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. Author manuscript; available in PMC: 2026 Oct 20.
Published before final editing as: Am J Lifestyle Med. 2026 Mar 7:15598276261430659. doi: 10.1177/15598276261430659

Feasibility and Acceptability of a Community and Family-Based Fitness and Healthy Lifestyle Program Among Latino Families: The Athletes for Life Program

Bianca Vargas Tequida 1, Sonia Vega-López 2, Alberto Flórez-Pregonero 3, Michael Todd 4, Frank Ray 5, Gabriel Q Shaibi 6, Noe C Crespo 7,8
PMCID: PMC12967276  NIHMSID: NIHMS2184066  PMID: 41804391

Abstract

Promoting fitness may be a viable and acceptable approach for chronic disease prevention. This pilot study evaluated the feasibility, acceptability, and preliminary efficacy of a behavioral and fitness-oriented intervention called “Athletes for Life Program” (AFL) implemented in a community center. AFL was a pre-post, 6-week program. Latino families (n = 24) participated in weekly 90-minute physical activity (PA) and nutrition sessions. Measures included fitness, accelerometer-measured PA, body mass index (BMI), and self-report survey. Feasibility and acceptability were evaluated via post-intervention interviews. Intervention effects were tested using paired samples t-test and qualitative data via thematic analysis. Most parents were female (96%) and Latino (79%), while children were male (57%) and Latino (83%). Retention and attendance rates were 75% and 67% for parents and 81% and 70.8% for children. Children improved muscular endurance, speed, and cardiovascular endurance (P < 0.01), with no change in habitual Moderate-to-Vigorous Physical Activity (MVPA). There were significant reductions in children’s consumption of soda (2.0 ± 1.4 vs 1.6 ± 1.2, P < 0.01), fruit-flavored drinks (2.0 ± 1.5 vs 1.1 ± 1.3, P = .01), and eating cake/pastries (1.48 ± 1.1 vs 1.0 ± 0.8, P = .05). Families expressed interest in continuing to participate in AFL. AFL is a promising family-based fitness-focused program to improve health among Latinos.

Keywords: fitness, healthy lifestyle, community-based, family program, Latino, community engaged lifestyle medicine, childhood obesity

Introduction

Chronic diseases are major public health challenges in the United States.1 Ethnic minority groups, such as Latinos and low-income individuals, suffer disproportionately from major chronic conditions and associated risk factors.2 Low-income Latino children have a greater prevalence of behavioral risk factors (e.g., low physical activity and a diet high in sugars and fat) compared to non-Hispanic white children.3,4 The causes for these racial and ethnic health inequities are multifactorial, and it is recognized that long-term success requires targeting multilevel factors such as social support5 as well as proximal (e.g., home)6 and distal environments (e.g., parks). Interventions that involve the family (both child and parent) and increase access to community resources, such as parks and healthy lifestyle programs, show greater potential for long-term success.7 The key challenge to these efforts is to design and implement programs that are both acceptable (e.g., culturally tailored) to the priority community and are feasible to implement (i.e., practical and sustainable).

Cardiovascular fitness (CVF) is an important health indicator for both children and adults.8 Children with low CVF are at an increased risk for obesity and chronic disease.9–12 Of note, the benefits of improving CVF are partially independent of obesity.13,14 Additionally, focusing on weight loss can result in weight stigma and blaming of parents, which in turn can lower parents’ willingness to engage in behavior change. Thus, a fitness- and behavioral-focused approach may be more acceptable and feasible among racially and ethnically minoritized populations. This approach is also in line with the recommendations by the American Heart Association to focus on evaluating CVF as an independent predictor of health risk.15,16 The purpose of this pilot study was to evaluate the feasibility, acceptability, and preliminary efficacy of a fitness- and lifestyle-oriented program called the Athletes for Life (AFL) program.

Methods

Community-Academic Partnership

The study team partnered with a local city recreation center in Phoenix, AZ, to co-design the AFL program. A key consideration was to develop a program that was appealing and culturally acceptable to the local community. This led to the development of a program that does not focus on weight loss or obesity but rather on health, prevention of chronic disease, and being physically fit through the lifespan; therefore, the program was named Athletes for Life. This partnership resulted in a longstanding collaboration with decisions made bilaterally, each collaborator contributes expertise and resources, and where dissemination and presentation of outcomes are conducted in collaboration with each partner. Intramural funding from the academic institution contributed to the implementation and evaluation of this program, while the community partner contributed to sharing contextual and regional expertise, space and facilities for the program, and avenues for recruitment and community outreach.

