Nicotine exposure from packaged cigarettes in tobacco retail settings.

BACKGROUND: Although many studies on exposure to environmental tobacco smoke from passive smoking have been conducted, most of such studies have only focused on the chemicals produced by active combustion. The current study examined the extent to which uncombusted and packaged cigarettes in cigarette racks at retail stores diffuse airborne nicotine. METHODS: Airborne nicotine samples were collected for 15 days on passive monitors mounted near the indoor cigarette racks (Point 1) and farthest point from the cigarette racks (Point 2) in tobacco retailer stores (N=95) in South Korea (5 months, data collection from January to May in 2022. RESULTS: The average airborne nicotine level was 0.0908 ug/m3 at Point 1 and 0.0345 ug/m3 at Point 2. We found a positive correlation (r=0.647, p <0.001) in nicotine concentration between the two measurement points. The interior size of the target stores was positively correlated (r=0.334, p <0.001) with the within-store difference in nicotine concentration between the two measurement points. The airborne nicotine concentration at Point 1 was statistically significantly higher than at Point 2 (z=-2.326, p=0.020, effect size: 0.2215), especially at larger stores. CONCLUSIONS: Our findings indicate that packaged, unopened, and uncombusted cigarettes in cigarette racks at tobacco retailers emits airborne nicotine, which is a previously unrecognized source of nicotine exposure. This result has implications for policy considerations, such as the potential installation of ventilation systems on cigarette racks or the exploration of alternative packaging methods.

Clinical, demographic factors, and substance use among Hispanic and non-Hispanic young adult childhood cancer survivors.

PURPOSE: The purpose of this study is to examine the protective and risk factors of substance use behaviors (tobacco, marijuana, e-cigarette, and alcohol) among young adult childhood cancer survivors. The study focused on clinical (receipt of cancer-related follow-up care, treatment intensity, late effects, depressive symptoms, self-rated health) and demographic (race/ethnicity, neighborhood socioeconomic status) factors and their associations with substance use. METHODS: Participants were from the Project Forward cohort, a population-based study of young adult survivors of childhood cancers. Participants (N = 1166, Mage = 25.1 years) were recruited through the Los Angeles Cancer Surveillance Program (Cancer Registry covering Los Angeles County, California). Multivariate path analyses were performed with substance use as the outcome variables and clinical and demographic factors as independent variables. Covariates included age and sex. FINDING: Substance use was positively associated with depressive symptoms, and inversely associated with cancer-related follow-up care, female sex, age, Hispanic ethnicity, treatment intensity, and self-rated health. Neighborhood SES was inversely associated with tobacco use, while being positively associated with binge drinking and e-cigarette use. The results highlight the interrelationship between the clinical and demographic variables and their associations with different substance use. CONCLUSION: Findings support the need for effective interventions targeting substance use behavior among CCS. This will help improve long-term outcomes and mitigate the risk for early morbidity.

Adult harm perceptions, purchase, and use related to synthetic vs. tobacco-derived nicotine vaping products: A mixed-methods study.

Objective: Synthetic nicotine (SN) e-cigarettes emerged on the market as an alternative to tobacco-derived nicotine (TDN) vaping products. It is critical to understand the harm perceptions, purchase, and use of SN vs. TDN e-cigarettes. Methods: From November 2021 to February 2023, we conducted intercept interviews with 263 adult customers at 37 vape shops in Southern California. Self-reported use and harm perceptions towards SN vs TDN e-cigarettes were examined. A qualitative analysis of researcher-obtained photographs of vaping items just purchased by customer participants was conducted. Results: Past 30-day SN e-cigarette use was reported by 44 (16.7 %) customers. Past 30-day SN e-cigarette users vs. non-users reported vaping on more days in the past month (29.3 vs. 26.1 days, p = 0.02). Overall, 23.8 % of participants perceived SN e-cigarettes as less harmful than TDN ones; never-smoking vapers and dual users perceived SN e-cigarettes as less harmful than salt-based TDN e-cigarettes. Among 44 customers who purchased SN products (verified through qualitative analysis of photographs), only 13 (29.6 %) self-reported using SN products in the past month, while 5 (11.4 %) indicated they were not aware of the existence of SN products. Most SN vaping products (71.4 %) displayed a modified "tobacco-free" warning label. Conclusions: Misperceptions about SN e-cigarettes were documented in this study, including the perception that SN is either less or more harmful than TDN. Further, some customers may be unknowingly purchasing and using SN e-cigarettes. Regulating "tobacco-free nicotine" terminology in SN vaping products marketing is suggested. SN product labeling should not imply that SN is safe/safer than TDN.

