body mass index (BMI) of ≥30 kg/m 2 , and individuals with a BMI of 25 to <30 kg/m 2 are considered overweight. The BMI is used instead of body weight in isolation, as it adjusts for the effect of height on body weight ( Nuttall, 2015 ). The relationship between a higher BMI and falls in older adults
Sheng H. Kioh, Sumaiyah Mat, Shahrul B. Kamaruzzaman, Fatimah Ibrahim, Mas S. Mokhtar, Noran N. Hairi, Robert G. Cumming, Phyo K. Myint and Maw P. Tan
Nathaniel S. Nye, Drew S. Kafer, Cara Olsen, David H. Carnahan and Paul F. Crawford
, 18 This is significant given the increasing rates of obesity; as of 2012, 34.9% of Americans aged 20 years and older were considered obese 19 [defined as body mass index (BMI) ≥ 30 kg/m 2 ], placing them at additional risk for lower extremity injury. The use of BMI as a measure of body habitus has
Michael J. Davies, Gail P. Dalsky and Paul M. Vanderburgh
This study employed allometry to scale maximal oxygen uptake (V̇O2 max) by body mass (BM) and lean body mass (LBM) in healthy older men. Ratio standards (ml · kg−1 · min−1) derived by dividing absolute V̇O2 max (L · min−1) by BM or LBM often fail to control for the body size variable. The subjects were 73 older men (mean ± SD: age = 69.7 ± 4.3 yrs, BM = 80.2 ± 9.6 kg, height = 174.1 ± 6.9 cm). V̇O2 max was assessed on a treadmill with the modified Balke protocol (V̇O2 max = 2.2 ± 0.4 L · min−1). Body fat (27.7 ± 6.4%) was assessed with dual energy x-ray absorptiometry. Allometry applied to BM and V̇O2 max determined the BM exponent to be 0.43, suggesting that heavier older men are being penalized when ratio standards are used. Allometric scaling applied to LBM revealed the LBM exponent to be 1.05 (not different from the ratio standard exponent of 1.0). These data suggest that the use of ratio standards to evaluate aerobic fitness in older men penalized fatter older men but not those with higher LBM.
Catherine R. Marinac, Mirja Quante, Sara Mariani, Jia Weng, Susan Redline, Elizabeth M. Cespedes Feliciano, J. Aaron Hipp, Daniel Wang, Emily R. Kaplan, Peter James and Jonathan A. Mitchell
within an individual. We, therefore, tested if the timing of meals, light exposure, physical activity, and sleep were associated with body mass index (BMI) in a sample of healthy adults who recorded the timing of behaviors over multiple days using a novel smartphone application and actigraphy. We first
Simone A. Tomaz, Alessandra Prioreschi, Estelle D. Watson, Joanne A. McVeigh, Dale E. Rae, Rachel A. Jones and Catherine E. Draper
, and research on sleep behavior in this age group is lacking from low- and middle-income countries (LMICs), such as South Africa. Furthermore, there has been limited research investigating the relationships between PA, SB, GMS, sleep duration, and body mass index (BMI) in preschool children from LMICs
Bo Shen and Chiren Xu
Researchers have studied exercise determinants primarily from cognitive and social psychology perspectives, which typically give minimal attention to the body as a physical and biological entity. With the belief that tapping into multidimensional variables would potentially help us better understand motivation in exercise, we designed this study to examine the influences of self-efficacy, body mass, and cardiorespiratory fitness level on Chinese college students’ leisure-time exercise motives.
208 college students completed measures of self-efficacy and exercise motives during regular physical education classes. Their body mass and cardiorespiratory fitness level data were derived from the latest annual physical training test. Multiple regression analyses were conducted to investigate the effects of self-efficacy, body mass, and cardiorespiratory fitness on exercise motives.
Cardiorespiratory fitness level and self-efficacy in exercise significantly contributed to both psychological and interpersonal motives. Body mass was the only significant predictor for body-related motives. However, analyses of health and fitness motives did not result in any significant predictors.
Physical and psychological variables have both independent and specialized functions on exercise motives. Future motivational studies in exercise should pay greater attention to ecological approaches that account for physical, psychological, and social factors.
Meenakshi Maria Fernandes and Roland Sturm
Physical activity at school can support obesity prevention among youth. This paper assesses the role of existing school physical activity programs for a national cohort from first grade to fifth grade.
We analyzed a cohort from the Early Childhood Longitudinal Survey—Kindergarten Cohort which included 8246 children in 970 schools across the country. Growth curve models estimate the effect of physical education (PE) and recess on individual child body mass trajectories controlling for child and school characteristics. Hierarchical models allow for unobserved school and child effects.
Among first graders, 7.0% met the National Association of Sport and Physical Education (NASPE) recommended time for PE and 70.7% met the recommended time for recess in the previous week. Boys experienced a greater increase in body mass than girls. Meeting the NASPE recommended time for recess was associated with a 0.74 unit decrease in BMI (body mass index) percentile for children overall. Meeting the NASPE recommendation for physical education was associated with 1.56 unit decrease in BMI percentile among boys but not girls.
We find evidence that meeting the national recommendations for PE and recess is effective in mitigating body mass increase among children.
Krista Schroeder, Martha Y. Kubik, Jiwoo Lee, John R. Sirard and Jayne A. Fulkerson
may inform interventions to minimize the decline. 5 – 10 Understanding these associations in preadolescents at risk for poor health outcomes, such as preadolescents with elevated body mass index (BMI), is especially important given the harmful health impact of physical inactivity and prolonged
Judith Jiménez, Maria Morera, Walter Salazar and Carl Gabbard
Motor skill competence has been associated with physical activity level, fitness, and other relevant health-related characteristics. Recent research has focused on understanding these relationships in children and adolescents, but little is known about subsequent years. The aim of this study was to examine the relationship between fundamental motor skill (FMS) ability and body mass index (BMI) in young adults.
Participants, 40 men and 40 women (M age = 19.25 yr, SD = 2.48), were assessed for BMI and motor competence with 10 fundamental motor skills (FMSs) using the Test for Fundamental Motor Skills in Adults (TFMSA).
BMI was negatively associated with total motor ability (r = –.257; p = .02) and object control skills (r = –.251; p = .02); the relationship with locomotor skills was marginally insignificant (r = –.204; p = .07). In regard to individual skills, a significant negative association was found for running, jumping, striking, and kicking (ps < .05). Multiple regression analysis indicated that BMI and gender predicted 42% of the variance in total FMS score; gender was the only significant predictor.
Overall, these preliminary findings suggest that young adults with higher FMS ability are more likely to have lower BMI scores.
Alina Cohen, Joseph Baker and Chris I. Ardern
Obesity is associated with impairments in health-related quality of life (HRQL), whereas physical activity (PA) is a promoter of HRQL.
The aim of this study was to investigate the interaction between BMI and PA with HRQL in younger and older Canadian adults.
Data from the 2012 annual component of the Canadian Community Health Survey (N = 48,041; = 30 years) were used to capture self-reported body mass index (BMI-kg/m2), PA (kcal/kg/day, KKD), and HRQL. Interactions between PA and age on the BMI and HRQL relationship were assessed using general linear models and logistic regression.
Those younger (younger: μ = 0.79 ± 0.02; older: μ = 0.70 ± 0.02) and more active (active: μ = 0.82 ± 0.02; moderately active: μ = 0.77 ± 0.03; inactive: μ = 0.73 ± 0.01) reported higher HRQL. Older inactive underweight, normal weight, and overweight adults have lower odds of high HRQL.
PA was associated with higher HRQL in younger adults. In older adults, BMI and PA influenced HRQL.