Astrid N. Zamora

It is well-established that technical and research experiences can support undergraduate retention in science, technology, engineering, and mathematics (STEM) disciplines, but little published research examines outcomes for community college students in internships provided by Department of Energy (DOE) national laboratories. To address this gap, we examined the academic and career activities of alumni who participated in two DOE-sponsored programs at Lawrence Berkeley National Laboratory (LBNL) between 2009 and 2016: the Community College Internship (CCI) and Science Undergraduate Laboratory Internship (SULI). Using self-reported academic and career information collected through alumni surveys, we compared outcomes for CCI alumni from community colleges with those for SULI alumni from baccalaureate-granting institutions. Among CCI alumni, 90% earned a STEM bachelor’s degree and 88% were on a STEM career pathway. For SULI alumni, 91% earned a STEM bachelor’s degree and 71% were on a STEM career pathway. Overall, 80% of CCI alumni and 56% of SULI alumni had entered the STEM workforce. In this sample, community college students who completed national laboratory internships completed academic degrees and pursued STEM careers at rates comparable to students from baccalaureate-granting institutions.

Sleep characteristics have been associated with body mass index (BMI) among adolescents, but population-representative evidence on sleep timing and variation across demographic subgroups remains limited. We conducted a cross-sectional analysis of 2017–2018 California Health Interview Survey data from 880 adolescents aged 12–17 years. Weeknight sleep duration was obtained from the CHIS-derived sleep-duration variable, based on reported school-night bedtimes and school-day wake times. Sleep-timing measures included bedtime, wake time, and the derived sleep midpoint. Pooled survey-weighted linear and logistic regression models used 160 jackknife replicate weights and adjusted for age, sex, race/ethnicity, household poverty category, and survey year; sensitivity models additionally adjusted for dietary and behavioral factors. Sleep duration was not associated with BMI overall (p = 0.161) or with the odds of having overweight or obesity (p = 0.36). The association between sleep duration and BMI varied by age group (p for interaction = 0.042). Each additional hour of sleep was associated with a lower BMI among adolescents aged 14–17 years (β = −0.895 kg/m²; 95% CI: −1.464 to −0.326; p = 0.002), but not among those aged 12–13 years. However, there was no evidence of an interaction when age was modeled continuously (p for interaction = 0.36). Bedtime, wake time, and sleep midpoint were not independently associated with BMI. Exploratory evidence that the association between sleep duration and overweight or obesity varied by race/ethnicity was attenuated after adjustment for dietary and behavioral factors (p for interaction changed from 0.04 to 0.05). In this cross-sectional study, neither sleep duration nor sleep timing was associated with BMI in the overall sample, and sleep duration was not associated with BMI-defined weight status. Subgroup findings were not consistent across model specifications and should be examined in longitudinal studies using objective and repeated measures of sleep.

Background: A growing number of studies have highlighted the importance of data visualization when utilizing mixed-methods approaches within community-based participatory research (CBPR). One such CBPR-derived method – Our Voice – employs a citizen-science (CS) framework that leverages mobile technology to improve health outcomes for residents from diverse communities. Virtual reality (VR) and augmented reality (AR) are two cutting-edge technologies that have been cited as potential tools to enhance data visualization and solution-building processes in Our Voice and similar community-facing methods. However, their utilization in such projects remains limited. In the present study, we report the first integration of VR and AR into two Our Voice projects and examine their feasibility and perceived utility within community-engaged settings. Methods: VR/AR technology was integrated into two Our Voice projects: (1) a project with adult unpaid care workers in Ciudad Bolívar, Bogotá, Colombia, and (2) a project with high school students in Half Moon Bay, CA, United States. In both settings, 360-degree simulations were integrated into a newly refined five-step Our Voice method, which included an “Imagine” step. Post-surveys assessed community members’ attitudes toward VR/AR using a six-point Likert scale. Data were descriptively analyzed. Results: Research using the Our Voice method revealed the integration of VR/AR resulted in citizen scientists and local stakeholders reporting VR/AR enhanced their ability to visualize community-level facilitators and barriers to leading healthy lives. Additionally, participants reported an increase in confidence in the potential of VR/AR to facilitate the development of innovative community-facing solutions to various issues around their neighborhoods. Conclusions: The findings from these pilot investigations suggest that VR/AR holds the promise in contributing to relevant advocacy changes across diverse communities, stakeholders, and problem areas. Future studies should explore developing user-friendly software that bridge data visualization and digital solution-building for broader community and organizational engagement.

