Blood Pressure, Diet, Healthy, Physical Activity, Sleep Health, Weight Loss
Conditions
Brief summary
Improving multiple domains of cardiometabolic health (CMH) through contextual behavioral interventions has the potential to substantially reduce persistent chronic disease disparities. Sleep is critical for preserving CMH and is amenable to intervention in real-world settings. Although sleep health, in conjunction with other lifestyle behaviors, can improve CMH through complementary or synergistic pathways, most existing lifestyle change programs focus solely on diet and physical activity. Sleep2BWell is a community-based cluster randomized trial aimed at evaluating the impact of incorporating a multidimensional sleep health intervention into the BWell4Life program, an ongoing 4-week program for promoting CMH through healthy diet and physical activity, delivered by peer health educators at faith-based organizations and community centers in underserved NYC neighborhoods. The enhanced 6-week intervention, Sleep2BWell, will include the following additional components: 1) two sleep health education and group coaching sessions, 2) self-monitoring and motivational enhancement using a Fitbit, and 3) addressing prevalent environmental barriers to healthy sleep in urban settings such as noise and light with a novel and timely extension to address indoor air pollution. A total of 10 community sites will receive the intervention enrolling an average of 15 participants per site for an expected sample of 150. The investigators will collect objective measures of sleep and physical activity throughout the study, and assess diet and CMH outcomes at baseline and 10 weeks (primary endpoint). The investigators hypothesize that Sleep2BWell will improve CMH, including reduced blood pressure (primary outcome) improved health behaviors (sleep, diet, physical activity) and adiposity markers (secondary outcomes). To ensure the successful completion and future expansion of this work, this study will use mixed methods to understand implementation determinants and outcomes, guided by implementation science frameworks. This first-of-its-kind effectiveness-implementation study, addressing individual level behaviors and factors and upstream influences and leveraging key behavior change and community engagement strategies, will investigate the integration of sleep health into a multi-behavior lifestyle change intervention aimed at addressing CMH disparities in community settings. This innovative multilevel intervention will inform scalable sustainable community health approaches and public health policy to improve sleep health and CMH disparities through advancement in novel multilevel bundled behavioral interventions.
Interventions
BEHAVIORALMultidimensional Sleep Health Sessions
The two sleep health educational sessions will include didactic content on defining sleep health, reviewing sleep recommendations, outlining the role of sleep in preserving cardiometabolic health, and correcting unhelpful sleep-related beliefs and debunking myths. Participants will learn to maximize the benefits of self-monitoring using a Fitbit and will receive a sleep mask, ear plugs, a blue light blocker, and an indoor air purifier to improve their sleep environment.
BEHAVIORALHealthy Diet Sessions
The two diet sessions include an overview of nutrition basics, examples of healthy dietary patterns and cooking methods to increase consumption of plant-based foods such as fruits, vegetables, and whole grains, promote choosing more lean proteins such as fish, and reduce intakes of red and processed meats, sugary foods, and sugar-sweetened beverages.
BEHAVIORALPhysical Activity Sessions
The two physical activity sessions provide an overview of the physical activity guidelines and include 30-60 minutes of exercise and a healthy living community resource mapping exercise. These sessions also address achieving and maintaining a healthy body weight.
