Heart rate during bicycle ergometer exercise in Watts per kilogram body weight of 12 and 13 year old boys.
Explore the source record for details and available documents.
Adolescent↗
Biomedical subjects
H C Kemper
Publications and source records attributed to H C Kemper.
Adolescent motor skill and performance: is physical activity in adolescence related to adult physical fitness?
In the Amsterdam Growth and Health Longitudinal Study (AGAHLS), a cohort of about 400 boys and girls (mean age 13 years) were followed over a period of 20 years. Over that period repeated measurements were done of body dimensions (height, weight, skinfolds), physical fitness (eight motor performance field tests: plate tapping, bent arm hang, 10 x 5 m sprint, arm pull, sit and reach, standing high jump, 10 leg lifts, 12-min endurance run, and one laboratory test to measure maximal aerobic power), and physical activity (by a cross-check interview). Three research questions were studied: (1) Is there a positive relationship between adolescent fitness (age 13-17 years) and adult physical activity (age 33 years)? (2) Do physical fitness and physical activity track from adolescence into adulthood? (3) What is the longitudinal relationship between physical fitness and physical activity? Multiple linear regression analysis showed that of the 9 physical fitness tests, only the 12-min endurance run and the maximal aerobic power during adolescence are significant (P < 0.05) predictors of adult physical activity. The effects are not influenced by biological age but by sex: only in females are the predictions significant (P < 0.05) Tracking over the period of 20 years estimated from stability coefficients showed values for physical fitness varying between 0.83 (plate tapping) to 0.38 (standing high jump and maximal aerobic power). Physical activity shows lower stability coefficients (0.35-0.29). A longitudinal linear regression technique was used to analyse the relationship between physical activity and physical fitness over the 20-year period; in this analysis corrections were made for both time-dependent (time, biological age, and cardiovascular factors) and time-independent variables (sex). All physical fitness tests show positive and significant (P < 0.05) standardized regression coefficients with physical activity, but the explained variance is less than 1%. Only maximal aerobic power has a higher explained variance of 1.8%. It can be concluded that: (1) Physical fitness in adolescence is only weakly related to adult physical activity; (2) between age 13 and 33 years, physical activity has low stability and physical fitness was higher stability; and (3) the longitudinal relationships between physical fitness and physical activity are only meaningful with maximal aerobic power.
Adolescent↗
Factors influencing tracking of cholesterol and high-density lipoprotein: the Amsterdam Growth and Health Study.
BACKGROUND: Tracking analysis of serum cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and the TC/HDL-C ratio was carried out by a new method based on generalized estimating equations (GEE). METHODS: Longitudinal data were derived from the Amsterdam Growth and Health Study, in which 181 subjects were measured six times from age of 13 years to the age of 27 years. RESULTS: Tracking coefficients (interpretable as coefficients of stability over time) calculated over a 15-year period with GEE for TC were 0.71 [95% confidence interval (CI) 0.60-0.74]; for HDL-C, males, 0.51 (95% CI 0.34-0.69); for HDL-C, females, 0.65 (95% CI 0.53-0.77); and for the TC/HDL-C ratio 0.71 (95% CI 0.63-0.79). The changes in TC were positively influenced by both body fatness (standardized regression coefficient beta = 0.13; 95% CI 0.04-0.21) and daily physical activity (beta = 0.08; 95% CI 0.00-0.16), and the changes in the TC/HDL-C ratio were positively influenced by body fatness (beta = 0.11; 95% 0.03-0.19). CONCLUSIONS: GEE tracking coefficients for TC and for the TC/HDL-C ratio were higher than the coefficients for HDL-C. Furthermore, multivariate analyses showed a positive influence of body fatness and daily physical activity measured at 13 years of age on the changes in TC over time. No relations were found between any of the biological, psychological, or lifestyle parameters and the changes in HDL-C, while the changes in the TC/HDL-C ratio were positively related to body fatness measured at 13 years of age.
Adolescent↗
Relative validity and repeatability of a new questionnaire on physical activity.
