Introduction

The “summer slide” or “summer setback” is a term that has been coined to describe the loss of a variety of academic gains made over the course of the school year, particularly in children representing racial/ethnic minorities and/or low-income families (Cooper et al., 1996; Entwisle & Alexander, 1992). While it may be assumed that this decline is due to a lack of practicing or utilizing academic related skills, it is important to highlight other lifestyle factors related to health and fitness that also regress during the summer, as many of these have been shown to be related to childhood cognition and hence influence academic achievement. For instance, school-aged children experience an accelerated rate of weight gain over the summer, which is more pronounced among children at risk of obesity, such as children who are currently overweight (Franckle et al., 2014). Wang et al., (2015) also reported that summer moderate-to-vigorous physical activity (MVPA) participation exhibited significant age-related declines with an 8.2-minute decrease per year. Further, elementary-aged children displayed more screen time over the summer and higher consumption of sugar-sweetened beverages, calories, and added sugar (Wang et al., 2015). While these behaviors typically are studied in relation to weight status, previous literature has also shown that they may play a role in academic achievement and cognitive function (Khan, Raine, Donovan, et al., 2014a, 2014b; Pindus et al., 2019), factors important for children’s current and future academic performance and quality of life. Therefore, the causes of the summer slide regarding academics may include engagement in poorer health behaviors during the summer months.

Physical activity participation, specifically meeting the recommended 60 minutes a day of MVPA (U.S. Department of Health and Human Services, 2018) and increases in cardiorespiratory fitness, have been shown to improve cognitive functions, as well as mitigate the negative effects of excess adiposity on cognition and academics in children (Hillman et al., 2014; Hsieh et al., 2021; Khan et al., 2014b; Logan et al., 2021; Piercy et al., 2018). Therefore, it is essential to encourage healthy lifestyle behaviors (i.e., physical activity (PA)) particularly during the summer for children to retain learning gains received during the school year and combat accelerated weight gain. While many PA interventions have been implemented to prevent negative consequences of engagement in poor health behaviors (Cleland et al., 2012; Fu et al., 2017; van Sluijs et al., 2011), there is still a need for continued research as there is heterogeneity surrounding program effectiveness (van Sluijs et al., 2011), a lack of analyses of understudied groups such as racial/ethnic minorities (Love et al., 2017), and most do not assess cognitive function as an outcome. More specifically, executive functions (attentional/inhibitory control, working memory, and cognitive flexibility)- a set of top-down processes involved in reasoning, planning, and problem solving- have been shown to be influenced by one’s lifestyle behaviors, such as diet and PA, and can be predictive of children’s academic abilities (Diamond, 2013). Therefore, executive function ought to be studied when employing physical activity interventions meant to combat the summer slide. Accordingly, the Illinois Physical Activity and Life Skills (iPALS) program focused on providing an enrichment program for children from low-income households representing many racial/ethnic minority groups. The summer program focused on increasing children’s PA levels to achieving the recommended 60 minutes of MVPA per day and reduce the negative consequences of the summer slide in terms of health behaviors and executive function.

We investigated potential changes in cardiorespiratory fitness, weight status, and body fat percentage among iPALS participants. Given previous work on PA participation and physical fitness, we expected children to exhibit improvements in their estimated cardiorespiratory fitness by increasing the number of laps completed during the Progressive Aerobic Cardiovascular Endurance Run (PACER) test, as well as maintain their BMI-for-age percentile and body fat percentage. Considering many children over the summer experience declines in academic skills gained during the school year, the flanker task was utilized to assess attentional inhibition- an executive function component linked to better academic performance (Alavi et al., 2019; Jacob & Parkinson, 2015). Therefore, we examined the potential changes in accuracy and reaction time from a modified flanker task to determine whether attentional inhibition over the course of the program was maintained or improved. Based on previous literature surrounding PA and cognitive function (Donnelly et al., 2016), we expected that children that participated in the iPALS program would exhibit improvements in executive functions, specifically attentional inhibition. Lastly, we aimed to explore the relationships between program participation (assessed via changes in MVPA and attendance) and changes in fitness, weight status, adiposity, and cognitive function to provide an evaluation of whether PA participation during the iPALS program contributed to the maintenance and/or improvements of the aforementioned health outcomes. We anticipated that change in MVPA during the iPALS program and attendance would significantly correlate to changes in children’s cardiorespiratory fitness, body composition, and performance on the flanker task.

