Background Obesity and physical inactivity contribute substantially to cardiovascular disease risk, diabetes, hypertension, and dyslipidemia. African American women experience disproportionately high rates of obesity and have among the lowest levels of physical activity and greatest sedentary time in the United States. Resource-limited neighborhoods may further constrain physical activity through limited access to safe parks, recreation facilities, walking routes, and other health-promoting resources. This protocol builds on prior community-based work in Washington, D.C., which demonstrated the feasibility of wearable activity monitoring among predominantly African American women in faith-based, lower-resource communities. It uses community-based participatory research principles and mobile health technology to deliver physical-activity coaching tailored either to individual factors or to available neighborhood resources. Objectives Primary objective To determine whether initiating an adaptive physical-activity intervention with remote, mobile-app coaching tailored to neighborhood physical-activity resources "tailored-to-place" coaching-produces a greater increase in steps per day over approximately three months than standard remote coaching. Secondary objectives The study will also: Compare four embedded adaptive intervention strategies over approximately six months. Assess the feasibility of remotely measuring weight, blood pressure, and blood glucose using connected devices. Evaluate effects on cardiometabolic measures, including BMI, blood pressure, lipids, glucose, dietary intake, self-reported physical activity, and smoking. Examine inflammatory, lipid, immunometabolic, psychosocial, behavioral, and social-determinants-of-health pathways related to physical-activity change. Evaluate changes in cardiac structure and function and body composition using optional cardiovascular and body-composition MRI. Assess relationships among sleep, ambulatory blood pressure, menopause-related factors, and immunometabolic markers in a postmenopausal sleep sub-study. Conduct user-centered testing of the mobile application and wearable/mobile health technologies. Explore COVID-19 exposure and pandemic-related psychosocial stress as potential confounders of immunologic and psychosocial outcomes. Eligibility: Inclusion Criteria Participants must: Be African American women aged 21-75 years. Have overweight or obesity, defined as BMI \>=25 kg/m\^2 Live in Washington, D.C., Wards 5, 7, or 8, or in neighboring areas of Prince George's County, Maryland. Have access to a smartphone compatible with the study application. Be able to provide informed consent independently. Speak and read English at approximately an eighth-grade level. Participants enter a two-week run-in period. Those averaging 7,500 steps per day or fewer and who complete the run-in are eligible for randomization into the intervention. Main study exclusion criteria Potential participants are excluded for conditions that could make increased physical activity unsafe or interfere with study assessments, including: Medical conditions or physical limitations that prohibit safe participation in physical activity. Recent myocardial infarction, documented obstructive coronary artery disease, recent coronary stenting, or significant decompensated structural heart disease. Pregnancy; pregnancy status is assessed as applicable during study visits. Other conditions determined by the investigator to make participation unsafe. Sleep sub-study eligibility The optional sleep sub-study is limited to postmenopausal women who are enrolled in or have completed the main study. Additional exclusions include night-shift work, conditions that interfere with overnight polysomnography, recent initiation of sleep-modifying medications, inability to tolerate ambulatory blood-pressure monitoring, and certain arm, vascular, skin, bleeding, or neurologic conditions. MRI participation is optional and requires separate screening for MRI-incompatible implanted devices or metal and, when applicable, eligibility for gadolinium contrast. Study design A six-month adaptive randomized trial will enroll overweight or obese African American women. After a two-week run-in, participants averaging \<=7,500 steps/day will receive either standard mobile-app coaching or coaching tailored to neighborhood physical-activity resources. At three months, nonresponders will be reassigned to intensified coaching. Steps will be measured with a wearable device, with assessments at baseline, three months, and six months. Optional monitoring and MRI/sleep sub-studies will assess cardiometabolic outcomes.
Targeted, effective behavioral interventions are critically needed to ameliorate the disproportionate prevalence of poor cardiometabolic health for African-American women. We propose a sequential, multiple-assignment, randomized trial targeting physical activity (PA) among at-risk African American women in resource-limited, Washington, D.C. communities using mobile health (mHealth) technology. We hypothesize that by beginning a community-based, adaptive PA intervention with remote coaching tailored to neighborhood environment PA resources, we will see greater increases in PA levels as compared to standard remote coaching. In Aim 1, we will determine if beginning an adaptive intervention with remote coaching tailored to neighborhood environment resources and delivered using mHealth technology (wearables and mobile applications) will lead to a greater PA increase (as measured by steps per day) as compared to standard remote coaching. In Aim 2, we will examine which of four embedded adaptive interventions produce the largest PA increase over the six-month study period. In Aim 3, we will evaluate the feasibility of remote capture of cardiometabolic measures, including blood pressure, weight, and glucose, using mHealth technology. We will also examine intervention effects on cardiometabolic health (adiposity, blood pressure, fasting lipids/glucose, self-reported PA, dietary intake, cigarette smoking). In Aim 4a, we will characterize effects of increasing PA on integrated serologic cytokine/chemokine and lipid inflammatory intermediates to identify potential novel inflammatory pathways linked to cardiometabolic risk phenotypes most responsive to the multi-level, community-based PA intervention. In Aim 4b, we examine the feasibility of measuring potential psychosocial and behavioral mediators of the relationship between PA change and CV health. In Aim 5, we will conduct iterative testing of the mobile health technology used in the protocol with a user-centered design approach. In Aim 6a and 6b, we will assess for changes in cardiac structure and function as well as body composition using MRI before and after the intervention. In Aim 7a and 7b, the intersection of common biological signatures of menopause, sleep disruption, and blood pressure as a marker of cardiometabolic risk in the setting of adverse social determinants of health will be investigated in the study population. We will also determine the feasibility of measuring behavioral and psychosocial mediating factors of the relationship between PA change and cardiometabolic health in this intervention, including chronic psychological/environmental stress and sedentary behavior/sleep. Also, since PA has the potential to improve sleep, vascular function, autonomic regulation, and inflammatory status, incorporating the sleep study and ambulatory blood pressure monitoring (ABPM) further provides more insights on how the behavioral changes from the Step-it-Up intervention translate into clinically meaningful physiological improvements in this population. In addition, because of the COVID-19 pandemic in 2020, we will measure exposure to COVID-19 and psychosocial stress caused by the pandemic as potential confounders of immunologic outcomes and psychosocial stressors in this study. Finally, we will explore the relationships between PA, social determinants of health, and biological markers in this intervention cohort and compare them to other populations using available cohort data. This project provides fundamental knowledge towards the development of tailored, effective behavioral interventions incorporating mHealth technology to promote health among populations most impacted by health disparities.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
SINGLE
Enrollment
325
Image reconstruction software
radiofrequency coils
pulse sequences
Image Reconstruction and Analysis Software
Bluetooth-enabled glucometer
Provides SRC components plus recommendations based on physical-activity resources near the participant s home, work, or church. Messages may recommend parks, recreation centers, exercise classes, trails, greenspaces, or walking routes within an approximately 0.75-mile radius.
