CONTEXT

High-intensity interval training (HIIT) has been widely used to prevent and treat cardiovascular risk factors in adolescents and adults; nevertheless, the available evidence in children is scarce.

OBJECTIVE

To synthesize evidence regarding the effectiveness of HIIT interventions on improving cardiovascular risk factors and cardiorespiratory fitness (CRF) in children from 5 to 12 years old.

DATA SOURCES

We searched 5 databases, Medline, Embase, SPORTDiscus, the Cochrane Library, and Web of Science.

STUDY SELECTION

Randomized controlled trials (RCTs) evaluating the effectiveness of HIIT interventions on cardiometabolic risk factors and CRF in children were included.

DATA EXTRACTION

Meta-analyses were conducted to determine the effect of HIIT on body composition, cardiometabolic and CRF variables in comparison with nontraining control groups.

RESULTS

A total of 11 RCTs and 512 participants were included. The results of the meta-analysis revealed a significant improvement in peak oxygen uptake (standardized mean difference [SMD] = 0.70, 95% confidence interval [CI] = 0.28 to 1.12; P = 0.001], in total cholesterol [SMD = −1.09, 95% CI = −1.88 to −0.30; P = 0.007], in low-density lipoprotein cholesterol [SMD = −1.28, 95% CI = −2.34 to −0.23; P = 0.017] and triglycerides [SMD = −0.71, 95% CI = −1.15 to −0.28; P = 0.001) levels.

LIMITATIONS

Because of the small number of available RCTs, it was not possible to conduct a subgroup analysis or a linear meta-regression analysis.

CONCLUSIONS

HIIT is a feasible and time-efficient approach for improving CRF, total cholesterol, low-density lipoprotein cholesterol, and triglycerides levels in children.

Clustering of risk factors in childhood may persist into youth, adolescence, and adult life, making their prevention an important goal in public health.1  Among the most recognized cardiovascular risk factors in children are the altered blood lipid profile (triglycerides, total cholesterol [TC], high-density lipoprotein cholesterol [HDL]), elevated blood pressure, and obesity.2  Frequently, these risk factors tend to aggregate and often appear combined in individuals.

Physical activity (PA) is one of the most important healthy lifestyles to prevent childhood obesity and to contribute important benefits to other cardiovascular risk factors in children.3,4  There is accumulating evidence about the effectiveness of school-based PA interventions to prevent obesity and reduce blood pressure and other cardiometabolic markers in children and adolescents. However, there is not enough evidence about which PA features are best.5,6 

Similarly, there is evidence suggesting that both PA and cardiorespiratory fitness (CRF) are independently related to the individual and composite scores related to cardiometabolic risk factors in children.7  In fact, researchers in a recent study concluded that CRF is a marker of cardiovascular health in children and adolescents, such that higher levels of CRF are associated with better cardiovascular health.810 

School-based PA interventions are one of the most accessible ways to practice PA11  and to improve CRF in children12 ; moreover, in recent years, the number of school-based interventions that include high-intensity interval training (HIIT) as a type of PA have increased. There is no concise definition for HIIT because of the variations in intervals and intensity; nevertheless, broadly, HIIT could be defined as a PA protocol which consists short and repeated bouts of high-intensity, close to maximal intensities, and interspersed by periods of lower intensity exercise or rest for recovery.13 

One advantage of HIIT programs is that they are a potent and time-efficient form of PA and health promotion14,15 ; in addition, HIIT corresponds to children's natural pattern of movement and play, with short periods of high-intensity activity,16  which may result in higher levels of compliance and could be a useful tool to provoke positive long-term behavioral changes. Moreover, studies performed with children and adolescents have shown that HIIT is more efficient than continuous or interval training at low or moderate intensity to decrease blood pressure and improve CRF.17  These facts, among others, have led to an increase in studies aimed at analyzing the evidence about the effectiveness of HIIT to prevent obesity and improve cardiovascular risk factors in adults and adolescents.18,19  However, although there are some reviews and meta-analyses examining the effectiveness of HIIT to improve cardiometabolic markers in children and adolescents,2023  there are no meta-analyses in which only randomized controlled trial (RCT) studies with a more homogeneous population of studies on school-aged children are included.

