Design and implementation of electronic health record-based tools to support a weight management program in primary care

Objectives

This paper reports on a mixed methods formative evaluation to support the design and implementation of information technology (IT) tools for a primary care weight management intervention delivered through the patient portal using primary care staff as coaches.

Methods

We performed a qualitative needs assessment, designed the IT tools to support the weight management program, and developed implementation tracking metrics. Implementation tracking metrics were designed to use real world electronic health record (EHR) data.

Results

The needs assessment revealed IT requirements as well as barriers and facilitators to implementation of EHR-based weight management interventions in primary care. We developed implementation metrics for the IT tools. These metrics were used in weekly project team calls to make sure that project resources were allocated to areas of need.

Conclusion

This study identifies the important role of IT in supporting weight management through patient identification, weight and activity tracking in the patient portal, and the use of the EHR as a population management tool. An intensive multi-level implementation approach is required for successful primary care-based weight management interventions including well-designed IT tools, comprehensive involvement of clinic leadership, and implementation tracking metrics to guide the process of workflow integration. This study helps to bridge the gap between informatics and implementation by using socio-technical formative evaluation methods early in order to support the implementation of IT tools.

Trial registration

clinicaltrials.gov, NCT04420936. Registered June 9, 2020.

Implementing weight maintenance with existing staff and electronic health record tools in a primary care setting: Baseline results from the MAINTAIN PRIME trial

BACKGROUND

There is need for interventions that can assist with long-term maintenance of healthy body weight and be sustainably integrated into existing primary care teams. The goal of MAINTAIN PRIME (Promoting Real (World) IMplEmentation) is to evaluate whether a successful electronic health record (EHR)-based weight maintenance intervention can be adapted to a new clinical setting with primary care staff serving as coaches.

METHODS

EHR tools include tracking tools, standardized surveys, and standardized "SmartPhrases" for coaching. Inclusion criteria were age 18-75 years, voluntary 5% weight loss in the past 2 years with prior BMI ≥ 25 kg/m2, and no bariatric procedures in past 2 years. Participants were randomized 1:1 to tailored online coaching with EHR tracking tools (coaching) or EHR tracking tools alone (tracking).

RESULTS

We screened 405 individuals between September 2021 and April 2023; 269 participants enrolled (134 coaching; 135 tracking). The most common reason for not enrolling was ineligibility (55%). At baseline, participants were 50.3 (SD 15.02) years old, 66.4% female, and 84% White; 83.7% reported moderate physical activity. Average weight and BMI at baseline were 205.0 (SD 48.9) lbs. and 33.2 (6.8) kg/m2, respectively. Participants lost an average of 10.7% (SD 5.2) of their body weight before enrolling. We recruited 39 primary care coaches over the same period. Conclusion The study successfully identified and recruited primary care patients with recent intentional weight loss for participation in a weight maintenance program that uses EHR-based tools. We also successfully recruited and trained primary care staff as coaches.

Screening for social determinants of health among populations at risk for MASLD: a scoping review

Background

Social determinants of health (SDoH) have been associated with disparate outcomes among those with metabolic dysfunction-associated steatotic liver disease (MASLD) and its risk factors. To address SDoH among this population, real-time SDoH screening in clinical settings is required, yet optimal screening methods are unclear. We performed a scoping review to describe the current literature on SDoH screening conducted in the clinical setting among individuals with MASLD and MASLD risk factors.

Methods

Through a systematic literature search of MEDLINE, Embase, and CINAHL Complete databases through 7/2023, we identified studies with clinic-based SDoH screening among individuals with or at risk for MASLD that reported pertinent clinical outcomes including change in MASLD risk factors like diabetes and hypertension.

Results

Ten studies (8 manuscripts, 2 abstracts) met inclusion criteria involving 148,151 patients: 89,408 with diabetes and 25,539 with hypertension. Screening was primarily completed in primary care clinics, and a variety of screening tools were used. The most commonly collected SDoH were financial stability, healthcare access, food insecurity and transportation. Associations between clinical outcomes and SDoH varied; overall, higher SDoH burden was associated with poorer outcomes including elevated blood pressure and hemoglobin A1c.

Conclusion

Despite numerous epidemiologic studies showing associations between clinical outcomes and SDoH, and guidelines recommending SDoH screening, few studies describe in-clinic SDoH screening among individuals with MASLD risk factors and none among patients with MASLD. Future research should prioritize real-time, comprehensive assessments of SDoH, particularly among patients at risk for and with MASLD, to mitigate disease progression and reduce MASLD health disparities.

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.

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.

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.

Aspects of Program Engagement in an Online Physical Activity Intervention and Baseline Predictors of Engagement

PURPOSE

Participant engagement in an online physical activity (PA) intervention is described and baseline factors related to engagement are identified.

DESIGN

Longitudinal Study Within Randomized Controlled Trial.

SETTING

Online/Internet.

SAMPLE

Primary care patients (21-70 years).

INTERVENTION

ActiveGOALS was a 3-month, self-directed online PA intervention (15 total lessons, remote coaching support, and a body-worn step-counter).

MEASURES

Engagement was measured across six outcomes related to lesson completion (total number and time to complete), coach contact, and behavior tracking (PA, sedentary). Self-reported baseline factors were examined from seven domains (confidence, environment, health, health care, demographic, lifestyle, and quality of life).

ANALYSIS

General linear and nonlinear mixed models were used to examine relationships between baseline factors and engagement outcomes within and across all domains.

RESULTS

Seventy-nine participants were included in the sample (77.2% female; 74.7% white non-Hispanic). Program engagement was high (58.2% completed all lessons; PA was tracked ≥3 times/week for 11.3 ± 4.0 weeks on average). Average time between completed lessons (days) was longer than expected and participants only contacted their coach about 1 of every 3 weeks. Individual predictors related to health, health care, demographics, lifestyle, and quality of life were significantly related to engagement.

