Abstract
Introduction: Lifestyle medicine can reduce the risk of developing cardiometabolic disease. Yet, interventions are predominantly designed for rehabilitation, and many struggle with time and location barriers. Virtual health coaching modalities show promise in addressing these barriers. This paper describes the outcomes of a semi-virtual, prevention-focused lifestyle medicine program that ranged from 10-12 weeks. Method: A retrospective, observational study was conducted to examine the impact of this program on participant outcomes. The results included changes in health risk factors (eg, weight, blood pressure, waist circumference) and lifestyle behaviors (eg, nutrition habits, exercise frequency, quality of life). Results: When comparing pre-post data, reductions in the primary health metrics including weight (mean: −8.5 pounds; SD: 7.54, P < 0.001), systolic blood pressure (mean: −6.1 mmHg; SD: 11.62, P < 0.001), and diastolic blood pressure (mean: −4.7 mmHg; SD: 9.03, P < 0.001) were observed. Significant improvements were noted in body mass index, waist and hip circumferences, resting heart rate, and quality of life. Participants adhered to the program and experienced meaningful clinical improvements. Conclusion: The reported outcomes demonstrate the potential benefits of this semi-virtual program, which utilized a health coaching approach, on participant health metrics.
Keywords: lifestyle medicine, heart disease, health coaching, Mediterranean diet, virtual, wellness program, prevention, chronic disease, chronic disease management, risk factor management, behavior change, health behaviors, patient education, plant-based diet, diabetes, hypertension, obesity, nutrition, exercise, wellness, wellbeing, mindful eating, mindfulness, weight management, quality of life
“A key component of the RENEW program is the health coaching model, in which coaches assist participants in engaging in lifestyle behaviors that align with their health and wellness goals.”
Introduction
Chronic Disease and Lifestyle: A Background
The prevalence of chronic diseases, including hypertension, stroke, heart disease, type 2 diabetes, and obesity, among others, are escalating at an alarming rate. Recent data suggests that over 80% of healthcare spending in the United States is linked to the cost burden of these, often preventable, chronic diseases that appear to stem, in part, from unhealthy lifestyle behaviors. 1 Lifestyle medicine is a medical specialty that emphasizes the prevention and treatment of chronic disease by focusing on lifestyle behavior modification. This specialty acts as an important complement to traditional medical therapies. Lifestyle medicine interventions take a whole-person approach, focusing on improved nutrition, exercise, stress, sleep, social well-being, and avoidance of risky substances (ie, alcohol, cigarettes, etc.). 1 Many of these interventions have demonstrated the ability to improve cardiometabolic disease risk in various settings.2-4 Still, designing cost-effective, prevention-focused, lifestyle medicine programs that result in meaningful health outcomes remains a challenge.
Lifestyle Medicine: Current State
Traditional lifestyle medicine interventions tend to focus on chronic-illness rehabilitation (eg, post-stroke, coronary artery disease, type 2 diabetes, etc.) and are often hosted in clinical settings.4,5 While these interventions are essential for their intended populations, the rehabilitation focus excludes relatively healthy populations who seek guidance on chronic disease prevention. In response, there is an increasing demand for lifestyle medicine interventions that take a more preventative focus.
With the successful outcomes of existing lifestyle interventions, healthcare systems look to integrate lifestyle medicine practices into their frameworks. 6 Healthcare systems are uniquely positioned to offer prevention-focused programs due to the availability of collaborative care teams and often expansive community reach. In one notable example, the New York City Health + Hospitals system hosted a lifestyle medicine program led by an interdisciplinary healthcare team. 2 While this study reported high demand for comprehensive, prevention-focused programs, some challenges identified included financial barriers and location/meeting times offered. 2
Digital Interventions and a Health Coaching Approach
To overcome these time and location barriers, future programs can look to the integration of remote design features, including virtual appointments. Digital interventions have increased in popularity in recent years, allowing for more flexible program offerings to participants. 7 Additionally, using a health coaching model for delivering these programs may be key to overcoming financial barriers and improving participant adherence to behavior changes. 8 Yet, there are still questions about the effectiveness of such programs in achieving meaningful outcomes. More data is needed to understand how to design effective interventions that operate sustainably and deliver positive patient outcomes.
The RENEW Program (Restore and Empower through Nutrition, Exercise, and Wellness), is a prevention-focused, semi-virtual, lifestyle medicine program designed and hosted by a large, public healthcare system to assist in preventing chronic disease development.
Study Aim
This study aims to assess the impact of this semi-virtual, health coaching program on participant outcomes. Primary outcomes of interest include weight loss and blood pressure improvements. Secondary outcomes include changes in waist and hip circumferences, resting heart rate, lifestyle behaviors, and quality of life (QOL) scores. Improvements in these outcomes support the overall program goal of assisting in the prevention of chronic disease.
Methods
Study Design
This retrospective repeated-measures, single-group study was designed to examine the impact of the RENEW program, which aimed to assist in the prevention of chronic disease by improving participant health, lifestyle behaviors, and QOL. This analysis included data from a 5-year period of the RENEW program, sourced from participants’ responses to pre- and post-program health, lifestyle, and QOL questionnaires.
