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Is the transition from primary to secondary school a risk factor for energy balance-related behaviours? A systematic review

Published online by Cambridge University Press:  04 May 2023

Helga Emke*
Affiliation:
Vrije Universiteit Amsterdam, Department of Health Sciences, Faculty of Science, De Boelelaan 1117 Amsterdam, The Netherlands Amsterdam Public Health Research Institute, Health Behaviour and Chronic Diseases and Methodology, Amsterdam, The Netherlands Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, The Netherlands
Coosje Dijkstra
Affiliation:
Vrije Universiteit Amsterdam, Department of Health Sciences, Faculty of Science, De Boelelaan 1117 Amsterdam, The Netherlands Amsterdam Public Health Research Institute, Health Behaviour and Chronic Diseases and Methodology, Amsterdam, The Netherlands
Stef Kremers
Affiliation:
Maastricht University Medical Centre, Department of Health Promotion, NUTRIM School of Nutrition and Translational Research in Metabolism, P. Debyelaan 25, Maastricht, The Netherlands
Mai JM Chinapaw
Affiliation:
Amsterdam Public Health Research Institute, Health Behaviour and Chronic Diseases and Methodology, Amsterdam, The Netherlands Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, The Netherlands
Teatske Altenburg
Affiliation:
Amsterdam Public Health Research Institute, Health Behaviour and Chronic Diseases and Methodology, Amsterdam, The Netherlands Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, The Netherlands
*
*Corresponding author: Email h.emke@amsterdamumc.nl
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Abstract

Objective:

The substantial changes in the physical and social environment during the transition from primary to secondary school may significantly impact adolescents’ energy balance-related behaviours (i.e. dietary behaviour, sedentary behaviour, sleep behaviour and physical activity (PA)). This is the first review systematically summarising evidence on changes in four energy balance-related behaviours of adolescents across the school transition from primary to secondary school.

Design:

For this systematic review, the electronic databases Embase, PsycINFO and SPORTDiscus were searched for relevant studies from inception to August 2021. PubMed was searched for relevant studies from inception to September 2022. Inclusion criteria were: (i) longitudinal studies reporting; (ii) one or more energy balance-related behaviours; and (iii) across the school transition, that is, with measurement(s) during both primary and secondary school.

Setting:

Transition from primary to secondary school

Participants:

Adolescents across the transition from primary to secondary school.

Results:

Thirty-four studies were eligible. We found strong evidence for an increase in sedentary time, moderate evidence for a decrease in fruit and vegetable consumption, and inconclusive evidence for a change in total, light, and moderate-to-vigorous PA, active transport, screen time, unhealthy snack consumption, and sugar-sweetened beverages consumption among adolescents across the school transition.

Conclusions:

During the transition from primary to secondary school, sedentary time and fruit and vegetable consumption tend to change unfavourably. More high-quality, longitudinal research is needed specifically on changes in energy balance-related behaviour across the school transition, especially regarding sleep behaviour. (Prospero registration: CRD42018084799)

Type
Review Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Nutrition Society

The number of adolescents with overweight and obesity is growing worldwide, and this public health problem is currently one of the most serious challenges of the twenty-first century(1). Adolescents with overweight and obesity are at increased risk of various lifestyle-related diseases later in life, including hypertension, hypercholesterolemia, diabetes mellitus type 2 and CVD(Reference Kemper, Post and Twisk2Reference Kemper, Post and Twisk4). Additionally, due to stigmatisation, adolescents with overweight and obesity tend to have lower self-esteem(Reference Tang-Péronard and Heitmann5), which can result in loneliness, sadness and tenseness(Reference Strauss6). It is therefore important to prevent overweight and obesity during childhood. Childhood overweight and obesity are caused by different behaviours that interact and influence each other(Reference Huang, Drewnowski and Kumanyika7), including an unhealthy diet, reduced sleep duration, low levels of physical activity (PA) and excessive screen time(Reference Kemper, Post and Twisk8Reference Kemper, Post and Twisk10). During adolescence, obesity prevalence is higher among 12–19-year-olds than 4–11-year-olds(Reference Kemper, Post and Twisk11,Reference Kemper, Post and Twisk12) . The transition from primary to secondary school might contribute to this increase in obesity prevalence.

Previous reviews on the age period of the transition showed that adolescents’ PA levels decreased, while their sedentary behaviour (SB) and screen time increased(Reference Kemper, Post and Twisk13,Reference Kemper, Post and Twisk14) . Other studies in the UK and the USA showed that dietary patterns from adolescents in secondary schools are more unfavourable (i.e. an increase in sugar-sweetened beverages (SSB) intake and a decrease in fruit and vegetable intake)(Reference Kemper, Post and Twisk15Reference Kemper, Post and Twisk17). In addition, when adolescents grow older they tend to increase their screen time(Reference Parent, Sanders and Forehand18), which is unfavourable since a systematic review showed that screen time was associated with reduced sleep duration and increased sleep problems among adolescents(Reference Hale and Guan10).

There are several explanations for the change towards unfavourable energy balance-related behaviours when adolescents transition from primary to secondary school. For example, when adolescents grow older changes in the biological regulatory processes occur that are known to cause a biological delay in the timing of sleep onset(Reference Bruce, Lunt and McDonagh19). Additionally, parents generally set less rules regarding, for example, screen time when their children grow older(Reference Ramirez, Norman and Rosenberg20). The transition in school environment also results in changes in intrapersonal factors and social and physical environmental factors(Reference Kemper, Post and Twisk21Reference Kemper, Post and Twisk24), including changes in sports facilities, academic expectations and self-judgement of PA skills(Reference Kemper, Post and Twisk23,Reference Kemper, Post and Twisk24) . Furthermore, adolescents experience more freedom and receive more pocket money that both enables them to buy high-energy foods and drinks(Reference Kemper, Post and Twisk25Reference Kemper, Post and Twisk27). On top of that, this period is associated with an increase in travel duration and adolescents experiencing social stress due to the school transition(Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk29) .

Currently, no systematic review studied dietary behaviour across the transition from primary to secondary school. Furthermore, no recent systematic review examined PA, SB, sleep behaviour and dietary behaviour during the school transition. A combined review is of interest because these behaviours are connected and influence each other, for example, more screen use leads to more unhealthy snacking, less PA and lower sleep quality(Reference Waterlander, Singh and Altenburg30). Therefore, this systematically review summarised the evidence on changes in four energy balance-related behaviours (i.e. PA, SB, sleep behaviour and dietary behaviour) of adolescents in the transition from primary to secondary school.

Methods

This systematic review was conducted following the PRISMA statement for reporting systematic reviews(Reference Page, McKenzie and Bossuyt31). The review protocol is registered in the International Prospective Register for Systematic Reviews (registration number CRD42018084799 at www.crd.york.ac.uk/prospero/).