CONCLUSION

Examining multiple aspects of engagement and a large number of potential predictors of engagement is likely needed to determine facilitators and barriers for high engagement in multi-faceted online intervention programs.

Sleep Technology Intervention to Target Cardiometabolic Health (STITCH): a randomized controlled study of a behavioral sleep extension intervention compared to an education control to improve sleep duration, blood pressure, and cardiometabolic health among adults with elevated blood pressure/hypertension

BACKGROUND

Short sleep duration, defined as < 7 h sleep on weeknights, affects 40% of the US adult population, contributing to the increased risk for cardiometabolic diseases, decreased safety, and poorer mental health. Despite the prevalence of short sleep duration, few studies have tested interventions to extend sleep duration. The objective of this study is to test the effects of a behavioral sleep extension intervention on sleep duration, blood pressure, and other measures of cardiometabolic health among adults with elevated blood pressure or hypertension.

METHODS

This is a single-blind, randomized controlled trial to determine the impact of a behavioral sleep extension intervention on sleep duration and cardiometabolic health among individuals with short sleep duration (< 7 h per night) and elevated blood pressure or hypertension (SBP 120-150 mmHg or DBP 80-90 mmHg). After completing the screening, participants will be randomly assigned to either a sleep coaching (intervention) or health education (control) group. The participants will have weekly contact for either coaching or education for 8 weeks (intervention period) followed by monthly coaching or education for the next 2 months (maintenance period). Participants will complete assessment visits, actigraphy, and 24-h ambulatory blood pressure recording at baseline/screening, 8 weeks, and 6 and 12 months. The primary outcome is sleep duration at 8 weeks, and the secondary outcome is blood pressure at 8 weeks.

DISCUSSION

The results of this study will determine the effects of behavioral sleep extension on sleep and cardiometabolic health among adults with short sleep duration and elevated BP/hypertension. The results will inform the feasibility and efficacy of behavioral sleep extension and provide information needed for future multi-site effectiveness studies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04766424. Registered on 21 February 2021.

Influence of Recent Standing, Moving, or Sitting on Daytime Ambulatory Blood Pressure

Background There are no recommendations for being seated versus nonseated during ambulatory blood pressure (BP) monitoring (ABPM). The authors examined how recent standing or moving versus sitting affect average daytime BP on ABPM. Methods and Results This analysis used baseline assessments from a clinical trial in desk workers with office systolic BP (SBP) 120 to 159 mm Hg or diastolic BP (DBP) 80 to 99 mm Hg. ABPM was measured every 30 minutes with a SunTech Medical Oscar 2 monitor. Concurrent posture (standing or seated) and moving (steps) were measured via a thigh-worn accelerometer. Linear regression determined within-person BP variability explained (R2) by standing and steps before ABPM readings. Mean daytime BP and the prevalence of mean daytime BP >135/85 mm Hg from readings after sitting (seated) or after recent standing or moving (nonseated) were compared with all readings. Participants (n=266, 59% women; age, 45.2±11.6 years) provided 32.5±3.9 daytime BP readings. Time standing and steps before readings explained variability up to 17% for daytime SBP and 14% for daytime DBP. Using the 5-minute prior interval, seated SBP/DBP was lower (130.8/79.7 mm Hg, P<0.001) and nonseated SBP/DBP was higher (137.8/84.3 mm Hg, P<0.001) than mean daytime SBP/DBP from all readings (133.9/81.6 mm Hg). The prevalence of mean daytime SBP/DBP ≥135/85 mm Hg also differed: 38.7% from seated readings, 70.3% from nonseated readings, and 52.6% from all readings (P<0.05). Conclusions Daytime BP was systematically higher after standing and moving compared with being seated. Individual variation in activity patterns could influence the diagnosis of high BP using daytime BP readings on ABPM.

Single-Pill Combination Product Availability of the Antihypertensive Regimens Used for Intensive Systolic Blood Pressure Treatment in the Systolic Blood Pressure Intervention Trial

BACKGROUND

Single-pill combination (SPC) antihypertensive products improve blood pressure control and medication adherence among patients with hypertension. It is unknown to what degree commercially available SPC products could be used to target an intensive systolic blood pressure goal of <120 mm Hg.

METHODS

This cross-sectional analysis included participants randomized to the intensive treatment arm (goal systolic blood pressure <120 mm Hg) of the Systolic Blood Pressure Intervention Trial (SPRINT) using ≥2 antihypertensive medication classes at the 12-month postrandomization visit. Antihypertensive medication data were collected using pill bottle review by research coordinators, and regimens were categorized by the unique combinations of antihypertensive classes. We calculated the proportion of regimens used, which are commercially available as one of the 7 SPC class combinations in the United States as of January 2023.

RESULTS

Among the 3833 SPRINT intensive arm participants included (median age, 67.0 years; 35.5% female), participants were using 219 unique antihypertensive regimens. The 7 regimens for which there are class-equivalent SPC products were used by 40.3% of participants. Only 3.2% of all medication class regimens used are available as a class-equivalent SPC product (7/219). There are no SPC products available with 4 or more medication classes, which were used by 1060 participants (27.7%).

CONCLUSIONS

Most SPRINT participants in the intensive arm used an antihypertensive medication regimen, which is not commercially available as a class equivalent SPC product. To achieve the SPRINT results in real-world settings, maximize the potential benefit of SPCs, and reduce pill burden, improvements in the product landscape are needed.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov/ct2/show/NCT01206062; Unique identifier: NCT01206062.

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.