Study Participants
This study includes data from all eligible RENEW program participants from the program’s inception in 2018 through 2023. The program was targeted to people who had an existing risk factor for cardiometabolic disease, eg, body mass index (BMI) over 25.0, hypertension, and hypercholesterolemia. Exclusion criteria for this study included participants who did not begin the program after the baseline appointment and participants without risk factors.
Study Setting
The RENEW program is a grant-funded program designed and delivered by a group of physicians, registered dietitians, certified personal trainers, and certified health coaches at Sarasota Memorial Health Care System (SMHCS). SMHCS is a large public health system in southwest Florida, offering full-service healthcare and serving as a regional safety net care provider. At its inception, the RENEW program exclusively served SMHCS employees. In 2021, the program offering was extended to community members. The study team for this research project includes the RENEW program medical directors, coordinator, registered dietitians and health coaches, as well as a biostatistician from the Sarasota Memorial Research Institute.
Intervention
Enrollment
Program participants were notified of the program through physician referrals, email and social media marketing campaigns, local newspaper magazine ads, and word of mouth. Applications were screened for inclusion and exclusion criteria. To join the program, participants must have had a history of at least one of the following cardiometabolic risk factors: BMI over 25.0, hypertension, hypercholesterolemia, hypertriglyceridemia, prediabetes, diabetes mellitus, family history of heart disease, current or past tobacco smoker, sleep apnea, stroke, coronary artery disease, transient ischemic attack, and peripheral vascular disease. Additionally, participants needed to be at least 21 years old, have the ability to exercise not contraindicated by a physician, possess a smartphone with Android or iOS capabilities, and have a moderate level of technology literacy. Participants with active cancer, pregnancy, or eating disorders were not permitted to join the program.
Health Coaching Delivery
The RENEW program structure consisted of weekly 30-min health coaching sessions and weekly 1-h group lessons that explored each pillar of the RENEW curriculum: nutrition, exercise, and wellness. This model evolved over the 5-year time period analyzed in this study. Weekly coaching sessions were initially delivered in-person, through an individual format. In response to the COVID-19 pandemic, the weekly coaching sessions transitioned to a virtual delivery in the Summer of 2020. In Spring of 2021, the individual coaching sessions were changed to a small-group format (including a maximum of 3 participants per coach). This change allowed for program scalability and enhanced community and connection amongst participants. From this point forward, the weekly coaching sessions remained small-group and virtual to provide more flexibility with scheduling. Finally, the cohort length started at 12 weeks and was reduced down to 10 weeks in Fall of 2021. The impact of these changes to the RENEW Program delivery and format will be the focus of a follow-up study.
Individual/small-group coaching sessions and group lessons were led by an interdisciplinary team of registered dietitians, certified health coaches, and certified personal trainers. Weekly group lessons included education on nutrition, exercise, or wellness, and allowed time for group discussion to foster social connection among participants. Individual/small-group health coaching sessions focused on setting individual health goals, navigating barriers to achieving these goals, and providing support and accountability to participants. Health goals were designed using the SMART (specific, measurable, achievable, relevant, time-bound) goal format. 9 This format allowed participants to set clear, short-term goals for their time in the program that were relevant to their long-term health and wellness goals. Each coaching session focused on supporting participant goals through the available program resources.
Nutrition & Plant-Based Mediterranean Diet
Program nutrition lessons focused on a primarily plant-based Mediterranean diet that emphasized whole foods and how to practice moderation around “treat” foods, ie, highly processed foods, red and processed meats, fried foods, refined grains, foods high in added sugar and sodium, and alcohol. These lessons included grocery store tours, cooking classes, and skill building around meal planning, mindful eating, and applying nutrition guidelines when dining out. Participants were able to use a photo-based food journal application called MealLogger by Metabite, Inc. to keep track of their daily food intake. This application allowed the registered dietitians to provide daily guidance, encouragement, and feedback to participants in accordance with the RENEW program’s nutrition guidelines.
Exercise
Program exercise lessons emphasized light to moderate aerobic exercise, with an additional focus on strength, flexibility, and functional, joyful movements for everyday life. Participants discussed their current exercise regimens with their coaches and were encouraged to increase their activity to the recommended 150 minutes per week of moderate-intensity exercise. 10
Mindfulness
Program wellness lessons were focused on fostering stress management skills through positive psychology and the PERMA (Positive emotion, Engagement, Relationships, Meaning, and Accomplishment) model. 11 Mindfulness activities included meditations, breathing techniques, mindful eating, and gratitude. Through the weekly curriculum, group lessons and coaching sessions the participants were encouraged to reflect on the relevance of mindfulness practice to their wellness goals.
Weekly Curriculum
To apply the RENEW curriculum, participants were asked to follow a primarily plant-based Mediterranean Diet, limit treat foods to two servings/day, practice stress management techniques, and increase their exercise frequency or duration beyond their pre-program starting point. Participants were provided resources in the form of a workbook, handouts, videos, meal plans, and recipes.
