Information theory reveals physiological manifestations of COVID-19 that correlate with symptom density of illness.

Algorithms for the detection of COVID-19 illness from wearable sensor devices tend to implicitly treat the disease as causing a stereotyped (and therefore recognizable) deviation from healthy physiology. In contrast, a substantial diversity of bodily responses to SARS-CoV-2 infection have been reported in the clinical milieu. This raises the question of how to characterize the diversity of illness manifestations, and whether such characterization could reveal meaningful relationships across different illness manifestations. Here, we present a framework motivated by information theory to generate quantified maps of illness presentation, which we term "manifestations," as resolved by continuous physiological data from a wearable device (Oura Ring). We test this framework on five physiological data streams (heart rate, heart rate variability, respiratory rate, metabolic activity, and sleep temperature) assessed at the time of reported illness onset in a previously reported COVID-19-positive cohort (N = 73). We find that the number of distinct manifestations are few in this cohort, compared to the space of all possible manifestations. In addition, manifestation frequency correlates with the rough number of symptoms reported by a given individual, over a several-day period prior to their imputed onset of illness. These findings suggest that information-theoretic approaches can be used to sort COVID-19 illness manifestations into types with real-world value. This proof of concept supports the use of information-theoretic approaches to map illness manifestations from continuous physiological data. Such approaches could likely inform algorithm design and real-time treatment decisions if developed on large, diverse samples.

Five million nights: temporal dynamics in human sleep phenotypes.

Sleep monitoring has become widespread with the rise of affordable wearable devices. However, converting sleep data into actionable change remains challenging as diverse factors can cause combinations of sleep parameters to differ both between people and within people over time. Researchers have attempted to combine sleep parameters to improve detecting similarities between nights of sleep. The cluster of similar combinations of sleep parameters from a night of sleep defines that night's sleep phenotype. To date, quantitative models of sleep phenotype made from data collected from large populations have used cross-sectional data, which preclude longitudinal analyses that could better quantify differences within individuals over time. In analyses reported here, we used five million nights of wearable sleep data to test (a) whether an individual's sleep phenotype changes over time and (b) whether these changes elucidate new information about acute periods of illness (e.g., flu, fever, COVID-19). We found evidence for 13 sleep phenotypes associated with sleep quality and that individuals transition between these phenotypes over time. Patterns of transitions significantly differ (i) between individuals (with vs. without a chronic health condition; chi-square test; p-value < 1e-100) and (ii) within individuals over time (before vs. during an acute condition; Chi-Square test; p-value < 1e-100). Finally, we found that the patterns of transitions carried more information about chronic and acute health conditions than did phenotype membership alone (longitudinal analyses yielded 2-10× as much information as cross-sectional analyses). These results support the use of temporal dynamics in the future development of longitudinal sleep analyses.

COVID-19 Vaccine Side Effects and Long-Term Neutralizing Antibody Response : A Prospective Cohort Study.

BACKGROUND: Concern about side effects is a common reason for SARS-CoV-2 vaccine hesitancy. OBJECTIVE: To determine whether short-term side effects of SARS-CoV-2 messenger RNA (mRNA) vaccination are associated with subsequent neutralizing antibody (nAB) response. DESIGN: Prospective cohort study. SETTING: San Francisco Bay Area. PARTICIPANTS: Adults who had not been vaccinated against or exposed to SARS-CoV-2, who then received 2 doses of either BNT162b2 or mRNA-1273. MEASUREMENTS: Serum nAB titer at 1 month and 6 months after the second vaccine dose. Daily symptom surveys and objective biometric measurements at each dose. RESULTS: 363 participants were included in symptom-related analyses (65.6% female; mean age, 52.4 years [SD, 11.9]), and 147 were included in biometric-related analyses (66.0% female; mean age, 58.8 years [SD, 5.3]). Chills, tiredness, feeling unwell, and headache after the second dose were each associated with 1.4 to 1.6 fold higher nAB at 1 and 6 months after vaccination. Symptom count and vaccination-induced change in skin temperature and heart rate were all positively associated with nAB across both follow-up time points. Each 1 °C increase in skin temperature after dose 2 was associated with 1.8 fold higher nAB 1 month later and 3.1 fold higher nAB 6 months later. LIMITATIONS: The study was conducted in 2021 in people receiving the primary vaccine series, making generalizability to people with prior SARS-CoV-2 vaccination or exposure unclear. Whether the observed associations would also apply for neutralizing activity against non-ancestral SARS-CoV-2 strains is also unknown. CONCLUSION: Convergent self-report and objective biometric findings indicate that short-term systemic side effects of SARS-CoV-2 mRNA vaccination are associated with greater long-lasting nAB responses. This may be relevant in addressing negative attitudes toward vaccine side effects, which are a barrier to vaccine uptake. PRIMARY FUNDING SOURCE: National Institute on Aging.

