Neighborhood Walkability Is Associated with Physical Activity and Prediabetes in a Behavioral Weight Loss Study: a Secondary Analysis.

BACKGROUND: Socio-environmental factors may affect uptake and utility of behavioral interventions targeting weight loss and cardiometabolic health. To evaluate the relation of neighborhood walkability to physical activity (PA) and glucose control in a sample of adults with overweight/obesity participating in a weight loss study. METHODS: Secondary analysis of a 12-month behavioral weight loss intervention (2011-2015) using one-group pretest-posttest design. Neighborhood walkability was assessed via residential Walk Score (0-100) at study entry. Fasting plasma glucose (FPG) via phlebotomy and PA via waist-worn ActiGraph GT3X were assessed at baseline and end of study. Study variables included neighborhood walkability (car-dependent: Walk Score < 50 vs. walkable: Walk Score ≥ 50), prediabetes (FPG 100-125 mg/dL), and recommended PA (moderate to vigorous PA [MVPA] > 22 min/day). Generalized linear model with logit link results were reported as adjusted odds ratios (AOR) with 95% confidence intervals (CI). RESULTS: The sample (N = 114) was mostly female (88.6%), white (83.3%), college educated (73.7%), and on average 51.4 ± 1.0 years of age. At baseline, persons residing in car-dependent neighborhoods tended to have higher income than those in walkable neighborhoods. Neighborhood walkability interacted with household income at study entry to predict participants' ability to meet the MVPA goal at 12 months (AOR = 13.52, 95% CI: 1.86-119.20). Those from walkable neighborhoods had 67% lower odds of having prediabetes compared to those from car-dependent neighborhoods (AOR = 0.33, 95% CI: 0.10-0.87) at 12 months. CONCLUSION: Our findings corroborate previous research characterizing the relationship between neighborhood walkability, PA, and prediabetes status. Key drivers of this impact warrant further investigation in a study with a larger, more diverse sample.

The Association between Neighborhood Walkability and Physical Activity in a Behavioral Weight Loss Trial Testing the Addition of Remotely Delivered Feedback Messages to Self-Monitoring.

Adding feedback messages (FB) to self-monitoring (SM) may reinforce behavior change. However, socio-environmental conditions (e.g., limited access to parks or low walkability) may limit one's ability to respond to FB focused on physical activity (PA). In this analysis, we hypothesized that high neighborhood walkability will positively modify the treatment effect of FB on PA, and residents of high walkability neighborhoods will achieve higher PA levels at 12 months than those in low walkability neighborhoods. The study is a secondary analysis of a 12-month behavioral weight-loss trial. Adults with overweight/obesity were randomized to SM + FB (n = 251) or SM alone (n = 251). SM + FB group received smartphone pop-up messages thrice/week tailored to their PA SM data. The assessment included neighborhood walkability via Walk Score (low [<50] vs. high [≥50]), moderate to vigorous PA (MVPA) and step count via Fitbit Charge 2™, and weight via smart scale. We report adjusted linear regression coefficients (b) with standard errors (SE). The analysis included participants who were primarily white, female, and with obesity. In adjusted models, neighborhood walkability did not moderate the effect of treatment assignment on log-transformed (ln) MVPA or steps count over 12 months. The SM + FB group had greater lnMVPA than the SM group, but lnMVPA and steps were similar between walkability groups. There were no significant interactions for group and time or group, time, and walkability. These findings suggest that adding FB to SM had a small but significant positive impact on PA over 12 months, but neighborhood walkability did not moderate the treatment effect of FB on PA.

Effect of Treatment of OSA With CPAP on Glycemic Control in Adults With Type 2 Diabetes: The Diabetes Sleep Treatment Trial (DSTT).

