Next Article in Journal
Sex Differences in the Association between Living Environmental Factors and Nutritional Status in Community-Dwelling Elderly Koreans
Next Article in Special Issue
Changes in Lipoinflammation Markers in People with Obesity after a Concurrent Training Program: A Comparison between Men and Women
Previous Article in Journal
Factors Related to Oral Healthcare Service Utilization among Korean Adults Aged 25–79 Years
Previous Article in Special Issue
Correction: Giménez-Meseguer, J., Tortosa-Martínez, J., Cortell-Tormo, J. M. The Benefits of Physical Exercise on Mental Disorders and Quality of Life in Substance Use Disorders Patients. Systematic Review and Meta-Analysis. International Journal of Environment Research and Public Health. 2020, 17, 3680
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 17
Issue 17
10.3390/ijerph17176031
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Evaluation of Physical Activity and Lifestyle Interventions Focused on School Children with Obesity Using Accelerometry: A Systematic Review and Meta-Analysis

by
Jose Manuel Jurado-Castro
1,
Mercedes Gil-Campos
1,2,3,*,
Hugo Gonzalez-Gonzalez
4 and
Francisco Jesus Llorente-Cantarero
1,2,5
1
Metabolism and Investigation Unit, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, 14004 Córdoba, Spain
2
CIBEROBN, (Physiopathology of Obesity and Nutrition), Institute of Health Carlos III (ISCIII), 28029 Madrid, Spain
3
Unit of Metabolism and Pediatric Research, Reina Sofia University Hospital, 14004 Córdoba, Spain
4
Department of Education, University of Cordoba, 14071 Córdoba, Spain
5
Department of Specific Didactics, Faculty of Education, University of Cordoba, 14071 Córdoba, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(17), 6031; https://doi.org/10.3390/ijerph17176031
Submission received: 9 July 2020 / Revised: 13 August 2020 / Accepted: 17 August 2020 / Published: 19 August 2020
(This article belongs to the Special Issue Management and Promotion of Healthy Habits and Active Life)
Browse Figures
Versions Notes

Abstract

:
Despite the existence of global recommendations for physical activity and lifestyle to avoid childhood obesity, there are no specific recommendations for school-age children. The aim of this meta-analysis was to measure the effects of current interventions with a physical activity component on body mass index (BMI) Z-score and on the moderate and vigorous physical activity (MVPA) time, measured by accelerometry, and focused on children with obesity. Randomized controlled trial studies (RCTs) based on physical activity interventions focused on children with obesity (6 to 12 years old) from January 1991 to August 2018 were included. The post-intervention mean and standard deviation of the BMI Z-score and MVPA engaged time were extracted to calculate the results using random effects models. Of a total of 229 studies considered potentially eligible, only 10 RCTs met the inclusion criteria. There were improvements in the BMI Z-score for physical activity intervention groups, compared with non-intervention children in addition to a significant increase in time engaged in MVPA. In conclusion, interventions with a physical activity component in school-children with obesity seem to be effective at reducing BMI and producing an increase in time spent engaged in physical activity. Therefore, interventions based on physical activity should be considered one of the main strategies in treating childhood obesity.

1. Introduction

Epidemiological studies continue to show an alarmingly increasing prevalence of childhood obesity in developed countries, despite the different strategies being carried out by governments [1]. It is well known that obesity increases the risk of cardiovascular diseases, and it is associated with physical and mental health problems in both children and adults [2]. In this regard, traditional obesity treatment in children tries to promote a healthier lifestyle and good nutritional habits by increasing physical activity (PA) and modifying behavior, such as walking to school. However, there is no specific information about the effects these interventions have on children with obesity [3,4,5], for example, the length, intensity and frequency per week of the sessions, weekend sessions or exercise type. Some reviews [6,7,8,9,10,11] have considered individual studies which examined behavioral interventions regarding weight control, obesity prevention or treatment. These included PA, dietary patterns or a combination of both and concluded that there was only limited evidence about specific recommendations. Moreover, most of these exercise- or PA-based interventions are obtained through questionnaires and not measured objectively using accelerometry [9]. Currently, accelerometry is the best tool to measure the time spent in sedentary and PA behaviors. It can also estimate the intensity levels of different evaluated periods [12]. In addition, variables such as age, sex, pubertal stage or BMI of the selected subjects, as well as the different intervention types and results, lead to high heterogeneity [6]. A Cochrane review [13] concluded that behavioral lifestyle interventions, which often include a multidisciplinary component in treating childhood obesity, could be effective in obtaining a significant reduction in overweight. However, the intervention effects on PA were not considered.
At present, regular PA practice, starting during childhood, appears to help to maintain a healthy metabolic status and seems to be an effective tool in treating childhood obesity [14]. This is especially true during growth [15] where it has been found to be associated with lower morbidity and mortality rates in adulthood [16]. Particularly in children and adolescents affected by obesity, it can induce a positive adjustment in adiposity tissue, regardless of weight loss [17]. In fact, since 2010, the World Health Organization (WHO) has recommended at least 60 min of daily moderate to vigorous PA (MVPA) engagement for children and young people (5–17 years) to improve health [18]. However, the percentage of children achieving these recommendations still remains very low [19] despite multiple protocols and interventions being carried out. This may be partly explained by the absence of specific recommendations for children at the prepubertal stage [20,21].
Addressing the alarming reduction in PA practice amongst children [19] is the main priority of the present programs to tackle childhood obesity. Therefore, an objective method is necessary to examine the daily routine of children and to be able to promote a more active lifestyle at different life stages. A particularly important group to target is that of school-aged children [8,9,22]. Under this premise, studies have been carried out on the effectiveness of interventions with a main component of PA measured objectively [7,23]. However, these interventions achieved small or negligible increases in PA for children and adolescents, as well as limited success in reducing BMI or body fat, or were carried out mainly in adolescents. Furthermore, it seems that subgroup analysis where interventions are aimed exclusively at an overweight or obese population tended to be slightly more effective compared to those aimed at all children [23].
After these findings, and due to the fact that the current evidence includes adolescents in its results, which may be confounding factors for younger children, it remains unknown how the interventions directed at school-age children with obesity affect them specifically. Thus, the aim of the present study is to evaluate the effect of current interventions with a PA component on body mass index (BMI) and time spent engaged in MVPA via accelerometry measurement, among school-age children with obesity to establish better practices that promote adherence to a more active lifestyle.