Formative Phase

During the formative phase (also known as needs assessment), a literature review was conducted to identify previously successful strategies and approaches for community-based programs promoting physical activity (PA) and healthy eating. Census data were reviewed to understand the demographic composition of the community, and two focus groups were conducted with potential parent participants to inform the AFL program characteristics, such as language, cultural considerations, session format, and topics of interest. The information gathered during the formative phase was used to design the pilot 6-week family-based pilot program.

Program Description

The AFL pilot program consisted of a single-group, pre-post, 6-week behavioral and fitness-oriented intervention in which children participated in structured PA (fitness, sports, and skills-oriented) sessions twice weekly for 1.5 hours each (total of twelve sessions). Child sessions were held at the gymnasium and outdoor space in the community center and led by trained undergraduate and graduate students. All sessions were implemented in a group format using various strategies to promote active play and engagement of all children. Sessions were designed to progressively increase the total time engaging in Moderate-to-Vigorous Physical Activity (MVPA). Parents participated simultaneously in weekly nutrition education classes, conducted in a separate room (a total of six sessions; lasting 1.5 hours each session; delivered in English or Spanish), while their children attended the physical activity sessions. Nutrition education classes covered basic nutrition concepts, highlighting the significance of adopting healthy lifestyle choices within the family context, and parenting strategies and skills/techniques for making healthier meals at home. Immediately after the 6-week program, a youth Olympics event was held to showcase children’s improvements in skills and fitness and foster a family-centered and fun environment (instead of purely competition-focused). The curriculum was focused on promoting long-term health goals and sustainable behavior change. Self-monitoring was facilitated via tracking sheets to reinforce family goals, and points and prizes were provided as incentives. The program was developed considering the principles of social-cognitive theory and operant learning theory, which have been effectively applied to promote and sustain behavior changes.17–19

Participants and Enrollment

The a priori targeted enrollment was 20 families (with at least one parent and one child participating in the program). While there is no standard recommendation for sample size for feasibility studies, this sample size was determined based on previous literature demonstrating that at least 20 participants are sufficient to evaluate the feasibility and acceptability of a healthy lifestyle behavioral intervention.20 Eligibility criteria were: (1) a child 6–11 years old and (2) a parent/caregiver 18 years or older. Exclusion criteria were having a physical or cognitive disability to participate in PA or nutrition education sessions. Recruitment activities were conducted two months before the 6-week program. Community partners promoted the program through targeted phone outreach, printed materials, word of mouth, and engagement at community events held near the recreation center. The final enrollment was 24 parents and 37 children (some parents participated with 2 children). Written informed consent and assent were obtained from the parent and child, respectively. This study was approved by the Institutional Review Board of Arizona State University. Participants’ consent procedures and study measurements were conducted at the recreation center.

Study Measures

Child Fitness.

Children’s fitness was measured using a modified version of the Presidential FitnessGram.21 The half mile was used instead of a one-mile run, and all other fitness tests were retained as recommended. All evaluation staff underwent several training sessions to standardize protocol implementation. After a warm-up, children ran a half-mile distance in small groups (4–6 children per group). A study team member ran with the group of children to help them keep pace and verbally encouraged them to make their best effort. Run time was registered in seconds by separate evaluation staff. The 20-yard dash was used to measure speed, and children completed this measure twice (after a short rest), and their best run time (in seconds) was used for analysis. The push-ups, sit-ups, and V-test (flexibility) exercises were performed following standard protocols.14,21 The total number of repetitions for push-ups and sit-ups, and the distance for the V-test achieved by each participant during a single attempt were recorded.

Anthropometrics.

Child and parent’s height and weight were measured in triplicate using a portable stadiometer and scale (respectively), and the child’s waist circumference was measured via a tape at the level of the umbilicus using standard National Health and Nutrition Examination Survey (NHANES) procedures.22 Body mass index (BMI) and BMI percentile were calculated for adults and children, respectively.

