The Effects of a Science-Based Community Intervention on Health Outcomes in Minority Children: The Translational Health in Nutrition and Kinesiology Program

in Journal of Physical Activity and Health

Background: This study evaluated the effects of a novel nutrition and movement science after-school program integrating laboratory experiences for minority children. Laboratory experiences demonstrated how the body moves, functions, and performs in response to exercise and healthy nutrition. Methods: A total of 76 children from 4 after-school programs that were primarily Latino and black were randomly assigned to either an experimental translational health in nutrition and kinesiology (THINK; n = 46) or standard curriculum that served as the control group (CON; n = 30). An analysis of covariance controlling for baseline values was used to compare differences between THINK and CON after the 4-month intervention. Results: Following the program, THINK participants evidenced lower triceps and subscapular skinfold thickness (P < .01 and <.05, respectively). THINK students showed greater improvements in aerobic fitness, grip strength, and agility than CON (P < .01, <.01, and <.05, respectively). Participants in THINK also demonstrated higher scores on their nutrition habits/behaviors questionnaire (P < .01), nutrition science (P < .05), and exercise fitness tests (P < .001) than CON. Conclusion: An innovative curriculum featuring nutrition and kinesiology education interfaced with hands-on laboratory experiences and physical activities can improve physical outcomes and health-related behaviors in after-school programs serving minority children.

According to recent estimates, approximately 31.8% of children and adolescents in the United States are overweight or obese.1 This presents a significant health burden today as children with overweight/obesity possess greater risks of cardiovascular disease, diabetes, cancer, and premature death later in life.2,3 Furthermore, increasing body mass index (BMI) growth trajectories have been linked to increasing cardiometabolic risks.4,5 Coupled with poor nutrition, physical inactivity, and subsequently low physical fitness levels can lead to obesity and its associated comorbidities, which are more prevalent among Latino and African American/black minorities.6,7 Therefore, primary prevention should begin early on in childhood or adolescence as this represents a period of significant physical and mental growth when lifestyle behaviors are more amenable to change.

After-school programs can provide a great opportunity to enhance activity and physical fitness levels in children by building upon physical activity, movement skills, and psychosocial development. Recent data show that as many as 6.6 million youth in the United States participate in after-school programs with even more families willing to participate if it were available.8 However, physical activity levels in most after-school programs remain well below recommended levels. Beets et al9 examined nearly 1000 children and showed that children spend an average of 125 minutes daily in after-school programs, yet they accumulate only 26.8 minutes of physical activity. Using pedometers, only 16.5% of all after-school programs met the 4600 steps per day requirement using standard guidelines.

More importantly, nutrition and exercise science education, which would empower children to improve their personal lifestyle behaviors beyond after-school programs, are often absent in such programs. The translational health in nutrition and kinesiology (THINK) program was designed to integrate nutrition and movement science (kinesiology) to educate children how to improve their personal lifestyle behaviors. Although other after-school curriculums have used nutritional educational10 and physical activities11 independently to improve general health in youth, we know of no after-school programs combining these integral components with laboratory elements to teach children how their bodies respond to exercise. These hands-on experiences enable youth to understand and appreciate their own biology and physiology and their bodies’ response to different movement patterns and proper nutrition. The primary purpose of this study was to determine whether the THINK program could improve elements of physical/anthropometric variables, physical fitness, physical literacy, and nutrition knowledge and behaviors in after-school programs with predominantly Latino and black participants. We hypothesized that the THINK program would differentially improve these outcome measures compared with students attending a standard after-school program with a focus on physical activity.

Methods

Participants and Recruitment

The THINK program was previously conducted in the community for several years as a summer program for middle school students. In the present study, the THINK program was adapted for elementary-aged students and conducted in partnership with the YMCA of South Florida, an organization that hosts the majority of after-school care programs in Miami-Dade County. A university/community partnership was established to evaluate whether the THINK curriculum adapted for the after-school setting could improve physical health and fitness in underserved minority children attending the YMCA after-school programs. To accomplish this goal, the YMCA solicited 4 after-school programs for the trial. Selection was based upon practical considerations including appropriate demographic representation (>55% Latino or black), school principal approval, adequate staff, and facilities conducive to indoor instruction and outdoor play. Investigators randomly assigned the after-school programs to THINK or the standard program, which served as the control (CON) group. Randomization occurred at the school level to ensure that one predominantly Latino and one predominantly black school would be eligible for the THINK program and that comparisons between groups across conditions (THINK vs CON) would possess similar racial demographics. Due to the more advanced nature of the materials and activities presented, students were recruited from more age appropriate third to fifth grade levels only. The program was open to all students enrolled in the selected YMCA after-school programs meeting the aforementioned eligibility requirements regardless of race or ethnicity.

The study was approved by the University of Miami’s Institutional Review Board for Use of Human Subjects and each school’s principal. Parental consent and child assent was given. The clinical trial was registered in clinicaltrials.gov (NCT02932813). Initially, 76 children completed baseline assessments (46 THINK and 30 CON). However, during the course of the program, 5 students in the experimental group and 4 students in CON dropped out, leaving a total of 67 students (41 THINK and 26 CON) available for posttesting assessments. Reasons cited for dropping out included moving, joining other after-school programs, and preference for being with friends.

Experimental Design

A pretest–posttest CON group design was used to evaluate the effects of the THINK intervention compared with CON. All measurements were conducted on site at the YMCA’s after-school locations. All outcomes were collected prior to the initiation of the THINK program and repeated again following the completion of the study. Data collection occurred during the same time of year at both intervention and CON after-school programs.

Procedures

All study staff were trained in an intensive 2-week workshop by the program director and clinical coordinator of the program on standardization of testing procedures to ensure accuracy and reliability of data collection. Trained research assistants in exercise physiology conducted all measurements. Participants were rotated through stations for physical testing after completing several questionnaires and surveys disseminated across a 1- to 2-week period of baseline testing.

The same investigators performed baseline and posttesting data collection to ensure consistency and reliability of measurements. All data collection was conducted using 3-digit codes, that is, 001 substituted for each participant’s name with all codes kept in a password-protected file possessed by the principal investigator. Therefore, investigators were blinded to the names of participants during testing and baseline scores during posttesting.

The 4-month THINK program was conducted 3 days per week for 2 hours immediately following school release, whereas the CON schools went through the standard YMCA after-school program for the same time period. The CON school activities consisted of completing homework, arts and crafts, and age-appropriate physical activities for elementary school children using the Sports, Play, and Active Recreation for Kids program described elsewhere.12 The program timeline is presented in Figure 1.