2. Materials and Methods

A systematic review and meta-analysis of published studies was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) [24] (Table S1). The pre-defined review protocol was registered at the PROSPERO (International Prospective Register of Systematic Reviews), registration number CRD42020095179.

2.1. Criteria for Considering Studies for Inclusion in the Review

This systematic review included randomized controlled trial studies (RCTs) published between January 1991 and August 2018.
The inclusion criteria were established according to the PICO(S) outline: P (population): Samples of school age children (6 to 12 years old) and also subsamples including children with obesity; I (intervention) and C (comparison): PA interventions objectively measured using accelerometry taking into consideration a MVPA evaluation versus a control group; O (outcome): Reduction of the BMI Z-Score and time spent engaged in MVPA; (S) (study type): Randomized controlled trials studies.
Exclusion criteria were non-primary studies (for example, letters and reviews of narrative literature; duplicate publications); studies conducted on children not in the 6 to 12 age range; studies not including children with obesity and a PA component; studies in which the PA data were not accelerometry-quantified; and studies in which the MVPA or BMI data were not reported.

2.2. Protocol for Electronic Searching

The search of scientific literature was performed in electronic databases of published articles such as MEDLINE (PubMed), Cochrane Register of Controlled Trials (CENTRAL), and Web of Science. A complementary search was carried out to explore other secondary national and international databases. These included ScienceDirect (SCOPUS), PROQuest, BVS (Biblioteca Virtual en Salud), Annual Reviews, LILACS (Literatura Latino Americana y del Caribe en CC de la Salud), Dialnet, and Scielo. The search strings consisted of key words related to “physical activity”, “accelerometry”, “child”, and “pediatric obesity” which are presented in the Supplementary Material. All identified studies were then critically examined to identify potentially eligible papers.

2.3. Study Selection and Data Collection

Two independent reviewers conducted the searches and analyzed the studies (J.M.J.-C. and F.J.L.-C.). Articles found were coded using the reference manager RefWorks [25], and discrepancies regarding the interpretation of the extracted data were discussed by both investigators. Moreover, the articles were filtered using the inclusion criteria. The dropout rate was studied for each study (<20%).
The search was divided into two phases. During the first search, articles were selected according to their title and summary/abstract. Articles that did not meet the inclusion criteria were discarded. In the second phase, the entire article was read and analyzed. Information from the articles was extracted regarding the number of participants, the countries in which the research had been carried out, the type and duration of the interventions, the percentage of both genders, and whether the studies included only children with obesity. In addition, specific data with regard to the use of accelerometry in each intervention were evaluated.

2.4. Risk of Bias in Individual Studies

Evaluation of the risk of bias was carried out following the recommendations of the Cochrane Collaboration [26]. For each study, seven domains were scored as having a high, low or unclear risk of bias. These domains were: sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome report, and other considered issues.

2.5. Statistical Analysis

A random-effects model method was used to measure the effect of the included studies, as it was more appropriate than a fixed-effects model due to the sample heterogeneity of the analysis. To perform the meta-analysis, the effect of the interventions with a principal component of PA was examined on BMI Z-score reduction and MVPA increase, comparing intervention with control groups. Data were obtained via mean and standard deviation from post-intervention selected data.
Another analysis was carried out using a fixed-effects analysis with studies only including children with obesity, due to sample homogeneity.
Some studies developed a PA intervention combined with nutritional recommendations. Therefore, a subgroup analysis was carried out to measure the effect of these interventions when focused on BMI Z-score reduction.
Meta-analysis outcomes were presented in forest plots as mean differences (MD) and 95% confidence interval (CI); each arm of a multi-arm study was presented separately. Heterogeneity (I2) was also presented. Heterogeneity was calculated by measuring its scope by the I2 index. The Q statistics were estimated, following a chi-square distribution with degrees of freedom n − 1 (n = number of studies included in the analysis). The authors examined the value of P for this statistic, warning of the presence of heterogeneity when P < 0.05, which compromises the validity of the pooled estimates [27]. Therefore, possible outliers were examined and sensitivity analysis was performed to explore the effect of removing some studies with results classified as outliers. After adjusting the sensitivity analysis, studies considering candidates acting as effect modifiers were excluded [28].
The available numeric data were extracted by the authors in Review Manager (RevMan, computer program) version 5.3. [29]. A value of P < 0.05 indicated statistical significance in all analyses. Results are shown in mean values followed by another value with the symbol ‘±’ (representing the standard deviation).

3. Results

3.1. Studies Selected

A flow chart diagram describes the selection of articles that were included in this meta-analysis (Figure 1). A total of 4656 papers were identified from the various included databases, following the review. A total of 1320 articles were deleted as duplicates, leaving a potential of 3336 papers to be selected for inclusion. A total of 3107 articles were eliminated for the following reasons: (1) the title or abstract was not associated with the aims; (2) they were not RCTs; or (3) the subjects did not meet the age criteria. Following this, 229 full text articles were considered to be potentially eligible according to the inclusion criteria. However, 179 were eliminated because the interventions did not include PA measures, and 40 were discarded because they did not include children with obesity in their samples. Thus, 10 articles were finally selected for the present meta-analysis, of which 4 studies included only children with obesity (Table 1).