Feasibility and acceptability of an integrated mind-body intervention for depression: whole-body hyperthermia (WBH) and cognitive behavioral therapy (CBT).

OBJECTIVE: To examine the feasibility of an integrated mind-body MDD treatment combining cognitive behavioral therapy (CBT) and whole-body hyperthermia (WBH). METHODS: In this single-arm trial, 16 adults with MDD initially received 8 weekly CBT sessions and 8 weekly WBH sessions. Outcomes included WBH sessions completed (primary), self-report depression assessments completed (secondary), and pre-post intervention changes in depression symptoms (secondary). We also explored changes in mood and cognitive processes and assessed changes in mood as predictors of overall treatment response. RESULTS: Thirteen participants (81.3%) completed ≥ 4 WBH sessions (primary outcome); midway through the trial, we reduced from 8 weekly to 4 bi-weekly WBH sessions to increase feasibility. The n = 12 participants who attended the final assessment visit completed 100% of administered self-report depression assessments; all enrolled participants (n = 16) completed 89% of these assessments. Among the n = 12 who attended the final assessment visit, the average pre-post-intervention BDI-II reduction was 15.8 points (95% CI: -22.0, -9.70), p = 0.0001, with 11 no longer meeting MDD criteria (secondary outcomes). Pre-post intervention improvements in negative automatic thinking, but not cognitive flexibility, achieved statistical significance. Improved mood from pre-post the initial WBH session predicted pre-post treatment BDI-II change (36.2%; rho = 0.60, p = 0.038); mood changes pre-post the first CBT session did not. LIMITATIONS: Small sample size and single-arm design limit generalizability. CONCLUSION: An integrated mind-body intervention comprising weekly CBT sessions and bi-weekly WBH sessions was feasible. Results warrant future larger controlled clinical trials.Clinivaltrials.gov Registration: NCT05708976.

The antidepressant effect of whole-body hyperthermia is associated with the classical interleukin-6 signaling pathway.