Figure 1
Figure 1

—Timeline for the experimental THINK and CON programs. CON indicates control; THINK, translational health in nutrition and kinesiology; SPARK, Sports, Play, and Active Recreation for Kids.

Citation: Journal of Physical Activity and Health 18, 9; 10.1123/jpah.2020-0622

Intervention

The THINK program consisted of 3 integrated components: (1) educational sessions on health-related themes, (2) hands-on laboratory experiences, and (3) structured physical activities. The program differed from the traditional pedagogical approach in that it used an “active learning” paradigm that engaged students with the materials presented, encouraged participation in class, and fostered group collaborative work.13 There was also a focus on physical literacy, which is the confidence, competence, and motivation to exercise along with a knowledge of the benefits of regular physical activity.14 Having already run a THINK summer program for underserved Latino and black youth,15,16 investigators worked with community administrators, parents, and children using focus groups to modify the program to be multiculturally sensitive to students’ needs and interests and to be administered in an after-school setting.

Health-related themes facilitated a greater understanding of appropriate terminology and nutrition/exercise concepts along with their health implications. The health-related themes were no more than 20 to 30 minutes to retain attention and reduce the adverse metabolic effects of prolonged sitting (eg, increased fasting glucose,17 triacylglycerol,18 and peripheral vasoconstriction19).

Laboratory experiences followed educational themes enabling children to learn more about their bodies from a science-based perspective. These included use of pedometers to learn how many steps are in one mile, goniometers to teach flexibility, dynamometers for strength, Douglas bag and flow meters to teach respiratory function, and pressure cuffs to learn how to take blood pressure and heart rates. Students were also exposed to anatomical models of muscles and bones during anatomy lessons. Understanding of materials was assessed using games, such as “Simon Says,” wherein students had to point to the correct bone (ulna, femur, or acromion process) or muscle (deltoid, biceps, or gastrocnemius) to stay in the game.

The activity component emphasized motor skill acquisition that reinforced laboratory experiences and health-related themes. Team relays and games were integrated with educational facts. For example, following a nutrition unit, students had to sprint to a supermarket bag, randomly select a grocery item, then sprint back to the MyPlate poster and place the item under the correct food group. Points were awarded to the fastest team with the most accurate placement of supermarket items.

To address methods for promoting and sustaining behavioral change, the curriculum design incorporated the social cognitive theory,20 which posits that behaviors are influenced by social, environmental, and individual attributes. Within this framework, the curriculum targeted the enhancement of self-efficacy using 4 domains: mastery experiences wherein students could learn by doing and gain success by mastering specific achievable skills through practice, vicarious experiences wherein students observed counselors and peers successfully demonstrating skills, social persuasion in which counselors and peers provided verbal encouragement for attempting skills, and emotional support from counselors when students displayed discouragement or insecurities when attempting skills.

Physical/Anthropometric and Physical Fitness Measures

Physical/Anthropometric

Children’s physical measurements included resting heart rate, blood pressure, and body composition. Resting heart rate and blood pressure were taken in the right arm while in a seated position after a minimum 5-minute rest period, using an automated electronic cuff (Omron Health Care, INC, Kyoto, Japan) inflated to 200 mm Hg with a gradual pressure release.21 Height (in centimeters) and weight (in kilograms) were measured using a wall mounted stadiometer and digital scale (Conair Corporation, Stamford, CT). BMI was computed using weight (in kilograms) divided by height (in meters squared). BMI delineating overweight/obese ≥85th percentiles and BMI z scores were reported using Center for Disease Control and Prevention guidelines. Three measures of skinfold thickness using a Lange skinfold caliper (Beta Technology, Santa Cruz, CA) were taken of the triceps, subscapular, and calf as a measure of adiposity according to standard procedures outlined by Lohman et al.22

Physical Fitness

All physical fitness tests included validated tests with established reliability. Upper body strength was measured by grip dynamometry using the dominant hand (JA Preston Corporation, Clifton, NJ) following procedures set forth by the American Society of Hand Therapists.23 Aerobic fitness was measured using a 2-minute walk test in which participants walked a 30.5-m course as quickly as possible in either direction (15.24 m) with 180° turns at each end.24 This has been shown to be a valid and reliable test for children aged 6–12 years.25 Abdominal muscular endurance was measured by asking participants to perform as many sit-ups as possible in 1 minute while resting briefly as needed to complete the test, using the protocol developed by the President’s Council on Physical Fitness and Sports.26 Lower body power was measured via vertical jump height (Vertec Jump Training System, Sports Imports, Hilliard, OH) using a static start jump in which the child’s standing height with the arm stretched overhead was subtracted from their maximum standing jump height following a squat countermovement to a self-selected depth.27 Flexibility of the lower back and hamstrings was measured using a Sit-and-Reach Box (Acuflex I; Novel Products Inc, Rockton, IL, USA). Participants were instructed to sit on the floor with their outstretched legs abutting the Sit-and-Reach Box and move a lever as far forward as possible without bending their knees.28 Agility was measured using a shuttle run test in which participants were required to run as quickly as possible between 2 parallel lines 9.14 m apart after picking up 2 foam blocks (5.08 × 5.08 × 10.16 cm) one at a time and putting them down at the parallel line opposite the starting line.26

Questionnaires/Tests

Nutrition

All participants completed a 51-item questionnaire from the Coordinated Approach to Child Health (CATCH) Kids Club,29 which consisted of modular assessments of nutrition knowledge, dietary intake/food intentions, and physical activity in elementary school children. These modules have been validated against the After-School Student Questionnaire and the System for Observing Fitness Instruction Time, an in-school physical activity assessment for elementary school children.

The investigators constructed a test from nutrition-related themes taught during the program. The test consisted of a 20-item multiple choice form on standard nutrition terminology, macronutrients, micronutrients, hydration, and practical label reading. The nutrition test was presented as raw scores.

Physical Literacy

The Physical Activity Enjoyment Scale30 is designed to rate how positively respondents feel about the physical activities they are doing at the moment. The scale has a maximum score of 100 with a reported Cronbach coefficient alpha of .96 and high test–retest reliability. The modified spinal cord injury Exercise Self-Efficacy Scale31 was used to evaluate self-confidence and self-efficacy. The scale has a maximum score of 100 with a reported Cronbach alpha of .92 and high internal consistency that has been successfully used in children.