Search strategy

The search strategy included terms related to PA, SB, sleep behaviour, and dietary behaviour and the transition from primary to secondary school. We searched for relevant studies in four electronic databases (PubMed, Embase, PsycINFO and SPORTDiscus) from inception until August 2021. In addition, we manually searched the reference lists of included studies for relevant studies.

Inclusion criteria

Studies were included if they had a longitudinal design and examined one or more energy balance-related behaviours across the transition from primary/elementary school (hereafter referred to as primary school) to secondary/middle school (hereafter referred to as secondary school), with at least one measurement in adolescents attending the final grades of primary school and one in the same adolescents attending the first grades of secondary school. Only full-text studies published in English in peer-reviewed journals were included.

Identification of relevant studies

First, one author (HE) performed the search in co-operation with a search specialist from the library of the Vrije Universiteit Amsterdam. Second, two authors independently checked potentially relevant studies by screening the titles and abstracts (HE and CD/TA); when abstracts were not available the studies were included for full-text screening. Third, two authors (HE and CD/TA) independently screened full-text studies to determine whether the inclusion criteria were met. Any discrepancies between the authors were resolved through discussion. A third reviewer (TA/CD) was consulted when consensus could not be reached.

Data extraction

Two authors (HE and CD/TA) independently extracted data from all included studies, using a structured data extraction form. Information was extracted regarding participant characteristics (i.e. ethnicity and gender), study characteristics (i.e. type of energy balance-related behaviour, length of follow-up and measurement of energy balance-related behaviours) and the study results. To reach consensus for a uniform data extraction procedure, two authors (HE and CD/TA) independently extracted data from the first three studies, before continuing with all other included studies. Discrepancies were resolved through discussion. A third reviewer (TA/CD) was consulted when consensus could not be reached.

Quality assessment

To assess the methodological quality of the included studies, we used the fourteen-item National Institute of Health (NIH) quality assessment tool for Observational Cohort and Cross-Sectional Studies(32). We included the following quality items: having a clearly stated research question, a clearly specified study population, a representative sample, non-biased recruitment of subjects, justification of sample size, valid and reliable assessment tool, an adequate follow-up rate, and statistical analysis adjusted for potential confounders (for the details see Table 1). Three of the included items were informative, and only the five validity/precision items were included in the quality score(Reference Chinapaw, Proper and Brug33). Six quality items of the tool were not applicable for our research question and study design and were therefore excluded, including exposure of interest, sufficient time frame, different levels of exposure, exposure measures and assessment, and blinding for exposure outcomes.

Table 1 Included quality items from NIH quality assessment tool for observational cohort and cross-sectional studies

* I, informative criterion; V/P, validity/precision criteria.

1Acceptable validity or reliability included that 75 % of the extracted items had a Cronbach’s alpha of above 0·7, and no items were below 0·4.

Quality items were scored following a ‘yes’, ‘no’, ‘cannot be determined’, ‘not applicable’ or ‘not reported’ answering format. Two assessors (HE and TA/CD) independently assessed the quality items of the included studies. Discrepancies were resolved through discussion. A third reviewer was consulted when consensus could not be reached (CD/TA). Studies that included multiple energy balance-related behaviours, used multiple outcomes for one behaviour, for example, moderate-to-vigorous physical activity (MVPA) and active transport or used multiple measurement tools for one behaviour (e.g. objective and self-reported) received multiple scores. A study was considered ‘strong’ when scoring 80–100 % of the validity/precision criteria points, ‘moderate’ when scoring 40–79 % of the validity/precision criteria points and ‘poor’ when scoring 0–39 % of the validity/precision points.

Best evidence synthesis

We applied best evidence synthesis to draw conclusions regarding the evidence for a change in energy balance-related behaviours across the transition from primary to secondary school. This evidence synthesis is in line with previous reviews(Reference Kemper, Post and Twisk33Reference Kemper, Post and Twisk35), taking the number of studies, the methodological quality of the studies and the consistency of the findings into account. The level of evidence was defined as:

  • Strong evidence: consistent findings in more than two strong quality studies.

  • Moderate evidence: consistent findings in one study of strong methodological quality and at least one study of moderate methodological quality or consistent findings in two or more studies of moderate methodological quality.

  • Inconclusive evidence: only one study available, or inconsistent findings in two or more studies.

We considered the results within a study consistent when at least 75 % of the outcomes (e.g. total physical activity (TPA), MVPA or transport) within the same behaviour (e.g. PA) showed statistically significant (P < 0·05) results in the same direction. Publications based on the same data were only counted once in the best evidence synthesis, that is, combining the results from those publications. When studies described changes in energy balance-related behaviours without testing whether these changes were statistically significant, we contacted the authors by email and requested additional analyses or the necessary data to conduct the analyses ourselves. We contacted the authors of seven studies of which two provided the requested information or dataset. These results of these studies were included in the evidence synthesis(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk37) , and the other studies could not be included. We considered the results across studies consistent when at least 75 % of the studies showed results in the same direction, which was defined by significance (P < 0·05). Studies with a poor quality rating are included in Table 2 but were not included in the evidence synthesis.

Table 2 Study characteristics – sorted by energy balance-related behaviour, study name, quality score and alphabetically by first author

PA, physical activity; PAQ-C, Physical Activity Questionnaire for Older Children; PE, physical education; PPEA, perceived physical education activity; LPA, light intensity physical activity; MVPA, moderate-to-vigorous physical activity; TPA, total physical activity; NW, normal weight; SB, sedentary behaviour; MPA, moderate physical activity; VPA, vigorous physical activity; OW, overweight; NSP, non-starch polysaccharide; SSB, sugar-sweetened beverages.

*Studies that produced multiple papers are listed together.

Studies with a poor quality rating are not mentioned in the evidence synthesis.

Results

Search results

After removing duplicates, the search yielded 3495 unique hits (see Fig. 1). Screening of titles and abstracts resulted in 107 potentially eligible studies. Full-text screening resulted in thirty-one studies that met the inclusion criteria. Three additional studies were included after a manual search of reference lists. This resulted in the inclusion of total thirty-four studies.

Fig. 1 Flow chart of the review process

Study characteristics

Table 2 presents the characteristics of the included studies, which were conducted in the USA, Australia, UK, Belgium, Finland, Japan, Korea, the Netherlands and Norway. Eighteen studies focused on PA(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk37Reference Kemper, Post and Twisk52) , eight on PA and SB(Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk53Reference Kemper, Post and Twisk59) , one on SB(Reference Atkin, Corder and van Sluijs60), one on PA, SB and dietary intake(Reference Dowda, Taverno Ross and McIver36), five on dietary intake(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk61Reference Kemper, Post and Twisk63) and none on sleep behaviour. In total, twenty-four studies used data from cohort studies, including the CHIC, PEACH, TRACK, SPEEDY, PASS, APPLES, CATCH, ECLS-K, CLAN, KCYPS and HEAPS studies. All studies were published between 1998 and 2021 with sample sizes ranging from 99 to 7445 participants. The average participant age at the time point at primary school ranged from 10 to 12 years and follow-up from 5 months to 4 years. Table 3 summarises nineteen strong and moderate quality studies reporting evidence on energy balance-related behaviours (i.e. PA, SB, sleep behaviour and dietary behaviour) across the transition from primary to secondary school.