Antihypertensive Medication Regimens Used by US Adults With Hypertension and the Potential for Fixed-Dose Combination Products: The National Health and Nutrition Examination Surveys 2015 to 2020

Background Fixed-dose combination (FDC) antihypertensive products improve blood pressure control and adherence among patients with hypertension. It is unknown to what degree commercially available FDC products meet the current hypertension management prescription patterns in the United States. Methods and Results This cross-sectional analysis of the National Health and Nutrition Examination Surveys 2015 to March 2020 included participants with hypertension taking ≥2 antihypertensive medications (N=2451). After constructing each participant's regimen according to antihypertensive classes used, we estimated the extent to which the 7 class-level FDC regimens available in the United States as of January 2023 would match the regimens used. Among a weighted population of 34.1 million US adults (mean age, 66.0 years; 52.8% women; 69.1% non-Hispanic White race and ethnicity), the proportions using 2, 3, 4, and ≥5 antihypertensive classes were 60.6%, 28.2%, 9.1%, and 1.6%, respectively. The 7 FDC regimens were among 189 total regimens used (3.7%), and 39.2% of the population used one of the FDC regimens (95% CI, 35.5%-43.0%; 13.4 million US adults); 60.8% of the population (95% CI, 57.0%-64.5%; 20.7 million US adults) were using a regimen not available as a class-equivalent FDC product. Conclusions Three in 5 US adults with hypertension taking ≥2 antihypertensive classes are using a regimen that is not commercially available as a class-equivalent FDC product as of January 2023. To maximize the potential benefit of FDCs to improve medication adherence (and thus blood pressure control) among patients taking multiple antihypertensive medications, use of FDC-compatible regimens and improvements in the product landscape are needed.

Abstract P399: The Effect of Self-Monitoring of Diet, Weight and Steps and Adherence to Diet, Fat and Physical Activity Goals on Weight Loss at 12 Months: Smarter RCT

Introduction: Self-monitoring (SM) is the core of behavioral weight loss. Efficacy evidence for mHealth to improve SM adherence and impact weight loss outcomes is limited.

Purpose: Examine associations among diet, weight, and physical activity (PA) SM and adherence to diet, fat and PA goals on weight loss at 12 mos in adults with overweight or obesity.

Methods: SMARTER was a single-site, 2-arm weight loss trial. We randomized adults with (BMI) 27-43 kg/m 2 to diet, weight, and PA SM plus tailored feedback messages (SM+FB, n=251) or SM alone (n=251). The SM+FB group received feedback messages via the SMARTER app on diet daily, PA every other day and weight weekly. The study provided Fitbit Charge 2™ for PA, smart scales for weight and Fitbit app for diet. Participants received individualized daily calorie/fat goals (based on sex & weight) and incremental weekly PA goals to reach ≥300 min/wk of moderate- and vigorous-intensity PA. Staff measured weight at baseline, 6 and 12 mos. Diet SM was the % of days with ≥50% of calorie goal recorded. Weight SM was the % of days with weight recorded. PA SM was % of days with ≥500 steps. Calorie goal adherence was % of days with ≥85% and <115% of calorie goals and fat goals as ≤25% of calorie goals. PA goal adherence was the average % of weekly MVPA meeting the PA goal for ≥4 days/wk. Weight loss at 12 mos was computed as the % of change in weight from baseline to 12 mos relative to baseline weight. We compared diet, weight and PA SM and adherence to calorie, fat and PA goals by treatment assignment using Wilcoxon rank-sum tests. The effect of diet, weight and PA SM and adherence to calorie, fat and PA goals on weight loss at 12 mos was examined using separate linear regression models considering treatment assignment and interaction effects.

Results: The sample (N=502) was 82% white (n=414), 79% female (n=399), on average 45.0±14.4 years of age with a mean BMI of 33.7±4.0 kg/m 2 . Treatment arms were similar on % days of weight and PA SM and % days adherent to calorie, fat and PA goals (p≥.05); however, the SM+FB group had greater % days of SM diet than the SM group (58.9 [24.7, 84.9] vs. 41.1 [14.0, 81.9]; P=.01). Weight loss at 12 mos was significantly associated (reported as b [95% CI]) with higher % of days of SM diet (-0.10 [-0.13, -0.08]), weight (-0.12 [-0.14, -0.09]) and PA (-0.10 [-0.13, -0.07]) and % days adherent to calorie (-0.06 [-0.11, -0.01]) and fat goals (-0.11 [-0.20, -0.02]) and average % days adherent to PA goals (-0.04 [-0.06, -0.02]). The effect of treatment assignment and its interactions with SM of diet, weight and PA and adherence to calorie, fat and PA goals on weight loss at 12 mos were not significant.

Conclusions: In this study, SM of lifestyle behaviors and adherence to diet and PA goals were associated with better weight loss at 12 months and did not depend on treatment group assignment, suggesting that the mHealth intervention did not enhance adherence sufficiently to affect weight loss outcomes.

Lifestyle strategies after intentional weight loss: results from the MAINTAIN-pc randomized trial

Introduction/Purpose

Weight maintenance following intentional weight loss is challenging and often unsuccessful. Physical activity and self-monitoring are strategies associated with successful weight loss maintenance. However, less is known about the type and number of lifestyle strategies used following intentional weight loss. The purpose of this study was to determine the types and amounts of strategies associated with successful long-term weight loss maintenance.

Methods

Data from the 24-month Maintaining Activity and Nutrition Through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) trial were analyzed. MAINTAIN-pc recruited adults (n=194; 53.4±12.2 years of age, body mass index (BMI): 30.4±5.9 kg/m2, 74% female) with recent intentional weight loss of ≥5%, randomized to tracking tools plus coaching (i.e., coaching group) or tracking tools without coaching (i.e., tracking-only group). At baseline, 6, 12, and 24 months, participants reported lifestyle strategies used in the past 6 months, including self-monitoring, group support, behavioral skills, and professional support. General linear models evaluated changes in the number of strategies over time between groups and the consistency of strategies used over the 24-month intervention.