The investigators constructed a test from health-related themes taught during the program. The test consisted of 20 multiple choice items, which included information on physical fitness, exercise science terminology, obesity prevention, and the importance of maintaining a physically active lifestyle. The exercise/fitness knowledge test was presented as raw scores.

Statistical Analysis

All data were analyzed using an SPSS statistical package (version 24; IBM SPSS Inc, Chicago, IL). Group means and standard error of the mean (SE) were calculated for all physical/anthropometric, physical fitness, physical literacy, and nutrition variables. An independent sample t test was performed to determine differences between experimental and CON groups in the aforementioned variables at baseline. Data, including age, were initially screened for normality of distribution by calculating skewness and kurtosis, and all values were within ±2.00, which was considered normal. As there were significant differences in baseline values, an analysis of covariance at posttesting was used to determine significant differences between experimental and CON groups after controlling for baseline values. The effect size reported as partial η2 was obtained from the analysis of covariance analyses. All reported P values were 2-sided with significance set at P ≥ .05.

Results

Descriptive Information

A total of 76 children (46 THINK and 30 CON) enrolled in the program and completed all baseline assessments. Age and demographic information for all participants are presented in Table 1.

Table 1

Participant Characteristics and Demographics at Baseline (N = 76)

CharacteristicsTHINKCON
Age, mean (SE), y9.87 (0.18)9.53 (0.18)
Race/ethnicity (number of participants)
 Latino2510
 Black1318
 White52
 Mixed30
Gender, %
 Boys52.263.3
 Girls47.836.7

Abbreviations: CON, control; THINK, translational health in nutrition and kinesiology.

Raw Scores at Baseline and Posttesting

Presented in Table 2 are the physical/anthropometric and physical fitness variables at baseline and follow-up. Children in the THINK program possessed significantly higher triceps skinfold thickness (t74 = 2.3, P < .05) and subscapular skinfold thickness (t74 = 2.0, P < .05) than the CON at baseline. There were no significant differences in any other physical/anthropometric or physical fitness variables at baseline between groups.

Table 2

Raw Scores for Physical/Anthropometric and Physical Fitness Variables at Baseline and Posttesting

THINKCON
VariablesBaselinePosttestingBaselinePosttesting
Physical/anthropometric
 RHR88.28 (1.63)79.65 (1.61)91.53 (2.46)82.08 (2.23)
 Resting systolic pressure118.09 (13.21)104.13 (2.06)110.63 (2.40)99.17 (1.83)
 Resting diastolic pressure69.35 (1.78)67.10 (1.21)74.23 (2.04)66.04 (2.21)
 Height, cm143.61 (0.53)145.59 (0.67)140.13 (0.62)140.97 (0.60)
 Weight, kg43.85 (4.16)45.40 (3.98)38.28 (4.39)37.67 (4.46)
 BMI, kg/m220.91 (0.63)22.07 (0.91)19.14 (0.64)18.76 (0.68)
  >85th percentile57%57%46%43%
  BMI z score0.00 (0.15)0.00 (0.16)0.00 (0.18)−0.24 (0.31)
 Triceps skinfold, mm17.63 (0.92)*15.92 (0.97)14.43 (0.93)16.57 (1.02)
 Subscapular skinfold, mm13.98 (1.04)*12.82 (0.97)10.97 (0.95)11.83 (0.89)
 Calf skinfold, mm14.83 (1.02)14.77 (1.09)13.23 (1.17)16.09 (1.24)
Physical fitness
 Cardiorespiratory fitness, %km21.97 (0.23)23.49 (0.34)22.13 (0.43)21.56 (0.48)
 Strength, kg15.63 (0.80)22.51 (0.94)13.39 (0.78)17.00 (1.25)
 Agility, s12.55 (0.19)12.72 (0.22)12.74 (0.37)13.42 (0.28)
 Flexibility, cm28.51 (1.92)25.23 (1.27)28.36 (1.28)28.56 (1.53)
 Lower body power, cm28.90 (0.48)33.48 (0.54)26.24 (0.61)28.85 (0.66)
 Muscular endurance, no.31.59 (1.35)38.44 (2.06)29.52 (2.14)36.95 (2.39)

Abbreviations: BMI, body mass index; CON, control; RHR, resting heart rate; THINK, translational health in nutrition and kinesiology. Note: Data are shown as mean (SE) unless otherwise indicated. Baseline comparisons were performed using unpaired sample t tests. Cardiorespiratory fitness was measured during a 2-minute walk test for distance covered; strength was measured using grip dynamometry; agility was measured using a shuttle run; flexibility was measured during a sit and reach test; lower body power was measured using the Vertec® jump test; and muscular endurance was measured using the maximum number of sit-ups performed.

*Significantly different than CON group at baseline P ≤ .05.

Raw scores for physical literacy and nutrition knowledge/behaviors are presented in Table 3. THINK participants scored higher on their baseline Nutrition Science Test (t73 = 2.5, P < .05) than CON. There were no differences between THINK and CON in any other nutrition or physical literacy variables at baseline.

Table 3

Raw Scores for Physical Literacy and Nutrition/Knowledge Behaviors at Baseline and Posttesting

THINKCON
VariablesBaselinePosttestingBaselinePosttesting
Physical literacy
 Exercise efficacy77.18 (3.10)80.26 (2.46)69.48 (3.25)71.78 (3.67)
 Physical activity enjoyment81.11 (2.56)81.89 (2.50)81.93 (3.06)74.71 (3.17)
 Exercise/fitness knowledge34.11 (1.99)49.69 (2.04)29.76 (2.03)30.43 (2.31)
Nutrition knowledge/behaviors
 CATCH questionnaire67.05 (1.45)79.09 (1.05)64.22 (1.44)71.54 (1.46)
 Nutrition science test56.88 (1.83)*63.63 (2.56)49.62 (2.17)51.52 (2.40)

Abbreviations: CATCH, Coordinated Approach to Child Health; CON, control; THINK, translational health in nutrition and kinesiology. Note: Data are shown as mean (SE) unless otherwise indicated. Baseline comparisons were performed using unpaired sample t tests. Catch questionnaire, physical activity enjoyment, exercise efficacy, exercise/fitness, and nutrition knowledge test scores were all measured on a 0% to 100% basis with the higher number indicating the better score.

