescence (i.e. puberty)

Line 81-82: please see comment above. Are you sure that 15-18 y is ‘preadolescent’? Or is this age group mid adolescence? My understanding is that 10-14 y is ‘preadolescent’.

Lines 83-91: This information would be better suited to the methodology section. It is also not clear from these sentences exactly how you will control for biological maturity. What do you mean by discriminating factor? How will you control for this in the analyses? Please state this clearly in the methodology section only (i.e. PHV) was entered as a covariate

Can you please provide a hypothesis. And also state how long you will measure PA for. You mention ‘longitudinally’. But do you just mean you will analyze their PA once when they are 11, and once again when they are 14. How long will you analyse PA for?

Methods

Line 96. What is ACDSi. Please define this abbreviation

Line 98. What do you mean by ‘multiple location approach’. Was their random stratified sampling from each area of the country?

Line 103. How were the subsample of n = 160 chosen? Was their random stratified sampling of the 385 children eligible?

Line 107: please delete of before 14

Line 108-109: how did you define sufficient wear time?

Line 128: delete ‘also’ before in

Line 129: why was a 7 d period chosen? Due to logistical reasons (i.e. amount of kit)? Does 7 d provide a reliable and valid measure of PA in these children?

Lines 132-134. What is this cut off based on? Why 5 d? and why > 90%?

Line 148: To have worn the devices for 7 d should the collection not have bene the following Wednesday? Or am I missing something

Lines 166 – 172. It is a little difficult to follow as a reader, who did not conduct the study, what you mean by first to second round of PA. Is this from October 2013 (i.e. aged 11), to October 2016 (i.e. aged 14)? What do you mean ‘final subsample’, and ‘initial subsample’, and ‘total sample’. Please be very clear and specific about the time (i.e. month/year), number and ages of children, sex etc that you are referring to

Line 171: please insert ‘the’ before following

Line 181: please state which variables, rather than just ‘multiple variables’

Line 182: provide n for ‘total sample’, provide n = for subsample, provide n = for subsample at age 11. I found it difficult to read this sentence, and to follow exactly which samples/children you are referring to.

Lines 182-187 may be more useful in line 165

Line 188: please state that SPSS was used in the first sentence, prior to stating a t-test was conducted

Can you please state how data is presented (e.g. mean and SD), and how effect sizes were calculated

Results:

Lines 198-200. Again this sentence is difficult to follow as a reader. Are you just repeating what you have mentioned in the methods section? Please be very clear and specific about the time (i.e. month/year), number and ages of children, sex etc that you are referring to. I would delete lines 198-200

Line 199: insert ‘the’ before subsample

Line 201. Please define ‘groups’

Line 205: please subscript the degrees of freedom

Line 208: can you please provide a citation to support his

Table 1: can you please removed the borders in the middle of the table, and only include borders at the top and bottom. Can you please state what you mean by average (was this the mean). Please include the mean and SD in one column only. Please include the minimum and maximum in once column only. Is there a reason why you are reporting both min-max and mean (SD)? Please use the SI units for age (i.e. y)

Line 215: when you state sig more PA. Do you mean MVPA was higher at age 11 compared to age 14? Or are you talking about total EE? Please format the parentheses appropriately and include the ES in the same parenthesis. Is this eta squared ES?

Please include ES for all analyses

Please be consistent with your terminology. You state on line 217 the ‘difference in MVPA’. Whereas again on line 218 you refer to ‘more active’. As you are not measuring overall PA, but looking at MVPA minutes, please use MVPA consistently, and remove any reference to ‘more physical activity’. I cannot see any reference to total EE. Is this what you mean by ‘more physically active’ – please use consistent terminology relevant to your outcome measures

Line 221 – 222.: please delete this sentence. Please make the results concise and clear. You have already described the analyses conducted in the analyses section, so you do not need to repeat again how the analyses was conducted

Line 222: Delete independent sample t test, and just sate what was found

Line 227: p<0.5 would not be significant. Is this a typing error?

Lines 227-229: can you please include the eta square value in the same parenthesis

Line 232: please delete

Discussion

Line 237: please delete the word critical, as we cannot determine causal inference that it is indeed critical. By PA do you mean MVPA or TEE?

Line 239: please delete the space between 7 and %. Can you please discuses the implications of an average of 40 min reduction in MVPA for girls aged 11 – 14, and a 10 min reduction for boys. Please discuss those who had very low MVPA (I.E. 24 or 18 min). What % of 11 and 14 year old boys and girls met the PA recommendations for Slovenia? The SD are rather large – suggesting a great deal of variance in the PA levels. Can you postulate why this is. Do you have any information on which schools these children came from, what areas they live in, their socioeconomic background etc?

Lines 264-269: This sentence is very long. Can you please re-word to make it easier for the reader to follow, as numerous thoughts and points are raised in this sentence.

Line 273: what do you mean by more efficient than girls of the same age in 1990?

Lines 276-277. I am not sure you can make such a confident statement given you did not directly measure any changes in physical fitness

Lines 278-280: Can you please reword this sentence. I do not understand what you mean by ‘the question arises as to how big a drop in PA levels from childhood does influence the physical efficiency of children when they reach adolescence’. What do you mean by efficiency? And children compared to adolescence? You only measured MVPA and total EE in 11 and 14 year olds.

Lines 281-284: as you did not directly measure PA and PE lessons, or support from friends etc, can you please reword/temper these sentences and relate directly to your findings.

Overall, the discussion needs some work in terms of the flow of sentences, and the tempering/relevance of the findings (see comments above on reporting total EE, discussing if differences are meaningful, reporting % of children that met PA guidelines etc). You cannot make any causal inference for some of the points you make (with regard to PE lesson, maturity etc), as you only looked at 7 d of MVPA at age 11 and age 14. Please ensure the discussion only directly relates to your findings. And any postulations are interpreted with caution.

Line 294-295. Please reword. It is not clear that you are discussing the wear time of the SWA in the present study compared to previous research.

Lines 300-301. Can you make this sentence more concise. You mention consistent measurement equipment and criteria separately, objective EE assessment. Are you simply referring to using the SWA with the PHV. Please use specific and consistent terminology, and do not overstate the measurements. Please provide the reference for the SWA being valid and reliable for MVPA and EE use over 7 d in children. With regards to the limitations, please also acknowledge only analyzing the PA for one week. You do not mention any data collection in terms of PE lesson, outside school PA or exercise, illness etc which may have been important for interpreting the findings

Line 321. Please insert pre-adolescents. Please replace similarly with similar

Line 323-324. You cannot determine causal inference from puberty (i..e PHV) and MVPA. It was only inserted as the covariate. It may not have been the reason why girls decreased their MVPA. I would suggest that future research needs to explore (quantitatively and qualitatively) the reasons why girls are decreasing their MVPA in Slovenia.

