Examining Utilization of an Outpatient Telenutrition Service Across Primary Care Clinics in South Carolina.

Introduction: Limited research exists on outpatient telenutrition, and more evidence is needed on service utilization and program evaluation. This study explored service utilization trends and patterns of the Medical University of South Carolina (MUSC) Outpatient Telehealth Nutrition (OT Nutrition) service. Methods: De-identified patient service utilization data were obtained from MUSC's OT Nutrition administrative files (2012-2020). Service utilization (referrals, visits scheduled, consultations, no-shows, no-show rate) was measured at the clinic level and stratified by patient type (adult/pediatric) and clinic rurality (rural/urban). Data were analyzed using descriptive statistics and a K-means cluster analysis. Results: Service utilization (2012-2020) reflected 6,212 referrals, 3,993 visits scheduled, and 2,880 consultations across 56 clinics. Yearly utilization trends showed high variability with no statistically significant differences observed on univariate comparisons of patient type or clinic rurality. The introduction of the Direct-To-Consumer modality mitigated a 36.7% decrease in consultations during the COVID-19 pandemic in 2020. Results of a K-means cluster analysis (p < 0.001) indicated 7% (n = 4) of clinics were very high and high utilizers, 36% (n = 21) were moderate and low utilizers, and 53% (n = 31) were very low utilizers. Discussion: Telenutrition can be delivered effectively to patients without requiring travel outside patients' medical homes or residences. Although continued advocacy is necessary for South Carolina to expand telenutrition coverage, more research is needed to evaluate the OT Nutrition service. Cluster analysis is an effective tool for identifying statistically significant groupings of clinics based on service utilization and could be used with implementation science in future program evaluation.

Pilot evaluation of a personalized commercial program on weight loss, health outcomes, and quality of life.

WW is a validated behavioral weight management program that encourages healthy habits. WW developed a method of personalizing the SmartPoints® budget depending on dietary and lifestyle preferences, and participants were placed into one of three plans as a pilot evaluation of this new program. In this 6-month, single-arm pilot study, participants attended weekly workshops and used an app to monitor eating and physical activity. Baseline and 6-month assessments included weight, waist circumference, blood pressure, energy intake, cravings, happiness, health-related quality of life, hunger, and fullness. Of 145 adults assessed at baseline, 126 (87%) provided follow-up data. Pre-post changes showed significant reductions in body weight (7.39% ± 5.93%), calories consumed (24.79% ± 32.35%) and significant improvements in cravings, happiness, all SF-36 scales and hunger but not in fullness. Greater % weight loss was related to greater improvements in happiness (r = .38, p < .001), general health perceptions (r = .29, p = .001), and health change (r = .31, p = .001), and greater reduction in role limitations due to personal or emotional problems (r = .24, p = .01). Greater % reduction in caloric intake was associated with greater reductions in cravings (r = .23, p = .01), as well as with greater improvements in happiness (r = .23, p = .01), physical functioning (r = .23, p = .01), and general health perceptions (r = .23, p = .01). Participants in this modified program achieved significant weight loss, regardless of dietary plan, as well as improvements in a variety of other physical and psychological constructs. Those who achieved greater reductions in weight also reported greater improvements in cravings, happiness and some quality of life measures.

Evaluation of a Lifestyle Change Worksite Weight Management Program Across Multiple Employers and Sites.

OBJECTIVE: The aim of the study was to assess weight loss outcomes among participants (N = 1090) of a weight management program across multiple worksites (N = 10) in a retrospective analysis. METHODS: Weekly classes focused on diet, exercise, and behavior change. One employer provided incentives for weight loss and two incentivized weight loss and class attendance. RESULTS: Mean weight loss (N = 1090; 79.3% female) was -2.9% (SD = 3.0%). Average number of classes attended was 6.87/10 (SD = 2.9) and was significantly correlated with percent weight change (r = -0.46; P < 0.001). Participants incentivized for attendance attended significantly more classes (M = 7.5, SD = 2.8) than did those not so incentivized (M = 6.4, SD = 2.9, P < 0.001), but did not lose more weight (P = 0.24). Participants incentivized for weight loss did not lose significantly more weight than those not so incentivized (P = 0.26). CONCLUSIONS: These data support the effectiveness of this worksite program. Utilizing incentives to promote class attendance may be beneficial for increasing engagement in similar programs.

Tools Clinicians Can Use to Help Get Patients Active.

An epidemic of physical inactivity has given rise to a population struggling with early mortality and an increase in chronic non-communicable diseases such as cardiovascular disease, diabetes, and cancer. Primary care providers as well as other clinicians are in a position to help overcome this epidemic of physical inactivity. The goal of this commentary is to provide clinicians with resources and recommendations from the recent literature to help overcome barriers to physical activity counseling and help patients become physically active. Theory-based interventions from communication and exercise prescriptions to wearables and mobile health technology are discussed. Limitations and future directions are explored.

Choosing between responsive-design websites versus mobile apps for your mobile behavioral intervention: presenting four case studies.

