Customizing Place-Tailored Messaging Using a Multilevel Approach: Pilot Study of the Step It Up Physical Activity Mobile App Tailored to Neighborhood Environment

HomeCirculation: Cardiovascular Quality and OutcomesVol. 15, No. 11Customizing Place-Tailored Messaging Using a Multilevel Approach: Pilot Study of the Step It Up Physical Activity Mobile App Tailored to Neighborhood Environment Free AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissionsDownload Articles + Supplements ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toSupplemental MaterialFree AccessResearch ArticlePDF/EPUBCustomizing Place-Tailored Messaging Using a Multilevel Approach: Pilot Study of the Step It Up Physical Activity Mobile App Tailored to Neighborhood Environment Nithya P. Vijayakumar, Sam J. Neally, Kameswari A. Potharaju, Kaveri Curlin, James F. Troendle, Billy S. Collins, Valerie M. Mitchell, Kosuke Tamura, Colby Ayers, Mario A. Pita, Hannatu A. Tarfa, Keitra Thompson, Foster Osei Baah, Andrew S. Baez, Lola R. Ortiz-Whittingham, Jennifer Wills Gallagher, Regina McCoy, Michael Heist, Cristhian A. Gutierrez-Huerta, Briana S. Turner, Yvonne Baumer, Nicole Farmer, Gwenyth R. Wallen, Tonya Dodge and Tiffany M. Powell-Wiley Nithya P. VijayakumarNithya P. Vijayakumar Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. *Dr Vijayakumar and S.J. Neally contributed equally. Search for more papers by this author , Sam J. NeallySam J. Neally https://orcid.org/0000-0002-4637-5241 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. *Dr Vijayakumar and S.J. Neally contributed equally. Search for more papers by this author , Kameswari A. PotharajuKameswari A. Potharaju https://orcid.org/0000-0003-2466-0233 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Kaveri CurlinKaveri Curlin Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , James F. TroendleJames F. Troendle Office of Biostatistics Research, Division of Intramural Research, National Heart, Lung, and Blood Institute (J.F.T.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Billy S. CollinsBilly S. Collins https://orcid.org/0000-0002-5271-3534 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Valerie M. MitchellValerie M. Mitchell https://orcid.org/0000-0002-9341-2535 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Kosuke TamuraKosuke Tamura https://orcid.org/0000-0002-4920-2856 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Colby AyersColby Ayers https://orcid.org/0000-0003-2060-2263 Donald W. Reynolds Cardiovascular Clinical Research Center at the University of Texas Southwestern Medical Center, Dallas (C.A.). Search for more papers by this author , Mario A. PitaMario A. Pita https://orcid.org/0000-0002-9208-6854 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Hannatu A. TarfaHannatu A. Tarfa https://orcid.org/0000-0002-4111-3488 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Keitra ThompsonKeitra Thompson Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities (K.T.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Foster Osei BaahFoster Osei Baah https://orcid.org/0000-0002-3836-9917 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Andrew S. BaezAndrew S. Baez https://orcid.org/0000-0002-7612-5104 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Lola R. Ortiz-WhittinghamLola R. Ortiz-Whittingham https://orcid.org/0000-0002-9085-1591 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Jennifer Wills GallagherJennifer Wills Gallagher https://orcid.org/0000-0001-5172-5966 Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill (J.W.G., R.M., M.H.). Search for more papers by this author , Regina McCoyRegina McCoy https://orcid.org/0000-0003-3451-052X Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill (J.W.G., R.M., M.H.). Search for more papers by this author , Michael HeistMichael Heist Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill (J.W.G., R.M., M.H.). Search for more papers by this author , Cristhian A. Gutierrez-HuertaCristhian A. Gutierrez-Huerta Donald W. Reynolds Cardiovascular Clinical Research Center at the University of Texas Southwestern Medical Center, Dallas (C.A.). Search for more papers by this author , Briana S. TurnerBriana S. Turner https://orcid.org/0000-0001-8556-6414 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Yvonne BaumerYvonne Baumer https://orcid.org/0000-0001-7400-0773 Search for more papers by this author , Nicole FarmerNicole Farmer https://orcid.org/0000-0003-3250-8688 Translational Biobehavioral and Health Disparities Branch, National Institutes of Health Clinical Center (N.F., G.R.W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Gwenyth R. WallenGwenyth R. Wallen https://orcid.org/0000-0001-7134-1636 Translational Biobehavioral and Health Disparities Branch, National Institutes of Health Clinical Center (N.F., G.R.W.), National Institutes of Health, Bethesda, MD. Search for more papers by this author , Tonya DodgeTonya Dodge Department of Psychological and Brain Sciences, George Washington University, DC (T.D.). Search for more papers by this author and Tiffany M. Powell-WileyTiffany M. Powell-Wiley Correspondence to: Tiffany M. Powell-Wiley, MD, MPH, Bldg 10, Room 5-5330, 10 Center Dr, Bethesda, MD 20814. Email E-mail Address: [email protected] https://orcid.org/0000-0001-9488-4131 Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute (N.P.V., S.J.N., K.A.P., K.C., B.S.C., V.M.M., M.A.P., H.T., K.T., F.O.B., A.S.B., L.O.-W., T.M.P.-W.), National Institutes of Health, Bethesda, MD. Intramural Research Program, National Institute on Minority Health and Health Disparities (T.M.P.-W), National Institutes of Health, Bethesda, MD. Search for more papers by this author Originally published15 Nov 2022https://doi.org/10.1161/CIRCOUTCOMES.122.009328Circulation: Cardiovascular Quality and Outcomes. 