OBJECTIVE: The effect of obstructive sleep apnea (OSA) treatment with continuous positive airway pressure (CPAP) on glycemic measures in patients with type 2 diabetes (T2D) remains unclear. We aimed to determine whether CPAP treatment of OSA improves glycemic measures in patients with T2D. METHODS: This randomized controlled trial (N = 98) examined changes in glycemic measures following 12 weeks of active (n = 49) or sham (n = 49) CPAP and consideried participants' adherence to CPAP therapy (percentage of days with ≥4 hours use and average hours/day of use). RESULTS: Baseline treatment groups were similar. Regarding the efficacy of active vs sham-CPAP over time, at 6 weeks, both groups had similar reductions in fructosamine (mean difference [MD], 95% confidence interval [CI]: CPAP -13.10 [-25.49 to -0.7] vs. sham -7.26 [-20.2 to 5.69]; P = .519) but different in HbA1c (CPAP -0.24 [-0.48 to -0.003] vs sham 0.15 [-0.10 to 0.4]; P = .027). At 12 weeks, reductions in HbA1c values were similar by group (CPAP -0.26 [-0.53 to 0.002] vs sham -0.24 [-0.53 to 0.04]; P = .924). HbA1c reductions were associated with a greater percentage of cumulative days of CPAP usage ≥4 hours per day (b [SE] = 0.006 [0.002]; P = .013) and cumulative hours of CPAP use (b [SE] = 0.08 [0.08]; P = .012). CPAP use of ≥7 hours was associated with a significant reduction in HbA1c (b [SE] 0.54 [0.16]; P = .0012). CONCLUSION: CPAP treatment of OSA did not result in sustained improved glycemic control compared to sham in the intent-to-treat analysis. CPAP adherence was associated with greater improvements in glycemic control.

Metabolic outcomes in adults with type 2 diabetes and sleep disorders.

PURPOSE: Insomnia is frequently co-morbid with obstructive sleep apnea (OSA); the effect of insomnia or co-morbid insomnia and OSA (OSA + I) on associated metabolic outcomes in adults with type 2 diabetes (T2D) remains unclear. This study in adults with T2D compared metabolic outcomes among persons with OSA, insomnia, or OSA + I. METHODS: This study analyzed baseline data from the Diabetes Sleep Treatment Trial of persons recruited for symptoms of OSA or poor sleep quality. Home sleep studies determined OSA presence and severity. Insomnia was evaluated using the Insomnia Severity Index. Height and weight to calculate body mass index (BMI) and blood for laboratory values were obtained. Multivariate general linear models were used to examine the impact of the type of sleep disorder and sociodemographic, lifestyle, and sleep risk factors on metabolic outcomes. RESULTS: Participants (N = 253) were middle-aged (56.3 ± 10.5 years), white (60.5%), obese (mean BMI of 35.3 ± 7.1 kg/m2), and male (51.4%) with poor glucose control (mean HbA1c of 8.0 ± 1.8%). Most participants had OSA + I (42.7%) or insomnia only (41.0%). HbA1c and BMI differed among the sleep disorder groups. In addition, in the adjusted models, having insomnia only, compared to OSA only, was associated on average with higher HbA1c levels (b = 1.08 ± 0.40, p < 0.007) and lower BMI (b = - 7.03 ± 1.43, p < 0.001). CONCLUSIONS: Findings suggest that insomnia frequently co-exists with OSA, is independently associated with metabolic outcomes in adults with T2D, and should be considered in investigations of the effects of OSA in persons with T2D. TRIAL REGISTRATION: Diabetes-Obstructive Sleep Apnea Treatment Trial (NCT01901055), https: Clinicaltrials.gov/ct2/show/NCT01901055; Registration date: July 17, 2013.

The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial.

BACKGROUND: Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. OBJECTIVE: The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. METHODS: All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants' dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). RESULTS: Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: -2.12%, 95% CI -3.04% to -1.21%, P<.001; SM: -2.39%, 95% CI -3.32% to -1.47%; P<.001), but no difference between the groups (-0.27%; 95% CI -1.57% to 1.03%; t =-0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=-0.10; 95% CI -0.13 to -0.07; t =-5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001). CONCLUSIONS: There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools. TRIAL REGISTRATION: Clinicaltrials.gov NCT03367936; https://clinicaltrials.gov/ct2/show/NCT03367936.

The association between sleep health and weight change during a 12-month behavioral weight loss intervention.