Measures
Health Metrics
Health metrics were recorded at baseline and the end of the program and included weight, height, waist and hip circumference, blood pressure, and resting heart rate. BMI and waist-to-hip ratios were calculated for each participant. Participants were encouraged to self-report pre- and post-program medications, dosages, and lab work including fasting blood glucose, hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL cholesterol), high-density lipoprotein cholesterol (HDL cholesterol), total cholesterol, and triglycerides.
Health Behaviors
Lifestyle behaviors were assessed through a food frequency questionnaire and physical activity questionnaire. Food frequency questionnaires (FFQs) are a common tool for dietary assessment to assess habitual dietary intake. Most FFQs query between 80 and 120 foods and beverages. To reduce the respondent burden, the program questionnaire was modeled after the Mini-EAT (Eating Assessment Tool), a 9‐item validated brief dietary screener that correlates well with a comprehensive food frequency questionnaire. 12 The RENEW FFQ is an 18-question non-quantitative FFQ of common food groups (beef, pork, poultry, fish and seafood, eggs, dairy, legumes, whole grains, refined grains, vegetables, fruits, nuts and seeds, and soy-based products) and foods that are commonly consumed by the target population and correlated with adverse health outcomes (sugar-sweetened beverages, desserts, fried foods, alcohol, and caffeine). The physical activity questionnaire used was modeled after the International Physical Activity Questionnaire (IPAQ) short form, a valid instrument that questions the frequency and duration of moderate and vigorous aerobic activities, as well as strength training within a typical week. 13
Quality of Life
A QOL questionnaire was developed to provide a score for participants’ sense of well-being. The questionnaire featured 20-items, using a five-point Likert scale for each answer to provide a score out of 100. The domains covered were lifestyle satisfaction, perceived health status, health-related limitations, and stress management. This QOL questionnaire was modeled after the WHOQOL-BREF (World Health Organization Quality of Life – BREF) but included more questions in areas such as problem-solving, coping with unplanned events, and emotional responses to stress. 14
Program Competencies
Competency measures were created to assess if participants achieved the intended competencies of program adherence, improved health outcomes, improved lifestyle behaviors, and improved QOL. Adherence to the program was defined by the participant having attended 80% of coaching sessions and the coach’s subjective evaluation that the participant followed the program guidelines. Improved health status included the participant experiencing at least 2 of the following outcomes: decreases in weight, BMI, waist circumference, hip circumference, blood pressure or resting heart rate, reduction in medications, improvement in lab values, or anecdotal improvements to feelings of wellbeing (energy, mental clarity, wellness behaviors, wellness beliefs, etc.).
For a participant to meet the improved lifestyle behaviors competency, they must have satisfied 3 criteria: increased intake of a “health-promoting food” (seafood, whole grains, legumes, nuts/seeds, vegetables, fruit, soy products), decreased intake of foods to limit (beef, pork, refined grains, desserts, fried foods, alcohol), and reported an increase in the overall amount of physical activity. Finally, participants must have reported an increase in total QOL score to meet the competency for improved QOL.
Data Collection and Statistical Analysis
Participants completed questionnaires to establish health metrics, lifestyle behaviors, and a QOL score at baseline and following completion of the program. These data were stored in Research Electronic Data Capture (REDCap). Data from participants who did not complete the program were not included in the outcomes analysis but were retained to discuss program attrition. Finally, participants who completed the program but with incomplete data points were excluded from the respective area of analysis.
Among those participants who completed the program, average pre- to post-health outcomes and QOL scores were compared using paired t-tests for correlated data. Because the cohorts experienced the program in three different formats (in-person, virtual, hybrid), the average pre- to post-program health outcomes and QOL scores were also evaluated with adjustment for cohort type using repeated measures analysis of covariance (RM-ANCOVA), with each model containing factors for time and cohort type. Average changes in health outcomes and QOL scores were compared between those who were adherent to the program and those who were non-adherent using Wilcoxon Rank Sum tests. Significance was defined as P < 0.05, and statistical analyses were performed using SAS statistical software version 9.4 (SAS Institute Inc., Cary NC).
Ethical Approvals
This project received expedited review and was exempt from informed consent by the Sarasota Memorial Health Care System’s Institutional Review Board.
Results
Participation
Sixteen cohorts of the RENEW Program at SMHCS were held between May 2018 and November 2023, serving a total of 432 participants. These participants were a combination of SMHCS employees, family members of SMHCS employees, and community members. Table 1 provides an overview of the demographics, participant type, and baseline diagnoses of all RENEW program participants during this 5-year time period.
The majority of the sample were female (85.4%), participants were on average 50.8 years of age (SD = 11.34 years), 78.2% of participants identified as White, while 8.6% identified as Hispanic/Latino and 8.3% identified as Black. Most participants were SMHCS employees (86.3%). The most common baseline health conditions reported by participants were having an elevated BMI (91.4%), a family history of heart disease (59.3%), hypertension (48.4%), and high cholesterol (38.4%). A history of smoking cigarettes was reported by 18.1% of participants, while 0.7% reported currently smoking.