*Significantly different than CON group at baseline P ≤ .05.

Posttest Comparisons

Reported in Figure 2 are the significant posttest skinfold measures between THINK and CON groups after adjustment for baseline values. At posttesting, THINK participants showed significantly lower mean triceps skinfold thickness (F1,59 = 11.2, P < .01) with a large effect size (partial η2 = .53) and lower subscapular skinfold thickness (F1,59 = 4.6, P < .05) with a large effect size (partial η2 = .62) than CON. There were no significant differences in BMI or calf skinfolds at posttesting.

Figure 2
Figure 2

—Graph illustrating significant changes in skinfold measures between THINK and CON group. Data are presented as posttest skinfold means adjusted for baseline values using ANCOVA for THINK and CON groups. ANCOVA indicates analysis of covariance; CON, control; THINK, translational health in nutrition and kinesiology. *P < .05 compared with CON. **P ≤ .001 compared with CON.

Citation: Journal of Physical Activity and Health 18, 9; 10.1123/jpah.2020-0622

Posttest scores for significant physical fitness variables are shown in Figure 3. Compared with CON, the THINK group covered more distance on the NIH 2-minute test (F1,50 = 10.9, P < .01) with a large effect size (partial η2 = .31) and demonstrated greater grip strength at posttesting (F1,55 = 12.2, P < 0.01) with a large effect size (partial η2 = .42). The THINK group also finished their agility/speed more quickly than CON (F1,49 = 4.1, P < .05) with a large effect size (partial η2 = .39).

Figure 3
Figure 3

—Graph illustrating group changes in physical fitness variables. Data are presented as posttest means adjusted for baseline values in physical fitness measures using ANCOVA for THINK and CON groups. Aerobic fitness measured during a 2-minute walk test for distance covered; agility measured using a shuttle run; strength measured using grip dynamometry. ANCOVA indicates analysis of covariance; CON, control; THINK, translational health in nutrition and kinesiology. *P ≤ .05 compared with CON. **P ≤ .01 compared with CON. ***P < .001 compared with CON.

Citation: Journal of Physical Activity and Health 18, 9; 10.1123/jpah.2020-0622

Reported in Figure 4 are the significant posttest scores for exercise/fitness, CATCH questionnaire, and nutrition science tests. Compared with CON, the THINK participants scored higher on their exercise/fitness test (F1,58 = 30.8, P < .001) with a large effect size (partial η2 = .23) and higher on their nutrition science test (F1,57 = 6.3, P < .05) with a large effect size (partial η2 = .15). They also scored higher on the CATCH questionnaire than CON (F1,57 = 13.2, P < .01) with a large effect size (partial η2 = .19).

Figure 4
Figure 4

—Graph illustrating group changes in exercise/fitness and nutrition knowledge/behaviors. Data are presented as posttest means adjusted for baseline values using ANCOVA for THINK and CON groups. Exercise/fitness test, CATCH questionnaire, and nutrition science test were all graded on a 0% to 100% basis. ANCOVA indicates analysis of covariance; CATCH, Coordinated Approach to Child Health; CON, control; THINK, translational health in nutrition and kinesiology. *P ≤ .05 compared with CON. **P < .001 compared with CON.

Citation: Journal of Physical Activity and Health 18, 9; 10.1123/jpah.2020-0622

Discussion

Many after-school programs either emphasize education or focus upon fitness and sport activities. The THINK program combined both elements, integrating health-related themes rooted in kinesiology with hands-on clinical experiences and physical activities. The goal was to empower children to improve their personal lifestyle behaviors and reflected a community–university partnership to create a culture of health and fitness that was racially/ethnically sensitive to all participants.

Obesity and its associated comorbidities (hypertension and type 2 diabetes) track well into adulthood and disproportionately affect Latino and black children.32 Furthermore, adult Latinos suffer from the highest rates of obesity-related medical issues, such as diabetes and heart disease, than any other racial group.33 The burden of obesity among Latino and other racial minorities has been a critical issue having long-term health implications. Almost 50% of the children in the study were Latino and almost 90% of the children were Latino or Black. Thus, a 24.9% and 17.2% greater reduction in triceps and subscapular skinfolds, respectively, found in the THINK compared with CON following the program are promising results. Findings may be related to the emphasis on exercise and fitness along with healthy dietary patterns and active play using activities promoting elevated energy expenditure. Interestingly, skinfold changes were observed despite no significant changes in BMI levels found in either group following the program. This indicates that both groups had comparable rates of growth throughout the program time frame but that the composition of this growth significantly differed between groups. Fat tissue decreased in THINK participants; therefore, increased muscle and/or lean body mass in the same group would explain comparable differences in BMI levels at posttesting.

Although both physical activity and physical fitness are related to positive health outcomes, the link between fitness and health outcomes is significantly stronger.34,35 Globally, fitness levels have been reported to be declining for years,36 and data suggest a significant drop in cardiorespiratory fitness levels even before adolescence.37 THINK participants evidenced 7% greater aerobic fitness, 20.3% greater musculoskeletal strength, and 4.7% better agility/speed at posttesting compared with CON. In the FitKids project, a 3-year physical activity and obesity prevention initiative resulted in positive improvements in both cardiorespiratory fitness and obesity in children except in summer months where attendance rates were greatly reduced.11 Within 8 months, significant improvements in cardiorespiratory fitness and obesity were observed in the FitKid program.38 In the current program, a 4-month intervention resulted in significant improvements in multiple physical fitness measures concomitant with reductions in adiposity levels. Furthermore, gains in fitness levels were all large and taken together with large reductions in adiposity, the THINK program can serve as a great preventative strategy for promoting long-term health in youth.

The concept of physical literacy has gained much attention as it relates to active lifestyle behaviors. Faigenbaum39 proposed the “Physical Inactivity Triad” to explain the complex interrelationship between physical illiteracy and sedentary behaviors and its adverse physiological sequelae that ultimately impact obesity in children today. Participants in the THINK program evidenced improvements in their exercise/fitness test, which encompassed knowledge of the benefits of regular physical activity but not exercise enjoyment or exercise self-confidence, which are also components of physical literacy. It may be that behavioral changes take longer to establish, that these behaviors may operate independently of other components of physical literacy, and/or that the questionnaires used to evaluate these behaviors were unable to discern changes in our sample of minority children.

