The relationships between Physical activity and asthma control and Body Mass Index (BMI) in patients with asthma.

OBJECTIVE: Asthma is one of the most common chronic conditions in developed countries. We examined whether physical activity (PA) is related to asthma control and body mass index (BMI) in asthma patients. METHODS: Cross-sectional data collected on PA (ActiGraph GT3X-BT), asthma control (the Asthma Control Questionnaire; ACQ), and BMI were examined in 206 adults (mean[sd] age 47.2[13.8] years; 49.5% had an obese BMI) with clinically diagnosed asthma. Relationships between PA and continuous BMI and asthma control were assessed using linear regression. Differences in PA across obesity (non-obese: <30 Kg/m2/obese: ≥30 Kg/m2) and asthma control categories (controlled: ≤0.75/uncontrolled: >0.75 ACQ score) were also examined. RESULTS: Median (p25, p75) steps counts and peak cadence were 6035 (4248, 8461) steps/day and 123 (115, 133) steps in a minute, respectively. There were nearly 2000 fewer steps/day among those with uncontrolled asthma versus controlled and among those with obese BMI versus nonobese, respectively (both p < 0.05). In regression models adjusted for relevant covariates each 1-unit increase in ACQ score was associated with -686 [95%CI -997, -13] (p ≤ 0.05) average steps/day. The statistical significance of these findings was attenuated (p ≥ 0.05) when BMI was added to the model. However, the point estimate was not reduced (-766 [95%CI -1060, 34]. CONCLUSIONS: Overall step counts were low in this population despite peak cadence values suggesting that most participants could perform moderate intensity activity. Increasing step counts should be considered an important lifestyle intervention goal in obese and non-obese asthma patients with low PA levels.

Perceived and calculated diet quality improvements in a randomized mHealth weight loss trial.

The diet quality of US adults is poor and cross-sectional analyses suggest self-perception of healthful dietary intake may be overestimated. This analysis assessed the concordance between calculated and perceived diet quality and changes in diet quality among adults seeking weight loss and enrolled in a 12-month randomized behavioral trial. Healthy Eating Index-2015 diet quality (HEI) was calculated from self-administered 24-hour recalls. Perceived diet quality (PDQ) was measured on a 100-point scale. Higher scores indicate better diet quality. Concordance was assessed using the concordance correlation coefficient and Bland-Altman plots. The one hundred and five participants with complete dietary data were mostly female and white. There was good agreement between HEI and PDQ scores at 12 months for less than a third of participants. Most of the disagreement arose from PDQ scores being higher than HEI scores. Even fewer participants had good agreement between HEI changes and PDQ changes. Participants perceived greater improvement in diet quality than indicated by HEI score changes. Concordance was low at 12 months and for change in diet quality. Despite the diet quality of adults seeking weight loss being suboptimal and not improving, many perceived their diet quality and diet quality improvements as better than calculated. Future studies might explore the effect of misperceptions on weight loss outcomes.

Effect of an mHealth weight loss intervention on Healthy Eating Index diet quality: the SMARTER randomised controlled trial.

In the few weight loss studies assessing diet quality, improvements have been minimal and recommended calculation methods have not been used. This secondary analysis of a parallel group randomised trial (regsitered: https://clinicaltrials.gov/ct2/show/NCT03367936) assessed whether self-monitoring with feedback (SM + FB) v. self-monitoring alone (SM) improved diet quality. Adults with overweight/obesity (randomised: SM n 251, SM + FB n 251; analysed SM n 170, SM + FB n 186) self-monitored diet, physical activity and weight. Real-time, personalised feedback, delivered via a study-specific app up to three times daily, was based on reported energy, fat and added sugar intake. Healthy Eating Index 2015 (HEI-2015) scores were calculated from 24-hour recalls. Higher scores represent better diet quality. Data were collected August 2018 to March 2021 and analysed spring 2022. The sample was mostly female (78·9 %) and white (85·4 %). At baseline, HEI-2015 total scores and bootstrapped 95 % CI were similar by treatment group (SM + FB: 63·11 (60·41, 65·24); SM: 61·02 (58·72, 62·81)) with similar minimal improvement observed at 6 months (SM + FB: 65·42 (63·30, 67·20); SM: 63·19 (61·22, 64·97)) and 12 months (SM + FB: 63·94 (61·40, 66·29); SM: 63·56 (60·81, 65·42)). Among those who lost ≥ 5 % of baseline weight, HEI-2015 scores improved (baseline: 62·00 (58·94, 64·12); 6 months: 68·02 (65·41, 71·23); 12 months: 65·93 (63·40, 68·61)). There was no effect of the intervention on diet quality change. Clinically meaningful weight loss was related to diet quality improvement. Feedback may need to incorporate more targeted nutritional content.