The delivery of the RENEW Program was continuously adapted over this 5-year intervention period, as illustrated in Table 2. Cohorts 1-6 (n = 95) weekly coaching sessions and group lessons were conducted in person at the SMHCS main campus. In March 2020, the COVID-19 pandemic necessitated a switch to a fully virtual setting. Programming for cohorts 7-11 (n= 185) was conducted over the video communication software Zoom. Cohorts 12-16 (n = 152) transitioned to a semi-virtual setting. In this format, a handful of group lessons were held in person at the SMHCS fitness facility, HealthFit, and the rest took place virtually via Zoom.
Participants who did not continue with the program after the baseline meeting were excluded from the study outcomes. A total of 102 (23.6%) participants dropped from the program over the 5-year period and are excluded from the following analysis.
Health Metrics Outcomes
Combined cohort pre- and post-program health outcomes and QOL outcomes are shown in Table 3. Average body composition changes included weight loss of −8.5 lbs (SD = 7.54, P < 0.001), BMI change of −1.5 kg/m2 (SD = 1.61, P < 0.001), a reduction of −2.6 inches in waist circumference (SD = 2.31, P < 0.001) and −2.3 inches in hip circumference (SD = 2.21, P < 0.001). On average, there was minimal to no change in the waist-to-hip ratio (mean = −0.01, SD = 0.06, P = 0.013). Other changes in cardiovascular biomarkers included a mean reduction in systolic blood pressure and diastolic blood pressure of −6.1 mmHg (SD = 11.62, P < 0.001) and −4.7 mmHg (SD = 9.03, P < 0.001), respectively. A mean reduction in resting heart rate of −5.5 beats per minute (BPM) (SD = 8.54, P < 0.001) was also observed.
Quality of Life Outcomes
Participants reported improvements in overall QOL and subcategories with an 8.0% average increase for total QOL score (6.0 points, SD = 7.40, P < 0.001). Mean results for the subcategories included a 7.7% improvement (3 points, SD = 4.51, P < 0.001) in lifestyle satisfaction score, 13.3% improvement (0.4 points, SD = 0.77, P < 0.001) in perceived health status, 7.4% improvement (0.9 points, SD = 1.88, P < 0.001) in health-related limitations, and 7.5% improvement (1.6 points, SD = 3.22, P < 0.001) in stress management. An overview of these lifestyle outcomes is shown in Table 4.
Adjustment for Cohort Type
To examine how participant outcomes varied across the cohort types, these results were adjusted for the in-person, virtual, and hybrid formats. Table 5 illustrates the average health and QOL changes with 95% confidence intervals experienced by program participants, adjusted for cohort type. Conclusions were unchanged when adjusting for the different cohort types.
Outcomes and Program Adherence
For those participants where adherence was evaluated (n = 241), 80.1% met this competency measure. Those who achieved program adherence had significantly greater average weight loss (−8.4 (7.17) vs −5.7 (6.42), P = 0.041), greater average reduction in waist measurements (−2.8 (2.39) vs −1.7 (2.46), P = 0.023), and greater average reduction in hip measurement (−2.7 (2.31) vs −1.9 (1.84), P = 0.019). No significant differences were seen between adherent and non-adherent participants when it came to changes in blood pressure, resting heart rate, BMI, or QOL measures. These results are illustrated in Table 6.
Programmatic Competencies
As described in the methods section, programmatic competencies were created to be able to assess at a glance if participants met the expected outcomes categories of program adherence, improved health outcomes, improved lifestyle behaviors, and improved QOL. These results are shown in Table 7. These measures were completed for cohorts 8-16, therefore participants in earlier cohorts are not included in Table 7. 80.1% (n = 193) of participants who completed the program were considered adherent. 97.4% (n = 229) of participants experienced health improvements, 91.6% (n = 207) showed improvements in lifestyle behaviors, and 77.4% (n = 175) reported improvements in their overall QOL after completing the program.
Discussion
Summary of Outcomes
Study participants experienced improvements in both primary and secondary health outcomes. These improvements included significant reductions in weight, BMI, waist and hip circumferences, waist-to-hip ratio, systolic and diastolic blood pressure, and resting heart rate. These results align with those from on-site programs, as well as programs that took place in a rehabilitative settings.2,5 Cumulatively, these data indicate favorable changes to body composition and possible reductions in disease risk. 15 These favorable health outcomes were maintained when adjusting the results by the changes to cohort type, eg: in-person, virtual, and hybrid formats.
On average, participants reported a significant improvement in total QOL. This umbrella metric encompassed significant improvements in all sub-categories including a lifestyle satisfaction score, perceived health status rating, health-related limitations rating, and stress management score. Overall, participants reported increased lifestyle satisfaction and decreased stress. In addition, participants’ perceptions of both their health status and health-related limitations improved. These favorable QOL outcomes were maintained when adjusting the results by the changes to cohort type, eg: in-person, virtual, and hybrid formats.
