Efficacy of Individual Nutrition Counseling on Resting Energy Expenditure, Oxygen Consumption, Fat-Free Mass and Percentage Fat of Body Weight

This article was originally published by Undergraduate Research Journal for the Human SciencesThere is agreement that optimizing intake of calories, protein, and carbohydrates to fuel muscle will enable athletes to train harder, but translating nutrition knowledge into nutrition behavior is problematic. The efficacy of individual nutrition counseling (INC) on nutrition behavior using objective measurements in competitive athletes has not been investigated. We therefore evaluated the influence of INC on the objective outcomes: oxygen consumption (VO2) at rest, resting energy expenditure (REE) measured by indirect calorimetry, fat-free mass (FFM), and percentage fat of body weight (PF) measured by tetra-polar bioelectrical impedance in varsity cross-country athletes at three-time points of pre-during-& post-season

Reciprocal associations between screen time and emotional disorder symptoms during adolescence

Screen-based sedentary behaviors and emotional disorders are associated with one another in youth. Yet, the direction of the association is unclear, as is whether specific types of screen-based sedentary behaviors and emotional disorder symptoms are more closely linked. This study estimated the bi-directional associations between two types of screen-based sedentary behaviors and four types of self-reported emotional disorder symptoms, and tested whether physical activity buffered these associations in a Los Angeles high school student cohort (N = 2525, baseline Mage = 14.6 years). Participants completed baseline (9th Grade, 2013) and 12-month follow-up (10th grade, 2014) surveys reporting on: television viewing and computer/videogame use (≥4 h/day; yes/no), physical activity (≥60 min/day for ≥5 days/week), and Major Depressive Disorder (MDD), Generalized Anxiety Disorder (GAD), Panic Disorder (PD), and Social Phobia (SP) symptoms (meet/exceed [sub]clinical symptom threshold; yes/no). After adjusting for baseline screen-based sedentary behavior and covariates, students with (sub)clinical baseline MDD and GAD were at increased odds of high computer/videogame use one year later (OR = 1.36[95%CI, 1.07–1.73]; OR = 1.36[95%CI,1.09–1.71], respectively). Baseline SP was marginally related to increased computer/videogame use at follow-up (OR = 1.33[95%CI,1.04–1.69]). Greater baseline computer/videogame use was associated with increased odds of (sub)clinical GAD (OR = 1.54[95%CI,1.23–1.94]) and (sub)clinical SP (OR = 1.64[95%CI 1.27–2.12]) at follow-up; these associations were suppressed among baseline physically active students. Television viewing was unrelated to emotional disorder symptoms and PD was not associated with screen-based sedentary behaviors. Thus, only reciprocal associations between computer/videogame use, SP, and GAD during a one-year period of adolescence were observed. Interventions reducing computer/videogame use and increasing physical activity may improve adolescent emotional health. Keywords: Sedentary behavior, Anxiety, Depression, Yout

Sleep and mood in older adults: coinciding changes in insomnia and depression symptoms

The aim of this analysis was to test if changes in insomnia symptoms and global sleep quality are associated with coinciding changes in depressed mood among older adults. We report on results yielded from secondary analysis of longitudinal data from a clinical trial of older adults (N = 49) aged 55 to 80 years who reported at least moderate levels of sleep problems. All measures were collected at baseline and after the trial ten weeks later. We computed change scores for two separate measures of disturbed sleep, the Athens Insomnia Scale (AIS) and the Pittsburgh Sleep Quality Index (PSQI), and tested their association with change in depressed mood (Beck Depression Inventory-II; BDI-II) in two separate linear regression models adjusted for biological covariates related to sleep (sex, age, body mass index, and NF-κB as a biological marker previously correlated with insomnia and depression). Change in AIS scores was associated with change in BDI-II scores (β = 0.38, p < 0.01). Change in PSQI scores was not significantly associated with change in BDI-II scores (β = 0.17, p = 0.26). Our findings suggest that improvements over ten weeks in insomnia symptoms rather than global sleep quality coincide with improvement in depressed mood among older adults