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.

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.

Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice.

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.

Chronic kidney disease, atherosclerotic plaque characteristics on carotid magnetic resonance imaging, and cardiovascular outcomes.

BACKGROUND: It is unclear whether faster progression of atherosclerosis explains the higher risk of cardiovascular events in CKD. The objectives of this study were to 1. Characterize the associations of CKD with presence and morphology of atherosclerotic plaques on carotid magnetic resonance imaging (MRI) and 2. Examine the associations of baseline CKD and carotid atherosclerotic plaques with subsequent cardiovascular events. METHODS: In a subgroup (N = 465) of Systolic Blood Pressure Intervention Trial. (SPRINT) participants, we measured carotid plaque presence and morphology at baseline and after 30-months with MRI. We examined the associations of CKD (baseline eGFR < 60 ml/min/1.73m2) with progression of carotid plaques and the SPRINT cardiovascular endpoint. RESULTS: One hundred and ninety six (42%) participants had CKD. Baseline eGFR in the non-CKD and CKD subgroups were 77 ± 14 and 49 ± 8 ml/min/1.73 m2, respectively. Lipid rich necrotic-core plaque was present in 137 (29.5%) participants. In 323 participants with both baseline and follow-up MRI measurements of maximum wall thickness, CKD was not associated with progression of maximum wall thickness (OR 0.62, 95% CI 0.36 to 1.07, p = 0.082). In 96 participants with necrotic core plaque at baseline and with a valid follow-up MRI, CKD was associated with lower odds of progression of necrotic core plaque (OR 0.41, 95% CI 0.17 to 0.95, p = 0.039). There were 28 cardiovascular events over 1764 person-years of follow-up. In separate Cox models, necrotic core plaque (HR 2.59, 95% CI 1.15 to 5.85) but not plaque defined by maximum wall thickness or presence of a plaque component (HR 1.79, 95% CI 0.73 to 4.43) was associated with cardiovascular events. Independent of necrotic core plaque, CKD (HR 3.35, 95% CI 1.40 to 7.99) was associated with cardiovascular events. CONCLUSIONS: Presence of necrotic core in carotid plaque rather than the presence of plaque per se was associated with increased risk of cardiovascular events. We did not find CKD to be associated with faster progression of necrotic core plaques, although both were independently associated with cardiovascular events. Thus, CKD may contribute to cardiovascular disease principally via mechanisms other than atherosclerosis such as arterial media calcification or stiffening. TRIAL REGISTRATION: NCT01475747 , registered on November 21, 2011.

Patient Recruitment Into a Multicenter Clinical Cohort Linking Electronic Health Records From 5 Health Systems: Cross-sectional Analysis.

BACKGROUND: There is growing interest in identifying and recruiting research participants from health systems using electronic health records (EHRs). However, few studies have described the practical aspects of the recruitment process or compared electronic recruitment methods to in-person recruitment, particularly across health systems. OBJECTIVE: The objective of this study was to describe the steps and efficiency of the recruitment process and participant characteristics by recruitment strategy. METHODS: EHR-based eligibility criteria included being an adult patient engaged in outpatient primary or bariatric surgery care at one of 5 health systems in the PaTH Clinical Research Network and having ≥2 weight measurements and 1 height measurement recorded in their EHR within the last 5 years. Recruitment strategies varied by site and included one or more of the following methods: (1) in-person recruitment by study staff from clinical sites, (2) US postal mail recruitment letters, (3) secure email, and (4) direct EHR recruitment through secure patient web portals. We used descriptive statistics to evaluate participant characteristics and proportion of patients recruited (ie, efficiency) by modality. RESULTS: The total number of eligible patients from the 5 health systems was 5,051,187. Of these, 40,048 (0.8%) were invited to enter an EHR-based cohort study and 1085 were enrolled. Recruitment efficiency was highest for in-person recruitment (33.5%), followed by electronic messaging (2.9%), including email (2.9%) and EHR patient portal messages (2.9%). Overall, 779 (65.7%) patients were enrolled through electronic messaging, which also showed greater rates of recruitment of Black patients compared with the other strategies. CONCLUSIONS: We recruited a total of 1085 patients from primary care and bariatric surgery settings using 4 recruitment strategies. The recruitment efficiency was 2.9% for email and EHR patient portals, with the majority of participants recruited electronically. This study can inform the design of future research studies using EHR-based recruitment.