Study Limitations
There are notable limitations to this study. Participants from cohorts 1-10 were SMHCS employees. The program extended to the greater community in cohorts 11-16, resulting in a larger percentage of employees participating (86.3%). Further, most participants identified as female (85.4%) and white (78.2%). Future studies should prioritize enrolling a more diverse sample of participants to improve the applicability of the program’s outcomes across various populations. Since participants had to apply to join the program, this suggests that the RENEW program participants may be more highly motivated individuals than the general population. Therefore, the program results may not be generalizable to less motivated populations that fall within the program’s eligibility criteria. Finally, to enroll in the program, participants needed access to a smartphone and moderate technology literacy, which could exclude individuals from lower socioeconomic backgrounds or those less familiar with technology.
This study could have been strengthened by adding a control group for comparison. Due to the retrospective nature of this study, this design was not feasible. However, the findings presented in Table 6 showed that adherent participants experienced greater improvements in mean weight loss and waist and hip circumferences when compared to non-adherent participants. These findings suggest that more engaged participation in the program led to more meaningful results in those two health categories.
The coaches worked with participants to apply nutrition, physical activity, and stress management practices addressed in the program curriculum. The majority of participants demonstrated improvements in their lifestyle behaviors. However, this data is based on self-reported questionnaires and is therefore inherently susceptible to inaccurate reporting. A more thorough evaluation of participant lifestyle behaviors, including nutrition, exercise, and sleep, will be part of a future project.
RENEW participants who chose to self-report laboratory measures included HbA1c, fasting glucose, LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides. While participants were encouraged to report labs, it was not a program requirement. Thus, there was insufficient data to include in this study. In future cohorts, it would be interesting to report on laboratory measures. However, the RENEW program in its current state is not equipped to draw labs nor does it have the capability to receive key clinical information such as diagnostic test results from providers of patient care or patient-authorized entities electronically.
Cohorts 1-6 were hosted in person, allowing for the program team to take both pre- and post-program health measurements for participants. Once the program transitioned to a virtual format, the participants became responsible for taking and submitting their own measurements. Due to the self-reported nature of some data, there is the potential for measurement error. To minimize this risk, the participants were provided video tutorials and handout instructions for how to measure waist and hip circumference. Participants were also given standardized measuring tapes to reduce the risk of measurement error. For greater consistency, participants were also encouraged to use the same scale and blood pressure cuff for pre- and post-program measurements of weight, blood pressure, and resting heart rate.
Modifications made to the RENEW Program structure and format over the 5-year period included in this analysis pose challenges to the present study’s internal validity and replicability. Such modifications include changes to program length, delivery (in-person, virtual, semi-virtual), and the format of weekly coaching sessions (individual vs small-group). There is a need to expand on the impact of these modifications in participant outcomes to better understand the potential efficacy of the RENEW Program. However, these adaptations reflect the real-world challenges faced by lifestyle medicine programs.2,7 These topics will be the focus of a future publication.
This study would be strengthened by the availability of long-term, follow-up data from participants. Collecting post-program data was a challenge, as some participants failed to complete the final questionnaires. Incomplete data points resulted in participant data being excluded from the analyses. Further, collecting more long-term, follow-up data proved to be a challenge. The program team attempted to collect data at 3 months, 6 months, and 1 year after program completion. Many people did not respond to email attempts to collect this data. This challenge appears to be common in lifestyle programs. More research is needed to establish successful methods for collecting follow-up data, so long-term results can appear in analyses.
Future Research Considerations
The RENEW program began as an on-site, 12-week program at SMHCS. However, the arrival of COVID-19 presented challenges to in-person meetings and forced the program to shift to a virtual format beginning in the Summer of 2020. This shift revealed a significant growth opportunity for the program. During this time, the program was able to reach more participants, provide greater flexibility for scheduling, and still maintain significant results in health, lifestyle, and QOL outcomes. Shortly thereafter, the program transitioned to a semi-virtual format consisting of small-group, virtual coaching sessions and some in-person group activities. This format shift was in response to participants expressing the desire for more in-person meetings. Another change in program structure was adjusting the length from 12 weeks to 10 weeks. Finally, in Spring 2023 the program switched from a free to paid model. This change applied to cohorts 14-16. A more in-depth analysis of the impact of changes to program length, delivery, and structure on participant outcomes will be the focus of a future study.
One significant feature of the RENEW program is the use of remote nutrition monitoring through a mobile meal logging application. Participants were able to record their meals in this application and receive daily meal feedback from registered dietitians to provide additional support in applying the nutrition guidelines. The use of such digital applications in lifestyle programs is a salient question in this technological era. 16 The impact of remote nutrition monitoring on participants’ outcomes is another topic that will be explored in future projects. Specifically, the authors would like to investigate whether participants who utilized the meal logging application more consistently experienced more desirable outcomes.
Attrition in both on-site and digital lifestyle programs is an important area of research for developing interventions. Participants dropping out of lifestyle medicine programs can pose challenges to intervention success and sustainability. Based on findings from recent publications, attrition rates for lifestyle interventions average around 40% in the first 12 months of participation.17,18 Over the RENEW program’s 16 cohorts, the attrition rate was 23.5%. Future projects will seek to elucidate the qualities of the program and participants that potentially contributed to this relatively low rate of attrition.
