Lifetime Exposure to Cigarette Smoke, B-Cell Tumor Immune Infiltration, and Immunoglobulin Abundance in Ovarian Tumors.

BACKGROUND: Cigarette smoke exposure has been linked to systemic immune dysfunction, including for B-cell and immunoglobulin (Ig) production, and poor outcomes in patients with ovarian cancer. No study has evaluated the impact of smoke exposure across the life-course on B-cell infiltration and Ig abundance in ovarian tumors. METHODS: We measured markers of B and plasma cells and Ig isotypes using multiplex immunofluorescence on 395 ovarian cancer tumors in the Nurses' Health Study (NHS)/NHSII. We conducted beta-binomial analyses evaluating odds ratios (OR) and 95% confidence intervals (CI) for positivity of immune markers by cigarette exposure among cases and Cox proportional hazards models to evaluate hazard ratios (HR) and 95% CI for developing tumors with low (

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot.

BACKGROUND: The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties. METHODS: Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size. RESULTS: TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention. CONCLUSIONS: A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support). TRIAL REGISTRATION: Clinicaltrials.gov ( NCT03509129 , April 26, 2018).

The Relationship Between How Participants Articulate Their Goals and Accomplishments and Weight Loss Outcomes: Secondary Analysis of a Pilot of a Web-Based Weight Loss Intervention.

BACKGROUND: In behavioral weight loss interventions, participants are asked to set weekly goals to support long-term habits that lead to weight loss. Although participants are asked to set and accomplish weekly goals, we do not know how often they do this and whether doing so is associated with weight loss. Web-based weight loss interventions allow for the analysis of participant engagement data, including how participants articulate their goals and accomplishments. OBJECTIVE: Using engagement data from a web-based weight loss intervention, we examined whether participants articulating their goals and accomplishments in measurable and repeating terms were associated with greater weight loss. METHODS: Adults with overweight or obesity received a 12-week Facebook-delivered weight loss intervention based on the Diabetes Prevention Program Lifestyle Intervention. Participants replied to conversation threads that queried about their goals and accomplishments. Two independent coders classified participants' posts that articulated goals or accomplishments as measurable or repeating. Crude and age-adjusted linear regression models were used to examine the relationship between the frequency of post type and percent weight loss. RESULTS: Participants (N=53; n=48, 91% female; n=48, 91% non-Hispanic White) were on average 46.2 (SD 10.5) years old with a mean BMI of 32.4 (SD 4.8) kg/m2. Over 12 weeks, participants shared a median of 4 (IQR 1-8) posts that reported goals and 10 (IQR 4-24) posts that reported accomplishments. Most participants shared ≥1 post with a goal (n=43, 81%) and ≥1 post with an accomplishment (n=47, 89%). Each post reporting a goal was associated with 0.2% greater weight loss (95% CI -0.3% to 0.0%). Sharing ≥1 post with a repeating goal was associated with an average of 2.2% greater weight loss (95% CI -3.9% to -0.4%). Each post with a repeating goal was associated with an average of 0.5% greater weight loss (95% CI -1.0% to 0.0%). Sharing ≥1 post with measurable and repeating goals was associated with an average of 1.9% greater weight loss (95% CI -3.7% to -0.2%). Sharing each post with an accomplishment was associated with an average of 0.1% greater weight loss (95% CI -0.1% to 0.0%). Every post with an accomplishment that was repeating was associated with an average of 0.2% greater weight loss (95% CI -0.3% to 0.0%). Sharing other types of goals and accomplishments was not associated with weight loss. CONCLUSIONS: In a web-based weight loss intervention, stating goals in repeating or both measurable and repeating terms was associated with greater weight loss, but simply stating them in measurable terms was not. For accomplishments, only those articulated in repeating terms were associated with greater weight loss. Posts about one-time goals and accomplishments represent an opportunity to encourage planning for future behaviors. Future research should examine if stating goals and accomplishments in repeating terms signals habit formation.

BabyByte: Qualitative Research to Inform the Development of an App to Improve Responsive Feeding Practices in Parents of Infants and Toddlers.

