Background Increasing physical activity (PA) levels in adolescents aged 12 to 18 years 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 and improving adherence to exercise programs. Objective The aim of this scoping review was to identify the efficacy or effectiveness of mHealth intervention strategies for facilitating PA among adolescents aged 12 to 18 years. Methods We conducted a systematic search for peer-reviewed studies published between 2008 and 2018 in the following electronic databases: PubMed, Google Scholar, PsychINFO, or SportDiscus. The search terms used included mHealth or “mobile health” or apps, “physical activity” or exercise, children or adolescents or teens or “young adults” or kids, and efficacy or effectiveness. Articles published outside of the date range (July 2008 to October 2018) and non-English articles were removed before abstract review. Three reviewers assessed all abstracts against the inclusion and exclusion criteria. Any uncertainties or differences in opinion were discussed as a group. The inclusion criteria were that the studies should (1) have an mHealth component, (2) target participants aged between 12 and 18 years, (3) have results on efficacy or effectiveness, and (4) assess PA-related outcomes. Reviews, abstracts only, protocols without results, and short message service text messaging–only interventions were excluded. We also extracted potentially relevant papers from reviews. At least 2 reviewers examined all full articles for fit with the criteria and extracted data for analysis. Data extracted from selected studies included study population, study type, components of PA intervention, and PA outcome results. Results Overall, 126 articles were initially identified. Reviewers pulled 18 additional articles from excluded review papers. Only 18 articles were passed onto full review, and 16 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. Overall, 5 mHealth intervention categories were identified: website, website+wearable, app, wearable+app, and website+wearable+app. The most common measures reported were subjective weekly PA (4/13) and objective daily moderate-to-vigorous PA (5/13) of the 19 different PA outcomes assessed. Furthermore, 5 of 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 5 studies, 3 permitted isolation of mHealth intervention components in the analysis. Conclusions PA outcomes for adolescents improved over time through mHealth intervention use; however, the lack of consi...

BackgroundOnly one in five American meets the physical activity recommendations of the Department of Health and Human Services. The proliferation of wearable devices and smartphones for physical activity tracking has led to an increasing number of interventions designed to facilitate regular physical activity, in particular to address the obesity epidemic, but also for cardiovascular disease patients, cancer survivors, and older adults. However, the inconsistent findings pertaining to the accuracy of wearable devices for step counting needs to be addressed, as well as factors known to affect gait (and thus potentially impact accuracy) such as age, body mass index (BMI), or leading arm.ObjectiveWe aim to assess the accuracy of recent mobile devices for counting steps, across three different age groups.MethodsWe recruited 60 participants in three age groups: 18-39 years, 40-64 years, and 65-84 years, who completed two separate 1000 step walks on a treadmill at a self-selected speed between 2 and 3 miles per hour. We tested two smartphones attached on each side of the waist, and five wrist-based devices worn on both wrists (2 devices on one wrist and 3 devices on the other), as well as the Actigraph wGT3X-BT, and swapped sides between each walk. All devices were swapped dominant-to-nondominant side and vice-versa between the two 1000 step walks. The number of steps was recorded with a tally counter. Age, sex, height, weight, and dominant hand were self-reported by each participant.ResultsAmong the 60 participants, 36 were female (60%) and 54 were right-handed (90%). Median age was 53 years (min=19, max=83), median BMI was 24.1 (min=18.4, max=39.6). There was no significant difference in left- and right-hand step counts by device. Our analyses show that the Fitbit Surge significantly undercounted steps across all age groups. Samsung Gear S2 significantly undercounted steps only for participants among the 40-64 year age group. Finally, the Nexus 6P significantly undercounted steps for the group ranging from 65-84 years.ConclusionsOur analysis shows that apart from the Fitbit Surge, most of the recent mobile devices we tested do not overcount or undercount steps in the 18-39-year-old age group, however some devices undercount steps in older age groups. This finding suggests that accuracy in step counting may be an issue with some popular wearable devices, and that age may be a factor in undercounting. These results are particularly important for clinical interventions using such devices and other activity trackers, in particular to balance energy requirements with energy expenditure in the context of a weight loss intervention program.

