Weight change and mental health status in a behavioral weight loss trial.

BACKGROUND: Obesity, depression, and anxiety often co-occur, but research on weight change and mental health status is limited. This analysis examined how the mental component score (MCS-12) from the Short Form health survey changed over 24 months in weight loss trial participants with vs. without treatment seeking for affective symptoms (TxASx) and by weight change quintiles. METHODS: Participants with complete data (n = 1163) were analyzed from enrollees in a cluster-randomized, behavioral weight loss trial in rural U.S. Midwestern primary care practices. Participants received a lifestyle intervention with different delivery models, including in-clinic individual, in-clinic group, or telephone group counseling visits. Participants were stratified by baseline TxASx status and 24-month weight change quintiles. Mixed models were used to estimate MCS-12 scores. RESULTS: There was a significant group-by-time interaction at the 24-month follow-up. The largest 0-24 month increase in MCS-12 scores (+5.3 points [12 %]) was observed in participants with TxASx who lost the most weight during the trial, while the largest decrease in MCS-12 scores (-1.8 points [-3 %]) was observed in participants without TxASx who gained the most weight (p < 0.001). LIMITATIONS: Notable limitations included self-reported mental health, the observational analytical design, and a largely homogenous source population, as well as the possibility of reverse causation biasing some findings. CONCLUSIONS: Mental health status generally improved, particularly among participants with TxASx who experienced significant weight loss. Those without TxASx who gained weight, however, had a decline in mental health status over 24 months. Replication of these findings is warranted.

A randomized controlled trial to test the effectiveness of two technology-enhanced diabetes prevention programs in primary care: The DiaBEAT-it study.

Objective: To evaluate the effectiveness of two technology-enhanced interventions for diabetes prevention among adults at risk for developing diabetes in a primary care setting. Methods: The DiaBEAT-it study employed a hybrid 2-group preference (Choice) and 3-group randomized controlled (RCT) design. This paper presents weight related primary outcomes of the RCT arm. Patients from Southwest Virginia were identified through the Carilion Clinic electronic health records. Eligible participants (18 and older, BMI ≥ 25, no Type 2 Diabetes) were randomized to either Choice (n = 264) or RCT (n = 334). RCT individuals were further randomized to one of three groups: (1) a 2-h small group class to help patients develop a personal action plan to prevent diabetes (SC, n = 117); (2) a 2-h small group class plus automated telephone calls using an interactive voice response system (IVR) to help participants initiate weight loss through a healthful diet and regular physical activity (Class/IVR, n = 110); or (3) a DVD with same content as the class plus the same IVR calls over a period of 12 months (DVD/IVR, n = 107). Results: Of the 334 participants that were randomized, 232 (69%) had study measured weights at 6 months, 221 (66%) at 12 months, and 208 (62%) at 18 months. Class/IVR participants were less likely to complete weight measures than SC or DVD/IVR. Intention to treat analyses, controlling for gender, race, age and baseline BMI, showed that DVD/IVR and Class/IVR led to reductions in BMI at 6 (DVD/IVR -0.94, p < 0.001; Class/IVR -0.70, p < 0.01), 12 (DVD/IVR -0.88, p < 0.001; Class/IVR-0.82, p < 0.001) and 18 (DVD/IVR -0.78, p < 0.001; Class/IVR -0.58, p < 0.01) months. All three groups showed a significant number of participants losing at least 5% of their body weight at 12 months (DVD/IVR 26.87%; Class/IVR 21.62%; SC 16.85%). When comparing groups, DVD/IVR were significantly more likely to decrease BMI at 6 months (p < 0.05) and maintain the reduction at 18 months (p < 0.05) when compared to SC. There were no differences between the other groups. Conclusions: The DiaBEAT-it interventions show promise in responding to the need for scalable, effective methods to manage obesity and prevent diabetes in primary care settings that do not over burden primary care clinics and providers. Registration: https://clinicaltrials.gov/ct2/show/NCT02162901, identifier: NCT02162901.

Human papillomavirus vaccine beliefs and practice characteristics in rural and urban adolescent care providers.