Lines 326 – 330. Can you please temper and/or remove these sentences. As they are not measured or related to the outcomes in your study. Please ensure the conclusion is relevant to the discussion and results

Reviewer #2: I was asked to read an interesting manuscript titled “Decline of physical activity from childhood to adolescence: A 3-year longitudinal study” by Dr. Sember et al. The study investigated the changes in physical activity during 3y follow-up period in adolescents and showed interestingly that MVPA declined in girls but not in boys.

General comments

Although the introduction describes important areas related to this study, it does not adequately describe the available evidence on the decline of physical activity from previous studies. The Authors also bring some ideas that maturation is important in study of changes in physical activity, but do not explain why and what is the evidence. Please revise the introduction to better cover previous evidence and to explain what is needed and what gaps this study fills.

The Authors used a physical activity monitor that was used continuously trough 24 hours. Why the Authors only study MVPA and not sedentary behaviour and sleep. That would strengthen the paper significantly.

Specific comments

L79-81. The children in Slovenia are one of the most active paediatric populations. Please define how this was measured.

L95-115. A lot of children dropped off the study How representative this sample was regarding available characteristics such as socioeconomic status, body composition and size (e.g. BMI percentile/sd-score, body fat percentage). Please define these information here and not just in the results.

L127-128. Can the Authors define how SWA was validated. Was it validated against doubly labelled water? What was the agreement between methods. Please expand this information.

L134-135. Please comment the epoch length. Can the Authors show that 60 s epoch length can capture physical activity level reliably. Some studies have shown that 60 s epoch is not able to capture true levels of moderate and vigorous physical activity (1).

L158-163. The Authors need to put more emphasis in the validity of their physical activity data. For example, it is important to describe whether adult derived MET definition (3.5 mL/kg/min) was used or was more appropriate definition used. There are strong data suggesting that adult derived METs are not suitable to used in children (2). Furthermore, METs can produce a significant bias in physical activity assessment (3) and fixed MET thresholds for moderate and vigorous physical activity underestimate true prevalence of physical activity in overweigh and low fit individuals (4). Therefore, I suggest that the Authors carefully describe the procedure used in the study, consider their effect on the results, and highlight these in the limitations.

It seems that the Authors have data on 20 metre shuttle run test. Although it is not the most valid method to assess cardiorespiratory fitness especially during puberty, it could be used to assess maximal endurance capacity in adolescents. Can the Authors use those results to individually calibrate physical activity intensity? This would be important next step in physical activity research.

Some of these limitations are partly covered in the limitations section, but these needs to be expanded.

L163-165. Please describe which formula was used to calculate maturity offset? Mirwald or Moore? Please also describe the whole formula and its validity in this age group.

L182-183. Please describe Mirwald method earlier. Please also note that age at peak height velocity is not equal to onset of puberty which is mostly assessed as transition from stage 1 to stage 2 in stages described by Tanner. Please revise the terminology accordingly.

L192-194. How maturity was used in the model as covariate? It was a bit unclear to me was it only baseline maturity or change in maturity. It is important also to control changes in maturity because at any age children and adolescents mature at different rates.

L193-195. It not clear here whether time x sex interaction were studied or how data was in fact analysed. A figure of results could make it clearer and show the trend of physical activity level and interactions in boys and girls.

L216. Please describe how ES was defined.

L126-232. Does this mean that the results did not change when maturity was adjusted for? It is still a bit unclear whether only baseline maturity was used as a covariate. It would be important to know whether larger changes in maturity (i.e. faster rate of maturation) are related to for example larger decline in physical activity especially in girls. Furthermore, be also aware when interpreting the data using METs that changes in body composition during pubertal development are different in males and females with increased body adiposity in females and decreased adiposity in males. These changes may have an influence on MET-based estimates of physical activity as MET itself is adiposity confounded metric.

L237-239. Although merely speculative, is it possible that the decline of physical activity in girls is just because of increasing adiposity as suggested by Kujala et al. (4). Thus, are the same fixed intensity thresholds valid in assessment of physical activity intensity especially during youth when body size and composition as well as physical fitness change remarkably. Please consider these issues at least in limitations.

L248-258. As the Authors state school is probably important factor influencing physical activity and sedentary time in youth. I suggest that the Authors consider also biological explanations explained for example in the article by Eisenmann and Wickel (5).

L262-264. The Authors state that there were no differences in physical activity at the age of 11 and 14 after adjustment for maturity. I was wondering that wasn’t this the case also without the adjustment. Please clarify. Please also consider my other comments on maturity.

L271-274. Please describe what the Authors mean by physical efficiency.

**********

6. 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 #2: Yes: Eero Haapala

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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.

Submitted filename: PLOS one 3 year PA review Sep 2019.docx

Click here for additional data file.

Submitted filename: review comments.docx

Click here for additional data file.

16 Nov 2019

REVIEWER 1

We would like to thank you for your thorough reading and very useful suggestions which we tried to incorporate in the revised version to our best abilities. It was especially useful to build on your in-depth understanding of growth and maturation processes and correct our inconsistencies and ambiguities. We are certain that this helped us improve our work considerably and hope that you will find the revised version as a considerable improvement of our original submission.

Abstract

• Line 17: please change ‘The study’ to ‘This study’

We changed it to ‘This study’.

• Line 18: please change to ‘boys and girls aged 11 and 14’. Please state n = for each age. From this sentence, it is not clear if the 11 year olds and 14 year olds were the same children (i.e. you analyzed their PA at aged 11, and then followed up 3 years later by analyzing their PA levels again at aged 14). Please make this clear to the reader. Also, can you please state how long they wore the Bodymedia for (i.e. how many days), and if the measurements were taken at the same time of year (please provide month and date)

We revised the text according to your suggestions. We changed to ‘boys and girls aged 11 and 14’ and we stated n = for each age. We also clarified that we measured the cohort of same children. We also made it clear, that children wore the Bodymedia armband for 7 days in October 2013 and October 2016.

• Line 20-21: It is not clear about when PA was measured, and what you mean by subsample at the age 11, and final subsample at age 11 and 14. Can you please re-word to clarify this for the reader

We revised the sentence according to your suggestions.