2022;15As outlined by the 2019 American College of Cardiology and the American Heart Association Guideline on the Primary Prevention of Cardiovascular Disease, strong evidence suggests that regular physical activity (PA), specifically aerobic exercise like walking, has clear benefits on cardiovascular disease (CVD) risk and outcomes.1 PA engagement is significantly determined by intra- and inter-personal factors, along with objective and perceived measures of neighborhood environment.2 Due to structural and social factors, Black women are more likely to live in resource-limited neighborhoods, exhibit lower PA rates, and are disproportionately affected by CVD.2,3 Previous work has elucidated the importance of incorporating social determinants of health (SDoH) into multilevel CVD interventions.3 Digital health technology can be used to address multiple socioecological factors that influence PA promotion within diverse communities. However, there is a need to specifically focus on the feasibility of digital health technology in populations highly impacted by SDoH.4We created Step It Up, a digital health app, to address barriers to increased PA engagement among Black women in lower-resourced neighborhoods. Place-tailored messaging is a method of improving PA resource awareness and utilization by providing information about nearby PA resources. Our prior work has determined elements important to PA in the community of focus, identifying links between neighborhood perception, PA and sedentary behaviors, as well as the acceptability and feasibility of utilizing the digital health technology described.4 Through a community-based pilot feasibility intervention, we sought to assess the impact of place-tailored messaging on PA and CVD outcomes. We also aimed to elucidate the multilevel environmental and psychosocial factors that associate with PA app engagement. Ultimately, study findings will be used to maximize user engagement in a 6-month, community-based PA intervention using the Step It Up app among Black women in the Washington, DC area.Local Challenges in ImplementationGiven the community-centered nature of this pilot intervention, it was crucial to interact directly with community members and seek their input during intervention development and implementation. While facilitating opportunities for sufficient community engagement can be challenging, we worked with the DC Cardiovascular Health and Obesity Collaborative (DC CHOC). DC CHOC is an established community advisory board consisting of leaders from faith-based and community organizations with expertise and/or interest in cardiovascular health (Supplemental Material). Through DC CHOC involvement, we were able to successfully incorporate the feedback of Black community members to design this intervention.Additionally, initiative implementation was impacted by neighborhood- and individual-level social factors relating to PA resources and perceptions. Generally, neighborhood-level socioeconomic disadvantage is directly attributed to discriminatory housing and urban planning policies that promote increased racial/ethnic segregation and decreased resource allocation to communities comprised predominantly of people of color.3 As a result of this adverse built and social neighborhood environment, residents are less able to engage in PA. Furthermore, PA may be influenced by perceived neighborhood social environment as a SDoH,3 which includes resident perceptions of neighborhood violence, physical/social environment, and social cohesion. Greater perceived crime and lack of neighborhood safety associate with low PA levels, especially women.2 At the individual-level among Black women, intra- and inter-personal factors determine an individual’s PA engagement. Anxiety and depression associate with decreased PA, as do other intrapersonal barriers such as time constraints, lack of motivation, and costs of exercise facilities. Interpersonal PA barriers include caregiving/family responsibilities, limited social support, and limited social accountability.2 The Step It Up app thus targets PA barriers using a multilevel approach.Design of the InitiativeThis intervention designed from a multi-level framework (Supplemental Methods, Figure S1) focused on Black women living in lower-resourced neighborhoods within the Washington, DC metropolitan area (Wards 5, 7, 8, and the contiguous Prince George’s County, MD). These neighborhoods have a population that is mostly Black, lower PA resources and median household income, and the highest CVD burden compared with other neighborhoods in the metropolitan area.4 Participants, recruited through engagement with DC CHOC, were 24 Black women with overweight/obesity (body mass index ≥25 kg/m2) aged 21 to 75 years. Participants had access to an Apple iOS smartphone compatible with the Step It Up app, which was designed in partnership with the DC CHOC and CHAI Core: Interventions (University of North Carolina, Chapel Hill) using an initial health and needs assessment, focus groups, and iterative end-user testing4 (Supplemental Methods, Table S1).Participants received one of 2 types of motivational messaging through push notifications 3 times a day at regular intervals via the Step It Up app. Participants randomized to standard messaging received motivational messages focused on intra- and interpersonal-level factors for PA, such as goal-setting, personal efficacy, and social support. Participants randomized to tailored-to-place messaging received additional messages addressing both individual- and neighborhood- level factors affecting PA, including available PA resources nearby (Supplemental Methods). Using a database of PA resources of parks, trails, fitness