Leuven Longitudinal Study Research Articles

Involvement in non-club organized sport: organizational patterns of sport participation from a longitudinal life course perspective

In this paper, patterns of participation in non-club organized sport over the life course of individuals are studied in order to enhance the understanding of their involvement in sport. The main research question of this investigation is to examine the correlation between prior sport experiences and current patterns of sport participation amongst middle-aged adults. The study is executed through the analysis of data from the Leuven Longitudinal Study on Lifestyle, Fitness and Health (LLSLFH). The LLSLFH was developed distinctly for men in 1969, 1991, 2002, 2012 and for women in 1979, 1999, 2012. In 2012, a remaining sample of 110 men and 108 women participated in the study. The association between patterns of participation (club organized or non-club organized sport) and/or stages of inactivity in various stages of life was analyzed by a descriptive tracking analysis and a multinomial regression analysis. Conclusively, previous patterns of participation are key factors for explaining the participation of middle-aged adults in non-club organized sport. In general, there is a positive relation between non-club organized sports in different stages of adulthood. However, the periods for tracking are short-term and occur at later stages in life. Non-club organized sport also appears to be more vulnerable to drop-outs than club organized sport. No patterns of transfer were observed between club and non-club organized sport participation.

Fitness And Cardiovascular Risk Factors In Males Of Contrasting Maturity Status.

During adolescence, the associations between biological maturation, fitness, and cardiovascular risk factors have been studied to some extent. Little is known, however, about the later outcomes of the maturation process. PURPOSE: To document the differences in fitness and risk factors between adult males of contrasting maturity status during adolescence. METHODS: In the Leuven Longitudinal Study on Lifestyle, Fitness and Health, 133 males were followed from 1969, when they were 12 to 13 years, until 2002-2004 when they were 47 years. Anthropometric variables, (height, weight, waist circumference, skinfolds, bioelectrical impedance, Dual X-ray absorptiometry) were measured, the adult Eurofit tests and Biodex strength measurements were administered, and risk factors ( blood pressure, glucose level, and blood lipids) were examined. Age at peak height velocity (APHV), derived from individual curve fitting using non-smoothed polynomials, was used to classify the adolescent boys into three maturity groups: (1) early maturing males: APHV -1 SD before mean APHV of the total sample, late maturing males: APHV +1 SD after mean APHV of the total sample, and average: APHV between 0.5 SD before and 0.5 SD after the mean APHV of the total sample. After normalization of the phenotypes, ANOVA's and post-hoc tests were used to verify the mean differences between the contrasting maturity groups. RESULTS: At 47 years, early maturing males had higher systolic blood pressure and biceps and subscapular skinfolds, whereas late maturing males had better strength (handgrip & isokinetic knee-extension torque at 60°/sec (borderline significant)), and power (standing long jump and counter movement jump). CONCLUSION: For some fitness components the adolescent advantage of early maturation reverses in adulthood whereas for some risk factors early maturing males are more at risk.

Methodological issues associated with longitudinal research: Findings from the Leuven Longitudinal Study on Lifestyle, Fitness and Health (1969 – 2004)

Longitudinal studies provide unique opportunities but are also faced with several limitations. The purpose of this study was to document three of these issues (“imperfect” design, evolution of data collection methods, representativeness) by means of the Leuven Longitudinal Study on Lifestyle, Fitness and Health (LLSLFH). The LLSLFH (1969 – 2004) comprises observations on males between 12 and 18 years and at 30, 35, 40, and 47 years, and on females at 16 and 40 years. In the most recent phase of the study, spouses and offspring were also included. The different phases and evolving research questions throughout the LLSLFH required an appropriate adaptation of the research design. The associated evolution of data collection methods largely reflects the changing ideas about physical fitness, body composition, and physical activity, the continuing search for new and better measurement techniques, and the need for adaptations with age. Ongoing study participants are representative in terms of body composition and, except for adolescence in males, also physical activity. No straightforward answer can be given concerning physical fitness. In both sexes, socio-economic status is above average. When informed about the possible “pitfalls” of longitudinal research in advance, several measures could be taken to prevent or limit them as much as possible.