Responsive feeding is associated with a reduced risk of childhood obesity. The objective of this qualitative study was to determine parental preferences for mobile health (mHealth) app content and features designed to improve responsive feeding practices. Parents of 0-2-year-old children were interviewed individually. Interview questions were informed by the Technology Acceptance Model, and parents provided feedback on sample app content and features. Interviews were audio-recorded, transcribed verbatim, and coded by two researchers using thematic analysis; responses were compared by parent gender and income. Parents (n = 20 fathers, n = 20 mothers) were, on average, 33 years old, low-income (50%), identified as non-white (52.5%), and had a bachelor's degree or higher (62%). Overall, parents were most interested in feeding tips and recipe content, and app features that allowed tracking child growth and setting feeding goals. Fathers were most interested in content about first foods, choking hazards, and nutrition information, while mothers preferred content on breastfeeding, picky eating, and portion sizes. Parents with lower incomes were interested in nutrition guidelines, breastfeeding, and introducing solids. Non-low-income parents preferred information related to food allergies, portion sizes, and picky eating. The findings of this study provide considerations when developing mHealth apps to improve responsive feeding practices in parents.

Pre-Enrollment Steps and Run-Ins in Weight Loss Trials: A Meta-Regression.

INTRODUCTION: The generalizability of study findings may be influenced by pre-enrollment trial procedures, including the use of behavioral run-in periods. The study goals were to determine whether behavioral run-in periods and other pre-enrollment processes affect outcomes in randomized trials of behavioral weight loss interventions that have contributed to clinical guidelines. METHODS: The sample was behavioral weight loss intervention trials included in the 2018 U.S. Preventive Services Task Force systematic review. Information on pre-enrollment processes (total steps, in-person steps, behavioral run-in) was abstracted, and meta-regressions were conducted in 2022 to test whether pre-enrollment processes were associated with weight loss at 6 or 12 months and trial retention at 12 months. RESULTS: Across 80 trials, the median number of total pre-enrollment steps was 2 (range=1-5), and that of in-person pre-enrollment steps was 1 (range=0-4). Almost one-third of the trials (k=24; 30%) used a behavioral run-in. The most common run-in tasks were self-monitoring physical activity (k=9) or both physical activity and diet (k=6). Greater weight loss was observed in trials with behavioral run-ins at 6 months (-2.33 kg; 95% CI= -3.72, -0.93) and, to an attenuated extent, at 12 months (-0.86 kg; 95% CI= -1.72, 0.01) compared to those without run-ins. The total number of pre-enrollment steps was also associated with greater 6-month weight loss (-0.85 kg; 95% CI= -1.59, -0.11). Higher retention was associated with total number of pre-enrollment steps and in-person steps and marginally with the presence of run-ins. DISCUSSION: The use of more pre-enrollment processes is associated with greater weight loss in behavioral weight loss trials and may impact the generalizability of outcomes.

Behavior change techniques in digital physical activity interventions for breast cancer survivors: a systematic review.

Given the broad benefits of physical activity (PA) but low PA levels among breast cancer survivors (i.e., women who have received a breast cancer diagnosis), innovative and evidence-based techniques are needed to motivate and support exercise. This study systematically reviews the use of behavior change techniques (BCTs) in digital PA interventions for breast cancer survivors. Studies were retrieved from five electronic databases and were included if they (i) sampled exclusively female breast cancer survivors aged >18 years, (ii) involved a digital intervention with the primary purpose of increasing PA, (iii) included a BCT component, (iv) used a randomized or quasi-randomized design, and (v) were published from January 2000 to May 2022. Two coders independently extracted data. Twenty primary studies met the inclusion criteria and were included in this review. All interventions used at least one BCT (mean 4 ± 1, range 2-13); self-monitoring (85%) and goal setting (79%) were the most common BCTs. Twelve of 20 (60%) studies reported improvements in PA behavior in the intervention vs. control group, and self-monitoring and goal setting were the most commonly used BCTs in these studies. Of the 93 total BCTs, 66 were not used in any interventions in the review, including critical constructs for PA behavior change (e.g., biofeedback). BCTs, important facilitators of PA behavior change, are being underutilized in digital PA interventions for breast cancer survivors. Future research should incorporate more diverse BCTs to explore if they can add to the effectiveness of digital interventions for this population.