General cognitive ability in high school, attained education, occupational complexity, and dementia risk.

INTRODUCTION: We address the extent to which adolescent cognition predicts dementia risk in later life, mediated by educational attainment and occupational complexity. METHODS: Using data from Project Talent Aging Study (PTAS), we fitted two structural equation models to test whether adolescent cognition predicts cognitive impairment (CI) and Ascertain Dementia 8 (AD8) status simultaneously (NCognitive Assessment = 2477) and AD8 alone (NQuestionnaire = 6491) 60 years later, mediated by education and occupational complexity. Co-twin control analysis examined 82 discordant pairs for CI/AD8. RESULTS: Education partially mediated the effect of adolescent cognition on CI in the cognitive assessment aample and AD8 in the questionnaire sample (Ps < 0.001). Within twin pairs, differences in adolescent cognition were small, but intrapair differences in education predicted CI status. DISCUSSION: Adolescent cognition predicted dementia risk 60 years later, partially mediated through education. Educational attainment, but not occupational complexity, contributes to CI risk beyond its role as a mediator of adolescent cognition, further supported by the co-twin analyses. HIGHLIGHTS: Project Talent Aging Study follows enrollees from high school for nearly 60 years. General cognitive ability in high school predicts later-life cognitive impairment. Low education is a risk partially due to its association with cognitive ability.

Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry.

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

Co-design Tensions Between Parents, Children, and Researchers Regarding Mobile Health Technology Design Needs and Decisions: Case Study.

BACKGROUND: Just-in-time adaptive interventions (JITAIs) in mobile health are an intervention design that provides behavior change support based on an individual's changing and dynamic contextual state. However, few studies have documented how end users of JITAI technologies are involved in their development, particularly from historically marginalized families and children. Less is known for public health researchers and designers of the tensions that occur as families negotiate their needs. OBJECTIVE: We aimed to broaden our understanding of how historically marginalized families are included in co-design from a public health perspective. We sought to address research questions surrounding JITAIs; co-design; and working with historically marginalized families, including Black, Indigenous, and people of color (BIPOC) children and adults, regarding improving sun protection behaviors. We sought to better understand value tensions in parents' and children's needs regarding mobile health technologies and how design decisions are made. METHODS: We examined 2 sets of co-design data (local and web-based) pertaining to a larger study on mobile SunSmart JITAI technologies with families in Los Angeles, California, United States, who were predominantly of Latinx and multiracial backgrounds. In these co-design sessions, we conducted stakeholder analysis through perceptions of harms and benefits and an assessment of stakeholder views and values. We open coded the data and compared the developed themes using a value-sensitive design framework by examining value tensions to help organize our qualitative data. Our study is formatted through a narrative case study that captures the essential meanings and qualities that are difficult to present, such as quotes in isolation. RESULTS: We presented 3 major themes from our co-design data: different experiences with the sun and protection, misconceptions about the sun and sun protection, and technological design and expectations. We also provided value flow (opportunities for design), value dam (challenges to design), or value flow or dam (a hybrid problem) subthemes. For each subtheme, we provided a design decision and a response we ended up making based on what was presented and the kinds of value tensions we observed. CONCLUSIONS: We provide empirical data to show what it is like to work with multiple BIPOC stakeholders in the roles of families and children. We demonstrate the use of the value tension framework to explain the different needs of multiple stakeholders and technology development. Specifically, we demonstrate that the value tension framework helps sort our participants' co-design responses into clear and easy-to-understand design guidelines. Using the value tension framework, we were able to sort the tensions between children and adults, family socioeconomic and health wellness needs, and researchers and participants while being able to make specific design decisions from this organized view. Finally, we provide design implications and guidance for the development of JITAI mobile interventions for BIPOC families.