Study Conclusions
With chronic disease on the rise, it is urgent to reconsider traditional approaches to healthcare. Lifestyle medicine is a holistic healthcare model that can serve diverse populations, including those who are seeking to prevent chronic illness. As lifestyle medicine practices and initiatives continue to expand in traditional healthcare settings, questions around efficacy, scalability, and accessibility are important to consider. This project contributes to the existing literature evaluating how lifestyle medicine programs assist in chronic disease prevention. Specifically, this project demonstrates how a hybrid program, delivered by an interdisciplinary team and backed by a large healthcare system can scale over time and help reduce key risk factors related to metabolic dysfunction.
Acknowledgments
Jennifer Bonamer, PhD, RN, Nursing Professional Development – Research Specialist at SMHCS: We thank Jennifer for her invaluable guidance and support throughout the research process. Her expertise in research and publication was instrumental in preparing this study for publication. Katie West, MSN, RN, Research Development Program Coordinator at SMHCS: We appreciate the assistance of Katie from The Research Institute at SMHCS who provided invaluable guidance in shaping the direction of this study. Sarasota Memorial Health Care Foundation: The RENEW program was funded by a grant from the Sarasota Memorial Health Care Foundation through the Jane C. Ebbs Memorial Fund, grant number 1468. We are grateful for their financial support, which allowed this program to positively impact the lives of hundreds of employees and community members. We also express gratitude for the foundation’s financial support of this research project, grant number 0923-04, which allows us to share our findings with the community.
Appendix A. Tables.
Table 1.
Baseline Characteristics of RENEW Participants.
| Characteristic | Frequency (n) | Value |
|---|---|---|
| Mean age, years | 428 | 50.8 (11.34) |
| Sex | ||
| Female | 369 | 85.4% |
| Male | 63 | 14.6% |
| Race/Ethnicity | ||
| White | 338 | 78.2% |
| Hispanic/Latino | 37 | 8.6% |
| Black | 36 | 8.3% |
| Asian | 7 | 1.6% |
| American Indian | 1 | 0.2% |
| Native Hawaiian | 1 | 0.2% |
| More than 1 | 3 | 0.7% |
| Other | 9 | 2.1% |
| Participant type | ||
| SMHCS employee | 373 | 86.3% |
| Family member of SMHCS employee | 31 | 7.2% |
| Community member | 28 | 6.5% |
| Baseline health conditions | ||
| Family history of heart disease | 256 | 59.3% |
| Elevated BMI | 395 | 91.4% |
| Hypertension | 209 | 48.4% |
| High cholesterol | 166 | 38.4% |
| Prediabetes | 34 | 7.9% |
| Type 2 diabetes | 75 | 17.4% |
| Type 1 diabetes | 2 | 0.5% |
| Peripheral vascular disease | 5 | 1.2% |
| Cardiovascular disease | 0 | 0% |
| Sleep apnea | 52 | 12.0% |
| High triglycerides | 11 | 2.5% |
| History of transient ischemic attack | 3 | 0.7% |
| History of myocardial infarction | 10 | 2.3% |
| Smoking status | ||
| Past smoker | 78 | 18.1% |
| Current smoker | 3 | 0.7% |
Table 2.
Participation Overview by Cohort Type.
| Cohort type | Participants n (%) |
|---|---|
| In person | 95 (22.0%) |
| Virtual | 185 (42.8%) |
| Hybrid | 152 (35.2%) |
Table 3.
RENEW Participant Health Outcomes.
| Outcome | N | Pre-program (Mean, SD) | Post-program (Mean, SD) | Outcome change (post-pre): Mean (SD) | Paired t-test P-value |
|---|---|---|---|---|---|
| Weight (lbs) | 319 | 212.7 (52.98) | 204.2 (50.51) | −8.5 (7.54) | <0.001 |
| BMI (kg/m2) | 317 | 35.0 (8.01) | 33.5 (7.52) | −1.5 (1.61) | <0.001 |
| Waist (in) | 311 | 43.0 (8.57) | 40.4 (8.34) | −2.6 (2.31) | <0.001 |
| Hips (in) | 311 | 48.1 (8.25) | 45.7 (8.19) | −2.5 (2.21) | <0.001 |
| Waist-to-hip ratio | 308 | 0.9 (0.09) | 0.9 (0.09) | −0.01 (0.06) | 0.013 |
| Systolic (mmHg) | 292 | 128.2 (13.81) | 122.1 (11.46) | −6.1 (11.62) | <0.001 |
| Diastolic (mmHg) | 288 | 80.2 (9.81) | 75.5 (8.04) | −4.7 (9.03) | <0.001 |
| Resting heart rate (BPM) | 287 | 75.1 (11.10) | 69.6 (9.81) | −5.5 (8.54) | <0.001 |
Table 4.