Physical activity (PA) has many benefits, yet PA levels are low among breast cancer survivors (i.e., women who have received a breast cancer diagnosis). This study reviews the use of behavior change techniques (BCTs) in digital PA interventions for breast cancer survivors. BCTs are evidence-based and are important for encouraging changes in health behaviors, such as PA. Twenty studies were included in this review. All interventions used at least one BCT (mean 4 ± 1, range 2­13); self-monitoring (85%) and goal setting (79%) were the most common BCTs. Twelve of 20 (60%) studies reported improvements in PA, and self-monitoring and goal setting were the most commonly used BCTs in these studies. Of the 93 total BCTs, 66 were not used in any interventions in the review. This finding reveals that many BCTs, which are important influencers of behavior change, are often not being used in digital PA interventions for breast cancer survivors. BCTs such as biofeedback (e.g., providing information on heart rate during exercise) and practical social support (e.g., virtual exercise coaching), could be helpful. Future research should include more diverse BCTs to explore if they can add to the usefulness of digital interventions for this population.

Privacy Concerns in Group Format Lifestyle Interventions for Obesity.

BACKGROUND: Group format weight loss interventions have benefits over individual format, but privacy concerns may limit their uptake. METHOD: In this study, adults with obesity and interest in losing weight were recruited nationally online and randomly assigned to view one of eight videos describing a hypothetical, group behavioral weight loss intervention. Based on three fully crossed factors, the videos varied on privacy features of intervention (present or not); matching participants to group based on weight loss barriers (matched or not); and intervention format (online or in-person). Participants rated their willingness to join, privacy concerns, and perceived effectiveness of these interventions. They further reported preference for individual or group format interventions and reason for preferences. RESULTS: Description of privacy features, matching of participants, and format did not affect willingness to join, privacy concerns, or perceived effectiveness of the intervention. Privacy concerns were associated with lower willingness to join and lower perceived intervention effectiveness, and greater social anxiety and weight stigma. More participants preferred individual over group format (40.1% vs 33.9%; 26% selected neither) and preference for individual format was associated with greater privacy concerns. CONCLUSION: Strategies to address privacy concerns in group-based interventions warrant further attention.

Lifetime Exposure to Cigarette Smoke and Risk of Ovarian Cancer by T-cell Tumor Immune Infiltration.

BACKGROUND: Exposure to cigarette smoke, particularly in early life, is modestly associated with ovarian cancer risk and may impact systemic immunity and the tumor immune response. However, no studies have evaluated whether cigarette smoke exposure impacts the ovarian tumor immune microenvironment. METHODS: Participants in the Nurses' Health Study (NHS) and NHSII reported on early life exposure to cigarette smoke and personal smoking history on questionnaires (n = 165,760). Multiplex immunofluorescence assays were used to measure markers of T cells and immune checkpoints in tumor tissue from 385 incident ovarian cancer cases. We used Cox proportional hazards models to evaluate HRs and 95% confidence intervals (CI) for developing ovarian tumors with a low (

Engaging primary care patients with existing online tools for weight loss: A pilot trial.

Objective: Free online tools show potential for promoting weight loss at a low cost, but there is limited evidence about how to effectively engage patients with them. To address this, a low-dose, flexible intervention was developed that aims to enhance weight-related discussions with primary care providers (PCPs) and engage patients with an organic (i.e., not researcher-created) weight loss-focused social media community and online self-monitoring tool. Feasibility and acceptability of the intervention was evaluated in a single-arm, 12-week pilot. Methods: PCPs were recruited at two clinics, then PCP's patients with upcoming appointments were identified and recruited. Patients received an interactive online kickoff before their scheduled primary care appointment, then 8 follow-up messages over 12 weeks via email or their electronic health record patient portal. Patients completed assessments at baseline, post-appointment, and week 12. Primary care providers and patients completed semi-structured interviews. Results: All PCPs approached enrolled (n = 6); patient recruitment was on track to meet the study goal prior to COVID-19 restrictions, and n = 27 patients enrolled. Patient satisfaction with the pre-appointment kickoff was high. Twenty-four patients reported discussing weight-related topics at their primary care appointment and all were satisfied with the discussion. Twenty-two patients completed 12-week assessments. Of these, 15 reported engaging with the self-monitoring tool and 9 with the social media community. Patient interviews revealed reasons for low social media community engagement, including perceived lack of fit. On average, patients with available data (n = 21) lost 2.4 ± 4.1% of baseline weight, and 28.6% of these patients lost ≥3% of baseline weight. Primary care providers reported high intervention satisfaction. Conclusions: The intervention and trial design show potential, although additional strategies are needed to promote tool engagement.