A National Portrait of Public Attitudes toward Opioid Use in the US: A Latent Class Analysis.

BACKGROUND: Opioid overdose rates have steadily been increasing in the United States (US) creating what is considered an overdose death crisis. The US has a mixture of public health and punitive policies aimed to address opioid use and the overdose crisis, yet little is known about public opinion relating to opioid use and policy support. Understanding the intersection of public opinion about opioid use disorder (OUD) and policy can be useful for developing interventions to address policy responses to overdose deaths. METHODS: A national sample of cross-sectional data from the AmeriSpeak survey conducted from 27 February 2020 through 2 March 2020 was analyzed. Measures included attitudes toward OUD and policy beliefs. Latent class analysis, a person-centered approach, was used to identify groups of individuals endorsing similar stigma and policy beliefs. We then examined the relationship between the identified groups (i.e., classes) and key behavioral and demographic factors. RESULTS: We identified three distinct groups: (1) "High Stigma/High Punitive Policy", (2) "High Stigma/Mixed Public Health and Punitive Policy", and (3) "Low Stigma/High Public Health Policy". People with higher levels of education had reduced odds of being in the "High Stigma/High Punitive Policy" group. CONCLUSION: Public health policies are most effective in addressing OUD. We suggest targeting interventions toward the "High Stigma/Mixed Public Health and Punitive Policy" group since this group already displays some support for public health policies. Broader interventions, such as eliminating stigmatizing messaging in the media and redacting punitive policies, could reduce OUD stigma among all groups.

Prognostic artificial intelligence model to predict 5 year survival at 1 year after gastric cancer surgery based on nutrition and body morphometry.

BACKGROUND: Personalized survival prediction is important in gastric cancer patients after gastrectomy based on large datasets with many variables including time-varying factors in nutrition and body morphometry. One year after gastrectomy might be the optimal timing to predict long-term survival because most patients experience significant nutritional change, muscle loss, and postoperative changes in the first year after gastrectomy. We aimed to develop a personalized prognostic artificial intelligence (AI) model to predict 5 year survival at 1 year after gastrectomy. METHODS: From a prospectively built gastric surgery registry from a tertiary hospital, 4025 gastric cancer patients (mean age 56.1 ± 10.9, 36.2% females) treated gastrectomy and survived more than a year were selected. Eighty-nine variables including clinical and derived time-varying variables were used as input variables. We proposed a multi-tree extreme gradient boosting (XGBoost) algorithm, an ensemble AI algorithm based on 100 datasets derived from repeated five-fold cross-validation. Internal validation was performed in split datasets (n = 1121) by comparing our proposed model and six other AI algorithms. External validation was performed in 590 patients from other hospitals (mean age 55.9 ± 11.2, 37.3% females). We performed a sensitivity analysis to analyse the effect of the nutritional and fat/muscle indices using a leave-one-out method. RESULTS: In the internal validation, our proposed model showed AUROC of 0.8237, which outperformed the other AI algorithms (0.7988-0.8165), 80.00% sensitivity, 72.34% specificity, and 76.17% balanced accuracy. In the external validation, our model showed AUROC of 0.8903, 86.96% sensitivity, 74.60% specificity, and 80.78% balanced accuracy. Sensitivity analysis demonstrated that the nutritional and fat/muscle indices influenced the balanced accuracy by 0.31% and 6.29% in the internal and external validation set, respectively. Our developed AI model was published on a website for personalized survival prediction. CONCLUSIONS: Our proposed AI model provides substantially good performance in predicting 5 year survival at 1 year after gastric cancer surgery. The nutritional and fat/muscle indices contributed to increase the prediction performance of our AI model.