• Line 21: please use abbreviation (MVPA)

We followed your suggestion to make the abstract more comprehensible, although the instructions on the PlosOne page are noting that “abstracts should not include citations and abbreviations, if possible”.

• Line 22: please clarify what you mean by ‘longitudinally measured’ and provide n =. What ages are you referring to? Both 11 and 14 years? Or just 11 years? And how did you compare?

We revised the sentence according to your suggestions and made clear that the same cohort was measured at ages 11 and 14. Due to space restrictions we could not provide the details on the measured physical fitness and somatic components in the abstract but this is described in details in the text.

• Line 23: please add ‘a’ before representative, and delete ‘the’ before age 11

We revised the sentence according to your suggestions.

• Line 24: please use abbreviation (MVPA)

We revised the sentence according to your sugestions.

• Line 24 – 24: compared to what?

We revised the sentence and made clear that we compared the average MVPA between ages 11 and 14.

• Lines 24-26: please provide p values. The results section is not clear for the reader. You have ES, the eta squared symbol, and p values. Can you please provide a concise statement about the results, and use consistent reporting values (i.e. p values, ES, t values, f ratios etc.)

We revised the sentence. We agree with your advice to make reporting consistent throughout the text. We explained use of different ES in the methods section.

• Line 28: please use abbreviation (MVPA)

We revised the sentence according to your suggestion.

• Line 28-29: please use abbreviation (MVPA)

We revised the sentence according to your suggestion.

• Lines 30-32: The conclusions do not match the aim or findings. Can you please reword to include an appropriate conclusion based on the findings, as you do not directly measure schoolwork, participation in PE lessons, or extracurricular PA/PA outside the school environment

We revised the sentence with the focus on the findings.

Introduction

• Line 35: please delete the full stop and ‘it’, and replace with ‘and’ is one of the

Corrected.

• Line 41: please add ‘the’ before adult

Corrected.

• Line 42: please insert a comma before which

Corrected.

• Line 43: please write World Health Organization in full before abbreviating

Corrected.

• Line 48: ‘suitable contents’ is not clear for the reader. Can you please define

We revised the sentence and describe clearly what was included in the guidelines.

• Lines 49 – 52: is there any evidence that the guidelines should differentiate between childhood and adolescence? Could you please clarify what you mean by childhood and adolescence (i.e. provide the ages in years). Is there any evidence that you can provide to support increased sedentary behavior in adolescence?

We are grateful for this comment as it points to an important rationale of this study, which concerns the increase of sedentary time and decline of MVPA in early adolescence. We provided additional references, reporting the increasingly sedentary behavior in early adolescents. We are not aware of any existing evidence of guidelines that are taking into account the biological maturity of children. Guideliness of some countries (Canada, Finland, Australia) are differentiating between different age groups but they do not provide any evidence for the rationale of differentiation. Following your further comments regarding terms childhood and adolescence we defined our subjects as pre- and early-adolescents. We defined pre- and early-adolescents in methods (sample) chapter. We used the same terminology pre-adolescents, early-adolescents and adolescents throughout the whole manuscript. We changed the title of our study to: “Decline of physical activity in early-adolescence: A 3-year cohort study”

• Lines 52-54: can you please provide the specific ages of childhood and adolescence (see comment above), and also provide evidence to support why it is important to analyse these changes. What does the literature state in terms of the transition from childhood and adolescence? How does this impact PA in adulthood etc.

We appreciate your insightful comment regarding terminology. We defined pre- and early-adolescents in the methods (sample) chapter. We revised this part of the text.

• Lines 54-56: I am not sure that ‘the matter is further complicated’ in relation to your study, as you are not comparing children from different countries, only Slovenia. So I would delete ‘the matter is further complicated’. You also use the word ‘different’ three times in this sentence. Could you please reword to allow the sentence to flow better for the reader

We revised the sentence according to your suggestions.

• Line 59: please provide evidence that the age groups you are referring to are the ‘most problematic’

We changed the paragraph and did not describe different age group as more or less problematic but instead characterized the period of early-adolescence as the most intensive period in regard of the most intensive period of PA behavioral change. We also provided evidence citing additional relevant sources:

REFERENCES

Currie, C., Molcho, M., Boyce, W., Holstein, B., Torsheim, T., & Richter, M. (2008). Researching health inequalities in adolescents: the development of the Health Behaviour in School-Aged Children (HBSC) family affluence scale. Social science & medicine, 66(6), 1429-1436.

Jiménez-Pavón D, Kelly J, Reilly JJ. Associations between objectively measured habitual physical activity and adiposity in children and adolescents: Systematic review. Int J Pediatr Obes. 2010;5: 3–18.

Straatmann, V. S., Oliveira, A. J., Rostila, M., & Lopes, C. S. (2016). Changes in physical activity and screen time related to psychological well-being in early adolescence: findings from longitudinal study ELANA. BMC public health, 16(1), 977.

Twisk JWR. Physical activity guidelines for children and adolescents. Sport Med. 2001;31: 617–627.

• Line 63 delete ‘the’ before recent

Corrected.

• Paragraph two (lines 60 – 78): I am not sure on the relevance of the paragraph to your study. You discuss advantages and limitations of questionnaires, DLW and accelerometers (none of which are utilized in your study). But you do not mention wearable technologies. And then the paragraph suddenly finishes, and moves on to discuss PA in Slovenia, which does not flow. As you are not comparing these methods (i.e. questionnaires, DLW or accelerometers) in your study I would remove this paragraph, and include pertinent and relevant information on wearable technologies and the use of the Body Media Sense wear armband to assess PA in children

We agree with your observation and thoroughly revised the paragraph. We also included information on wearable technologies and use of the BodyMedia SenseWear armband to assess PA in children according to your suggestion.

• Line 79: please specify the ages of the school children

We specified the age of children which is 6 to 17 years of age.

• Lines 81-86: Here you define preadolescents, and puberty. However, in the first paragraph (lines 50-51) you talk about the difference between childhood and adolescence. As you are only looking at PA in children aged 11 and 14, I do not think you can refer to ‘issues/problems’ between childhood and adolescence (in the first paragraph), as you are not actually measuring this in your study. The world health organization defines adolescence as between the ages of 10 and 19. Early adolescence (i.e. puberty) may be defined as ages 10-14. I would suggest therefore, that you temper your introduction (particularly the first paragraph), as you are not really examining differences in PA between childhood and adolescence, but looking at the change in PA during early adolescence (i.e. puberty)

We defined pre- and early-adolescents in the methods (sample) chapter. We used the same terminology pre-adolescents, early-adolescents and adolescents throughout the whole manuscript. We tempered our introduction according to your suggestions.