Results

At baseline, 100% used behavioral skills, 73% used group support, 69% used self-monitoring, and 68% used professional support in the past 6 months; at 24 months, these rates were 98%, 60%, 75%, and 61%, respectively. While the number of participants utilizing individual strategies did not change significantly over time, the overall number of strategies participants reported decreased. More strategies were used at baseline and 6 months compared to 12- and 24-month follow-ups. The coaching group used more strategies at months 6 and 12 than the tracking-only group. Consistent use of professional support strategies over the 24-month study period was associated with less weight regain.

Conclusion

Weight loss maintenance interventions that incorporate continued follow-up and support from healthcare professionals are likely to prevent weight regain after intentional weight loss.

Associations of physical and social workplace characteristics with movement behaviors at work

Introduction/Purpose

Sedentary behavior (SB) is common in desk-based work and prolonged periods of SB are associated with negative health outcomes. This study assessed associations between workplace characteristics and setting and movement patterns during working hours.

Methods

This secondary analysis used baseline data from the Reducing Sedentary Behavior to Decrease Blood Pressure (RESET BP) clinical trial which enrolled inactive, desk-based workers with elevated blood pressure (n=271; mean age: 45.3±11.6 years; body mass index (BMI): 30.66±7.1 kg/m2; 59.4% women). Physical and social workplace characteristics were assessed by a study-developed questionnaire and the Office Environment and Sitting Scale (OFFESS). Participants also wore an activPAL activity monitor for 7 days and reported working hours in a diary to measure SB and physical activity (PA) specifically while working. Linear regression was used to analyze cross-sectional associations between workplace characteristics and SB and PA. A stratified analysis was also conducted to assess associations among home-based and in-office desk workers separately. Analyses were adjusted for age, gender, BMI, and work wear time.

Results

Participants spent 77% of working hours in SB. Public vs. private offices, working in-office vs. at home, higher local connectivity, and greater overall connectedness were associated with lower SB and/or greater PA (all p<0.05). Higher frequency of face-to-face interactions, and greater visibility and proximity to co-workers was associated with less SB and more PA (all p<0.05). For example, home-based workers had more total SB (+17.2±8.4 mins/day), more SB bouts ≥30 mins (+39.1±12.8 mins/day), and less steps (695±201 steps/day) than in-office employees. Stratification by office setting revealed differences in associations between SB and PA and workplace characteristics.

Conclusions

More public, open spaces with more social interactions and physical walkways could improve SB and PA patterns during work. Home-based workers had more SB, less PA, and unique associations of these activities with workplace characteristics, suggesting a need for tailored interventions.

Impact of electronic health record-coaching features in weight change: A secondary analysis from the MAINTAIN-pc randomized trial

OBJECTIVE

This study aimed to evaluate whether coaching features were successfully transmitted via electronic health record (EHR) communication and to evaluate their relationship with weight change in a previously tested EHR-based coaching intervention.

METHODS

A secondary analysis from the Maintaining Activity and Nutrition through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) study randomized clinical trial was conducted in nine primary care practices and one specialty practice (endocrinology) affiliated with the University of Pittsburgh Medical Center. Eligibility included age 18 to 75 years, intentional 5% weight loss in the previous 2 years, access to an internet-connected computer, and receipt of care from a University of Pittsburgh Medical Center primary care provider. Survey data were collected during the randomized clinical trial.

RESULTS

Participants content with intervention delivery via the EHR and those who felt a strong connection to their coach had significantly less weight regain (p = 0.013 and p < 0.01, respectively). Participants who had needs unmet by the intervention (e.g., "in-person" support in a group setting or individual settings) regained more weight (p < 0.01).

CONCLUSIONS

The data suggest heterogeneity in the patient population regarding preference for in-person versus EHR-based coaching formats. Such heterogeneity might result in the differential success of EHR-based interventions.

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.

Comparative Safety and Effectiveness of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy for Weight Loss and Type 2 Diabetes Across Race and Ethnicity in the PCORnet Bariatric Study Cohort

Importance

Bariatric surgery is the most effective treatment for severe obesity; yet it is unclear whether the long-term safety and comparative effectiveness of these operations differ across racial and ethnic groups.

Objective

To compare outcomes of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) across racial and ethnic groups in the National Patient-Centered Clinical Research Network (PCORnet) Bariatric Study.

Design, Setting, and Participants

This was a retrospective, observational, comparative effectiveness cohort study that comprised 25 health care systems in the PCORnet Bariatric Study. Patients were adults and adolescents aged 12 to 79 years who underwent a primary (first nonrevisional) RYGB or SG operation between January 1, 2005, and September 30, 2015, at participating health systems. Patient race and ethnicity included Black, Hispanic, White, other, and unrecorded. Data were analyzed from July 1, 2021, to January 17, 2022.

Exposure

RYGB or SG.

Outcomes

Percentage total weight loss (%TWL); type 2 diabetes remission, relapse, and change in hemoglobin A1c (HbA1c) level; and postsurgical safety and utilization outcomes (operations, interventions, revisions/conversions, endoscopy, hospitalizations, mortality, 30-day major adverse events) at 1, 3, and 5 years after surgery.