BACKGROUND: A physical activity questionnaire was developed with the aim to estimate usual individual daily energy expenditure. The questionnaire focused on the number of hours usually spent on various activities. In a pilot study it was tested for repeatability and validity in a population of 126 Dutch adults (64 men, 62 women). METHODS: For assessment of repeatability the questionnaire was administered three times during the course of 1 year. A four-times-repeated 3-day activity diary was used as a reference instrument to evaluate validity. RESULTS: Differences in mean energy expenditure among repeated administrations of the questionnaire were small and not significant. Spearman's test-retest correlation coefficients for total energy expenditure for men were 0.76 [95% confidence interval (CI) 0.63-0.85] and 0.70 (95% CI 0.54-0.81) at 5 and 11 months, respectively, and for women were 0.58 (95% CI 0.36-0.74) and 0.71 (95% CI 0.54-0.82). There was a significant trend showing increasing mean diary energy expenditure for successive tertiles of questionnaire energy expenditure. The correlation between the questionnaire and the diary was 0.66 (95% CI 0.49-0.78) for men and 0.43 (95% CI 0.18-0.63) for women. CONCLUSIONS: It was concluded that this questionnaire is a useful tool for estimating energy expenditure in epidemiological studies.
Adult↗
Smoking behaviour and biological maturation in males and females: a 20-year longitudinal study. Analysis of data from the Amsterdam Growth and Health Longitudinal Study.
PRIMARY OBJECTIVE: (1) Describe the longitudinal smoking behaviour of boys and girls during adolescence in relation to calendar age, skeletal age, years from peak height velocity (PHV) and years from menarche (in girls). (2) and (3) Investigate the timing of biological maturation (early or late maturation) in relation to smoking behaviour in adolescence and in adulthood (i.e. calendar age 32/33). HPOTHESIS: We hypothesized skeletal age, years from PHV and years from menarche to be better predictors of smoking than calendar age. RESEARCH DESIGN: This study is part of the Amsterdam Growth and Health Longitudinal Study (AGAHLS) that was started in 1977 with 619 pupils from two secondary schools (mean age 13.0 SD 0.6). METHODS AND PROCEDURES: Smoking behaviour was assessed four times between 1977 and 1980 and once in 1996/1997. Calendar age and skeletal age were measured annually whereas height and menarche were measured every 4 months. Maturation rate (skeletal age minus calendar age), age at PHV and age at menarche were used to estimate timing of biological maturation. Generalized Estimating Equation (GEE) analysis was used to study maturation rate in relation to smoking during adolescence, whereas logistic regression analyses were used to study mean maturation rate, years from PHV and years from menarche in relation to smoking in adulthood. OUTCOME AND RESULTS: Skeletal age, years from PHV and years from menarche are no better predictors of smoking during adolescence than calendar age. The prevalence of smoking rises gradually with the increase in all four estimates of biological maturation. Timing of biological maturation was positively related to smoking but only at calendar age 13 (OR 3.34, CI 1.58, 7.07). None of the three measures to estimate timing of biological maturation was significantly related to smoking status in adulthood.
Adolescent↗
Height velocity in a group of teenage boys.
In a multi-discipline longitudinal study, 'Growth and Health of Teenagers', height velocity was measured four monthly during four consecutive years in a group of about 250 growing Dutch youngsters. From the individual velocity curves of height we calculated peak height velocity (PHV) and the age at which PHV occurred. Height velocity was estimated in 102 boys from the derivative of a second degree moving polynomial function over five measurements. PHV varies in boys between 6.1 and 14.0 cm/year. The median value of the age at PHV in boys is 14.0 years. Early-maturing boys have approximately 2 cm/year greater PHVs than late-maturing boys.
Adolescent↗
Longitudinal study of maximal aerobic power in teenagers.
On the basis of measurement of maximal aerobic power (VO2max) over a period of four years in a teenage population of boys (N = 102) and girls (N = 133), we studied the growth of VO2max in absolute values and in relative values: relative to whole body mass (VO2max/BM), to fat-free mass (VO2max/LBM) and to height squared (VO2max/H2). The changes in VO2max were studied in relation to chronological age (CA), skeletal age (SA), and age relative to peak height velocity (PA). Since no significant testing or measuring effects could be demonstrated and the reproducibility was high, the longitudinal design seems adequate to trace individual growth curves of VO2max. With CA VO2max increases in boys from 2.41/min at age 12+ to 3.81/min at age 17+. The increase in girls is less, from 2.31/min to 2.71/min over the same age range. VO2max/BM remained constant in boys (591/min.kg) and in girls it gradually decreased from 50 at age 12+ to 45 ml/min.kg at age 17+. The decrease in girls has been caused partly by an increase in body fat. When VO2max is aligned on PA, the results show that the peak increase coincides roughly with the age at peak height velocity. It demonstrates that in general in boys and girls during their teens no discrepancy between structural and functional growth occurs as far as VO2max is concerned.
Adolescent↗
Is physical exercise good for the brain of a child?
Explore the source record for details and available documents.
Brain Injuries↗
Relation between the longitudinal development of personality characteristics and biological and lifestyle risk factors for coronary heart disease.
