Peak Oxygen Uptake and Physical Activity in 11- to 16-Year-Olds

Armstrong, Neil; Balding, John; Gentle, Peter; Williams, Joanne; Kirby, Brian J.

doi:10.1123/pes.2.4.349

Cited by 68 publications

(24 citation statements)

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“…The latter disciplines do state that most active play occurs outdoors in both genders (e.g., Sallis et al, 1990;Baranowski et al, 1993) and that # children B3 years or older (and adolescents) are more active than~children and adolescents of the same age (e.g., Armstrong et al, 1990Armstrong et al, , 1991Sallis et al, 1996;Beunen and Thomis, 1999;Bradley et al, 2000). In general, they also find ethnic and socioeconomic ''effects'' in active physical activity (e.g., Sallis et al, 1996), similar to our attributes classes.…”

supporting

confidence: 77%

Developing meaningful cohorts for human exposure models

Graham

McCurdy

2004

J Expo Sci Environ Epidemiol

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This paper summarizes numerous statistical analyses focused on the US Environmental Protection Agency's Consolidated Human Activity Database (CHAD), used by many exposure modelers as the basis for data on what people do and where they spend their time. In doing so, modelers tend to divide the total population being analyzed into ''cohorts'', to reduce extraneous interindividual variability by focusing on people with common characteristics. Age and gender are typically used as the primary cohort-defining attributes, but more complex exposure models also use weather, day-of-the-week, and employment attributes for this purpose. We analyzed all of these attributes and others to determine if statistically significant differences exist among them to warrant their being used to define distinct cohort groups. We focused our attention mostly on the relationship between cohort attributes and the time spent outdoors, indoors, and in motor vehicles. Our results indicate that besides age and gender, other important attributes for defining cohorts are the physical activity level of individuals, weather factors such as daily maximum temperature in combination with months of the year, and combined weekday/weekend with employment status. Less important are precipitation and ethnic data. While statistically significant, the collective set of attributes does not explain a large amount of variance in outdoor, indoor, or in-vehicle locational decisions. Based on other research, parameters such as lifestyle and life stages that are absent from CHAD might have reduced the amount of unexplained variance. At this time, we recommend that exposure modelers use age and gender as ''first-order'' attributes to define cohorts followed by physical activity level, daily maximum temperature or other suitable weather parameters, and day type possibly beyond a simple weekday/weekend classification.

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supporting

confidence: 77%

Developing meaningful cohorts for human exposure models

Graham

McCurdy

2004

J Expo Sci Environ Epidemiol

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“…In the present study physical activity was recorded for four days. Armstrong et al (1990) compared physical activity of children aged 11 to 16 years on week and weekend days and found no significant differences, in the present study it was logistically easier to visit children's homes during the weekends.…”

Section: Methodsmentioning

confidence: 92%

“…The system can be worn during all normal activities without altering usual physical activity patterns. Treiber et al (1989) have shown this method to have good validity in children aged 5 to 10 years and it has been widely used in physical activity surveys of young people (Armstrong et al, 1990;Atkins, 1998).…”

Section: Methodsmentioning

confidence: 99%

Physical activity and psychological well-being in children with Type 1 diabetes

Edmunds

Roche

Stratton

et al. 2007

Psychology, Health & Medicine

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Physical activity and psychological well being contribute to positive lifestyle and well being in youngsters who have Type 1 diabetes. The aims of this study were to objectively assess the physical activity levels of children with Type 1 diabetes, and investigate associations between physical activity levels, psychological well-being and HbA 1c . Thirty-six children, mean age 12.8 years, participated in the investigation. Physical activity was assessed using heart rate monitoring over four days. Children further completed the Diabetes Quality of Life for Youths Questionnaire, the Physical Self-Perception Profile for Children, and the Self-Efficacy for Diabetes Scale. Routine outpatient HbA 1c measurements were recorded. There were no significant associations between psychological well-being and physical activity, or HbA 1c and physical activity, thus suggesting physical activity does not directly relate to psychological wellbeing in children with Type 1 diabetes. It may be that the effect of physical activity differs from that in children without Type 1 diabetes because of the place of physical activity within diabetes management and the need to balance this with insulin dosage and dietary intake to maintain blood glucose levels.

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“…5,6 This focus is timely, as these fatness trends are accompanied by evidence of low levels of activity, particularly in girls. 7,8 Furthermore, the increasing prevalence of inactive leisure pursuits, such as watching television and playing computer games, is of concern as evidence is emerging, linking these activities directly to obesity. 9 Change in eating styles is also an important contributory factor to the increasing level of overweight and obesity.…”

Section: Introductionmentioning

confidence: 99%

Is body composition important in young people’s weight management decision-making?

Fox

1998

Int J Obes

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AIM: Young people are often seen as an important target for prevention of overweight, but we know little about the factors which are important for their weight management decisions. This study aimed to evaluate the extent to which elements of body composition and dimensions were implicated in their decisions to change their weight. PARTICIPANTS: Participants were 116 male and 126 female volunteers from a tertiary college in the south-west of England with a mean age of 17.90 (s.d. 1.90) y. MEASURES: Body composition measures included height (m), weight (kg), waist and hip circumferences (mm), shoulder and hip girths (mm) and skinfold thicknesses (triceps, calf and subscapular, mm). Students also provided self-reported information on dietary practices they had undertaken in the last year. RESULTS: More females reported attempting weight loss in the last year compared to males (51.5 vs 17.6%), although more males reported attempting weight gain (19.3 vs 2.3%). Reported dietary strategies for both males and females centred around eating less fatty foods, eating less than usual and exercising more. However, a signi®cant proportion of females also reported excessive strategies, such as self-induced vomiting and regular crash dieting. Results indicated that females who desired to lose weight were signi®cantly (P`0.05) heavier, and bigger in terms of circumferences and skeletal breadths, compared to females who did not wish to change their weight. For males, thè weight loss' group were signi®cantly (P`0.05) bigger, heavier and fatter compared to the`no change and`weight gain' group. For females only, the previously signi®cant main effect for body dimensions across weight management groups (Pillais F 14,188 3.81, P`0.001) was extinguished when controlling for bone dimensions (Pillais F 12,198 1.68, P 0.074). CONCLUSION: These results indicate that frame size, particularly in the lower trunk, is a more important predictor of female weight management decision-making, than their levels of fatness. For males, fatness appears to drive their weight management decision-making processes to a greater extent.

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Peak Oxygen Uptake and Physical Activity in 11- to 16-Year-Olds

Cited by 68 publications

References 0 publications

Developing meaningful cohorts for human exposure models

Developing meaningful cohorts for human exposure models

Physical activity and psychological well-being in children with Type 1 diabetes

Is body composition important in young people’s weight management decision-making?

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