Background: Metabolic syndrome (MetS) comprises a cluster of cardiometabolic risk factors that are associated with dietary patterns and social conditions. Examining how dietary patterns and MetS are associated and whether assocations are moderated by food security and sex may inform targeted nutrition strategies for MetS prevention. Aim: To examine associations between data-driven dietary patterns and MetS in a nationally representative sample of US adults and to assess whether associations differed by sex and household food security status. Methods: This cross-sectional study analyzed data from 1333 adults aged ≥18 years in the 2015–2018 National Health and Nutrition Examination Survey. Dietary intake was assessed using two non-consecutive 24-h recalls, and survey-weighted principal components analysis identified dietary patterns from energy-adjusted intakes of 26 food groups. MetS was defined using National Cholesterol Education Program Adult Treatment Panel III criteria (≥3 of: Elevated waist circumference, blood pressure, fasting glucose, triglycerides, or reduced high-density lipoprotein cholesterol). Survey-weighted logistic regression estimated odds of MetS across tertiles of dietary pattern adherence, adjusting for potential confounders. Results: Three major dietary patterns were identified in the overall sample, with greater adherence to a Prudent Seafood and Plant-Based pattern associated with lower MetS z -scores ( p = 0.0019) and a lower odds of MetS ( p = 0.0069). Among males, a Refined Grain, Tomato and Cheese pattern was associated with lower odds of MetS ( p = 0.04), while an Oils, Nuts and Processed Meats pattern was associated with higher odds ( p = 0.03). Food security status modified the association between the Whole Grain, Produce and Low-Fat Dairy pattern and MetS ( p < 0.0001). Conclusions: In a sample of US adults, data-driven dietary patterns showed differential associations with MetS, varying by sex and food security status. These findings indicate effect modification by sex and food security in the relationship between dietary patterns and MetS.

Background: Neighborhood conditions are key social determinants of health (SDOH) that play a critical role in healthy aging. Incorporating contextual measures into behavioral medicine interventions is essential for creating adaptable, equity-focused health solutions. Yet, few physical activity (PA) interventions explicitly evaluate how these factors influence effectiveness. We conducted a secondary analysis of the Computerized Physical Activity Support for Seniors (COMPASS) Trial to examine whether neighborhood context, measured by the California Healthy Places Index (HPI), moderated intervention effects on PA among Latino/a older adults. Methods: The COMPASS trial was a single-blind, cluster-randomized non-inferiority trial comparing an interactive virtual advisor (reference arm) with a trained human peer advisor. PA outcomes, including weekly minutes of walking and moderate-to-vigorous physical activity (MVPA), were assessed with the CHAMPS questionnaire at baseline and 12 months. Neighborhood conditions were measured with the HPI, a composite index of 25 indicators across eight domains (e.g., housing, education, transportation) that reflect place-based SDOH. Scores range from 0 to 100, with higher values indicating more health-supportive environments. Mixed-effects ANCOVA models adjusted for baseline PA, age, and gender, with a random intercept for study site, and tested effect modification via interaction terms between intervention arm and HPI. Results: Among 245 Latino/a participants (mean age = 62.3 years; 78.8% female), HPI significantly moderated intervention effects. When modeled continuously, significant interactions were observed for 12-month changes in walking (β = − 2.93; P = .041) and MVPA (β = − 2.54 min/week per HPI point; P = .033). These findings indicated that the human advisor was comparatively more effective in lower-HPI neighborhoods, whereas the virtual advisor produced stronger improvements in higher-HPI neighborhoods. In sensitivity analyses using dichotomized HPI, the interaction was significant for MVPA (β = − 112.9; P = .026) and trended for walking ( P = .077). Conclusions: Neighborhood context moderated the relative effectiveness of digital versus human-delivered PA interventions. These findings suggest that tailoring delivery strategies, leveraging digital tools in advantaged areas and peer support in under-resourced neighborhoods, may enhance equity in health promotion for older Latino/a adults by explicitly accounting for neighborhood-level social determinants of health. Trial registration: Clinicaltrials.gov NCT02111213 Registered April 2, 2014 https://clinicaltrials.gov/study/NCT02111213 .