Examining the Factor Structure of an Adapted Posttraumatic Growth Inventory in a Sample of Childhood Cancer Survivors: A Brief Report.

Posttraumatic growth (PTG) represents positive changes following a trauma, crisis, and/or psychologically distressing event. Experiencing cancer can serve as a traumatic event for patients, resulting in life changes among survivors. Various PTG measures have been used to assess post-cancer change among childhood cancer survivors (CCS), but few have been evaluated for use in this population. This study examined the factor structure of an adapted, 11-item version of the Posttraumatic Growth Inventory (PTGI) among CCS. A randomly selected subgroup of participants (N = 332) was selected from the Los Angeles Cancer Surveillance Program (mean age of 26.5 years at time of survey, mean age at diagnosis of 12 years, primarily male [53.6%], and Hispanic [51.5%]). Participants indicated the degree to which they experienced positive, negative, or no change in their life because of their cancer experience. An exploratory factor analysis (EFA) identified two factors: Appreciation of New Possibilities and Spiritual Change. The adapted, 11-item PTGI was deemed appropriate for use among CCS. Additional research is needed to confirm the use of the two-factor model with confirmatory factor analysis in an independent sample. Future research on PTG among CCS can consider spiritual change as a potential independent factor.

Longitudinal Examination of an Ethnic Paradox of Stress and Mental Health in Older Black and Latinx Adults.

OBJECTIVES: To explain the ethnic paradox of mental health in aging, we evaluated whether Black and Latinx older adults experience (1) fewer depressive symptoms (DepSx), but more physical problems, and (2) greater psychological resilience as a result of life stressors than White older adults. METHODS: DepSx, physical health, and recent stress were obtained biennially from 25,893 older adults (77% White, 15% Black, 9% Latinx) in the U.S. Health and Retirement Study, across 16 years. Psychological resilience, lifetime stress, and discrimination experiences were available for 13,655 individuals. We conducted mixed-effects and linear regression analyses. RESULTS: For Blacks and Latinxs, experiencing more-than-usual stress events was associated with less increase in DepSx compared to Whites, although on average Blacks and Latinxs experience more DepSx. Black adults showed worse physical health than White adults and weaker effects of stress on psychological resilience despite experiencing more stress of all types. Findings were mixed for Latinxs. CONCLUSIONS: Studying effects of time-varying stress on changes in health and multiple stressors on psychological resilience by race/ethnicity elucidates mechanisms for later-age health disparities. CLINICAL IMPLICATIONS: Cross-sectional evaluations of stress and psychological health in a clinical setting may provide incomplete appraisals of health risks for Black and Latinx older Americans.

Hypothetical flavour ban and intention to vape among vape shop customers: the role of flavour preference and e-cigarette dependence.

INTRODUCTION: E-cigarette users typically initiate vaping with flavoured e-liquids. People who vape flavours tend to underestimate the harm of vaping. We examined the inter-relationship between flavour preference, vaping for cessation purposes, e-cigarette dependence, e-cigarette harm perception and purchase/use intention, given a hypothetical flavour ban. We hypothesised that non-tobacco flavour preference and vaping for cessation would be negatively associated with harm perception of e-cigarettes and intention to continue vaping if a flavour ban occurred and that these effects would be mediated by e-cigarette dependence. METHODS: From July 2019 to March 2020, we conducted intercept interviews with 276 customers at 44 vape shops in California. The predictor variables were flavour preference and vaping for cessation. The outcome variables were harm perception of e-cigarettes and intention to purchase/use, given a hypothetical flavour ban. Multilevel structural equation modelling tested whether e-cigarette dependence mediates the effects of flavour preference on hypothetical continued vaping and purchase. RESULTS: Those who preferred flavours showed significantly lower intention to purchase e-liquids (ß=-0.28, p<0.001) and to continue vaping (ß=-0.17, p=0.001), given a hypothetical flavour ban. Those who vaped for smoking cessation indicated greater intention to purchase e-liquid (ß=0.10, p=0.016) and to continue vaping (ß=0.17, p=0.001), given a hypothetical flavour ban. E-cigarette dependence significantly mediated these effects (ps<0.04). DISCUSSION: Flavour preference was negatively related to intention to continue to vape within a hypothetical flavour ban. Our results also highlight the importance of e-cigarette dependence and use of e-cigarettes as smoking cessation methods. Implications for future flavour bans are discussed.