There is urgent need for novel antidepressant treatments that confer therapeutic benefits via engagement with identified mechanistic targets. The objective of the study was to determine whether activation of the classical anti-inflammatory interleukin-6 signaling pathways is associated with the antidepressant effects of whole-body hyperthermia. A 6-week, randomized, double-blind study compared whole-body hyperthermia with a sham condition in a university-based medical center. Medically healthy participants aged 18-65 years who met criteria for major depressive disorder, were free of psychotropic medication use, and had a baseline 17-item Hamilton Depression Rating Scale score ≥ 16 were randomized with 1-to-1 allocation in blocks of 6 to receive whole-body hyperthermia or sham. Of 338 individuals screened, 34 were randomized, 30 received interventions and 26 had ≥ 2 blood draws and depressive symptom assessments. Secondary data analysis examined change in the ratio of IL-6:soluble IL-6 receptor pre-intervention, post-intervention, and at weeks 1 and 4. Hierarchical linear modeling tested whether increased IL-6:soluble IL-6 receptor ratio post-intervention was associated with decreased depressive symptom at weeks 1, 2, 4 and 6 for those randomized to whole-body hyperthermia. Twenty-six individuals were randomized to whole-body hyperthermia [n = 12; 75 % female; age = 37.9 years (SD = 15.3) or sham [n = 14; 57.1 % female; age = 41.1 years (SD = 12.5). When compared to the sham condition, active whole-body hyperthermia only increased the IL-6:soluble IL-6 receptor ratio post-treatment [F(3,72) = 11.73,p < .001], but not pre-intervention or at weeks 1 and 4. Using hierarchical linear modeling, increased IL-6:sIL-6R ratio following whole-body hyperthermia moderated depressive symptoms at weeks 1, 2, 4 and 6, such that increases in the IL-6:soluble IL-6 receptor ratio were associated with decreased depressive symptoms at weeks 1, 2, 4 and 6 for those receiving the active whole-body hyperthermia compared to sham treatment (B = -229.44, t = -3.82,p < .001). Acute activation of classical intereukin-6 signaling might emerge as a heretofore unrecognized novel mechanism that could be harnessed to expand the antidepressant armamentarium.

Impact of Hypoglossal Nerve Stimulation on Consumer Sleep Technology Metrics and Patient Symptoms.

OBJECTIVES: Obstructive sleep apnea (OSA) is usually assessed at discrete and infrequent timepoints. Wearable consumer sleep technologies (CST) may allow for more granular and longitudinal assessments of OSA therapy responses and OSA-related symptoms. METHODS: In this case series, we enrolled hypoglossal nerve stimulator (HGNS) patients who had an effective treatment response for an 8-week study using a wearable CST. Participants started with "HGNS-on," were randomized to turn off HGNS therapy during either week 4 or 5 ("HGNS-off"), followed by a return to therapy, "HGNS-resume." Participants completed validated symptom questionnaires assessing sleepiness, insomnia symptoms, functional status, and overall sleep health (Satisfaction, Alertness, Timing, Efficiency, and Duration, SATED) each week. CST metrics and survey scores were compared between HGNS treatment phases. Associations between CST metrics and survey scores were assessed. RESULTS: Seven participants with a total of 304 nights of CST data showed no statistically significant changes in total sleep time (TST), wake time after sleep onset, or sleep efficiency (SE) across the study periods. During HGNS-off, survey scores indicated significantly worsened OSA-related symptom scores. Two participants had significantly higher heart rate variability (HRV) during HGNS-off (by 3.3 and 6.3 ms) when compared to HGNS active therapy periods. Amongst CST metrics, SATED scores correlated with TST (r = 0.434, p < 0.0001), HRV (r = -0.486, p < 0.0001), and SE (r = 0.320, = 0.0014). In addition, FOSQ-10 scores correlated with average HR during sleep (r = -0.489, p < 0.001). CONCLUSION: A 1-week HGNS therapy withdrawal period impacted OSA-related sleep symptoms. Sleep-related metrics measured by a wearable CST correlated with symptom scores indicating potential value in the use of CSTs for longitudinal sleep-tracking in OSA patients. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:3406-3411, 2024.

Utilizing Wearable Device Data for Syndromic Surveillance: A Fever Detection Approach.