• Line 81-82: please see comment above. Are you sure that 15-18 y is ‘preadolescent’? Or is this age group mid adolescence? My understanding is that 10-14 y is ‘preadolescent’.

The [15-18] in the square brackets referred to references, not age groups but still had the potential to confuse the readers. The numeration of references is now changed and this ambiguity resolved.

• Lines 83-91: This information would be better suited to the methodology section. It is also not clear from these sentences exactly how you will control for biological maturity. What do you mean by discriminating factor? How will you control for this in the analyses? Please state this clearly in the methodology section only (i.e. PHV) was entered as a covariate

We deleted this part from introduction part and we included the information in methods section under data analysis. We deleted the phrase “discriminating factor” since it was not used appropriately. At the end of the methods part (under data analysis) we described how we controlled for “biological maturity” – it was used as covariate.

• Can you please provide a hypothesis. And also state how long you will measure PA for. You mention ‘longitudinally’. But do you just mean you will analyze their PA once when they are 11, and once again when they are 14. How long will you analyse PA for?

We provided a hypothesis. We described the measurements and statistical analyses in more details in the methods section.

Methods

• Line 96. What is ACDSi. Please define this abbreviation

We defined the abbreviation and revised the sentence.

• Line 98. What do you mean by ‘multiple location approach’. Was their random stratified sampling from each area of the country?

We changed “multiple location approach” to “sentinel approach” which is more appropriate to use in the context of our study. We provided more detailed description of the sampling.

• Line 103. How were the subsample of n = 160 chosen? Was their random stratified sampling of the 385 children eligible?

Of the whole sample of 11-year-olds who were invited to wear SWA, only n=160 children returned the informed written consent from parents to wear the SWA for the whole week. We were not able to use random stratified sampling without the risk of seriously reducing the sample size at the time of measurements.

• Line 107: please delete of before 14

Deleted.

• Line 108-109: how did you define sufficient wear time?

Sufficient wear time is defined in methods section. Following recommendations for measuring PA measuring with multisensory devices and accelerometers are ranging from 3 to 10 days, where 7 days might be reasonable standard for all ages (Cain et al., 2013). Definition of valid day is typically defined by a minimum number of wearing hours but can be determined in other ways such as calculating study-specific ratios (e.g. 70/80 rule, where valid day is 80% of a time period defined by 70% of the sample having data) (Cattelier et al., 2005). From the sample of 160 schoolchildren included for PA measurements, 121 children wore accelerometer for 80% of the day. Three years after, from 160 children 70% of children wore monitor for more than 80% of time. We decided to additionally tighten our inclusion criteria and included only children who wore the monitor for at least 90% of the day at age 11 and three years after. This is why we only included 50 children, who wore the monitor for 90% of time. This is how we ensured real longitudinal design with sufficient wear time and reduced the under- or overestimation of PA due to non-wear time.

REFERENCES

Cain, K. L., Sallis, J. F., Conway, T. L., Van Dyck, D., & Calhoon, L. (2013). Using accelerometers in youth physical activity studies: a review of methods. Journal of Physical Activity and Health, 10(3), 437-450.

Catellier, d. j., Hannan, p. j., Murray, d. m., Addy, c. l., Conway, t. l., Yang, s., & Rice, j. C. (2005). Imputation of missing data when measuring physical activity by accelerometry. Medicine and science in sports and exercise, 37(11 Suppl), S555.

Sallis, J. F., Buono, M. J., Roby, J. J., Micale, F. G., & Nelson, J. A. (1993). Seven-day recall and other physical activity self-reports in children and adolescents. Medicine and science in sports and exercise, 25(1), 99-108.

Trost, S. G., Pate, R. R., Freedson, P. S., Sallis, J. F., & Taylor, W. C. (2000). Using objective physical activity measures with youth: how many days of monitoring are needed?. Medicine & Science in Sports & Exercise, 32(2), 426.

• Line 128: delete ‘also’ before in

Deleted.

• Line 129: why was a 7 d period chosen? Due to logistical reasons (i.e. amount of kit)? Does 7 d provide a reliable and valid measure of PA in these children?

Sufficient wear time is defined in methods section. The recommendations for PA measuring with multisensory devices and accelerometers are ranging from 3 to 10 days, where 5 to 7 days are considered a reasonable standard for all ages (Cain et al., 2013; Sallis et al., 1993; Trost et al., 2000). Seven days provide reliable and valid measure of PA in these children.

REFERENCES

Cain, K. L., Sallis, J. F., Conway, T. L., Van Dyck, D., & Calhoon, L. (2013). Using accelerometers in youth physical activity studies: a review of methods. Journal of Physical Activity and Health, 10(3), 437-450.

Sallis, J. F., Buono, M. J., Roby, J. J., Micale, F. G., & Nelson, J. A. (1993). Seven-day recall and other physical activity self-reports in children and adolescents. Medicine and science in sports and exercise, 25(1), 99-108.

Trost, S. G., Pate, R. R., Freedson, P. S., Sallis, J. F., & Taylor, W. C. (2000). Using objective physical activity measures with youth: how many days of monitoring are needed?. Medicine & Science in Sports & Exercise, 32(2), 426.

• Lines 132-134. What is this cut off based on? Why 5 d? and why > 90%?

We based our approach on the consensus for measuring PA among the researchers in the field (Esliger et al., 2005). The recommendations of measuring are ranging from 3 to 7 days, and for school-aged children at least one weekend day is recomended (Esliger et al., 2005; Rowlands et al., 2007). The recommendations state that the analysis should include at least 5 consecutive days. We decided for more rigorous inclusion criteria regarding wear-time (5d and >90%), because we wanted to get a more realistic picture of the whole day physical activity.

REFERENCES

Esliger, D. W., Copeland, J. L., Barnes, J. D., & Tremblay, M. S. (2005). Standardizing and optimizing the use of accelerometer data for free-living physical activity monitoring. Journal of Physical Activity and Health, 2(3), 366-383.

Rowlands, A. V., & Eston, R. G. (2007). The measurement and interpretation of children’s physical activity. Journal of sports science & medicine, 6(3), 270.

• Line 148: To have worn the devices for 7 d should the collection not have bene the following Wednesday? Or am I missing something

Children wore the devices from Wednesday morning untill Tuesday evening (6 days through daytime and 6 nights). From Tuesday to Wednesday we needed to change the batteries, collect the data, clean the monitors and prepare them for the children from another school for the following day (Wednesday). Since we looked only for full 5 consecutive days and did not analyse sleep patterns, the methodology did not affect the final results.