Sleep and mood in older adults: coinciding changes in insomnia and depression symptoms

The aim of this analysis was to test if changes in insomnia symptoms and global sleep quality are associated with coinciding changes in depressed mood among older adults. We report on results yielded from secondary analysis of longitudinal data from a clinical trial of older adults (N = 49) aged 55 to 80 years who reported at least moderate levels of sleep problems. All measures were collected at baseline and after the trial ten weeks later. We computed change scores for two separate measures of disturbed sleep, the Athens Insomnia Scale (AIS) and the Pittsburgh Sleep Quality Index (PSQI), and tested their association with change in depressed mood (Beck Depression Inventory-II; BDI-II) in two separate linear regression models adjusted for biological covariates related to sleep (sex, age, body mass index, and NF-κB as a biological marker previously correlated with insomnia and depression). Change in AIS scores was associated with change in BDI-II scores (β = 0.38, p < 0.01). Change in PSQI scores was not significantly associated with change in BDI-II scores (β = 0.17, p = 0.26). Our findings suggest that improvements over ten weeks in insomnia symptoms rather than global sleep quality coincide with improvement in depressed mood among older adults

Accessing Vaping Products When Underage: A Qualitative Study of Young Adults in Southern California

IntroductionCalifornia implemented multiple strategies, such as a Tobacco 21 law and compliance checks, to reduce high rates of youth e-cigarette use. However, the prevalence of use among underage youth and young adults continues rising. Little is known about how underage individuals obtain e-cigarettes.Aims and methodsWe conducted structured qualitative interviews with 61 young adult (18-25 years old) vapers in the Los Angeles, CA area between June 2018 and June 2019. Interviews were comprehensive and designed to elicit information on participants' thoughts, feelings, and experiences related to vaping. We queried participants on where and how they obtained vaping products, and participants discussed their experiences accessing products while under the legal age for sale. Directed content analysis was used to analyze interviews.ResultsFour concepts emerged: (1) early experimentation of e-cigarettes with peers often occurred in a school setting, (2) continued use of e-cigarettes commonly obtained through peer sales, (3) inconsistent implementation of age restrictions at in-person retailers, and (4) at online retailers. Participants had peers purchase products on their behalf and frequented in-person and online retailers with few to no age verification processes. Few participants faced challenges when purchasing products from retailers.ConclusionsThe current study's findings offer insight into where and how underage individuals obtain vaping products despite restrictions to prevent them from doing so. Participant accounts of mixed ease of underage purchasing in-person and online suggest retailer education is needed, along with additional research to inform more effective policies to reduce underage access to vaping products.ImplicationsDespite legal age restrictions, e-cigarettes remain accessible to underage individuals, but specific strategies that underage youth utilize to evade legal age restrictions are largely unknown. We found that participants often accessed vaping products for the first time at school. Sales between peers were common, and participants also reported frequenting in-person retailers that inconsistently enforced age restrictions. Many participants reported little to no age verification online, though some believed online age verification measures were increasingly difficult to surpass. Knowledge of strategies underage youth utilize to access e-cigarettes can inform enforcement efforts

Trajectories of Nicotine Use Leading to Dual and Cyclical Tobacco Product Use in Young Adults.

IntroductionYoung adult never-smokers who vape are at elevated risk of initiating cigarettes, while young adults who smoke often begin vaping to substitute or reduce cigarette use. Reasons underlying different use patterns of tobacco products are not well-understood.Aims and methodsWe conducted 1-on-1 qualitative interviews with young adults (N = 62) who vape in Los Angeles, California from June 2018 to June 2019. Participants were 18-25 years old (79% male; racially/ethnically diverse) and self-reported vaping ≥1x/week. We used a semi-structured interview guide and applied thematic analysis method to analyze data.ResultsYoung adults initiated vaping due to peer socialization and e-liquid flavor novelty. They often reported vaping (after first smoking) due to a belief that e-cigarettes are healthier, social pressure to quit smoking, and convenience of use. Participants reported smoking (after first vaping) when traveling outside of the United States where vaping products were less accessible, and cigarettes were normative. Many of the personal narratives described patterns of dual and cyclical use, which was often attributed to nicotine dependence and cost, or described as dependent upon the current environment (eg, at a party).ConclusionsThe current study characterizes nicotine use trajectories and reasons why young adults vape, and smoke cigarettes. Dual and cyclical use of both e-cigarettes and cigarettes was common; this pattern of use should be considered in policy and prevention work to address nicotine dependence among young people.ImplicationsWe display findings from the current study in a model depicting common trajectories of nicotine use, along with reasons for initiation, transitions between products, and dual/cyclical e-cigarette and combustible cigarette use