Physical Activity.

Children’s habitual physical activity was measured using an ActiGraph accelerometer (GT3X). To capture non-intervention and intervention PA data, children wore accelerometers (at the hip) for 14 days (7 days at baseline, non-intervention week, and 7 days during the first week of the intervention). This procedure was repeated at the end of the AFL program to capture another 14 days of wear time (during the last week of the program and immediately after the program). Estimates of children’s time in MVPA were derived using equations for children, including using age-specific cut-points and 4.5 METs for the lower cut point of moderate intensity activity.23 Accelerometer wear compliance criteria were defined as a minimum of 3 week days and one weekend day for at least 10 h per day. Exceptions were made when a child engaged in water-based activities, which prevented them from achieving 10 h of wearing time (e.g., swimming). In such cases, adherence criteria were reduced to 8 h of wearing time in the day that the child engaged in water-based activities. Accelerometers were initialized the same day they were to be distributed and set to start recording data at 3 am on the following day at 30-second epochs.24 Parents were given a 7-day accelerometer diary and instructed to write down when and for what reasons their child did not wear the accelerometer during the measurement period. If the minimum compliance criteria were not met, participants were asked to re-wear the accelerometer for the necessary days needed to meet the minimum wear-time criteria.

Survey.

Parents completed a survey including questions on demographics and their children’s PA and dietary behaviors, and questions about the use of nutrition labels and food preparation methods. Children’s dietary behaviors were measured via parental reports using a previously validated food frequency questionnaire (Cronbach’s alpha = 0.52).25 Parents reported on the frequency that their child consumed specific food groups/items with the following response options: 0 days, 1 day, 2 days, 3–4 days, 5–6 days, every day. The average frequency for days/week for each variable was used in the analysis. An example of the instrument is available in Appendix A.

Feasibility and acceptability were assessed via post-intervention interviews with parents. Questions were focused on practical and logistical aspects of participating (program time, length, location, etc.), and their personal experience with the sessions (enjoyment, difficulty of material, etc.). Session attendance, 6-week retention rates, and resources needed to implement the program (e.g., staff training time and program materials) were recorded to assess feasibility. A priori thresholds for feasibility and acceptability were established based on previous pediatric obesity prevention trials in minority or low-income populations. Program retention was considered acceptable if ≥ 86% of participants completed the 6-week follow-up assessment, consistent with benchmarks reported by Cui et al (2015).26 Session attendance was considered feasible if parents and children individually attended ≥70% of scheduled sessions.27

Data Analysis

Quantitative data were summarized using means, standard deviations, and frequency counts. Paired samples t-test was used to test for pre- vs post-intervention effects on all available paired data for anthropometric, fitness, PA, and dietary outcomes (all continuous data). For MVPA data, analyses were conducted separately for MVPA during AFL sessions vs MVPA outside AFL sessions (i.e., habitual MVPA). Post-hoc analyses compared results based on session attendance to determine if results differed by level of attendance (≥50% attendance). Effect sizes were calculated as Cohen’s d (mean difference divided by the pooled standard deviation). Qualitative post-intervention data (eight parent interviews) were analyzed through thematic analysis of audio transcripts by a trained research assistant. Audio recordings were transcribed verbatim in the participant’s original language (all were in Spanish), and emergent themes were identified by organizing participants’ responses that demonstrated common ideas and constructs (e.g., enjoyment, barriers to participation, etc.). Notable quotes were translated into English and used to represent the themes.

Results

A total of 24 parents and 37 children provided baseline data, and 23–24 children completed all post-intervention measurements (Figure 1). Nearly all parents (96%) were female, 79% were Latino, and 89% were classified as living below the federal poverty level. Regarding the medical history of the parents, 18 women (75%) self-reported having had gestational diabetes, four (16%) reported having been diagnosed with type 2 diabetes, five (21%) had hypertension, and three (12%) had hypercholesterolemia. Fifty-seven percent of the children were male, and 83% were Latino. Parents’ session attendance ranged from 0–6 sessions, with a mean attendance of 4 ± 2 out of 6 (67%). Child attendance ranged from 0 to 12 sessions, with a mean of 8.5 ± 3.1 out of 12 sessions (70.8%), and 51.4% attended at least 9 sessions. The 6-week retention rates were 75% for parents and 81% for children. The reasons for discontinuing participation in the program included a lack of reliable transportation and competing demands (work schedule change, lack of childcare). Table 1 shows the anthropometric characteristics of study participants at baseline.