Table 3 Summary of evidence on changes in energy balance-related behaviours across the school transition

TPA, total physical activity; SSB, sugar-sweetened beverages; MVPA, moderate-to-vigorous physical activity; PA, physical activity.

Note that only strong and moderate quality studies were included in the evidence synthesis. In bold = study with high quality rating, + = a significant improvement in behaviour, − = significant worsening in behaviour, 0 = no change in behaviour, ± = inconsistent findings within a study, a = different results for different measurement method, b = different results for boys and girls, c = different results for different weight categories, d = different results for different time segments of the day or week, e = different results in subcategories of energy balance-related behaviours and f = different results for different intensity levels of active transport.

Physical activity

PA was assessed using accelerometers(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk38,Reference Kemper, Post and Twisk40,Reference Kemper, Post and Twisk41,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk46,Reference Kemper, Post and Twisk47,Reference Kemper, Post and Twisk49Reference Kemper, Post and Twisk52,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk59,Reference Kemper, Post and Twisk64) , self-report questionnaires(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk37,Reference Kemper, Post and Twisk38,Reference Kemper, Post and Twisk42,Reference Kemper, Post and Twisk44,Reference Kemper, Post and Twisk45,Reference Kemper, Post and Twisk48,Reference Kemper, Post and Twisk50,Reference Kemper, Post and Twisk53,Reference Kemper, Post and Twisk55) , pedometers(Reference Kemper, Post and Twisk57,Reference Kemper, Post and Twisk58) , parent-reported questionnaires(Reference Dowda, Dishman and Saunders50), activity logs(Reference Garcia, Pender and Antonakos39), Global Positioning System (GPS), loggers and Geographical Information Systems (GIS) data(Reference Remmers, Van Kann and Kremers51). Fourteen studies examined multiple PA measures(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk38,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk48,Reference Kemper, Post and Twisk50,Reference Kemper, Post and Twisk51,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk58,Reference Kemper, Post and Twisk64) and fourteen studies examined one PA measure: TPA, MVPA, level of PA (duration and intensity of sixteen activities), active/non-active classification (active defined as having a score of at least 3 out of 5 points on the Physical Activity Questionnaire for Older Children), Perceived Physical Education Activity (PPEA), active transport and number of vigorous activities(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk37,Reference Kemper, Post and Twisk39Reference Kemper, Post and Twisk42,Reference Kemper, Post and Twisk44Reference Kemper, Post and Twisk47,Reference Kemper, Post and Twisk49,Reference Kemper, Post and Twisk53,Reference Kemper, Post and Twisk59) . Eight studies received a strong methodological quality rating(Reference Kemper, Post and Twisk38,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk46,Reference Kemper, Post and Twisk49,Reference Kemper, Post and Twisk51,Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk64) . Three studies received a strong methodological quality rating for the accelerometer-based data and a moderate quality rating for the questionnaire-based data(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk55) . Twelve studies received a moderate quality rating(Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk37,Reference Kemper, Post and Twisk40,Reference Kemper, Post and Twisk41,Reference Kemper, Post and Twisk47,Reference Kemper, Post and Twisk48,Reference Kemper, Post and Twisk50,Reference Kemper, Post and Twisk52,Reference Kemper, Post and Twisk57Reference Kemper, Post and Twisk59) , and five studies received a poor quality rating(Reference Kemper, Post and Twisk39,Reference Kemper, Post and Twisk42,Reference Kemper, Post and Twisk44,Reference Kemper, Post and Twisk45,Reference Kemper, Post and Twisk53) . Sixteen studies were included in the evidence synthesis(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk37,Reference Kemper, Post and Twisk40,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk45,Reference Kemper, Post and Twisk46,Reference Kemper, Post and Twisk49,Reference Kemper, Post and Twisk51,Reference Kemper, Post and Twisk52,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk58,Reference Kemper, Post and Twisk64) .

Seven studies examined the change in TPA across the transition from primary to secondary school. One study with moderate quality rating for the questionnaire-based data and strong quality rating for the accelerometer-based data showed a significant decrease in questionnaire-based TPA (min/d), but no change in accelerometer-based TPA or MVPA (min/d)(Reference De Meester, Van Dyck and De Bourdeaudhuij21). Three strong quality studies based on the TRACK data showed a significant decrease in overall TPA (min/h)(Reference Kemper, Post and Twisk46,Reference Kemper, Post and Twisk49) , TPA during school time, TPA after school time and TPA during evening time(Reference Lau, Dowda and McIver43). One moderate quality study showed a significant decrease in TPA among boys with a healthy weight, but not among boys with overweight or girls with or without overweight(Reference Rutten, Boen and Seghers58). The last moderate quality study examined TPA in various times of the day, and the study showed a significant decrease in the number of adolescents classified as active and decrease in TPA during recess and lunchtime, but no changes were found in physical education (PE), PA after school time, PA in the evenings and PA in the weekends(Reference Ridley and Dollman45).

Five strong quality studies examined the change in LPA(Reference Kemper, Post and Twisk51,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk64) , of which two studies showed a significant decrease in LPA (min/d)(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk55) , one study showed no changes(Reference Okazaki, Koyama and Ohkawara64) and one study showed a significant decrease among boys but not among girls(Reference Ridgers, Timperio and Crawford56). One study showed a significant decrease in LPA during and after school time (min/d), but no changes before school time and on weekend days. Context-specific results showed a decrease in LPA before school time at home, during school time at school, and after school time at sports grounds and other locations(Reference Remmers, Van Kann and Kremers51). There was a significant increase in LPA during school time at other locations (e.g. at friend’s homes or at parks). No changes were found for weekend days(Reference Remmers, Van Kann and Kremers51).

Ten studies examined the change in MVPA of which two studies examined moderate physical activity (MPA) and vigorous physical activity (VPA)(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk51,Reference Kemper, Post and Twisk52,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk64) . We combined findings of the MPA and VPA studies with those of the studies examining MVPA, as results for these behaviours were in the same direction. Four studies with a strong quality rating showed a significant decrease in total MVPA(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk55,Reference Kemper, Post and Twisk64) and MVPA during recess and lunchtime(Reference Ridgers, Timperio and Crawford56). Two moderate quality studies showed a significant decrease in MVPA of which one among girls only(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk52) . Two studies with strong quality rating showed a significant increase in weekday MVPA(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28) . One study, with a strong quality rating, examined MVPA during various times in the day and showed a significant decrease in MVPA during school time among boys and girls, during the evening among girls only, but no changes in MVPA after school time(Reference Lau, Dowda and McIver43). The last study, with a strong quality rating showed a significant decrease in MVPA after school time, but no changes before school time, during school time and on weekend days(Reference Remmers, Van Kann and Kremers51). Context-specific data showed a decrease in MVPA after school time at school and at other locations, a significant increase in MVPA during school time at other locations, while no changes were found before school time and on weekend days(Reference Remmers, Van Kann and Kremers51).