BACKGROUND: The human papillomavirus (HPV) vaccine is recommended for all adolescents age 11-12 years. HPV vaccine coverage remains suboptimal in the United States though, particularly in rural areas. We surveyed adolescent immunization providers in two Midwestern states to assess rural vs. urban differences in HPV vaccine resources, practices, and attitudes. METHODS: A cross-sectional survey was sent to all licensed adolescent care providers in a subset of urban and rural counties in Minnesota and Wisconsin during 2019. Multivariable regression was used to identify attitudes and practices that differentiated rural vs. urban providers. RESULTS: There were 437 survey respondents (31% rural). Significantly fewer rural providers had evening/weekend adolescent vaccination appointments available (adjusted odds ratio (aOR) = 0.21 [95% confidence interval (CI): 0.12, 0.36]), had prior experience with adolescent vaccine quality improvement projects (aOR = 0.52 [95% CI: 0.28, 0.98]), and routinely recommended HPV vaccine during urgent/acute care visits (aOR = 0.37 [95% CI: 0.18, 0.79]). Significantly more rural providers had standing orders to administer all recommended adolescent vaccines (aOR = 2.81 [95% CI: 1.61, 4.91]) and reported giving HPV vaccine information to their patients/families before it is due (aOR = 3.10 [95% CI: 1.68, 5.71]). CONCLUSIONS: Rural vs. urban differences in provider practices were mixed in that rural providers do not implement some practices that may promote HPV vaccination, but do implement other practices that promote HPV vaccination. It remains unclear how the observed differences would affect HPV vaccine attitudes or adolescent vaccination decisions for parents in rural areas.

Effects of a Digital Diabetes Prevention Program: An RCT.

INTRODUCTION: In light of the need to expand the reach and access of clinically proven digital Diabetes Prevention Programs (d-DPPs) and the need for rigorous evidence of effectiveness, the purpose of this study was to determine the effectiveness of a digital Diabetes Prevention Program for improving weight, HbA1c, and cardiovascular risk factors among people with prediabetes compared to enhanced standard care plus waitlist control. STUDY DESIGN: This was a single-blind RCT among participants at risk of developing type 2 diabetes and included 12 months of follow-up. SETTING/PARTICIPANTS: A total of 599 volunteer patients with prediabetes were recruited primarily through electronic medical records and primary care practices. INTERVENTION: Participants were randomized to either a d-DPP (n=299) or a single-session small-group diabetes-prevention education class (n=300) focused on action planning for weight loss. The d-DPPs consisted of 52 weekly sessions, lifestyle coaching, virtual peer support, and behavior tracking tools. MAIN OUTCOME MEASURES: The primary outcome was a change in HbA1c from baseline to 12 months using intent-to-treat analyses. On the basis of multiple comparisons of endpoints, 95% CIs are presented and 2-sided p<0.025 was required for statistical significance. Secondary outcomes included body weight and cardiovascular disease risk factors. RESULTS: Among 599 randomized participants (mean age=55.4 years, 61.4% women), 483 (80%) completed the study. The d-DPPs produced significantly greater reductions in HbA1c (0.08%, 95% CI= -0.12, -0.03) and percentage change in body weight (-5.5% vs -2.1%, p<0.001) at 12 months. A greater proportion of the d-DPPs group achieved a clinically significant weight loss ≥5% (43% vs 21%, p<0.001), and more participants shifted from prediabetes to normal HbA1c range (58% vs 48%, p=0.04). Engagement in d-DPPs was significantly related to improved HbA1c and weight loss. CONCLUSIONS: This d-DPPs demonstrated clinical effectiveness and has significant potential for widespread dissemination and impact, particularly considering the growing demand for telemedicine in preventive healthcare services. TRIAL REGISTRATION: This study is registered at www. CLINICALTRIALS: gov (ClinicalTrials.gov Identifier: NCT03312764).

Affective disorders, weight change, and patient engagement in a rural behavioral weight loss trial.

