A sedentary lifestyle and especially poor cardiorespiratory fitness are not only associated with the MS but could also be considered features of the MS. Measurement of VO(2max) in sedentary men with risk factors may provide an efficient means for targeting individuals who would benefit from interventions to prevent the MS and its consequences.

Background and aimsDespite many positive benefits, mobile phone use can be associated with harmful and detrimental behaviors. The aim of this study was twofold: to examine (a) cross-cultural patterns of perceived dependence on mobile phones in ten European countries, first, grouped in four different regions (North: Finland and UK; South: Spain and Italy; East: Hungary and Poland; West: France, Belgium, Germany, and Switzerland), and second by country, and (b) how socio-demographics, geographic differences, mobile phone usage patterns, and associated activities predicted this perceived dependence.MethodsA sample of 2,775 young adults (aged 18–29 years) were recruited in different European Universities who participated in an online survey. Measures included socio-demographic variables, patterns of mobile phone use, and the dependence subscale of a short version of the Problematic Mobile Phone Use Questionnaire (PMPUQ; Billieux, Van der Linden, & Rochat, 2008).ResultsThe young adults from the Northern and Southern regions reported the heaviest use of mobile phones, whereas perceived dependence was less prevalent in the Eastern region. However, the proportion of highly dependent mobile phone users was more elevated in Belgium, UK, and France. Regression analysis identified several risk factors for increased scores on the PMPUQ dependence subscale, namely using mobile phones daily, being female, engaging in social networking, playing video games, shopping and viewing TV shows through the Internet, chatting and messaging, and using mobile phones for downloading-related activities.Discussion and conclusionsSelf-reported dependence on mobile phone use is influenced by frequency and specific application usage.

Background and AimsThe aim of this study was to identify problematic gaming behavior among Finnish adolescents and young adults, and evaluate its connection to a variety of psychological, social, and physical health symptoms.MethodsThis cross-sectional study was conducted with a random sample of 293 respondents aged from 13 to 24 years. Participants completed an online survey. Problematic gaming behavior was measured with the Game Addiction Scale (GAS). Self-reports covered health measures such as psychological health (psychopathological symptoms, satisfaction with life), social health (preferences for social interaction), and physical health (general health, Body Mass Index [BMI], body discomfort, physical activity).ResultsProblematic gaming behavior was found to relate to psychological and health problems, namely fatigue, sleep interference, depression and anxiety symptoms. Multiple linear regression indicated that the amount of weekly gaming, depression and a preference for online social interaction predicted increased problematic gaming symptoms.ConclusionsThis research emphasized that problematic gaming behavior had a strong negative correlation to a variety of subjective health outcomes.

This systematic review and meta-analysis aimed to investigate the interplay between problematic gaming behaviour and health-related outcomes at different developmental stages. A total of 50 empirical studies met the specified inclusion criteria, and a meta-analysis using correlation coefficients was used for the studies that reported adverse health implications regarding the impact of problematic gaming behaviour on depression, anxiety, obsessive-compulsive disorder and somatisation. Overall, the results suggested that problematic gaming behaviour is significantly associated with a wide range of detrimental health-related outcomes. Finally, the limitations of this review alongside its implications were discussed and considered for future research.

Background and aimsGaming applications have become one of the main entertainment features on smartphones, and this could be potentially problematic in terms of dangerous, prohibited, and dependent use among a minority of individuals. A cross-national study was conducted in Belgium and Finland. The aim was to examine the relationship between gaming on smartphones and self-perceived problematic smartphone use via an online survey to ascertain potential predictors.MethodsThe Short Version of the Problematic Mobile Phone Use Questionnaire (PMPUQ-SV) was administered to a sample comprising 899 participants (30% male; age range: 18–67 years).ResultsGood validity and adequate reliability were confirmed regarding the PMPUQ-SV, especially the dependence subscale, but low prevalence rates were reported in both countries using the scale. Regression analysis showed that downloading, using Facebook, and being stressed contributed to problematic smartphone use. Anxiety emerged as predictor for dependence. Mobile games were used by one-third of the respective populations, but their use did not predict problematic smartphone use. Very few cross-cultural differences were found in relation to gaming through smartphones.ConclusionFindings suggest mobile gaming does not appear to be problematic in Belgium and Finland.

Authors' contributions: OL-F (principal investigator) wrote the first draft, with CD and LJ, who supported the statistical analysis and initial interpretation of the data. JB, DJK, HMP, MDG and OL-F supported the review of the second draft. JB, AS, MDG, and OL-F also supported the review of the third draft. All authors reviewed the manuscript adding comments and suggestions and oversaw the second and third drafts. All co-authors contributed to adapting the short version of the CIUS into their 3 languages, collecting data in their respective countries, and revising the subsequent versions until the final write-up of the manuscript.

The prevalence of mobile phone use across the world has increased greatly over the past two decades. Problematic Mobile Phone Use (PMPU) has been studied in relation to public health and comprises various behaviours, including dangerous, prohibited, and dependent use. These types of problematic mobile phone behaviours are typically assessed with the short version of the Problematic Mobile Phone Use Questionnaire (PMPUQ–SV). However, to date, no study has ever examined the degree to which the PMPU scale assesses the same construct across different languages. The aims of the present study were to (i) determine an optimal factor structure for the PMPUQ–SV among university populations using eight versions of the scale (i.e., French, German, Hungarian, English, Finnish, Italian, Polish, and Spanish); and (ii) simultaneously examine the measurement invariance (MI) of the PMPUQ–SV across all languages. The whole study sample comprised 3038 participants. Descriptive statistics, correlations, and Cronbach’s alpha coefficients were extracted from the demographic and PMPUQ-SV items. Individual and multigroup confirmatory factor analyses alongside MI analyses were conducted. Results showed a similar pattern of PMPU across the translated scales. A three-factor model of the PMPUQ-SV fitted the data well and presented with good psychometric properties. Six languages were validated independently, and five were compared via measurement invariance for future cross-cultural comparisons. The present paper contributes to the assessment of problematic mobile phone use because it is the first study to provide a cross-cultural psychometric analysis of the PMPUQ-SV.

Aims To identify clusters of health behaviours among Finnish adolescents and examine whether these clusters are associated with body mass index (BMI). Methods The data, drawn from the prospective population‐based Northern Finland Birth Cohort 1986, comprised a total of 7182 adolescents who replied to a follow‐up postal questionnaire at the age 15 to 16. The adolescents were asked about multiple health behaviours, such as physical activity, screen time, cigarette smoking, alcohol use and diet. Adolescents who answered the questions concerning all of these variables were included in the study, yielding a final sample of 4305 subjects. K‐means cluster analysis was performed to identify group of adolescents with similar health behaviours. Chi‐squared tests were performed to analyse the association between the clusters and BMI. Results Two clusters – Healthy Lifestyle and Unhealthy Lifestyle – were identified for both genders. The values of all the studied variables differed significantly between the clusters identified for both boys and girls. No significant relationship between the identified clusters and BMI was found for either boys or girls. Conclusions It is important to consider multiple lifestyle‐related behaviours and trying to identify groups that present probability for developing lifestyle diseases.