Results

A total of 36 871 patients (mean [SE] age, 45.0 [11.7] years; 29 746 female patients [81%]) were included in the weight analysis. Patients identified with the following race and ethnic categories: 6891 Black (19%), 8756 Hispanic (24%), 19 645 White (53%), 826 other (2%), and 783 unrecorded (2%). Weight loss and mean reductions in HbA1c level were larger for RYGB than SG in all years for Black, Hispanic, and White patients (difference in 5-year weight loss: Black, -7.6%; 95% CI, -8.0 to -7.1; P < .001; Hispanic, -6.2%; 95% CI, -6.6 to -5.9; P < .001; White, -5.9%; 95% CI, -6.3 to -5.7; P < .001; difference in change in year 5 HbA1c level: Black, -0.29; 95% CI, -0.51 to -0.08; P = .009; Hispanic, -0.45; 95% CI, -0.61 to -0.29; P < .001; and White, -0.25; 95% CI, -0.40 to -0.11; P = .001.) The magnitude of these differences was small among racial and ethnic groups (1%-3% of %TWL). Black and Hispanic patients had higher risk of hospitalization when they had RYGB compared with SG (hazard ratio [HR], 1.45; 95% CI, 1.17-1.79; P = .001 and 1.48; 95% CI, 1.22-1.79; P < .001, respectively). Hispanic patients had greater risk of all-cause mortality (HR, 2.41; 95% CI, 1.24-4.70; P = .01) and higher odds of a 30-day major adverse event (odds ratio, 1.92; 95% CI, 1.38-2.68; P < .001) for RYGB compared with SG. There was no interaction between race and ethnicity and operation type for diabetes remission and relapse.

Conclusions and Relevance

Variability of the comparative effectiveness of operations for %TWL and HbA1c level across race and ethnicity was clinically small; however, differences in safety and utilization outcomes were clinically and statistically significant for Black and Hispanic patients who had RYGB compared with SG. These findings can inform shared decision-making regarding bariatric operation choice for different racial and ethnic groups of patients.

Early Outcomes of a New NIH Program to Support Research in Residency

The work of physician-investigators has historically led to key discoveries and developments in modern medicine, but recent decades have seen significant declines in the number of U.S. physician-investigators. One of the barriers to physicians participating in research is the lack of mentored research opportunities during clinical training, especially during residency training. In response to this identified barrier and to expand the physician-investigator workforce, the National Institutes of Health initiated the R38 program, known as Stimulating Access to Research in Residency, to support mentored research opportunities for residents. This article reports on the early outcomes of the recipients of the initial round of R38 awards, granted in 2018. Early positive outcomes include increases in the reported likelihood of resident-investigators pursuing physician-investigator careers, greater reported clarity in resident-investigators' research directions, the commitment of additional institutional resources to support the R38-awarded programs, and the approval of resident-investigators as having met training requirements for certification by multiple medical boards.

Implementing a Dutch Physical Therapy Intervention Into a U.S. Health System: Selecting Strategies Using Implementation Mapping

Background

Coach2Move is a person-centered physical therapy intervention that has demonstrated success in changing physical activity behaviors among older adults in the Netherlands. In this manuscript, we describe how we developed an implementation plan for Coach2move in a U.S. population and healthcare system using Implementation Mapping.

Methods

We established an implementation planning team of researchers, patients, and clinicians. The Consolidated Framework for Implementation Research provided an overall structure for consideration of the context for implementation. Implementation Mapping guided the planning process. The implementation planning team worked sequentially through the five tasks of Implementation Mapping (1) Identify needs, program adopters and implementers; (2) Identify adoption and implementation outcomes, performance objectives, determinants, and matrices of change; (3) Choose theoretical models and implementation strategies; (4) Produce implementation protocols; (5) Evaluate implementation outcomes. In this manuscript, we identify our evaluation plan but not results as data collection is ongoing.

Results

Clinic managers and physical therapists were identified as program adopters and implementors. Performance objectives necessary steps to achieving implementation outcomes were linked to Coach2Move fidelity indicators with implementation by the physical therapist. These included delivery of person-centered care, motivational interviewing, meaningful goal setting, shared decision-making in planning, and systematic monitoring and follow-up. Determinants linked to these performance objectives included knowledge, outcome expectations, skills and self-efficacy, and perceived norms. Implementation strategies were selected based on a review of methods effective for influencing these determinants. This resulted in four primary strategies (1) educational meetings and dynamic training, (2) peer-assessment meetings, (3) changing the electronic health record template, and (4) reminders and prompts. Measures of intervention acceptability, appropriateness, and feasibility will be collected after training and early in implementation. Fidelity and effectiveness measures will be collected over the next 12-months.

Conclusion

Implementation mapping provided a systematic process for identifying what physical therapists would need to implement Coach2Move with fidelity. The result was a matrix linking behavioral determinants and performance objectives. These matrices of change allowed for systematic identification and tailoring of implementation strategies to the needs of our population and setting. The process was acceptable to diverse stakeholders, facilitated communication across stakeholders.

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

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

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.

The Impact of a Yearlong Diabetes Prevention Program-Based Lifestyle Intervention on Cardiovascular Health Metrics

Introduction

The American Heart Association created “Life’s Simple Seven” metrics to estimate progress toward improving US cardiovascular health in a standardized manner. Given the widespread use of federally funded Diabetes Prevention Program (DPP)-based lifestyle interventions such as the Group Lifestyle Balance (DPP-GLB), evaluation of change in health metrics within such a program is of national interest. This study examined change in cardiovascular health metric scores during the course of a yearlong DPP-GLB intervention.

Methods

Data were combined from 2 similar randomized trials offering a community based DPP-GLB lifestyle intervention to overweight/obese individuals with prediabetes and/or metabolic syndrome. Pre/post lifestyle intervention participation changes in 5 of the 7 cardiovascular health metrics were examined at 6 and 12 months (BMI, blood pressure, total cholesterol, fasting plasma glucose, physical activity). Smoking was rare and diet was not measured.

Results

Among 305 participants with complete data (81.8% of 373 eligible adults), significant improvements were demonstrated in all 5 risk factors measured continuously at 6 and 12 months. There were significant positive shifts in the “ideal” and “total” metric scores at both time points. Also noted were beneficial shifts in the proportion of participants across categories for BMI, activity, and blood pressure.

