OBJECTIVE:Across the lifespan, more women than men report abdominal bloating. However, little is known about bloating during the menopause transition (MT). The purpose of this study was to assess patterns of bloating severity during the MT in relation to age, reproductive aging stage, reproductive- and stress-related biomarkers, and stress-related perceptions in a longitudinal cohort study. METHODS:This analysis included 291 women from the Seattle Midlife Women's Health Study who provided health diary data and could be classified into reproductive aging stages. A subset of 131 women also provided urine samples, which were assayed for estrone glucuronide, follicle-stimulating hormone, testosterone, cortisol, norepinephrine, and epinephrine levels. Mixed-effects multilevel modeling was used to examine the relationship between bloating severity and age, reproductive aging stages, reproductive- and stress-related biomarkers, and stress-related perceptions. RESULTS:In the univariate model, the early MT stage, tension, and anxiety were associated with increased bloating severity, whereas the early postmenopausal stage and testosterone levels were associated with decreased bloating severity. In the multivariate model, both the early and late MT stages were related to an increase in bloating severity. Age and testosterone levels were associated with decreased bloating severity. Tension was related to increased bloating severity. CONCLUSIONS:Tension and anxiety may play a role in increased bloating severity, whereas testosterone levels and age are associated with decreased bloating severity. The MT stage may contribute to bloating through several mechanisms. More research is needed to fully elucidate these relationships.

Objective: To examine the association between race/ethnicity and type 2 diabetes risk in women and assess the interaction between race/ethnicity and body mass index (BMI). Research design and methods: We analysed individual-level data from 730,408 women across 15 cohort studies. Six racial/ethnic groups were identified: White, Chinese, Japanese, South/Southeast Asian, Black, and Mixed/Other. Cox proportional hazards models with study as a random effect were used to estimate hazard ratios (HRs) for type 2 diabetes associated with race/ethnicity. The joint association of race/ethnicity and BMI was assessed using BMI categories incorporating Asian-specific cutoffs (<18.5, 18.5-22.9, 23.0-24.9, 25.0-27.4, 27.5-29.9, and ≥30 kg/m2), with White women having a BMI of 18.5-22.9 kg/m2 as the reference. Results: Overall, 37,329 (5.1%) women were diagnosed with type 2 diabetes. By age 70, the cumulative incidence was highest among South/Southeast Asian (24.6%) and Black women (23.6%), with baseline obesity rates of 40.0% (BMI ≥27.5 kg/m²) and 45.6% (BMI ≥30 kg/m²), respectively. After adjusting for BMI, South/Southeast Asian women had the highest diabetes risk compared with White women (HR:4.13, 95%CI 3.78-4.51), while other racial/ethnic groups had about twice the risk. Joint effect analysis showed South/Southeast Asian women with a BMI ≥23 kg/m2 had a substantially greater diabetes risk than other racial/ethnic groups with the same BMI, especially those with BMI 27.5-29.9 kg/m2 (HR:23.17, 19.21-27.95) and ≥30 kg/m2 (HR:35.52, 30.57-41.28). Conclusions: South/Southeast Asian women have a markedly elevated risk of type 2 diabetes, further amplified by modestly higher BMI, highlighting the need for ethnicity-specific diabetes prevention strategies for women.