Materials and Methods

Program and Participants

The iPALS program, a pilot study, was aimed towards elementary-aged (6-10 years) children living in one public school district in a midwestern state and were eligible for the free/reduced lunch program. For enrollment in the program, children were required to be eligible for the free/reduced lunch program or recommended to enroll by school administrators to improve social, emotional, and/or behavioral skills, as well as be entering into grades 1-5. Although for the purpose of the current study, children with neurological disorders such as ADHD and autism spectrum disorder were excluded (n = 2). Participants were informed of the research being conducted prior to enrolling in the program. As a part of the enrollment, a packet was provided detailing the research protocols and parental consent and child assent forms. All participants and legal guardians provided written assent and consent, respectively. All procedures were approved by the University of Illinois at Urbana-Champaign Institutional Review Board (IRB #19796) and conformed to the guidelines of the Declaration of Helsinki. The program occurred 5 days a week (Monday – Friday) for a total of three weeks from 8:00 am to 3:00 pm. Children were grouped based on age and recent grade level and participated in 6 stations throughout the day, in which 4 were based solely on PA. A variety of activities were implemented including badminton, cooperative games, soccer, dance, and tchoukball. The remaining 2 stations involved nutrition education and academic enrichment. Figure 1 depicts an example of the daily rotation schedule.

Fig. 1
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Depiction iPALS program rotation schedule

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Participants engaged in physical activity lessons framed around developing competency in social and emotional skills throughout the program. As a primary component of the iPALS program, social and emotional learning was embedded into the curriculum through the implementation of the Teaching Personal and Social Responsibility (TPSR) model. TPSR was initially developed as a guide for promoting fundamental prosocial behaviors in physical activity contexts (Hellison, 2011; Walsh, 2012). iPALS adopted social emotional learning goals focused on respect, participation and effort, self-direction, leadership and helping others, and transfer. The instructors and station leaders were provided a one-week training that focused on implementation of the TPSR model from an expert in the field prior to the start of the program. Throughout the program, instructors and station leaders focused on teaching and implementing appropriate personal and social responsibility behaviors, such as modeling respect, giving choices and voices, and fostering positive social interactions. Additionally, time at the beginning and end of the time was allotted for participants to reflect on relationships and have awareness and lesson focus talks with their groups. The application of these practices aimed to develop a positive culture and environment that fostered relationship development and conflict management.

All study procedures, besides participant PA participation, were conducted once at the beginning of week 1 and once at the end of week 3 in the form of stations. Due to staff and timing constraints, procedures were conducted over the course of two consecutive days during weeks 1 and 3 to complete all data collection. While 77 were included in the current study, not all were able to complete each study procedure due to absence from the program that day because of illness, personal/familial reasons, or other time commitments, or opting out of the procedure.

Physical Activity and Cardiorespiratory Fitness Assessments

Children wore a triaxial wGT3X-BT accelerometer (ActiGraph LLC., Pensacola, FL, USA; 3.3 x4.6 x1.5 cm; 19 g; dynamic range ± 8 g) from 8:00 am to 3:00 pm (Monday – Friday) on their right hip to assess PA participation while at program. The raw acceleration data were converted to vertical axis counts at 15s epochs using ActiLife software (v.6.13.3, ActiGraph LLC., Pensacola, FL, USA). Non-wear time was defined as 30 minutes of consecutive 0 counts as recommended by (Vanhelst et al., 2019). Time spent in each PA intensity was based on Evenson et al. (2008) counts per minute (CPM) thresholds (i.e. MVPA ≥ 574 CPM) (Evenson et al., 2008).