Conclusion

AHA-metrics could have clinical utility in estimating an individual’s cardiovascular health status and in capturing improvement in cardiometabolic/behavioral risk factors resulting from participation in a community-based translation of the DPP lifestyle intervention.

Effect of Reducing Sedentary Behavior on Blood Pressure (RESET BP): Rationale, design, and methods

Sedentary behavior (SB) has recently been recognized as a strong risk factor for cardiovascular disease, with new guidelines encouraging adults to 'sit less, move more.' Yet, there are few randomized trials demonstrating that reducing SB improves cardiovascular health. The Effect of Reducing Sedentary Behavior on Blood Pressure (RESET BP) randomized clinical trial addresses this gap by testing the effect of a 3-month SB reduction intervention on resting systolic BP. Secondary outcomes include other BP measures, pulse wave velocity, plasma renin activity and aldosterone, and objectively-measured SB (via thigh-mounted activPAL) and physical activity (via waist-worn GT3X accelerometer). RESET BP has a targeted recruitment of 300 adults with desk jobs, along with elevated, non-medicated BP (systolic BP 120-159 mmHg or diastolic BP 80-99 mmHg) and physical inactivity (self-reported aerobic physical activity below recommended levels). The multi-component intervention promotes 2-4 fewer hours of SB per day by replacing sitting with standing and light-intensity movement breaks. Participants assigned to the intervention condition receive a sit-stand desk attachment, a wrist-worn activity prompter, behavioral counseling every two weeks (alternating in-person and phone), and twice-weekly automated text messages. Herein, we review the study rationale, describe and evaluate recruitment strategies based on enrollment to date, and detail the intervention and assessment protocols. We also document our mid-trial adaptations to participant recruitment, intervention deployment, and outcome assessments due to the intervening COVID-19 pandemic. Our research methods, experiences to date, and COVID-specific accommodations could inform other research studying BP and hypertension or targeting working populations, including those seeking remote methods.

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.

Inequities in Hypertension Control in the United States Exposed and Exacerbated by COVID-19 and the Role of Home Blood Pressure and Virtual Health Care During and After the COVID-19 Pandemic

The COVID‐19 pandemic is a public health crisis, having killed more than 514 000 US adults as of March 2, 2021. COVID‐19 mitigation strategies have unintended consequences on managing chronic conditions such as hypertension, a leading cause of cardiovascular disease and health disparities in the United States. During the first wave of the pandemic in the United States, the combination of observed racial/ethnic inequities in COVID‐19 deaths and social unrest reinvigorated a national conversation about systemic racism in health care and society. The 4th Annual University of Utah Translational Hypertension Symposium gathered frontline clinicians, researchers, and leaders from diverse backgrounds to discuss the intersection of these 2 critical social and public health phenomena and to highlight preexisting disparities in hypertension treatment and control exacerbated by COVID‐19. The discussion underscored environmental and socioeconomic factors that are deeply embedded in US health care and research that impact inequities in hypertension. Structural racism plays a central role at both the health system and individual levels. At the same time, virtual healthcare platforms are being accelerated into widespread use by COVID‐19, which may widen the divide in healthcare access across levels of wealth, geography, and education. Blood pressure control rates are declining, especially among communities of color and those without health insurance or access to health care. Hypertension awareness, therapeutic lifestyle changes, and evidence‐based pharmacotherapy are essential. There is a need to improve the implementation of community‐based interventions and blood pressure self‐monitoring, which can help build patient trust and increase healthcare engagement.

Angiotensin II receptor blocker or angiotensin-converting enzyme inhibitor use and COVID-19-related outcomes among US Veterans

BACKGROUND

Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) may positively or negatively impact outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association of ARB or ACEI use with coronavirus disease 2019 (COVID-19)-related outcomes in US Veterans with treated hypertension using an active comparator design, appropriate covariate adjustment, and negative control analyses.

METHODS AND FINDINGS

In this retrospective cohort study of Veterans with treated hypertension in the Veterans Health Administration (01/19/2020-08/28/2020), we compared users of (A) ARB/ACEI vs. non-ARB/ACEI (excluding Veterans with compelling indications to reduce confounding by indication) and (B) ARB vs. ACEI among (1) SARS-CoV-2+ outpatients and (2) COVID-19 hospitalized inpatients. The primary outcome was all-cause hospitalization or mortality (outpatients) and all-cause mortality (inpatients). We estimated hazard ratios (HR) using propensity score-weighted Cox regression. Baseline characteristics were well-balanced between exposure groups after weighting. Among outpatients, there were 5.0 and 6.0 primary outcomes per 100 person-months for ARB/ACEI (n = 2,482) vs. non-ARB/ACEI (n = 2,487) users (HR 0.85, 95% confidence interval [CI] 0.73-0.99, median follow-up 87 days). Among outpatients who were ARB (n = 4,877) vs. ACEI (n = 8,704) users, there were 13.2 and 14.8 primary outcomes per 100 person-months (HR 0.91, 95%CI 0.86-0.97, median follow-up 85 days). Among inpatients who were ARB/ACEI (n = 210) vs. non-ARB/ACEI (n = 275) users, there were 3.4 and 2.0 all-cause deaths per 100 person months (HR 1.25, 95%CI 0.30-5.13, median follow-up 30 days). Among inpatients, ARB (n = 1,164) and ACEI (n = 2,014) users had 21.0 vs. 17.7 all-cause deaths, per 100 person-months (HR 1.13, 95%CI 0.93-1.38, median follow-up 30 days).

CONCLUSIONS

This observational analysis supports continued ARB or ACEI use for patients already using these medications before SARS-CoV-2 infection. The novel beneficial association observed among outpatients between users of ARBs vs. ACEIs on hospitalization or mortality should be confirmed with randomized trials.

Appetite and Energy Intake Regulation in Response to Acute Exercise

PURPOSE

This study aimed to determine if energy intake and appetite regulation differ in response to an acute bout of resistance exercise (REx) versus aerobic exercise (AEx).