Characterizing symptoms of e-cigarette dependence: a qualitative study of young adults

BackgroundWhile rates of e-cigarette use ('vaping') continue to potentiate concern, there is limited data on common symptoms of e-cigarette dependence among young adults who vape. This study sought to critically explore how young adults experience, manifest, and conceptualize vaping dependence symptoms in their everyday lives.MethodsBetween June 2018 and 2019, in-depth qualitative interviews were conducted with 62 young adults who use e-cigarettes (aged 18-25) and live in Southern California. We explored participants' product preferences, daily e-cigarette use patterns, vaping history, withdrawal experiences, and quit attempts or periods of cessation. We used a thematic analysis approach to interpret the transcripts.ResultsYoung adults discussed nine dimensions of vaping dependence that were organized into two categories: 1) general nicotine dependence symptoms, and 2) unique dependence symptoms related to vaping. Nicotine dependence symptoms included cravings and urgency to use, increased use to achieve desired effects, and unsuccessful quit attempts and withdrawal. Symptoms unique to vaping dependence included greater nicotine consumption due to accessibility and lack of restrictions, habitual vaping, inability to track vaping frequency, immediate gratification and comfort, social acceptability and norms, and awareness of vaping dependency.ConclusionsIn addition to nicotine dependence symptoms that have been characterized for other tobacco products, young adult e-cigarette users described unique symptoms of vaping dependence that necessitate the need for more refined measures. All dimensions of vaping dependence should be considered in discussions of policies as well as treatment and education efforts intended to protect young people from e-cigarette dependence

Critical Challenges and Creative Solutions for Quantifying Nicotine Vaping: Qualitative Reports From Young Adults.

IntroductionPrevious studies suggest that young adults who vape nicotine experience difficulty when answering survey items assessing the quantity of vaping. The current study asked young adults who vape to provide suggestions for improving the scientific measurement of vaping.Aims and methodsWe conducted semi-structured qualitative interviews with 62 young adults who vape in Los Angeles, California between June 2018 and June 2019. We analyzed participants' responses to the following question: "What do you think is the best way for us to understand how much people vape?" using thematic content analysis.ResultsWe identified two major themes: (1) challenges stemming from differences between the way researchers query about vaping and how individuals self-monitor vaping frequency, and (2) insights for future measurement of vaping. Participants reported that challenges of accurately quantifying vaping were due to inherently hard-to-answer questions (eg, puffs per day), lack of awareness of or not actively monitoring consumption of vaping products, or because vaping behaviors vary considerably between and within individuals over time, making "on-average" questions challenging. Participants discussed ideas for improving survey measures that could accurately assess vaping quantity, including querying about the type of device used, and frequency of replenishment of nicotine solutions.ConclusionsExisting vaping behavior survey measures may not accurately capture the quantity of vaping as they differ from how (or if) participants track their own vaping consumption patterns. While continued research is needed to optimally refine survey measures on vaping consumption, future measures may better align with vapers' self-monitoring by including questions on device-type and replenishment frequency.ImplicationsThe present study provides insights regarding the variability that exists between vaping quantity measurements utilized by researchers and individuals who consume e-cigarettes. The qualitative data analyzed for this study support previous reports of difficulties faced by vapers when asked questions by researchers related to their vaping behavior. Furthermore, the present findings suggest the direction for the future development of accurate measurements of vaping frequency