Relative reinforcement from physical activity in real-world environments: a novel application of behavioral economics.

Behavioral economics suggests that individuals are likely to engage in a behavior if it is more reinforcing and readily available than other possible options. In real-world environments, sedentary behaviors are often more reinforcing and easily available than physical activities. In order to promote regular physical activity in an environment with sedentary alternatives, it is important to understand the proportion of overall reinforcement that is derived from physical activity (i.e., relative reinforcement, RR). Conceptually similar laboratory-research supports this notion, but applications to individual, real-world environments remain understudied. The current study used a novel survey-based approach to estimate the RR of common physical activities. Healthy adults (N = 348, M age = 39.0 ± 8.7) from the United States completed an online survey between April-May 2020, including a modified activity survey with ten physically active and ten sedentary activities. Regression analysis showed that total RR of physical activity was related to greater physical activity levels when controlling for enjoyment and other covariates. Four factors were identified (household, conditioning, sports, and outdoor activities) using exploratory structural equation modeling, but internal consistency was limited when items were constrained to each factor in the structural equation model. Previous laboratory findings on overall RR of physical activity were replicated with the survey-based measure, but further improvement for relative reinforcement of different sub-domains of physical activity is needed. Researchers and practitioners can use this survey to determine attractive physical activities on the individual level that can compete with sedentary leisure activities.

Engaging adults with obesity in organic online communities to support weight loss: a mixed methods pilot study.

OBJECTIVES: Organic online communities have shown potential for aiding weight loss, but few adults use them. We sought to test strategies to encourage adults to select and engage in online communities for weight loss. DESIGN: 4-week single-arm, mixed-methods pilot. MAIN OUTCOME MEASURES: Quantitative and qualitative data on selection of online community, engagement with community, and engagement and satisfaction with tasks. RESULTS: On average, participants (n = 25) were female (80.0%) and white (68.0%), 45.2 ± 18.1 years old, with a BMI of 36.2 ± 6.5 kg/m2. Selection of online community varied across participants (13 MyFitnessPal, 5 Facebook, 5 Reddit). In qualitative analyses, reasons for selection included experience with community, privacy considerations, and seeking people similar to them. Most tasks were fully or partially completed by a majority of participants (>80.0%). For most tasks, ∼50% of participants felt the task helped them with weight loss support. Variability in response was observed, especially between tasks that requested reading compared to posting/commenting in the community. Frequent reading of community content throughout the study was reported by >70.0% of participants, though posting/commenting was less frequent. Barriers to further engagement included concerns about privacy, judgement, and misinformation. CONCLUSIONS: This study provides insights about strategies for engaging individuals in online health communities.

The Faith, Activity, and Nutrition (FAN) dissemination and implementation study: changes in and maintenance of organizational practices over 24 months in a statewide initiative.