Sponsors
Columbia University
Weill Medical College of Cornell University
National Institute on Minority Health and Health Disparities (NIMHD)
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
20 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. English- and/or Spanish-speaking 2. aged ≥20 years 3. having at minimum SBP in the elevated or hypertension category (i.e., SBP ≥120 mmHg)
Exclusion criteria
1. No known medical conditions that would prevent them from safely participating in the trial (e.g., neurological degenerative disease such as Parkinsons, severe psychiatric disorders, substance use disorder) 2. History of cardiovascular disease or cancer 3. Pregnant or desire to become pregnant during the study 4. Less than one year postpartum
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in systolic blood pressure | baseline to 10 weeks | The change systolic blood pressure (mmHg) from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in diastolic blood pressure | baseline, 10 weeks | The change diastolic blood pressure (mmHg) from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in sleep health | baseline, 10 weeks | Sleep health will be assessed using sleep duration, regularity, efficiency, and timing from the Fitbit and self-reported sleep satisfaction and alertness (measured by daytime sleepiness). Optimal sleep health will be defined as having an average sleep duration (hours/night) ≥7 hours and \<9 hours, regular sleep duration and timing (standard deviation of sleep duration and timing variables \<90 minutes), sleep efficiency (%) ≥85%, an earlier sleep period (sleep midpoint earlier than 4:00 AM), normal daytime sleepiness (Epworth Sleepiness Scale ≤10), and good self-rated sleep satisfaction and quality. Sleep health will be assessed at baseline and 10 weeks. Changes in sleep health from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in sleep duration | baseline, 10 weeks | Sleep duration (hours) will be assessed at baseline and 10 weeks. Changes in sleep duration from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in sleep efficiency | baseline, 10 weeks | Sleep efficiency (%) will be assessed at baseline and 10 weeks. Changes in sleep efficiency from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in sleep regularity | baseline, 10 weeks | Sleep regularity will be assessed from the standard deviation of sleep duration and timing at baseline and 10 weeks. Changes in sleep regularity from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in sleep quality | baseline, 10 weeks | Sleep quality will be assessed using the Pittsburgh Sleep Quality Index (score range: 0-21) at baseline and 10 weeks. Changes in sleep quality from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in alertness | baseline, 10 weeks | Alertness will be captured by measuring excessive daytime sleepiness using the Epworth Sleepiness Scale (range: 0-24) at baseline and 10 weeks. Changes in daytime sleepiness from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in diet quality | baseline, 10 weeks | The change in the Mediterranean Eating Pattern for Americans (MEPA) score (range: 0-16 with higher scores indicating more favorable diet quality) from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in physical activity | baseline, 10 weeks | The change in minutes/week spent in moderate-to-vigorous intensity and light intensity physical activity from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in body weight | baseline, 10 weeks | The change in body weight (in lbs) from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in waist circumference | baseline, 10 weeks | The change in waist circumference (inches) from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Change in percent body fat | baseline, 10 weeks | The change in % body fat from baseline to follow-up at 10 weeks will be calculated and compared across randomization arms. |
| Acceptability of Implementation | 10 weeks | Acceptability will be measured by questionnaire. Items are adapted from the validated Acceptability of Implementation Measure (AIM) and are rated on a 5-point Likert scale ranging from 1 to 5, with 1 indicating "Completely disagree" and 5 indicating "Completely agree." Higher scores indicate better intervention acceptability. The items are analyzed individually and not summed to a total score. |
| Feasibility of Implementation | 10 weeks | Feasibility will be measured by questionnaire using items adapted from the validated Feasibility of Implementation Measure (FIM) and rated on a 5-point Likert scale ranging from 1 to 5, with 1 indicating "Completely disagree" and 5 indicating "Completely agree." Higher scores indicate better feasibility. The items are analyzed individually and not summed to a total score. |
| Appropriateness of Implementation | 10 weeks | Appropriateness will be measured by questionnaire. Items are adapted from the validated Implementation Appropriateness Measure (IAM) and are rated on a 5-point Likert scale ranging from 1 to 5, with 1 indicating "Completely disagree" and 5 indicating "Completely agree." Higher scores indicate better appropriateness. The items are analyzed individually and not summed to a total score. |
| Satisfaction with Intervention | 10 weeks | Net promoter score (score range: 1-10) and Program Quality Rating on Likert Scale (Excellent, Very Good, Good, Fair, Poor) |
Countries
United States
Contacts
CONTACTResearch Project Coordinator
PRINCIPAL_INVESTIGATORNour Makarem, PhD, FAHA
Columbia University
Outcome results
None listed