For this reason, the aim of this meta-analysis was to synthesize evidence regarding the effectiveness of HIIT interventions on improving cardiovascular risk factors such as obesity, hypercholesterolemia, CRF, and blood pressure in schoolchildren from 5 to 12 years old.

The study was conducted on the basis of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement24  and followed the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions.25  This meta-analysis was registered with the PROSPERO International prospective register of systematic reviews database (CRD42018093432). In addition, a previous protocol of this study has been published.26 

The literature search examined Medline (via PubMed), Embase (via Scopus), SPORTDiscus, the Cochrane Library, and the Web of Science databases. The systematic search was conducted from inception through April 2021. In addition, when relevant full-text articles and systematic reviews were identified in the database search results, relevant references included in the selected studies were hand searched for related studies. The following search strategy was applied: (“High Intensity Interval Training” OR “High Intensity Intermittent Exercise” OR “High Intensity Interval Exercise” OR “Intermittent Training” OR “HIIT”) AND (Child OR “School-Aged” OR Prepubertal OR Preadolescent) AND (obesity OR BMI OR “body fat percentage” OR “body composition” OR fitness OR “cardiorespiratory fitness” OR “cardiovascular risk factors” OR “blood pressure” OR triglyceride OR lipids OR cholesterol OR “waist circumference” OR “glycemia” OR “glucose” OR “insulin”) AND (“randomized controlled trial” (see Supplemental Table 2 for the Medline database search strategy). Restrictions based on language were made, such that only studies written in English were included. The included articles were RCTs in which the authors assessed HIIT for improving body composition, cardiometabolic risk factors, and/or CRF in children, in which the control group (CG) did not receive any PA intervention. Observational, systematic reviews of prospective cohort studies and RCTs performed with adolescents or adults were excluded. Study records were managed by using the Mendeley Desktop 1.13 reference manager.

Two authors (M.S.M. and D.P.P.C.) separately examined the titles and abstracts of potentially eligible studies identified by the search strategy, and any disagreement in study selection was resolved by consensus or with a third investigator (A.H.A.).

The inclusion criteria were as follows: (1) Participants were children from 5 to 11 years of age regardless of their weight status. (2) Type of study was an RCT in which the CG did not receive any PA intervention. (3) HIIT interventions were prescribed as high-intensity exercise; the intensity was ≥90% peak oxygen uptake (Vo2peak) that had an intensity that was ≥100% maximal aerobic speed (MAS) and/or ensured that the participant´s heart rate (HR) was ≥90% of their peak HR. Studies were also included if HIIT was combined with the nutritional intervention used in the CG. (4) Primary outcome measures: changes in obesity in the form of BMI and body composition in the form of body fat percentage (BF%), changes in the levels of some cardiometabolic risk factors, such as systolic blood pressure (SBP) and diastolic blood pressure (DBP), TC, low-density lipoprotein cholesterol (LDL) and HDL cholesterol, and triglycerides, and changes in the CRF assessed as Vo2peak and maximal heart rate (HRmax). There were no exclusion criteria in terms of intervention exercise modality, number of repetitions, number of series, or between-series recovery duration or intensity.

Two authors (M.S.M. and D.P.P.C.) independently reviewed each published study and extracted the following data: (1) author identification, (2) year of publication, (3) characteristics of participants (number, age, and weight status), (4) characteristics of HIIT intervention (type, duration, modality, and intensity), (5) outcomes, and (6) means and SDs of obesity, body composition, cardiometabolic, and CRF variables from pre- to postintervention between groups (HIIT versus CG). When we encountered missing or unclear data, we emailed corresponding authors for additional information.