Cost-Effectiveness of Intensive versus Standard Blood-Pressure Control.

BACKGROUND: In the Systolic Blood Pressure Intervention Trial (SPRINT), adults at high risk for cardiovascular disease who received intensive systolic blood-pressure control (target, <120 mm Hg) had significantly lower rates of death and cardiovascular disease events than did those who received standard control (target, <140 mm Hg). On the basis of these data, we wanted to determine the lifetime health benefits and health care costs associated with intensive control versus standard control. METHODS: We used a microsimulation model to apply SPRINT treatment effects and health care costs from national sources to a hypothetical cohort of SPRINT-eligible adults. The model projected lifetime costs of treatment and monitoring in patients with hypertension, cardiovascular disease events and subsequent treatment costs, treatment-related risks of serious adverse events and subsequent costs, and quality-adjusted life-years (QALYs) for intensive control versus standard control of systolic blood pressure. RESULTS: We determined that the mean number of QALYs would be 0.27 higher among patients who received intensive control than among those who received standard control and would cost approximately $47,000 more per QALY gained if there were a reduction in adherence and treatment effects after 5 years; the cost would be approximately $28,000 more per QALY gained if the treatment effects persisted for the remaining lifetime of the patient. Most simulation results indicated that intensive treatment would be cost-effective (51 to 79% below the willingness-to-pay threshold of $50,000 per QALY and 76 to 93% below the threshold of $100,000 per QALY), regardless of whether treatment effects were reduced after 5 years or persisted for the remaining lifetime. CONCLUSIONS: In this simulation study, intensive systolic blood-pressure control prevented cardiovascular disease events and prolonged life and did so at levels below common willingness-to-pay thresholds per QALY, regardless of whether benefits were reduced after 5 years or persisted for the patient's remaining lifetime. (Funded by the National Heart, Lung, and Blood Institute and others; SPRINT ClinicalTrials.gov number, NCT01206062 .).

Effect of Intensive Blood-Pressure Treatment on Patient-Reported Outcomes.

BACKGROUND: The previously published results of the Systolic Blood Pressure Intervention Trial showed that among participants with hypertension and an increased cardiovascular risk, but without diabetes, the rates of cardiovascular events were lower among those who were assigned to a target systolic blood pressure of less than 120 mm Hg (intensive treatment) than among those who were assigned to a target of less than 140 mm Hg (standard treatment). Whether such intensive treatment affected patient-reported outcomes was uncertain; those results from the trial are reported here. METHODS: We randomly assigned 9361 participants with hypertension to a systolic blood-pressure target of less than 120 mm Hg or a target of less than 140 mm Hg. Patient-reported outcome measures included the scores on the Physical Component Summary (PCS) and Mental Component Summary (MCS) of the Veterans RAND 12-Item Health Survey, the Patient Health Questionnaire 9-item depression scale (PHQ-9), patient-reported satisfaction with their blood-pressure care and blood-pressure medications, and adherence to blood-pressure medications. We compared the scores in the intensive-treatment group with those in the standard-treatment group among all participants and among participants stratified according to physical and cognitive function. RESULTS: Participants who received intensive treatment received an average of one additional antihypertensive medication, and the systolic blood pressure was 14.8 mm Hg (95% confidence interval, 14.3 to 15.4) lower in the group that received intensive treatment than in the group that received standard treatment. Mean PCS, MCS, and PHQ-9 scores were relatively stable over a median of 3 years of follow-up, with no significant differences between the two treatment groups. No significant differences between the treatment groups were noted when participants were stratified according to baseline measures of physical or cognitive function. Satisfaction with blood-pressure care was high in both treatment groups, and we found no significant difference in adherence to blood-pressure medications. CONCLUSIONS: Patient-reported outcomes among participants who received intensive treatment, which targeted a systolic blood pressure of less than 120 mm Hg, were similar to those among participants who received standard treatment, including among participants with decreased physical or cognitive function. (Funded by the National Institutes of Health; SPRINT ClinicalTrials.gov number, NCT01206062 .).