Cardiorespiratory fitness was assessed with the PACER, a multistage field-based test of aerobic capacity that progressively increases in difficulty and useful for large groups (Plowman & Meredith, 2013). This is a valid and reliable test that has been used previously to assess cardiovascular fitness in children (Leger & Lambert, 1982; Meredith & Welk, 2013). Further, previous studies have used the PACER to assess cardiorespiratory fitness in children during the summer months (Brusseau & Burns, 2018). It is a feasible test when aiming to analyze large cohorts in a short amount of time as many children can participate at once. Participants were instructed to run 15 meters back and forth in time with a series of beeps in which that time between them gets increasingly smaller. This required participants to increase their speed to remain on track with the beeps. When a participant can no longer keep up with the beeps, defined by two consecutive beeps, the test is complete. Their score was based on the number of laps successfully completed.

Body Composition Assessments

Children’s height was measured using a stadiometer (model 240: Seca, Hamburg, Germany). Weight and other body composition measures (i.e., adiposity, muscle mass) were assessed with bio-electrical impedance analysis (BIA) (InBody 270: Biospace, California, USA). Using height and weight, participants’ BMI and BMI-for-age percentile (BMI%ile) were calculated.

Cognitive Function Assessments

A modified version of the Eriksen flanker task (Eriksen, 1995) was used to assess attentional inhibition, a component of executive function. The flanker task has been linked to both physical activity and weight status in children (Hillman et al., 2014; Kamijo et al., 2012), each of which are a health markers of concern during the summer months. During the task, 5 goldfish were presented on the screen in which participants respond to the direction of the central or target fish, which is flanked by four fish facing either the same (congruent) or opposite direction (incongruent) of the target. Participants completed a practice block that consisted of 48 trials of each congruency in a random order. After getting a score of >50% accuracy, participants moved on to two experimental blocks, which consisted of 56 trials per block with an equiprobable distribution of each congruency and presented in random order. The stimulus was presented for 200 milliseconds (ms) with a jittered inter-trial interval of 1600, 1800, or 2000ms.

Statistical Analysis

A power calculation (G-Power 3.1.9.6) in which a small to moderate effect size (f2=0.15) along with an alpha set at 0.05 and beta at 0.08 was chosen, which estimated a sample size of 55 needed to address the study aims. All variables were checked for normality with visual inspection using histograms and Kalmogorov-Smirnov tests. A log transformation was conducted to normalized scores for the PACER test at baseline. Potential outliers were assessed using box plots and no significant outliers (>3 standard deviations from the mean) appeared. Paired t-tests were conducted to assess changes between week 1 and week 3 in PACER laps, body composition measures, and cognitive abilities. Additionally, a one-way repeated measures analysis of variance (ANOVA) was conducted to assess changes in participation in MVPA during the program between weeks 1, 2, and 3. To determine relationships between program participation and changes in fitness and cognitive function, two step regression analyses were conducted in which step 1 included age and sex and step 2 included changes in MVPA from week 3 to week 1 and days attended. Including age and sex in step 1 of the models was based on a priori as these are critical variables that contribute to children’s growth and development and influence fitness and body composition. Outcomes for regression analyses included the change scores of the PACER test, flanker task, and BMI%ile and body fat percentage. For the flanker task, regression analyses were only conducted on variables that exhibited a significant change Statistical significance was set at p < 0.05 and analyses were conducted using SPSS version 28 (IBM, Chicago, Illinois, USA).

To address participants who did not complete PACER, the flanker task, or body composition analyses at week 3 due to absence from program during testing day or opting out, multiple imputations (MI) were employed using a linear regression method under the assumption that values are missing at random (Manly & Wells, 2015). SPSS’s ‘impute missing data values’ command generated 5 imputed datasets in which analyses run were pooled according to Rubin’s rule. In the case that Rubin’s rule did not apply, (i.e., R and p values in regressions) a range of the values from all 5 imputed data sets are presented. Missing data were only imputed at post testing to ensure that only participants that completed baseline were included in analyses. The percentage of missing data ranged from 4-23%, and therefore resulted in imputed data for 4 participants for the PACER, 3 participants for body composition analyses, and 16 for the Flanker task. This resulted in 69 participants having been included in all analyses. Imputed results compare reasonably to observed and listwise deletion and therefore imputed results are presented.