3.2. Description of Selected Studies

The characteristics of the included RCTs are provided in Table 1. Four of the selected studies were carried out in the USA [30,31,32,33], two in New Zealand [34,35], one in Switzerland [36], others in Australia [37] and Malaysia [38], and one in Spain [39]. A total of 478 children (9 ± 1.57 years) participated in a PA intervention compared to 474 (9 ± 1.62 years) who were recruited to a control group without intervention. The dropout rate was studied for each intervention; a 16.3% average was obtained. The average intervention duration was 8.4 ± 6 months. Most of the PA interventions were accompanied by a lifestyle educational intervention, where the principal aim was to increase activity time and promote healthy behavioral habits [30,31,39]. Interventions with a nutritional component were based mainly on recommendations [32,35,37,38]. Alternatively, active video games (AVG) were incorporated [33,34]. Lifestyle education was included in six of these interventions.
To define obesity, different criteria were used in all of the included studies. Four studies [32,33,35,38] used the cut-off points of the Centers for Disease Control and Prevention of United States [40], three studies [34,37,39] went with the International Obesity Task Force [41], another study [36], applied Kromeyer-Hauschild et al. [42], and in other cases [30,31], nothing was referred to. The BMI Z-score ranged between 1.72 ± 0.52 and 2.92 ± 0.65 in the intervention groups, and between 1.55 ± 0.59 and 3.00 ± 0.49 in non-PA intervention groups.
Different protocols [43,44,45,46,47,48,49,50,51] in accelerometry measurements were described (Table 1). The ActiGraph was the most commonly used device to quantify PA, especially the GT3X + model. Wear time ranged between 5 [32,38] and 8 days [35,37,39]. The time spent engaged in MVPA ranged from 20.7 min [30] to 104.3 min [31] for the intervention groups. In contrast, engagement in the control groups was reported to range between 17.2 min [30] and 83.3 min [34] of MVPA.

3.3. Risk of Bias in Included Studies

Within the seven domains established to analyze the risk of bias, only three present noteworthy aspects. After comprehensively reading all of the selected articles, it remained unclear whether the blinding of participants, personnel, and outcome data had been correctly carried out for eight of the articles [30,31,32,33,34,36,38,39]. Furthermore, the inclusion of normal weight or overweight children as part of the intervention group resulted in a high risk of bias in six studies [30,33,34,35,37,39] (Figure S1).

3.4. Effects of the Interventions

To measure the effect of PA interventions, the BMI Z-score and time spent engaged in MVPA were analyzed. Of the 10 articles selected, two studies were excluded because they did not present BMI results as a Z-score [37,39]. Moreover, a further four studies were excluded from the MVPA analysis: Three showed the data as counts per min [36,37,38], and the other only showed the percentage of MVPA time [39].

3.4.1. BMI Reduction

The BMI Z-score was measured in eight studies included in the meta-analysis (MD −0.06; CI −0.15 to 0.03; P = 0.17; I2 = 88%) (Figure 2A). After a sensitivity analysis, O’Connor’s study [32] was excluded to reduce heterogeneity to a moderate level (MD −0.10; CI −0.17 to −0.03; P = 0.004; I2 = 53%) (Figure 2B). The first section included studies with PA intervention as the principal component [30,31,33,34,36], and a significant effect was found in the reduction of this variable (MD −0.12; CI −0.19 to −0.04; P = 0.002; I2 = 55%). Trost et al. [33] presented the highest proportion in this meta-analysis (35.7%), followed by Farpour-Lambert et al. [36]: (30.3%) (Figure 2B). The second section included interventions with nutritional recommendations [35,38] without effects (MD −0.03; CI −0.15 to 0.10; P = 0.65; I2 = 0%).
Additionally, a second analysis including only children with obesity [31,32,36,38] showed that protocols did not present a significant effect on the intervention (MD −0.01; CI −0.04 to 0.02; P = 0.53; I2 = 80%) (Figure 3A). However, after the sensitivity analysis excluding the O′Connor study [32], a significant effect was found in BMI reduction (MD −0.09; CI −0.15 to −0.03; P = 0.002; I2 = 55%). Farpour-Lambert et al. [36] showed the highest proportion in this sub-analysis (92.1%), compared to 4% in the study by Wafa et al. [38] and 3.9% in the Davis et al. study [31] (Figure 3B).

3.4.2. Engagement in Physical Activity

Regarding MVPA, the meta-analysis did not show effects on increasing the minutes of PA in the intervention groups compared with the control groups, although there was a high heterogeneity (MD 3.18 min; CI −0.63 to 7.00; P = 0.10; I² = 81%) (Figure 4A). After the sensitivity analysis excluded the O’Connor study [32], the meta-analyses showed a significant difference in the intervention and a reduction of heterogeneity without changing the direction of the outcome (MD 5.83 min; CI 4.13 to 7.52; P < 0.001; I² = 4%) (Figure 4B). Only one study showed significant changes following the intervention [33], with an increase in MVPA minutes in the intervention group with respect to the non-intervention group. In addition, Trost et al. [33] reported the greatest weight in the analysis (86.3%).

