The purpose of this study was to examine the relationships among body mass index (BMI), body image perception, physical activity habits, and exercise stage of change in college-aged females. Volunteers (N = 134) completed a survey of demographics, Stage of Exercise Scale (SOES; Cardinal, 1995a; Cardinal, 1995b), Physical Activity History questionnaire (PAH; Jacobs, Hahn, Haskell, Pirie, & Sidney, 1989), and Body Shape Questionnaire (BSQ; Cooper, Taylor, Cooper, & Fairburn, 1987). Participants were categorized into five exercise stages of change: precontemplation, contemplation, preparation, action, and maintenance. Relationships between the variables were analyzed with Pearson r correlations. Kruskal-Wallis independence tests were also used for analyses. Approximately 60% of the participants reported current physical inactivity or irregular exercise. BMI and body image score were significantly linearly related, with higher body mass indicating more negative body image (r = 30, p <.017). Significant differences existed between exercise stages for physical activity score, X2 (3, N = 134) = 19.98, p <.05. Based upon follow-up tests participants in the maintenance stage had significantly higher physical activity scores than all other stages. No significant differences were found for BMI or body image between exercise stages. Regular exercisers had the highest frequency of disordered eating and weight-preoccupied attitudes and behaviors. The majority of these women were not currently regularly physically active, professed dissatisfaction with their current level of activity, and expressed a fear of being fat. Further study directed at specific factors related to body image and exercise behaviors, as well as the impact of stage-specific interventions are suggested.
Molly Burger and Dennis Dolny
Geoff P. Lovell, John K. Parker, Abbe Brady, Stewart T. Cotterill and Glyn Howatson
Research has reported that initial evaluations of consultants’ competency are affected by dress and build. This investigation examined how athletes’ perceptions of sport psychology consultants (SPCs) are affected by SPCs’ physical characteristics of BMI and dress, and whether these perceptions are moderated by the athletes’ sex or standard of competition. Two hundred and thirty three competitive sports volunteers classified by sex and competitive standard viewed computer generated images of the same female SPC in sports and formal attire manipulated to represent a range of body mass indexes. Participants were asked to rank the SPCs in order of their preference to work with them, and to rate their perceived effectiveness of each of the SPCs. Results demonstrated that SPCs’ physical characteristics do influence athletes’ preference to work with them and perceptions of their effectiveness. Furthermore, athlete’s competitive standard does significantly moderate initial evaluation of SPCs based on physical characteristics.
David Feeny, Rochelle Garner, Julie Bernier, Amanda Thompson, Bentson H. McFarland, Nathalie Huguet, Mark S. Kaplan, Nancy A. Ross and Chris M. Blanchard
The objective of this study was to assess the associations among body mass index (BMI), leisure time physical activity (LTPA) and health-related quality of life (HRQL) trajectories among adults.
Self-reported data were drawn from the Canadian National Population Health Survey, with respondents being interviewed every 2 years between 1996–97 and 2006–07. Using growth curve modeling, HRQL trajectories for individuals aged 18 and over were associated with measures of BMI and LTPA. Growth models were constructed separately for males and females.
Findings suggested that, for males, BMI categories had little impact on baseline HRQL, and no impact on the rate of change in HRQL. Among women, higher BMI categories were associated with significantly lower baseline HRQL. However, BMI had no impact on the rate of change of HRQL. Conversely, for both men and women and regardless of BMI category, LTPA had significant impacts on baseline HRQL, as well as the rate of change in HRQL. Individuals who were inactive or sedentary had much steeper declines in HRQL as they aged, as compared with individuals who were active in their leisure time.
The results underscore the importance of LTPA in shaping trajectories of HRQL.
Rebecca A. Schlaff, Claudia Holzman, Lanay M. Mudd, Karin A. Pfeiffer and James M. Pivarnik
Little is known about how leisure-time physical activity (LTPA) influences gestational weight gain (GWG) among body mass index (BMI) categories. The purpose of this study was to examine the relationship between pregnancy LTPA and the proportion of normal, overweight, and obese women who meet GWG recommendations.
Participants included 449 subcohort women from the Pregnancy Outcomes and Community Health (POUCH) study. LTPA was collapsed into 3 categories [(None, < 7.5 kcal/kg/wk (low), ≥ 7.5 kcal/kg/wk (recommended)]. GWG was categorized according to IOM recommendations (low, recommended, or excess). Chi-square and logistic regression analyses were used to evaluate relationships among LTPA, BMI, and GWG.
Overweight women were more likely to have high GWG vs. normal weight women (OR = 2.3, 95% CI 1.3–4.0). Obese women were more likely to experience low GWG (OR = 7.3, 95% CI 3.6–15.1; vs. normal and overweight women) or excess GWG (OR = 3.5, 95% CI 1.9–6.5; vs. normal weight women). LTPA did not vary by prepregnancy BMI category (P = .55) and was not related to GWG in any prepregnancy BMI category (P = .78).
Regardless of prepregnancy BMI, LTPA did not affect a woman’s GWG according to IOM recommendations. Results may be due to LTPA not differing among BMI categories.