METHODS

Physically inactive adults (n = 24, 35% ± 2% body fat, 50% female) completed three conditions: AEx (walking at 65%-70% heart rate max for 45 min), REx (1 set to failure of 12 exercises), and sedentary control (SED). Each condition was initiated in the postprandial state (35 min after breakfast). Appetite (visual analog scale for hunger, satiety, and prospective food consumption) and hormones (ghrelin, peptide YY (PYY), and glucagon-like peptide-1 (GLP-1)) were measured before and 30, 90, 120, 150, and 180 min after a standardized breakfast. Area under the curve was calculated using the trapezoid method. Ad libitum energy intake was evaluated at a lunch meal after the 180-min measurements.

RESULTS

No differences in ad libitum energy intake (REx, 991 ± 68; AEx, 937 ± 65; SED, 944 ± 76 kcal; P = 0.50) or appetite ratings (all, P > 0.05) were detected. The area under the curve for ghrelin, PYY, and GLP-1 were all lower after REx versus AEx (ghrelin: 130,737 ± 4928 for REx; 143,708 ± 7500 for AEx (P = 0.006); PYY: 20,540 ± 1177 for REx, 23,812 ± 1592 for AEx (P = 0.001); and GLP-1: 1314 ± 93 for REx, 1615 ± 110 for AEx (P = 0.013)). Neither exercise condition significantly differed from SED.

CONCLUSIONS

Acute REx lowers both orexigenic (ghrelin) and anorectic (PYY and GLP-1) gut peptides compared with acute AEx. Ad libitum energy intake did not increase compared with SED in either exercise condition, indicating both exercise modalities have appetite and energy intake suppressing effects. Future work is needed to determine if exercise of differing modalities influences chronic appetite regulation.

Measuring Adherence to U.S. Preventive Services Task Force Diabetes Prevention Guidelines Within Two Healthcare Systems

ABSTRACT

Measuring adherence to the 2015 U.S. Preventive Services Task Force (USPSTF) diabetes prevention guidelines can inform implementation efforts to prevent or delay Type 2 diabetes. A retrospective cohort was used to study patients without a diagnosis of diabetes attributed to primary care clinics within two large healthcare systems in our state to study adherence to the following: (1) screening at-risk patients and (2) referring individuals with confirmed prediabetes to participate in an intensive behavioral counseling intervention, defined as a Center for Disease Control and Prevention (CDC)-recognized Diabetes Prevention Program (DPP). Among 461,866 adults attributed to 79 primary care clinics, 45.7% of patients were screened, yet variability at the level of the clinic ranged from 14.5% to 83.2%. Very few patients participated in a CDC-recognized DPP (0.52%; range 0%-3.53%). These findings support the importance of a systematic implementation strategy to specifically target barriers to diabetes prevention screening and referral to treatment.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02260-x.

Efficacy of an Online Physical Activity Intervention Coordinated With Routine Clinical Care: Protocol for a Pilot Randomized Controlled Trial

Background

Most adults are not achieving recommended levels of physical activity (150 minutes/week, moderate-to-vigorous intensity). Inadequate activity levels are associated with numerous poor health outcomes, and clinical recommendations endorse physical activity in the front-line treatment of obesity, diabetes, dyslipidemia, and hypertension. A framework for physical activity prescription and referral has been developed, but has not been widely implemented. This may be due, in part, to the lack of feasible and effective physical activity intervention programs designed to coordinate with clinical care delivery.

Objective

This manuscript describes the protocol for a pilot randomized controlled trial (RCT) that tests the efficacy of a 13-week online intervention for increasing physical activity in adult primary care patients (aged 21-70 years) reporting inadequate activity levels. The feasibility of implementing specific components of a physical activity clinical referral program, including screening for low activity levels and reporting patient program success to referring physicians, will also be examined. Analyses will include participant perspectives on maintaining physical activity.

Methods

This pilot study includes a 3-month wait-listed control RCT (1:1 ratio within age strata 21-54 and 55-70 years). After the RCT primary end point at 3 months, wait-listed participants are offered the full intervention and all participants are followed to 6 months after starting the intervention program. Primary RCT outcomes include differences across randomized groups in average step count, moderate-to-vigorous physical activity, and sedentary behavior (minutes/day) derived from accelerometers. Maintenance of physical activity changes will be examined for all participants at 6 months after the intervention start.

Results

Recruitment took place between October 2018 and May 2019 (79 participants were randomized). Data collection was completed in February 2020. Primary data analyses are ongoing.

Conclusions

The results of this study will inform the development of a clinical referral program for physical activity improvement that combines an online intervention with clinical screening for low activity levels, support for postintervention behavior maintenance, and feedback to the referring physician.

Trial Registration

ClinicalTrials.gov NCT03695016; https://clinicaltrials.gov/ct2/show/NCT03695016.

International Registered Report Identifier (IRRID)

DERR1-10.2196/18891

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.

Provider Advice and Patient Perceptions on Weight Across Five Health Systems

INTRODUCTION

To improve the management of overweight and obesity in the primary care setting, an analysis of patient perceptions of weight status and predictors of weight loss attempts for those with overweight and obesity is needed.

METHODS

Primary care patients (n=949) across 5 health systems in the Mid-Atlantic region of the U.S. were surveyed in 2015; data analysis was performed in 2018. Survey data was combined with data via the electronic health record to understand patients' perceptions of weight, factors associated with weight loss efforts, and provider counseling practices.