Both mobile apps and responsive-design websites (web apps) can be used to deliver mobile health (mHealth) interventions, but it can be difficult to discern which to use in research. The goal of this paper is to present four case studies from behavioral interventions that developed either a mobile app or a web app for research and present an information table to help researchers determine which mobile option would work best for them. Four behavioral intervention case studies (two developed a mobile app, and two developed a web app) presented include time, cost, and expertise. Considerations for adopting a mobile app or a web app-such as time, cost, access to programmers, data collection, security needs, and intervention components- are presented. Future studies will likely integrate both mobile app and web app modalities. The considerations presented here can help guide researchers on which platforms to choose prior to starting an mHealth intervention.

The Fast-Casual Conundrum: Fast-Casual Restaurant Entrées Are Higher in Calories than Fast Food.

BACKGROUND: Frequently eating fast food has been associated with consuming a diet high in calories, and there is a public perception that fast-casual restaurants (eg, Chipotle) are healthier than traditional fast food (eg, McDonald's). However, research has not examined whether fast-food entrées and fast-casual entrées differ in calorie content. OBJECTIVE: The purpose of this study was to determine whether the caloric content of entrées at fast-food restaurants differed from that found at fast-casual restaurants. DESIGN: This study was a cross-sectional analysis of secondary data. Calorie information from 2014 for lunch and dinner entrées for fast-food and fast-casual restaurants was downloaded from the MenuStat database. OUTCOME MEASURES: Mean calories per entrée between fast-food restaurants and fast-casual restaurants and the proportion of restaurant entrées that fell into different calorie ranges were assessed. STATISTICAL ANALYSES PERFORMED: A t test was conducted to test the hypothesis that there was no difference between the average calories per entrée at fast-food and fast-casual restaurants. To examine the difference in distribution of entrées in different calorie ranges between fast-food and fast-casual restaurants, χ(2) tests were used. RESULTS: There were 34 fast-food and 28 fast-casual restaurants included in the analysis (n=3,193 entrées). Fast-casual entrées had significantly more calories per entrée (760±301 kcal) than fast-food entrées (561±268; P<0.0001). A greater proportion of fast-casual entrées compared with fast-food entrées exceeded the median of 640 kcal per entrée (P<0.0001). CONCLUSIONS: Although fast-casual entrées contained more calories than fast-food entrées in the study sample, future studies should compare actual purchasing patterns from these restaurants to determine whether the energy content or nutrient density of full meals (ie, entrées with sides and drinks) differs between fast-casual restaurants and fast-food restaurants. Calorie-conscious consumers should consider the calorie content of entrée items before purchase, regardless of restaurant type.

Transitioning to new child-care nutrition policies: nutrient content of preschool menus differs by presence of vegetarian main entrée.

Children who attend child care outside the home may be at increased risk for developing obesity. In 2012, the South Carolina ABC Child Care program issued new standards for food and nutrition. The goal of our study (conducted June to December 2012) was to examine changes that occurred at a large, Columbia, SC, preschool during the implementation of the South Carolina ABC Child Care program standards using an observational design, including a survey of parents and nutrient analysis of menus. The nutrition content of menu items before (n=15 days; six of which were vegetarian) and after (n=15 days; six of which were vegetarian) implementation of the new standards was compared. In addition, parents (N=75) were surveyed to examine opinions and support for the changes. Independent samples t tests were used to compare nutrient values before and after menu changes and analysis of variance was used to compare pre- and post-change vegetarian menus and pre- and post-change nonvegetarian menus. There were no significant differences between before and after menus with the exception of a 0.3 cup/day increase in vegetables (P<0.05). Vegetarian menus after the revisions were significantly higher in fiber (13 ± 3 g) than postrevision nonvegetarian menus (11 ± 3 g; P<0.05) and lower in sodium (1,068 ± 207 mg) than postrevision nonvegetarian menus (1,656 ± 488 mg; P<0.05). Standards that received the most parental support were serving at least two vegetables (score of 8.7 on a scale of one to nine) and two fruits per day (score of 8.6) and implementing policies against staff using food as a reward or punishment (score of 8.6). The center-specific policy of only bringing healthy foods for celebrations received the lowest support (score of 5.8). Adding more vegetarian menu items has the potential to improve the nutrient content of menus while keeping energy intake, saturated fat, sodium, and cholesterol levels at a more optimum level.

Varying social media post types differentially impacts engagement in a behavioral weight loss intervention.

The purpose of this study was to examine whether different types of posts differentially affect participant engagement and if engagement with social media enhances weight loss. Data are a subanalysis from a randomized weight loss study with a 4-month follow-up support period via private Facebook groups and monthly meetings. Counselors posted five different post types/week based on social cognitive theory (weight-related, recipes, nutrition information, poll votes, or requests for suggestions). Types of participant engagement (likes, comments/poll votes, and views) were assessed. Poll votes were the most engaging (mean number of votes or comments/poll 14.6 ± 3.4, P < 0.01) followed by suggestions (9.1 ± 2.7 posts, P < 0.01) and weight-related posts (7.4 ± 3.1 posts, P < 0.01). Engagement with Facebook was significantly associated with weight loss during the 4-month maintenance period (B = -0.09, P = 0.04). The findings provide evidence for ways to provide social support during weight loss interventions using remote methodology.