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.Nutrients 2020, 12, 167 2 of 18 childhood and adolescence, a shift in diet composition is observed to include higher rates of snack and soft drink consumption and lower intakes of fruits and vegetables [9]. Alongside increases in the prevalence of obesity [1,10], data from 1977 to 2014 show that snacking in adolescents has increased over the last four decades. It has also been shown that calories from salty snacks, desserts, sweets, and sugar-sweetened beverages continue to be a leading source of calories [11]. While fruit and vegetable intake has decreased, calories provided by these less healthy snacks has increased [12]. Thus, adverse eating behaviors resulting in excess calorie consumption, such as less healthy or frequent snacking, can potentially contribute to the rise of obesity during adolescence.SES is a strong determinant of an individual's weight, risk for obesity, and eating behaviors [13]. Individuals with lower SES are more likely to live in disordered and vulnerable neighborhood settings, which are associated with unhealthy food access and consumption [14]. Although rates of obesity have increased across all socioeconomic levels, adolescents who are from families with lower incomes are more likely than those from families with higher incomes to develop obesity [15]. SES, as defined by household income and/or parental education level for adolescents, has the potential to influence food choices [16]. Specifically, SES has been shown to have a strong influence on the consumption of certain food groups over others on a global scale [17][18][19][20], with those with lower SES positions te...

Objective This randomized trial experimentally manipulated social status to assess effects on acute eating behavior and 24‐hour energy balance. Methods Participants (n = 133 Hispanics; age 15‐21 years; 60.2% females) were randomized to low social status (“LOW”) or high social status (“HIGH”) conditions in a rigged game of Monopoly (Hasbro, Inc.). Acute energy intake in a lunchtime meal was measured by food scales. Twenty‐four‐hour energy balance was assessed via summation of resting metabolic rate (metabolic cart), physical activity energy expenditure (accelerometer), thermic effect of food, and subtraction of twenty‐four‐hour energy intake (food diary). Results In the total sample, no significant differences were observed by study condition at lunchtime. LOW females consumed a greater percent of lunchtime daily energy needs (37.5%) relative to HIGH females (34.3%); however, this difference was not statistically significant (P = 0.291). In males, however, LOW consumed significantly less (36.5%) of their daily energy needs relative to HIGH males (45.8%; P = 0.001). For 24‐hour energy balance, sex differences were nearly significant (P = 0.057; LOW females: surplus +200 kcal; HIGH males: surplus +445 kcal). Food‐insecure individuals consumed a nearly significant greater lunchtime percent daily energy than those with food security (40.7% vs. 36.3%; P = 0.0797). Conclusions The data demonstrate differential acute and 24‐hour eating behavior responses between Hispanic male and female adolescents in experimentally manipulated conditions of low social status.

Summary Background In adults, the Taq1a polymorphism (rs1800497) near the D2 receptor (DRD2) gene is associated with body mass index and binge eating and is more prevalent among non‐Hispanic Blacks (NHB) and Hispanic–Americans (HA) relative to non‐Hispanic Whites (NHW). We hypothesize Taq1a polymorphism (rs1800497) risk alleles contribute to paediatric racial/ethnic differences in obesity phenotypes. Objectives This study aims to characterize the relationship between the Taq1a polymorphism (rs1800497), diet and adiposity in a multi‐ethnic cohort of 286 children (98 NHB, 76 HA and 112 NHW), ages 7–12. Methods Dual‐energy X‐ray absorptiometry, computed tomography scans and two 24‐h dietary recalls assessed body composition, fat distribution and dietary intakes, respectively. Results Children with two Taq1a risk alleles (NHB = 50.0%, HA = 43.3%, NHW = 6.7%) reported a 20% increase in total energy intake (P = 0.0034) and per cent of calories from sugar consumed (P = 0.0077) than did children with less than two risk alleles. Children with two Taq1a risk alleles demonstrated significantly higher total body fat (P = 0.0145), body fat percentage (P = 0.0377), intra‐abdominal adiposity (P = 0.0459), subcutaneous abdominal adiposity (P = 0.0213) and total abdominal adiposity (P = 0.0209) than did children with one or no Taq1a risk alleles. Conclusions Our results suggest that having two Taq1a risk alleles is associated with an increase in reported calorie and sugar consumption and is a potential risk factor for early development of excess adiposity in multi‐ethnic children. These results need to be confirmed in a larger sample.