Figure 1.

Figure 1.

Athletes for life consort diagram.

Table 1.

Adult and Child Anthropometric Characteristics at Baseline.

N Min Max Mean ± SD
Adults
 Weight (kg) 24 51.4 125.2 80.7 ± 19.2
 BMI (kg/m2) 24 21.1 47.8 32.4 ± 7.0
Children
 WC (cm) 37 50.4 116.0 75.4 ± 15.1
 Weight (kg) 37 17.3 87.2 41.3 ± 16.6
 BMI (kg/m2) 37 13.7 41.2 22.4 ± 5.8
 BMI percentile 37 4.7 99.6 85.4 ± 22.4
 BMI z-score 37 −1.6 2.7 1.5 ± 1.0
Adults N (%) Children N (%)
Classification by BMI category
 Underweight (<18.5) 0 Underweight (<5th %ile) 1 (2.7)
 Normal weight (18.5 ≤ 25) 4 (17) Normal weight (5th- ≤ 85th %ile) 10 (27)
 Overweight (25 ≤ 30) 4 (17) Overweight (85th- ≤ 95th %ile) 6 (16)
 Obesity (≥30) 16 (66) Obesity (≥95th %ile) 20 (54)

Abbreviations: SD, standard deviation; BMI, body mass index; WC, waist circumference.

Children improved on several fitness outcomes, including muscular endurance (push-ups), speed (20-yard dash), and cardiovascular endurance (half-mile run) (Table 2). Accelerometer data showed that children’s MVPA minutes increased during AFL sessions (average 32 ± 15.28 MVPA minutes in week 1- sessions 1 & 2 vs 40 ± 32.40 MVPA minutes in week 6-sessions 11 & 12), P = 0.03. However, there was no change in habitual MVPA min/day (outside program time) pre vs post (P = 0.09).

Table 2.

Intervention Effects on Child Fitness and Physical Activity Outcomes.

N Baseline Mean ± SD Post Mean ± SD Diff. 95% CI P-value Cohen’s d
Push-ups (total #) 24 4.5 ± 2.6 10.7 ± 7.6 6.2 3.02, 9.32 <0.01 1.09
Sit-ups (total #) 23 6.8 ± 7.6 6.5 ± 4.5 −0.3 −3.17, 2.57 0.8 0.04
Sit & reach (cm) 24 24.1 ± 8.9 26.6 ± 5.7 2.5 −0.78, 5.86 0.13 0.34
20-Yard dash (sec) 23 4.9 ± 0.4 4.4 ± 0.3 −0.4 −0.56, −0.30 <0.01 1.25
Half-mile run (sec) 24 311 ± 60 275 ± 60 −36 −51.1, −20.26 <0.01 0.60
MVPA (min/day) 10 52.9 ± 21.5 42.3 ± 14.5 −10.6 −23.39, 2.17 0.09 0.58

Abbreviations: SD, standard deviation; MVPA, moderate-to-vigorous physical activity.

There was also a statistically significant reduction (pre to post) in parent-reported frequency of days per week that their children consumed soda (2.0 ± 1.4 vs 1.6 ± 1.2, P < 0.01) and fruit-flavored drinks (2.0 ± 1.5 vs 1.1 ± 1.3, P = .01). There was also a trend towards a reduction in frequency of children eating cake/pastries (1.48 ± 1.1 vs 1.0 ± 0.8, P = .05). No other dietary outcomes demonstrated a trend or were statistically significant.

There were no significant changes in BMI among participants or in child waist circumference (Table 3). Children who participated in ≥10 sessions (n = 18) vs ≤9 sessions (n = 12) showed favorable and significant improvements in waist circumference (−1.1 cm vs +2.6 cm, P < 0.01), weight (+0.09 vs +1.2 kg, P < 0.01), BMI (−0.19 kg/m2 vs + 0.24 kg/m2, P = 0.04), and BMI percentile (−2.18 vs +0.16, P = 0.06).