One study with strong quality rating(Reference Remmers, Van Kann and Kremers51) and four studies with a moderate quality rating examined the change in active transport(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk37,Reference Kemper, Post and Twisk40,Reference Kemper, Post and Twisk55) . The strong quality study showed a significant increase in active transport-related LPA before school time and a decrease in passive transport-related LPA before school time, after school time and during weekends, but no changes in active and passive transport-related MVPA(Reference Remmers, Van Kann and Kremers51). Three moderate quality studies showed a significant increase in active transportation to/from school (min/d)(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk37) or MVPA when commuting (min/d)(Reference Harrison, van Sluijs and Corder40), of which one showed no change in active transport to leisure-time destinations(Reference Vanwolleghem, Van Dyck and De Meester37). The last study with moderate quality showed a significant decrease in times per week cycling or scooting to/from school, while no changes were found for walking to/from school(Reference Marks, Barnett and Strugnell55).

Two studies with a moderate quality rating did not fit the previous categories. One study found a significant decrease in extracurricular PA(Reference De Meester, Van Dyck and De Bourdeaudhuij21). Another study found a significant decrease in school-related PA among boys with a healthy weight, and leisure-time PA among boys and girls with a healthy weight, but no changes among boys and girls with overweight(Reference Rutten, Boen and Seghers58).

Overall, based on inconsistent findings, we found inconclusive evidence for a change in TPA, LPA, MVPA and active transport of adolescents across the transition from primary to secondary school.

Sedentary behaviour

SB was assessed using accelerometers(Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk59,Reference Kemper, Post and Twisk60,Reference Kemper, Post and Twisk64) and questionnaires(Reference Kemper, Post and Twisk53,Reference Kemper, Post and Twisk55,Reference Kemper, Post and Twisk57,Reference Kemper, Post and Twisk58,Reference Kemper, Post and Twisk60) . Three studies received a strong methodological quality rating(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk64) , and one study received a strong methodological quality rating for the accelerometer-based data and a moderate quality rating for the questionnaire-based outcomes(Reference Marks, Barnett and Strugnell55). Six studies received a moderate methodological quality rating(Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk57Reference Kemper, Post and Twisk60) , and one study received a poor quality rating(Reference Bradley, McMurray and Harrell53). Six studies could be included in the evidence synthesis(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk54Reference Kemper, Post and Twisk56,Reference Kemper, Post and Twisk58,Reference Kemper, Post and Twisk64) .

Five studies examined the change in sedentary time, of which four studies showed a significant increase across the transition from primary to secondary school. Two of these studies received a strong quality rating(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk64) , one a strong quality rating for the accelerometer-based data(Reference Marks, Barnett and Strugnell55) and one a moderate quality rating(Reference Dowda, Taverno Ross and McIver36). One study with a strong quality rating found a significant increase in the proportion of sedentary time during recess and lunchtime(Reference Ridgers, Timperio and Crawford56).

Two studies with a moderate quality rating examined the change in self-reported screen time across the school transition. One of the studies showed a significant increase in screen time for homework and leisure time during the week, but not during the weekend(Reference Marks, Barnett and Strugnell55). The other study showed a significant increase in screen time in boys with a healthy weight but no changes in girls or boys with overweight(Reference Rutten, Boen and Seghers58).

Overall, we found strong evidence for an increase in SB of adolescents across the transition from primary to secondary school. We found inconclusive evidence for a change in screen time across the transition due to inconsistent results.

Dietary behaviour

Dietary behaviours were assessed using 24-h recalls(Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk36) , FFQ(Reference Kemper, Post and Twisk61Reference Kemper, Post and Twisk63) and food diaries(Reference Winpenny, Corder and Jones15). Two studies examined overall diet quality(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk63) . Four studies examined the consumption of fruit, vegetable, snacks and SSB(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk61,Reference Kemper, Post and Twisk62) . Three studies examined additional dietary behaviours, with one study examining breakfast, lunch, milk, and fruit-flavoured beverage consumption(Reference Lytle, Seifert and Greenstein16), one study examining total energy intake and macro- and micronutrient intake(Reference Winpenny, Corder and Jones15), and one study examining milk consumption(Reference Oza-Frank, Zavodny and Cunningham62). Five studies received a moderate quality rating(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk61,Reference Kemper, Post and Twisk63) and one a poor quality rating(Reference Oza-Frank, Zavodny and Cunningham62). Five studies were included in the evidence synthesis(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk61,Reference Kemper, Post and Twisk63) .

Three studies with a moderate quality rating examined the change in fruit and vegetable consumption across the transition from primary to secondary school, all showing a significant decrease in consumption(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk61) .

Three studies with a moderate quality rating examined the change in unhealthy snack consumption(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk61) . One study showed a significant decrease in the consumption of non-core food items, such as potato chips and chocolate(Reference Marks, Barnett and Allender61). One study showed a significant increase in the consumption of fries and confectionary, but no change in the consumption of other savoury snacks(Reference Winpenny, Corder and Jones15). The last study showed a significant decrease in the consumption of high-fat salty snacks, but no change in the consumption of overall snacks, and high-fat sweet snacks consumption(Reference Lytle, Seifert and Greenstein16).

Three studies with a moderate quality rating examined the change in consumption of SSB(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16,Reference Kemper, Post and Twisk61) . Two studies showed a significant increase in the consumption of SSB(Reference Kemper, Post and Twisk15,Reference Kemper, Post and Twisk16) . One of these studies showed a significant decrease in the consumption of fruit juice(Reference Lytle, Seifert and Greenstein16). A third study showed a significant decrease in the consumption of SSB(Reference Marks, Barnett and Allender61).

Three studies with a moderate quality rating did not fit the previous categories. Two studies based on data from the TRACK study showed a significant decrease in total diet quality(Reference Kemper, Post and Twisk36,Reference Kemper, Post and Twisk63) , and one study showed a significant decrease in the consumption of milk(Reference Lytle, Seifert and Greenstein16). The last study showed a significant increase in total energy intake and dietary fibre intake and a significant decrease in total daily energy intake from sugars and the intake of SFA(Reference Winpenny, Corder and Jones15). In this study, no significant changes were found for daily energy percentages from protein, carbohydrates and fat(Reference Winpenny, Corder and Jones15).

Overall, we found moderate evidence for a decrease in fruit and vegetable consumption of adolescents across the primary to secondary school transition. Studies on unhealthy snack and SSB consumption showed inconsistent results leading to inconclusive evidence. The outcomes in studies that did not fit the previous categories were only reported once, leading to inconclusive evidence.