Commercially available wearable devices (wearables) show promise for continuous physiological monitoring. Previous works have demonstrated that wearables can be used to detect the onset of acute infectious diseases, particularly those characterized by fever. We aimed to evaluate whether these devices could be used for the more general task of syndromic surveillance. We obtained wearable device data (Oura Ring) from 63,153 participants. We constructed a dataset using participants' wearable device data and participants' responses to daily online questionnaires. We included days from the participants if they (1) completed the questionnaire, (2) reported not experiencing fever and reported a self-collected body temperature below 38 °C (negative class), or reported experiencing fever and reported a self-collected body temperature at or above 38 °C (positive class), and (3) wore the wearable device the nights before and after that day. We used wearable device data (i.e., skin temperature, heart rate, and sleep) from the nights before and after participants' fever day to train a tree-based classifier to detect self-reported fevers. We evaluated the performance of our model using a five-fold cross-validation scheme. Sixteen thousand, seven hundred, and ninety-four participants provided at least one valid ground truth day; there were a total of 724 fever days (positive class examples) from 463 participants and 342,430 non-fever days (negative class examples) from 16,687 participants. Our model exhibited an area under the receiver operating characteristic curve (AUROC) of 0.85 and an average precision (AP) of 0.25. At a sensitivity of 0.50, our calibrated model had a false positive rate of 0.8%. Our results suggest that it might be possible to leverage data from these devices at a public health level for live fever surveillance. Implementing these models could increase our ability to detect disease prevalence and spread in real-time during infectious disease outbreaks.

Elevated body temperature is associated with depressive symptoms: results from the TemPredict Study.

Correlations between altered body temperature and depression have been reported in small samples; greater confidence in these associations would provide a rationale for further examining potential mechanisms of depression related to body temperature regulation. We sought to test the hypotheses that greater depression symptom severity is associated with (1) higher body temperature, (2) smaller differences between body temperature when awake versus asleep, and (3) lower diurnal body temperature amplitude. Data collected included both self-reported body temperature (using standard thermometers), wearable sensor-assessed distal body temperature (using an off-the-shelf wearable sensor that collected minute-level physiological data), and self-reported depressive symptoms from > 20,000 participants over the course of ~ 7 months as part of the TemPredict Study. Higher self-reported and wearable sensor-assessed body temperatures when awake were associated with greater depression symptom severity. Lower diurnal body temperature amplitude, computed using wearable sensor-assessed distal body temperature data, tended to be associated with greater depression symptom severity, though this association did not achieve statistical significance. These findings, drawn from a large sample, replicate and expand upon prior data pointing to body temperature alterations as potentially relevant factors in depression etiology and may hold implications for development of novel approaches to the treatment of major depressive disorder.

Variability of temperature measurements recorded by a wearable device by biological sex.

BACKGROUND: Females have been historically excluded from biomedical research due in part to the documented presumption that results with male subjects will generalize effectively to females. This has been justified in part by the assumption that ovarian rhythms will increase the overall variance of pooled random samples. But not all variance in samples is random. Human biometrics are continuously changing in response to stimuli and biological rhythms; single measurements taken sporadically do not easily support exploration of variance across time scales. Recently we reported that in mice, core body temperature measured longitudinally shows higher variance in males than cycling females, both within and across individuals at multiple time scales. METHODS: Here, we explore longitudinal human distal body temperature, measured by a wearable sensor device (Oura Ring), for 6 months in females and males ranging in age from 20 to 79 years. In this study, we did not limit the comparisons to female versus male, but instead we developed a method for categorizing individuals as cyclic or acyclic depending on the presence of a roughly monthly pattern to their nightly temperature. We then compared structure and variance across time scales using multiple standard instruments. RESULTS: Sex differences exist as expected, but across multiple statistical comparisons and timescales, there was no one group that consistently exceeded the others in variance. When variability was assessed across time, females, whether or not their temperature contained monthly cycles, did not significantly differ from males both on daily and monthly time scales. CONCLUSIONS: These findings contradict the viewpoint that human females are too variable across menstrual cycles to include in biomedical research. Longitudinal temperature of females does not accumulate greater measurement error over time than do males and the majority of unexplained variance is within sex category, not between them.