Results

Participant demographics are depicted in Table 1. Average attendance was 12.68 ± 2.81 out of 15 days, most participants (~80%) represented racial/ethnic minorities, and 66.7% came from a home with an income less than $40,000 a year. The children’s PA participation, PACER scores, Flanker scores, and body fat percentage analyses are presented in Table 2.

Table 1 Participant demographic information
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Table 2 Changes in body composition, PACER scores, PA participation, and flanker scores
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Paired t-tests revealed no significant changes in BMI%ile (Figure 2) or body fat percentage between week 1 and week 3. There was a significant increase in PACER score from 10.71 ± 7.72 to 13.33 ± 10.71 laps (p <0.001) (Figure 3). There was no change in performance measures of the flanker task except for a significant increase in incongruent accuracy (p = 0.007) (Figure 4). Lastly, the one-way repeated measures ANOVA revealed a significant increase in MVPA between week 1 and week 3 (F (2, 126) = 9.639, p <0.001). Post hoc analyses indicated a significant increase between week 1 and week 2, however, no significant change in MVPA occurred between weeks 2 and 3 (Figure 5).

Fig. 2
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Depiction of changes in BMI%ile between week 1 and week 3. Labeled means without a common letter differ, p <0.05

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Fig. 3
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Depiction of changes in PACER laps between week 1 and week 3. Labeled means without a common letter differ, p <0.05

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Fig. 4
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Depiction of changes in flanker incongruent accuracy between week 1 and week 3. Labeled means without a common letter differ, p <0.05

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Fig. 5
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Depiction of changes in MVPA between week 1, 2, and 3. Labeled means without a common letter differ, p <0.05

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Regression analyses, depicted in Table 3, revealed that changes in MVPA and attendance were not significantly related to changes in BMI%ile, body fat, PACER score, or performance on the flanker task. However, age was positively related to change in PACER score. Lastly, a significant negative age by sex effect (β= -0.146, p = 0.006) was observed in subsequent regression analyses assessing changes in body fat percentage, indicating that females of younger age exhibiting declines in body fat.

Table 3 Regression analyses describing the relationship between program participation and changes in weight status, fitness, and flanker task performance
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Discussion

This study focused on changes in body composition, fitness, and cognitive function after a summer PA program provided for children from disadvantaged households. The negative consequences of the lack of scheduled PA programs in the summer has been shown to be more harmful for children of racial/ethnic minority groups and/or from low-income households (Cooper et al., 1996; Entwisle & Alexander, 1992). Therefore, this program aimed to recruit children from these groups and provide them with the minimum 60 minutes of MVPA per day as well as nutrition education and academic enrichment. Further, the current study aimed to assess whether children maintained their weight status while improving their fitness and cognitive abilities, and hypothesized that MVPA during the program would be related to these outcomes.

Regarding the programs’ recruitment efforts, 77 children were recruited to participate, a majority eligible for the free/reduced lunch program. Additionally, over two-thirds of the participants came from households with annual incomes less than $40,000 a year, which, according to the U.S. census, is below the median income in the state of Illinois. Children enrolled in iPALS also represented many racial groups as 80% identified as Black/African American, Asian, American Indian, or mixed/other. Furthermore, the participants’ average MVPA participation at the program exceeded the national recommendation of 60 minutes per day, whereas the average attendance was 12 out of 15 days in total. Therefore, the iPALS program was successful in its goal of recruiting children that may experience consequences of the summer slide and provided them with opportunities to possibly mitigate those negative effects.