Background Rising rates of psychological distress (symptoms of depression, anxiety, and stress) among adults in the United States necessitate effective mental wellness interventions. Despite the prevalence of smartphone app–based programs, research on their efficacy is limited, with only 14% showing clinically validated evidence. Our study evaluates Noom Mood, a commercially available smartphone-based app that uses cognitive behavioral therapy and mindfulness-based programming. In this study, we address gaps in the existing literature by examining postintervention outcomes and the broader impact on mental wellness. Objective Noom Mood is a smartphone-based mental wellness program designed to be used by the general population. This prospective study evaluates the efficacy and postintervention outcomes of Noom Mood. We aim to address the rising psychological distress among adults in the United States. Methods A 1-arm study design was used, with participants having access to the Noom Mood program for 16 weeks (N=273). Surveys were conducted at baseline, week 4, week 8, week 12, week 16, and week 32 (16 weeks’ postprogram follow-up). This study assessed a range of mental health outcomes, including anxiety symptoms, depressive symptoms, perceived stress, well-being, quality of life, coping, emotion regulation, sleep, and workplace productivity (absenteeism or presenteeism). Results The mean age of participants was 40.5 (SD 11.7) years. Statistically significant improvements in anxiety symptoms, depressive symptoms, and perceived stress were observed by week 4 and maintained through the 16-week intervention and the 32-week follow-up. The largest changes were observed in the first 4 weeks (29% lower, 25% lower, and 15% lower for anxiety symptoms, depressive symptoms, and perceived stress, respectively), and only small improvements were observed afterward. Reductions in clinically relevant anxiety (7-item generalized anxiety disorder scale) and depression (8-item Patient Health Questionnaire depression scale) criteria were also maintained from program initiation through the 16-week intervention and the 32-week follow-up. Work productivity also showed statistically significant results, with participants gaining 2.57 productive work days from baseline at 16 weeks, and remaining relatively stable (2.23 productive work days gained) at follow-up (32 weeks). Additionally, effects across all coping, sleep disturbance (23% lower at 32 weeks), and emotion dysregulation variables exhibited positive and significant trends at all time points (15% higher, 23% lower, and 25% higher respectively at 32 weeks). Conclusions This study contributes insights into the promising positive impact of Noom Mood on mental health and well-being outcomes, extending beyond the intervention phase. Though more rigorous studies are necessary to understand the mechanism of action at play, this exploratory study addresses critical gaps in the literature, highlighting the potential of smartphone-based mental wellness programs to lessen barriers to mental health support and improve diverse dimensions of well-being. Future research should explore the scalability, feasibility, and long-term adherence of such interventions across diverse populations.

Background Accessible self-management interventions are required to support people living with breast cancer. Objective This was an industry-academic partnership study that aimed to collect qualitative user experience data of a prototype app with built-in peer and coach support designed to support the management of health behaviors and weight in women living with breast cancer. Methods Participants were aged ≥18 years, were diagnosed with breast cancer of any stage within the last 5 years, had completed active treatment, and were prescribed oral hormone therapy. Participants completed demographic surveys and were asked to use the app for 4 weeks. Following this, they took part in in-depth qualitative interviews about their experiences. These were analyzed using thematic analysis. Results Eight participants (mean age, 45 years; mean time since diagnosis, 32 months) were included. Of the 8 participants, 7 (88%) were white, 6 (75%) had a graduate degree or above, and 6 (75%) had stage I-III breast cancer. Four overarching themes were identified: (1) Support for providing an app earlier in the care pathway; (2) Desire for more weight-focused content tailored to the breast cancer experience; (3) Tracking of health behaviors that are generally popular; and (4) High value of in-app social support. Conclusions This early user experience work showed that women with breast cancer found an app with integrated social and psychological support appealing to receive support for behavior change and weight management or self-management. However, many features were recommended for further development. This work is the first step in an academic-industry collaboration that would ultimately aim to develop and empirically test a supportive app that could be integrated into the cancer care pathway.

BACKGROUND:There is little understanding of men's weight loss outcomes and behaviors in self-directed contexts, such as digital commercial mobile weight management programs. This is an especially pressing question given that men often express disinterest in weight management programs and it is unknown how that manifests in self-directed environments. Aims. Two studies fill this gap by retrospectively observing how men lose weight and engage in weight loss behaviors (Study 1) and their perceptions of improvements and gained knowledge (Study 2) when participating in the full length of a commercial mobile behavior change program called Noom.METHOD:In Study 1, repeated-measures linear mixed modeling was used to examine whether weight loss was statistically significant from baseline to 16 weeks and how engagement behaviors predicted weight in a sample of 7,495 male Noom users. In Study 2, 971 male Noom users completed an exploratory survey on the impact of the behavior change education in the program.RESULTS:In Study 1, men who remained in the full length of the program lost statistically significant weight from baseline to 16 weeks. 63% achieved clinically meaningful (5% or more) weight loss. Engagement in weight loss behaviors on the program predicted the amount of weight lost. In Study 2, men reported learning most about practical application and psychological aspects relating to food and psychology.DISCUSSION AND CONCLUSION:This is the first study to observe men's weight loss outcomes, behaviors, and perceptions of what they learned in a self-directed behavior change program. Our findings have important implications for more effective health promotion for the many men who choose to self-direct their weight loss.