RENEW Participant Quality of Life (QOL) Outcomes.
| Outcome | N | Pre-program (mean, SD) | Post-program (mean, SD) | Outcome change (post-pre): mean (SD) | Paired t-test P-value |
|---|---|---|---|---|---|
| Lifestyle satisfaction | 270 | 39.0 (5.45) | 42.0 (4.69) | 3.0 (4.51) | <0.001 |
| Perceived health status | 269 | 3.0 (0.82) | 3.4 (0.76) | 0.4 (0.77) | <0.001 |
| Health-related limitations | 269 | 12.1 (2.25) | 13.0 (1.85) | 0.9 (1.88) | <0.001 |
| Stress management | 270 | 21.2 (3.60) | 22.8 (3.18) | 1.6 (3.22) | <0.001 |
| Total QOL | 288 | 75.2 (9.47) | 81.2 (8.19) | 6.0 (7.40) | <0.001 |
aFor the health-related limitations measure, a higher rating correlates to fewer health-related limitations. Therefore, an increased score is desirable as it reflects that the participants perceived a reduction in health-related limitations.
Table 5.
Average Participant Outcomes Adjusted for Cohort Type: In-Person, Virtual, and Hybrid a .
| Outcome | Adjusted mean difference | 95% confidence interval | Adjusted P-value |
|---|---|---|---|
| Weight (lbs) | −8.5 | −9.29, −7.63 | <0.001 |
| BMI (kg/m2) | −1.5 | −1.63, −1.28 | <0.001 |
| Waist (in) | −2.6 | −2.85, −2.34 | <0.001 |
| Hips (in) | −2.5 | −2.70, −2.20 | <0.001 |
| Waist-to-hip ratio | −0.01 | −0.014, −0.002 | 0.013 |
| Systolic (mmHg) | −6.1 | −7.44, −4.77 | <0.001 |
| Diastolic (mmHg) | −4.7 | −5.73, −3.64 | <0.001 |
| Resting heart rate (BPM) | −5.5 | −6.52, −4.53 | <0.001 |
| Lifestyle satisfaction | 3.0 | 2.46, 3.54 | <0.001 |
| Perceived health status | 0.4 | 0.34, 0.53 | <0.001 |
| Health-related limitations | 0.9 | 0.68, 1.13 | <0.001 |
| Stress management | 1.6 (1.20, 1.97) | <0.001 | |
| Total QOL | 6.0 (5.11, 6.82) | <0.001 |
a“Cohort type” refers to the program format which included: in-person, virtual, or hybrid.
Table 6.
Participant Outcomes Based on Program Adherence.
| Outcome | Non-adherent participants (n = 48) mean (SD) | Adherent participants (n = 193) mean (SD) | Wilcoxon rank sum P-value a |
|---|---|---|---|
| Weight (lbs) | −5.7 (6.42) | −8.4 (7.17) | 0.041 |
| BMI (kg/m2) | −1.4 (2.92) | −1.4 (1.35) | 0.15 |
| Waist (in) | −1.7 (2.46) | −2.8 (2.39) | 0.023 |
| Hips (in) | −1.9 (1.84) | −2.7 (2.31) | 0.019 |
| Waist-to-hip ratio | 0.0 (0.05) | −0.0 (0.05) | 0.24 |
| Systolic (mmHg) | −5.4 (13.07) | −5.4 (10.72) | 0.98 |
| Diastolic (mmHg) | −4.2 (9.44) | −4.0 (8.64) | 0.84 |
| Resting heart rate (BPM) | −4.4 (11.19) | −5.4 (8.62) | 0.48 |
| Lifestyle satisfaction | 3.4 (3.62) | 3.0 (4.47) | 0.47 |
| Perceived health status | 0.2 (0.79) | 0.4 (0.73) | 0.24 |
| Health-related limitations | 0.3 (1.64) | 0.8 (1.93) | 0.08 |
| Stress management | 0.7 (2.07) | 1.6 (3.28) | 0.09 |
| Total QOL | 5.0 (5.14) | 6.0 (7.26) | 0.60 |
aWilcoxon rank sum P-value.
Table 7.
Programmatic Competencies.
| Competency measures | N a | Met competency n (%) | Did not meet competency n (%) |
|---|---|---|---|
| Programmatic adherence | 241 | 193 (80.1%) | 48 (19.9%) |
| Improved health status | 235 | 229 (97.4%) | 6 (2.6%) |
| Improved lifestyle behaviors | 226 | 207 (91.6%) | 19 (8.4%) |
| Improved QOL | 226 | 175 (77.4%) | 51 (22.6%) |
aThe programmatic competencies were only measured for those participants who completed the program. Dropped participants were excluded from the competencies. In addition, any missing data points are not included in this table.
Footnotes
Author Contributions: Kirk Voelker, MD: Study design, research team and writing support
Chippy Ajithan, MD: Study design, research team and writing support
Jordan Colbert, MPH, RDN: Principal Investigator
Mikka Ipri, RDN: Sub Investigator
Lauren Pullman, MS: Research team and writing support
Tonya King, PhD: Biostatistician and writing support.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the Sarasota Memorial Health Care System Healthcare Foundation, grant number 0923-04. The authors also disclose receipt of the following financial support for the research: a discounted enrollment fee and data retrieval assistance from Wellness Foundry.