Women are still excluded from research disproportionately, due in part to documented concerns that menstrual cycles make them more variable and so harder to study. In the past, we have challenged this claim, finding it does not hold for animal physiology, animal behavior, or human behavior. Here we are able to show that it does not hold in human physiology either. We analyzed 6 months of continuously collected temperature data measured by a commercial wearable device, in order to determine if it is true that females are more variable or less predictable than males. We found that temperatures mostly vary as a function of time of day and whether the individual was awake or asleep. Additionally, for some females, nightly maximum temperature contained a cyclical pattern with a period of around 28 days, consistent with menstrual cycles. The variability was different between cycling females, not cycling females, and males, but only cycling female temperature contained a monthly structure, making their changes more predictable than those of non-cycling females and males. We found the majority of unexplained variance to be within each sex/cycling category, not between them. All groups had indistinguishable measurement errors across time. This analysis of temperature suggests data-driven characteristics might be more helpful distinguishing individuals than historical categories such as binary sex. The work also supports the inclusion of females as subjects within biological research, as this inclusion does not weaken statistical comparisons, but does allow more equitable coverage of research results in the world.

Assessing Adherence to Multi-Modal Oura Ring Wearables From COVID-19 Detection Among Healthcare Workers.

Background Identifying early signs of a SARS-CoV-2 infection in healthcare workers could be a critical tool in reducing disease transmission. To provide this information, both daily symptom surveys and wearable device monitoring could have utility, assuming there is a sufficiently high level of participant adherence. Purpose The aim of this study is to evaluate adherence to a daily symptom survey and a wearable device (Oura Ring) among healthcare professionals (attending physicians and other clinical staff) and trainees (residents and medical students) in a hospital setting during the early stages of the COVID-19 pandemic. Methods In this mixed-methods observational study, the data were a subset (N=91) of those collected as part of the larger TemPredict Study. Demographic data analyses were conducted with descriptive statistics. Participant adherence to the wearable device protocol was reported as the percentage of days that sleep was recorded, and adherence to the daily survey was reported as the percentage of days with submitted surveys. Comparisons for the primary (wearable and survey adherence of groups) and secondary (adherence patterns among subgroups) outcomes were conducted using descriptive statistics, two-tailed independent t-tests, and Welch's ANOVA with post hoc analysis using Games-Howell. Results Wearable device adherence was significantly higher than the daily symptom survey adherence for most participants. Overall, participants were highly adherent to the wearable device, wearing the device an average of 87.8 ± 11.6% of study nights compared to survey submission, showing an average of 63.8 ± 27.4% of study days. In subgroup analysis, we found that healthcare professionals (HCPs) and medical students had the highest adherence to wearing the wearable device, while medical residents had lower adherence in both wearable adherence and daily symptom survey adherence. Conclusions These results indicated high participant adherence to wearable devices to monitor for impending infection in the course of a research study conducted as part of clinical practice. Subgroup analysis indicated HCPs and medical students maintained high adherence, but residents' adherence was lower, which is likely multifactorial, with differences in work demands and stress contributing to the findings. These results can guide the development of adherence strategies for a wearable device to increase the quality of data collection and assist in disease detection in this and future pandemics.

A Randomized Controlled Trial of Community-Delivered Heated Hatha Yoga for Moderate-to-Severe Depression.

Objective: To evaluate feasibility, acceptability, and preliminary efficacy of heated yoga to treat moderate-to-severe depression.Design: An 8-week randomized controlled trial (RCT) of heated yoga versus waitlist control was conducted from March 2017 to August 2019.Methods: Participants in the yoga condition were asked to attend heated yoga classes at 2 community heated yoga studios at least twice weekly. We assessed acceptability and feasibility using exit interview and attendance data, respectively. The primary intervention efficacy outcome variable was change in the Inventory of Depressive Symptomatology-Clinician Rated (IDS-CR) score from baseline to post-intervention (week 8).Results: We randomized 80 participants and included 65 (mean [± SD] age 32.7 [± 11.7] years; 81.5% female) in the analyses (yoga n = 33, waitlist n = 32). The mean IDS-CR score at baseline was 35.6 (± 7.9) for the full sample, 36.9 (± 8.8) for yoga participants, and 34.4 (± 6.7) for waitlist participants. Participants attended an average of 10.3 (± 7.1) total classes over the 8-week intervention period. Yoga participants had a significantly greater pre- to post-intervention reduction in IDS-CR scores than waitlist participants (Cohen d = 1.04, P < .001). More yoga participants (59.3%; n = 16) than waitlist participants (6.3%; n = 2) evidenced larger treatment responses (IDS-CR ≥ 50% decrease in symptoms). Participants rated the heated yoga and its aftereffects positively in exit interviews.Conclusions: Approximately 1 heated yoga session per week (mean of 10.3 classes over 8 weeks) was associated with significantly greater reduction in depression symptoms than a waitlist control. Participants rated heated yoga positively. Taken together, results suggest feasibility, acceptability, and preliminary efficacy for patients with depression and warrant further research using active control conditions.Trial Registration: ClinicalTrials.gov identifier: NCT02607514.