Discussion

This systematic review summarised the evidence on changes in energy balance-related behaviours (i.e. PA, SB, sleep behaviour and dietary behaviour) of adolescents across the transition from primary to secondary school. We found strong evidence for an increase in SB, moderate evidence for a decrease in fruit and vegetable consumption, and inconclusive evidence for a change in TPA, LPA, MVPA, active transport, screen time, unhealthy snack and SSB consumption. No studies were identified examining the change in sleep behaviour across the transition from primary to secondary school.

Our results regarding inconclusive evidence for a change in TPA, LPA and MVPA across the transition from primary to secondary school is in contrast with previous literature. A review on PA change during adolescence (e.g. age-related literature not specifically focused on the school transition) found evidence for a decrease in PA (combining various outcomes of PA) in growing adolescents(Reference Dumith, Gigante and Domingues65). Another study found a decline in TPA and MVPA when adolescents grow older(Reference Farooq, Parkinson and Adamson66). We found inconsistent results for a change in MVPA across the transition from primary to secondary school. Most of the included studies examining MVPA showed a significant decrease in total MVPA(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk55) , MVPA during recess and lunchtime(Reference Ridgers, Timperio and Crawford56), and MVPA during school time but not after school time(Reference Lau, Dowda and McIver43). Remarkably, two studies showed a significant increase in weekday MVPA(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28) . Our findings correspond to a recent review showing that changes in 24-h movement behaviours across the school transition largely depend on the time segments of the day or week(Reference Chong, Parrish and Cliff13). The increase in weekday MVPA across the transition might be explained by an increase in active transport. Although we found inconclusive evidence for an increase in active transport in the current review, three out of five studies showed a significant increase in MVPA during commuting(Reference Harrison, van Sluijs and Corder40) and active transportation to/from school(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk37) . One study found an increase in active transport-related LPA during weekdays and a decrease during weekend days across the school transition(Reference Remmers, Van Kann and Kremers51). Generally, the distance to/from school increases as adolescents transition from primary to secondary school, which can result in an increase in active transport(Reference Cooper, Jago and Southward28). Conversely, an increased distance to/from school can also result in an increase in SB due to using passive, public transportation(Reference Cooper, Jago and Southward28).

The finding of an increase in SB across the transition from primary to secondary school is consistent with previous studies in adolescents that showed an increase in SB when adolescents grow older(Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk67) , and with a review that found an increase in SB across the primary to secondary school transition(Reference Pearson, Haycraft and Johnston14). However, our finding of inconclusive evidence for a change in screen time across the transition is in contrast to the findings of the review by Pearson et al. who showed an increase in screen time across the school transition(Reference Pearson, Haycraft and Johnston14). Different inclusion criteria regarding the transition from primary to secondary school might explain this difference. In the present review, studies had to describe clearly that at least one measurement was taken in adolescents attending primary school and one in the same adolescents attending secondary school. Five studies included in the review of Pearson et al. did not meet our inclusion criterion because they did not mention a transition from primary to secondary school.

We found moderate evidence for a decrease in fruit and vegetable consumption and inconclusive evidence for a change in unhealthy snack and SSB consumption. This is partly confirmed in one cross-sectional study that found a decrease in fruit consumption and no change for vegetable consumption with increasing age(Reference Albani, Butler and Traill68). A review including age-related studies found a lack of evidence for many potential determinants of fruit and vegetable consumption in children and adolescents, especially for determinants related to the physical and social school environment(Reference Rasmussen, Krølner and Klepp69). Studies on determinants of fruit and vegetable consumption across the transition from primary to secondary school are currently lacking. Based on previous studies, we expected a significant increase in unhealthy snack and SSB consumption due to adolescents experiencing more freedom and receiving more pocket money across the school transition from primary to secondary school(Reference Kemper, Post and Twisk25Reference Kemper, Post and Twisk27,Reference Kemper, Post and Twisk70) . An important remark regarding studies examining dietary behaviour is the use of many different self-report measures often of unknown validity and reliability(Reference Naska, Lagiou and Lagiou71). Consequently, the studies included in the present review examining dietary behaviour received a low-quality rating resulting in inconclusive evidence.

No studies on sleep behaviour were available that met our inclusion criteria. However, as mentioned in the introduction, we do expect changes in sleep behaviour across the transition from primary to secondary school. A study in Australian children showed that the majority of 10–11-year-olds met the minimum sleep requirements on school nights (9–11 h), while a quarter of 12–13-year-olds did not meet the minimum sleep requirements on school nights (8–10 h)(Reference Evans-Whipp and Gasser72). More research is needed to investigate sleep behaviour across the primary to secondary school transition.

The results from this review suggest a worsening in aspects of the energy balance-related behaviours PA, SB and dietary behaviour across the transition from primary to secondary school. Energy balance-related behaviours are connected and strengthen each other, for example, an increase in screen time has been associated with an increase in unhealthy snack consumption, a decrease in fruit and vegetable consumption(Reference Falbe, Willett and Rosner73) and less sleep(Reference Hale and Guan10). Interventions targeting these energy balance-related behaviours during the transition from primary to secondary school therefore seem warranted. In the current review, nine out of thirty-three included studies examined more than one behaviour, of which eight on PA and SB(Reference Kemper, Post and Twisk22,Reference Kemper, Post and Twisk53Reference Kemper, Post and Twisk59) , and one on PA, SB and dietary intake(Reference Dowda, Taverno Ross and McIver36). In these studies, the outcomes of these behaviours were linked as results indicate that PA decreases were often replaced by SB(Reference Kemper, Post and Twisk53Reference Kemper, Post and Twisk56). However, more longitudinal research is needed on changes in energy balance-related behaviour across the school transition, especially regarding sleep behaviour. Moreover, future research should focus on how energy balance-related behaviours influence each other in the school transition. Furthermore, qualitative research regarding the reasons for changes in behaviours related to the change in school environment is needed in order to develop appropriate interventions. To the best of our knowledge, current interventions do not specifically target the school transition period but mainly focus on primary or secondary school. Moreover, many school-based interventions targeting PA and dietary behaviour exist, while only a few target healthy sleep behaviour(Reference Busch, Altenburg and Harmsen74).

Seven out of thirty-three studies included in the present review received a strong methodological quality rating(Reference Kemper, Post and Twisk38,Reference Kemper, Post and Twisk43,Reference Kemper, Post and Twisk46,Reference Kemper, Post and Twisk49,Reference Kemper, Post and Twisk52,Reference Kemper, Post and Twisk54,Reference Kemper, Post and Twisk56) . Three studies received a strong methodological quality rating for the accelerometer-based data and a moderate quality rating for the questionnaire-based data(Reference Kemper, Post and Twisk21,Reference Kemper, Post and Twisk28,Reference Kemper, Post and Twisk55) . Quality items that limited the methodological quality rating of a study included a follow-up rate below 70 %, not having a representative sample, or not adjusting for potential confounders in the statistical analysis. Future studies should keep these potential sources of bias in mind when designing their study in order to conduct high-quality studies.