Tracking of Physical Fitness and Physical Activity from Youth to Adulthood in Females

To evaluate stability of physical fitness and physical activity from adolescence into middle adulthood in Flemish females. Within the scope of the Leuven Longitudinal Study on Lifestyle, Fitness and Health, 138 females (mean age=16.6+/-1.1 yr) from the Leuven Growth Study of Flemish Girls were seen in adulthood (mean age=40.5+/-1.1 yr). Several body dimensions and motor fitness tests were taken. Physical activity was assessed by means of a sports participation inventory. Inter-age correlations were calculated between adolescent and adult values. Cross-tabulation was used to identify the percentage of subjects remaining in the same BMI and physical activity group or shifting from one group to another from adolescence to adulthood. Odds ratios for less activity and overweight in adulthood according to adolescent activity or weight status were calculated. Except for flamingo balance, plate tapping, leg lifts, and arm pull, all anthropometric and physical fitness characteristics were stable from adolescence to adulthood (r ranging from 0.49 to 0.96). Sports participation was not a stable characteristic (r=0.13). From adolescence to adulthood, 84.5 and 63.6%, respectively, remained in the normal-weight and overweight group, whereas 62.5 and 54.4%, respectively, remained in the less active and active group. The odds of being overweight in adulthood was 9.53 (95% CI: 3.1-29.8) times greater in overweight compared with normal-weight adolescent girls. In Flemish females, anthropometric and fitness characteristics demonstrate higher levels of stability from adolescence to middle adulthood than physical activity. Weight status during adolescence is indicative of adult weight status, and a pattern of less activity rather than activity tends to continue from youth to adulthood.

Alpha-actinin-3 R577X Genotype is Associated with Muscle Power in Middle-aged Men and Women

The alpha-actinin-3 (ACTN3) gene encodes a protein of the Z disk of fast-contracting myofibers, and a polymorphism of ACTN3 (C to T) results in complete loss of the protein. The ACTN3 genotype (R577X) has been found to be associated with performance in Australian elite athletes and responses to training, however, little is known about the importance of this polymorphism in the interindividual variation of strength and power in the general population. PURPOSE: To study the association of the R577X ACTN3 genotype with muscle strength and power in middle age. It was hypothesized that X allele carriers showed lower explosive and maximal strength. METHODS: The R577X ACTN3 polymorphism (rs1815739, Sequenom MassARRAY SNP) was typed in 151 males (47 +/− 0.67 yr) and 135 females (40.50 +/− 1.1 yr) of the Leuven Longitudinal Study on Fitness, Lifestyle and Health. Three commonly used strength and power tests were administered (HGR= hand grip, VTJ= vertical jump, SBJ= standing broad jump). Genotype-phenotype effects were tested using AN(C)OVA with body mass as covariate. RESULTS: Lack of ACTN3 (X/X carriers) was observed in 26% of males and 23% of females (X frequencies 0.49 in males, 0.45 in females, no violation of HWE). No association was found with HGR strength. For VTJ, corrected for body mass, XX genotype carriers perform consistently and significantly (P<0.01) lower than X/R or R/R genotypes. Having at least one copy of the ACTN3 coding allele (R/X andR/R genotypes) did not differentiate performance in females, however in males an additive effect of the R allele was present. Similar results were found for absolute VTJ performances. For SBJ performance, similar trends (n.s.) were found. The ACTN3 R577X genotype explained between 2.5 and 6% of total variance in VTJ performance. CONCLUSIONS: Also in the general adult population, individuals lacking the ACTN3 protein, show decreased power performance, however, no effects are found on isometric strength.