4. Discussion

The present meta-analysis provides evidence regarding the effectiveness of interventions with a PA component and lifestyle recommendations to reduce BMI Z-score in studies including children with obesity by increasing MVPA engagement. Increases were found in MVPA time in intervention groups compared with the control groups in the RCTs. However, these results should be interpreted with caution because the study by O′Connor et al. [32] must be excluded from the sensitivity analysis, due to the heterogeneity in the effect of the intervention, resulting in an outlier case of heterogeneity in the model. Nevertheless, forest plots shown in the meta-analysis before and after the sensitivity analysis indicate there was no variation in the direction of the meta-analysis effect in any of the cases. The only exception was in the PA intervention subgroups which included a nutritional recommendation; these changed the direction of the control group toward the intervention effect (Figure 2 and Figure 3).
The Tremblay et al. meta-analysis [52] reported significant reductions in BMI which were associated with a lower sedentary time. However, there are some limitations to this paper which must be considered. Firstly, children and adolescents (5 to 17 years old) were considered together, which may present a confounding factor in this analysis. Adolescents do not usually demonstrate the same habits or lifestyle as school children, with the latter experiencing greater parental control over their activities. Moreover, the intervention′s duration appears to be crucial when determining their effectiveness with regard to BMI changes. Our analysis was carried out on controlled and intervention groups based on mean differences among basal and post-intervention time using the variables BMI Z-score and MVPA time. Non-significant results, similar to those found by Nooijen et al. [7], were reached. Therefore, thereafter, the effect of PA interventions on how to reduce these variables was examined, selecting only post-intervention data for school-age children.
Considering the studies included in the present meta-analysis that reported validated data for this anthropometric variable, between 3 and 6 months are required to reduce BMI Z-score following involvement in a PA intervention [30,33,34,36,38]. These results are reinforced after the sub-analysis considering only studies with children with obesity [31,32,36] in which Farpour-Lambert et al. [36] represents 92.1% of the analysis weight. Therefore, it seems that engaging in three 60 min sessions [36] of controlled training by a physical education instructor a week is enough to begin a BMI Z-score improvement.
Combining an adequate time spent engaging in PA with an adequate intensity may lead to better changes—for example, a study combining aerobic and strength exercises showed a decrease in BMI [36]. In the present work, Trost et al. [33] showed the greatest weight in the analysis with the lowest BMI values after a PA intervention compared with the control group. This may be due combining PA practice (minimum of 60 min MVPA daily) with AVG. AVG have been suggested as a useful tool for increasing MVPA within the obese pediatric population and encouraging parents to substitute passive video games for these active games [34]. This tool seems to show a positive change from short to moderate PA time in participants aged between 3 and 17 years [53]. However, it is not clear if AVG are appropriate for reducing sedentary habits or whether they might promote increased passive gaming time. In addition, other protocols whose aims only included PA components [30] or telemedicine [31] did not find changes in BMI. Therefore, it seems that interventions not carried out under the direct supervision of a physical education instructor present lower effectiveness than online or indirect actions.
Nutritional intervention combined with PA intervention is another factor to be considered in the treatment of pediatric obesity. Four of the studies [32,35,37,38] included in the present meta-analysis reported good obesity control results despite the majority only including nutritional recommendations and not specific controlled interventions. The O’Connor’s study [32] was based on giving families nutritional advice but offered no limitations of specific foods. Wafa et al. [38] also gave parents behavioral change techniques during educational sessions, and Taylor et al. [35] proposed dietary objectives evaluated by questionnaires which obtained a specific healthy intake pattern score. Cliff et al. [37] included a dietary modification program, thus allowing parents to improve food behavior and diet quality.
A combination of PA and nutritional programs has been described as more effective at improving adiposity [54] or BMI Z-score [55], relative to PA or interventions with nutritional recommendations when delivered individually. A recent meta-analysis has also shown greater effectiveness through multidisciplinary interventions incorporating both nutrition and PA when delivered to overweight/obese children [13,56], although the weight of each intervention has not been shown. In our meta-analysis, the results obtained based on a BMI Z-score reduction showed a significant global effectiveness (Figure 2 and Figure 3). However, of the PA interventions with a complementary nutritional recommendation, only two studies [35,38] in the nutritional subgroup showed non-significant effectiveness. Therefore, PA seems to be an important component in BMI reduction in children with obesity.
In relation to the increase in MVPA practice, an intervention duration of between 4 and 6 months [30,33,34] generates an increase in minutes of engagement and intensity levels in children with obesity. Moreover, the effects of PA seem to be maintained long-term in interventions of up to 24 months [35]. Trost et al. [33] showed the greatest weight in the meta-analysis in favor of the intervention by increasing MVPA min in children with obesity, with an intervention based on an AVG program. It would be interesting to study how long the effects achieved by the AVG program last over a longer period of time. In addition, it would have been interesting to investigate whether these children adhere to outdoor PA, given that children’s motor skills and muscular strength development could be improved [57].

5. Limitations

There is very limited literature [31,32,36,38] focusing solely on obese school-aged children, regarding the number of PA component interventions and objectively accelerometry measured PA, which is recognized by the authors as a possible limitation. This meta-analysis incorporated studies where PA intervention was generally accompanied by other interventional components (Table 1), the reason being that the treatment of childhood obesity cannot be solely based on PA—it must be a multidisciplinary treatment including nutritional and motivational interventions. Moreover, many of the studies focused on lifestyle interventions, including different BMI groups or age groups. Therefore, the present meta-analysis is based principally on PA and BMI Z-score changes, although there are other (possible) susceptible factors to be included in the interventions. These studies may influence the participant´s level of BMI reduction acting as cofounding factors compared with PA only interventions; however, this subgroup analysis was shown in the forest plot.
Further, the mean reduction effect for the BMI Z-Score was (−0.09); although it produced a significant effect in meta-analysis results, this absolute value difference may not be clinically significant in treating childhood obesity.

6. Conclusions

In conclusion, this meta-analysis supports the notion that interventions with a PA component in school children with obesity seem to be successful in reducing BMI and produce an increase in time spent engaged in PA, especially MVPA. Therefore, interventions based on PA should be considered one of the main strategies to be implemented to fight childhood obesity.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/17/17/6031/s1, Figure S1: Assessment of risk of bias, Table S1: PRISMA Checklist, Appendix: Research strategy.

Author Contributions

Conceptualization, F.J.L.-C. and M.G.-C.; Data curation, J.M.J.-C. and F.J.L.-C.; Formal analysis, J.M.J.-C. and F.J.L.-C.; Funding Acquisition: M.G.-C.; Investigation, J.M.J.-C. and F.J.L.-C.; Methodology, J.M.J.-C. and F.J.L.-C.; Project Administration: M.G.-C.; Resources: M.G.-C.; Software, J.M.J.-C. and F.J.L.-C.; Supervision, F.J.L.-C. and H.G.-G.; Validation, M.G.-C.; Visualization, F.J.L.-C. and H.G.-G.; Writing—Original Draft Preparation, J.M.J.-C.; Writing—Review and Editing, J.M.J.-C., M.G.-C., H.G.-G., and F.J.L.-C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the project PI18/00930 MELIPOP, integrated in the Plan Estatal de I+D+I 2013-2016 and co-financed by the ISCIII-Subdirección General de Evaluación y Fomento de la investigación el Fondo Europeo de Desarrollo Regional (FEDER), and by the University of Córdoba.