12070 Background: Post-diagnosis weight gain is common among women with early-stage breast cancer and is associated with increased risk of recurrence, breast cancer death, and all-cause mortality. Intentional weight loss following diagnosis is difficult to maintain. Targeted lifestyle interventions focusing on behavioral changes and education that can be implemented long-term are needed. Methods: This was a prospective single-arm pilot study in patients with history of early-stage breast cancer (NCT04753268). Key eligibility criteria included body mass index (BMI) ≥27.5 kg/m2, stage I-III breast cancer, and completion of active cancer treatment ≥6 months prior to study enrollment. Patients were recruited at the Dempsey Center in Lewiston, ME and via social media. Participants were given access to the Noom mobile application, which utilizes cognitive behavioral therapy, motivational interviewing, and self-determination theory to induce behavior change using an educational curriculum of daily articles, virtual health coaching, social networking, food records, and physical activity logs. The primary endpoint was change in self-reported weight from baseline to 26 weeks. Secondary endpoints included change in physical activity measured using step count and the Global Physical Activity Questionnaire (GPAQ), change in diet patterns analyzed using the Nutrition Data System for Research, patient-reported outcome (PRO) measures, and metrics for engagement with the mobile application. Results: 31 patients were enrolled; 24 at the Dempsey Center and 7 via social media. Mean age was 56.8 and mean baseline BMI was 33.5 kg/m2. Mean weight change was -4.8 kg (range +0.6 to -19.9 kg, p < 0.001) and mean percent weight change was -5.6%; 11/31 patients (35.5%) lost ≥5% of their initial weight. Average daily step count increased by 54.7% (p = 0.004). Mean GPAQ score for physical activity increased from 990 to 1773 (p = 0.01), and the proportion of patients who met physical activity guidelines increased from 45.1% to 74.2%. Mean energy intake did not change significantly over 26 weeks (p = 0.779). Improvements were observed in PROMIS-Physical Functioning T-scores and Body Image Scale scores (p = 0.04, p < 0.001 respectively). Metrics of engagement with Noom that were predictive of weight loss ≥5% included total articles read (p = 0.012), total weights logged (p = 0.006), total food records logged (p = 0.001), messages sent to coach (p = 0.001), and number of times the application was opened (p = 0.014). Conclusions: In this pilot study, breast cancer survivors lost weight and became more physically active using a commercially-available mobile application. This digital weight loss program is a scalable intervention, and these findings support future studies investigating impact on breast cancer outcomes. Clinical trial information: NCT04753268 .