Deep Learning-Based Automatic Detection and Grading of Motion-Related Artifacts on Gadoxetic Acid-Enhanced Liver MRI.

OBJECTIVES: The aim of this study was to develop and validate a deep learning-based algorithm (DLA) for automatic detection and grading of motion-related artifacts on arterial phase liver magnetic resonance imaging (MRI). MATERIALS AND METHODS: Multistep DLA for detection and grading of motion-related artifacts, based on the modified ResNet-101 and U-net, were trained using 336 arterial phase images of gadoxetic acid-enhanced liver MRI examinations obtained in 2017 (training dataset; mean age, 68.6 years [range, 18-95]; 254 men). Motion-related artifacts were evaluated in 4 different MRI slices using a 3-tier grading system. In the validation dataset, 313 images from the same institution obtained in 2018 (internal validation dataset; mean age, 67.2 years [range, 21-87]; 228 men) and 329 from 3 different institutions (external validation dataset; mean age, 64.0 years [range, 23-90]; 214 men) were included, and the per-slice and per-examination performances for the detection of motion-related artifacts were evaluated. RESULTS: The per-slice sensitivity and specificity of the DLA for detecting grade 3 motion-related artifacts were 91.5% (97/106) and 96.8% (1134/1172) in the internal validation dataset and 93.3% (265/284) and 91.6% (948/1035) in the external validation dataset. The per-examination sensitivity and specificity were 92.0% (23/25) and 99.7% (287/288) in the internal validation dataset and 90.0% (72/80) and 96.0% (239/249) in the external validation dataset, respectively. The processing time of the DLA for automatic grading of motion-related artifacts was from 4.11 to 4.22 seconds per MRI examination. CONCLUSIONS: The DLA enabled automatic and instant detection and grading of motion-related artifacts on arterial phase gadoxetic acid-enhanced liver MRI.

An Assessment of Vape Shop Products in California before and after Implementation of FDA and State Regulations.

Vape shops specialize in sales of e-cigarettes and related products. This study examines whether vape shops adapted their products and services in response to changes in federal and state policies that affect the tobacco retail environment between 2014-2022. In this multicohort study, four waves of study data were used to examine the trends in products sold in vape shops in Southern California. Items sold were assessed through systematic store product observations and included categories of e-cigarettes, device modification equipment, and other products (e.g., Cannabidiol (CBD), paraphernalia). Descriptive statistics are reported. The availability of disposable devices increased from 18% at Wave 1 to 98% of shops at Wave 4. Pod mods were first observed in 79% of the shops beginning at Wave 3. Device modification drills later become obsolete, from 60% at Wave 1 to 0 by Wave 4; self-service sampling displays declined from 83% of shops to 9%. Vape shops did not carry CBD products until Wave 3 (2017/2018), when 19.0% of shops carried CBD products and 72.9% at Wave 4. Future research should examine how e-cigarette retailers and manufacturers respond to changing state and federal regulations to better understand the implications of regulatory efforts.

Substance Use Descriptive Norms and Behaviors among US College Students: Findings from the Healthy Minds Study.