BACKGROUND: Prior research on the relationship between sleep and attempted weight loss failed to recognize the multidimensional nature of sleep. We examined the relationship between a composite measure of sleep health and change in weight and body composition among adults in a weight loss intervention. METHODS: Adults (N = 125) with overweight or obesity (50.3 ± 10.6 years, 91% female, 81% white) participated in a 12-month behavioral weight loss intervention, with assessments of sleep, weight, fat mass, and fat-free mass at baseline, 6 months, and 12 months. Six sleep dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as "good" or "poor" using questionnaires and actigraphy. A composite score was calculated by summing the number of "good" dimensions. Obstructive sleep apnea (OSA) was assessed in a subsample (n = 117), using the apnea-hypopnea index (AHI) to determine OSA severity. Linear mixed modeling was used to examine the relationships between sleep health and outcomes of percent weight, fat mass, or fat-free mass change during the subsequent 6-month interval, adjusting for age, sex, bed partner, and race; an additional model adjusted for AHI. RESULTS: Mean baseline and 6-month sleep health was 4.5 ± 1.1 and 4.5 ± 1.2, respectively. Mean weight, fat mass, and fat-free mass changes from 0 to 6 months were -9.3 ± 6.1%, -16.9 ± 13.5%, and -3.4 ± 3.4%, respectively, and 0.4 ± 4.8%, -0.3 ± 10.3%, and 0.7 ± 4.1% from 6 to 12 months. Better sleep health was associated with greater subsequent weight loss (P = 0.016) and fat loss (P = 0.006), but not fat-free mass loss (P = 0.232). Following AHI adjustment, the association between sleep health and weight loss was attenuated (P = 0.102) but remained significant with fat loss (P = 0.040). Regularity, satisfaction, timing, and efficiency were each associated with weight and/or fat loss (P ≤ 0.041). CONCLUSIONS: Better sleep health was associated with greater weight and fat loss, with associations attenuated after accounting for OSA severity. Future studies should explore whether improving sleep health, OSA, or the combination improves weight loss.

Psychiatric Medication Changes Associated With Increased Rate of Medical Readmissions in Patients With Serious Mental Illness.

ABSTRACT: To identify the impact of postdischarge psychiatric medication changes on general medical readmissions among patients with serious mental illness (SMI; bipolar disorder, major depressive disorder, and schizophrenia), claims from a 5% national sample of Medicare fee-for-service (FFS) beneficiaries hospitalized between 2013 and 2016 were studied. A total of 165,490 Medicare FFS beneficiaries with SMI 18 years or older with at least 1 year of continuous Medicare enrollment were identified. Within 30 days of discharge from index admission, 47.4% experienced a psychiatric medication change-including 75,892 beneficiaries experiencing a deletion and 55,713 experiencing an addition. After adjusting for potential confounders, those with a medication change experienced an 10% increase in the odds of 30-day readmission (odds ratio, 1.10; SE, 0.019; p < 0.001). Comorbid drug use disorder was also associated with an increased odds of readmission after controlling for other covariates. These findings suggest important factors that clinicians should be aware of when discharging patients with SMI.

Reliability and Validity of Survey Instruments to Measure Work-Related Fatigue in the Emergency Medical Services Setting: A Systematic Review.

BACKGROUND: This study sought to systematically search the literature to identify reliable and valid survey instruments for fatigue measurement in the Emergency Medical Services (EMS) occupational setting. METHODS: A systematic review study design was used and searched six databases, including one website. The research question guiding the search was developed a priori and registered with the PROSPERO database of systematic reviews: "Are there reliable and valid instruments for measuring fatigue among EMS personnel?" (2016:CRD42016040097). The primary outcome of interest was criterion-related validity. Important outcomes of interest included reliability (e.g., internal consistency), and indicators of sensitivity and specificity. Members of the research team independently screened records from the databases. Full-text articles were evaluated by adapting the Bolster and Rourke system for categorizing findings of systematic reviews, and the rated data abstracted from the body of literature as favorable, unfavorable, mixed/inconclusive, or no impact. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology was used to evaluate the quality of evidence. RESULTS: The search strategy yielded 1,257 unique records. Thirty-four unique experimental and non-experimental studies were determined relevant following full-text review. Nineteen studies reported on the reliability and/or validity of ten different fatigue survey instruments. Eighteen different studies evaluated the reliability and/or validity of four different sleepiness survey instruments. None of the retained studies reported sensitivity or specificity. Evidence quality was rated as very low across all outcomes. CONCLUSIONS: In this systematic review, limited evidence of the reliability and validity of 14 different survey instruments to assess the fatigue and/or sleepiness status of EMS personnel and related shift worker groups was identified.

Effect of Task Load Interventions on Fatigue in Emergency Medical Services Personnel and Other Shift Workers: A Systematic Review.