Michael Duncan, Elizabeth Bryant, Mike Price, Samuel Oxford, Emma Eyre and Mathew Hill
This study examined postural sway in children in eyes open (EO) and eyes closed (EC) conditions, controlling for body mass index (BMI) and physical activity (PA). Sixty two children (aged 8–11years) underwent sway assessment using computerized posturography from which 95% ellipse sway area, anterior/posterior (AP) sway, medial/lateral (ML) sway displacement and sway velocity were assessed. Six trials were performed alternatively in EO and EC. BMI (kg/m2) was determined from height and mass. PA was determined using sealed pedometry. AP amplitude (p = .038), ML amplitude (p = .001), 95% ellipse (p = .0001), and sway velocity (p = .012) were higher in EC compared with EO conditions. BMI and PA were not significant as covariates. None of the sway variables were significantly related to PA. However, sway velocity during EO (p = .0001) and EC (p = .0001) was significantly related to BMI. These results indicate that sway is poorer when vision is removed, that BMI influences sway velocity, but that pedometer-assessed PA was not associated with postural sway.
Jeffrey Liew, Ping Xiang, Audrea Y. Johnson and Oi-Man Kwok
Schools often include running in their physical education and health curriculum to increase physical activity and reduce childhood overweight. But having students run around may not be enough to sustain physical activity habits if motivational factors are not well understood. This study examined effortful persistence as a predictor of running.
Participants were 246 5th graders, and data on their demographic information, body mass index (BMI), effortful persistence, and time to complete a 1-mile run were collected across 4 years.
Between 5th to 8th grades, effortful persistence predicted time to complete a 1-mile run even when BMI was taken into account at every grade except for 7th grade. Rank-order stability was found in major variables across-time, but no across-time prediction was found for effortful persistence on a 1-mile run.
Lack of longitudinal predictions bodes well for interventions aimed at increasing physical activity, because children or youth with high BMIs or low effortful persistence are not destined for future underachievement on physically challenging activities. Given the stability of variables, interventions that target fostering self-regulatory efficacy or effortful persistence may be particularly important for getting children on trajectories toward healthy and sustained levels of physical activity.
Ann M. Swartz, Scott J. Strath, Sarah J. Parker and Nora E. Miller
The purpose of this study was to investigate the combined impact of obesity and physical activity (PA) on the health of older adults. Pedometer-determined steps/d, body-mass index (BMI), resting blood pressure, and fasting glucose (FG) were assessed in 137 older adults (69.0 ± 8.9 yr). The active group (>4,227 steps/d) had lower systolic blood pressure (SBP; p = .001), diastolic blood pressure (DBP; p = .028), and FG (p < .001) than the inactive group (≤4,227 steps/d). The normal-BMI group (18.5-24.9 kg/m2) had lower SBP (p < .001) and DBP (p = .01) than the obese group (≤30 kg/m2). There were no differences in SBP (p = .963) or DBP (p = 1.0) between active obese and inactive normal-BMI groups. The active obese group, however, had a more favorable FG than the inactive normal-BMI group (χ2 = 18.9, df = 3, p = .001). Efforts to increase PA of older adults should receive the same priority as reducing obesity to improve BP and FG levels.
Joseph J. Knapik, Bruce H. Jones, James A. Vogel, Louis E. Banderet, Michael S. Bahrke and John S. O’Connor
This study describes associations between age, body mass index (BMI), and performance on three common measures of physical fitness: maximum pushups in 2 min, maximum sit-ups in 2 min, and 3.2-km run for time. Subjects were 5,346 healthy male soldiers, ages 18 to 53 years. Before age 30, there were few age-related differences between the youngest and the older age groups on any test; after age 30, performance declined as age increased, averaging 16%, 17%, and 7% per decade for push-ups, sit-ups, and the run, respectively. Regression analysis showed that age accounted for 10%, 15% and 9% of the variance in push-up, sit-up, and run performances, respectively. When BMI was added to the regression model it increased the variance accounted for in the run to 16% (age plus BMI) but did not explain variance in push-ups or sit-ups. There are systematic age-related declines in the performance of push-ups, sit-ups, and 3.2-km running, with age alone accounting for only 9% to 15% of the total performance variance in this sample of healthy men.
Martin D. Hoffman, Linjun Chen and Eswar Krishnan
Little is known about the sociodemographics and lifestyle behaviors of ultramarathon runners, and the effects of these characteristics on body weight and body mass index (BMI).
We cross-sectionally analyzed baseline data of 1212 ultramarathoners on sociodemographics, lifestyle behaviors and BMI from the initial 12-month enrollment period in a longitudinal observational study.
The ultramarathoners were mostly middle-aged men who were more educated, more likely to be in a stable relationship, and more likely to use over-the-counter vitamins/supplements than the general population. They appear to gain less body weight with advancing age than the general population. Factors with the greatest effect on current BMI were BMI at 25 years of age and sex, which explained 48% and 3% of the variance. Negligible, but statistically significant direct relationships, with BMI were observed for age, work hours per week, television watching hours per week, and composite fat consumption frequency score. Negligible, but statistically significant inverse relationships, with BMI were observed for running distance during the prior year, and composite fruit and vegetable consumption frequency score.
While lifestyle decisions were found to impact BMI within this group of ultramarathoners, BMI at age 25 was the strongest predictor of current BMI.
Odessa Addison, Monica C. Serra, Leslie Katzel, Jamie Giffuni, Cathy C. Lee, Steven Castle, Willy M. Valencia, Teresa Kopp, Heather Cammarata, Michelle McDonald, Kris A. Oursler, Chani Jain, Janet Prvu Bettger, Megan Pearson, Kenneth M. Manning, Orna Intrator, Peter Veazie, Richard Sloane, Jiejin Li and Miriam C. Morey
a standardized assessment of mobility function testing by a trained exercise staff at each site to establish a baseline mobility status. The body mass index (BMI) was determined from a baseline assessment of height and weight. The mobility function assessment included the (a) time to complete a 10-m