Katrien Delvaux

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.

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.

Lumbosacral pain in an athlete.

This report presents a case of a stress fracture in the sacrum. The diagnosis of a stress fracture in the sacrum is an uncommon localization and has been reported infrequently in the English literature. Association of this type of stress fracture with a pneumatocyst has not previously been reported.

Associations between daily physical activity and physical fitness in Flemish males: A cross‐sectional analysis

The relationship of physical activity to several components of physical fitness was investigated in a sample of 166 males 40 years of age. In addition to Pearson correlations, multivariate canonical correlations were calculated. Physical activity during work (work index), sport (sport index), and leisure time (leisure time index) was assessed by the Baecke questionnaire. Physical fitness included cardiorespiratory fitness measures, the body mass index (BMI), the sum of seven skinfold thicknesses (SKI), percentage body fat (PFAT), balance, and several tests of muscle strength and endurance, flexibility, and speed of limb movement. More than 86% of the variance was shared by the two first canonical variables. The first canonical variable can be interpreted as a health‐related fitness function. Carciorespiratory fitness, balance, speed of limb movement, explosive strength, and trunk muscle strength are clearly related to this function. From the physical activity measures, the Baecke sport index correlated significantly with this health‐related fitness function. The second canonical variable can be explained as a fatness function, since body weight, BMI, SKI, and PFAT showed the highest correlations with the variable. The Baecke work index was inversely related to this canonical variable. The sample was also divided into physical activity groups in order to look for differences in physical fitness. The data indicate that physical activity during work was modestly, but inversely related to adiposity. Sport activity was beneficially associated to several fitness components, including cardiorespiratory fitness, trunk muscle strength, and upper body muscular endurance. Am. J. Hum. Biol. 11:587–597, 1999.

Adolescent physical performance and adult physical activity in Flemish males

Limited information is available about the associations between adolescent fitness levels and adult physical activity. In the present study, these associations are investigated using different indicators of physical activity. It is hypothesized that both health‐ and performance‐related fitness characteristics, observed during the adolescent period, contribute equally to the explained variance in adult physical activity levels. Subjects were 109 Flemish males followed over a period of 27 years from 13 to 40 years of age in the Leuven Longitudinal Study on Lifestyle Fitness and Health. Performance and health‐related fitness characteristics were observed during the growth period and at 40 years of age. The Work Index, Leisure Time Index, and Sport Index of the Baecke questionnaire were used as indicators of physical activity together with triaxial accelerometry. Multiple regression and discriminant analyses contrasting extreme quintiles of activity groupings were used to analyse the associations. Only the Baecke Sport Index showed consistent significant associations (R2 = 0.03 to R2 = 0.23) with adolescent fitness levels observed at 13, 15, and 18 years. When upper and lower quintiles were contrasted, fitness characteristics observed at the three age levels during adolescence were significantly different for each of the three indices of the Baecke questionnaire at 40 years of age. Lowest associations (R2 = 0.09 to R2 = 0.17) were found for the Work Index, followed by the Leisure Time Index (R2 = 0.12 to R2 = 0.28) and Sport Index (R2 = 0.25 to R2 = 0.43). Highest associations were evident for the 18‐ to 40‐year interval. Performance‐ and health‐related fitness characteristics explain equally well the variance in physical activity indicators. Am. J. Hum. Biol. 13:173–179, 2001.

Associations between physical activity, nutritional practices and health-related anthropometry in Flemish males: a 5-year follow-up study

OBJECTIVE: To examine the extent to which extent health-related anthropometric characteristics such as body mass index, waist–hip ratio, waist girth, percentage of body fat and weight gain are associated with physical activity and nutritional habits in a prospective follow-up study.DESIGN: A 5-y prospective follow-up study.SUBJECTS: 132 healthy men from The Leuven Longitudinal Study on Lifestyle, Physical Fitness, and Health.MEASUREMENTS: The main outcome measures in this study were body mass index, waist–hip ratio, waist girth, percentage of body fat and significant weight gain at the ages of 35 and 40 y. An unhealthy body composition was defined as a body mass index above 26, a waist–hip ratio above 0.95, a waist girth and body fat percentage above percentile 75 at the end of the 5-y follow-up period and a significant weight gain of 5 kg or more between the two examination periods. Anthropometric characteristics were derived from clinical examination. Physical activity at the age of 35 and 40 and nutritional habits at the age of 40 were determined from questionnaires.RESULTS: Physical activity was the most important predictor for the waist–hip ratio in this sample. In contrast, nutritional habits show a stronger relationship with body mass index. The absolute amount of energy intake is not as important as the dietary factors in predicting subjects with overweight or an unhealthy body composition. The index of occupational activities appears to be the most important physical activity variable.CONCLUSION: The relative contribution of physical activity and nutritional habits in health-related anthropometry varies with the characteristic considered. It is important to include all components of physical activity, and occupational activities in particular, in determining these relationships in a general population sample.