• Lines 166 – 172. It is a little difficult to follow as a reader, who did not conduct the study, what you mean by first to second round of PA. Is this from October 2013 (i.e. aged 11), to October 2016 (i.e. aged 14)? What do you mean ‘final subsample’, and ‘initial subsample’, and ‘total sample’. Please be very clear and specific about the time (i.e. month/year), number and ages of children, sex etc. that you are referring to

Thank you for your remark. We directed readers to our flowchart (Fig. 1) for easier understanding and described the flow of the analysis in more detail.

• Line 171: please insert ‘the’ before following

Inserted.

• Line 181: please state which variables, rather than just ‘multiple variables’

We listed all the variables.

• Line 182: provide n for ‘total sample’, provide n = for subsample, provide n = for subsample at age 11. I found it difficult to read this sentence, and to follow exactly which samples/children you are referring to.

We revised this part and also redirected the readers to Fig.1 (flowchart).

• Lines 182-187 may be more useful in line 165

We followed your suggestion and moved this part in upper section of the manuscript.

• Line 188: please state that SPSS was used in the first sentence, prior to stating a t-test was conducted

We rephrased and moved this sentence at the beginning of the paragraph.

• Can you please state how data is presented (e.g. mean and SD), and how effect sizes were calculated

We added a statement on the presentation of the data and calculation of ES according to your suggestion.

Results

• Lines 198-200. Again this sentence is difficult to follow as a reader. Are you just repeating what you have mentioned in the methods section? Please be very clear and specific about the time (i.e. month/year), number and ages of children, sex etc that you are referring to. I would delete lines 198-200

We revised the text according to your suggestions.

• Line 199: insert ‘the’ before subsample

We revised this part of the text.

• Line 201. Please define ‘groups’

We defined the groups and redirected reader to flowchart (Fig.1):

• Line 205: please subscript the degrees of freedom

Since the journal does not have specific rules on how to report the degrees of freedom we used the standard reporting (t(df)=x.xx, p=x.xxx).

• Line 208: can you please provide a citation to support his

We have revised the sentence since we also changed the analysis at age 11 which showed no statistical differences in girls who were included/excluded from the analysis, onlyu one difference in boys. We were, however, unable to find any evidence for flexibility to be linked to the level of PA. On the contrary, the existing evidence shows that obese children who are less physically active often have greater flexibility due to their low muscular tonus. We, thus could not provide any citation in this case but decided not to discuss the flexibility-PA relation since it is not the focus of the paper.

• Table 1: can you please removed the borders in the middle of the table, and only include borders at the top and bottom. Can you please state what you mean by average (was this the mean). Please include the mean and SD in one column only. Please include the minimum and maximum in once column only. Is there a reason why you are reporting both min-max and mean (SD)? Please use the SI units for age (i.e. y)

We designed our table (which is now S5 Table) according to the PlosOne instructions. By “average” we meant mean. We changed it to mean in the manuscript. We combined mean and standard deviation in one column and minimum and maximum in a separate one. We reported min and max, to give more precise information to reader about children’s MVPA duration. We also deleted a part of the table with energy expenditure, because all further analysis was focused only on MVPA (min). We used SI units. Instead of Table 1 is now in manuscript Fig 2.

• Line 215: when you state sig more PA. Do you mean MVPA was higher at age 11 compared to age 14? Or are you talking about total EE? Please format the parentheses appropriately and include the ES in the same parenthesis. Is this eta squared ES?

We removed a part of the table with energy expenditure results (now S5 Table). We meant MVPA was higher at age 11 compared to age 14; therefore we reworded the sentence (below). We used Cohen’s d and reported results accordingly.

• Please include ES for all analyses

We included ES for all the analyses according to your suggestion.

• Please be consistent with your terminology. You state on line 217 the ‘difference in MVPA’. Whereas again on line 218 you refer to ‘more active’. As you are not measuring overall PA, but looking at MVPA minutes, please use MVPA consistently, and remove any reference to ‘more physical activity’. I cannot see any reference to total EE. Is this what you mean by ‘more physically active’ – please use consistent terminology relevant to your outcome measures

We revised all sentences according to your observation. Since we analyze only MVPA we included only MVPA in Table 1 (now S5 Table) and reported results for MVPA accordingly.

• Line 221 – 222.: please delete this sentence. Please make the results concise and clear. You have already described the analyses conducted in the analyses section, so you do not need to repeat again how the analyses was conducted

We deleted tis part.

• Line 222: Delete independent sample t test, and just sate what was found

We deleted the first part of the sentence and reported only the results.

• Line 227: p<0.5 would not be significant. Is this a typing error?

Thank you for noticing this typing error and we changed it to “p<0.05”.

• Lines 227-229: can you please include the eta square value in the same parenthesis

We included eta square value in the same parenthesis.

• Line 232: please delete

We agree with the comment and we deleted the line accordingly.

Discussion

• Line 237: please delete the word critical, as we cannot determine causal inference that it is indeed critical. By PA do you mean MVPA or TEE?

We replaced word “critical” with “visible”. When talking about PA and results of our study, we changed everything to “MVPA”.

By PA we meant MVPA.

• Line 239: please delete the space between 7 and %.

We deleted the space.

• Can you please discuses the implications of an average of 40 min reduction in MVPA for girls aged 11 – 14, and a 10 min reduction for boys.

We did not control MVPA with any environmental variables and other PA determinants, therefore we cannot be confident about the cause-effect relationship. Future studies should continue prioritizing longitudinal methodologies with bigger implications on gender differences in MVPA, including information about other PA determinants (environment, socioeconomic status, parental education…) (mentioned in conclusion part).

• Please discuss those who had very low MVPA (I.E. 24 or 18 min). What % of 11 and 14 year old boys and girls met the PA recommendations for Slovenia?

The very low data belong to a girl who is obese. We rearranged this part of discussion and we provided data for children meeting recommendations from longitudinal sample and separately for children at age 11 and 14.

• The SD are rather large – suggesting a great deal of variance in the PA levels. Can you postulate why this is. Do you have any information on which schools these children came from, what areas they live in, their socioeconomic background etc?