Familial Resemblance In Physical Fitness

Given the positive relationship between health related physical fitness and health status, insight in determinants of physical fitness might be useful for intervention and/ or health promotion campaigns. These determinants can be influenced by genetic and non-genetic relationships between family members. PURPOSE To quantify familial resemblance in physical fitness components. METHODS 148 fathers (47y ± 0.7) of the “Leuven Longitudinal Study on Lifestyle, Fitness and Health”, 103 mothers (44.4y ± 2.6), 60 sons (17.3y ± 1.8) and 45 daughters (17. 1y ± 2.2) performed physical fitness tests to quantify muscular strength (isometric, explosive, functional and trunk), maximal aerobic performance, speed of limb movement, flexibility and balance. Pearson product moment correlations were calculated between all family members to estimate familial resemblance in physical fitness characteristics. RESULTS Largest correlations between genetically related family members were found for isometric strength (0.24–0.70), maximal aerobic performance (0.16–0.42) and flexibility (0.14–0.37). High father-mother-correlations were found for isometric strength (0.48), maximal aerobic performance (0.42) and speed of limb movement (0.28). For trunk strength significant parent-son correlations were observed (0.31–0.34) and the spousal correlation was 0.22, although it was not significant. Family members' scores for balance and explosive strength did not correlate significantly. CONCLUSIONS As first degree family members share on average 50% of their genetic material, correlations found in this study for isometric strength, maximal aerobic performance and flexibility suggest a component of genetic transmission. However, as the spousal correlations for isometric strength, maximal aerobic performance and speed of limb movement are quite high (0.28–0.48), assortative mating and/or shared environmental factors are presumably also causing part of the variance of these variables. No clear patterns can be derived from the familial correlations in balance and explosive strength, suggesting larger individual environmental influences. Supported: The Flemish Policy Research Center Sport, Physical Activity and Health is supported by the Flemish Government.

Generational Differences In Physical Fitness

PURPOSE To document the generational differences in male adolescents and to study the father-son correlations in physical fitness. METHODS Between 1969 and 1974, Belgian male adolescents were observed in the Leuven Growth Study of Belgian Boys and, in 2003, their sons participated in the last phase of the Leuven Longitudinal Study of Lifestyle, Fitness and Health. Height, weight, BMI were measured, and the Leuven fitness test battery was administered in 77 father-son pairs observed about 33 years apart but, at the same age level (15.7 ± 1.75 yrs). Generational differences were tested and father-son correlations calculated. RESULTS Present-day male adolescents are taller, heavier and perform less well in static strength, flexibility and speed of limb movement than their fathers during their adolescence. No differences were found for BMI, explosive strength or power, muscular endurance, and running speed. Father-son correlations were rather high (above .40) for isometric strength, power, speed of limb movement and flexibility. Non-significant correlations were observed for running speed and muscular endurance. CONCLUSIONS Present-day male adolescents perform worse than their fathers during their adolescence, and relatively high father-son correlations were observed, indicating genetic and/or cultural transmission. Supported: The Flemish Policy Research Center Sport, Physical Activity and Health is supported by the Flemish Government.

Generational Differences In Physical Fitness

PURPOSE To document the generational differences in male adolescents and to study the father-son correlations in physical fitness. METHODS Between 1969 and 1974, Belgian male adolescents were observed in the Leuven Growth Study of Belgian Boys and, in 2003, their sons participated in the last phase of the Leuven Longitudinal Study of Lifestyle, Fitness and Health. Height, weight, BMI were measured, and the Leuven fitness test battery was administered in 77 father-son pairs observed about 33 years apart but, at the same age level (15.7 ± 1.75 yrs). Generational differences were tested and father-son correlations calculated. RESULTS Present-day male adolescents are taller, heavier and perform less well in static strength, flexibility and speed of limb movement than their fathers during their adolescence. No differences were found for BMI, explosive strength or power, muscular endurance, and running speed. Father-son correlations were rather high (above .40) for isometric strength, power, speed of limb movement and flexibility. Non-significant correlations were observed for running speed and muscular endurance. CONCLUSIONS Present-day male adolescents perform worse than their fathers during their adolescence, and relatively high father-son correlations were observed, indicating genetic and/or cultural transmission. Supported: The Flemish Policy Research Center Sport, Physical Activity and Health is supported by the Flemish Government.

Adolescent Correlates of Adult Physical Activity: A 26-year Follow-up

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. 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. 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. 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.

Relation between cardiovascular risk factors at adult age, and physical activity during youth and adulthood: the Leuven Longitudinal Study on Lifestyle, Fitness and Health.