The risk of bias assessment was conducted by using the RoB 2.0 tool established by the Cochrane Collaboration.27  This version includes 5 domains: bias arising from the randomization process, bias because of deviations from intended interventions, bias because of missing outcome data, bias in measurement of the outcome, and bias in selection of the reported result. Each domain is scored as high risk, some concerns or low risk. A sixth domain, overall bias, will have a low-risk result if the other domains are of low risk, some concerns if there are some domains assessed with some concerns, and high risk if there are one or more domains with high risk of bias.

We performed an additional analysis by removing those studies scoring “high risk” in the overall bias domain to assess the robustness of the summary estimates.

Meta-analyses were conducted to determine the effect of HIIT on obesity, body composition, and cardiometabolic and CRF variables compared with nontraining CGs. For studies that included both nontraining CGs and moderate-intensity PA comparison groups, only the CG data were included in the meta-analyses. The effect size (ES) using Cohen’s d index28  was calculated as the standardized mean difference (SMD) in the variables from pre- to postintervention between groups (HIIT versus CG) by using a random effects model29  (DerSimonian-Laird approach). Negative ES values indicated a decrease in the variables in favor of the HIIT group over CG, with the exception of HDL and Vo2peak, for which a positive ES value indicated an improvement. Finally, the ES of all included studies were pooled to estimate an overall summary ES, with a 95% confidence interval (CI) by using a random effects model. All analyses were conducted by using Comprehensive Meta-analysis Software (2nd version, Biostat, Englewood, NJ) and StataSE software, version 16 (StataCorp, College Station, TX).

Heterogeneity among studies was estimated by using the I2 statistic, with values that were classified as follows: no relevant heterogeneity (0% to 40%), moderate heterogeneity (30% to 60%), substantial heterogeneity (50% to 90%) and considerable heterogeneity (75% to 100%). The corresponding P values and 95% CI for I2 were also measured.25 

For each pooled ES, we conducted a sensitivity analysis by eliminating the studies one by one to assess the robustness of the summary estimates and to detect whether any study accounted for a large proportion of heterogeneity.

Finally, publication bias was graphically evaluated using a funnel plot, as well as with the method proposed by Egger.30 

Systematic Review

The search retrieved a total of 400 articles, of which 32 were duplicates. After screening the titles and abstracts of the remaining 368 studies, 344 were not included on the basis of the previously described inclusion criteria, leaving 24 full-text articles to be reviewed. Of those, 13 were excluded, leaving 11 articles for the final meta-analysis.3141  The reasons for exclusion based on full texts are reported in Supplemental Table 3. The PRISMA flow diagram is shown in Fig 1.

FIGURE 1

PRISMA flow diagram of the study selection process.

FIGURE 1

PRISMA flow diagram of the study selection process.

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Study Characteristics

The main characteristics of the 11 RCTs and 512 participants included are summarized in Table 1. The studies were published between 2004 and 2021; of the 11 included studies, 4 studies enrolled subjects with overweight and/or obesity,3134  1 study included subjects with normal weight and obesity,35  and 6 studies included subjects with normal weight.3641  Three studies included boys only,31,33,40  and the 8 remaining studies included both boys and girls.32,3439,41  Ten studies enrolled children <12 years old,31,3341  and regarding the Dias et al study,32  which included children in the age range of 7 to 16 years old, the authors provided us with data for the children aged 7 to 12 years old. Two studies were conducted in a school setting,35,40  and 9 studies were conducted in a clinical setting.3134,3639,41  The durations of interventions in the included studies were 6 weeks,34,35  7 weeks,38,41  8 weeks,36,37,39,40  and 12 weeks.3133  Exercise training sessions were implemented twice a week in 4 studies,3537,39  and there were 3 sessions per week for 7 studies.3134,38,40,41  The mode of HIIT interventions primarily involved running in 7 studies31,34,3639,41 ; 3 studies administered a cycling protocol32,33,40 ; and in the remaining study, the exercise modality was child-specific games.35 

