Tailoring Mobile Health Technology to Reduce Obesity and Improve Cardiovascular Health in Resource-Limited Neighborhood Environments

NCT ID: NCT03288207

Last Updated: 2025-12-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

325 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-06-21

Study Completion Date

2026-03-28

Brief Summary

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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:

* Are overweight or obese
* Live in certain areas near Washington, DC
* Have a smartphone that can use the study app

Design:

At visit 1, participants will

* Answer survey questions. These may be about medical history, physical activity, and weight. They may also cover body image, health perception, and spirituality.
* Have body size measured and get blood tests
* Get a device to wear on the wrist. It will record physical activity and hours of sleep.
* Learn how to download and use the study mobile app

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.

Detailed Description

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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. 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. 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.

Conditions

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Obesity

Keywords

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Community-Based Participatory Research Obesity Cardiovascular Disease Risk Social Determinants of Health

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

SEQUENTIAL

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

SINGLE

Participants

Study Groups

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Group 2 Label: PA monitor with standard remote coaching (SRC)

African American women who are at risk for cardiovascular outcomes in resource-limited communities in the Washington D.C. area.

Group Type OTHER

Step it Up mobile app

Intervention Type DEVICE

Step it Up mobile app

Global Positioning System (GPS) Device

Intervention Type DEVICE

Global Positioning System (GPS) Device

Bluetooth-enabled scale

Intervention Type DEVICE

Bluetooth-enabled scale

Bluetooth-enabled glucometer

Intervention Type DEVICE

Bluetooth-enabled glucometer

MRI: Image Reconstruction and Analysis Software (Device Manufacturer: NIH)

Intervention Type DEVICE

Image Reconstruction and Analysis Software

MRI: Research pulse sequences (Device Manufacturer: NIH)

Intervention Type DEVICE

pulse sequences

MRI: radiofrequency coils (Device Manufacturer: Siemens Medical Solutions USA, Inc.)

Intervention Type DEVICE

radiofrequency coils

AMRA Researcher Image reconstruction software

Intervention Type DEVICE

Image reconstruction software

Group 1 Label: PA monitor with remote coaching tailored to place

African American women who are at risk for cardiovascular outcomes in resource-limited communities in the Washington D.C. area.

Group Type OTHER

Step it Up mobile app

Intervention Type DEVICE

Step it Up mobile app

Global Positioning System (GPS) Device

Intervention Type DEVICE

Global Positioning System (GPS) Device

Bluetooth-enabled scale

Intervention Type DEVICE

Bluetooth-enabled scale

Bluetooth-enabled glucometer

Intervention Type DEVICE

Bluetooth-enabled glucometer

MRI: Image Reconstruction and Analysis Software (Device Manufacturer: NIH)

Intervention Type DEVICE

Image Reconstruction and Analysis Software

MRI: Research pulse sequences (Device Manufacturer: NIH)

Intervention Type DEVICE

pulse sequences

MRI: radiofrequency coils (Device Manufacturer: Siemens Medical Solutions USA, Inc.)

Intervention Type DEVICE

radiofrequency coils

AMRA Researcher Image reconstruction software

Intervention Type DEVICE

Image reconstruction software

Interventions

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Step it Up mobile app

Step it Up mobile app

Intervention Type DEVICE

Global Positioning System (GPS) Device

Global Positioning System (GPS) Device

Intervention Type DEVICE

Bluetooth-enabled scale

Bluetooth-enabled scale

Intervention Type DEVICE

Bluetooth-enabled glucometer

Bluetooth-enabled glucometer

Intervention Type DEVICE

MRI: Image Reconstruction and Analysis Software (Device Manufacturer: NIH)

Image Reconstruction and Analysis Software

Intervention Type DEVICE

MRI: Research pulse sequences (Device Manufacturer: NIH)

pulse sequences

Intervention Type DEVICE

MRI: radiofrequency coils (Device Manufacturer: Siemens Medical Solutions USA, Inc.)

radiofrequency coils

Intervention Type DEVICE

AMRA Researcher Image reconstruction software

Image reconstruction software

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

Individuals eligible for this protocol are overweight or obese (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.


* Must be an African-American female
* Must be within the age of 21-75 years old
* Must be overweight or obese (Body Mass Index (BMI) \>= 25 kg/m\^2)
* Must live in Washington DC Wards (5, 7, or 8) or live in Prince George s County, Maryland
* Must have a smartphone that is compatible with the study software (mobile app)
* Must be willing to use the software on personal smartphone for the study
* Must be able to provide consent
* Must be willing to wear the wrist-worn physical activity device for the study
* Must not be pregnant

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.