OBJECTIVE: This study was undertaken to assess the stability of personality characteristics (ie, inadequacy, rigidity, dominance, self-sufficiency, and social inadequacy) over a 15-year period covering adolescence and young adulthood and to analyze the longitudinal relationships between personality characteristics and both biological (ie, lipoproteins, blood pressure, and body fatness) and lifestyle (ie, physical activity, dietary intake, smoking, and alcohol consumption) risk factors for coronary heart disease (CHD). METHODS: The data were derived from the Amsterdam Growth and Health Study, an observational longitudinal study in which, over a period from 13 to 27 years of age, six repeated measurements were performed on 181 subjects. Both the stability analysis and the analysis of the longitudinal relationships were performed by generalized estimating equations (GEE). This method is suitable for both continuous and dichotomous outcome variables, by using all available longitudinal data. RESULTS: Stability coefficients for the personality characteristics varied between 0.39 for self-sufficiency and dominance and 0.53 for social inadequacy. Self-sufficiency was inversely related to total serum cholesterol (only male subjects) and body fatness; inadequacy was inversely related to systolic blood pressure. Dominance (female subjects) was positively related to body fatness and social inadequacy (male subjects) was positively related to total serum cholesterol. Furthermore, inadequacy was positively related to smoking behavior. Social inadequacy and rigidity were inversely related to smoking behavior. Self-sufficiency was inversely related to alcohol consumption. CONCLUSIONS: Over a period of 15 years, personality characteristics showed marginal stability. Weak relationships were found between personality characteristics and both biological and lifestyle CHD risk factors.
Adolescent↗
Prevention of running injuries by warm-up, cool-down, and stretching exercises.
The purpose of this study was to evaluate the effect of a health education intervention on running injuries. The intervention consisted of information on, and the subsequent performance of, standardized warm-up, cool-down, and stretching exercises. Four hundred twenty-one male recreational runners were matched for age, weekly running distance, and general knowledge of preventing sports injuries. They were randomly split into an intervention and a control group: 167 control and 159 intervention subjects participated throughout the study. During the 16-week study, both groups kept a daily diary on their running distance and time, and reported all injuries. In addition, the intervention group was asked to note compliance with the standardized program. At the end of the study period, knowledge and attitude were again measured. There were 23 injuries in the control group and 26 in the intervention group. Injury incidence for control and intervention subjects was 4.9 and 5.5 running injuries per 1000 hours, respectively. The intervention was not effective in reducing the number of running injuries; it proved significantly effective (P < 0.05) in improving specific knowledge of warm-up and cool-down techniques in the intervention group. This positive change can perhaps be regarded as a first step on the way to a change of behavior, which may eventually lead to a reduction of running injuries.
Adult↗
Which lifestyle parameters discriminate high- from low-risk participants for coronary heart disease risk factors. Longitudinal analysis covering adolescence and young adulthood.
BACKGROUND: The purpose of this study was to analyse which lifestyle parameters (daily physical activity, dietary intake, smoking habits and alcohol consumption) discriminate between participants at high-risk and those at low-risk for coronary heart disease (CHD) [systolic and diastolic blood pressure (SBP/DBP), total serum cholesterol (TC), high-density lipoprotein cholesterol (HDL), the TC: HDL ratio, body fatness (sum of skinfolds [SSF]) and cardiopulmonary fitness (VO2-max)]. METHODS: The data were derived from the Amsterdam Growth and Health Study (AGHS); an observational longitudinal study in which six repeated measurements were carried out over a period of 15 years on 181 participants aged 13 years at entry to the study. To assess possible discriminating factors, generalized estimating equations were used. This method makes use of risk group changing behaviour over time by using all available longitudinal data. RESULTS: For DBP no significant relationships were found; high risk for SBP was inversely related to smoking habits (OR=0.52; P<0.01). No significant relationships were found for TC; high risk for HDL was positively related to the intake of carbohydrates (OR=1.2; P=0.02) and to smoking habits (OR=1.6; P=0.04); high risk for the TC:HDL ratio was positively related to the intake of carbohydrates (OR=1.3; P=0.01). High risk for SSF was positively related to the intake of protein (OR=1.5; P<0.01) and smoking habits (OR=1.8; P=0.01) and inversely related to daily physical activity (OR=0.81; P=0.01). High risk for VO2-max was inversely related to daily physical activity (OR=0.67; P<0.01). CONCLUSIONS: In the relative young and healthy population of the AGHS during adolescence and young adulthood, physical inactivity was the most important lifestyle parameter related to high risk for CHD.
Adolescent↗