The treatment of noncommunicable diseases (NCD), like coronary heart disease or type 2 diabetes mellitus, causes rising costs for the health system. Physical activity is supposed to reduce the risk for these diseases. Results of cross-sectional studies showed that physical activity is associated with better health, and that physical activity could prevent the development of these diseases. The purpose of this review is to summarize existing evidence for the long-term (>5 years) relationship between physical activity and weight gain, obesity, coronary heart disease, type 2 diabetes mellitus, Alzheimer’s disease and dementia.

Not only in adults but also in children and adolescents, obesity increases the risk for several health disorders. In turn, many factors including genetic variations and environmental influences (e.g. physical activity) increase the risk of obesity. For instance, 25 to 40 percent of people inherit a predisposition for a high body mass index (BMI). The purpose of this systematic review was to summarize current cross-sectional and longitudinal studies on physical activity, fitness and overweight in adolescents and to identify mediator and moderator effects by evaluating the interaction between these three parameters.

Higher education students often suffer from physiological and psychological health problems caused by stress, which may negatively impact their academic performance (AP). Physical activity (PA) can be a promising strategy to buffer these stress-induced complaints. Therefore, the aim of this investigation was to summarize evidence for the tridimensional construct of PA, stress, and AP, as well as to quantify the relationships among these variables. Five databases (PubMed, Scopus, SMEI, ERIC, and Web of Science) were systematically searched in November 2019 for publications that examined PA, stress, and AP of university students, without any restrictions regarding the publication period. The systematic review includes four original research studies with a moderate-to-high risk of bias. Results of included studies were narratively summarized and quantified in a meta-analysis using random effect models. Whereas study results point to a positive relation between PA and AP, relationships between PA and stress seem to be negative, while the relation between stress and AP is undecided. The meta-analysis found no significant associations and considerable heterogeneity of the results. Findings indicate a research gap concerning the connection of PA, stress, and AP in university students. Future studies should use validated measuring tools and consider the timepoint of data collection in order to extract truly stressful periods.

Background: Children and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions. Objective: This review and meta-analysis investigated the effectiveness of mHealth interventions on IPA and SB, with a special focus on the age and level of individualization. Methods: PubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library were searched for randomized controlled trials published between January 2000 and March 2021. mHealth interventions for primary prevention in children and adolescents addressing behavior change related to IPA and SB were included. Included studies were compared for content characteristics and methodological quality and summarized narratively. In addition, a meta-analysis with a subsequent exploratory meta-regression examining the moderating effects of age and individualization on overall effectiveness was performed. Results: On the basis of the inclusion criteria, 1.3% (11/828) of the preliminary identified studies were included in the qualitative synthesis, and 1.2% (10/828) were included in the meta-analysis. Trials included a total of 1515 participants (mean age (11.69, SD 0.788 years; 65% male and 35% female) self-reported (3/11, 27%) or device-measured (8/11, 73%) health data on the duration of SB and IPA for an average of 9.3 (SD 5.6) weeks. Studies with high levels of individualization significantly decreased insufficient PA levels (Cohen d=0.33; 95% CI 0.08-0.58; Z=2.55; P=.01), whereas those with low levels of individualization (Cohen d=−0.06; 95% CI −0.32 to 0.20; Z=0.48; P=.63) or targeting SB (Cohen d=−0.11; 95% CI −0.01 to 0.23; Z=1.73; P=.08) indicated no overall significant effect. The heterogeneity of the studies was moderate to low, and significant subgroup differences were found between trials with high and low levels of individualization (χ21=4.0; P=.04; I2=75.2%). Age as a moderator variable showed a small effect; however, the results were not significant, which might have been because of being underpowered. Conclusions: Evidence suggests that mHealth interventions for children and adolescents can foster moderate reductions in IPA but not SB. Moreover, individualized mHealth interventions to reduce IPA seem to be more effective for adolescents than for children. Although, to date, only a few mHealth studies have addressed inactive and sedentary young people, and their quality of evidence is moderate, these findings indicate the relevance of individualization on the one hand and the difficulties in reducing SB using mHealth interventions on the other. Trial Registration: PROSPERO CRD42020209417; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=209417

Reduced physical activity (PA) and prolonged screen time (ST) negatively influence health-related quality of life (HRQoL), a protective factor against illness and mortality. Studies addressing the relationship between PA, ST, and mental health in youth are scarce, especially in times with high mental health burdens like the COVID-19 pandemic. The purpose of this examination was to investigate whether PA, ST, and HRQoL before COVID-19 predict PA, ST, and HRQoL during the COVID-19 pandemic. Participants from the Motorik-Modul Study (MoMo; N = 1711; M_age = 10.36 (SD = 4.04) years, female = 49.8%; healthy weight = 76.8%) self-reported their PA and ST as well as HRQoL both before and during COVID-19. Relationships of all variables, from before to during COVID-19, were investigated through a path prediction model. Results showed all variables during COVID-19 were predicted by the respective levels before COVID-19, independent of gender and age. Cross-lags revealed a negative influence of before COVID-19 ST on during COVID-19 PA. HRQoL before COVID-19 was positively associated with during COVID-19 PA in children younger than 10 years and females, but not in adolescents and boys. As age- and gender-independent negative influence of before COVID-19 ST on during COVID-19 PA has been detected, health policy may be advised to focus on a general reduction in ST instead of PA enhancement to ensure high PA levels.

Objective: The purposes of this paper were to (a) develop a new short, theory-driven, version of the physical activity enjoyment scale (PACES-S) using content analysis; and (b) subsequently to measure the psychometric properties (construct validity, internal consistency, test–retest reliability, and concurrent validity) of the PACES-S for adolescents. Methods: Six experts used a four-point Likert scale to assess the content validity of each of the 16 items of the physical activity enjoyment scale according to a provided definition of physical activity enjoyment. Based on the results, exploratory factor analysis was used to analyze survey data from a longitudinal study of 182 individuals (Measure 1 of Study 1: 15.75 ± 3.39 yrs; 56.6% boys, 43.4% girls), and confirmatory factor analysis (Measure 2 of Study 1: 15.69 ± 3.44 yrs; 56.3% boys, 43.7% girls) was used to analyze the survey data from a cross-sectional study of 3219 individuals (Study 2; 15.99 ± 3.10 yrs; 47.8% boys, 52.2% girls) to assess the construct validity of the new measure. To assess the reliability, test–retest reliability was assessed in Study 1 and internal consistency in Study 1 and 2. For the concurrent validity, correlations with self-reported and device-based physical activity behavior were assessed in both studies. Results: Four out of sixteen items were selected for PACES-S. Exploratory factor analysis and confirmatory factor analyses identified and supported its factorial validity (χ² = 53.62, df = 2, p < 0.001; RMSEA = 0.073; CFI = 0.99; RFI = 0.96; NFI = 0.99; TLI = 0.96; IFI = 0.99). Results showed good test–retest reliability (r = 0.76) and internal consistency (a = 0.82 to 0.88). Regarding concurrent validity, the results showed positive correlations with a physical activity questionnaire (Study 1: r = 0.36), with a physical activity diary (Study 1: r = 0.44), and with accelerometer-recorded data (Study 1: r = 0.32; Study 2: r = 0.21). Conclusions: The results indicate that PACES-S is a reliable and valid instrument that may be particularly useful to measure physical activity enjoyment in large-scale studies. It shows comparable measurement properties as the long version of PACES.