The Noom Weight program is a smartphone-based weight management program that uses cognitive behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention. This retrospective database analysis aimed to evaluate the impact of Noom Weight use on health care resource utilization (HRU) and health care costs among individuals with overweight and obesity. Electronic health record data, insurance claims data, and Noom Weight program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non–Noom Weight users aged between 18 and 80 years with a BMI of ≥25 kg/m² and residing in the United States. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week on average. Inverse probability treatment weighting was used to balance sociodemographic covariates between the 2 cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed. Within 12 months after the index date, Noom Weight users had less inpatient costs (mean difference [MD] −US $20.10, 95% CI −US $30.08 to −US $10.12), less outpatient costs (MD −US $124.33, 95% CI −US $159.76 to −US $88.89), less overall prescription costs (MD −US $313.82, 95% CI −US $565.42 to −US $62.21), and less overall health care costs (MD −US $450.39, 95% CI −US $706.28 to −US $194.50) per user than non–Noom Weight users. In terms of HRU, Noom Weight users had fewer inpatient visits (MD −0.03, 95% CI −0.04 to −0.03), fewer outpatient visits (MD −0.78, 95% CI −0.93 to −0.62), fewer surgeries (MD −0.01, 95% CI −0.01 to 0.00), and fewer prescriptions (MD −1.39, 95% CI −1.76 to −1.03) per user than non–Noom Weight users. Among a subset of individuals with 24-month follow-up data, Noom Weight users incurred lower overall prescription costs (MD −US $1139.52, 95% CI −US $1972.21 to −US $306.83) and lower overall health care costs (MD −US $1219.06, 95% CI −US $2061.56 to −US $376.55) per user than non–Noom Weight users. The key differences were associated with reduced prescription use. Noom Weight use is associated with lower HRU and costs than non–Noom Weight use, with potential cost savings of up to US $1219.06 per user at 24 months after the index date. These findings suggest that Noom Weight could be a cost-effective weight management program for individuals with overweight and obesity. This study provides valuable evidence for health care providers and payers in evaluating the potential benefits of digital weight loss interventions such as Noom Weight.

AbstractBackgroundBehavioral weight loss programs often lead to significant short‐term weight loss, but long‐term weight maintenance remains a challenge. Most weight maintenance data come from clinical trials, in‐person programs, or general population surveys, but there is a need for better understanding of long‐term weight maintenance in real‐world digital programs.MethodsThis observational survey study examined weight maintenance reported by individuals who had used Noom Weight, a digital commercial behavior change program, and identified factors associated with greater weight maintenance. The cross‐sectional survey was completed by 840 individuals who had lost at least 10% of their body weight using Noom Weight 6–24 months prior.ResultsThe study found that 75% of individuals maintained at least 5% weight loss after 1 year, and 49% maintained 10% weight loss. On average, 65% of initial weight loss was maintained after 1 year and 57% after 2 years. Habitual behaviors, such as healthy snacking and exercise, were associated with greater weight maintenance, while demographic factors were not.ConclusionThis study provides real‐world data on the long‐term weight maintenance achieved using a fully digital behavioral program. The results suggest that Noom Weight is associated with successful weight maintenance in a substantial proportion of users. Future research will use a randomized controlled trial to track weight maintenance after random assignment and at a 2 year follow‐up.

Background: The Noom Weight program is a smartphone-based weight management program that utilizes cognitive-behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention. Objective: This retrospective database analysis aimed to evaluate the impact of Noom Weight use on healthcare resource utilization (HRU) and healthcare costs among overweight and obese patients. Methods: Electronic health records (EHR) data, claims data, and Noom program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non-Noom users aged 18-80 with a body mass index (BMI) ?25 kg/m² and residing in the U.S. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week, on average. Inverse probability treatment weighting (IPTW) was used to balance sociodemographic covariates between the two cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed. Results: Within 12 months post-index, Noom Weight users had, on average, $20.10 less inpatient costs (95% CI: -$30.08, -$10.12), $124.33 less outpatient costs (95% CI: -$159.76, -$88.89), $313.82 less overall prescription costs (95% CI: -$565.42, -$62.21), and $450.39 less overall healthcare costs (95% CI: -$706.28, -$

Background & Aims: Lifestyle intervention remains the foundation of clinical care for patients with NASH; however, most patients are unsuccessful in enacting sustained behavioral change. There remains a clear unmet need to develop lifestyle intervention programs to support weight loss. Mobile health (mHealth) programs offer promise to address this need, yet their efficacy remains unexplored. Approach & Results: We conducted a 16-week randomized controlled clinical trial involving adults with NASH. Patients were randomly assigned (1:1 ratio) to receive Noom Weight (NW), a mHealth lifestyle intervention program, or standard clinical care. The primary end point was a change in body weight. Secondary end points included feasibility (weekly app engagement), acceptability (>50% approached enrolled), and safety. Of 51 patients approached, 40 (78%) were randomly assigned (20 NW and 20 standard clinical care). NW significantly decreased body weight when compared to standard clinical care (-5.5 kg vs. -0.3 kg, p = 0.008; -5.4% vs. -0.4%, p = 0.004). More NW subjects achieved a clinically significant weight loss of ≥5% body weight (45% vs. 15%, p = 0.038). No adverse events occurred, and the majority (70%) of subjects in the NW arm met the feasibility criteria. Conclusions: This clinical trial demonstrated that NW is not only feasible, acceptable, and safe but also highly efficacious because this mHealth lifestyle intervention program led to significantly greater body weight loss than standard clinical care. Future large-scale studies are required to validate these findings with more representative samples and to determine if mHealth lifestyle intervention programs can lead to sustained, long-term weight loss in patients with NASH.