Acknowledgments

This paper will be included in J.M.J-C.’s doctorate, under the “Social and Legal Sciences Program” at the University of Córdoba, Spain.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Katzmarzyk, P.T.; Chaput, J.-P.; Fogelholm, M.; Hu, G.; Maher, C.; Maia, J.; Olds, T.; Sarmiento, O.L.; Standage, M.; Tremblay, M.; et al. International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): Contributions to Understanding the Global Obesity Epidemic. Nutrients 2019, 11, 848. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Daniels, S.R. The consequences of childhood overweight and obesity. Future Child. 2006, 16, 47–67. [Google Scholar] [CrossRef] [PubMed]
  3. Gaziano, J.M. Fifth phase of the epidemiologic transition: The age of obesity and inactivity. JAMA 2010, 303, 275–276. [Google Scholar] [CrossRef]
  4. August, G.P.; Caprio, S.; Fennoy, I.; Freemark, M.; Kaufman, F.R.; Lustig, R.H.; Silverstein, J.H.; Speiser, P.W.; Styne, D.M.; Montori, V.M.; et al. Prevention and treatment of pediatric obesity: An endocrine society clinical practice guideline based on expert opinion. J. Clin. Endocrinol. Metab. 2008, 93, 4576–4599. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Matson, K.L.; Fallon, R.M. Treatment of Obesity in Children and Adolescents. J. Pediatr. Pharmacol. Ther. 2012, 17, 45–57. [Google Scholar]
  6. Khambalia, A.Z.; Dickinson, S.; Hardy, L.L.; Gill, T.; Baur, L.A. A synthesis of existing systematic reviews and meta-analyses of school-based behavioural interventions for controlling and preventing obesity. Obes. Rev. 2011, 13, 214–233. [Google Scholar] [CrossRef] [PubMed]
  7. Nooijen, C.F.J.; Galanti, M.R.; Engström, K.; Möller, J.; Forsell, Y. Effectiveness of interventions on physical activity in overweight or obese children: A systematic review and meta-analysis including studies with objectively measured outcomes. Obes. Rev. 2017, 18, 195–213. [Google Scholar] [CrossRef]
  8. Stice, E.; Shaw, H.; Marti, C.N. A meta-analytic review of obesity prevention programs for children and adolescents: The skinny on interventions that work. Psychol. Bull. 2006, 132, 667–691. [Google Scholar] [CrossRef] [Green Version]
  9. Cliff, D.P.; Okely, A.D.; Morgan, P.J.; Jones, R.A.; Steele, J.R. The impact of child and adolescent obesity treatment interventions on physical activity: A systematic review. Obes. Rev. 2009, 11, 516–530. [Google Scholar] [CrossRef]
  10. Biddle, S.J.H.; Braithwaite, R.; Pearson, N. The effectiveness of interventions to increase physical activity among young girls: A meta-analysis. Prev. Med. 2014, 62, 119–131. [Google Scholar] [CrossRef] [Green Version]
  11. Love, R.; Adams, J.; Van Sluijs, E.M.F. Are school-based physical activity interventions effective and equitable? A meta-analysis of cluster randomized controlled trials with accelerometer-assessed activity. Obes. Rev. 2019, 20, 859–870. [Google Scholar] [CrossRef] [PubMed]
  12. Migueles, J.H.; Cadenas-Sanchez, C.; Ekelund, U.; Nyström, C.D.; Mora-Gonzalez, J.; Löf, M.; Labayen, I.; Ruiz, J.R.; Ortega, F.B. Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations. Sports Med. 2017, 47, 1821–1845. [Google Scholar] [CrossRef] [PubMed]
  13. Oude Luttikhuis, H.; Baur, L.; Jansen, H.; Shrewsbury, V.A.; O’Malley, C.; Stolk, R.P.; Summerbell, C.D. Interventions for treating obesity in children. Cochrane Database Syst. Rev. 2009, 4, 1571–1729. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Pinto, R.M.; Silva, J.V.P.; Monteiro, G.M.C.; de Resende, R.C.; Clemente, R.D.; De Souza, C. Physical Activity: Benefits for Prevention and Treatment of Childhood Obesity. J. Child Obes. 2018, 3, S2-003. [Google Scholar] [CrossRef]
  15. Oliveira, R.G.; Guedes, D.P. Physical Activity, Sedentary Behavior, Cardiorespiratory Fitness and Metabolic Syndrome in Adolescents: Systematic Review and Meta-Analysis of Observational Evidence. PLoS ONE 2016, 11, e0168503. [Google Scholar] [CrossRef]
  16. Shrestha, R.; Copenhaver, M. Long-Term Effects of Childhood Risk Factors on Cardiovascular Health During Adulthood. Clin. Med. Rev. Vasc. Health 2015, 7, 1–5. [Google Scholar] [CrossRef] [Green Version]
  17. Ness, A.R.; Leary, S.D.; Mattocks, C.; Blair, S.N.; Reilly, J.J.; Wells, J.C.; Ingle, S.; Tilling, K.; Smith, G.D.; Riddoch, C. Objectively Measured Physical Activity and Fat Mass in a Large Cohort of Children. PLoS Med. 2007, 4, e97. [Google Scholar] [CrossRef] [Green Version]
  18. World Health Organization. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World; WHO: Geneva, Switzerland, 2018. [Google Scholar]
  19. Guthold, R.; Stevens, G.A.; Riley, L.M.; Bull, F.C. Global trends in insufficient physical activity among adolescents: A pooled analysis of 298 population-based surveys with 1·6 million participants. Lancet Child Adolesc. Health 2020, 4, 23–35. [Google Scholar] [CrossRef]
  20. McGuire, S. Institute of Medicine. 2012. Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. Washington, DC: The National Academies Press. Adv. Nutr. 2012, 3, 708–709. [Google Scholar] [CrossRef] [Green Version]
  21. Schwarzfischer, P.; Totzauer, M.; Gruszfeld, D.; Socha, P.; Luque, V.; Escribano, J.; Xhonneux, A.; Verduci, E.; Mariani, B.; Koletzko, B.; et al. BMI and recommended levels of physical activity in school children. BMC Public Health 2017, 17, 595. [Google Scholar] [CrossRef] [Green Version]
  22. Gori, D.; Guaraldi, F.; Cinocca, S.; Moser, G.; Rucci, P.; Fantini, M.P. Effectiveness of educational and lifestyle interventions to prevent paediatric obesity: Systematic review and meta-analyses of randomized and non-randomized controlled trials. Obes. Sci. Pract. 2017, 3, 235–248. [Google Scholar] [CrossRef] [PubMed]