Table 3.

Intervention Effects on Adult and Child Weight and BMI.

N Baseline Mean ± SD Post Mean ± SD Diff. 95% CI P-value Cohen’s d
Adults
 Weight (kg) 18 77.37 ± 16.6 76.82 ± 16.2 −0.55 −1.10– 0.00 0.05 0.03
 BMI (kg/m2) 18 31.02 ± 6.3 30.81 ± 6.1 −0.22 −0.43– 0.00 0.05 0.03
Children
 WC (cm) 30 74.16 ± 15.2 74.51 ± 15.2 0.35 −1.75, 1.06 0.61 0.02
 Weight (kg) 30 40.69 ± 17.3 41.21 ± 17.3 0.52 0.12, 0.92 0.01 0.03
 BMI (kg/m2) 30 21.93 ± 5.9 21.91 ± 5.9 −0.02 −0.20, 0.23 0.86 0.00
 BMI %tile 30 83.68 ± 23.8 82.44 ± 25.1 −1.25 −2.73, 0.24 0.09 0.05
 BMI z-score 30 1.38 ± 1.04 1.35 ± 1.1 −0.03 −0.02, 0.09 0.20 0.02

Abbreviations: SD, standard deviation; BMI, body mass index; WC, waist circumference.

Implementation Notes

Here we describe our team’s direct observations during the implementation of the Youth Olympics event. A total of six parents volunteered to help plan the AFL Youth Olympics event and helped to conduct several of the events (e.g., baseball throw and soccer ball kick). Award ribbons were given to children (by age group) for the “most improved” in each fitness event and for 1st, 2nd, and 3rd place in each event. The Olympic event was attended by 15 study families, including other household and extended family members (e.g., the father, grandparents, aunts/uncles, and friends of the family). Notable quotes by children were: “All my friends joined AFL, and it made it more fun,” “The Olympics event was the best. I had fun showing off my new skills.” Notable quotes from parents were: “I met a lot of other parents interested in being healthier, ” “I was able to spend time with my kids doing something to improve both our lives.”

Post-intervention interviews with eight parents revealed valuable information regarding their experiences with the program and their recommendations for improvements. Common emergent themes were the desire that the program length be extended beyond 6 weeks to allow them to cover/learn more material. Parents also demonstrated interest in participating in more sessions and in participating in structured group PA sessions for adults, such as walking, yoga, aerobics, and Zumba. Overall, parents commented that they and their children enjoyed the program. Children expressed that they enjoyed the fitness- and sport-oriented program and the types of games and skills they learned. Barriers to participating in the program included time constraints and time conflicts (work and child school schedules), unexpected illness in the family, and unreliable transportation.

Discussion

The results of this 6-week pilot study were promising and suggested that the AFL program was feasible and acceptable to study participants. When evaluated against predefined feasibility thresholds, parent attendance fell slightly below the 70% target, while child attendance met the criteria. Six-week retention met the predefined benchmark among parents but not among children. Despite these mixed quantitative results, qualitative feedback from parents indicated strong program acceptability, supporting the feasibility of implementing AFL within Latino families.

On average, families attended 66% of the total sessions, and qualitative data supported the feasibility and acceptability of the AFL program. The primary reasons for missing program sessions were related to outside factors (e.g., lack of transportation, lack of childcare for younger children not participating in the program, and conflicting work schedules). This is consistent with the barriers to participation that are reported in previous studies among low-income families.28 The AFL program was held on weekdays and in the late afternoon to allow parents and children to participate outside work and school hours. However, it was difficult to identify times that worked for all families, given that constraints varied by family and other factors that changed during the program. Nonetheless, parents and children expressed their interest in continuing with the program and felt that the program length was too short. Given this evidence, future efforts should consider offering the program on different days of the week (including weekends) and hours of the day to facilitate program participation from families with differing schedules and needs.

The preliminary efficacy data support our hypothesis that a child’s fitness and performance can be improved in a short time frame (6 weeks) through a fitness- and sports-oriented program. Of importance was that these fitness improvements were observed without changes in anthropometric measures (BMI or waist circumference). These results are consistent with previous research that supports the efficacy of improving fitness among young children independent of BMI.29 These findings also support the rationale for our approach, which targets improvements in fitness rather than a change in BMI and provides preliminary evidence to develop larger-scale efficacy studies.