Executive functioning is a key component involved in many of the processes necessary for effective weight management behavior change (e.g., setting goals). Cognitive behavioral therapy (CBT) and third-wave CBT (e.g., mindfulness) are considered first-line treatments for obesity, but it is unknown to what extent they can improve or sustain executive functioning in a generalized weight management intervention. This pilot randomized controlled trial examined if a CBT-based generalized weight management intervention would affect executive functioning and executive function-related brain activity in individuals with obesity or overweight. Participants were randomized to an intervention condition (N = 24) that received the Noom Weight program or to a control group (N = 26) receiving weekly educational newsletters. EEG measurements were taken during Flanker, Stroop, and N-back tasks at baseline and months 1 through 4. After 4 months, the intervention condition evidenced greater accuracy over time on the Flanker and Stroop tasks and, to a lesser extent, neural markers of executive function compared to the control group. The intervention condition also lost more weight than controls (−7.1 pounds vs. +1.0 pounds). Given mixed evidence on whether weight management interventions, particularly CBT-based weight management interventions, are associated with changes in markers of executive function, this pilot study contributes preliminary evidence that a multicomponent CBT-based weight management intervention (i.e., that which provides both support for weight management and is based on CBT) can help individuals sustain executive function over 4 months compared to controls.

BACKGROUND:Overweight and obesity are serious public health concerns. As the prevalence of excess weight among individuals continues to increase, there is a parallel need for inexpensive, highly accessible, and evidence-based weight loss programs. OBJECTIVE:This weight loss trial will aim to examine the efficacy of the Noom weight loss program in comparison to a digital control after a 6-month intervention phase and a 24-month maintenance phase, with assessments continuing for 2 years beyond the intervention (to 30 months-after the baseline). The secondary outcomes include quality of life, psychosocial functioning, sleep quality, physical activity, diet, and health status. This trial will also examine the severity of obesity-related functional impairment, weight loss history, and demographic moderators, along with adherence and self-efficacy as mediators of the outcome. METHODS:A total of 600 participants were randomized in a parallel-group, controlled trial to either Noom Healthy Weight Program (intervention) or Noom Healthy Weight Control (control) for a 6-month intervention. Both intervention and control groups include diet and exercise recommendations, educational content, daily logging capabilities, and daily weigh-in entries. The Noom Healthy Weight Program also includes a coach support for weight loss. Remote follow-up assessments of eating, physical activity, psychosocial factors, app use data, and weight will be conducted at 1, 4, 6, 12, 18, 24, and 30 months after baseline. Weight is measured at each follow-up point during a Zoom call using the participants' scales. RESULTS:Enrollment began in March 2021 and the 6-month intervention phase ended in March 2022. Data collection for the final assessment will be completed in March 2024. CONCLUSIONS:This study tests commercially available digital lifestyle interventions for individuals with overweight and obesity seeking weight loss support. Data obtained from the study will evaluate whether the Noom Healthy Weight Control Program can help individuals overcome weight loss, achieve long-term maintenance, adhere to lifestyle changes, and feature use barriers that are present in other traditional weight loss treatments. TRIAL REGISTRATION:ClinicalTrials.gov NCT04797169; https://clinicaltrials.gov/ct2/show/NCT04797169. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/37541.