BACKGROUND: Social norms have been associated with alcohol use in college populations; however, more research is needed to confirm the associations between social norms and a range of substance use behaviors during the COVID-19 pandemic. METHODS: We analyzed data from the Healthy Minds Study (September 2020-December 2020), a non-probability sample administered online to college students. We used multivariable logistic regression to test for associations between respondents' perceptions of substance use behaviors in their respective colleges and their own substance use behaviors, adjusting for age, gender, race/ethnicity, and international student status. RESULTS: We found that those who overestimated the prevalence of alcohol use, cigarette use, cannabis use, and vaping were significantly more likely to use these substances when compared with those who did not overestimate. These associations persisted even when using different prevalence estimates of substance use, though some associations lost statistical significance when applying the survey weights to account for non-response. CONCLUSION: College students overestimated the prevalence of substance use in their respective colleges, even during the early stages of the pandemic when social interactions were limited, and these beliefs were associated with substance use. Future studies may test the utility of campaigns to alter perceptions of social norms and interventions that use personalized normative feedback to reduce substance use during pandemics.

Time-Varying Associations Between Device-Based and Ecological Momentary Assessment-Reported Sedentary Behaviors and the Concurrent Affective States Among Adolescents: Proof-of-Concept Study.

BACKGROUND: Previous studies on affective state-sedentary behavior (SB) associations have not accounted for their potentially time-varying nature and have used inconsistent SB measurement modalities. We investigated whether the strength of the associations between affective states and SB varied as a function of the time of day and by SB measurement modality (device-measured SB vs ecological momentary assessment-reported screen-based SB) in youth. OBJECTIVE: This study aimed to establish a proof of concept that SB-affective state associations may not be static during the day. In addition, we aimed to inform the methodology of future work, which may need to model associations as functions of the time of day and carefully consider how SB is operationalized or measured. METHODS: A total of 15 adolescents (age: mean 13.07, SD 1.03 years; 10/15, 67% female; 6/15, 40% Hispanic; 10/15, 67% healthy weight) wore thigh-mounted activPAL accelerometers and simultaneously reported their screen-based SBs and concurrent positive and negative affective states via ecological momentary assessment for 7 to 14 days (N=636 occasions). Time-varying effect models (varying slopes) examined how each measure of SB was associated with concurrent affective states from 7 AM to 8 PM. RESULTS: Time-varying effect model plots revealed that these associations varied in strength throughout the day. Specifically, device-based SB was related to greater concurrent negative affect only after approximately 5 PM and was unrelated to concurrent positive affect. Screen-based SB was related to greater concurrent negative affect only from 7 AM to approximately 9 AM. This was also related to greater concurrent positive affect from 7 AM to approximately 9:30 AM and from approximately 3 PM to approximately 7 PM. CONCLUSIONS: We provide preliminary evidence to suggest that future confirmatory studies investigating the SB-affective state relationship should consider the time-varying nature of these associations and SB measurement modality. There may be critical time windows when specific types of SBs co-occur with affect, suggesting that interventions may need tailoring to the time of day and type of SB if future studies using similar methodologies can replicate our findings.

Alcohol use trajectories among U.S. adults during the first 42 weeks of the COVID-19 pandemic.