Strength and limitations

This review is the first summarising changes in dietary behaviour across the transition from primary to secondary school. Furthermore, this is the first review including all four energy balance-related behaviours (PA, SB, sleep behaviour and dietary behaviour) in a systematic review on changes in these behaviours across the school transition, which adds information to previous reviews by Pearson et al. and Chong et al. that only included two or three behaviours(Reference Kemper, Post and Twisk13,Reference Kemper, Post and Twisk14) . Other strengths of this review include the broad search strategy, which included four electronic databases without publication data restrictions. Furthermore, two independent reviewers conducted title and abstract screening, quality assessment, and data extraction resulting in the elimination of bias and errors in the methodology. A limitation is that we could have missed relevant studies that did not clearly state that the measurements were taken in adolescents attending primary school and in the same adolescents attending secondary school. We applied this strict inclusion criterion because we were interested in transitions accompanying a change in school environment, as such transitions may influence adolescents’ energy balance-related behaviours(Reference Marks, Barnett and Strugnell55). Another limitation is that only studies published in English were included. Additionally, we did not include grey literature in our search strategy. Furthermore, conducting a meta-analysis was not feasible because of the heterogeneity in outcomes and research methods in the included studies. In this review, we found inconsistencies between study results that are due to differences in measurement, setting and outcome. We recommend to develop and use an agreed set of key outcomes to be measured and reported in all future studies examining changes in energy balance-related behaviours to benefit evidence synthesis from all published studies(Reference de Vries, Harrington and Grooten75). Furthermore, we recommend future studies to provide more detailed characteristics of the school setting as a difference in setting could explain the different results between studies. For example, one study could have included schools that provided school meals, while another study included schools without school meals. This specific information about characteristic in the setting could not be extracted from the included studies. Lastly, the findings may not be generalisable to the adolescents of low- and middle-income countries because all studies were conducted in high-income countries.

Conclusion

The current review found strong evidence for an increase in SB and moderate evidence for a decrease in fruit and vegetable consumption of adolescents across the transition from primary to secondary school. There was inconclusive evidence for the other energy balance-related behavioural outcomes due to inconsistent results and lack of high-quality studies. More longitudinal research is needed specifically on changes in energy balance-related behaviour across the school transition, especially regarding sleep behaviour. These studies should keep potential sources of bias in mind when designing their study in order to conduct high-quality studies.

Acknowledgements

Acknowledgements: Not applicable. Authorship: All authors conceptualised and designed the study. The literature search was performed by H.E.. Screening and article review were performed by H.E. and C.D./T.A.. Data extraction and quality assessment were done by H.E. and C.D./T.A.. Data analysis and synthesis were performed by H.E.. HE drafted the manuscript. C.D., S.K., M.C. and T.A. provided guidance about the content of the review, suggested pertinent literature and contributed to multiple revisions of the manuscript. All authors revised the manuscript and approved the final manuscript. Ethics of human subject participation: Not applicable.

Financial support:

This work was supported by a grant from the Netherlands Cardiovascular Research. Initiative: An initiative with support of the Dutch Heart Foundation, ZonMw, CVON2016-07 LIKE.

Conflicts of interest:

The authors declare that they have no competing interest.