  23. Metcalf, B.; Henley, W.; Wilkin, T. Effectiveness of intervention on physical activity of children: Systematic review and meta-analysis of controlled trials with objectively measured outcomes (EarlyBird 54). BMJ 2012, 345, e5888. [Google Scholar] [CrossRef] [Green Version]
  24. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred Reporting Items for Systematic reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Hendrix, I.C. RefWorks. J. Med. Libr. Assoc. 2004, 92, 111. [Google Scholar]
  26. Higgins, J.P.; Altman, D.G.; Gøtzsche, P.C.; Jüni, P.; Moher, D.; Oxman, A.D.; Savović, J.; Schulz, K.F.; Weeks, L.; Sterne, J.A.C. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011, 343, d5928. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Takkouche, B.; Cadarso-Suárez, C.; Spiegelman, D. Evaluation of old and new tests of heterogeneity in epidemiologic meta-analysis. Am. J. Epidemiol. 1999, 150, 206–215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Copas, J. Meta-analysis, funnel plots and sensitivity analysis. Biostatistics 2000, 1, 247–262. [Google Scholar] [CrossRef] [Green Version]
  29. Cochrane, T. Review Manager (RevMan) 5.3; The Nordic Cochrane Centre: Copenhagen, Denmark, 2008. [Google Scholar]
  30. Boudreau, A.D.A.; Kurowski, D.S.; Gonzalez, W.I.; Dimond, M.A.; Oreskovic, N.M. Latino families, primary care, and childhood obesity: A randomized controlled trial. Am. J. Prev. Med. 2013, 44, S247–S257. [Google Scholar] [CrossRef] [Green Version]
  31. Davis, A.M.; Sampilo, M.; Gallagher, K.S.; Landrum, Y.; Malone, B. Treating rural pediatric obesity through telemedicine: Outcomes from a small randomized controlled trial. J. Pediatr. Psychol. 2013, 38, 932–943. [Google Scholar] [CrossRef] [Green Version]
  32. O’Connor, T.M.; Hilmers, A.; Watson, K.; Baranowski, T.; Giardino, A.P. Feasibility of an obesity intervention for paediatric primary care targeting parenting and children: Helping HAND. Child Care Health Dev. 2011, 39, 141–149. [Google Scholar] [CrossRef]
  33. Trost, S.G.; Sundal, D.; Foster, G.D.; Lent, M.R.; Vojta, D. Effects of a Pediatric Weight Management Program With and Without Active Video Games. JAMA Pediatr. 2014, 168, 407. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Maddison, R.; Foley, L.; Ni Mhurchu, C.; Jiang, Y.; Jull, A.; Prapavessis, H.; Hohepa, M.; Rodgers, A. Effects of active video games on body composition: A randomized controlled trial. Am. J. Clin. Nutr. 2011, 94, 156–163. [Google Scholar] [CrossRef] [Green Version]
  35. Taylor, R.W.; Cox, A.; Knight, L.; Brown, D.A.; Meredith-Jones, K.; Haszard, J.J.; Dawson, A.M.; Taylor, B.J.; Williams, S.M. A Tailored Family-Based Obesity Intervention: A Randomized Trial. Pediatrics 2015, 136, 281–289. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Farpour-Lambert, N.J.; Aggoun, Y.; Marchand, L.M.; Martin, X.E.; Herrmann, F.R.; Beghetti, M. Physical Activity Reduces Systemic Blood Pressure and Improves Early Markers of Atherosclerosis in Pre-Pubertal Obese Children. J. Am. Coll. Cardiol. 2009, 54, 2396–2406. [Google Scholar] [CrossRef] [PubMed]
  37. Cliff, D.P.; Okely, A.D.; Morgan, P.J.; Steele, J.R.; Jones, R.A.; Colyvas, K.; Baur, L.A. Movement Skills and Physical Activity in Obese Children. Med. Sci. Sports Exerc. 2011, 43, 90–100. [Google Scholar] [CrossRef] [PubMed]
  38. Wafa, S.W.; Talib, R.A.; Hamzaid, N.H.; McColl, J.H.; Rajikan, R.; Ng, L.O.; Ramli, A.H.; Reilly, J.J. Randomized controlled trial of a good practice approach to treatment of childhood obesity in Malaysia: Malaysian Childhood Obesity Treatment Trial (MASCOT). Pediatr. Obes. 2011, 6, e62–e69. [Google Scholar] [CrossRef] [Green Version]
  39. Serra-Payá, N.; Ensenyat, A.; Castro-Viñuales, I.; Real, J.; Sinfreu-Bergues, X.; Zapata, A.; Mur, J.M.; Galindo-Ortego, G.; Solé-Mir, E.; Teixido, C. Effectiveness of a Multi-Component Intervention for Overweight and Obese Children (Nereu Program): A Randomized Controlled Trial. PLoS ONE 2015, 10, e0144502. [Google Scholar] [CrossRef] [Green Version]
  40. Ogden, C.L.; Kuczmarski, R.J.; Flegal, K.M.; Mei, Z.; Guo, S.; Wei, R.; Grummer-Strawn, L.M.; Curtin, L.R.; Roche, A.F.; Johnson, C.L. Centers for Disease Control and Prevention 2000 growth charts for the United States: Improvements to the 1977 National Center for Health Statistics version. Pediatrics 2002, 109, 45–60. [Google Scholar] [CrossRef] [Green Version]
  41. Cole, T.J.; Bellizzi, M.C.; Flegal, K.M.; Dietz, W.H. Establishing a standard definition for child overweight and obesity worldwide: International survey. BMJ 2000, 320, 1240. [Google Scholar] [CrossRef] [Green Version]
  42. Kromeyer-Hauschild, K.; Zellner, K. Trends in overweight and obesity and changes in the distribution of body mass index in schoolchildren of Jena, East Germany. Eur. J. Clin. Nutr. 2006, 61, 404–411. [Google Scholar] [CrossRef] [Green Version]
  43. Trost, S.G.; McIver, K.L.; Pate, R.R. Conducting Accelerometer-Based Activity Assessments in Field-Based Research. Med. Sci. Sports Exerc. 2005, 37, S531–S543. [Google Scholar] [CrossRef] [PubMed]
  44. Freedson, P.S.; Sirard, J.; Debold, E.; Pate, R.; Dowda, M.; Trost, S.; Sallis, J. Calibration of the computer science and applications, inc.(CSA) accelerometer 256. Med. Sci. Sports Exerc. 1997, 29, 45. [Google Scholar] [CrossRef]
  45. Sirard, J.R.; Melanson, E.L.; Li, L.; Freedson, P.S. Field evaluation of the Computer Science and Applications, Inc. physical activity monitor. Med. Sci. Sports Exerc. 2000, 32, 695–700. [Google Scholar] [CrossRef] [PubMed]