Provides individual-level physical-activity coaching based on goal setting, self-efficacy, barriers, personal preferences, and step data. Educational content is adapted from the Diabetes Prevention Program. Messaging encourages progression toward 10,000 steps/day.
Participants self-monitor activity during an approximately 2-week run-in period without receiving intervention messaging. Participants averaging 7,500 steps/day proceed to randomization.
Measures systolic and diastolic blood pressure and pulse over approximately 48 hours during usual daily activities.
Overnight monitoring using EEG, EOG, EMG, ECG, respiratory airflow and effort, oxygen saturation, body position, snoring, and leg-movement sensors to characterize sleep, including slow-wave sleep.
National Institutes of Health Clinical Center
Bethesda, Maryland, United States
RECRUITINGChange in physical activity, measured as average steps per day
Compare the change in objectively measured daily step counts between participants initially assigned to remote coaching tailored to neighborhood physical-activity resources (tailored-to-place coaching) and those assigned to standard remote coaching. Steps are captured by a wrist-worn physical-activity monitor and summarized as average steps per day. The protocol's primary treatment effect is based on the average weekly step counts during the final four weeks of the six-month intervention, approximately weeks 21-24 for the longer-term adaptive intervention analysis.
Time frame: Baseline/run-in through approximately 3 months after randomization
Cardiac structure, function, and perfusion
Assess changes in biventricular and left-ventricular structure and function, myocardial characteristics, and vasodilator stress perfusion using cardiovascular magnetic resonance in an optional subset.
Time frame: Optional CMR during the run-in/baseline period and again within the month-6 visit window
Mobile-health technology feasibility and acceptability
Evaluate usability, acceptability, functionality, engagement, message delivery, app use, wearable-device adherence, and completion of ecological momentary assessments and educational modules.
Time frame: Pilot period of approximately 23 days; intervention period up to approximately 6.5 months
Psychosocial and behavioral mediators
Assess chronic psychological and environmental stress, social support and isolation, perceived discrimination, neighborhood environment, sedentary behavior, sleep quality and duration, and other factors that may mediate or modify the relationship between physical activity and cardiovascular health.
Time frame: Baseline, approximately 3 months, and approximately 6 months
Inflammatory and immunometabolic biomarkers
Characterize changes associated with increasing physical activity in cytokines, chemokines, lipid inflammatory intermediates, vascular/endothelial markers, immune-cell measures, and related inflammatory pathways.
Time frame: Baseline, approximately 3 months, and approximately 6 months
Cardiometabolic health factors
Evaluate changes in BMI, weight, waist and hip circumference, blood pressure, fasting lipids, fasting glucose, hemoglobin A1c, insulin-resistance markers, dietary intake/DASH adherence, self-reported moderate-to-vigorous physical activity, and cigarette smoking.
Time frame: Baseline, approximately 3 months, and approximately 6 months
Feasibility of remote cardiometabolic monitoring
Assess participant use and data capture from wireless devices for blood pressure, weight/body fat percentage, and blood glucose. Feasibility measures include device use, data upload, and completeness of measurements.
Time frame: During the intervention, up to approximately 6 months
Physical activity response across adaptive interventions
Compare change in objectively measured steps per day across the four embedded adaptive intervention strategies, including continued coaching, tailored-to-place coaching, increased messaging, and virtual or face-to-face coaching.
Time frame: Baseline/run-in, approximately 3 months, and approximately 6 months
Body composition
Assess changes in visceral and subcutaneous adipose tissue, liver fat, intramuscular fat, muscle volume, and related body-composition measures using noncontrast MRI.
Time frame: Optional MRI at baseline or within the first month and again before or after the month-6 visit
Sleep and ambulatory blood pressure
Examine relationships between sleep quality, sleep architecture particularly slow-wave sleep-and ambulatory systolic and diastolic blood pressure among postmenopausal participants.
Time frame: Sleep sub-study: 48-hour ABPM and overnight polysomnography after enrollment or study completion
Immunometabolic mediation of sleep blood-pressure relationships
Determine whether cortisol, immune-cell function, and other immunometabolic markers mediate the association between sleep parameters and ambulatory blood pressure.
Time frame: Sleep sub-study visits, generally around the ABPM and polysomnography assessments
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