Tailoring Mobile Health Technology to Reduce Obesity and Improve Cardiovascular Health in Resource-Limited Neighborhood Environments: A Multi-Level, Community-Based Physical Activity Intervention
Tailoring Mobile Health Technology to Reduce Obesity and Improve Cardiovascular Health in Resource-Limited Neighborhood Environments: A Multi-Level, Community-Based Physical Activity Intervention
Background:
Heart disease is a leading cause of death. People can reduce their heart disease risk by exercising more. Mobile health technology may make people more successful at increasing their exercise. This includes things like physical activity monitors and smartphone apps.
Objective:
To find out if mobile health technology can increase physical activity.
Eligibility:
African American women ages 21-75 who:
Design:
At visit 1, participants will
For 2 weeks, researchers will collect data about participants physical activity.
Then participants will have a study visit with additional blood tests.
All participants will get messages from the app that encourage exercise.
Some participants will get data from the app about exercise near their home or work.
Some participants may get face-to-face coaching.
Participants may get wireless devices. These measure body weight, blood pressure, and blood glucose. Participants can measure these at home and upload the data to the app for the study.
Participants will have visits after 3 and 6 months. They will repeat the visit 1 tests.
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.
Individuals eligible for this protocol have overweight or obesity (BMI >= 25 kg/m^2) African American women aged 21-75 years who live in Washington, DC Wards 5,7, or 8 and neighboring areas of Prince George s County, MD. Eligible participants should also have access to a smartphone compatible with the mobile app for the protocol that they can use for the study. Eligible participants must be able to provide informed consent independently and also speak and read English at the 8th grade level.
EXCLUSION CRITERIA:
Pilot Study INCLUSION CRITERIA:
Eligibility for Post-Menopausal Status for Sleep Sub-study:
Eligibility is limited to post-menopausal women who have either completed or are currently enrolled in the main study. Confirmation of post-menopausal status will be determined by review of medical history prior to final eligibility assessment for the study. In patients with prior hysterectomy and retained ovaries, menopause cannot be diagnosed using menstrual criteria. Diagnosis will be made clinically based on age consistent with natural menopause ( >=45) and the presence of menopausal symptoms, such as vasomotor or genitourinary symptoms.
In addition to the Step it Up Study fs exclusion criteria, during the screening visit, which can happen by telephone or telehealth, participants will be asked for certain conditions such as bilateral arm deformity, significant peripheral vascular disease, lymphedema, an arteriovenous (AV) fistula or graft in the monitoring arm, severe skin conditions or wounds at the cuff site, inability to tolerate cuff inflation, severe blood disorder or coagulopathy, and any other condition deemed unsafe at the discretion of the principal investigator.
Additionally, participants will not be eligible for the optional Sleep Sub-study if:
Optional MRI Tests
Subjects will be screened for implanted metal objects or devices that may be incompatible with MRI (i.e. cerebral aneurysm clip, cochlear implant, pacemaker, etc.) These subjects will be eligible to proceed with study enrollment but will not undergo the optional MRI study.
marie.marah@nih.gov(301) 640-1701
powelltm2@mail.nih.govNot Listed