Scores on the CATCH questionnaire29 encompassing nutrition knowledge and dietary and physical activity behaviors were higher in THINK compared with CON, and this was reinforced by higher scores on their nutrition science test at the end of the program. The importance of adequate nutrient intake during the early–middle stages of child development, ages 6 to 12, has been championed by The Academy of Nutrition and Dietetics.40 In a 7-month after-school program for fourth- to sixth-grade children focusing on nutrient consumption, the intake of fruits and vegetables increased, but results were only significant for participants who were initially deficient.41 Although we did not quantify fruit and vegetable deficiencies, our results are quite promising in view of the early impact that poor nutrition behaviors can have on long-term cardiovascular health and well-being.42

There were several limitations of the study that should be addressed. This was not a randomized trial as the YMCA selected 4 schools based on logistical considerations discussed earlier. With only 4 schools and a limited sample size, random assignment of students to THINK and CON may not have resolved this problem. There was no power analysis since the randomization occurred at the school level and not the participant level. Therefore, all students who attended the after-school program at the school attended the randomized program (THINK or CON program). As the THINK group possessed higher skinfold thicknesses and BMI ≥ 85% initially, there was the potential for regression toward the mean at posttesting. Due to absenteeism in both groups, not all students were able to complete all posttesting evaluations. Results for Latino and black children were combined in our analyses; however, in the future, it may be advisable to examine Latino and black children independently. Clinical outcomes, such as physical activity levels using accelerometer trackers, were not measured. Although physical fitness levels were carefully examined, more scientific methods of evaluating physical activity should be included. Although physical fitness levels were carefully examined, more scientific methods of evaluating physical activity, using trackers or accelerometers, should be included. Finally, executing this program required a large number of staff members trained in movement science and nutrition. Future research should include testing the efficacy of training current after-school support staff on executing the THINK program, including workshops, periodic seminars, and site visits to provide widespread dissemination of the THINK program to underserved, economically disadvantaged communities. Of note, the laboratory elements included low-cost, portable equipment that could easily be transported or housed onsite. Given improvements in variables integral to one’s personal health and well-being, the benefit to cost ratio would warrant support from the local school board, parent–teachers association, and/or local community.

Conclusion

The THINK program differed from the traditional after-school curriculum in that it used hands-on laboratory experiences in exercise science and appropriate physical activities to reinforce health-related themes. The focus on nutrition and physical literacy aimed to improve children’s ability to maintain an active healthy lifestyle along with a knowledge of the benefits of regular physical activity.14 To our knowledge, this is the first type of program to integrate such elements into a single program. The program also demonstrated the importance of a strong partnership between a local university and the community in promoting health and fitness. Future research should focus on strategies to enhance long-term implementation and sustainability of the THINK program across a larger number of participating after-school programs, placing greater emphasis on the interface of physical literacy components with physical fitness and clinical outcome measures.

Acknowledgments

The authors gratefully acknowledge the contribution of the anonymous foundation that supported the study, the YMCA after-school organization that facilitated the study, and the student volunteers who helped run the program.

References

  • 1.

    Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311(8):806814. PubMed ID: 24570244 doi:10.1001/jama.2014.732

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Han JC, Lawlor DA, Kimm SYS. Childhood obesity. Lancet. 2010;375:17371748. PubMed ID: 20451244

  • 3.

    Franks PW, Hanson RL, Knowler WC, Sievers ML, Bennett PH, Looker HC. Childhood obesity, other cardiovascular risk factors, and premature death. N Engl J Med. 2010;362(6):485493. PubMed ID: 20147714 doi:10.1056/NEJMoa0904130

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Hao G, Wang X, Treiber FA, Harshfield G, Kapuku G. Su S. Body mass index trajectories in childhood is predictive of cardiovascular risk: results from the 23-year longitudinal Georgia Stress and Heart Study. Int J Obes. 2018;42(4):923925. doi:10.1038/ijo.2017.244

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Ziyab AH, Karmaus W, Kurukulaaratchy RJ, Zhang H, Arshad SH. Developmental trajectories of body mass index from infancy to 18 years of age: prenatal determinants and health consequences. J Epidemol Commun Health. 2014;68(10):934941. doi:10.1136/jech-2014-203808

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Ferdinand KC. Hypertension in minority populations. J Clin Hypertens. 2006;8(5):365368. doi:10.1111/j.1524-6175.2006.05112.x.

  • 7.

    Chow E, Footer H, Gonzalez V, Mclver L. The disparate impact of diabetes on racial/ethnic minority populations. Clin Diab. 2012;30(3):130133. doi:10.2337/diaclin.30.3.130

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Smith EP. The role of afterschool settings in positive youth development. J Adolesc Health. 2007;41(3):219220. PubMed ID: 17707289 doi:10.1016/j.jadohealth.2007.06.010

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Beets MW, Huberty J, Beighle A, Healthy Afterschool Program Network. Physical activity of children attending afterschool programs: research- and practice-based implications. Am J Prev Med. 2012;42(2):180184. PubMed ID: 22261215 doi:10.1016/j.amepre.2011.10.007

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Slawta J, Bentley J, Smith J, Kelly J, Syman-Degler L. Promoting healthy lifestyles in children: a pilot program of be a fit kid. Health Promot Pract. 2008;9(3):305312. PubMed ID: 16803930 doi:10.1177/1524839906289221

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Yin Z, Moore JB, Johnson MH, Vernon MM, Gutin B. The impact of a 3-year after-school obesity prevention program in elementary school children. Child Obes. 2012;8(1):6070. PubMed ID: 22799482 doi:10.1089/chi.2011.0085

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Herrick H, Thompson H, Kinder J, Madsen KA. Use of SPARK to promote after-school physical activity. J Sch Health. 2012; 82(10):457461. PubMed ID: 22954164 doi:10.1111/j.1746-1561.2012.00722.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Gruner J. The Course Syllabus: A Learning-Centered Approach. Jaffrey, NH: Anker Publishing Company, Inc.; 1997.

  • 14.

    Longmuir PE, Boyer C, Yang Y, Boiarskaia E, Zhu W, Tremblay MS. The Canadian Assessment of Physical literacy: methods for children in grades 4-6 (8-12 years). BMC Public Health. 2015;15(1):767793. PubMed ID: 26260572 doi:10.1186/s12889-015-2106-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Mantilla C. A Comparison Between a Comprehensive Wellness-Based After-School Program and a Traditional YMCA After-School Program on Measures of Physical Fitness, Health-Related and Executive Cognitive Function Variables in Minority Elementary School Children. University of Miami;ProQuest Dissertations & Theses Global.2014; 3683759.