Lifestyle Habits Associated with Weight Regain After Intentional Loss in Primary Care Patients Participating in a Randomized Trial.

BACKGROUND: Though long-term weight loss maintenance is the treatment goal for obesity, weight regain is typical and few studies have evaluated lifestyle habits associated with weight regain. OBJECTIVE: To identify dietary and physical activity habits associated with 6- and 24-month weight regain among participants in a weight loss maintenance clinical trial. DESIGN: Secondary analysis of randomized clinical trial data. PARTICIPANTS: Adult primary care patients with recent, intentional weight loss of at least 5%. MAIN MEASURES: Lifestyle habits included consumption of low-fat foods, fish, desserts, sugary beverages, fruits, and vegetables and eating at restaurants from the Connor Diet Habit Survey; moderate-vigorous physical activity by self-report; steps recorded by a pedometer; and sedentary behavior by self-report. The outcome variable was weight change at 6 and 24 months. Linear regression models estimated adjusted associations between changes in weight and changes in dietary and physical activity habits. KEY RESULTS: Overall, participants (mean (SD): 53.4 (12.2) years old; 26% male; 88% white) maintained weight loss at 6 months (n = 178, mean (SD): - 0.02 (5.70)% change) but began to regain weight by 24 months (n = 157, mean (SD): 4.22 (9.15)% increase). When considered all together, more eating at restaurants, reduced fish consumption, and less physical activity were most consistently associated with weight regain in fully adjusted models at both 6 and 24 months of follow-up. In addition, more sedentary behavior was associated with weight regain at 6 months while reduced consumption of low-fat foods, and more desserts and sugary beverages were associated with weight regain at 24 months. CONCLUSIONS: Consuming less fish, fewer steps per day, and more frequent restaurant eating were most consistently associated with weight regain in primary care patients. Primary care providers may consider addressing specific lifestyle behaviors when counseling patients after successful weight loss. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01946191.

Effect of Electronic Health Record-Based Coaching on Weight Maintenance: A Randomized Trial.

Background: Weight regain after intentional loss is common. Most evidence-based weight management programs focus on short-term loss rather than long-term maintenance. Objective: To evaluate the benefit of coaching in an electronic health record (EHR)-based weight maintenance intervention. Design: Randomized controlled trial. (ClinicalTrials.gov: NCT01946191). Setting: Practices affiliated with an academic medical center. Participants: Adult outpatients with body mass index (BMI) of 25 kg/m2 or higher, intentional weight loss of at least 5% in the previous 2 years, and no bariatric procedures in the previous 5 years. Intervention: Participants were randomly assigned to EHR tools (tracking group) versus EHR tools plus coaching (coaching group). The EHR tools included weight, diet, and physical activity tracking flow sheets; standardized surveys; and reminders. The coaching group received 24 months of personalized coaching through the EHR patient portal, with 24 scheduled contacts. Measurements: The primary outcome was weight change at 24 months. Secondary outcomes included 5% weight loss maintenance and changes in BMI, waist circumference, number of steps per day, health-related quality of life, physical function, blood pressure, and satisfaction. Results: Among 194 randomly assigned participants (mean age, 53.4 years [SD, 12.2]; 143 [74%] women; 171 [88%] white), 157 (81%) completed the trial. Mean baseline weight and BMI were 85.8 kg (SD, 19.1) and 30.4 kg/m2 (SD, 5.9). At 24 months, mean weight regain (± SE) was 2.1 ± 0.62 kg and 4.9 ± 0.63 kg in the coaching and tracking groups, respectively. The between-group difference in weight change at 24 months was significant (-2.86 kg [95% CI, -4.60 to -1.11 kg]) in the linear mixed model. At 24 months, 65% of participants in the coaching group and 50% in the tracking group maintained weight loss of at least 5%. Limitation: Single-site trial, which limits generalizability. Conclusion: Among adults with intentional weight loss of at least 5%, use of EHR tools plus coaching resulted in less weight regain than EHR tools alone. Primary Funding Source: Agency for Healthcare Research and Quality and National Institutes of Health.