  46. Ekelund, U.L.; Sjöström, M.; Yngve, A.; Poortvliet, E.; Nilsson, A.; Froberg, K.A.; Wedderkopp, N.; Westerterp, K. Physical activity assessed by activity monitor and doubly labeled water in children. Med. Sci. Sports Exerc. 2001, 33, 275–281. [Google Scholar] [CrossRef] [PubMed]
  47. Freedson, P.S.; Pober, D.; Janz, K.F. Calibration of Accelerometer Output for Children. Med. Sci. Sports Exerc. 2005, 37, S523–S530. [Google Scholar] [CrossRef] [PubMed]
  48. Treuth, M.S.; Schmitz, K.; Catellier, D.J.; McMurray, R.G.; Murray, D.M.; Almeida, M.J.; Going, S.; Norman, J.E.; Pate, R. Defining accelerometer thresholds for activity intensities in adolescent girls. Med. Sci. Sports Exerc. 2004, 36, 1259–1266. [Google Scholar] [PubMed]
  49. Evenson, K.R.; Catellier, D.J.; Gill, K.; Ondrak, K.S.; McMurray, R.G. Calibration of two objective measures of physical activity for children. J. Sports Sci. 2008, 26, 1557–1565. [Google Scholar] [CrossRef]
  50. Reilly, J.J.; Coyle, J.; Kelly, L.; Burke, G.; Grant, S.; Paton, J.Y. An Objective Method for Measurement of Sedentary Behavior in 3- to 4-Year Olds. Obes. Res. 2003, 11, 1155–1158. [Google Scholar] [CrossRef]
  51. Puyau, M.R.; Adolph, A.L.; Vohra, F.A.; Butte, N.F. Validation and Calibration of Physical Activity Monitors in Children. Obes. Res. 2002, 10, 150–157. [Google Scholar] [CrossRef]
  52. Tremblay, M.S.; LeBlanc, A.G.; Kho, M.E.; Saunders, T.J.; Larouche, R.; Colley, R.C.; Goldfield, G.; Gorber, S.C. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 98. [Google Scholar] [CrossRef] [Green Version]
  53. LeBlanc, A.G.; Chaput, J.-P.; McFarlane, A.; Colley, R.C.; Thivel, D.; Biddle, S.J.H.; Maddison, R.; Leatherdale, S.T.; Tremblay, M.S. Active Video Games and Health Indicators in Children and Youth: A Systematic Review. PLoS ONE 2013, 8, e65351. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Okely, A.D.; Collins, C.E.; Morgan, P.J.; Jones, R.A.; Warren, J.M.; Cliff, D.P.; Burrows, T.L.; Colyvas, K.; Steele, J.R.; Baur, L.A. Multi-Site Randomized Controlled Trial of a Child-Centered Physical Activity Program, a Parent-Centered Dietary-Modification Program, or Both in Overweight Children: The HIKCUPS Study. J. Pediatr. 2010, 157, 388–394. [Google Scholar] [CrossRef]
  55. Shalitin, S.; Ashkenazi-Hoffnung, L.; Yackobovitch-Gavan, M.; Nagelberg, N.; Karni, Y.; Hershkovitz, E.; Loewenthal, N.; Shtaif, B.; Gat-Yablonski, G.; Phillip, M. Effects of a Twelve-Week Randomized Intervention of Exercise and/or Diet on Weight Loss and Weight Maintenance, and Other Metabolic Parameters in Obese Preadolescent Children. Horm. Res. 2009, 72, 287–301. [Google Scholar] [CrossRef] [PubMed]
  56. Hamid, M.S.A.; Sazlina, S.G. Interventions for obesity among schoolchildren: A systematic review and meta-analyses. PLoS ONE 2019, 14, e0209746. [Google Scholar] [CrossRef] [PubMed]
  57. Faigenbaum, A.D.; Rebullido, T.R.; MacDonald, J.P. Pediatric Inactivity Triad: A risky PIT. Curr. Sports Med. Rep. 2018, 17, 45–47. [Google Scholar] [CrossRef]
Ijerph 17 06031 g001 550
Figure 1. Flow diagram for the scientific paper selection from databases. RCTs, randomized controlled trials.
Figure 1. Flow diagram for the scientific paper selection from databases. RCTs, randomized controlled trials.
Ijerph 17 06031 g001
Ijerph 17 06031 g002 550
Figure 2. Effect interventions on BMI Z-score reduction. (A) BMI Z-score values forest plot. (B) Sensitivity analysis of BMI Z-score forest plot (O’Connor et al. study [32] not included). CI, confidence interval.
Figure 2. Effect interventions on BMI Z-score reduction. (A) BMI Z-score values forest plot. (B) Sensitivity analysis of BMI Z-score forest plot (O’Connor et al. study [32] not included). CI, confidence interval.
Ijerph 17 06031 g002
Ijerph 17 06031 g003 550
Figure 3. Effect interventions on BMI Z-score reduction in studies only including children with obesity. (A) BMI Z-score values forest plot. (B) Sensitivity analysis of BMI Z-score forest plot (O’Connor et al. [32] study not included). CI, confidence interval.
Figure 3. Effect interventions on BMI Z-score reduction in studies only including children with obesity. (A) BMI Z-score values forest plot. (B) Sensitivity analysis of BMI Z-score forest plot (O’Connor et al. [32] study not included). CI, confidence interval.
Ijerph 17 06031 g003
Ijerph 17 06031 g004 550
Figure 4. Effect interventions on increased moderate to vigorous physical activity time in minutes. (A) Moderate to vigorous physical activity levels forest plot. (B) Sensitivity analysis of moderate to vigorous physical activity forest plot (O’Connor et al. [32] not included). CI, confidence interval.
Figure 4. Effect interventions on increased moderate to vigorous physical activity time in minutes. (A) Moderate to vigorous physical activity levels forest plot. (B) Sensitivity analysis of moderate to vigorous physical activity forest plot (O’Connor et al. [32] not included). CI, confidence interval.
Ijerph 17 06031 g004
Table
Table 1. Characteristics of selected studies by interventions content physical activity and accelerometry [30,31,32,33,34,35,36,37,38,39].
Table 1. Characteristics of selected studies by interventions content physical activity and accelerometry [30,31,32,33,34,35,36,37,38,39].
StudyGroupSample (n)Included Only Obese Children (Yes/No) /Obese Children (%)Gender (%F)Treatment LengthIntervention
Type		Treatment Content PAAccelerometerAccelerometer TimeAuthor Accelerometer Protocol
Arauz-Boudreau et al. (2013)Control