BACKGROUND: Modifying the task load of Emergency Medical Services (EMS) personnel may mitigate fatigue, sleep quality and fatigue related risks. A review of the literature addressing task load interventions may benefit EMS administrators as they craft policies related to mitigating fatigue. We conducted a systematic review of the peer-reviewed literature to address the following question: "In EMS personnel, do task load interventions mitigate fatigue, mitigate fatigue-related risks, and/or improve sleep?" (PROSPERO 2016:CRD42016040114). METHODS: We performed a systematic review of the literature that described use of randomized controlled trials, quasi-experimental studies, and observational study designs. We retained and reviewed research that involved EMS personnel or similar shift worker groups 18 years of age and older. Studies of 'healthy volunteers' and non-shift worker populations were excluded. Studies were included where the methodology of the study implied a theoretical framework of task load (or workload) affecting fatigue, and then fatigue related outcomes. Outcomes of interest included personnel safety, patient safety, personnel performance, acute fatigue, and cost to system. We used the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology to summarize findings and assess quality of evidence from very low to high quality. RESULTS: The search strategy yielded 3,394 unique records resulting in 58 records included as potentially eligible. An additional 69 studies were reviewed in full following searches of bibliographies. We detected wide variation in the description and measurement of task load in the retained and excluded research. Among 127 potentially relevant studies reviewed in full, five were judged eligible. None of the retained studies reported findings germane to personnel safety, patient safety, or cost to system. We judged most studies to have serious or very serious risk of bias. CONCLUSIONS: The effect of task load interventions on fatigue, fatigue-related risks, and/or sleep quality was not estimable and the overall quality of evidence was judged low or very low. There was considerable heterogeneity in how task load was defined and measured.

Shorter Versus Longer Shift Durations to Mitigate Fatigue and Fatigue-Related Risks in Emergency Medical Services Personnel and Related Shift Workers: A Systematic Review.

BACKGROUND: This study comprehensively reviewed the literature on the impact of shorter versus longer shifts on critical and important outcomes for Emergency Medical Services (EMS) personnel and related shift worker groups. METHODS: Six databases (e.g., PubMed/MEDLINE) were searched, including one website. This search was guided by a research question developed by an expert panel a priori and registered with the PROSPERO database of systematic reviews (2016:CRD42016040099). The critical outcomes of interest were patient safety and personnel safety. The important outcomes of interest were personnel performance, acute fatigue, sleep and sleep quality, retention/turnover, long-term health, burnout/stress, and cost to system. Screeners worked independently and full-text articles were assessed for relevance. Data abstracted from the retained literature were categorized as favorable, unfavorable, mixed/inconclusive, or no impact toward the shorter shift duration. This research characterized the evidence as very low, low, moderate, or high quality according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. RESULTS: The searched yielded n = 21,674 records. Of the 480 full-text articles reviewed, 100 reported comparisons of outcomes of interest by shift duration. We identified 24 different shift duration comparisons, most commonly 8 hours versus 12 hours. No one study reported findings for all 9 outcomes. Two studies reported findings linked to both critical outcomes of patient and personnel safety, 34 reported findings for one of two critical outcomes, and 64 did not report findings for critical outcomes. Fifteen studies were grouped to compare shifts <24 hours versus shifts ≥24 hours. None of the findings for the critical outcomes of patient and personnel safety were categorized as unfavorable toward shorter duration shifts (<24 hours). Nine studies were favorable toward shifts <24 hours for at least one of the 7 important outcomes, while findings from one study were categorized as unfavorable. Evidence quality was low or very low. CONCLUSIONS: The quality of existing evidence on the impact of shift duration on fatigue and fatigue-related risks is low or very low. Despite these limitations, this systematic review suggests that for outcomes considered critical or important to EMS personnel, shifts <24 hours in duration are more favorable than shifts ≥24 hours.

Navigating Precision Oncology: Insights from an Integrated Clinical Data and Biobank Repository Initiative across a Network Cancer Program.

Advancing cancer treatment relies on the rapid translation of new scientific discoveries to patient care. To facilitate this, an oncology biobank and data repository program, also referred to as the "Moonshot" program, was launched in 2021 within the Integrated Network Cancer Program of the Allegheny Health Network. A clinical data program (CDP) and biospecimen repository were established, and patient data and blood and tissue samples have been collected prospectively. To date, the study has accrued 2920 patients, predominantly female (61%) and Caucasian (90%), with a mean age of 64 ± 13 years. The most common cancer sites were the endometrium/uterus (12%), lung/bronchus (12%), breast (11%), and colon/rectum (11%). Of patients diagnosed with cancer, 34% were diagnosed at stage I, 25% at stage II, 26% at stage III, and 15% at stage IV. The CDP is designed to support our initiative in advancing personalized cancer research by providing a comprehensive array of patient data, encompassing demographic characteristics, diagnostic details, and treatment responses. The "Moonshot" initiative aims to predict therapy responses and clinical outcomes through cancer-related biomarkers. The CDP facilitates this initiative by fostering data sharing, enabling comparative analyses, and informing the development of novel diagnostic and therapeutic methods.