TABLE 1

Characteristics of Studies Included in the Meta-analysis

Author, Year PublishedSample PopulationDuration, wkGroup, nModality/IntensityRepeated Bouts/FrequencyExercise Bout/Recovery DurationProtocol Duration (Including Recovery)Outcome Measures
Paahoo et al,31  2021 Overweight/obesity boys: n = 30; 9–12 y 12 HIIT (15), CG (15) — Bouts:10 (3 times weekly) 10 s/3–4 min 45 min BMI, %BF, TC, HDL, LDL, triglycerides 
Dias et al,32  2018 Obesity children; n = 67; 7–12a12 HIIT (33), CG (34) Cycling (85% to 95% HRmaxBouts: 4 (3 times weekly) 4 min/3 min 40 min BMI, %BF, TC, HDL, LDL, triglycerides, Vo2peak, HRmax 
Chuensiri et al,33  2017 Obesity boys; n = 48; 8–12 y 12 HIIT (16), CG (16) Cycling (90% Vo2peakBouts:8; 1-min rest between set (3 times weekly) 2 min/1 min 24 min BMI, %BF, TC, HDL, LDL, triglycerides, SBP, DBP, Vo2peak 
Lau et al,34  2015 Overweight children: n = 48; 10.4±0.9 y HIIT (15), CG (27) Shuttle runs (120% MAS) Bouts: 12 (3 times weekly) 15 s/15 s 6 min BMI, HRmax 
Lambrick et al,35  2015 Obese and normal wt children; n = 55; 8–10 y HIIT (28), CG (27) Child-specific games (93% mean HRmaxBouts: 7 (2 times weekly) 6 min/ 2 min 60 min BMI, %BF, Vo2peak, HRmax 
Mucci et al,36  2013 Normal wt children; n = 18; 9–11 y HIIT (9), CG (9) Shuttle runs (100% to 130% MAS) Bouts: 1; sets: 4; 3-min rest between set (2 times weekly) 10–20 s/10–20 s 30 min Vo2peak 
Rosenkranz et al,37  2012 Normal wt children; n = 16; 7–12 y HIIT (8), CG (9) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 4 times (2 times weekly) 10–20 s/ 10–20s 30 min BMI, %BF, SBP, DBP, TC, HDL, LDL, triglycerides, Vo2peak, HRmax 
Baquet et al,38  2010 Normal wt children; n = 77; 8–11 y HIIT (22), CG (20) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 1–4; 3-min rest between set (3 times weekly) 10–30 s/10–30 s 25–35 min BMI, Vo2peak, HRmax 
Nourry et al,39  2005 Normal wt children; n = 18; 10.3±0.8 y HIIT (9), CG (12) Shuttle runs (100% to 130% MAS) Bouts: 10; sets: 4 times; 3-min rest between set (2 times weekly) 10–20 s/ 10–20 s 30 min %BF, Vo2peak, HRmax 
McManus et al,40  2005 Normal wt boys; n = 35; 9–11 y HIIT (10), CG (10) Cycling (power elicited at Vo2peakBouts: 7 (3 times weekly) 30 s/45 s 20 min Vo2peak, HRmax 
Baquet et al,41  2004 Normal wt children; n = 100; 9.7±0.8 y HIIT (47), CG (53) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 1–4; 3-min rest between set (3 times weekly) 10–20 s/10–20 s 30 min %BF 
Author, Year PublishedSample PopulationDuration, wkGroup, nModality/IntensityRepeated Bouts/FrequencyExercise Bout/Recovery DurationProtocol Duration (Including Recovery)Outcome Measures
Paahoo et al,31  2021 Overweight/obesity boys: n = 30; 9–12 y 12 HIIT (15), CG (15) — Bouts:10 (3 times weekly) 10 s/3–4 min 45 min BMI, %BF, TC, HDL, LDL, triglycerides 
Dias et al,32  2018 Obesity children; n = 67; 7–12a12 HIIT (33), CG (34) Cycling (85% to 95% HRmaxBouts: 4 (3 times weekly) 4 min/3 min 40 min BMI, %BF, TC, HDL, LDL, triglycerides, Vo2peak, HRmax 
Chuensiri et al,33  2017 Obesity boys; n = 48; 8–12 y 12 HIIT (16), CG (16) Cycling (90% Vo2peakBouts:8; 1-min rest between set (3 times weekly) 2 min/1 min 24 min BMI, %BF, TC, HDL, LDL, triglycerides, SBP, DBP, Vo2peak 
Lau et al,34  2015 Overweight children: n = 48; 10.4±0.9 y HIIT (15), CG (27) Shuttle runs (120% MAS) Bouts: 12 (3 times weekly) 15 s/15 s 6 min BMI, HRmax 
Lambrick et al,35  2015 Obese and normal wt children; n = 55; 8–10 y HIIT (28), CG (27) Child-specific games (93% mean HRmaxBouts: 7 (2 times weekly) 6 min/ 2 min 60 min BMI, %BF, Vo2peak, HRmax 
Mucci et al,36  2013 Normal wt children; n = 18; 9–11 y HIIT (9), CG (9) Shuttle runs (100% to 130% MAS) Bouts: 1; sets: 4; 3-min rest between set (2 times weekly) 10–20 s/10–20 s 30 min Vo2peak 
Rosenkranz et al,37  2012 Normal wt children; n = 16; 7–12 y HIIT (8), CG (9) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 4 times (2 times weekly) 10–20 s/ 10–20s 30 min BMI, %BF, SBP, DBP, TC, HDL, LDL, triglycerides, Vo2peak, HRmax 
Baquet et al,38  2010 Normal wt children; n = 77; 8–11 y HIIT (22), CG (20) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 1–4; 3-min rest between set (3 times weekly) 10–30 s/10–30 s 25–35 min BMI, Vo2peak, HRmax 
Nourry et al,39  2005 Normal wt children; n = 18; 10.3±0.8 y HIIT (9), CG (12) Shuttle runs (100% to 130% MAS) Bouts: 10; sets: 4 times; 3-min rest between set (2 times weekly) 10–20 s/ 10–20 s 30 min %BF, Vo2peak, HRmax 
McManus et al,40  2005 Normal wt boys; n = 35; 9–11 y HIIT (10), CG (10) Cycling (power elicited at Vo2peakBouts: 7 (3 times weekly) 30 s/45 s 20 min Vo2peak, HRmax 
Baquet et al,41  2004 Normal wt children; n = 100; 9.7±0.8 y HIIT (47), CG (53) Shuttle runs (100% to 130% MAS) Bouts: 5–10; sets: 1–4; 3-min rest between set (3 times weekly) 10–20 s/10–20 s 30 min %BF 
a

