Adolescent correlates of adult physical activity: a 26-year follow-up.

PURPOSE: It is hypothesized that adolescent physical activity, fitness, anthropometric dimensions, fatness, biological maturity, and family characteristics contribute to the variation in physical activity at 40 yr of age, and that these associations vary with age. METHODS: Subjects were 166 males followed from 1969 to 1996, between the ages of 14 and 40 yr from the Leuven Longitudinal Study on Lifestyle, Fitness and Health. Sports participation, fitness, anthropometric dimensions, fatness, and biological maturity were observed during the growth period. Also, sociocultural characteristics of the family were examined. The work, leisure time, and sport activity index of the Baecke Questionnaire and activity counts of a triaxial accelerometer were used as outcome variables at 40 yr. RESULTS: When upper and lower activity groups (quintiles) at 40 yr were contrasted, moderate associations were found (R2c varied between 0.1419 and 0.3736). No or low associations were found with the leisure time index. Body dimensions, fitness scores, sports practice, and family characteristics contributed to the explained variance in work, sport index, and activity counts. Multiple correlations were low (R2 = 0.037-0.085) for the work and leisure time activities, and were somewhat higher (R2 = 0.06-0.156) for the sport index and the activity counts in the total sample. CONCLUSION: Adolescent somatic dimensions, fitness, sports participation, parental sociocultural characteristics, and sport participation contributed to a small-to-moderate extent to the contrast between high and low active adults.

Influence of participation in high-impact sports during adolescence and adulthood on bone mineral density in middle-aged men: a 27-year follow-up study.

This study examined whether participation in high-impact sports during adolescence and adulthood contributes to bone health in males aged 40 years. Data were analyzed on 154 Belgian men aged 13 years at study onset in 1969 and aged 40 years at the end of the 27-year follow-up. In a second analysis, subjects were divided into three groups according to their sports participation history: participation during adolescence and adulthood in high-impact sports (HH; n=18), participation during adolescence in high-impact sports and during adulthood in nonimpact sports or no sports (HN; n=15), and participation during adolescence and adulthood in nonimpact sports or no sports (NN; n=14). Body mass and impact loading during adulthood were significant predictors of total body bone mineral density (BMD) and lumbar spine BMD. Analysis of variance revealed significant differences for lumbar spine BMD between the HH (1.12 g/cm2) group and the HN (1.01 g/cm2) and NN (0.99 g/cm2) groups (F=5.07, p=0.01). Total body BMD was also higher in the HH group at age 40 years, but not significantly (F=3.17, p=0.0515). Covariance analyses for total body BMD and lumbar spine BMD, with body mass and time spent participating in sports as covariates, confirmed these results. Continued participation in impact sports is beneficial for the skeletal health of males aged 40 years.

Modeling stability and change in strength development: a study in adolescent boys.

The purpose of this study was to investigate stability and change in different expressions of strength development in adolescent boys using structural equation modeling. Three models were used: Markov simplex to study stability or tracking, Wiener or random walk to investigate fanning-out or spread effects in change, and latent growth to study differences in individual pathways of change as well as group changes. In the Leuven Growth Study, 588 male subjects were followed for 6 years with a mean age of 12.7 years at the onset of the study. Vertical jump, arm pull, and bent arm hang were used to mark the following strength factors: explosive strength, static strength, and functional strength. All models were tested with robust estimation procedures based on the software EQS 6.0. Main results and conclusions are as follows: 1) all strength factors showed moderate to high tracking, with low values of instability in relative position of the subjects in their developmental channels; 2) the fanning-out effect is not obvious, although some evidence showed a spread effect in functional and explosive strength; 3) there are marked interindividual differences in developmental pathways of strength manifestations; 4) strength development is linear and also has some curvilinearity, something akin to a breaking effect; 5) linear trend is negatively correlated with initial status and the leveling-off effect is also negatively correlated with the linear change.

O tracking da atividade física: um estudo em adolescentes do sexo masculino / Tracking of physical activity: a study with adolescent males

Este estudo pretende investigar o tracking da atividade física de adolescentes do sexo masculino recorrendo a um modelo quasi-sinplex formulado no seio da modelaçäo de estruturas de covariância. Os dados provêm do estudo de crescimento de Leuven, em que foram seguidos longitudinalmente 588 sujeitos do sexo masculino durante 6 anos. No ínicio do estudo, os sujeitos tinham 12,76 anos de idade média, e no final 17,73 anos. A avaliaçäo da atividade física foi efetuada com recurso de um questionário estrututado e validado. Só consideramos, como indicador da atividade física, o número de horas de prática desportiva informal, independentemente das horas dedicadas à Educaçäo Física. A análise dos dados constou de um modelo quasi-simplex de natureza auto-regressiva, permitindo pesquisar diferentes formulaçöes do tracking. Recorreu-se a métodos robustos de estimaçäo de máxima verossimilhança. Verificou-se uma elevada estabilidade da atividade física considerada ano-ano, tracking moderado na adolescência e resultados baixos a moderados na instabilidade intraindividual nas diferenças que ocorrem entre os sujeitos em cada ponto do tempo.

Daily physical activity and physical fitness from adolescence to adulthood: A longitudinal study.

The stability of physical fitness and physical activity in Flemish males from 18 to 40 years of age was investigated. In addition, effects of a consistently low-activity or high-activity level during the same age period on physical fitness were studied. The sample consisted of males who were followed longitudinally from age 13 to age 18 years, and were remeasured at the ages of 30, 35, and 40 years. Complete data about physical fitness and physical activity between 13 and 40 years were available for 130 subjects. Stability was measured using Pearson autocorrelations and simplex models. Multivariate analysis of variance (MANOVA) for repeated measurements was used to look for the effects of activity level on physical fitness. Simplex models showed higher stability coefficients than Pearson correlations, and stability of physical fitness was higher than stability of physical activity. Physical fitness showed the highest stability in flexibility (r = 0.91 between 18 and 30 years, r = 0.96 for both the 30-35 and 35-40 ages intervals), while physical activity showed the highest stability during work (r between 0.70 and 0.98 for the 5-year intervals). Results from MANOVA indicated that for some fitness characteristics the high-active subjects were more fit than their low-active peers. Stability of physical activity was higher than assumed and, therefore, it is a useful and independent indicator for further research. Although possible confounding factors are present (e.g., heredity), a higher level of physical activity during work and leisure time on a regular basis benefits physical fitness considerably. Am. J. Hum. Biol. 12:487-497, 2000. Copyright 2000 Wiley-Liss, Inc.

Sociogeographic variation in the physical fitness of a cross-sectional sample of Flemish girls 13 to 18 years of age.

Three aspects of physical fitness-somatic characteristics, motor fitness, and sport participation-of girls from different sociogeographic origins of Belgium were contrasted. The sample consisted of a cross-sectional sample of 4,528 Flemish girls 13 to 18 years of age, who were classified by dwelling area as rural, semi-urban, and urban. Somatic characteristics included 16 anthropometric dimensions, skeletal maturity, and somatotype. Motor fitness was assessed by 10 tests. Sociocultural background information and the level of sport participation were investigated by questionnaire and interview. Data were analysed via one-way analyses of variance and growth curves were plotted to compare the sociogeographic differentiation patterns in physical fitness variables. The results show small motor and somatic differences between rural and urban youngsters, which is explained by the process of conurbation. However, urban girls were significantly more involved in sports than their rural counterparts. This is most probably due to greater sport involvement of parents from urban girls and/or the differences in available sport facilities.