    • Search Google Scholar
    • Export Citation
  • 16.

    Edwards ES. Results From a Pilot Translational Health and Wellness-Based Summer Program in Minority Adolescents. University of Miami: ProQuest Dissertations and Theses Global. 2011; 3456328.

    • Search Google Scholar
    • Export Citation
  • 17.

    Bailey DP, Locke CD. Breaking up prolonged sitting with light intensity walking improves postprandial glycemia, but breaking up sitting does not. J Sci Med Sport. 2015;18(3):294298. doi:10.1016/j.jsams.2014.03.008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Saunders TJ, Larouche R, Colley RC, Tremblay MS. Acute sedentary behavior and markers of cardiometabolc risk: a systemic review of intervention studies. J Nutr Met. 2012;44:1–12.

    • Search Google Scholar
    • Export Citation
  • 19.

    Restaino RM, Holwerda SW, Credeur DP, Fadel PJ, Padilla J. Impact of prolonged sitting on lower and upper limb micro- and macro-vascular dilator function. Exp Physiol. 2015;100(7):829838. doi:10.1113/EP085238

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Bandura A. Self-efficacy. In: Ramachaudran IVS, ed. Encyclopedia of Human Behavior. New York, NY: Academic Press; 1994:7181.

  • 21.

    Kirkendall WM, Feinleib M, Freis ED, Mark AL. Recommendations for human blood pressure determination by sphygmomanometers. Subcommittee of the AHA Postgraduate Education Committee. Circulation. 1980;62(5):1146A55A. PubMed ID: 7309211

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Manual. Champaign, IL: Human Kinetics Books; 1988.

  • 23.

    Fess E. Grip strength. JS Casanova, ed. Clinical Assessment Recommendations. 2nd edition. Chicago, IL:American Society of Hand Therapists; 1992;2:4145.

    • Search Google Scholar
    • Export Citation
  • 24.

    Bohannon RW, Bubela D, Magasi S, McCreath H, Wang YC, Reuben D, Rymer WZ, Gershon R. Comparison of walking performance over the first 2 minutes and the full 6 minutes of the Six-Minute Walk Test. BMC Res Notes. 2014;7(1):269. PubMed ID: 24767634 doi:10.1186/1756-0500-7-269

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Pin TW, Choi HL. Reliability, validity, and norms of the 2-min walk test in children with and without neuromuscular disorders aged 6-12. Disabil Rehabil. 2018;40(11):12661272. PubMed ID: 28637155 doi:10.1080/09638288.2017.1294208

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    The President’s Challenge: Physical Activity and Fitness Awards Program (PCPFS). Physical activity & fitness awards program. In: The President’s Council on Physical Fitness and Sports. US. Department of Health and Human Services; 2009–2010:12–13.

    • Search Google Scholar
    • Export Citation
  • 27.

    Ferreira LC, Schilling BK, Weiss LW, Fry AC, Chiu LZ. Reach height and jump displacement: implications for standardization of reach determination. J Strength Cond Res. 2010;24(6):15961601. PubMed ID: 20508464 doi:10.1519/JSC.0b013e3181d54a25

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Plowman SA, Meredith MD. Fitnessgram/Activitygram Reference Guide. 4th ed. Dallas, TX: The Cooper Institute; 2013.

  • 29.

    Kelder S, Hoelscher DM, Barroso CS, Walker JL, Cribb P, Hu S. The CATCH Kids Club: a pilot after-school study for improving elementary students’ nutrition and physical activity. Public Health Nutr. 2005;8(2):133140. PubMed ID: 15877906 doi:10.1079/PHN2004678

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Kendzierski D, DeCarlo J. Physical activity enjoyment scale: two validation studies. J Sport Exerc Psychol. 1991;13(1):5064. doi:10.1123/jsep.13.1.50

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Kroll T, Kehn M, Ho PS, Groah S. The SCI Exercise Self-Efficacy Scale (ESES): development and psychometric properties. Int J Behav Nutr Phys Act. 2007;4(1):34. PubMed ID: 17760999 doi:10.1186/1479-5868-4-34

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Rosenbaum M. Epidemiology of pediatric obesity. Pediatr Ann. 2007;36(2):8995. PubMed ID: 17330571 doi:10.3928/0090-4481-20070201-07

  • 33.

    Daviglus ML, Talavera GA, Aviles-Santa ML, et al. . Prevalence of major cardiovascular risk factors and cardiovascular diseases among Hispanic/Latino individuals of diverse backgrounds in the United States. JAMA. 2012;308:17751784.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Kvaavik E, Klepp KI, Tell GS, Meyer HE, Batty GD. Physical fitness and physical activity at 13 years as predictors of cardiovascular disease risk factors at ages 15, 25, 33, and 40 years: extended follow-up of the Oslo Youth Study. Pediatrics. 2009;123:e80e86.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Report, 2008. Washington, DC: U.S. Department of Health and Human Services; 2008.

    • Search Google Scholar
    • Export Citation
  • 36.

    Tomkinson GR, Olds TS. Secular changes in pediatric aerobic fitness test performance: the global picture. Med Sport Sci. 2007;50:4666. PubMed ID: 17387251

  • 37.

    Farooq MA, Parkinson KN, Adamson AJ, Pearce MS, Reilly JK, Hughes AR, Janssen X, Basterfield L, Reilly JJ. Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study. Br J Sports Med. 2018;52(15):10021006. PubMed ID: 28288966 doi:10.1136/bjsports-2016-096933

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Gutin B, Yin Z, Johnson M, Barbeau P. Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project. Int J Pediatr Obes. 2008;3(suppl):39. doi:10.1080/17477160801896457

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Faigenbaum AD, Rebullido TR, MacDonald JP. Pediatric inactivity triad: a risky PIT. Curr Sports Med Rep. 2018;17(2):4547. PubMed ID: 29420346 doi:10.1249/JSR.0000000000000450

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Ogata BN, Hayes D. Position of the Academy of Nutrition and Dietetics: nutrition guidance for healthy children ages 2 to 11 years. J Acad Nutr Diet. 2014;114(8):12571276. PubMed ID: 25060139 doi:10.1016/j.jand.2014.06.001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41.