Intervention		12

14		No/NR61%6 monthsLifestyle educational classes and PA training sessions5 consecutive weekly sessions, increased to six 3 months later.ActiGraph GT1MComplete week; ≥8
hours on ≥4 days		Trost, 2005
Cliff et al. (2011)Control

Intervention		42

60		No/78%58%12 monthsPA skill development program and dietary modification programs aimed at parents6 months intervention divided into two components: 10-week face to face and 3 months with minimal contact. The first phase of treatment included weekly 2 h group sessions (90 min PA per session) and weekly ‘‘home challenge’’ activities.ActiGraph 7164≥8 consecutive days during waking hoursFreedson, 1997
Davis et al. (2013)Control

Intervention		27

31		Yes/100%39%8 monthsMultidisciplinary actions based on psychoeducational group sessions delivered via telemedicineSession over the phone with parents to encourage healthy habits. 1-h duration for 8 weeksActiGraphComplete week; ≥6 h on ≥3 daysSirard, 2000
Farpour-Lambert et al. (2009)Control

Intervention		22

22		Yes/100%64%3 months (3 months post-intervention)PA training sessionsThe exercise group trained 60 min 3 times/week for 3 months.ActiGraph MT 6471Complete week; 24 h/day on ≥4 days (including 1 weekend day)Ekelund, 2001
Maddison et al. (2011)Control

Intervention		162

160		No/NR37%6 monthsActive video gamesChildren were encouraged to meet the current PA recommendations by supplementing periods of inactivity or substituting periods of traditional non-active video games for playing AVG.ActiGraph AM7164-2.2CComplete weekFreedson, 2005
O’Connor et al. (2013)Control

Intervention		20

20		Yes/100%80%7 monthsHealthy family activity and nutritional recommendationsPromote healthy child lifestyle behavior with effective behavior-specific parenting practicesActiGraph 7064≥5 days; ≥800 min/dayTreuth, 2004
Serra-Paya et al. (2015)Control

Intervention		59

54		No/NR44%8 monthsPA sessions, theoretical and practical sessions for parents, behavior strategy sessions for both children and parents, and weekend activities.90 min PA session—3 ses/w for 8 monthsActiGraph GT3X+≥8 consecutive days during waking hoursNR
Taylor et al. (2015)Control

Intervention		102

104		No/NR55%24 monthsFamily-based intervention with specific goals based on dietary intake and PAFamilies attended monthly multidisciplinary sessions to develop specific goals suitable for the first year. Thereafter, every third month for another 12 months to discuss progress and provide support.ActiGraph GT3XComplete week; ≥8
hours on ≥4 days		Evenson, 2008
Trost et al. (2014)Control

Intervention		41

34		No/35,7%55%4 monthsLifestyle educational parents and programmed active gaming24 session topics about aspects of nutrition, sleep hygiene, PA, screen time, and AVG 60 min PA AVG sessionActiGraph GT3X / GT3X+Complete week; ≥9 h on ≥3 daysEvenson, 2008
Wafa et al. (2011)Control

Intervention		55

52		Yes/100%50%6 monthsInformation based nutrition and health education60 min PA intervention sessions (8 sessions for 6 months)ActiGraph GT1M5 days; ≥10 h on ≥4 daysReilly, 2003
Puyau, 2002
AVG, active video games; F, female; NR, not referred; PA, physical activity; ses/w, sessions per week.

Share and Cite

MDPI and ACS Style

Jurado-Castro, J.M.; Gil-Campos, M.; Gonzalez-Gonzalez, H.; Llorente-Cantarero, F.J. Evaluation of Physical Activity and Lifestyle Interventions Focused on School Children with Obesity Using Accelerometry: A Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2020, 17, 6031. https://doi.org/10.3390/ijerph17176031

AMA Style

Jurado-Castro JM, Gil-Campos M, Gonzalez-Gonzalez H, Llorente-Cantarero FJ. Evaluation of Physical Activity and Lifestyle Interventions Focused on School Children with Obesity Using Accelerometry: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2020; 17(17):6031. https://doi.org/10.3390/ijerph17176031

Chicago/Turabian Style

Jurado-Castro, Jose Manuel, Mercedes Gil-Campos, Hugo Gonzalez-Gonzalez, and Francisco Jesus Llorente-Cantarero. 2020. "Evaluation of Physical Activity and Lifestyle Interventions Focused on School Children with Obesity Using Accelerometry: A Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 17, no. 17: 6031. https://doi.org/10.3390/ijerph17176031

APA Style

Jurado-Castro, J. M., Gil-Campos, M., Gonzalez-Gonzalez, H., & Llorente-Cantarero, F. J. (2020). Evaluation of Physical Activity and Lifestyle Interventions Focused on School Children with Obesity Using Accelerometry: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health, 17(17), 6031. https://doi.org/10.3390/ijerph17176031

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop