Cardiopulmonary Fitness, Physical Activity Patterns, and Selected Coronary Risk Factor Variables in 11- to 16-Year-Olds

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

doi:10.1123/pes.3.3.219

Cited by 56 publications

(26 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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“…The positive association between _ V O 2peak and HDL-C concentration was consistent with previous studies of young people (Al-Hazzaa et al 1994;Armstrong et al 1991;Macek et al 1989;Sallis et al 1988;Suter and Hawes 1993;Tell and Vellar 1988;Valimaki et al 1980). The association between _ V O 2peak and HDL-C concentration (r=0.41) was similar to previous studies of welltrained athletes as well.…”

Section: _ V O 2peak and Blood Lipidssupporting

confidence: 92%

Blood lipids of young distance runners: distribution and inter-relationships among training volume, peak oxygen consumption, and body fatness

Eisenmann

Womack

Reeves

et al. 2001

European Journal of Applied Physiology

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This study describes the distribution of blood lipid concentrations and examines relationships among training volume (TV, kilometers per week), peak oxygen consumption (VO2peak), body fatness, and blood lipid concentrations in 48 male and 22 female distance runners, aged 10-19 years. Comparisons were made to a current reference sample and clinical cut-off points. Relationships were assessed by partial correlations allowing for age and sexual maturity. Compared to reference median values, mean concentrations of total cholesterol (P=0.07) and low density lipoprotein-cholesterol (P<0.005) were higher, while high density lipoprotein-cholesterol (HDL-C; P=0.24) was comparable in male distance runners. Blood lipid concentrations in female distance runners were comparable to reference median values. Although some subjects had dyslipidemic values, most possessed clinically normal concentrations of blood lipids. The TV was weakly correlated with blood lipid concentrations, but may have been indirectly related with HDL-C through its relationship with VO2peak in males runners (r=0.32). In female runners, correlations between sum of skinfolds (SSF), the trunk-to-extremity ratio (TER) and blood lipid concentrations were low (r=0.16 to -0.27), with one exception (TER and HDL-C, r=-0.60). The most consistent relationships existed among TV, VO2peak, SSF, and HDL-C with partial correlations ranging from low (r=0.10 TV) to moderate (r=0.37 SSF, r=0.41 VO2peak). The correlation between VO2peak and HDL-C remained significant after allowing for age and SSF, while the partial correlation between SSF and HDL-C, allowing for age and VO2peak, was reduced and not significant (r=-0.19, P=0.20). In female runners, the correlation between VO2peak and HDL-C was r=0.32, whereas the partial correlation between SSF and HDLC, allowing for age and VO2peak, was r=0.00. Blood lipid concentrations of young male distance runners were not, on average, different to the general population of the youth of the United States. The young distance runners showed considerable heterogeneity in blood lipid phenotypes, including dyslipidemic values. The results highlight the complex relationships among TV, VO2peak, body fat and HDL-C, and indicate the unique contribution of VO2peak as an important predictor of HDL-C in young distance runners.

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“…It is important to note that significant relationships existed prior to adjusting for body fatness in those studies showing no relationship between Aerobic fitness, BMI and CVD JC Eisenmann et al aerobic fitness and CVD risk factors. [36][37][38][39] In this study, there were both main effects for PWC and BMI, as well as interaction effects, depending on the particular risk factor. This indicates that the relationships between fitness, fatness and CVD risk in adolescents are complex and vary depending on the risk factor under consideration.…”

Section: Discussionmentioning

confidence: 63%

Aerobic fitness, body mass index, and CVD risk factors among adolescents: the Québec family study

et al. 2005

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PURPOSE:The purpose of this study was to examine the association of body mass index (BMI) and aerobic fitness on cardiovascular disease (CVD) risk factors in adolescents. METHODS: The sample included 416 boys and 345 girls 9-18 y of age from the Québec Family Study. Participants were crosstabulated into four groups using a median split of age-adjusted physical working capacity (PWC) and body mass index (BMI). Group differences in age-adjusted CVD risk factors (blood pressures, fasting total cholesterol (CHOL), LDL -C, HDL-C, HDL/ CHOL, triglycerides, glucose, and a composite risk factor score) were examined by two-way ANOVA. RESULTS: Several CVD risk factors showed significant main effects for PWC, BMI and/or the PWC by BMI interaction. In general, low fit males and females had higher blood lipids and glucose compared to their high fit counterparts within BMI categories although none of the differences reached statistical significance. The high fit/low BMI group showed the best CVD risk factor profile while the low fit/high BMI showed a poorer profile as evidenced by several significant differences between these two groups. Other significant differences occurred for various risk factors between groups. CONCLUSION: Both aerobic fitness and BMI show an independent association with CVD risk factors in adolescents.

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Cardiopulmonary Fitness, Physical Activity Patterns, and Selected Coronary Risk Factor Variables in 11- to 16-Year-Olds

Cited by 56 publications

References 0 publications

Developing meaningful cohorts for human exposure models

Developing meaningful cohorts for human exposure models

Blood lipids of young distance runners: distribution and inter-relationships among training volume, peak oxygen consumption, and body fatness

Aerobic fitness, body mass index, and CVD risk factors among adolescents: the Québec family study

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