    Iversen CS, Nigg C, Titchenal CA. The impact of an elementary after-school nutrition and physical activity program on children’s fruit and vegetable intake, physical activity, and body mass index: Fun 5. Hawaii Med J. 2011;70(7)(suppl 1):3741.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Gidding SS, Dennison BA, Birch LL, et al. . Dietary recommendations for children and adolescents: a guide for practitioners: consensus statement from the American Heart Association. Circulation. 2005;112(13):20612075. PubMed ID: 16186441 doi:10.1161/CIRCULATIONAHA.105.169251

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

Perry, Flanagan, Velasquez, Bolon, and Zito are with the Department of Kinesiology and Sport Sciences, School of Education and Human Development, University of Miami, Coral Gables, FL, USA. Ahn is with the Department of Educational and Psychological Studies, School of Education and Human Development, University of Miami, Coral Gables, FL, USA.

Perry (aperry@miami.edu) is corresponding author.
  • View in gallery

    —Timeline for the experimental THINK and CON programs. CON indicates control; THINK, translational health in nutrition and kinesiology; SPARK, Sports, Play, and Active Recreation for Kids.

  • View in gallery

    —Graph illustrating significant changes in skinfold measures between THINK and CON group. Data are presented as posttest skinfold means adjusted for baseline values using ANCOVA for THINK and CON groups. ANCOVA indicates analysis of covariance; CON, control; THINK, translational health in nutrition and kinesiology. *P < .05 compared with CON. **P ≤ .001 compared with CON.

  • View in gallery

    —Graph illustrating group changes in physical fitness variables. Data are presented as posttest means adjusted for baseline values in physical fitness measures using ANCOVA for THINK and CON groups. Aerobic fitness measured during a 2-minute walk test for distance covered; agility measured using a shuttle run; strength measured using grip dynamometry. ANCOVA indicates analysis of covariance; CON, control; THINK, translational health in nutrition and kinesiology. *P ≤ .05 compared with CON. **P ≤ .01 compared with CON. ***P < .001 compared with CON.

  • View in gallery

    —Graph illustrating group changes in exercise/fitness and nutrition knowledge/behaviors. Data are presented as posttest means adjusted for baseline values using ANCOVA for THINK and CON groups. Exercise/fitness test, CATCH questionnaire, and nutrition science test were all graded on a 0% to 100% basis. ANCOVA indicates analysis of covariance; CATCH, Coordinated Approach to Child Health; CON, control; THINK, translational health in nutrition and kinesiology. *P ≤ .05 compared with CON. **P < .001 compared with CON.

  • 1.

    Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014;311(8):806814. PubMed ID: 24570244 doi:10.1001/jama.2014.732

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Han JC, Lawlor DA, Kimm SYS. Childhood obesity. Lancet. 2010;375:17371748. PubMed ID: 20451244

  • 3.

    Franks PW, Hanson RL, Knowler WC, Sievers ML, Bennett PH, Looker HC. Childhood obesity, other cardiovascular risk factors, and premature death. N Engl J Med. 2010;362(6):485493. PubMed ID: 20147714 doi:10.1056/NEJMoa0904130

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Hao G, Wang X, Treiber FA, Harshfield G, Kapuku G. Su S. Body mass index trajectories in childhood is predictive of cardiovascular risk: results from the 23-year longitudinal Georgia Stress and Heart Study. Int J Obes. 2018;42(4):923925. doi:10.1038/ijo.2017.244

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Ziyab AH, Karmaus W, Kurukulaaratchy RJ, Zhang H, Arshad SH. Developmental trajectories of body mass index from infancy to 18 years of age: prenatal determinants and health consequences. J Epidemol Commun Health. 2014;68(10):934941. doi:10.1136/jech-2014-203808

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Ferdinand KC. Hypertension in minority populations. J Clin Hypertens. 2006;8(5):365368. doi:10.1111/j.1524-6175.2006.05112.x.

  • 7.

    Chow E, Footer H, Gonzalez V, Mclver L. The disparate impact of diabetes on racial/ethnic minority populations. Clin Diab. 2012;30(3):130133. doi:10.2337/diaclin.30.3.130

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Smith EP. The role of afterschool settings in positive youth development. J Adolesc Health. 2007;41(3):219220. PubMed ID: 17707289 doi:10.1016/j.jadohealth.2007.06.010

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Beets MW, Huberty J, Beighle A, Healthy Afterschool Program Network. Physical activity of children attending afterschool programs: research- and practice-based implications. Am J Prev Med. 2012;42(2):180184. PubMed ID: 22261215 doi:10.1016/j.amepre.2011.10.007

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Slawta J, Bentley J, Smith J, Kelly J, Syman-Degler L. Promoting healthy lifestyles in children: a pilot program of be a fit kid. Health Promot Pract. 2008;9(3):305312. PubMed ID: 16803930 doi:10.1177/1524839906289221

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Yin Z, Moore JB, Johnson MH, Vernon MM, Gutin B. The impact of a 3-year after-school obesity prevention program in elementary school children. Child Obes. 2012;8(1):6070. PubMed ID: 22799482 doi:10.1089/chi.2011.0085

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Herrick H, Thompson H, Kinder J, Madsen KA. Use of SPARK to promote after-school physical activity. J Sch Health. 2012; 82(10):457461. PubMed ID: 22954164 doi:10.1111/j.1746-1561.2012.00722.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Gruner J. The Course Syllabus: A Learning-Centered Approach. Jaffrey, NH: Anker Publishing Company, Inc.; 1997.

  • 14.

    Longmuir PE, Boyer C, Yang Y, Boiarskaia E, Zhu W, Tremblay MS. The Canadian Assessment of Physical literacy: methods for children in grades 4-6 (8-12 years). BMC Public Health. 2015;15(1):767793. PubMed ID: 26260572 doi:10.1186/s12889-015-2106-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Mantilla C. A Comparison Between a Comprehensive Wellness-Based After-School Program and a Traditional YMCA After-School Program on Measures of Physical Fitness, Health-Related and Executive Cognitive Function Variables in Minority Elementary School Children. University of Miami;ProQuest Dissertations & Theses Global.2014; 3683759.

    • Search Google Scholar
    • Export Citation
  • 16.

    Edwards ES. Results From a Pilot Translational Health and Wellness-Based Summer Program in Minority Adolescents. University of Miami: ProQuest Dissertations and Theses Global. 2011; 3456328.

    • Search Google Scholar
    • Export Citation
  • 17.