To identify pre-intervention predictors of meeting a 12-month walking goal among generally healthy, insufficiently active midlife and older Latino/a adults ≥ 50 years enrolled in a 12-month cluster-randomized physical activity (PA) effectiveness trial. Midlife and older adult participants (N = 245) from the Computerized Physical Activity Support for Seniors trial were randomly assigned to a human peer or virtual advisor. Signal detection analysis (SDA) was used to identify combinations of the 41 baseline sociodemographic, behavioral, clinical, and psychosocial variables, along with the intervention arm (human peer vs. virtual advisor), that formed subgroups that varied in how likely they were to achieve the ≥ 150 min per week walking goal at the 12-month endpoint using the validated Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. Mean (SD) age was 62.3 (8.4) years, and 78.8% were female. Overall, 49.8% of the sample met the walking goal. SDA identified eight subgroups, and intervention arm was not a key factor. Among participants in smaller households (< 3 people), the best predictors of meeting the walking goal were high acculturation to U.S. (English) media and a lower average resting systolic blood pressure. Among participants in larger households (≥ 3 people), the best predictors of meeting the walking goal were lower levels of sedentary behavior and a lower average resting heart rate. We found that household composition, acculturation level, sedentary behavior and pre-intervention walking behavior, in addition to multiple clinical markers successfully differentiated subgroups that varied in their success of meeting the 12-month walking goal. Results underscore the importance of exploring subgroups to inform the development of customized, precision exercise interventions to enhance PA among insufficiently active older Latino/a adults.

Objective: To identify subgroups of midlife and older adults from the United States (US), defined by specific combinations of factors, who are more or less likely to meet age-specific sleep duration recommendations. Methods: Participants ( n = 3,124) aged ≥ 40 years were drawn from the 2011-2018 National Health and Nutrition Examination Survey cycles. The primary outcome was meeting age-specific sleep duration recommendations (7 to 9 hours per night) to promote optimal health. Signal detection analysis was used to identify subgroups, defined by combinations of socio-demographic, clinical, cardiometabolic, and behavioral factors, that predicted whether participants met age-specific sleep duration recommendations. Results: The mean age of participants was 58.3 (standard error = 0.3) years, with a mean sleep duration of 7.3 (standard error = 0.03) hours/night. Overall, 64.3% met the age-specific sleep duration recommendations. Eight subgroups were identified through signal detection, with race/ethnicity being the primary splitting variable. The subgroup most likely to meet the sleep duration recommendations (82.9%; 353/426) identified as Non-Hispanic White, had a poverty income ratio score ≥ 3.2 (indicating household income 3.2 times the poverty threshold), and had no history of trouble sleeping. In contrast, the subgroup least likely to meet the sleep duration recommendations (45.0%; 144/320) identified as racial/ethnic minorities, had a history of trouble sleeping, and engaged in less than 324 minutes of moderate-to-vigorous physical activity per week. Conclusions: Findings from this cross-sectional study highlight the importance of examining combinations of factors to systematically identify subgroups more or less likely to meet age-specific sleep duration recommendations for optimal health. Future research should explore how these factors change over time to inform public health strategies aimed at improving sleep health among US midlife and older adults, particularly those from racial and ethnic minority backgrounds.

Purpose: ‘Exercise snacks’— brief, intermittent sessions of moderate-to-high intensity activity— offer a novel and promising solution for sedentary office workers. However, perceptions and experiences related to engaging in this approach are limited or largely unknown. Approach and Participants: This qualitative study employed semi-structured interviews with 20 office workers who completed a pilot exercise snack intervention called Move Often eVeryDay (MOV’D). The sample consisted of 10 participants from the MOV'D intervention group and 10 participants from the self-monitoring group. Setting: Interviews were conducted remotely via Zoom. Methods: Interview transcripts were analyzed using open-coded, thematic analysis, with themes and subthemes identified both a priori and inductively during the analysis. Results: The mean (SD) age of participants was 43.8 (11.3) years, 80% identified as women or transgender women, and 35% reported being Non-Hispanic White. Emergent themes included enjoyment of study components, increased motivation and physical activity awareness, and knowledge gained. Common barriers included time constraints and competing obligations. Facilitators of engagement included behavioral adaptations and the minimal space needed for activities. Key suggestions for future iterations included having more reminders throughout the study, enhanced social connection, and adjustments to intervention materials. Conclusion: Although exercise snacks are brief and accessible, findings highlight the need to refine the intervention to reduce participation barriers and support long-term habit formation. The insights garnered from the present pilot study offer actionable recommendations for enhancing this and other similar health promotion behavioral interventions. Trial registration: The trial was registered on May 3, 2022 (before recruitment began) at https://clinicaltrials.gov/study/NCT05360485 , clinical trial number: NCT05360485.