Identifying Predictors of Adherence to the Physical Activity Goal: A Secondary Analysis of the SMARTER Weight Loss Trial.

INTRODUCTION/PURPOSE: Research is needed to inform tailoring supportive strategies for promoting physical activity (PA) in the context of behavioral treatment of obesity. We aimed to identify baseline participant characteristics and short-term intervention response predictors associated with adherence to the study-defined PA goal in a mobile health (mHealth) weight loss trial. METHODS: A secondary analysis was conducted of a 12-month weight loss trial (SMARTER) that randomized 502 adults with overweight or obesity to either self-monitoring of diet, PA, and weight with tailored feedback messages ( n = 251) or self-monitoring alone ( n = 251). The primary outcome was average adherence to the PA goal of ≥150 min·wk -1 of moderate- and vigorous-intensity aerobic activities (MVPA) from Fitbit Charge 2™ trackers over 52 wk. Twenty-five explanatory variables were considered. Machine learning methods and linear regression were used to identify predictors of adherence to the PA goal. RESULTS: The sample ( N = 502) was mostly female (80%), White (82%) with the average age of 45 ± 14.4 yr and body mass index of 33.7 ± 4.0 kg·m -2 . Machine learning methods identified PA goal adherence for the first week as the most important predictor of long-term PA goal adherence. In the parsimonious linear regression model, higher PA goal adherence for the first week, greater PA FB messages opened, older age, being male, higher education, being single and not having obstructive sleep apnea were associated with higher long-term PA goal adherence. CONCLUSIONS: To our knowledge, this is the first study using machine learning approaches to identify predictors of long-term PA goal adherence in a mHealth weight loss trial. Future studies focusing on facilitators or barriers to PA among young and middle-age adults and women with low PA goal adherence are warranted.

Intensive Daily Symptom and Function Monitoring Is Feasible and Acceptable to Women Undergoing First-Line Chemotherapy for Gynecologic Cancer.

BACKGROUND: Women receiving chemotherapy for gynecologic cancer (GC) experience severe symptoms with associated functional changes. Understanding day-to-day symptom and function variation within and across chemotherapy treatment cycles could inform improved symptom management, but such studies are rare and may be infeasible in clinical care. OBJECTIVE: The aim of this study was to evaluate feasibility and acceptability of daily symptom monitoring combined with objective and self-reported functional assessments every 21 days during active chemotherapy for GC. METHODS: Thirty women enrolled in a prospective observational study during first-line chemotherapy completed a daily symptom and falls diary during their entire chemotherapy treatment period. Patient-reported outcomes and objective symptom and function testing were assessed before each chemotherapy appointment. Study outcomes included accrual and attrition rates, completion of study assessments, and qualitative perceptions of study participation. RESULTS: Participants were 92% White, 60% had high school or higher education, 68% were married/partnered, and 62% had stage III or IV cancer at diagnosis. The study had an 83% accrual rate, 6.6% early withdrawal rate, and 17% total attrition rate. Missing assessments for prechemotherapy patient-reported outcomes and objective assessments ranged from 27% to 35% and 35% to 47% respectively, with a general decrease across cycles. Daily diary completion rate was 83% overall. Participants rated study participation positively. CONCLUSIONS: Intensive daily symptom and function monitoring was feasible and acceptable to GC patients and may provide a sense of symptom controllability. IMPLICATIONS FOR PRACTICE: Daily symptom and function monitoring in research studies may provide patients with information to support symptom discussions with the clinical team. Future work should develop proactive symptom management interventions using personalized symptom trajectories.

Effect of tailored, daily feedback with lifestyle self-monitoring on weight loss: The SMARTER randomized clinical trial.