BACKGROUND: This study characterized the prevalence, drinking patterns, and sociodemographic characteristics of U.S. adult subpopulations with distinct drinking trajectories during the COVID-19 pandemic's first 42 weeks. METHODS: Adult respondents (n = 8130) in a nationally representative prospective longitudinal study completed 21 biweekly web surveys (March 2020 to January 2021). Past-week alcohol drinking frequency (drinking days [range: 0 to 7]) and intensity (binge drinking on usual past-week drinking day [yes/no]) were assessed at each timepoint. Growth mixture models identified multiple subpopulations with homogenous drinking trajectories based on mean drinking days or binge drinking proportional probabilities across time. RESULTS: Four drinking frequency trajectories were identified: Minimal/stable (72.8% [95% CI = 71.8 to 73.8]) with <1 mean past-week drinking days throughout; Moderate/late decreasing (6.7% [95% CI = 6.2 to 7.3) with 3.13 mean March drinking days and reductions during summer, reaching 2.12 days by January 2021; Moderate/early increasing (12.9% [95% CI = 12.2 to 13.6) with 2.13 mean March drinking days that increased in April and then plateaued, ending with 3.20 mean days in January 2021; and Near daily/early increasing (7.6% [95% CI = 7.0 to 8.2]) with 5.58 mean March drinking days that continued increasing without returning to baseline. Four drinking intensity trajectories were identified: Minimal/stable (85.8% [95% CI = 85.0% to 86.5%]) with <0.01 binge drinking probabilities throughout; Low-to-moderate/fluctuating (7.4% [95% CI = 6.8% to 8%]) with varying binge probabilities across timepoints (range:0.12 to 0.26); Moderate/mid increasing (4.2% [95% CI = 3.7% to 4.6%]) with 0.39 April binge drinking probability rising to 0.65 during August-September without returning to baseline; High/early increasing trajectory (2.7% [95% CI = 2.3% to 3%]) with 0.84 binge drinking probability rising to 0.96 by June without returning to baseline. Males, Whites, middle-aged/older adults, college degree recipients, those consistently working, and those above the poverty limit were overrepresented in various increasing (vs. minimal/stable) frequency trajectories. Males, Whites, nonmarried, those without college degree, 18 to 39-year-olds, and middle aged were overrepresented in increasing (vs. minimal/stable) intensity trajectories. CONCLUSIONS: Several distinct U.S. adult sociodemographic subpopulations appear to have acquired new drinking patterns during the pandemic's first 42 weeks. Frequent alcohol use assessment in the COVID-19 era could improve personalized medicine and population health efforts to reduce drinking.

Validating the Group-Based Medical Mistrust Scale with English and Spanish Speaking Latino Parents of Adolescents.

BACKGROUND: Medical mistrust can be a barrier to health care utilization. While the Group-Based Medical Mistrust Scale (GBMMS) has been validated among diverse populations, we know little about its psychometric performance among English-Speaking (ES) and Spanish-Speaking (SS) Latinos. We aim to examine the factor structure of GBMMS among Latino parents and explore whether scale latent factor structures would be different across preferred languages. METHODS: Parents of adolescents participating in an urban academic enrichment program for low-income students completed an online survey as part of a cross-sectional study about Human Papillomavirus (HPV) prevention. We tested the validity of the GBMMS in ES and SS respondents and performed exploratory factor analysis to identify latent factors. We examined scale scores, item means, item endorsement, and residual variance across language groups. RESULTS: 2-factor latent structure was identified for both ES and SS groups; factors were labeled as 'Suspicion' and 'System-wide discrimination.' Scale validity was better among SS (α = 0.76). Medical mistrust scores did not vary across language groups, but variation emerged in item endorsement by language. DISCUSSION: Our results suggest that the factor structures of the medical mistrust construct, measured by the GBMMS, are similar across ES and SS Latinos and that the GBMMS is valid for both populations. High factor pattern loading reflects a shared mistrust of how health care systems view and treat people of their racial/ethnic background, independent of their preferred languages. Measurement of medical mistrust and identifying its underlying causes are needed within diverse populations to fully address structural- and community-level influences on health inequities.

Patterns of Objectively Measured Sedentary Time and Emotional Disorder Symptoms Among Youth.

OBJECTIVE: We examined the within-person longitudinal and bidirectional associations between patterns of sedentary time accumulation [alpha (sedentary bout duration/length), sedentary breaks (number of breaks in sedentary bouts)], and symptoms of major depressive disorder and generalized anxiety disorder. METHODS: Children [N = 167, 10.1(0.9) years old, 54.5% female, 59.3% Hispanic, 35.9% overweight/obese at baseline] participated in a 3-year longitudinal study that consisted of assessments of sedentary time, and depressive and anxiety symptoms. At each assessment, participants wore accelerometers and completed the Revised Child Anxiety and Depression Scale. Separate random intercept cross-lagged panel models estimated the within-person longitudinal and bidirectional associations between alpha, sedentary breaks, and symptoms of major depressive disorder and generalized anxiety disorder across chronological age intervals. RESULTS: Having greater than one's own usual depressive symptoms at age 11 was associated with fewer sedentary breaks 1 year later. Having greater than one's own usual generalized anxiety symptoms at age 11 was associated with longer sedentary bouts and fewer sedentary breaks 1 year later. In contrast, having greater than one's own usual sedentary breaks at age 10 was associated with fewer generalized anxiety symptoms 1 year later. All other associations, including at younger ages, were null. CONCLUSION: Deviations from one's usual levels of depressive or anxiety symptoms may be important for how sedentary time is subsequently accumulated. Intraindividual processes appear to be at play, therefore more within-person research is needed. Intervention strategies for promoting a healthier accumulation of sedentary time may consider targeting occasions when depressive and anxiety symptoms are greater than usual.