RESULTS

Most participants with overweight or obesity perceived themselves as weighing too much and reported trying to lose weight. Furthermore, most participants with obesity reported receiving advice to lose weight by a provider in the past 12 months. However, less than half of patients with overweight reported receiving advice to lose weight, maintain weight, or develop healthy eating and physical activity patterns from a health professional in the past 12 months. Among participants with overweight and obesity, multivariable logistic regression analysis demonstrated that the perception of being overweight and receiving healthcare advice to lose weight had the highest odds of reporting attempted weight loss (OR=5.5, 95% CI=2.7, 11.2 and OR=3.9, 95% CI=1.9, 7.9, respectively).

CONCLUSIONS

The findings emphasize the importance of provider attention to weight management counseling and identifies patients with overweight as needing increased attention by providers.

0176 Short Sleep Duration and Poor Sleep Quality Predict Blunted Weight Loss in a Behavioral Weight Loss Intervention

Introduction

Short sleep duration and poor sleep quality have each been associated with obesity and weight gain. However, less is known regarding how sleep may impact attempted weight loss. The purpose of this study was to investigate the associations between sleep duration and sleep quality, both independently and in combination, with weight loss in a 12-month behavioral weight loss intervention.

Methods

Young to middle-aged adults who were overweight or obese (N=296) completed a 12-month behavioral weight loss intervention, with weight assessed at baseline, 6 and 12 months. Sleep duration and quality were derived from the Pittsburgh Sleep Quality Index. Analyses examined the change in sleep over time and the association between baseline sleep and changes in sleep with 6- and 12-month weight loss following adjustment for relevant covariates including age, gender, race, education, baseline body mass index, and baseline risk for sleep apnea.

Results

Participants (with an average baseline weight of 97.0±1.0 kg) lost 6.6±1.1 kg (6.8%) and 6.7±1.2 kg (6.9%) at 6 and 12 months relative to baseline, respectively. Global sleep quality significantly improved over the 12-month intervention (P=.03), but average sleep duration and the prevalence of short sleep duration (&lt;6 h) or poor sleep quality did not change significantly (each P≥.45). Adults with short sleep duration at baseline lost 3.3±0.9% less weight than those with ≥6 h sleep duration (P&lt;.001). Adults with poor sleep quality at baseline lost 1.6±0.8% less weight than those with good sleep quality (P=.04). When considered together, adults with both short sleep duration and poor sleep quality lost at least 5.0% less weight compared with all other sleep duration/quality group combinations (P&lt;.001).

Conclusion

Our findings highlight the importance of both sleep duration and sleep quality as predictors of behavioral weight loss and suggest that screening for sleep disturbance may be useful to determine who may benefit from additional counseling and resources.

Support

R01HL077525, K23HL118318

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.

The SMARTER Trial: Design of a trial testing tailored mHealth feedback to impact self-monitoring of diet, physical activity, and weight

BACKGROUND

Self-monitoring food intake and physical activity (PA) is positively related to weight loss and the addition of feedback (FB) messages has been shown to reinforce behavior change. Moreover, the more immediate the delivery of reinforcing FB messages, the more likely they will promote the desired behaviors.

PURPOSE

Describe design and rationale of SMARTER, a National Institute of Heart, Lung, and Blood (NHLBI)-sponsored randomized, controlled trial, which compares the differential efficacy of two weight loss treatments among 530 adults, ages 18 and older.

METHODS

Single-site, 2-group design trial with subjects randomized 1:1 to either: 1) self-monitoring (SM), where participants self-monitor diet, PA, and weight using a commercial smartphone application (app); or 2) SM + FB, where participants self-monitor and receive real-time, tailored feedback (FB) as pop-up messages up to 3 times/day for 12 months. Daily FB messages address diet and PA behaviors and a weekly FB message addresses self-weighing. We hypothesize that subjects assigned to SM + FB will show greater weight loss at 6 and 12 months and greater sustained engagement in the program than the SM group, measured by adherence to the study's lifestyle and SM protocol. We will explore temporal relationships of the frequency, timing, and type of FB delivered and subsequent lifestyle behaviors through examination of serially collected real-time SM (diet, PA, weight) data over 12 months.

CONCLUSIONS

If efficacious, this fully scalable intervention could be efficiently translated and disseminated to reach large numbers of individuals through commercial apps at lower cost than existing in-person weight loss programs.

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.

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 ≧ 25 kg/m². Of patients with BMI ≧ 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.

Scholarly Research Projects Benefit Medical Students' Research Productivity and Residency Choice: Outcomes From the University of Pittsburgh School of Medicine

PURPOSE

Many medical schools require scholarly research projects. However, outcomes data from these initiatives are scarce. The authors studied the impact of the Scholarly Research Project (SRP), a four-year longitudinal requirement for all students at the University of Pittsburgh School of Medicine (UPSOM), on research productivity and residency match.

METHOD

The authors conducted a longitudinal study of non-dual-degree UPSOM graduates in 2006 (n = 121, non-SRP participants) versus 2008 (n = 118), 2010 (n = 106), and 2012 (n = 132), all SRP participants. The authors used PubMed for publication data, National Resident Matching Program for residency match results, and Blue Ridge Institute for Medical Research for National Institutes of Health funding rank for residency-affiliated academic institutions.

RESULTS

Research productivity of students increased for those completing the SRP, measured as a greater proportion of students with publications (27.3% in 2006 vs. 45.8% in 2008, 55.7% in 2010, and 54.5% in 2012; P < .001) and first-authorship (9.9% in 2006 vs. 26.3% in 2008, 33.0% in 2010, and 35.6% in 2012; P < .001). Across years, there was a significantly greater proportion of students with peer-reviewed publications matched in higher-ranked residency programs (57.0% with publications in the top 10%, 52.7% in the top 10%-25%, 32.4% in the top 25%-50%, 41.2% in the bottom 50%, and 45.2% in unranked programs; P = .018).

CONCLUSIONS

Longitudinal research experiences for medical students may be one effective tool in fostering student publications and interest in extending training in a research-focused medical center.