Supplementary material

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S1368980023000812

References

WHO (2014) Facts and Figures on Childhood Obesity. http://www.who.int/end-childhood-obesity/facts/en/ (accessed September 2020).Google Scholar
Freedman, DS, Dietz, WH, Srinivasan, SR et al. (1999) The relation of overweight to cardiovascular risk factors among children and adolescents: the Bogalusa Heart Study. Pediatrics 103, 11751182.CrossRefGoogle ScholarPubMed
Kemper, H, Post, G, Twisk, J et al. (1999) Lifestyle and obesity in adolescence and young adulthood: results from the Amsterdam Growth And Health Longitudinal Study (AGAHLS). Int J Obes 23, S34S40.CrossRefGoogle Scholar
Sherry, B & Dietz, WH (2004) Pediatric Overweight: an Overview. Handbook of Obesity. New York, NY: Marcel Dekker Inc. pp. 117134.Google Scholar
Tang-Péronard, J & Heitmann, B (2008) Stigmatization of obese children and adolescents, the importance of gender. Obes Rev 9, 522534.CrossRefGoogle ScholarPubMed
Strauss, RS (2000) Childhood obesity and self-esteem. Pediatrics 105, e15-e.CrossRefGoogle ScholarPubMed
Huang, TT, Drewnowski, A, Kumanyika, SK et al. (2009) A systems-oriented multilevel framework for addressing obesity in the 21st century. Prev Chronic Dis 6, A82.Google ScholarPubMed
Mamun, AA, Lawlor, DA, Cramb, S et al. (2007) Do childhood sleeping problems predict obesity in young adulthood? Evidence from a prospective birth cohort study. Am J Epidemiol 166, 13681373.CrossRefGoogle ScholarPubMed
Sahoo, K, Sahoo, B, Choudhury, AK et al. (2015) Childhood obesity: causes and consequences. J Fam Med Prim Care 4, 187192.Google ScholarPubMed
Hale, L & Guan, S (2015) Screen time and sleep among school-aged children and adolescents: a systematic literature review. Sleep Med Rev 21, 5058.CrossRefGoogle ScholarPubMed
Hales, CM, Carroll, MD, Fryar, CD et al. (2017) Prevalence of Obesity among Adults and Youth: United States, 2015–2016. NCHS Data Brief no 288. PHS 2018–1209. Hyattsville, MD: DHHS Publication.Google Scholar
Statistics Netherlands (2020) StatLine (Internet). https://opendata.cbs.nl/statline/ (accessed February 2021).Google Scholar
Chong, KH, Parrish, A-M, Cliff, DP et al. (2020) Changes in physical activity, sedentary behaviour and sleep across the transition from primary to secondary school: a systematic review. J Sci Med Sport 23, 498505.CrossRefGoogle ScholarPubMed
Pearson, N, Haycraft, E, Johnston, JP et al. (2017) Sedentary behaviour across the primary-secondary school transition: a systematic review. Prev Med 94, 4047.CrossRefGoogle ScholarPubMed
Winpenny, EM, Corder, KL, Jones, A et al. (2017) Changes in diet from age 10 to 14 years and prospective associations with school lunch choice. Appetite 116, 259267.CrossRefGoogle ScholarPubMed
Lytle, LA, Seifert, S, Greenstein, J et al. (2000) How do children’s eating patterns and food choices change over time? Results from a cohort study. Am J Health Promot 14, 222228.CrossRefGoogle ScholarPubMed
Bleich, SN & Wolfson, JA (2015) Trends in SSBs and snack consumption among children by age, body weight, and race/ethnicity. Obesity 23, 10391046.CrossRefGoogle ScholarPubMed
Parent, J, Sanders, W & Forehand, R (2016) Youth screen time and behavioral health problems: the role of sleep duration and disturbances. J Dev Behav Pediatr 37, 277284.CrossRefGoogle ScholarPubMed
Bruce, ES, Lunt, L & McDonagh, JE (2017) Sleep in adolescents and young adults. Clin Med (Lond) 17, 424428.CrossRefGoogle ScholarPubMed
Ramirez, ER, Norman, GJ, Rosenberg, DE et al. (2011) Adolescent screen time and rules to limit screen time in the home. J Adolesc Health 48, 379385.CrossRefGoogle ScholarPubMed
De Meester, F, Van Dyck, D, De Bourdeaudhuij, I et al. (2014) Changes in physical activity during the transition from primary to secondary school in Belgian children: what is the role of the school environment? BMC Public Health 14, 261.CrossRefGoogle ScholarPubMed
Morton, KL, Corder, K, Suhrcke, M et al. (2016) School polices, programmes and facilities, and objectively measured sedentary time, LPA and MVPA: associations in secondary school and over the transition from primary to secondary school. Int J Behav Nutr Phys Act 13, 54.CrossRefGoogle ScholarPubMed
McGaughey, T, Vlaar, J, Naylor, PJ et al. (2020) Individual and environmental factors associated with participation in physical activity as adolescents transition to secondary school: a qualitative inquiry. Int J Environ Res Public Health 17, 7646.CrossRefGoogle ScholarPubMed
Morton, K, Atkin, A, Corder, K et al. (2016) The school environment and adolescent physical activity and sedentary behaviour: a mixed-studies systematic review. Obes Rev 17, 142158.CrossRefGoogle ScholarPubMed
Brown, J, Croxford, L & Minty, S (2017) Pupils as Citizens: Participation, Responsibility and Voice in the Transition from Primary to Secondary School. Edinburgh: Centre for Research in Education Inclusion and Diversity.Google Scholar
Ashton, R (2008) Improving the transfer to secondary school: how every child’s voice can matter. Support Learning 23, 176182.CrossRefGoogle Scholar
Li, M, Xue, H, Jia, P et al. (2017) Pocket money, eating behaviors, and weight status among Chinese children: the childhood obesity study in China mega-cities. Prev Med 100, 208215.CrossRefGoogle Scholar
Cooper, AR, Jago, R, Southward, EF et al. (2012) Active travel and physical activity across the school transition: the PEACH project. Med Sci Sports Exerc 44, 18901897.CrossRefGoogle ScholarPubMed
Dahl, RE & Lewin, DS (2002) Pathways to adolescent health sleep regulation and behavior. J Adolesc Health 31, 175184.CrossRefGoogle Scholar
Waterlander, WE, Singh, A, Altenburg, T, et al. (2020) Understanding obesity-related behaviors in youth from a systems dynamics perspective: the use of causal loop diagrams. Obes Rev 22, e13185.Google Scholar
Page, MJ, McKenzie, JE, Bossuyt, PM et al. (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372, n71.CrossRefGoogle ScholarPubMed
National Institutes of Health (2018) NIH Quality assessment Tool for Observational Cohort and Cross-Sectional Studies. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools (accessed December 2018).Google Scholar
Chinapaw, M, Proper, K, Brug, J et al. (2011) Relationship between young peoples’ sedentary behaviour and biomedical health indicators: a systematic review of prospective studies. Obes Rev 12, e621e632.CrossRefGoogle ScholarPubMed
van Ekris, E, Altenburg, T, Singh, AS et al. (2016) An evidence-update on the prospective relationship between childhood sedentary behaviour and biomedical health indicators: a systematic review and meta-analysis. Obes Rev 17, 833849.CrossRefGoogle ScholarPubMed
Singh, AS, Mulder, C, Twisk, JW et al. (2008) Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev 9, 474488.CrossRefGoogle ScholarPubMed
Dowda, M, Taverno Ross, SE, McIver, KL et al. (2017) Physical activity and changes in adiposity in the transition from elementary to middle school. Child Obes 13, 5362.CrossRefGoogle ScholarPubMed
Vanwolleghem, G, Van Dyck, D, De Meester, F et al. (2016) Which socio-ecological factors associate with a switch to or maintenance of active and passive transport during the transition from primary to secondary school? PLoS One 11, e0156531.CrossRefGoogle ScholarPubMed
Coombes, E, Jones, A, Page, A et al. (2014) Is change in environmental supportiveness between primary and secondary school associated with a decline in children’s physical activity levels? Health Place 29, 171178.CrossRefGoogle Scholar
Garcia, AW, Pender, NJ, Antonakos, CL et al. (1998) Changes in physical activity beliefs and behaviors of boys and girls across the transition to junior high school. J Adolesc Health 22, 394402.CrossRefGoogle ScholarPubMed
Harrison, F, van Sluijs, EMF, Corder, K et al. (2016) School grounds and physical activity: associations at secondary schools, and over the transition from primary to secondary schools. Health Place 39, 3442.CrossRefGoogle ScholarPubMed
Jago, R, Page, AS & Cooper, AR (2012) Friends and physical activity during the transition from primary to secondary school. Med Sci Sports Exerc 44, 111117.CrossRefGoogle ScholarPubMed