AFL also targeted changes in children’s dietary and physical activity behaviors. Parent-report data demonstrated improvements in several targeted child dietary behaviors (e.g., reduction in frequency of soda consumption), and these findings support previous family-based behavioral interventions.30 Lastly, child MVPA minutes during the program sessions (weeks 1 and 6) significantly increased. This increase in MVPA was purposeful, given the program structure and curriculum, and supports that the AFL program was successful at increasing time in MVPA during the child sessions. However, the child’s MVPA min/day outside the program (baseline vs post) did not change and demonstrated a trend toward a reduction. The average habitual MVPA was 42.3 min/day, which is below the national guidelines of 60 minutes per day of MVPA for children aged 6–17 years.31 These findings suggest that MVPA during the AFL program may not translate to increases in habitual MVPA, or perhaps there can be a compensatory decrease in habitual MVPA if children increase sedentary time outside the sessions. A longer and more intensive behavioral approach may be needed to exhibit changes in the child’s habitual MVPA or to prevent compensatory increases in sedentary time.32 Future research should incorporate behavioral strategies that support lifestyle changes in children’s participation in recreational and sports activities that are outside a structured program.

Study limitations include a lack of control group, a relatively small sample size, the use of self-report measures of child dietary behaviors, and the use of a single reviewer to analyze the qualitative data. Thus, the study results should be interpreted with caution. Nonetheless, the primary aims of this pilot study were achieved, as it appears that the AFL program was feasible and acceptable to study participants, and there were improvements in child fitness parameters.

Implications for Practice

The AFL program demonstrates potential for sustainability and scalability, particularly for Latino families and in community centers. This offers valuable implications for health equity and practice-based research. It provides a novel and potentially replicable model for programs seeking to engage families in culturally responsive, community-driven health promotion. Future research should rigorously evaluate cost-effectiveness, short- and long-term efficacy for fitness- and behavioral-outcomes, extend behavior change strategies outside the AFL program sessions, and rigorously monitor fidelity and set a priori feasibility thresholds.

Conclusion

These preliminary results help set the foundation for the development of larger randomized controlled trials that leverage resources among multiple organizations to implement and evaluate efficacious programs aimed at reducing cardiovascular disease risk among high-risk populations. Community centers are an important setting for implementing family-based programs. This study highlights important considerations for future community-based research programs.

Supplementary Material

SJ

Supplemental material is available online.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Administrative and (or) IT support was provided to NCC by the SDSU HealthLINK Endowment (S21MD010690) and College Health Solutions at Arizona State University.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

“Families attended 66% of the total sessions, and qualitative data supported the feasibility and acceptability of the AFL program.”

Contributor Information

Bianca Vargas Tequida, Institute for Behavioral and Community Health, San Diego State University, San Diego, CA, USA.

Sonia Vega-López, College of Health Solutions and Southwest Interdisciplinary Research Center, Arizona State University, Phoenix, AZ, USA.

Alberto Flórez-Pregonero, Facultad de Educación, Pontificia Universidad Javeriana, Bogotá, Colombia.

Michael Todd, College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA.

Frank Ray, Department of Parks and Recreation, City of Phoenix, Phoenix, AZ, USA.

Gabriel Q. Shaibi, Center for Health Promotion and Disease Prevention, Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA.

Noe C. Crespo, Institute for Behavioral and Community Health, San Diego State University, San Diego, CA, USA; School of Public Health, San Diego State University, San Diego, CA, USA..