Perceptions and experiences of appetite awareness training among African-American women who binge eat.

INTRODUCTION: Binge eating may contribute to the prevalence of obesity in African-American women. Yet, there has been scant intervention research on the treatment of binge eating in this population. We tested the feasibility of an appetite awareness training (AAT) intervention in a sample of African-American women with binge and overeating behaviors. Participants who completed AAT were recruited to participate in focus groups to elicit information about their perceptions and experiences with this intervention to inform the design of future interventions to treat binge eating and obesity in African-American women. METHODS: African-American women, aged 18-70 years, who had completed an 8-week randomized AAT intervention, were invited to attend a focus group discussion. Session content was recorded and transcribed. Data were analyzed by use of open coding. Themes were identified that described their perceptions and experiences of participating in the intervention. RESULTS: Seventeen women participated in three focus group discussions. Pertinent themes identified included: paying attention to internal cues of hunger and satiety, influence of culture on eating patterns, breaking patterns of disordered eating, and perceptions about weight. Overall, participants were satisfied with their experience of AAT, and reported they found it valuable to learn about listening to biological signals of hunger and satiety and to learn specific strategies to reduce maladaptive eating patterns. CONCLUSION: AAT was acceptable and provided helpful eating behavior instruction to African-American women with reported binge and overeating behaviors. Future research should examine the potential of AAT to improve weight management in this underserved population. LEVEL OF EVIDENCE: Level V, qualitative descriptive study.

Understanding Primary Care Patients' Self-weighing Habits: Cohort Analysis from the PaTH Clinical Data Research Network.

BACKGROUND: Greater than 60% of adults have overweight or obesity. Self-weighing is an effective weight loss and weight maintenance tool. However, little is known about self-weighing habits among the primary care patient population. Our objective was to examine the frequency of patient-reported self-weighing, and to evaluate the associations of self-weighing with demographic characteristics and self-monitoring behaviors. METHODS: We conducted an analysis of survey data collected as part of the PaTH Clinical Data Research Network, which recruited a cohort of 1,021 primary care patients at 4 academic medical centers. Patients of all body mass index (BMI) categories were included. RESULTS: Response rate of 6-month survey was 727 (71%). The mean age was 56 years, and most were female (68%), White (78%), college graduates (66%), and employed/retired (85%). The mean BMI was 30.2 kg/m2, 80% of participants had a BMI â‰§ 25 kg/m2. Of patients with BMI â‰§ 25 kg/m2, 35% of participants self-weighed weekly and 23% daily. Participants who reported self-weighing at least weekly were more likely to be older (59 vs 54 years, p < 0.01), married (p = 0.01), college graduates (p = 0.03), White (p < 0.01), and employed vs disabled/unemployed (p < 0.01). Patients who self-weighed daily had a lower BMI (29 kg/m2 vs 31 kg/m2, p = 0.04). Patients who tracked exercise or food intake were more likely to self-weigh daily (p < 0.01), as were patients wanting to lose or maintain weight (p < 0.01). CONCLUSIONS: Despite its potential for primary and secondary obesity prevention, only 35% of primary care patients with overweight or obesity engage in self-weighing weekly and less than a quarter (23%) self-weigh daily. Socioeconomic status appears to be a factor influencing regular self-weighing in this population, potentially contributing to greater health disparities in obesity rates. Patients who self-weighed daily had a lower BMI, suggesting that it may play a role in primary prevention of obesity. More work is needed to explore self-weighing among patients.

Online Lifestyle Modification Intervention: Survey of Primary Care Providers' Attitudes and Views.