We agree with the observation and we are aware of the large variances in the PA levels, but the results are in line with other results in Slovenia (Jurak et al., 2015; Kovač, Strel, Jurak, Leskošek, & Dremelj, 2013). Slovenia has a public school system which is very homogeneous in terms of teachers, curricula, infrastructure, quality of PE, etc. and the school environment does not present a discriminating factor. We have limited availability of SES data but our other analyses of this data showed no effect of SES on physical fitness. We are currently working on the geographical data (green spaces, playgrounds, roads…) but since these analyses are extremely complex we do not expect to have any useful data for the next two years.

REFERENCES

Jurak, G., Sorič, M., Starc, G., Kovač, M., MiŠigoj-Duraković, M., Borer, K., & Strel, J. (2015). School day and weekend patterns of physical activity in urban 11-year-olds: A cross-cultural comparison. American Journal of Human Biology, 27(2), 192–200. https://doi.org/10.1002/ajhb.22637

Kovač, M., Strel, J., Jurak, G., Leskošek, B., & Dremelj, S. (2013). Physical Activity, Physical Fitness Levels, Daily Energy Intake and Some Eating Habits of 11-Year-Old Children. , (1), 127–139.

• Lines 264-269: This sentence is very long. Can you please re-word to make it easier for the reader to follow, as numerous thoughts and points are raised in this sentence.

We revised this part.

• Line 273: what do you mean by more efficient than girls of the same age in 1990?

We substituted “physical efficiency” with “physical fitness” and changed the sentences accordingly. We use the term physically efficient for children who show high levels of physical fitness.

• Lines 276-277. I am not sure you can make such a confident statement given you did not directly measure any changes in physical fitness

We now included also supplementary tables S3 and S3 which include the results of physical fitness tests but we omitted this statement from the text.

• Lines 278-280: Can you please reword this sentence. I do not understand what you mean by ‘the question arises as to how big a drop in PA levels from childhood does influence the physical efficiency of children when they reach adolescence’. What do you mean by efficiency? And children compared to adolescence? You only measured MVPA and total EE in 11 and 14 year olds.

We changed “physical efficiency” to “physical fitness” throughout the whole manuscript. We added references for decline of PA in these ages and we deleted the last sentence/question, since we do not want to open a new, extensive chapter of physical fitness and since it is not the aim of present study. We explained the use of “children and adolescents” above.

• Lines 281-284: as you did not directly measure PA and PE lessons, or support from friends etc, can you please reword/temper these sentences and relate directly to your findings. Overall, the discussion needs some work in terms of the flow of sentences, and the tempering/relevance of the findings (see comments above on reporting total EE, discussing if differences are meaningful, reporting % of children that met PA guidelines etc). You cannot make any causal inference for some of the points you make (with regard to PE lesson, maturity etc.), as you only looked at 7 d of MVPA at age 11 and age 14. Please ensure the discussion only directly relates to your findings. And any postulations are interpreted with caution.

We omitted the unrelated points from the text.

• Line 294-295. Please reword. It is not clear that you are discussing the wear time of the SWA in the present study compared to previous research.

We revised the sentence.

• Lines 300-301. Can you make this sentence more concise. You mention consistent measurement equipment and criteria separately, objective EE assessment. Are you simply referring to using the SWA with the PHV. Please use specific and consistent terminology, and do not overstate the measurements.

We revised the text according to your suggestions.

• Please provide the reference for the SWA being valid and reliable for MVPA and EE use over 7 d in children. With regards to the limitations, please also acknowledge only analyzing the PA for one week. You do not mention any data collection in terms of PE lesson, outside school PA or exercise, illness etc which may have been important for interpreting the findings

We provided the references that proved SWA to be valid and reliable for assessment of MVPA in children and adolescents in introduction and methods part. We also acknowledged in the limitation of measuring PA only for one week. As stated before, Slovenia has a very uniform public educational system and curriculum, and any analyses of PE lessons would not contribute any additional value to the analyses. This paper was focused on the trends of decline and possible effects of maturation and did not control for other cofounders that might influence the results. This is why we did not mention other data collection.

• Line 321. Please insert pre-adolescents. Please replace similarly with similar

We revised it accordingly to your comment.

• Line 323-324. You cannot determine causal inference from puberty (i..e PHV) and MVPA. It was only inserted as the covariate. It may not have been the reason why girls decreased their MVPA. I would suggest that future research needs to explore (quantitatively and qualitatively) the reasons why girls are decreasing their MVPA in Slovenia.

We entirely agree with your observation and have used it to emphasise the inability to ascertain maturation to be underlying reason for decline of PA.

• Lines 326 – 330. Can you please temper and/or remove these sentences. As they are not measured or related to the outcomes in your study. Please ensure the conclusion is relevant to the discussion and results

We deleted the mentioned statements according to your suggestion.

REVIEWER 2

We are very thankful for your very constructive and challenging comments, and especially for the excellent ideas regarding the adjustment of MET thresholds and controlling for body composition. It would be a real pleasure to working with you on our future research and publications because we rarely come across reviewers with such a constructive approach. We tried to address your suggestions to our (and our data) best ability. We believe your thorough reading, in-depth understanding and excellent suggestions helped us to improve the quality of this manuscript.

General comments

Although the introduction describes important areas related to this study, it does not adequately describe the available evidence on the decline of physical activity from previous studies. The Authors also bring some ideas that maturation is important in study of changes in physical activity, but do not explain why and what is the evidence. Please revise the introduction to better cover previous evidence and to explain what is needed and what gaps this study fills.

Thank you for this insight. We additionally described the available evidence on the decline of PA with longitudinal methodologies from previous studies in the introduction part. However, none of the identified longitudinal studies on PA considered the maturation aspect of participants.

The Authors used a physical activity monitor that was used continuously trough 24 hours. Why the Authors only study MVPA and not sedentary behaviour and sleep. That would strengthen the paper significantly.

We agree with your suggestion but we were reserved towards the analysis of sleep since SWA monitors have not proven to be the most reliable for sleep detection. We are currently working on another analysis of sedentariness in relation to school-related work and the use of screen technologies and decided not to replicate the same data in two different papers.

Specific comments

• L79-81. The children in Slovenia are one of the most active paediatric populations. Please define how this was measured.

We described that this was measured objectively and subjectively and we added additional references.

• L95-115. A lot of children dropped off the study How representative this sample was regarding available characteristics such as socioeconomic status, body composition and size (e.g. BMI percentile/sd-score, body fat percentage). Please define these information here and not just in the results.