References

  • 1.Hacker K The burden of chronic disease. Mayo Clin Proc Innov Qual Outcomes. 2024;8(1):112–119. doi: 10.1016/j.mayocpiqo.2023.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Obesity and Hispanic Americans. Accessed 18 June 2024, 2024.https://minorityhealth.hhs.gov/obesity-and-hispanic-americans
  • 3.Taveras EM, Gillman MW, Kleinman K, Rich-Edwards JW, Rifas-Shiman SL. Racial/Ethnic differences in early-life risk factors for childhood obesity. Pediatrics. 2010;125(4):686–695. doi: 10.1542/peds.2009-2100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Domogalla B, Ko LK, Jones R, et al. Rural Latino parent and child physical activity patterns: family environment matters. BMC Public Health. 2021;21(1): 2043. doi: 10.1186/s12889-021-12085-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Li JS, Barnett TA, Goodman E, Wasserman RC, Kemper AR. Approaches to the prevention and management of childhood obesity: the role of social networks and the use of social media and related electronic technologies: a scientific statement from the American heart association. Circulation. 2013;127(2):260–267. doi: 10.1161/CIR.0b013e3182756d8e [DOI] [PubMed] [Google Scholar]
  • 6.Ochoa A, Berge JM. Home environmental influences on childhood obesity in the Latino population: a decade review of literature. J Immigr Minority Health. 2017;19(2):430–447. doi: 10.1007/s10903-016-0539-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Epstein LH, Valoski A, Wing RR, McCurley J. Ten-year outcomes of behavioral family-based treatment for childhood obesity. Health Psychol. 1994;13(5):373–383. doi: 10.1037//0278-6133.13.5.373 [DOI] [PubMed] [Google Scholar]
  • 8.Kaminsky LA, Arena R, Beckie TM, et al. The importance of cardiorespiratory fitness in the United States: the need for a national registry: a policy statement from the American heart association. Circulation. 2013; 127(5):652–662. doi: 10.1161/CIR.0b013e31827ee100 [DOI] [PubMed] [Google Scholar]
  • 9.Ortega FB, Ruiz JR, Hurtig-Wennlöf A, et al. Cardiovascular fitness modifies the associations between physical activity and abdominal adiposity in children and adolescents: the european youth heart study. Br J Sports Med. 2010;44(4):256–262. [DOI] [PubMed] [Google Scholar]
  • 10.McGavock JM, Torrance BD, McGuire KA, Wozny PD, Lewanczuk RZ. Cardiorespiratory fitness and the risk of overweight in youth: the healthy hearts longitudinal study of cardiometabolic health. Obesity. 2009;17(9):1802–1807. doi: 10.1038/oby.2009.59 [DOI] [PubMed] [Google Scholar]
  • 11.Ortega FB, Labayen I, Ruiz JR, et al. Improvements in fitness reduce the risk of becoming overweight across puberty. Med Sci Sports Exerc. 2011; 43(10):1891–1897. doi: 10.1249/MSS.0b013e3182190d71 [DOI] [PubMed] [Google Scholar]
  • 12.Lee SJ, Arslanian SA. Cardiorespiratory fitness and abdominal adiposity in youth. Eur J Clin Nutr. 2007;61(4): 561–565. doi: 10.1038/sj.ejcn.1602541 [DOI] [PubMed] [Google Scholar]
  • 13.Barry VW, Baruth M, Beets MW, Durstine JL, Liu J, Blair SN . Fitness vs. fatness on all-cause mortality: a meta-analysis. Prog Cardiovasc Dis. 2014;56(4):382–390. doi: 10.1016/j.pcad.2013.09.002 [DOI] [PubMed] [Google Scholar]
  • 14.Slawta JN, DeNeui D. Be a fit kid: nutrition and physical activity for the fourth grade. Health Promot Pract. 2010;11(4):522–529. doi: 10.1177/1524839908328992 [DOI] [PubMed] [Google Scholar]
  • 15.Ross R, Blair SN, Arena R, et al. On behalf of theAmerican Heart Association Physical Activity Committee of the Council on Lifestyle and Cardiometabolic Health; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Council on Cardiovascular and Stroke Nursing; Council on Functional Genomics and Translational Biology; and Stroke Council. Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign—A scientific statement from the American heart association. Circulation. 2016;134(24):e653–e699. doi: 10.1161/CIR.0000000000000461 [DOI] [PubMed] [Google Scholar]