Kirby, J, Levin, KA & Inchley, J (2011) Parental and peer influences on physical activity among Scottish adolescents: a longitudinal study. J Phys Act Health 8, 785793.CrossRefGoogle ScholarPubMed
Lau, EY, Dowda, M, McIver, KL et al. (2017) Changes in physical activity in the school, afterschool, and evening periods during the transition from elementary to middle school. J Sch Health 87, 531537.CrossRefGoogle ScholarPubMed
Shin, M, Lee, C & Lee, Y (2019) Effect of aggression on peer acceptance among adolescents during school transition and non-transition: focusing on the moderating effects of gender and physical education activities. Int J Environ Res Public Health 16, 3190.CrossRefGoogle ScholarPubMed
Ridley, K & Dollman, J (2019) Changes in physical activity behaviour and psychosocial correlates unique to the transition from primary to secondary schooling in adolescent females: a longitudinal cohort study. Int J Environ Res Public Health 16, 4959.CrossRefGoogle Scholar
Pate, RR, Dowda, M, Dishman, RK et al. (2019) Change in children’s physical activity: predictors in the transition from elementary to middle school. Am J Prev Med 56, e65e73.CrossRefGoogle ScholarPubMed
Pate, RR, Schenkelberg, MA, Dowda, M et al. (2019) Group-based physical activity trajectories in children transitioning from elementary to high school. BMC Public Health 19, 323.CrossRefGoogle ScholarPubMed
Dowda, M, Saunders, RP, Colabianchi, N et al. (2020) Longitudinal associations between psychosocial, home, and neighborhood factors and children’s physical activity. J Phys Act Health 17, 306312.CrossRefGoogle ScholarPubMed
Clennin, MN, Lian, M, Colabianchi, N et al. (2019) Associations among neighborhood socioeconomic deprivation, physical activity facilities, and physical activity in youth during the transition from childhood to adolescence. Int J Environ Res Public Health 16, 3703.CrossRefGoogle ScholarPubMed
Dowda, M, Dishman, RK, Saunders, RP et al. (2021) Associations between three measures of physical activity and selected influences on physical activity in youth transitioning from elementary to middle school. Sports Med Health Sci 3, 2127.CrossRefGoogle ScholarPubMed
Remmers, T, Van Kann, D, Kremers, S et al. (2020) Investigating longitudinal context-specific physical activity patterns in transition from primary to secondary school using accelerometers, GPS, and GIS. Int J Behav Nutr Phys Act 17, 114.CrossRefGoogle ScholarPubMed
Mikalsen, HK, Bentzen, M, Säfvenbom, R et al. (2020) Trajectories of physical activity among adolescents in the transition from primary to secondary school. Front Sports Active Living 2, 85.CrossRefGoogle ScholarPubMed
Bradley, CB, McMurray, RG, Harrell, JS et al. (2000) Changes in common activities of 3rd through 10th graders: the CHIC study. Med Sci Sports Exerc 32, 20712078.CrossRefGoogle ScholarPubMed
Corder, K, Sharp, SJ, Atkin, AJ et al. (2015) Change in objectively measured physical activity during the transition to adolescence. Br J Sports Med 49, 730736.CrossRefGoogle ScholarPubMed
Marks, J, Barnett, LM, Strugnell, C et al. (2015) Changing from primary to secondary school highlights opportunities for school environment interventions aiming to increase physical activity and reduce sedentary behaviour: a longitudinal cohort study. Int J Behav Nutr Phys Act 12, 59.CrossRefGoogle ScholarPubMed
Ridgers, ND, Timperio, A, Crawford, D et al. (2012) Five-year changes in school recess and lunchtime and the contribution to children’s daily physical activity. Br J Sports Med 46, 741746.CrossRefGoogle ScholarPubMed
Rutten, C, Boen, F & Seghers, J (2015) Which school- and home-based factors in elementary school-age children predict physical activity and sedentary behavior in secondary school-age children? A prospective cohort study. J Phys Act Health 12, 409417.CrossRefGoogle ScholarPubMed
Rutten, C, Boen, F & Seghers, J (2014) Changes in physical activity and sedentary behavior during the transition from elementary to secondary school. J Phys Act Health 11, 16071613.CrossRefGoogle ScholarPubMed
Jaakkola, T, Hakonen, H, Kankaanpaa, A et al. (2019) Longitudinal associations of fundamental movement skills with objectively measured physical activity and sedentariness during school transition from primary to lower secondary school. J Sci Med Sport 22, 8590.CrossRefGoogle ScholarPubMed
Atkin, AJ, Corder, K & van Sluijs, EMF (2013) Bedroom media, sedentary time and screen-time in children: a longitudinal analysis. Int J Behav Nutr Phys Act 10, 137.CrossRefGoogle ScholarPubMed
Marks, J, Barnett, LM & Allender, S (2015) Change of school in early adolescence and adverse obesity-related dietary behavior: a longitudinal cohort study, Victoria, Australia, 2013–2014. Prev Chronic Dis 12, E145.CrossRefGoogle ScholarPubMed
Oza-Frank, R, Zavodny, M & Cunningham, SA (2012) Beverage displacement between elementary and middle school, 2004–2007. J Acad Nutr Diet 112, 13901396.CrossRefGoogle ScholarPubMed
Taverno Ross, SE, Militello, G, Dowda, M et al. (2020) Changes in diet quality in youth living in South Carolina from fifth to 11th grade. J Nutr Educ Behav 52, 928934.CrossRefGoogle ScholarPubMed
Okazaki, K, Koyama, Y & Ohkawara, K (2022) Changes in physical activity patterns of students from primary to secondary school: a 5-year longitudinal study. Sci Rep 12, 19.CrossRefGoogle ScholarPubMed
Dumith, SC, Gigante, DP, Domingues, MR et al. (2011) Physical activity change during adolescence: a systematic review and a pooled analysis. Int J Epidemiol 40, 685698.CrossRefGoogle Scholar
Farooq, MA, Parkinson, KN, Adamson, AJ et al. (2018) Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study. Br J Sports Med 52, 10021006.CrossRefGoogle ScholarPubMed
Pate, RR, Mitchell, JA, Byun, W et al. (2011) Sedentary behaviour in youth. Br J Sports Med 45, 906913.CrossRefGoogle ScholarPubMed
Albani, V, Butler, LT, Traill, WB et al. (2017) Fruit and vegetable intake: change with age across childhood and adolescence. Br J Nutr 117, 759765.CrossRefGoogle ScholarPubMed
Rasmussen, M, Krølner, R, Klepp, K-I et al. (2006) Determinants of fruit and vegetable consumption among children and adolescents: a review of the literature. Part I: quantitative studies. Int J Behav Nutr Phys Act 3, 22.CrossRefGoogle ScholarPubMed
Ludwig, DS, Peterson, KE & Gortmaker, SL (2001) Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. Lancet 357, 505508.CrossRefGoogle ScholarPubMed
Naska, A, Lagiou, A & Lagiou, P (2017) Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Research 6, 926.CrossRefGoogle ScholarPubMed
Evans-Whipp, T & Gasser, C (2018) Are Children and Adolescents Getting Enough Sleep. Growing up in Australia The Longitudinal Study of Australian Children (LSAC) Annual Statistical Report. https://growingupinaustralia.gov.au/research-findings/annual-statistical-reports-2018 (accessed May 2022).Google Scholar
Falbe, J, Willett, WC, Rosner, B et al. (2014) Longitudinal relations of television, electronic games, and digital versatile discs with changes in diet in adolescents. Am J Clin Nutr 100, 11731181.CrossRefGoogle ScholarPubMed
Busch, V, Altenburg, TM, Harmsen, IA et al. (2017) Interventions that stimulate healthy sleep in school-aged children: a systematic literature review. Eur J Public Health 27, 5365.CrossRefGoogle ScholarPubMed
de Vries, LW, Harrington, D, Grooten, I et al. (2022) Development of a core outcome set for school-based intervention studies on preventing childhood overweight and obesity: study protocol. BMJ Open 12, e051726.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Included quality items from NIH quality assessment tool for observational cohort and cross-sectional studies

Figure 1

Table 2 Study characteristics – sorted by energy balance-related behaviour, study name, quality score and alphabetically by first author

Figure 2

Fig. 1 Flow chart of the review process

Figure 3

Table 3 Summary of evidence on changes in energy balance-related behaviours across the school transition

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