Children did not actually droup out of the study, we mostly excluded their data from the analysis because of SWA malfunctions, incomplete data and rigorous demands for wear time (90% of the whole day). Nevertheless we followed the 70/80 rule for wear-time. From 160 schoolchildren, 121 children had complete data for inclusion in further analysis. Three years later some children changed school and did not want to wear SWA anymore. We described in more detail how the sample was constructed from the environmental point of view. In our previous researches in Slovenia SES never proved to be significantly related to either physical fitness or PA of children. We tried to make the physical characteristics of the sample as transparent as possible and we included additional supplemental tables S3 and S4 to show that the sample bias was negligible.

• L127-128. Can the Authors define how SWA was validated. Was it validated against doubly labelled water? What was the agreement between methods. Please expand this information.

SWA was validated against doubly labelled water in children with high correlations for all comparisons (>0.90). We expanded this information in manuscript and we also added additional references.

• L134-135. Please comment the epoch length. Can the Authors show that 60 s epoch length can capture physical activity level reliably. Some studies have shown that 60 s epoch is not able to capture true levels of moderate and vigorous physical activity (1).

We are aware of the importance of shorter epoch length, therefore we added one-minute epoch length to the limitations of our study. Nevertheless, we measured MVPA with same equipment and epoch length in both time points. Review articles are indicating that 60 second epoch length is still one of the most common used in youth PA studies, which is good in terms of comparisons. The actual reasons for not using shorter epoch are deriving from the SWA monitor itself. Namely, the manufacturer itself stated that the one-minute epoch algorithm is reliable but that using shorter epochs is not reliable. The second reason is that the use of shorter epochs would decrease battery life and use more memory which means that we would not be able to use the monitors for six consecutive days and this presented serious logisitc problem.

REFERENCE

Cain, K. L., Sallis, J. F., Conway, T. L., Van Dyck, D., & Calhoon, L. (2013). Using accelerometers in youth physical activity studies: a review of methods. Journal of Physical Activity and Health, 10(3), 437-450.

• L158-163. The Authors need to put more emphasis in the validity of their physical activity data. For example, it is important to describe whether adult derived MET definition (3.5 mL/kg/min) was used or was more appropriate definition used. There are strong data suggesting that adult derived METs are not suitable to used in children (2).

We are very thankful for raising these concerns. In the cited article (3), there is a statement that lean mass proportional measures of energy expenditure would enable a more truthful choice to assess physical activity. We used 4 MET as a threshold of MVPA which is a stricter criterion than the usual 3 MET threshold and we think we have been very conservative in this regard.

• Furthermore, METs can produce a significant bias in physical activity assessment (3) and fixed MET thresholds for moderate and vigorous physical activity underestimate true prevalence of physical activity in overweigh and low fit individuals (4). Therefore, I suggest that the Authors carefully describe the procedure used in the study, consider their effect on the results, and highlight these in the limitations.

We acknowledge that we (i.e. SWA software algorithm) used body mass (and not lean mass), hence we included this into limitations of the study. It is not possible to extract raw data to recalculate energy expenditure and control data for obesity or fitness level from the SWA data. Regarding the fixed MET thresholds, the SWA software uses variables such as sex, age, height and weight of a measured subject and has algorithms, adjusted to children.

• It seems that the Authors have data on 20 metre shuttle run test. Although it is not the most valid method to assess cardiorespiratory fitness especially during puberty, it could be used to assess maximal endurance capacity in adolescents. Can the Authors use those results to individually calibrate physical activity intensity? This would be important next step in physical activity research. Some of these limitations are partly covered in the limitations section, but these needs to be expanded.

This is a superb and inovative idea, and we would very much like to use this approach in the future, but we think that such an analysis deserves a separate and focused analysis.

• L163-165. Please describe which formula was used to calculate maturity offset? Mirwald or Moore? Please also describe the whole formula and its validity in this age group.

We revised this part of methods according ti your suggestions. We used and described the Mirwald's equation for maturity offset calculations and we also wrote both formulas – for boys and girls. Application of the used equations was recommended for boys between 10 – 18 years (Mirwald et al., 2012; see also Sherar, Mirwald, Baxter-Jones & Thomis, 2005). The same formulas have been used in studies of youth physical activity (Beets, Vogel, Forlaw, Pitetti, & Cardinal, 2006; Nurmi-Lawton et al., 2004; Weeks & Beck, 2012; Wickel, Eisenmann, & Welk, 2009) and of young athletes (Malina et al., 2012; Matthys, Vaeyens, Coelho e Silva, Lenoir, & Philippaerts, 2012; Sherar, Baxter-Jones, Faulkner, & Russell, 2007; Till, Cobley, O‘Hara, Chapman, & Cooke, 2010; Vandendriessche et al., 2012). Moreover, this method has been validated in an independent longitudinal samples in girls (Malina et al., 2006) and in boys Malina and Kozieł, 2014).

REFERENCES:

Beets, M. W., Vogel, R., Forlaw, L., Pitetti, K. H., & Cardinal, B. J. (2006). Social support and youth physical activity: the role of provider and type. American Journal of Health Behavior, 30(3), 278-289.

Mirwald, R. L., Baxter-Jones, A. D., Bailey, D. A., & Beunen, G. P. (2002). An assessment of maturity from anthropometric measurements. Medicine & science in sports & exercise, 34(4), 689-694.

Matthys, S. P. J., Vaeyens, R., Coelho-e-Silva, M. J., Lenoir, M., & Philippaerts, R. (2012). The contribution of growth and maturation in the functional capacity and skill performance of male adolescent handball players. International journal of sports medicine, 33(07), 543-549.

Malina, R. M., Claessens, A. L., Van, K. A., Thomis, M., Lefevre, J., Philippaerts, R., & Beunen, G. P. (2006). Maturity offset in gymnasts: application of a prediction equation. Medicine and science in sports and exercise, 38(7), 1342-1347.

Nurmi‐Lawton, J. A., Baxter‐Jones, A. D., Mirwald, R. L., Bishop, J. A., Taylor, P., Cooper, C., & New, S. A. (2004). Evidence of sustained skeletal benefits from impact‐loading exercise in young females: a 3‐year longitudinal study. Journal of Bone and Mineral Research, 19(2), 314-322.

Sherar, L. B., Mirwald, R. L., Baxter-Jones, A. D., & Thomis, M. (2005). Prediction of adult height using maturity-based cumulative height velocity curves. The Journal of pediatrics, 147(4), 508-514.

Sherar, L. B., Baxter-Jones, A. D., Faulkner, R. A., & Russell, K. W. (2007). Do physical maturity and birth date predict talent in male youth ice hockey players?. Journal of sports sciences, 25(8), 879-886.