The more symptoms the better? Covid-19 vaccine side effects and long-term neutralizing antibody response.

Protection against SARS-CoV-2 wanes over time, and booster uptake has been low, in part because of concern about side effects. We examined the relationships between local and systemic symptoms, biometric changes, and neutralizing antibodies (nAB) after mRNA vaccination. Data were collected from adults (n = 364) who received two doses of either BNT162b2 or mRNA-1273. Serum nAB concentration was measured at 1 and 6 months post-vaccination. Daily symptom surveys were completed for six days starting on the day of each dose. Concurrently, objective biometric measurements, including skin temperature, heart rate, heart rate variability, and respiratory rate, were collected. We found that certain symptoms (chills, tiredness, feeling unwell, and headache) after the second dose were associated with increases in nAB at 1 and 6 months post-vaccination, to roughly 140-160% the level of individuals without each symptom. Each additional symptom predicted a 1.1-fold nAB increase. Greater increases in skin temperature and heart rate after the second dose predicted higher nAB levels at both time points, but skin temperature change was more predictive of durable (6 month) nAB response than of short-term (1 month) nAB response. In the context of low ongoing vaccine uptake, our convergent symptom and biometric findings suggest that public health messaging could seek to reframe systemic symptoms after vaccination as desirable.

Protocol for a randomized controlled trial comparing a very low-carbohydrate diet or moderate-carbohydrate plate-method diet for type 2 diabetes: the LEGEND (Lifestyle Education about Nutrition for Diabetes) trial.

BACKGROUND: Optimal carbohydrate intake is an important and controversial area in the nutritional management of type 2 diabetes. Some evidence indicates that reducing overall carbohydrate intake with a low- or very low-carbohydrate eating plan can improve glycemic control compared to following eating plans that involve greater carbohydrate intake. However, critical knowledge gaps currently prevent clear recommendations about carbohydrate intake levels. METHODS: The LEGEND (Lifestyle Education about Nutrition for Diabetes) Trial aims to compare a very low-carbohydrate diet to a moderate-carbohydrate plate-method diet for glycemic control in adults with type 2 diabetes. This two-site trial plans to recruit 180 adults with type 2 diabetes. We will randomize participants to either a 20-session group-based diet and lifestyle intervention that teaches either a very low-carbohydrate diet or a moderate-carbohydrate plate-method diet. We will assess participants at study entry and 4 and 12 months later. The primary outcome is HbA1c, and secondary outcomes include inflammation (high sensitivity C-reactive protein), body weight, changes in diabetes medications, lipids (small particle LDL, HDL, triglycerides), skeletal metabolism (bone mineral density from dual-energy x-ray absorptiometry and bone turnover markers serum procollagen type I N propeptide and serum C-terminal telopeptide of type I collagen), and body composition (percent body fat, percent lean body mass). DISCUSSION: The LEGEND trial is a randomized controlled trial to assess optimal carbohydrate intake in type 2 diabetes by evaluating the effects of a very low-carbohydrate diet vs. a moderate-carbohydrate plate-method diet over a year-long period. The research addresses important gaps in the evidence base for the nutritional management of type 2 diabetes by providing data on potential benefits and adverse effects of different levels of carbohydrate intake. TRIAL REGISTRATION: ClinicalTrials.gov NCT05237128. Registered on February 11, 2022.