OBJECTIVE:The aim of this study was to determine the effects of menstrual cycle phases (postmenses and premenses), self-report of premenstrual syndrome (PMS), late reproductive stages (LRS1 and LRS2), and early menopausal transition (EMT) stage (Stages of Reproductive Aging Workshop [STRAW]) on severity of five symptom groups.METHODS:A subset of Seattle Midlife Women's Health Study participants (n = 290) in either LRS1 or LRS2 or EMT (STRAW+10 criteria) provided daily symptom data for at least one full menstrual cycle during the first year of the study and reported current PMS. Symptom severity was rated (1-4, least to most severe) in the daily diary for five symptom groups (dysphoric mood, neuromuscular, somatic, vasomotor, and insomnia) identified earlier with the same sample ( Maturitas 1996;25:1-10). A three-way analysis of variance was used to test for within- and between-participants effects on symptom severity.RESULTS:Stage had no effect on severity for any of the five symptom groups. Dysphoric mood and neuromuscular and somatic symptom severity (but not vasomotor or insomnia severity) differed significantly across menstrual cycle phases, increasing from postmenses to premenses. Current PMS and premenses cycle phase had significant interactive effects on dysphoric mood and neuromuscular symptoms, but there were no significant interaction effects on somatic, vasomotor, or insomnia symptom severity.CONCLUSIONS:Dysphoric mood, neuromuscular, and somatic symptoms exhibit cyclicity and are influenced by current PMS. Late reproductive stages and EMT stage do not have significant effects on the five symptom groups. Vasomotor or insomnia symptoms do not exhibit significant cyclicity from postmenses to premenses and are not affected by current PMS. Future studies of symptom cyclicity and reproductive aging including daily symptom data across an entire menstrual cycle in samples including women in late menopausal transition stage are essential to capture the effects of both cyclicity and self-reported PMS to capture symptom severity reports at their peak.

Behavioral weight loss reduces risk of weight-related health complications. Outcomes of behavioral weight loss programs include attrition and weight loss. There is reason to believe that individuals’ written language on a weight management program may be associated with outcomes. Exploring associations between written language and these outcomes could potentially inform future efforts towards real-time automated identification of moments or individuals at high risk of suboptimal outcomes. Thus, in the first study of its kind, we explored whether individuals’ written language in actual use of a program (i.e., outside of a controlled trial) is associated with attrition and weight loss. We examined two types of language: goal setting (i.e., language used in setting a goal at the start of the program) and goal striving (i.e., language used in conversations with a coach about the process of striving for goals) and whether they are associated with attrition and weight loss on a mobile weight management program. We used the most established automated text analysis program, Linguistic Inquiry Word Count (LIWC), to retrospectively analyze transcripts extracted from the program database. The strongest effects emerged for goal striving language. In striving for goals, psychologically distanced language was associated with more weight loss and less attrition, while psychologically immediate language was associated with less weight loss and higher attrition. Our results highlight the potential importance of distanced and immediate language in understanding outcomes like attrition and weight loss. These results, generated from real-world language, attrition, and weight loss (i.e., from individuals’ natural usage of the program), have important implications for how future work can better understand outcomes, especially in real-world settings.

Background: Moderate weight loss of 5–10% is considered a realistically achievable weight loss goal and is associated with decreased risk of obesity-related health complications. However, individuals tend to expect that they will lose as much as 20–30% of their body weight when they start a behavioral weight loss program. Current research is limited on how these expectations change over time during weight loss and the consequences of adjusting one’s expectations in a more realistic direction, particularly on a CBT-based program. Method: Therefore, this prospective cohort study evaluated whether individuals adjusted their weight loss expectations over time during real-world use of a mobile CBT-based behavior-change program (Noom Weight) and how this adjustment related to weight loss outcomes, as well as how the amount of adjustment depended on program engagement. Participants had recently signed up for Noom Weight and reported their weight, expectations for weight loss, and psychological well-being at baseline and six months. Engagement was automatically recorded by the program. Results: We found that after using Noom Weight for six months, participants’ expectations became more realistic (i.e., significantly decreased) compared to baseline (−5.77, s.e. = 0.57, p < 0.001), and this downward adjustment was associated with greater weight loss (b = 1.80, 95% CI 1.21–2.38, p < 0.001). Higher program engagement, particularly reading articles focused on CBT-based principles, was associated with greater decreases in expectations over time (b = −0.007, t = −2.22, p = 0.03). Conclusions: The results suggest that CBT-based principles may aid in adjusting weight loss expectations to more realistic levels and that such adjustment is associated with positive weight outcomes. Future research should build on these results by evaluating adjustment in weight loss expectations over time, rather than solely expectations at baseline.