Dias et al provided us with data for children aged 7 to 12. —, unavailable.

Main Outcomes

With the exception of 2 studies,36,40  all of the remaining studies assessed body composition or obesity indicators. Dual radiograph absorptiometry was used in 1 study,35  bioimpedance analysis in 2 studies,33,35  both dual radiograph absorptiometry and bioimpedance in 1 study,37  skinfold thickness measurements in 4 studies,31,34,39,41  and BMI measurements in 2 studies.31,38 

The CRF parameters were assessed jointly in 7 studies with measurements of Vo2peak and HRmax.32,3540  Three out of these 7 studies used an incremental maximal test performed in the laboratory,32,35,38  and in the remaining studies, the exercise test was conducted on a magnetic brake bicycle ergometer. Chuensiri et al33  assessed only Vo2peak with the exercise test on a magnetic brake bicycle ergometer, and the “YoYo intermittent field test” was used in 1 study with measurement of only HRmax.34 

Cardiometabolic risk blood markers were assessed in 4 studies,3133,37  and blood pressure markers were assessed in 2 studies.33,37 

Risk of Bias

Methodologic “risk of bias” scores were assessed on the basis of the RoB 2.0 tool27 : 4 studies3133,35  were assessed as “low risk of bias”; 3 studies37,39,40  were assessed as “some concerns”; and 4 studies34,36,38,41  were assessed as “high risk of bias” (Fig 2). In the studies deemed to have a high or some risk of bias,34,36,38,41  the bias arose from the randomization process.

FIGURE 2

Risk of bias assessments for included RCT (RoB 2.0).