Pertinent to the participant’s health behaviors, analyses revealed no change in weight status in terms of their BMI%ile as well as no change in body fat percentage. This is important to note, as children have been reported to gain excessive weight over the summer months (Franckle et al., 2014; Tanskey et al., 2018, 2019). Additionally, analyses revealed improvements in estimated cardiorespiratory fitness via an increase in the number of laps completed on the PACER. This is a crucial element as physical fitness has been shown to predict children’s PA participation during child and adulthood (Barnekow-Bergkvist et al., 1998; Jaakkola et al., 2016), as well as cognitive abilities which are important for school and life success (Chaddock et al., 2012). When considering cognitive abilities, participants exhibited significant improvements in performance on the flanker task, an assessment of attentional and inhibitory control. Specifically, they improved scores on the incongruent trials, which are considered more difficult as they require higher levels of inhibition. While it was clear that the program prevented summer weight gain and improved fitness and cognitive abilities, regression analyses indicated these benefits were not directly related to MVPA or attendance. However, given that we did not assess PA prior to enrollment in the program or PA outside of the program (e.g., at home), we are unable to test the influence of changes in overall PA on the improvement of those outcomes. Further, age and sex (0 coded as female, 1 coded as male) were both negatively related to changes in body fat percentage and age was positively related to changes in PACER scores. This indicated that younger girls experienced larger increases in BMI%ile and older children had larger PACER score changes. Therefore, it’s possible that these demographic variables played a larger role in influencing these health factors than PA participation. Future studies should consider how children of different ages may respond to a PA programs framed around social-emotional learning. Previous studies have indicated that female preadolescents, particularly Black/African American and Mexican, tend to participate in less PA and exhibit higher BMI compared to their white counterparts by the age of 6 (Winkleby et al., 1999). In fact, interventions aimed towards younger girls representing ethnic minority groups may be necessary to build healthy habits early and prevent poor health behaviors in adolescence and late adulthood.

There are several limitations that ought to be acknowledged in this study. First, our study lacked a control group, which did not allow for us to draw any causal conclusions regarding the effects of the program. In the future, having a control group as a comparison will allow for more robust conclusions regarding the effects of the program. Additionally, the length of the program was considerably shorter than previous PA interventions due to time, staff, and spacing constraints in the community during the covid-19 pandemic. Therefore, it is possible that improvements in fitness and MVPA were due to increased confidence and comfortability at the program. These are factors worth considering for future work as they have shown to predict PA participation in children (Babic et al., 2014). Although, the volume of daily PA provided was greater than other interventions which may have been a sufficient amount of total MVPA over the course of the program. Due to the length of the program improvements in the flanker task could be attributed to a practice effect, although, improvements were amongst only the incongruent trials, which is typically an indicator of improvements in the attentional inhibition skills as previous work has linked health behaviors to be associated selectively to the incongruent trials, which requires upregulation of attentional and inhibitory control (Hillman et al., 2014). Further, the assessment of PA was only conducted while participants were at the program. While this provided the amount of activity engaged in during the program, we cannot draw conclusions regarding the program’s effects on habitual PA patterns or accurately estimate how total PA changed throughout the program duration. Further, the flanker task was used as an assessment of attentional inhibition, although, this is not a direct measure of overall executive function or academic achievement. Future studies ought to consider utilizing a standardized academic battery to assess academic skills during the summer. Also, the PACER test is not a clinical measure of aerobic capacity, as there is no conversion for PACER score to VO2 max for children under 10 years old (Meredith & Welk, 2013). Therefore, the results surrounding PACER should not be used as a direct estimation of improvements or changes aerobic capacity. Lastly, nutritional status was not included. Although, diet is a critical factor that has been implicated as being negatively affected by the ‘summer slide’ and contributes to weight and cognitive function, (Khan, Raine, Donovan, et al., 2014a, 2014b; Wang et al., 2015), and therefore it is worth considering children’s specific nutrient intake, dietary patterns, and adherence to the U.S. Dietary Guidelines for Americans (e.g., Healthy Eating Index scores). Despite the aforementioned limitations, a few strengths include the successful recruitment of children from low income households, as well as representation of races and ethnicities that have been reported to have poorer health behaviors and suffer from negative consequences of unstructured summer days. Altogether, this is one of few summer PA programs using a social emotional framework that included assessments of cognitive function along with cardiorespiratory fitness and body composition.

In conclusion, this study found that a three-week summer PA program was successful in providing children from low-income households opportunities to not only meet but exceed the recommended physical activity guidelines. Participants exhibited improvements in estimated cardiorespiratory fitness via PACER score and performance on an attentional control task and maintained their weight status throughout the program. Future interventions should continue to target children at-risk of poor health behaviors, particularly during the summer months, and encourage increased PA participation to improve fitness and enhancing cognitive abilities, as these behaviors are beneficial for children’s overall physical and mental wellbeing.