  • 16.Ross R, Arena R, Myers J, Kokkinos P, Kaminsky LA. Update to the 2016 American heart association cardiorespiratory fitness statement. Prog Cardiovasc Dis. 2024;83:10–15. doi: 10.1016/j.pcad.2024.02.003 [DOI] [PubMed] [Google Scholar]
  • 17.Adams MA, Hovell MF, Irvin V, Sallis JF, Coleman KJ, Liles S. Promoting stair use by modeling: an experimental application of the behavioral ecological model. Am J Health Promot. 2006;21(2):101–109. doi: 10.4278/0890-1171-21.2.101 [DOI] [PubMed] [Google Scholar]
  • 18.Krohn MD, Skinner WF, Massey JL, Akers RL. Social learning theory and adolescent cigarette smoking: a longitudinal study. Soc Probl. 1985; 32(5):455–473. doi: 10.1525/sp.1985.32.5.03a00050 [DOI] [Google Scholar]
  • 19.Wong SE. Operant learning theory. In: Thyer BA, Sowers KM, Dulmus CN, eds. Comprehensive Handbook of Social Work and Social Welfare. Vol 2. Human Behavior in the Social Environment. John Wiley & Sons, Inc.; 2008:69–99. doi: 10.1002/9780470373705.chsw002006 [DOI] [Google Scholar]
  • 20.Kinlin LM, Oreskovich SM, Dubrowski R, et al. Managing obesity in young children: a multiple methods study assessing feasibility, acceptability, and implementation of a multicomponent, family-based intervention. Child Obes. 2022;18:409–421. doi: 10.1089/chi.2021.0221 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Plowman SAMMD. Fitnessgram/Activitygram Reference Guide. 4th ed. The Cooper Institute; 2013. [Google Scholar]
  • 22.Anthropometry Procedures Manual. National Health and Nutrition Examination Surveys (NHANES). Hyattsville, MD: Centers for Disease Control and Prevention; 2017. [Google Scholar]
  • 23.Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005;37(11 Suppl):S523–S530. doi: 10.1249/01.mss.0000185658.28284.ba [DOI] [PubMed] [Google Scholar]
  • 24.Ward DS, Evenson KR, Vaughn A, Rodgers AB, Troiano RP. Accelerometer use in physical activity: best practices and research recommendations. Med Sci Sports Exerc. 2005;37(11 Suppl):S582–S588. doi: 10.1249/01.mss.0000185292.71933.91 [DOI] [PubMed] [Google Scholar]
  • 25.Rockett HR, Breitenbach M, Frazier AL, et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med. 1997;26(6):808–816. doi: 10.1006/pmed.1997.0200 [DOI] [PubMed] [Google Scholar]
  • 26.Cui Z, Seburg EM, Sherwood NE, Faith MS, Ward DS. Recruitment and retention in obesity prevention and treatment trials targeting minority or low-income children: a review of the clinical trials registration database. Trials. 2015;16:564. doi: 10.1186/s13063-015-1089-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Eldridge SM, Chan CL, Campbell MJ, et al. l. CONSORT 2010 statement: extension to randomized pilot and feasibility trials. Br Med J. 2016;355: i5239. doi: 10.1136/bmj.i5239 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Dawson-McClure S, Calzada EJ, Brotman LM. Engaging parents in preventive interventions for young children: working with cultural diversity within low-income, urban neighborhoods. Prev Sci. 2017;18(6): 660–670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Carrel AL, Clark RR, Peterson SE, Nemeth BA, Sullivan J, Allen DB. Improvement of fitness, body composition, and insulin sensitivity in overweight children in a school-based exercise program: a randomized, controlled study. Arch Pediatr Adolesc Med. 2005;159(10):963–968. [DOI] [PubMed] [Google Scholar]
  • 30.Barragan M, Luna V, Hammons AJ, et al. Reducing obesogenic eating behaviors in Hispanic children through a family-based, culturally-tailored RCT: Abriendo caminos. Int J Environ Res Publ Health. 2022;19(4): 1917. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans, 2nd Edition. Washington (DC): Office of Disease Prevention and Health Promotion; 2018. Available from: https://www.health.gov/sites/default/files/2019-09/Physical_Activity_Guidelines_2nd_edition.pdf [Google Scholar]
  • 32.Morrow JR, Freedson PS. Relationship between habitual physical activity and aerobic fitness in adolescents. Pediatr Exerc Sci. 1994;6(4):315–329. [Google Scholar]

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