BACKGROUND: Adults in rural areas have a higher prevalence of obesity and some mental health conditions. The degree to which mental health influences weight loss among rural residents remains unclear. This study evaluated changes in body weight, physical activity, diet, and program engagement outcomes in a cohort of participants with vs. without an affective disorder in a behavioral weight loss trial. METHODS: A sample of 1407 adults with obesity were recruited from rural U.S. primary care practices to participate in a weight loss trial. In this secondary analysis, participants were stratified by those with vs. without an affective disorder at baseline. Mixed models were used to estimate changes in outcomes over 24 months. RESULTS: One-third of participants (n = 468) had an affective disorder. After covariate adjustment, both groups experienced significant weight loss over 24 months, but weight loss was significantly less among those with an affective disorder at all follow-up times (all p's < 0.001; 24-month weight loss -2.7 ±â€¯0.4 vs. -4.8 ±â€¯0.3 kg). Compared to those without an affective disorder, participants with an affective disorder also had significantly less improvement in physical activity and fruit/vegetable consumption, lower attendance at weight loss sessions, and less engagement in setting weight loss goals and strategies. CONCLUSION: Participants with an affective disorder lost less body weight and less improvement in lifestyle measures over 24 months. These trends paralleled reduced engagement in critical intervention activities such as weight loss session attendance. Future interventions should consider additional methods to minimize disengagement in adults with underlying affective disorders.

Chronic pain and weight regain in a lifestyle modification trial.

OBJECTIVE: Obesity and chronic pain often co-occur and exert bidirectional influences on one another. How patients with obesity and chronic pain respond to weight loss treatments, however, remains unclear. This study evaluated body weight, physical activity, and diet outcomes in participants with and without chronic pain in a 2-year behavioral weight loss trial. METHODS: An analytical cohort of 397 adults was assembled from a Midwestern healthcare system that participated in the larger trial. Participants with chronic pain 1 year prior to, or during, the trial were identified using a validated medical records algorithm. Mixed models were used to estimate changes in outcomes over 24 months. RESULTS: One-third of participants (n = 130) had chronic pain. After adjustment for age, sex, body mass index, and trial arm, weight loss was similar in both groups at 6-months (-7.0 ± 0.8 kg with chronic pain vs. -7.7 ± 0.6 kg without). Participants with chronic pain had significantly less weight loss at 24-months relative to those without (-3.6 ± 0.5 vs. -5.2 ± 0.4 kg; p = 0.007). Physical activity, screen time, dietary fat, fruit/vegetable consumption, and sugar-sweetened beverage intake improved similarly in both groups over time. CONCLUSIONS: Participants with chronic pain lost ∼33% less weight over 2 years, which was driven by greater weight regain after the first 6 months. Future research should test tailored weight loss maintenance strategies for individuals with chronic pain.

Preventing diabetes with digital health and coaching for translation and scalability (PREDICTS): A type 1 hybrid effectiveness-implementation trial protocol.

BACKGROUND: Diabetes prevention remains a top public health priority; digital approaches are potential solutions to existing scalability and accessibility challenges. There remains a gap in our understanding of the relationship between effectiveness, costs, and potential for sustained implementation of digital diabetes prevention strategies within typical healthcare settings. PURPOSE: To describe the methods and design of a type 1 hybrid effectiveness-implementation trial of a digital diabetes prevention program (DPP) using the iPARIHS and RE-AIM frameworks. METHODS: The trial will contrast the effects of two DPP interventions: (1) small group, in-person class, and (2) a digital DPP consisting of small group support, personalized health coaching, digital tracking tools, and weekly behavior change curriculum. Each intervention includes personal action planning with a focus on key elements of the lifestyle intervention from the CDC National DPP. Adults at risk for diabetes (BMI ≥25 and 5.7% ≤ HbA1c ≤ 6.4) will be randomly assigned to either the intervention group (n = 241) or the small group (n = 241). Assessment of primary (HbA1c) and secondary (weight loss, costs, cardiovascular risk factors) outcomes will occur at baseline, 4, and 12 months. Additionally, the trial will explore the potential for future adoption, implementation, and sustainability of the digitally-based intervention within a regional healthcare system based on key informant interviews and assessments of organizational administrators and primary care physicians. CONCLUSION: This trial of a digital DPP will allow the research team to determine the relationships between reach, effectiveness, implementation, and costs.

Factors influencing high respiratory mortality in coal-mining counties: a repeated cross-sectional study.