BACKGROUND: Few studies have examined the impact of ecological health promotion interventions on organizational practices over time, especially in faith-based settings. This statewide dissemination and implementation study examined change in organizational practices and their predictors across a 24-month period, as well as maintenance of change. METHODS: Using a pre-post quasi-experimental design, church coordinators from 92 United Methodist Churches in South Carolina (42% predominantly African American congregations) completed surveys at baseline, and immediate, 12-, and 24-months post-training regarding physical activity (PA) and healthy eating (HE) organizational practices consistent with the Faith, Activity, and Nutrition (FAN) program (opportunities, policies, pastor support, messages) and possible predictors. The study was guided by the RE-AIM framework and the Consolidated Framework for Implementation Research (CFIR). Mixed model repeated measures analyses examined change in organizational practices over time. Regression models examined CFIR predictors of 24-month PA and HE organizational practices, controlling for baseline practices. Churches were also classified as maintainers (implemented at 12 and 24 months), non-sustained implementers (implemented at 12 but not 24 months), delayed implementers (implemented at 24 but not 12 months), and low implementers (implemented at neither 12 nor 24 months) for each FAN component. RESULTS: PA and HE organizational practices increased over time (p < .0001). CFIR domains (and constructs within) of intervention characteristics (adaptability, relative advantage, cost/time), inner setting (relative priority, organizational rewards, readiness, congregant needs), characteristics of the implementer (self-efficacy, perceived benefits), and implementation process (engaging opinion leaders, engaging champions) were important predictors of 24-month PA and HE organizational practices. Over half of churches implementing PA policies, PA messages, HE policies, and HE opportunities at 12 months were maintainers at 24 months, and one-third were maintainers for PA opportunities, HE messages, and PA and HE pastor support. Furthermore, 16% of 12-month non-implementers were delayed implementers at 24 months for PA policies and 31% were delayed implementers for HE policies. CONCLUSIONS: This study makes important contributions to the faith-based health promotion literature by including a large sample of churches, testing an ecological intervention approach, and assessing organizational practices over a 24-month period. Study findings can guide technical assistance and program adaptations over time. TRIAL REGISTRATION: This study was registered in clinicaltrials.gov NCT02868866 on August 16, 2016.

Reporting of Physical Activity Device Measurement and Analysis Protocols in Lifestyle Interventions.

This systematic review examined the extent to which lifestyle physical activity interventions that used wearable devices (eg, pedometers, accelerometers) reported on the length of device wear time requested in their protocols, criteria for analytic inclusion of data, and participant compliance with device use protocols. Literature were searches were conducted using PubMed, Cochrane Central Register, and PsychInfo. Studies were included if they were the main outcomes paper of a trial that reported on a randomized or quasi-randomized trial focused on increasing lifestyle physical activity and were published between January 1, 2006 and March 30, 2016. Titles and abstracts were screened by 2 independent reviewers; eligible full texts were retrieved and reviewed by 2 independent reviewers. A total of 104 studies used wearable devices (n = 57 pedometers, n = 47 accelerometers). Most studies (n = 65, 67.3%) asked participants to wear devices for 7 days. Almost half of the studies (n = 46, 44.2%) did not report minimum device wear time required for analytic inclusion of data, and variation existed among studies reporting these criteria. Most studies (n = 60, 57.7%) did not report average device wear time, or participant compliance with device wear. Overall, there was heterogeneity in reporting of physical activity device data. Refinement and streamlining of guidelines for device use, analysis, and reporting of data could improve comparability across studies.

Lessons Learned: Beta-Testing the Digital Health Checklist for Researchers Prompts a Call to Action by Behavioral Scientists.

Digital technologies offer unique opportunities for health research. For example, Twitter posts can support public health surveillance to identify outbreaks (eg, influenza and COVID-19), and a wearable fitness tracker can provide real-time data collection to assess the effectiveness of a behavior change intervention. With these opportunities, it is necessary to consider the potential risks and benefits to research participants when using digital tools or strategies. Researchers need to be involved in the risk assessment process, as many tools in the marketplace (eg, wellness apps, fitness sensors) are underregulated. However, there is little guidance to assist researchers and institutional review boards in their evaluation of digital tools for research purposes. To address this gap, the Digital Health Checklist for Researchers (DHC-R) was developed as a decision support tool. A participatory research approach involving a group of behavioral scientists was used to inform DHC-R development. Scientists beta-tested the checklist by retrospectively evaluating the technologies they had chosen for use in their research. This paper describes the lessons learned because of their involvement in the beta-testing process and concludes with recommendations for how the DHC-R could be useful for a variety of digital health stakeholders. Recommendations focus on future research and policy development to support research ethics, including the development of best practices to advance safe and responsible digital health research.

Methods-Motivational Interviewing Approach for Enhanced Retention and Attendance.

