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ObjectivesThe aim of this study was to investigate the association between SARS-CoV-2 infection and muscle strain injury in elite athletes.MethodsA prospective cohort study in three Belgian professional male football teams was performed during the first half of the 2020–2021 season (June 2020–January 2021). Injury data were collected using established surveillance methods. Assessment of SARS-CoV-2 infection was performed by a PCR test before each official game.ResultsOf the 84 included participants, 22 were infected with SARS-CoV-2 and 14 players developed a muscle strain during the follow-up period. Cox’s proportional hazards regression analyses demonstrated a significant association between SARS-CoV-2 infection and the development of muscle strain (HR 5.1; 95% CI 1.1 to 23.1; p=0.037), indicating an increased risk of developing muscle strains following SARS-CoV-2 infection. All athletes who sustained a muscle strain after infection were injured within the first month (15.71±11.74 days) after sports resumption and completed a longer time in quarantine (14.57±6.50 days) compared with the infected players who did not develop a muscle strain (11.18±5.25 days).ConclusionThis study reported a five times higher risk of developing a muscle strain after a SARS-CoV-2 infection in elite male football players. Although this association should be examined further, it is possible that short-term detraining effects due to quarantine, and potentially pathological effects of the SARS-CoV-2 infection are associated with a higher risk of muscle strain injury.

A study was conducted to investigate the association of muscular strength and aerobic fitness with a continuous metabolic syndrome risk score in male and female adults. The results show that muscular strength and aerobic fitness are independently and inversely associated with metabolic syndrome risk in women aged 18-75 and support the inclusion of strength training in physical activity recommendations in addition to aerobic exercise.

Adolescent physical activity, fitness, anthropometric dimensions, fatness, biological maturity, and family characteristics contribute to the variation in physical activity at 40 years of age, is hypothesized. 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.

This study was designed to validate a continuous metabolic syndrome risk score (cMSy) using the International Diabetes Federation risk factors (1). Increasing evidence supports using a cMSy instead of a [...]

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. © 2001 Wiley‐Liss, Inc.

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. © 2000 Wiley‐Liss, Inc.

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. © 1999 Wiley-Liss, Inc.