BACKGROUND: Previous studies have associated elevated mortality risk in central Appalachia with coal-mining activities, but few have explored how different non-coal factors influence the association within each county. Consequently, there is a knowledge gap in identifying effective ways to address health disparities in coal-mining counties. To specifically address this knowledge gap, this study estimated the effect of living in a coal-mining county on non-malignant respiratory diseases (NMRD) mortality, and defined this as "coal-county effect." We also investigated what factors may accentuate or attenuate the coal-county effect. METHODS: An ecological epidemiology protocol was designed to observe the characteristics of three populations and to identify the effects of coal-mining on community health. Records for seven coal-mining counties (n = 19,692) were obtained with approvals from the Virginia Department of Health Office of Vital Statistics for the years 2005 to 2012. Also requested were records from three adjacent coal counties (n = 10,425) to provide a geographic comparison. For a baseline comparison, records were requested for eleven tobacco-producing counties (n = 27,800). We analyzed the association of 57,917 individual mortality records in Virginia with coal-mining county residency, county-level socioeconomic status, health access, behavioral risk factors, and coal production. The development of a two-level hierarchical model allowed the coal-county effect to vary by county-level characteristics. Wald tests detected sets of significant factors explaining the variation of impacts across counties. Furthermore, to illustrate how the model estimations help explain health disparities, two coal-mining county case studies were presented. RESULTS: The main result revealed that coal-mining county residency increased the probability of dying from NMRD. The coal-county effect was accentuated by surface coal mining, high smoking rates, decreasing health insurance coverage, and a shortage of doctors. In Virginia coal-mining regions, the average coal-county effect increased by 147% (p-value< 0.01) when one doctor per 1000 left, and the effect increased by 68% (p-value< 0.01) with a 1% reduction of health insurance rates, holding other factors fixed. CONCLUSIONS: This study showed a high mortality risk of NMRD associated with residents living in Virginia coal-mining counties. Our results also revealed the critical role of health access in reducing health disparities related to coal exposure.

Effectiveness of DVD vs. group-initiated diabetes prevention on information uptake for high & low health literacy participants.

OBJECTIVE: This study evaluates the effectiveness of technology versus in-person, group-initiated diabetes prevention to enhance comprehension of learning objectives between patients with differing health literacy (HL). METHODS: Evidence-based content through either a DVD (n = 217) or in-person, group class (n = 225) to initiate the intervention. A teach-back call was used to assess comprehension of, and reinforce, learning objectives. Chi-squared was used to determine differences between conditions (DVD vs Class) and HL levels (High n = 361 vs. Low n = 81) and regression analyses were used to examine relationships. RESULTS: DVD participants performed significantly better across teach back questions (15.4 ± 2.5 v. 14.8 ± 2.6, p < 0.01), demonstrated comprehension in fewer teach-back rounds (1.9 ± 0.7 v. 2.1 ± 0.7, p < 0.01), and answered more questions correctly on the first try (4.2 ± 1.6 v. 3.4 ± 1.8, p < 0.01). Models for HL levels and modality by HL level were statistically significant (p < 0.01) favoring the DVD. CONCLUSION: Initiating a diabetes prevention program with the use of a DVD appears to be a superior option to in-person, class sessions. Teach-back and teach-to-goal strategies enables participants of both high and low health literacy levels to receive and confirm mastery of diabetes prevention objectives. PRACTICE IMPLICATIONS: A teach-back call may improve information uptake increasing the likelihood of health behavior uptake.

Brief self-efficacy scales for use in weight-loss trials: Preliminary evidence of validity.

Self-efficacy is a commonly included cognitive variable in weight-loss trials, but there is little uniformity in its measurement. Weight-loss trials frequently focus on physical activity (PA) and eating behavior, as well as weight loss, but no survey is available that offers reliable measurement of self-efficacy as it relates to each of these targeted outcomes. The purpose of this study was to test the psychometric properties of brief, pragmatic self-efficacy scales specific to PA, healthful eating and weight-loss (4 items each). An adult sample (n = 1,790) from 28 worksites enrolled in a worksite weight-loss program completed the self-efficacy scales, as well as measures of PA, dietary fat intake, and weight, at baseline, 6-, and 12-months. Confirmatory factor analysis supported the hypothesized factor structure indicating, 3 latent self-efficacy factors, specific to PA, healthful eating, and weight-loss. Measurement equivalence/invariance between relevant demographic groups, and over time was also supported. Parallel growth processes in self-efficacy factors and outcomes (PA, fat intake, and weight) support the predictive validity of score interpretations. Overall, this initial series of psychometric analyses supports the interpretation that scores on these scales reflect self-efficacy for PA, healthful eating, and weight-loss. The use of this instrument in large-scale weight-loss trials is encouraged. (PsycINFO Database Record