OBJECTIVE: This study aimed to test the efficacy of self-monitoring and feedback (SM+FB) versus SM without FB (SM) in a behavioral weight-loss intervention at 6 months. METHODS: This was a randomized clinical trial. Eligibility criteria included the following: ≥18 years of age, BMI ≥ 27 and ≤43, smartphone user, and ability to engage in moderate physical activity. All participants received a 90-minute 1:1 counseling session, a Fitbit Charge 2, and a digital scale for SM. SM+FB participants were provided access to a customized smartphone application that provided three daily FB messages. The primary outcome was percentage of weight change from 0 to 6 months. RESULTS: The sample (N = 502) was 45 (SD 14.4) years old, BMI was 33.7 (SD 4.00) kg/m2 , 79.5% of participants were female (n = 399), and 84.3% were White (n = 423). At 6 months, there was 85.86% retention and a significant percentage of weight change in both groups (SM+FB: -3.16%, 95% CI: -3.85% to -2.47%, p < 0.0001; SM: -3.20%, 95% CI: -3.86% to -2.54%, p < 0.0001) but no significant between-group mean difference (-0.04%, 95% CI: -0.99% to 0.91%, p = 0.940). A ≥5% weight loss was achieved by 31.9% of the SM+FB group and 28.3% of the SM group. CONCLUSIONS: There was no significant between-group difference in weight loss at 6 months.

Bidirectional relationship between sleep and sedentary behavior in adults with overweight or obesity: A secondary analysis.

STUDY OBJECTIVES: The relationships between daytime sedentary behavior and that night's sleep and sleep and next day's sedentary behavior are unknown. The purpose of this analysis was to examine these potentially bidirectional associations. METHODS: This study was a secondary analysis of baseline data from an ecological momentary assessment study to determine the triggers for dietary lapses during a weight loss intervention. Sedentary behavior, physical activity, and sleep were objectively measured using accelerometers. Linear mixed modeling was used to examine the bidirectional multivariate associations between activity and sleep characteristics for each outcome examined separately. The models included sex, age, body mass index (BMI), education, and day of the week (weekday vs. weekend). RESULTS: Participants were predominantly white (81.5%) and female (88.9%) with a mean age of 51.2 ± 10.6 years. Longer previous night's total sleep time (TST) (b = -0.320, standard error [SE] = 0.060; p < .001) and being a weekend (b = -63.845, SE = 9.406; p < .001) were associated with less sedentary time the next day. More daytime sedentary time was associated with less wake after sleep onset (b = -0.018, SE = 0.008; p = .016), fewer awakenings (b = -0.010, SE = 0.004; p = .016), and less TST (b = -0.060, SE = 0.028; p = .029) that night. CONCLUSIONS: The bidirectional relationships between sedentary time and sleep characteristics are complex and may vary depending on participant characteristics and duration of sedentary and sleep time. Interventions to decrease sedentary behavior may benefit by targeting sleep duration and weekday activity.

Substantial hospital level variation in all-cause readmission rates among medicare beneficiaries with serious mental illness.

BACKGROUND: Patients with serious mental illness (i.e., SMI; bipolar disorder, major depressive disorder, and schizophrenia) are at increased risk of readmission, yet little is known about the extent to which readmission rates among these patients vary across hospitals. The purpose of this study was to examine the variation across hospitals in readmissions for patients with SMI and differences in the characteristics of hospitals with the highest and lowest adjusted readmission rates. METHODS: We conducted a cross-sectional analysis of pooled inpatient claims from 2013-2016. Mixed logit models with hospital random effects were used to estimate the hospital-level variance. The sample included patients with SMI from a 5% sample of fee-for-service Medicare beneficiaries. RESULTS: We identified 2066 hospitals with at least 30 index admissions for Medicare beneficiaries with SMI. In multivariate analyses, factors most strongly associated with increased risk of readmission included substance use disorder (OR 2.311; p < 0.001) and end stage renal disease (OR 2.024; p < 0.001). Unadjusted readmission for hospitals at the 5th and 95th percentiles of performance were 7.05% and 15.24%, respectively, constituting an 8.2% difference. Adjusting for patient and community characteristics reduced the spread in readmission rates between the 5th and 95th percentiles of hospitals by 1.0% (i.e. to 7.2%). Hospitals in the lowest vs. highest quintiles of adjusted readmission rates were more likely to be teaching hospitals (11.1% vs. 16.7%; p < 0.05) and located in the South (37.7% vs. 40.4%) or Midwest (19.8% vs. 30.0%; p < 0.001 for region differences). CONCLUSIONS: There is substantial hospital-level variation in readmission rates among patients with serious mental illness, even after adjusting for patient and community characteristics. This has implications for policy guiding investment in hospital-based services and community resources, to improve transitions of care for patients with SMI.