BACKGROUND: Online tools are a convenient and effective method of delivering lifestyle interventions to obese adult primary care patients. A referral model allows physicians to efficiently direct their patients to the intervention during a primary care visit. However, little is known of physicians' perspectives and utilization of the referral model for an online lifestyle modification intervention. OBJECTIVE: The aim was to evaluate the response of primary care providers (PCPs) to a referral model for implementing a year-long online intervention for weight loss to obese adult patients. METHODS: The PCPs at six primary care clinics were asked to refer adult obese patients to a year-long online lifestyle intervention providing self-management support for weight loss. Following the 1-year intervention, all providers at the participating practices were surveyed regarding their views of the program. Respondents completed survey items assessing their attitudes regarding the 1-year intensive weight loss intervention and identifying resources they would find helpful for assisting patients with weight loss. Referring physicians were asked about their level of satisfaction with implementing the counseling services using standard electronic health record referral processes. Attitudes toward obesity counseling among referring and nonreferring providers were compared. Impressions of how smoothly the referral model of obesity treatment integrated with the clinical workflow were also quantified. RESULTS: Of the 67 providers who completed the surveys, nonreferring providers (n=17) were more likely to prefer counseling themselves (P=.04) and to report having sufficient time to do so (P=.03) than referring providers (n=50) were. Nonreferring providers were more likely to report that their patients lacked computer skills (76%, 13/17 vs 34%, 17/50) or had less access to the Internet (65%, 11/17 vs 32%, 16/50). CONCLUSIONS: Understanding providers' views and barriers regarding the integration of online tools will facilitate widespread implementation of an online lifestyle modification intervention.

Sleep Duration and Quality: Impact on Lifestyle Behaviors and Cardiometabolic Health: A Scientific Statement From the American Heart Association.

Sleep is increasingly recognized as an important lifestyle contributor to health. However, this has not always been the case, and an increasing number of Americans choose to curtail sleep in favor of other social, leisure, or work-related activities. This has resulted in a decline in average sleep duration over time. Sleep duration, mostly short sleep, and sleep disorders have emerged as being related to adverse cardiometabolic risk, including obesity, hypertension, type 2 diabetes mellitus, and cardiovascular disease. Here, we review the evidence relating sleep duration and sleep disorders to cardiometabolic risk and call for health organizations to include evidence-based sleep recommendations in their guidelines for optimal health.

Community-Based Healthy Aging Interventions for Older Adults with Arthritis and Multimorbidity.

Examine the impact of programs led by community health workers on health and function in older adults with arthritis and other health conditions. We conducted a cluster-randomized trial of the Arthritis Foundation Exercise Program (AFEP) enhanced with the "10 Keys"™ to Healthy Aging compared with the AFEP program at 54 sites in 462 participants (mean age 73 years, 88 % women, 80 % white). Trained Community health workers delivered the 10-week programs. Outcomes assessed after 6 months included physical performance [Short Physical Performance Battery (SPPB)], Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index, and preventive health behaviors. Both groups experienced improvements. Performance improved by 0.3 SPPB points in the AFEP/"10 Keys"™ group and 0.5 in AFEP alone; WOMAC scores declined by 3.0 and 3.9 points respectively. More participants had controlled hypertension at 6 months in both groups (60.1 % baseline to 76.7 % in AFEP/10 Keys and from 76.5 to 84.9 % in AFEP alone) and greater diabetes control (from 15.0 to 34.9 and 15.5 to 34.1 %, respectively). These community-based programs showed similar improvements in preventive health, mobility and arthritis outcomes.

Knowledge, barriers and facilitators of exercise in dialysis patients: a qualitative study of patients, staff and nephrologists.

BACKGROUND: Despite growing evidence on benefits of increased physical activity in hemodialysis (HD) patients and safety of intra-dialytic exercise, it is not part of standard clinical care, resulting in a missed opportunity to improve clinical outcomes in these patients. To develop a successful exercise program for HD patients, it is critical to understand patients', staff and nephrologists' knowledge, barriers, motivators and preferences for patient exercise. METHODS: In-depth interviews were conducted with a purposive sample of HD patients, staff and nephrologists from 4 dialysis units. The data collection, analysis and interpretation followed Criteria for Reporting Qualitative Research guidelines. Using grounded theory, emergent themes were identified, discussed and organized into major themes and subthemes. RESULTS: We interviewed 16 in-center HD patients (mean age 60 years, 50% females, 63% blacks), 14 dialysis staff members (6 nurses, 3 technicians, 2 dietitians, 1 social worker, 2 unit administrators) and 6 nephrologists (50% females, 50% in private practice). Although majority of the participants viewed exercise as beneficial for overall health, most patients failed to recognize potential mental health benefits. Most commonly reported barriers to exercise were dialysis-related fatigue, comorbid health conditions and lack of motivation. Specifically for intra-dialytic exercise, participants expressed concern over safety and type of exercise, impact on staff workload and resistance to changing dialysis routine. One of the most important motivators identified was support from friends, family and health care providers. Specific recommendations for an intra-dialytic exercise program included building a culture of exercise in the dialysis unit, and providing an individualized engaging program that incorporates education and incentives for exercising. CONCLUSION: Patients, staff and nephrologists perceive a number of barriers to exercise, some of which may be modifiable. Participants desired an individualized intra-dialytic exercise program which incorporates education and motivation, and they provided a number of recommendations that should be considered when implementing such a program.