This study investigated the relationship between sports participation/physical activity during youth (13 - 18 years of age) and adulthood (30 - 40 years of age), and cardiovascular risk factors (body fat and fat distribution, blood pressure, lipoprotein levels and cardiorespiratory fitness) at 40 years of age. Subjects were 166 Flemish males from "The Leuven Longitudinal Study on Lifestyle, Fitness and Health". Physical activity was assessed by means of a sports participation inventory and the Tecumseh community Health Study Questionnaire. In addition to correlation and multiple stepwise regression analyses, different groups (at risk, not at risk) were contrasted on sports participation/physical activity parameters using ANOVA. Long-term exposure during adulthood to daily physical activity was slightly related to a low/high risk profile for waist circumference, percent body fatness, triglycerides and peak VO(2). Sports participation during adolescence was not related to levels of cardiovascular risk factors at 40 years of age.

Prediction of cardiovascular disease risk factors later in life by physical activity and physical fitness in youth: general comments and conclusions.

This supplement has brought together six longitudinal observational studies investigating the relationship between physical activity and physical fitness (i. e., cardiopulmonary fitness) during youth and CVD risk factors later in life. In the Amsterdam Growth and Health Study [16], over a period of 20 years, eight repeated measurements were carried out. The study started at the age of 13 years and the last measurement was carried out at the age of 32 years. The total longitudinal cohort consisted of 212 males and 241 females. The Muscatine Study [6] describes a 5-year longitudinal project with annual measurements. The initial age of the 125 subjects was 10.5 years. In the Leuven Longitudinal Study on Lifestyle, Fitness and Health [7] a cohort of 166 Belgian boys was followed over a period of 27 years, in which nine repeated measurements were carried out. Like in the Amsterdam Growth and Health Study, the initial age of the children in the Leuven Longitudinal Study on Lifestyle, Fitness and Health was 13 years. The Northern Ireland Young Hearts Project [3] started with one cohort of 12-year old school children, and with one cohort of 15-year-old school children. The follow-up period of this longitudinal study was about 9 years and the total number of subjects available for analysis was 226 males and 193 females. In the Danish Youth and Sports Study [4] two measurements were carried out over a period of 8 years. Eighty-eight males and 117 females with an initial age between 15 and 19 years participated in this study. The Bogalusa Heart Study [12] concerns a biracial sample of children with initial ages between 5 and 14 years. The follow-up period of the 1169 subjects (64 % white, 36 % black, 50 % males and 50 % females) was around 15 years. Fig. [1] gives an overview of the six studies involved in this supplement.

Bone mass and lifetime physical activity in Flemish males: a 27-year follow-up study

The present population study is conducted to examine the extent to which lifetime physical activity and lifestyle parameters contribute to bone mass. The design of the project is a 27-yr prospective follow-up study. Subjects are 126 males gathered from the Leuven Longitudinal Study on Lifestyle, Physical Fitness and Health, and aged 13 yr at the onset of the study and 40 at the end of the follow-up. Physical activity and lifestyle parameters are obtained with questionnaires. Bone mass is measured by means of dual-energy x-ray absorptiometry (DXA). Results from correlation and regression analyses show that the body mass index (BMI) is the most important parameter in relation to cortical and trabecular bone mass at every examination period. Longitudinally, static arm strength, running speed, and upper muscular endurance contribute significantly to the prediction of adult bone mass. The parameter "change in motor fitness" between 18 and 13 yr old was used to control for hereditary influences. The score for static arm strength and trunk muscle strength demonstrates a significant correlation with adult total bone mineral content (BMC) and lumbar bone mineral density (BMD), respectively. At the age of 40, the Baecke sports index is almost equally important as BMI in explaining the variance in BMD, and static arm strength is the most important parameter (after BMI) for BMC. Lifetime physical activity, physical fitness, and BMI all contribute to adult bone mass. The clinical relevance of these findings is emphasized by the fact that the observed patterns of physical activity and motor fitness pertain to customary lifestyle and are thus feasible targets.

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.

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

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. A 5-y prospective follow-up study. 132 healthy men from The Leuven Longitudinal Study on Lifestyle, Physical Fitness, and Health. 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 40y. 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. 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. 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.

STABILITY IN PHYSICAL FITNESS. A STUDY ON BELGIAN MALES FOLLOWED LONGITUDINALLY FROM 12 TO 30 YEARS.