INTRODUCTION: Suboptimal and differential participant engagement in randomized trials-including retention at primary outcome assessments and attendance at intervention sessions-undermines rigor, internal validity, and trial conclusions. METHODS: First, this study describes Methods-Motivational Interviewing approach and strategies for implementation. This approach engages potential participants before randomization through interactive, prerequisite orientation sessions that illustrate the scientific rationale behind trial methods in accessible language and use motivational interviewing to diffuse ambivalence about participation. Then, this study examines the potential improvements in retention (proportion of participants assessed at follow-up visits) and attendance (e.g., mean percentage of intervention sessions attended, percentage of participants who attended 0 sessions) in 3 randomized weight-management trials that quickly added prerequisite orientations to their protocols following early signs of suboptimal or differential participant engagement (Supporting Health by Integrating Nutrition and Exercise [2009-2013, n=194]; Get Social [2016-2020, n=217]; GestationaL Weight Gain and Optimal Wellness [2014-2018, n=389]). Using a pre-post analytical design, adjusted estimates from regression models controlling for condition and assessment timepoint (analyses from 2020) are reported. RESULTS: After adding prerequisite orientations, all 3 trials attained higher participant engagement. Retention at assessments was 11.4% and 17.3% higher (Get Social and Supporting Health by Integrating Nutrition and Exercise, respectively). Mean percentage of attendance at intervention sessions was 8.8% higher (GestationaL Weight Gain and Optimal Wellness), and 10.1% fewer participants attended 0 intervention sessions (Get Social). Descriptively, all the remaining retention and attendance outcomes were consistently higher but were nonsignificant. Across the trials, adding prerequisite orientations did not impact the proportion of eligible participants enrolled or the baseline demographics. CONCLUSIONS: The Methods-Motivational Interviewing approach shows promise for increasing the rigor of randomized trials and is readily adaptable to in-person, webinar, and conference call formats. TRIAL REGISTRATION: All 3 trials are registered at www.clinicaltrials.gov (Supporting Health by Integrating Nutrition and Exercise: NCT00960414; Get Social: NCT02646618; and GestationaL Weight Gain and Optimal Wellness: NCT02130232).

Early life physical activity and risk of ovarian cancer in adulthood.

Emerging data suggest that exposures in early life may affect ovarian development and contribute to ovarian cancer risk. We evaluated the association between early life physical activity and risk of ovarian cancer in adulthood in two large prospective cohorts, the Nurses' Health Study (NHS) and NHSII. In total, analyses included 28 232 NHS participants (followed from 2004 to 2016) and 56 553 NHSII participants (followed from 1997 to 2017). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of ovarian cancer overall and by early life body mass index (BMI). Neither physical activity at ages 12-13, 14-17 or 18-22 years nor average physical activity across these three periods was associated with ovarian cancer risk overall (≥78 vs <24 MET-h/wk, HRs = 1.34, 1.21, 1.08 and 1.24, respectively), or by categories of early life BMI (Pheterogeneity ≥ .44). No association was observed with the risk of high-grade serous or poorly differentiated tumors or postmenopausal ovarian cancer. Overall, early life physical activity was not clearly related to ovarian cancer risk during adulthood.

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review.

BACKGROUND: Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood. OBJECTIVE: This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices. METHODS: We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood. RESULTS: There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA. CONCLUSIONS: Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

Pathways of influences leading to adoption of the Faith, Activity and Nutrition (FAN) program in a statewide initiative.

RE-AIM (Reach, effectiveness, Adoption, Implementation, Maintenance) and CFIR (Consolidated Framework for Implementation Research) are complementary frameworks guiding research on dissemination and implementation of evidence-based interventions and factors influencing this process. Faith, Activity, and Nutrition (FAN) is an evidence-based program that increased physical activity and fruit and vegetable intake in faith-based settings. The aims of this adoption study were to quantify state-wide church level adoption rates and congregant reach of FAN in accordance with RE-AIM guidelines, and to explore the association of CFIR-derived constructs of the church inner setting and pastor characteristics with FAN adoption. Church recruitment was documented, and data were collected via telephone-administered surveys from 93 pastors in adopting churches and 60 pastors in non-adopting churches. Qualitative Comparative Analysis (QCA) identified combinations of CFIR-derived church and pastor characteristics sufficient for FAN adoption. As defined by RE-AIM, church-level FAN adoption was 11.7 % and congregant-level reach was 20.0 %. Fourteen pathways to adoption were identified; seven of these featured the presence of a culture of concern for congregant health along with openness to new ideas. Results suggest early assessment of these two CFIR-derived inner setting constructs may help identify faith-based organizations predisposed to undertake a comprehensive, environmental intervention to promote congregant health.