Ethical Statement
Ethical Considerations
This project received expedited review and was exempt from informed consent by the Sarasota Memorial Health Care System’s Institutional Review Board.
Consent to Participate
For the purposes of this project, informed consent has been waived by the Institutional Review Board.
ORCID iDs
Jordan Colbert https://orcid.org/0009-0001-3180-8729
Kirk Voelker https://orcid.org/0009-0001-0421-2815
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request due to the privacy of our participants.*
References
- 1.American College of Lifestyle Medicine . PortalLifestyleMedicine. https://portal.lifestylemedicine.org/Portal/ACLM/About/What_is_Lifestyle_Medicine_/Lifestyle_Medicine.aspx. Accessed August 29, 2024.
- 2.Albert SL, Massar RE, Kwok L, et al. Pilot plant-based lifestyle medicine program in an urban public healthcare system: evaluating demand and implementation. Am J Lifestyle Med. 2024;18:155982762211135. doi: 10.1177/15598276221113507. Published online July 12, 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Kelly J, Karlsen M, Steinke G. Type 2 diabetes remission and lifestyle medicine: a position statement from the American college of lifestyle medicine. Am J Lifestyle Med. 2020;14(4):406-419. doi: 10.1177/1559827620930962 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Krauss J, Frates E, Parekh M, Chan J, Kiratli BJ, Myers J. Comprehensive lifestyle medicine program improves fitness, function, and blood pressure in poststroke veteran cohort: a pilot study. Am J Lifestyle Med. 2021;16(6):765-771. doi: 10.1177/1559827620988659 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ornish D, Scherwitz LW, Billings JH, et al. Intensive lifestyle changes for reversal of coronary heart disease. JAMA. 1998;280(23):2001-2007. doi: 10.1001/jama.280.23.2001 [DOI] [PubMed] [Google Scholar]
- 6.American College of Lifestyle Medicine Health Systems Council . LifestyleMedicine. https://lifestylemedicine.org/health-systems-council/. Accessed August 29, 2024.
- 7.Mauriello L, Artz K. Digital lifestyle medicine: Designing, delivering, and scaling for impact. Am J Lifestyle Med. 2021;17(1):93-96. doi: 10.1177/15598276211029219 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Conn S, Curtain S. Health coaching as a lifestyle medicine process in primary care. Aust J Gen Pract. 2019;48(10):677-680. doi: 10.31128/ajgp-07-19-4984 [DOI] [PubMed] [Google Scholar]
- 9.Smart Goals: A How to Guide. University of California. 2016. https://www.ucop.edu/local-human-resources/_files/performance-appraisal/How_to_write_SMART-Goals_v2.pdf. Accessed August 29, 2024. [Google Scholar]
- 10.American heart association recommendations for physical activity in adults and kids. Heart. https://www.heart.org/en/healthy-living/fitness/fitness-basics/aha-recs-for-physical-activity-in-adults. Accessed August 29, 2024.
- 11.Seligman MEP. Flourish: A Visionary New Understanding of Happiness and well-being. Simon & Schuster; 2011. [Google Scholar]
- 12.Lara‐Breitinger KM, Medina IJR, Li Z, et al. Validation of a brief dietary questionnaire for use in clinical practice: mini‐eat (eating assessment tool). J Am Heart Assoc. 2023;12(1). doi: 10.1161/jaha.121.025064 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Craig CL, Marshall AL, Sjöström M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381-1395. doi: 10.1249/01.MSS.0000078924.61453.FB [DOI] [PubMed] [Google Scholar]
- 14.The WHOQOL Group . Development of the world health organization WHOQOL-BREF quality of life assessment. Psychol Med. 1998;28(3):551-558. doi: 10.1017/S0033291798006667 [DOI] [PubMed] [Google Scholar]
- 15.Ross R, Neeland IJ, Yamashita S, et al. Waist circumference as a vital sign in clinical practice: a consensus statement from the IAS and ICCR working group on visceral obesity. Nat Rev Endocrinol. 2020;16(3):177-189. doi: 10.1038/s41574-019-0310-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sequi-Dominguez I, Alvarez-Bueno C, Martinez-Vizcaino V, Fernandez-Rodriguez R, Del Saz Lara A, Cavero-Redondo I. Effectiveness of mobile health interventions promoting physical activity and lifestyle interventions to reduce cardiovascular risk among individuals with metabolic syndrome: systematic review and meta-analysis. J Med Internet Res. 2020;22(8):e17790. doi: 10.2196/17790 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Meyerowitz-Katz G, Ravi S, Arnolda L, Feng X, Maberly G, Astell-Burt T. Rates of attrition and dropout in app-based interventions for chronic disease: systematic review and meta-analysis. J Med Internet Res. 2020;22(9):e20283. doi: 10.2196/20283 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Colombo O, Ferretti VVV, Ferraris C, et al. Is drop-out from obesity treatment a predictable and preventable event? Nutr J. 2014;13(1):13. doi: 10.1186/1475-2891-13-13 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request due to the privacy of our participants.*