Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Increasing physical activity (PA) levels in adolescents ages 12-18 is associated with prevention of unhealthy weight gain and improvement in cardiovascular fitness. The widespread availability of mobile health (mHealth) and wearable devices offers self-monitoring and motivational features for increasing PA levels as well as improving adherence to exercise programs. Objective: The aim of this scoping review is to identify the efficacy or effectiveness of mHealth intervention strategies for facilitating PA among adolescents. Methods: We conducted a systematic search for peer-reviewed studies published between 2008 and 2017 in the following electronic databases: PubMed, Google Scholar, PsychINFO, or SportDiscus. The search terms used include (mHealth OR “mobile health” OR apps) AND (“physical activity” OR exercise) AND (children OR adolescents OR teens OR “young adults” OR kids) AND (efficacy OR effectiveness). Articles published outside of the date range (07/10/2008 – 09/01/2017) and non-English articles were removed pre-abstract review. Three reviewers assessed all abstracts against the inclusion and exclusion criteria. Any uncertainty or differences in opinion were discussed as a group. If the disagreement was still unresolved, the abstract was included in the full article review. The inclusion criteria were that the studies shall 1) have a mHealth component, 2) target participants between 12 and 18 years old, 3) have results on efficacy or effectiveness, and 4) assess PA-related outcomes. Reviews, abstracts only, protocols without results, SMS-only interventions were excluded. We also extracted potentially relevant papers from reviews. At least two reviewers examined all full articles for fit with criteria and extracted data for analysis. Data extracted from selected studies included study population, study type, components of PA intervention, and PA outcomes results. Results: 95 articles were initially identified and reviewers pulled 18 additional articles from excluded review papers. Only 15 articles were passed onto full review and 13 were kept for analysis. The included studies differed in the sizes of the study populations (11- 607 participants), locations of the study sites (7 countries), study setting, and study design. The most common measures reported were subjective weekly PA (4/13) and objective daily moderate-to-vigorous physical activity (MVPA, 4/13) of the 19 different PA outcomes assessed. Only 6/13 studies with a control or comparison group showed a significant improvement in PA outcomes between the intervention group and the control or comparison group. Of those 6, 4 permitted isolation of mHealth intervention components in the analysis. Conclusions: Our findings indicate that PA outcomes for adolescents improved over time through mHealth interventions use; however, the lack of consistency in chosen PA outcome measures, paucity of significant outcomes via between group analyses, and the weak study designs that prevent separating the effects of intervention components calls into question their true effect.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Eating behaviors, including unhealthy snacking or excessive snacking leading to excess calorie consumption, may contribute to obesity among adolescents. Socioeconomic status (SES) also significantly influences eating behaviors, and low SES is associated with increased risk for obesity. However, little is known regarding the relationship between snacking behavior and SES among adolescents and how this may contribute to obesity-related outcomes. The primary objective of this scoping review was to review the literature to assess and characterize the relationship between SES and snacking in adolescents. The secondary objective was to assess weight-related outcomes and their relation to snacking habits. Included articles were published between January 2000 and May 2019; written in English, Portuguese, or Spanish; and focused on adolescents (13–17 years). In total, 14 bibliographic databases were searched, and seven studies met the inclusion criteria. Preliminary evidence from the seven included studies suggests a weak but potential link between SES and snacking. Additionally, these dietary patterns seemed to differ by sex and income type of country. Finally, only three of the included studies addressed weight-related outcomes, but the overall available evidence suggests that snacking does not significantly affect weight-related outcomes. Due to the small number of included studies, results should be interpreted with caution.

Background: Physical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data. Methods: Using existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures. Results: Two relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures. Conclusions: Improved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual’s home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community.

Low social status (SS) is a determinant of poor health status and is associated with increased disease burden. Obesity affects 20.6% of American adolescents, most of whom are from low-SS families. Contributors to the development of obesity among adolescents include sedentary behavior and low levels of physical activity. Environmental determinants—infrastructure, policy, and social relationships—influence engagement in physical activity and are affected by SS. Significant declines in physical activity have been documented during adolescence, and adolescents of low SS engage in significantly less physical activity per week than those with high SS. This article briefly reviews the literature on the relationship between SS and physical activity in adolescents and introduces a proposed biological mechanism that may explain that relationship. Characterizing the effects that SS can have on physical activity may help tailor clinical interventions and public health campaigns seeking to improve adolescent physical activity and weight management, thus increasing their effectiveness. This may be particularly beneficial for underserved populations.