Early life exposure to tobacco smoke and ovarian cancer risk in adulthood.

BACKGROUND: Ovarian cancer risk in adulthood may be affected by early life exposure to tobacco smoke. We investigated this relationship in two large prospective cohorts, the Nurses' Health Study (NHS) and NHSII. METHODS: In total, analyses included 110 305 NHS participants (1976-2016) and 112 859 NHSII participants (1989-2017). Self-reported early life smoking exposures were queried at baseline or follow-up questionnaires. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of ovarian cancer overall and by tumour histotype. RESULTS: Overall, ovarian cancer risk was not different among participants whose mothers did versus did not smoke during pregnancy (HR = 1.05, 95% CI: 0.87-1.27); however, an increased risk was observed among women who themselves were never smokers (HR = 1.38, 95% CI: 1.05-1.81) but not among ever smokers (HR = 0.86, 95% CI: 0.66-1.14; Pheterogeneity = 0.02). Compared with women who never smoked, ovarian cancer risk was similar for women who started to smoke at age <18 (HR = 0.98, 95% CI: 0.86-1.11) or ≥18 (HR = 1.02, 95% CI: 0.93-1.12). These associations did not differ by histotype (Pheterogeneity ≥0.35). Parental smoking in the home during childhood/adolescence was related to a 15% increased risk of ovarian cancer in adulthood (HR = 1.15, 95% CI: 1.04-1.27) and this association was suggestively stronger among women with non-serous/low-grade serous tumours (HR = 1.28, 95% CI: 1.02-1.61) versus high-grade serous/poorly differentiated tumours (HR = 1.09, 95% CI: 0.93-1.28; Pheterogeneity = 0.25). CONCLUSIONS: Exposure to parental tobacco smoke in the home, but not early initiation of smoking, was associated with a modest elevated risk of ovarian cancer. Further investigations are required to confirm these findings and elucidate underlying mechanisms.

Effects of sleep deprivation on endothelial function in adult humans: a systematic review.

Sleep deprivation is highly prevalent and is associated with increased cardiovascular disease (CVD) morbidity and mortality. Age-related alterations in sleep and chronobiology may exaggerate CVD susceptibility in older individuals. The mechanisms responsible for the association between sleep deprivation and CVD are not fully understood, but endothelial dysfunction may play a central role. Our objective was to conduct a systematic literature review to evaluate the evidence on the effects of sleep deprivation on endothelial function (EF). This review adhered to the PRISMA guidelines and was pre-registered with PROSPERO (#CRD42020192485, 07/24/2020). We searched PubMed, Web of Science, Embase, and Cochrane Library for articles published through May 1, 2020. Eligibility criteria included publication in English and use of well-established EF methodologies in adult humans. Two investigators independently performed the literature search, study selection, data extraction, risk-of-bias assessment, and qualitative data synthesis. Out of 3571 articles identified, 24 articles were included in the systematic review. Main findings include the following: (1) shorter sleep duration is associated with lower macrovascular EF; (2) not sleeping 7-9 h/night is linked with impaired microvascular EF; (3) sleep restriction impairs micro- and macrovascular EF; (4) acute total sleep deprivation impairs micro- and macrovascular EF but data on macrovascular EF are less consistent; and (5) shift work impairs macrovascular EF. In conclusion, sleep deprivation impairs EF, which may explain the link between insufficient sleep and CVD. Future investigations should fully elucidate the underlying mechanisms and develop strategies to combat the adverse endothelial effects of sleep deprivation across the lifespan.