Controlled trial of a workplace sales ban on sugar-sweetened beverages.

OBJECTIVE: To examine the effectiveness of a workplace sugar-sweetened beverage (SSB) sales ban on reducing SSB consumption in employees, including those with cardiometabolic disease risk factors. DESIGN: A controlled trial of ethnically diverse, full-time employees who consumed SSB heavily (sales ban n 315; control n 342). Outcomes included standardised measures of change in SSB consumption in the workplace (primary) and at home between baseline and 6 months post-sales ban. SETTING: Sutter Health, a large non-profit healthcare delivery system in Northern California. PARTICIPANTS: Full-time employees at Sutter Health screened for heavy SSB consumption. RESULTS: Participants were 66·1 % non-White. On average, participants consumed 34·7 ounces (about 1 litre) of SSB per d, and the majority had an elevated baseline BMI (mean = 29·5). In adjusted regression analyses, those exposed to a workplace SSB sales ban for 6 months consumed 2·7 (95 % CI -4·9, -0·5) fewer ounces of SSB per d while at work, and 4·3 (95 % CI -8·4, -0·2) fewer total ounces per d, compared to controls. Sales ban participants with an elevated BMI or waist circumference had greater post-intervention reductions in workplace SSB consumption. CONCLUSIONS: Workplace sales bans can reduce SSB consumption in ethnically diverse employee populations, including those at higher risk for cardiometabolic disease.

Psychological Support Strategies for Adults With Type 2 Diabetes in a Very Low-Carbohydrate Web-Based Program: Randomized Controlled Trial.

BACKGROUND: A very low-carbohydrate (VLC) nutritional strategy may improve glycemic control and weight loss in adults with type 2 diabetes (T2D). However, the supplementary behavioral strategies that might be able to improve outcomes using this nutritional strategy are uncertain. OBJECTIVE: This study aims to compare the impact of adding 3 different supplementary behavioral strategies to a web-based VLC diet intervention. To our knowledge, this is the first trial to randomize participants to different frequencies of dietary self-monitoring. METHODS: The study included 112 overweight adults with T2D (hemoglobin A1c ≥6.5%) taking no antiglycemic medications or only metformin. They received a remotely delivered 12-month VLC diet intervention. Participants were randomly assigned through a full factorial 2×2×2 design to supplementary strategies: either daily or monthly dietary self-monitoring, either mindful eating training or not, and either positive affect skills training or not. Our research goal was to determine whether 3 different supplemental strategies had at least a medium effect size (Cohen d=0.5). RESULTS: Overall, the VLC intervention led to statistically significant improvements in glycemic control (-0.70%, 95% CI -1.04% to -0.35%; P<.001), weight loss (-6.82%, 95% CI -8.57% to -5.08%; P<.001), and depressive symptom severity (Cohen d -0.67, 95% CI -0.92 to -0.41; P<.001). Furthermore, 30% (25/83) of the participants taking metformin at baseline reduced or discontinued their metformin. Only 1 Cohen d point estimate reached 0.5; daily (vs monthly) dietary self-monitoring had a worse impact on depressive symptoms severity (Cohen d=0.47, 95% CI -0.02 to 0.95; P=.06). None of the strategies had a statistically significant effect on outcomes. For changes in our primary outcome, hemoglobin A1c, the daily (vs monthly) dietary self-monitoring impact was 0.42% (95% CI -0.28% to 1.12%); for mindful eating, it was -0.47% (95% CI -1.15% to 0.22%); and for positive affect, it was 0.12% (95% CI -0.57% to 0.82%). Other results for daily (vs monthly) dietary self-monitoring were mixed, suggesting an increase in weight (0.98%) and depressive symptoms (Cohen d=0.47), less intervention satisfaction (Cohen d=-0.20), more sessions viewed (3.02), and greater dietary adherence (Cohen d=0.24). For mindful eating, the results suggested a benefit for dietary adherence (Cohen d=0.24) and intervention satisfaction (Cohen d=0.30). For positive affect, the results suggested a benefit for depressive symptoms (Cohen d=-0.32), the number of sessions viewed (3.68), dietary adherence (Cohen d=0.16), and intervention satisfaction (Cohen d=0.25). CONCLUSIONS: Overall, our results support the use of a VLC diet intervention in adults with T2D. The addition of monthly (not daily) dietary self-monitoring, mindful eating, and positive affect skills training did not show a definitive benefit, but it is worth further testing. TRIAL REGISTRATION: ClinicalTrials.gov NCT03037528; https://clinicaltrials.gov/ct2/show/NCT03037528.

