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SIMULTANEOUS INVESTIGATION OF ACTIVITY BEHAVIORS, DIETARY PATTERNS, AND PHYSICAL FITNESS WITH ADIPOSITY IN PREADOLESCENT CHILDREN

Abstract

Juliette Levet-Bourtayre1, Lauren C. Bates1, Nicholas Castro2, Gabriel Zieff1, Patricia Pagan Lassalle1, Lee Stoner, FACSM1. 1University of North Carolina at Chapel Hill, Chapel Hill, NC. 2University of North Carolina at Wilmington, Wilmington, NC.

BACKGROUND: The increasing prevalence of childhood obesity is a major public health concern due to its association with an increased risk of developing early-onset cardiometabolic diseases. Poor activity behaviors, dietary patterns, and physical fitness have been shown to independently contribute to adiposity risk, however these multifactorial behaviors interact with one another potentially increasing risk. Therefore, the purpose of this cross-sectional study was to simultaneously investigate the associations among dietary patterns, activity behaviors, and physical fitness with adiposity in preadolescent children. METHODS: A sample of 392 preadolescent children (age: 9.5 ± 1.1 years) were recruited from schools in three relatively large cities in New Zealand. Body fat percentage (BF%) and fat mass (kg) were measured via bioelectrical impedance analysis. Height, weight, waist circumference and hip circumference (waist to hip ratio, WHR) were measured to calculate the anthropometric indices. Fat mass index (FMI) was calculated by dividing fat mass (kg) by height squared (m2) and body mass index (BMI) was calculated by diving body mass (kg) by height squared (m2). Cardiorespiratory fitness (CRF, VO2 max) was estimated via the 20-Meter Shuffle Test and muscular strength was assessed using a handgrip dynamometer. Physical activity (PA) and sedentary behavior were measured through the Youth Physical Activity Questionnaire. The PEDALS-Food Frequency Questionnaire (FFQ) was used to determine dietary patterns. Sleep questions were used to record sleep duration, social jetlag and sleep disturbance. RESULTS: Multivariable regression, adjusted for sex, ethnicity, age, and school decile revealed that (a) V̇O₂max, fruit and vegetables pattern and breakfast food pattern were associated with body fat percentage (β = -11.34, .44 and -.58, respectively; all p < 0.05); and (b) V̇O₂max was the only factor associated with FMI (β = -2.45; p < .001), BMI (β = -3.54; p < .001) and WHR (β = .03; p ≤ 0.01). CONCLUSIONS: CRF correlated most strongly with adiposity. Therefore, participating in PA to increase CRF should be at the forefront of pediatric health guidelines to address the childhood obesity epidemic.

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