Health-promoting lifestyle behaviors (e.g., as measured by the HPLP-II) are associated with reductions in lifestyle disease mortality, as well as improved well-being, mental health, and quality of life. However, it is unclear how a weight-management program relates to a broad range of these behaviors (i.e., health responsibility, physical activity, nutrition, spiritual growth, interpersonal relations, and stress management), especially a fully digital program on which individuals have to self-manage their own behaviors in their daily lives (with assistance from a virtual human coach). In the context of a digital setting, this study examined the changes in health-promoting behaviors over 12 months, as well as the associations between health-promoting behaviors and weight loss, retention, and engagement, among participants who self-enrolled in a mobile CBT-based nutritionally focused behavior change weight management program (n = 242). Participants lost a statistically significant amount of weight (M = 6.7 kg; SD = 12.7 kg; t(80) = 9.26, p < 0.001) and reported significantly improved overall health-promoting lifestyle behaviors (i.e., HPLP-II summary scores), as well as, specifically, health responsibility, physical activity, nutrition, spiritual growth, stress management, and interpersonal relations behaviors from baseline to 6 months and from 6 months to 12 months (all ps < 0.008). Health-promoting behaviors at 6 months (i.e., learned health-promoting behaviors) compared to baseline were better predictors of retention and program engagement. A fully digital, mobile weight management intervention can improve HPLP-II scores, which, in turn, has implications for improved retention, program engagement, and better understanding the comprehensive effects of weight management programs, particularly in a digital setting.

Recent work has shown that obesity may be a risk factor for severe COVID-19. However, it is unclear to what extent individuals have heard or believe this risk factor information, and how these beliefs may predict their preventive behaviors (e.g., weight management behaviors or COVID-19 preventive behaviors). Previous work has primarily looked at overall risk likelihood perceptions (i.e., not about obesity as a risk factor) within general populations of varying weight and concentrated on COVID-19-related preventive behaviors. Therefore, this prospective cohort study explored whether beliefs about obesity as a risk factor and overall risk likelihood perceptions predicted weight management and COVID-19 preventive behaviors over the next 16 weeks in individuals with obesity or overweight. Participants were 393 individuals in the US who joined a commercial weight management program in January, 2021. We leveraged the mobile program’s automatic measurement of real-time engagement in weight management behaviors (e.g., steps taken), while surveys measured risk beliefs at baseline as well as when individuals received COVID-19 vaccination doses (asked monthly) over the next 16 weeks. Mixed effects models predicted engagement and weight loss each week for 16 weeks, while ordinal logistic regression models predicted the month that individuals got vaccinated against COVID-19. We found that belief in obesity as a risk factor at baseline significantly predicted greater engagement (e.g., steps taken, foods logged) in program-measured weight management behaviors over the next 16 weeks in models adjusted for baseline BMI, age, gender, and local vaccination rates (minimally adjusted) and in models additionally adjusted for demographic factors. Belief in obesity as a risk factor at baseline also significantly predicted speed of COVID-19 vaccination uptake in minimally adjusted models but not when demographic factors were taken into account. Exposure to obesity risk factor information at baseline predicted greater engagement over 16 weeks in minimally adjusted models. The results highlight the potential utility of effective education to increase individuals’ belief in obesity risk factor information and ultimately promote engagement or faster vaccination. Future research should investigate to what extent the results generalize to other populations.