Effectiveness of a physical activity and weight loss intervention for middle-aged women: healthy bodies, healthy hearts randomized trial.

BACKGROUND: Physical inactivity is a significant risk factor for cardiovascular disease and remains highly prevalent in middle-aged women. OBJECTIVE: We hypothesized that an interventionist-led (IL), primary-care-based physical activity (PA) and weight loss intervention would increase PA levels and decrease weight to a greater degree than a self-guided (SG) program. DESIGN: We conducted a randomized trial. PARTICIPANTS: Ninety-nine inactive women aged 45-65 years and with BMI ≥ 25 kg/m(2) were recruited from three primary care clinics. INTERVENTIONS: The interventionist-led (IL) group (n = 49) had 12 weekly sessions of 30 min discussions with 30 min of moderate-intensity PA. The self-guided (SG) group (n = 50) received a manual for independent use. MAIN MEASURES: Assessments were conducted at 0, 3, and 12 months; PA and weight were primary outcomes. Weight was measured with a standardized protocol. Leisure PA levels were assessed using the Modifiable Activity Questionnaire. Differences in changes by group were analyzed with a t-test or Wilcoxon rank-sum test. Mixed models were used to analyze differences in changes of outcomes by group, using an intention-to-treat principle. KEY RESULTS: Data from 98 women were available for analysis. At baseline, mean (SD) age was 53.9 (5.4) years and 37 % were black. Mean weight was 92.3 (17.7) kg and mean BMI was 34.7 (5.9) kg/m(2). Median PA level was 2.8 metabolic equivalent hours per week (MET-hour/week) (IQR 0.0, 12.0). At 3 months, IL women had a significantly greater increase in PA levels (7.5 vs. 1.9 MET-hour/week; p = 0.02) than SG women; there was no significant difference in weight change. At 12 months, the difference between groups was no longer significant (4.7 vs. 0.7 MET-hour/week; p = 0.38). Mixed model analysis showed a significant (p = 0.048) difference in PA change between groups at 3 months only. CONCLUSIONS: The IL intervention was successful in increasing the physical activity levels of obese, inactive middle-aged women in the short-term. No significant changes in weight were observed.

The use of mHealth to deliver tailored messages reduces reported energy and fat intake.

BACKGROUND: Evidence supports the role of feedback in reinforcing motivation for behavior change. Feedback that provides reinforcement has the potential to increase dietary self-monitoring and enhance attainment of recommended dietary intake. OBJECTIVE: The aim of this study was to examine the impact of daily feedback (DFB) messages, delivered remotely, on changes in dietary intake. METHODS: This was a secondary analysis of the Self- Monitoring And Recording using Technology (SMART) Trial, a single-center, 24-month randomized clinical trial of behavioral treatment for weight loss. Participants included 210 obese adults (mean body mass index, 34.0 kg/m²) who were randomized to either a paper diary (PD), personal digital assistant (PDA), or PDA plus daily tailored feedback messages (PDA + FB). To determine the role of daily tailored feedback in dietary intake, we compared the self-monitoring with DFB group (DFB group; n = 70) with the self-monitoring without DFB group (no-DFB group, n = 140). All participants received a standard behavioral intervention for weight loss. Self-reported changes in dietary intake were compared between the DFB and no-DFB groups and were measured at baseline and at 6, 12, 18, and 24 months. Linear mixed modeling was used to examine percentage changes in dietary intake from baseline. RESULTS: Compared with the no-DFB group, the DFB group achieved a larger reduction in energy (-22.8% vs -14.0%; P = .02) and saturated fat (-11.3% vs -0.5%; P = .03) intake and a trend toward a greater decrease in total fat intake (-10.4% vs -4.7%; P = .09). There were significant improvements over time in carbohydrate intake and total fat intake for both groups (P values < .05). CONCLUSION: Daily tailored feedback messages designed to target energy and fat intake and delivered remotely in real time using mobile devices may play an important role in the reduction of energy and fat intake.