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Jason A. Mendoza, Jessica McLeod, Tzu-An Chen, Theresa A. Nicklas and Tom Baranowski

Background:

Childhood obesity is at record high levels in the US and disproportionately affects Latino children; however, studies examining Latino preschool children’s obesity-related risk factors are sparse. This study determined correlates of Latino preschoolers’ (ages 3–5 years) adiposity to inform future obesity interventions and policies.

Methods:

Latino preschoolers (n = 96) from 4 Head Start centers in Houston, Texas were recruited. Parents reported acculturation and neighborhood safety. Children’s and parents’ height and weight were measured. Children’s television (TV) viewing was measured by TV diaries and physical activity by accelerometers. Linear regression was used with body mass index (BMI) z-score as the dependent variable and covariates sequentially added and retained in 4 blocks: 1) child age, gender, parent education, and BMI; 2) neighborhood safety and parent and child acculturation; 3) TV viewing; and 4) moderate-to-vigorous physical activity (MVPA).

Results:

In the final model (n = 96), only neighborhood disorder (β = 0.30, P = .005) and MVPA (β = –0.21, P = .049) were significantly associated with BMI z-score.

Conclusions:

Among Latino preschoolers, higher neighborhood disorder and lower MVPA were associated with greater children’s BMI z-scores.

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Jessica G. Markbreiter, Bronson K. Sagon, Tamara C. Valovich McLeod and Cailee E. Welch

Clinical Scenario:

An individual’s movement patterns while landing from a jump can predispose him or her to lower-extremity injury, if performed improperly. The Landing Error Scoring System (LESS) is a clinical tool to assess jump-landing biomechanics as an individual jumps forward from a box. Improper movement patterns, which could predispose an individual to lower-extremity injuries, are scored as errors. However, because of the subjective nature of scoring errors during the task, the consistency and reliability of scoring the task are important. Since the LESS is a newer assessment tool, it is important to understand its reliability.

Focused Clinical Question:

Are clinicians reliable at scoring the LESS to assess jump-landing biomechanics of physically active individuals?

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Norma Olvera, Kendall E. McCarley, Patrick Leung, Jessica McLeod and Augusto X. Rodriguez

The purpose of this study was to assess physical activity preferences (PAP) in preadolescent children. 191 Latino and White children (M = 11.9, SD = ±0.7) participated. Demographic, anthropometric, and PAP measures were employed. Both Latino and White children reported water play, basketball, and bicycling as their most preferred activities while indoor chores were least preferred. Compared with Latino, White children reported a higher preference for baseball/softball. Exploratory factor analysis of PAP measure indicated a three-factor solution: free play, sports, and exercise. Multiple linear regression models revealed that PAP varied as a function of ethnicity, gender, age, and body mass index.

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Alison R. Snyder, Jessica C. Martinez, R. Curtis Bay, John T. Parsons, Eric L. Sauers and Tamara C. Valovich McLeod

Context:

Patient-oriented outcome measures such as the Medical Outcomes Short Form (SF-36) and the Pediatric Outcomes Data Collection Instrument (PODCI) are important tools for determining the impact of events like sport-related injury on health-related quality of life (HRQoL). Unfortunately, there are no published studies using these instruments that compare adolescent athletes with their nonathlete peers, making interpretations of these measures in this population difficult.

Objective:

To compare HRQoL in adolescent athletes and nonathletes using 2 common instruments.

Design:

Cross-sectional.

Setting:

7 high schools.

Participants:

219 athletes and 106 nonathletes.

Intervention:

None.

Main Outcome Measures:

The SF-36 and the PODCI were completed in a counterbalanced manner during 1 session. Dependent variables included the 8 subscale and 2 composite scores of the SF-36 and the 5 subscale scores and 1 global score of the PODCI.

Results:

On the SF-36, athletes reported higher scores on the physical function, general health, social functioning, and mental health subscales and the mental composite score and lower scores on the bodily pain subscale than nonathletes. On the PODCI, athletes reported higher scores on the sport and physical function and happiness subscales and lower scores on the pain/comfort subscale.

Conclusions:

Athletes reported higher scores on a number of SF-36 and PODCI subscales related to mental, emotional, and physical well-being than nonathletes. Our findings suggest that athletic involvement may be a benefit to the overall health status of adolescents and imply that athletes may be a distinct adolescent group requiring their own normative values when using the SF-36 and PODCI.