FIGURE 2

Risk of bias assessments for included RCT (RoB 2.0).

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Meta-analysis

BMI

The ESs in individual studies ranged from −0.37 to 0.26 (n = 7). There was no significant effect of HIIT on BMI (SMD = −0.01, 95% CI = −0.25 to 0.23; P = .96) and no significant heterogeneity (I2 = 0%; P = .94) (Fig 3).

FIGURE 3

Pooled ES (Cohen’s d) forest plot for BMI and BF%.

FIGURE 3

Pooled ES (Cohen’s d) forest plot for BMI and BF%.

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BF%

The ESs in individual studies ranged from −0.89 to 0.00 (n = 7). There was no significant effect of HIIT on BF% (SMD = −0.16, 95% CI = −0.40 to 0.07; P = .178) and no significant heterogeneity (I2 = 0%; P = .63) (Fig 3).

Vo2peak

The ESs in individual studies ranged from −0.35 to 1.35 (n = 8). The results of the meta-analysis indicated a significant effect of HIIT on Vo2peak (SMD = 0.70, 95% CI = 0.28 to 1.12; P = .001) (Fig 4). However, there was heterogeneity and moderate inconsistency in the effects of HIIT (I2 = 59%; P = .02).

FIGURE 4

Pooled ES (Cohen’s d) forest plot for Vo2peak and HRmax.

FIGURE 4

Pooled ES (Cohen’s d) forest plot for Vo2peak and HRmax.

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HRmax

The ESs in individual studies ranged from −0.72 to 0.64 (n = 8). There was no significant effect of HIIT on HRmax (SMD = 0.12, 95% CI = −0.18 to 0.41; P = .45) and no significant heterogeneity (I2 = 30%; P = .19) (Fig 4).

Blood Pressure

The ESs in individual studies ranged from −0.23 to −0.08 (n = 2) for SBP and −0.17 to −0.15 (n = 2) for DBP. There were no significant effects of HIIT on SBP (SMD = −0.17, 95% CI = −0.80 to 0.47; P = .61) or DBP (SMD = −0.16, 95% CI = −0.80 to 0.48; P = .62) (Fig 5) and no significant heterogeneity (I2 = 0%, P = .81; I2 = 0%, P = .97, respectively).

FIGURE 5

Pooled ES (Cohen’s d) forest plot for blood pressure–related outcomes.

FIGURE 5

Pooled ES (Cohen’s d) forest plot for blood pressure–related outcomes.

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Lipid Profile

The ESs in individual studies ranged from −2.27 to −0.49 (n = 4) for TC, −0.30 to 1.75 (n = 4) for HDL, −2.75 to −0.33 (n = 4) for LDL, and −1.17 to −0.38 (n = 4) for triglycerides. There was a significant effect of HIIT on TC (SMD = −1.09, 95% CI = −1.88 to −0.30; P = .007), LDL (SMD = −1.28, 95% CI = −2.34 to −0.23; P = .017), and triglycerides (SMD = −0.71, 95% CI = −1.15 to −0.28; P = .001). There was no significant effect of HIIT on HDL (SMD = 0.39, 95% CI = −0.51 to 1.30; P = .395). There was significant heterogeneity and high inconsistency for all variables except triglycerides (Fig 6).

FIGURE 6

Pooled ES (Cohen’s d) forest plot for lipid-related outcomes.

FIGURE 6

Pooled ES (Cohen’s d) forest plot for lipid-related outcomes.

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Publication Bias and Sensitivity Analysis

Both funnel plot asymmetry and Egger’s test revealed no significant publication bias for any of the outcome variables. In the sensitivity analysis, when each study was deleted one by one from the model, the results remained the same across all deletions.

This meta-analysis identified data on >500 school-aged children from RCTs revealing that HIIT can significantly improve CRF (Vo2peak) and blood lipids (TC, LDL, and triglycerides) in comparison with nontraining CG conditions. However, the effects of HIIT on obesity or body composition indicators (BMI and BF%), blood pressure (SBP and DBP), HDL, and HRmax were not statistically significant.