    Bailey DP, Locke CD. Breaking up prolonged sitting with light intensity walking improves postprandial glycemia, but breaking up sitting does not. J Sci Med Sport. 2015;18(3):294298. doi:10.1016/j.jsams.2014.03.008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Saunders TJ, Larouche R, Colley RC, Tremblay MS. Acute sedentary behavior and markers of cardiometabolc risk: a systemic review of intervention studies. J Nutr Met. 2012;44:1–12.

    • Search Google Scholar
    • Export Citation
  • 19.

    Restaino RM, Holwerda SW, Credeur DP, Fadel PJ, Padilla J. Impact of prolonged sitting on lower and upper limb micro- and macro-vascular dilator function. Exp Physiol. 2015;100(7):829838. doi:10.1113/EP085238

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Bandura A. Self-efficacy. In: Ramachaudran IVS, ed. Encyclopedia of Human Behavior. New York, NY: Academic Press; 1994:7181.

  • 21.

    Kirkendall WM, Feinleib M, Freis ED, Mark AL. Recommendations for human blood pressure determination by sphygmomanometers. Subcommittee of the AHA Postgraduate Education Committee. Circulation. 1980;62(5):1146A55A. PubMed ID: 7309211

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Manual. Champaign, IL: Human Kinetics Books; 1988.

  • 23.

    Fess E. Grip strength. JS Casanova, ed. Clinical Assessment Recommendations. 2nd edition. Chicago, IL:American Society of Hand Therapists; 1992;2:4145.

    • Search Google Scholar
    • Export Citation
  • 24.

    Bohannon RW, Bubela D, Magasi S, McCreath H, Wang YC, Reuben D, Rymer WZ, Gershon R. Comparison of walking performance over the first 2 minutes and the full 6 minutes of the Six-Minute Walk Test. BMC Res Notes. 2014;7(1):269. PubMed ID: 24767634 doi:10.1186/1756-0500-7-269

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Pin TW, Choi HL. Reliability, validity, and norms of the 2-min walk test in children with and without neuromuscular disorders aged 6-12. Disabil Rehabil. 2018;40(11):12661272. PubMed ID: 28637155 doi:10.1080/09638288.2017.1294208

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    The President’s Challenge: Physical Activity and Fitness Awards Program (PCPFS). Physical activity & fitness awards program. In: The President’s Council on Physical Fitness and Sports. US. Department of Health and Human Services; 2009–2010:12–13.

    • Search Google Scholar
    • Export Citation
  • 27.

    Ferreira LC, Schilling BK, Weiss LW, Fry AC, Chiu LZ. Reach height and jump displacement: implications for standardization of reach determination. J Strength Cond Res. 2010;24(6):15961601. PubMed ID: 20508464 doi:10.1519/JSC.0b013e3181d54a25

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Plowman SA, Meredith MD. Fitnessgram/Activitygram Reference Guide. 4th ed. Dallas, TX: The Cooper Institute; 2013.

  • 29.

    Kelder S, Hoelscher DM, Barroso CS, Walker JL, Cribb P, Hu S. The CATCH Kids Club: a pilot after-school study for improving elementary students’ nutrition and physical activity. Public Health Nutr. 2005;8(2):133140. PubMed ID: 15877906 doi:10.1079/PHN2004678

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Kendzierski D, DeCarlo J. Physical activity enjoyment scale: two validation studies. J Sport Exerc Psychol. 1991;13(1):5064. doi:10.1123/jsep.13.1.50

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 31.

    Kroll T, Kehn M, Ho PS, Groah S. The SCI Exercise Self-Efficacy Scale (ESES): development and psychometric properties. Int J Behav Nutr Phys Act. 2007;4(1):34. PubMed ID: 17760999 doi:10.1186/1479-5868-4-34

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Rosenbaum M. Epidemiology of pediatric obesity. Pediatr Ann. 2007;36(2):8995. PubMed ID: 17330571 doi:10.3928/0090-4481-20070201-07

  • 33.

    Daviglus ML, Talavera GA, Aviles-Santa ML, et al. . Prevalence of major cardiovascular risk factors and cardiovascular diseases among Hispanic/Latino individuals of diverse backgrounds in the United States. JAMA. 2012;308:17751784.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Kvaavik E, Klepp KI, Tell GS, Meyer HE, Batty GD. Physical fitness and physical activity at 13 years as predictors of cardiovascular disease risk factors at ages 15, 25, 33, and 40 years: extended follow-up of the Oslo Youth Study. Pediatrics. 2009;123:e80e86.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Report, 2008. Washington, DC: U.S. Department of Health and Human Services; 2008.

    • Search Google Scholar
    • Export Citation
  • 36.

    Tomkinson GR, Olds TS. Secular changes in pediatric aerobic fitness test performance: the global picture. Med Sport Sci. 2007;50:4666. PubMed ID: 17387251

  • 37.

    Farooq MA, Parkinson KN, Adamson AJ, Pearce MS, Reilly JK, Hughes AR, Janssen X, Basterfield L, Reilly JJ. Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study. Br J Sports Med. 2018;52(15):10021006. PubMed ID: 28288966 doi:10.1136/bjsports-2016-096933

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Gutin B, Yin Z, Johnson M, Barbeau P. Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project. Int J Pediatr Obes. 2008;3(suppl):39. doi:10.1080/17477160801896457

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39.

    Faigenbaum AD, Rebullido TR, MacDonald JP. Pediatric inactivity triad: a risky PIT. Curr Sports Med Rep. 2018;17(2):4547. PubMed ID: 29420346 doi:10.1249/JSR.0000000000000450

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Ogata BN, Hayes D. Position of the Academy of Nutrition and Dietetics: nutrition guidance for healthy children ages 2 to 11 years. J Acad Nutr Diet. 2014;114(8):12571276. PubMed ID: 25060139 doi:10.1016/j.jand.2014.06.001

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 41.

    Iversen CS, Nigg C, Titchenal CA. The impact of an elementary after-school nutrition and physical activity program on children’s fruit and vegetable intake, physical activity, and body mass index: Fun 5. Hawaii Med J. 2011;70(7)(suppl 1):3741.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Gidding SS, Dennison BA, Birch LL, et al. . Dietary recommendations for children and adolescents: a guide for practitioners: consensus statement from the American Heart Association. Circulation. 2005;112(13):20612075. PubMed ID: 16186441 doi:10.1161/CIRCULATIONAHA.105.169251

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 116 116 116
PDF Downloads 95 95 95