Exclusion Criteria

* Medical condition, including heart failure, recent unintentional weight loss or physical limitation, that might prohibit safe participation in physical activity for any reason
* Heart disease as indicated by history of myocardial infarction in past 1 year, documented obstructive coronary artery disease on coronary angiography, coronary artery stent placement, within the last year significant structural heart disease (e.g. hypertrophic or dilated cardiomyopathy with EF \<35%, severe valvular heart disease) with evidence of decompensation.
* Pregnant women due to large hormonal changes during pregnancy that affect study variables and potential pregnancy-related restrictions on exercise. All participants of childbearing potential will need to self-report a negative pregnancy at the screening visit, baseline visit, and at the three-month and six-month visits, unless the participant self-reports being postmenopausal, having had a tubal ligation, or having undergone a complete hysterectomy.
Minimum Eligible Age

21 Years

Maximum Eligible Age

75 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Sponsors

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George Washington University

OTHER

Sponsor Role collaborator

National Heart, Lung, and Blood Institute (NHLBI)

NIH

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Tiffany M Powell-Wiley, M.D.

Role: PRINCIPAL_INVESTIGATOR

National Heart, Lung, and Blood Institute (NHLBI)

Locations

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National Institutes of Health Clinical Center

Bethesda, Maryland, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Marie Marah, R.N.

Role: CONTACT

Phone: (301) 640-1701

Email: [email protected]

Tiffany M Powell-Wiley, M.D.

Role: CONTACT

Phone: (301) 594-3735

Email: [email protected]

Facility Contacts

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For more information at the NIH Clinical Center contact Office of Patient Recruitment (OPR)

Role: primary

References

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Boggs DA, Rosenberg L, Cozier YC, Wise LA, Coogan PF, Ruiz-Narvaez EA, Palmer JR. General and abdominal obesity and risk of death among black women. N Engl J Med. 2011 Sep 8;365(10):901-8. doi: 10.1056/NEJMoa1104119.

Reference Type BACKGROUND
PMID: 21899451 (View on PubMed)

Writing Group Members; Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, Das SR, de Ferranti S, Despres JP, Fullerton HJ, Howard VJ, Huffman MD, Isasi CR, Jimenez MC, Judd SE, Kissela BM, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Magid DJ, McGuire DK, Mohler ER 3rd, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Rosamond W, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Woo D, Yeh RW, Turner MB; American Heart Association Statistics Committee; Stroke Statistics Subcommittee. Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association. Circulation. 2016 Jan 26;133(4):447-54. doi: 10.1161/CIR.0000000000000366. No abstract available.

Reference Type BACKGROUND
PMID: 26811276 (View on PubMed)

Lightwood J, Bibbins-Domingo K, Coxson P, Wang YC, Williams L, Goldman L. Forecasting the future economic burden of current adolescent overweight: an estimate of the coronary heart disease policy model. Am J Public Health. 2009 Dec;99(12):2230-7. doi: 10.2105/AJPH.2008.152595. Epub 2009 Oct 15.

Reference Type BACKGROUND
PMID: 19833999 (View on PubMed)

Troendle JF, Sur A, Leifer ES, Powell-Wiley T. Sensitivity Analyses for Missing in Repeatedly Measured Outcome Data. Stat Med. 2025 Oct;44(23-24):e70282. doi: 10.1002/sim.70282.

Reference Type DERIVED
PMID: 41057147 (View on PubMed)

Tamura K, Vijayakumar NP, Troendle JF, Curlin K, Neally SJ, Mitchell VM, Collins BS, Baumer Y, Gutierrez-Huerta CA, Islam R, Turner BS, Andrews MR, Ceasar JN, Claudel SE, Tippey KG, Giuliano S, McCoy R, Zahurak J, Lambert S, Moore PJ, Douglas-Brown M, Wallen GR, Dodge T, Powell-Wiley TM. Multilevel mobile health approach to improve cardiovascular health in resource-limited communities with Step It Up: a randomised controlled trial protocol targeting physical activity. BMJ Open. 2020 Dec 21;10(12):e040702. doi: 10.1136/bmjopen-2020-040702.

Reference Type DERIVED
PMID: 33371027 (View on PubMed)

Related Links

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Other Identifiers

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17-H-0162

Identifier Type: -

Identifier Source: secondary_id

170162

Identifier Type: -

Identifier Source: org_study_id