Regarding CRF, our meta-analysis obtained results that are in line with those showing the benefit of HIIT on CRF in children and adolescents between 6 and 17 years,22,42  in overweight and obese youth,17  and in adults with normal weight, overweight or obesity.19 

Specifically, our meta-analysis revealed that HIIT had a statistically significant effect on CRF (Vo2max, SMD = 0.70; WMD = 4.10 mL/kg per minute; P = .001). Comparing the size of this effect with those shown by other studies, our results exceed those of a previous review in which authors examined the effect of HIIT in children and adolescents showing statistically significant effects for Vo2max ranging from 1.6 to 3.7 mL/kg per minute.43 In this regard, a previous study showed that an improvement in CRF by 1 mL/kg per minute, assessed by a maximum bike test, decreased the risk of developing overweight or obesity by 10% in 6 years,44 highlighting the clinical usefulness of HIIT. Therefore, HIIT appears to confer numerous health benefits, because there is strong and consistent evidence from epidemiological studies that a low CRF is associated with increased morbidity and mortality from all causes, including cardiovascular disease and cancer.45 

Although HRmax is a crucial determinant of CRF by incrementing cardiac output in the Fick equation, our meta-analysis did not find any significant change in HRmax after exposure to a HIIT program, suggesting that other central or peripheral factors are involved in the observed CRF improvement. This is consistent with the literature that has shown that variations in maximal stroke volume (central adaptations) or increases in muscle oxidative potential and the ability to extract and use available oxygen (peripheral adaptation), rather than HRmax, are mainly related to the benefits found in CRF in response to exercise.46,47 

In our work, HIIT positively influenced plasma concentrations of atherogenic lipids, with significant reductions and large effects on TC, LDL, and triglycerides, which could have profound clinical and health implications. Specifically, the improvements in TC, LDL, and triglycerides (measured as weighted mean difference) −22.81 mg/dL, −17.66 mg/dL, and −22.88 mg/dL, respectively. For context, a reduction of 1% in plasma concentrations of TC leads to a decrease in coronary heart disease by 2%.48  Thus, the American Academy of Pediatrics concluded that elevated cholesterol levels during childhood and adolescence increase the risk for future coronary heart disease as adults, although the exact risk is unknown.49 

These findings somehow challenge the conclusions of different reviews that have exhibited equivocal results in the association between aerobic exercise training and lipid profiles in healthy children and adolescents, suggesting that the different exercise characteristics may influence lipid profile.50,51 

Nevertheless, the relationship between exercise and blood lipids is complex because potential modifiers, such as obesity, baseline level of blood lipids, weight loss, effects of genetics, sex, age, and maturational status.50,52 

In addition to the confounders, exercise characteristics such as volume and intensity seem to play a key role in the beneficial effects of PA, with inconsistent results. For example, it has been claimed that a minimum amount of activity53  or weekly aerobic exercise energy expenditure is required to induce significant changes in lipids,54  with no clear benefits of HIIT or high-intensity versus moderate-intensity continuous training, which emphasizes the effect of volume over intensity. However, researchers in 2 meta-analyses of RCTs in children and adolescents22  and childhood obesity55  found that HIIT outperformed moderate-intensity continuous training for CRF.

Specifically, a systematic review of meta-analyses in a young population with obesity concluded that to be effective, programs should last at least 4 to 12 weeks, involve a total exercise time of at least 1500 minutes, or include sessions of at least 60 minutes.56  However, authors of a recent meta-analysis found that intervention duration (≤8 weeks vs >8 weeks), work and rest ratio (≤1 vs >1) and total bouts (≤180 vs >180) did not significantly modify the effect of HIIT on CRF.22 

Thus, despite the abovementioned equivocal results from these 2 reviews50,51  focused on healthy children and adolescents, authors of a review studying children with obesity found that aerobic exercise significantly improved LDL and triglycerides, which is in line with our findings.57  Interestingly, 3 out of 4 studies involved in our meta-analysis studied patients with obesity. It is worth mentioning that the associated weight loss during the exercise program may be a confounder, because researchers in several studies have concluded that LDL is not reduced significantly with aerobic exercise unless there is also a decrease in body weight. However, our study found significant improvements in LDL irrespective of weight loss.58,59 