Adolescent Body Mass Index and Exposure to Peers with Overweight and Obesity: A Structural Equation Model Approach to Longitudinal Network Data.

Purpose: Considerable evidence has shown that social networks influence a wide variety of health behaviors. This study investigates whether having friends with overweight/obesity in one's social network (network exposure) can predict changes in body mass index (BMI) throughout high school in a diverse urban population of students. Methods: Racially and ethnically diverse students from five high schools in Los Angeles County were surveyed at four time points throughout high school from 2010 to 2013 (N = 2091). Surveys included questions on students' social networks, demographics, and health-related information. BMI and weight categories were calculated for all students who provided height and weight information (∼50%). A latent growth curve model was used to assess the growth trajectory of BMI and the time-varying effect of network exposure to friends with overweight/obesity while controlling for demographic covariates. Results: Hispanic students had a significantly higher initial BMI compared with non-Hispanic students (p < 0.01). There was a significant positive slope for time on BMI growth (p < 0.01). Greater personal network exposure to friends with overweight/obesity was associated with a significant 0.65-point average increase in BMI (p < 0.05) at the first follow-up time point (T2) and a significant 0.62-point average increase in BMI (p < 0.01) at the last follow-up (T4) while controlling for covariates. Conclusions: Using structural equation modeling to understand the relationship between BMI and social networks, we found that increased network exposure to peers with overweight/obesity is associated with higher individual BMI, demonstrating that friendships may influence adolescents' weight status over time.

A reliable and robust method for the upper thigh muscle quantification on computed tomography: toward a quantitative biomarker for sarcopenia.

BACKGROUND: We aimed to evaluate the feasibility of the upper thigh level as a landmark to measure muscle area for sarcopenia assessment on computed tomography (CT). METHODS: In the 116 healthy subjects who performed CT scans covering from mid-abdomen to feet, the skeletal muscle area in the upper thigh level at the inferior tip of ischial tuberosity (SMAUT), the mid-thigh level (SMAMT), and L3 inferior endplate level (SMAL3) were measured by two independent readers. Pearson correlation coefficients between SMAUT, SMAMT, and SMAL3 were calculated. Inter-reader agreement between the two readers were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman plots with 95% limit of agreement (LOA). RESULTS: In readers 1 and 2, very high positive correlations were observed between SMAUT and SMAMT (r = 0.91 and 0.92, respectively) and between SMAUT and SMAL3 (r = 0.90 and 0.91, respectively), while high positive correlation were observed between SMAMT and SMAL3 (r = 0.87 and 0.87, respectively). Based on ICC values, the inter-reader agreement was the best in the SMAUT (0.999), followed by the SMAL3 (0.990) and SMAMT (0.956). The 95% LOAs in the Bland-Altman plots indicated that the inter-reader agreement of the SMAUT (- 0.462 to 1.513) was the best, followed by the SMAL3 (- 9.949 to 7.636) and SMAMT (- 12.105 to 14.605). CONCLUSION: Muscle area measurement at the upper thigh level correlates well with those with the mid-thigh and L3 inferior endpoint level and shows the highest inter-reader agreement. Thus, the upper thigh level might be an excellent landmark enabling SMAUT as a reliable and robust biomarker for muscle area measurement for sarcopenia assessment.