1732 The purposes of this study were (1) to establish the stability for individual differences in several physical fitness indicators, and (2) to present the quasisimplex strategy for the analysis of this problem. The sample comes from the Leuven Longitudinal Study on Lifestyle, Fitness and Health. For this study a sub-sample of 100 males was chosen, followed longitudinally and measured at mean ages of 12.7, 13.7, 14.6, 15.6, 16.7, 17.7 and 30 years. The physical fitness assessments included: arm pull, bent arm hang, plate tapping, sit and reach, shuttle run and vertical jump. In field reliability for these tests are ranged between 0.63<r<0.91. Data analysis for this multiwave panel design consists of auto-regressive quasi-simplex models as suggested by Joreskog & Sorbom (1970) and Maia et al. (1997). Calculations were performed independently for each indicator of physical fitness. Results are of three types: global fit measures (χ2, RMSEA, CFI), explained variance for structural equations (R2), stability estimates (β) which are functional dependencies of fitness indicators, say, from time 3 to time 2, and tracking coefficients (r) which are disattenuated auto-correlations. Global fit measures for each model of multiwave motor tests are within accepted bounds (χ2<31.69, p>0.04; RMSEA<0.11; CFI>0.95); explained variance of the structural equations for the dependency of fitness indicators of agej on agei is 0.40<R2<0.97; stability coefficients are high and statistically significant, 0.63<β<0.98, and tracking coefficients between the seven time points are within the range of 0.34<r<0.98. In conclusion: (1) auto regressive quasi-simplex models are well suited for the analysis of stability of physical fitness indicators; (2) models fit the data well with a variance accounted for by greater than 40%; (3) stability estimates of motor tests showed high values(β >0.63), and tracking coefficients for each indicator, exclusively from age 12.7 to age 30 are within the bounds of 0.34 to 0.64.

Development and Tracking in Fitness Components: Leuven Longitudinal Study on Lifestyle, Fitness and Health

In the Leuven Growth Study of Belgian Boys the growth and physical performance of Belgian boys followed longitudinally between 12 and 19 years were studied. Subsequently, a subsample (n = 240) of Flemish-speaking males were reexamined at 30 and 35 years. A first question relates to the individual growth patterns in a variety of physical fitness characteristics. The three strength tests (static, functional, explosive) show curves that are qualitatively similar to those for height and weight. Their adolescent spurts occur after the height spurt. Flexibility and the two speed tests appear to reach maximum velocities prior to the height and weight spurts. Longitudinal principal component analysis was applied to the study of growth patterns of several somatic and motor characteristics. The results for height show three components sufficient to provide an adequate representation of the original information. The first component characterizes the general position of an individual growth curve. Components 2 and 3 reflect fluctuation in percentile level during the age period studied and can be conceived as indices of stability and are related to age at peak height velocity (APHV) and peak height velocity (PHV), respectively. Relationships between somatic characteristics, physical performance, and APHV have been studied in a sample of 173 Flemish boys, measured yearly between +/- 13 and +/- 18 years and again as adults at 30 years of age. The sample was divided into three contrasting maturity categories based on the APHV. There are consistent differences among boys of contrasting maturity status during adolescence in body weight, skeletal lengths and breadths, circumferences, and skinfolds on the trunk. There are no differences in skinfolds on the extremities. None of the differences in somatic dimensions and ratios among the three contrasting maturity groups are significant at 30 years of age except those for subscapular skinfold and the trunk/extremity skinfold ratio. During adolescence, speed of limb movement, explosive strength and static strength are negatively related to APHV; thus, early maturers performed better than late maturers. However, between late adolescence and adulthood (30 years), the late maturers not only caught up to the early maturers, but there were significant differences for explosive strength and functional strength in favor of late maturers. Finally, age-specific tracking, using inter-age correlations, of adult health- and performance-related fitness scores were investigated. In addition, the independent contribution of adolescent physical characteristics to the explanation of adult fitness scores was also studied. Tracking between age 13 and age 30 years was moderately high (46% of variance explained) for flexibility, low to moderate (between 19% and 27% of variance explained) for the other fitness parameters and low for pulse recovery and static strength (7% to 11% of variance explained). Between age 18 and age 30 years the tracking was high for flexibility, moderately high for explosive and static strength, and moderate for the other fitness parameters except for pulse recovery. The amount of variance of adult fitness levels explained increased significantly when other characteristics observed during adolescence entered the regressions or discriminant functions.