In this review, the obesity and body composition indicators data revealed inconsistent results on BMI and BF%. No study reported any significant changes in BMI or BF% in response to HIIT, and only 1 article showed a positive effect on the results assessed by the sum of skinfolds.34  The findings of a review in children and adolescents20  suggested that pubertal children may reach a greater benefit as a result of HIIT compared with prepubertal children, which is a subject that has been broadly examined.6063 

With regard to blood pressure, only 2 studies analyzed SBP and DBP in children.33,37  Although the trend in both studies with blood pressure was positive in favor of HIIT, which was in line with a Cochrane review in children and adolescents published in 2013,43  our pooled analysis did not reveal significant reductions in SBP or DBP. These results could be a result of most of the children included in the RCTs having normal blood pressure levels, and thus, small reductions in blood pressure should be expected in this population.

The present meta-analysis has certain limitations that should be noted: (1) various types of HIIT programs were applied, and different instruments to measure performance were used, possibly resulting in high heterogeneity, which limits the consistency of our results; (2) because of the small number of available RCTs, it was not possible to conduct a subgroup analysis to assess whether the weight status influenced the overall ES; (3) because of the insufficiency of studies, a linear meta-regression analysis was not possible to explore whether covariates could be associated with the magnitude of the effect and could explain the observed statistical heterogeneity; (4) the low sample size of the populations studied, the short duration of the HIIT training programs, and the relatively low volume of weekly exercise training could have resulted in a lack of power to detect significant changes; and (5) adherence to training programs was not reported. It is important to emphasize that, especially regarding the child population, any effort aimed at increasing the “fun factor” in PA is beneficial, as play has intrinsic motivation that could improve compliance.64 

Nevertheless, an important strength of this meta-analysis is that only RCT studies involving a child population with a high level of homogeneity were included.

Based on this meta-analysis, HIIT programs could be an effective strategy to improve and treat cardiovascular risk factors and improve overall health in children. In future studies, researchers should incorporate a follow-up period within their study design to assess the long-term postintervention sustainability of positive HIIT-elicited benefits.

We would like to thank the authors of the included studies, who provided us with extra data for this review.

Dr Pozuelo-Carrascosa was the principal investigator and guarantor, conceptualized and designed the study, was one of the main coordinators of the study, and reviewed and revised the manuscript; Dr Solera-Martínez was one of the main coordinators of the study, designed the study, drafted the initial manuscript, and revised the manuscript; Dr Herráiz-Adillo helped conduct the study, provided statistical and epidemiological support, helped write the manuscript, and revised the manuscript; Mr Manzanares-Domínguez and Drs Lucas-De La Cruz and Martínez-Vizcaíno helped conduct the study and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

This trial has been registered with PROSPERO (registration no. CRD42018093432).

FUNDING: No external funding.

     
  • BF%

    body fat percentage

  •  
  • CG

    control group

  •  
  • CI

    confidence interval

  •  
  • CRF

    cardiorespiratory fitness

  •  
  • DBP

    diastolic blood pressure

  •  
  • ES

    effect size

  •  
  • HDL

    high-density lipoprotein cholesterol

  •  
  • HIIT

    high-intensity interval training

  •  
  • HR

    heart rate

  •  
  • HRmax

    maximal heart rate

  •  
  • LDL

    low-density lipoprotein cholesterol

  •  
  • MAS

    maximal aerobic speed

  •  
  • PA

    physical activity

  •  
  • PRISMA

    Preferred Reporting Items for Systematic Reviews and Meta-Analyses

  •  
  • RCT

    randomized controlled trial

  •  
  • SBP

    systolic blood pressure

  •  
  • SMD

    standardized mean difference

  •  
  • TC

    total cholesterol

  •  
  • Vo2peak

    peak oxygen uptake

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURES: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data