Predictors of long-term neutralizing antibody titers following COVID-19 vaccination by three vaccine types: the BOOST study.

As concerns related to the COVID-19 pandemic continue, it is critical to understand the impact of vaccination type on neutralizing antibody response durability as well as to identify individual difference factors related to decline in neutralization. This was a head-to-head comparison study following 498 healthy, community volunteers who received the BNT162b2 (n = 287), mRNA-1273 (n = 149), and Ad26.COV2.S (n = 62). Participants completed questionnaires and underwent blood draws prior to vaccination, 1 month, and 6 months after the vaccination series, and neutralizing antibody (nAB) titers at 1- and 6-months post vaccination were quantified using a high-throughput pseudovirus assay. Over 6 months of follow-up, nABs declined in recipients of BNT162b2 and mRNA-1273, while nABs in recipients of Ad26.COV2.S showed a significant increase. At the 6-month time point, nABs to Ad26.COV2.S were significantly higher than nABs to BNT162b2 and equivalent to mRNA-1273. Irrespective of follow-up timing, being older was associated with lower nAB for participants who received BNT162b2 and Ad26.COV2.S but not for those who received mRNA-1273. A higher baseline BMI was associated with a lower nAB for Ad26.COV2.S recipients but not for recipients of other vaccines. Women and non-smokers showed higher nAB compared to men and current smokers, respectively. The durability of neutralizing antibody responses differed by vaccine type and several sociodemographic factors that predicted response. These findings may inform booster recommendations in the future.

Impact of digital meditation on work stress and health outcomes among adults with overweight: A randomized controlled trial.

Mindfulness meditation may improve well-being at work; however, effects on food cravings and metabolic health are not well known. We tested effects of digital meditation, alone or in combination with a healthy eating program, on perceived stress, cravings, and adiposity. We randomized 161 participants with overweight and moderate stress to digital meditation ('MED,' n = 38), digital meditation + healthy eating ('MED+HE,' n = 40), active control ('HE,' n = 41), or waitlist control ('WL,' n = 42) for 8 weeks. Participants (n = 145; M(SD) BMI: 30.8 (5.4) kg/m2) completed baseline and 8-week measures of stress (Perceived Stress Scale), cravings (Food Acceptance and Awareness Questionnaire) and adiposity (sagittal diameter and BMI). ANCOVAs revealed that those randomized to MED or MED+HE (vs. HE or WL) showed decreases in perceived stress (F = 15.19, p < .001, η2 = .10) and sagittal diameter (F = 4.59, p = .03, η2 = .04), with no differences in cravings or BMI. Those high in binge eating who received MED or MED+HE showed decreases in sagittal diameter (p = .03). Those with greater adherence to MED or MED+HE had greater reductions in stress, cravings, and adiposity (ps < .05). A brief digital mindfulness-based program is a low-cost method for reducing perceptions of stress and improving abdominal fat distribution patterns among adults with overweight and moderate stress. Future work should seek to clarify mechanisms by which such interventions contribute to improvements in health. Trial registration: Clinical trial registration http://www.ClinicalTrials.gov: identifier NCT03945214.