BackgroundMotor performance is an important factor for health. Already in childhood, motor performance is associated with, e.g., obesity and risk factors for cardiovascular diseases. It is widely believed that the motor performance of children has declined over recent years. However, this belief is lacking clear evidence. The objective of this study was to examine trends in motor performance of first grade students during a period of 10 years (2006–2015). We examined trends in (a) aerobic fitness, (b) strength, (c) speed, and (d) balance for boys and girls separately and considered body mass index (BMI) as a potential confounder.MethodsFrom 2006 to 2015, we tested 5,001 first graders [50.8% boys; mean age 6.76 (0.56) years] of 18 primary schools in Germany. Each year between 441 and 552 students of the same schools were surveyed. Performance tests were taken from the Motorik-Module Study and the “German Motor Ability Test”: “6-min run,” “push-ups,” “20-m sprint,” and “static stand.” Linear regression models were conducted for statistical analysis.ResultsA slightly negative trend in aerobic fitness performance was revealed in boys (β = −0.050; p = 0.012) but not in girls. In the strength performance test no trend over time was detected. Performance in speed (boys: β = −0.094; girls: β = −0.143; p ≤ 0.001) and balance tests (boys: β = −0.142; girls: β = −0.232; p ≤ 0.001) increased over time for both boys and girls. These findings held true when BMI was considered.ConclusionThis study only partly supported the assumption that motor performance of children has declined: in our study, aerobic fitness declined (only in boys), while strength remained stable and speed and balance even increased in both sexes. Moreover, it seems as if BMI can explain changes in performance only to a small extent. Changed lifestyles might be a substantial cause. Further research on recent trends of motor performance and interacting variables is needed to support the results of our study and to provide more knowledge on causes of these trends.

Background: Health behaviors are of great importance for public health. Previous research shows that health behaviors are clustered and do not occur by chance. The main objective of this study was to investigate and describe the clustering of alcohol consumption, nutrition, physical activity and smoking while also considering the influence of sex, age and education.Methods: Using data from the population-based KORA S4/F4 cohort study, latent class regression analysis was undertaken to identify different clusters of health behavior patterns. The clusters were described according to demographics. Furthermore, the clusters were described regarding health-related quality of life at baseline and at a 7 year follow-up.Results: Based on a sample of 4,238 participants, three distinct classes were identified. One overall healthy class and two heterogeneous classes. Classes varied especially according to sex, indicating a healthier behavior pattern for females. No clear association between healthier classes and age, education or physical and mental health-related quality of life was found.Discussion: This study strengthens the literature on the clustering of health behaviors and additionally describes the identified clusters in association with health-related quality of life. More research on associations between clustering of health behaviors and important clinical outcomes is needed.

IntroductionLongitudinal evidence on the association between physical activity (PA) or weight and health-related quality of life (HRQL) is sparse and studies describe inconclusive results. The aim of this study was to examine longitudinal associations between change in PA and HRQL as between change in weight and HRQL respectively.MethodsAnalyses are based on data from the KORA S4 cohort study (1999–2001; n = 4,261, mean age 49.0 ± 13.3 years) and the two follow-up examinations (F4: 2006–2008; FF4: 2013–2014). Information on PA was collected in standardized interviews. Weight was measured objectively. Mental and physical components of HRQL were assessed via the SF-12 questionnaire. First, change in HRQL was regressed on change in PA and weight. Second, hierarchical linear models were fitted, which allowed estimation of between-subject and within-subject effects. Analyses were adjusted for the covariates sex, baseline diseases, and education.ResultsA change to a physically more active lifestyle is positively associated with physical and mental HRQL. Although weight gain is associated with impairments in physical HRQL, the data show an inverse relationship between weight gain and mental HRQL. The results were consistent for both the change score analyses and the hierarchical linear models.DiscussionOur findings stress the importance of interventions on PA/weight. Nonetheless, more research is needed to reveal the causal relationship between PA/weight and HRQL.