ABSTRACT
The purpose of the current study was to determine the influence of parenting style on body mass index (BMI) percentile, physical activity (PA), and sedentary time (ST) in children. Accelerometers were used to assess PA and ST in 152 fifth-grade children. Parenting style was assessed by the child participants' responses to modified questions from the Parenting Style Inventory II and dichotomized as authoritative or non-authoritative. Multiple linear regression analyses were utilized to identify significant predictors of outcomes of interest. Parenting style did not predict ST or any intensity of PA; however, BMI percentile and gender were significant predictors of moderate-intensity PA, vigorous-intensity PA, and moderate-to-vigorous intensity PA (P < .01). BMI percentile was predicted to be lower in females with authoritative mothers (P < .01). While authoritative and non-authoritative parenting style did not predict objectively measured PA or ST in early adolescents, authoritative parenting style did predict BMI percentile in female participants.
ABSTRACT
BACKGROUND: The Functional Movement Screen (FMS™) is a popular test used by sports medicine professionals to identify dysfunctional movement patterns by analyzing mobility and stability during prescribed movements. Although the FMS™ has been a popular topic of research in recent years, normative data and asymmetries in college-aged students have not been established through research. PURPOSE: The objective was to determine normative FMS™ scores, report frequency counts for FMS™ asymmetries, and determine if the number of sports seasons and number of different sports an individual participated in during high school varied between university students that showed FMS™ identified asymmetries. STUDY DESIGN: Cross-sectional Study. METHODS: One hundred university students completed the FMS™ and an associated survey to determine which sport(s) and for how many seasons they participated in each sport(s) during high school. Total FMS™ scores were assessed as well as identifying the presence of an asymmetry during a FMS™ screen. An asymmetry within the FMS™ was defined as achieving an unequal score on any of the screens that assessed right versus left movements of the body. DATA ANALYSIS: Data analysis included descriptive statistics, Pearson correlation was utilized to investigate the relationship between number of sports played and number of sport seasons. Shapiro Wilk test for normality, and Mann Whitney U test was employed to investigate group differences in number of sports played. All analyses were conducted using SPSS software. RESULTS: Statistically significant correlations (r = .286, r2 = .08, p < 0.01) were found for both number of sport seasons and number of sports with FMS™ total score. In addition, participants without FMS™-detected asymmetries played significantly more seasons and more sports than their peers that presented asymmetries (U = 946.5, z = -1.98, p = 0.047). Finish with the actual p-value in parenthesis. CONCLUSION: Participating in multiple sports and multiple sport seasons during high school was associated with higher FMS™ total scores. Results suggest that participating in multiple sports and multiple sport seasons was associated with fewer asymmetries, which may decrease subsequent injury risk. LEVEL OF EVIDENCE: 3b.
ABSTRACT
This study aimed to develop an equation to reduce variability of VO2peak prediction from a step test and compare VO2peak prediction from the new equation to the Queen's College Step Test (QCST). The development group (n=86; 21.7±2 years) was utilized to develop the SDState step test equation to predict relative VO2peak. The cross-validation group (n=99; 21.6±2 years) was used to determine the validity of the SDState step test VO2peak prediction equation. A regression analysis was used to identify the best model to predict VO2peak. Analysis of variance (ANOVA) was further used to determine differences among predicted and measured VO2peak values. Forward stepwise multiple regression identified age, sex, abdominal circumference, and active heart rate at the 3-min mark of the step test to be significant predictors of VO2peak (mL·kg-1·min-1). No differences among measured VO2peak (47.3±7.1 mL·kg-1·min-1) and predicted VO2peak (QCST, 46.9±9.3 mL·kg-1·min-1; SDState 48.3±5.7 mL·kg-1·min-1) were found. Pearson correlations, ICC, SEE, TEE, Bland-Altman plots, and Mountain plots indicate the SDState step test equation provides less variation in the prediction of VO2peak compared to the QCST. The SDState step test equation is effective for predicting VO2peak from the YMCA step test in young, healthy adults.