Wickel, E. E., Eisenmann, J. C., & Welk, G. J. (2009). Maturity-related variation in moderate-to-vigorous physical activity among 9–14 year olds. Journal of Physical Activity and Health, 6(5), 597-605.

Till, K., Cobley, S., Wattie, N., O'Hara, J., Cooke, C., & Chapman, C. (2010). The prevalence, influential factors and mechanisms of relative age effects in UK Rugby League. Scandinavian journal of medicine & science in sports, 20(2), 320-329.

Vandendriessche, J. B., Vaeyens, R., Vandorpe, B., Lenoir, M., Lefevre, J., & Philippaerts, R. M. (2012). Biological maturation, morphology, fitness, and motor coordination as part of a selection strategy in the search for international youth soccer players (age 15–16 years). Journal of Sports Sciences, 30(15), 1695-1703.

• L182-183. Please describe Mirwald method earlier. Please also note that age at peak height velocity is not equal to onset of puberty which is mostly assessed as transition from stage 1 to stage 2 in stages described by Tanner. Please revise the terminology accordingly.

We described the Mirwald equation earlier in the chapter Methods (variables). We also revised the terminology according to your suggestions and used it consistently. We decided to use adolescent growth spurt instead of peak height velocity and acknowledged that adolescent growth spurt typically occurs approximately 2 years after the onset of puberty.

• L192-194. How maturity was used in the model as covariate? It was a bit unclear to me was it only baseline maturity or change in maturity. It is important also to control changes in maturity because at any age children and adolescents mature at different rates.

We used only baseline maturity. We were not able to control for the tempo of maturity since the use of Tanner's methods for assesment of maturity would result in a serious drop-out and jeopardised our entire study, which was an unacceptable risk since the ACDSi study is a study with the longest tradition in Slovenia. It is becoming extremely difficult to use Tanner's methods like we used to thirty years ago since children and also parents today find it as a serious breach of personal integrity. We tried to use the next best non-invasive measure and this meant we had to rely on an indicator, based on the leg length to body height ratio.

• L193-195. It not clear here whether time x sex interaction were studied or how data was in fact analysed. A figure of results could make it clearer and show the trend of physical activity level and interactions in boys and girls.

We agree with your observation therefore we present Fig 2 instead of Table 1 (now S5 Table) to graphicaly present the interaction.

• L216. Please describe how ES was defined.

We added a statement on how our data is presented (below) and at the end of the Data analysis section, we described how ES was calculated. We also calculated ES for all the analyses.

• L126-232. Does this mean that the results did not change when maturity was adjusted for? It is still a bit unclear whether only baseline maturity was used as a covariate. It would be important to know whether larger changes in maturity (i.e. faster rate of maturation) are related to for example larger decline in physical activity especially in girls. Furthermore, be also aware when interpreting the data using METs that changes in body composition during pubertal development are different in males and females with increased body adiposity in females and decreased adiposity in males. These changes may have an influence on MET-based estimates of physical activity as MET itself is adiposity confounded metric.

You are right on the target. The results, in fact did not change when maturity was adjusted for (we used baseline maturity as a covariate). This seems to indicate that changes in maturity might not be the underlying cause of PA decline in adolescence and that we should probably focus our attention more on environmantal factors. If this is in fact true, this would mean that we could develop and implement the adequate changes in the adolescent environment to prevent the decline. If the mechanism was underlied by biological development, thare would not be much we could do to tackle the problem. You expressed another terrific idea of adjusting energy expenditure with body composition, which is a problem that deserves a separate analysis and is currently ahead of time. In our view it would be extremely important ti exclude fat mass from the energy expenditure estimations in the future since energy is spent only in muscle cells. Fat mass is dead mass in this regard. Since METs that were calculated by SWA software were estimated from, gender, age weight and height, we wouldn't classify MET as an adiposity confounded metric since it does not differentiate between fat and lean mass.

• L237-239. Although merely speculative, is it possible that the decline of physical activity in girls is just because of increasing adiposity as suggested by Kujala et al. (4). Thus, are the same fixed intensity thresholds valid in assessment of physical activity intensity especially during youth when body size and composition as well as physical fitness change remarkably. Please consider these issues at least in limitations.

This is an interesting idea but we are not confident what is cause and effect here. It would be more logical to consider growing adiposity as an indicator of lower habitual PA. It makes perfect sense that different people experience the same intensity of PA differently and that the same intensity does not mean the same level of PA for different people. We, nevertheless, included your suggestions in the limitation part.

• L248-258. As the Authors state school is probably important factor influencing physical activity and sedentary time in youth. I suggest that the Authors consider also biological explanations explained for example in the article by Eisenmann and Wickel (5).

We included your suggestion for other biological factor affecting PA in the discussion part.

• L262-264. The Authors state that there were no differences in physical activity at the age of 11 and 14 after adjustment for maturity. I was wondering that wasn’t this the case also without the adjustment. Please clarify. Please also consider my other comments on maturity.

This part was revised and we emphasised that the differences were the same regardless the adjustment for maturity.

• L271-274. Please describe what the Authors mean by physical efficiency.

We replaced “physical efficiency” with “physical fitness” throughout the entire manuscript. Otherwise, we use physical efficiency as a term describing the level of physical fitness. Children who have high level of physical fitness are physically efficient.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

4 Feb 2020

Decline of physical activity in early adolescence: A 3-year cohort study

PONE-D-19-20032R1

Dear Dr. Starc,

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

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. 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 enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and 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.

With kind regards,

Kathryn L. Weston, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Please ensure that the minor typographical requests from Reviewer 1 are addressed in the final manuscript submission.

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 #2: All comments have been addressed

**********

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: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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: Yes

Reviewer #2: Yes

**********

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: Yes

Reviewer #2: Yes

**********

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 authors have done an excellent job in responding to the comments, and the manuscript has been greatly improved. I just have a few minor specific comments below

Abstract

Lines 28, 30, 31, 33: please provide p values

Methods

Line 113 please change N = to n = to be consistent throughout the paper

Results:

Line 263: here you report age as 12.01 ± 1.0. Prior to this you report your mean and SD with no space (i.e. 12.01±1.0). Please check the manuscript for consistency with spaces

Reviewer #2: (No Response)

**********

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 #2: No

11 Feb 2020

PONE-D-19-20032R1

Decline of physical activity in early adolescence: A 3-year cohort study

Dear Dr. Starc:

I am 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 notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, 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.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Kathryn L. Weston

Academic Editor

PLOS ONE