centers, and PA locations identified through community engagement4 within study areas, geofences were created with a 0.75-mile radius (approximately representing a 10–15 minute walk) around each PA location.4 Users randomized to place-tailored messaging received messages informing participants of nearby PA locations during the appropriate time frame and encouraged PA. Among those randomized to place-tailored messaging, there were 2 variations. The first group (objective) received messaging that included only locations from the registry compiled by the research team. The second group (personalized) added 5 of their own preferred PA locations, including informal resources like schools, homes, and workplaces.All participants received a wearable PA monitor (Fitbit Charge 2, Fitbit, San Francisco, CA), which synced with the Step It Up app, allowing users to monitor daily step count. Users were encouraged to wear the Fitbit daily, and track sleep, minutes of vigorous activity, total activity, and daily steps through the Step It Up app because all Fitbit app and tracker notifications were disabled during the study. The Fitbit was chosen for its comfort, features, and ease-of-use, and has been validated to reliably measure outcome variables (steps per day) of this study.4Implementation of the InitiativeThis Step It Up pilot intervention was conducted with 24 participants between October 2019 and February 2020. Each participant was studied for 3 weeks, and randomized into 1 of 3 messaging types, which were standard messaging, standard messaging with objective place-tailored messaging, or standard with personalized place-tailored messaging. Upon enrollment, all participants completed surveys assessing sociodemographics, health history, and behavioral, psychosocial, and environmental factors that may influence PA. A Fitbit Charge 2 was configured for PA monitoring and the Step It Up app was installed on their mobile phones. Participants had access to the Fitbit, but the Step It Up app was not active during the first week. After collecting baseline data for the first week, participants had access to all features of the app for the second and third weeks, including ecological momentary stress assessments (EMA), educational PA modules, a community forum, and personalized goal-setting tools, the details of which have been previously published.4Key outcomes for this pilot included PA, computed for each participant based on available Fitbit data as mean number of steps per day for each week of the intervention. In addition, we examined engagement with the Step It Up app as determined by a cumulative score ranging from 0 to 18 based on user interactions with various features of the app (number of educational modules completed [max=2 points], number of weeks utilizing the goal-setting tools [max=2 points], and number of days completing an EMA [max=14 points]). We conducted statistical analyses to determine associations between (1) place-tailored messaging with PA change over time using linear mixed models and (2) environmental and psychosocial factors with app engagement using linear regression models.Success of the InitiativePlace-tailored messaging was associated with PA increases of up to 1588 steps (SE=894, P=0.08) per day during Week 2 and 1344 steps per day (SE=894, P=0.14) during Week 3 in our fully adjusted model (Table). We adjusted for age and body mass index because higher values for these variables may increase the difficulty of walking and thereby affect steps per day. The observed change in steps during weeks 2 and 3 for participants who received place-tailored messaging was between 1000 and 2000 steps a day compared with either baseline or to the standard messaging group, trending towards clinical significance.5 On average, participants wore the Fitbit 20.96 hours/day over the 21-day study period, with all participants wearing the Fitbit for 21 days (Table S2).Table. Linear Mixed Modeling of Change in Average Steps/Day by Week and Message Type (n=72 Person-Weeks, 24 Participants)EffectAdjusted (age, BMI)Adjusted (TPM)Fully adjusted (TPM, age, BMI*)Estimate (SE)PEstimate (SE)PEstimate (SE)PIntercept6096 (7084)0.407840 (869)<0.00018034 (7108)0.27Week 2685 (429)0.12−361 (720)0.62−373 (727)0.61Week 31180 (429)0.01*295 (720)0.68284 (727)0.70Place-tailored Messaging (TPM)−221 (1505)0.88−154 (1515)0.92Week 2 TPM1571 (882)0.08*1588 (894)0.08*Week 3 TPM1327 (882)0.141344 (894)0.14Age17 (67)0.819 (66)0.89BMI25 (120)0.84−16 (119)0.89Referent group for the TPM group were those that received standard messaging (without any location-specific information). BMI indicates body mass index; and TPM, place-tailored messaging.With regards to app engagement patterns, mean app engagement score was 9.8 (SD±6.3) out of 18 points. 37.5% of participants completed all 14 EMA and 62.5% completed at least half of the EMA. 62.5% of participants additionally completed all modules, but only 12.5% of participants utilized the personal goal-setting tools. At the neighborhood level, greater perceived neighborhood social cohesion and greater neighborhood safety were associated with greater app engagement (B=3.48, SE=1.43, P=0.02 and B=3.05, SE=1.30, and P=0.03, respectively). On the individual level, greater social isolation was associated with greater app engagement (B=5.24, SE=2.38, P=0.04; Table S3).The multi-level approach to analyzing PA app engagement focused on both neighborhood- and individual-level factors allows for a more nuanced understanding of the barriers and incentives to increased PA and utilization of tools within the Step It Up app. We observed the effects of individual experiences and neighborhood environment perceptions on PA app engagement. Some participants expressed that the app was useful to discover PA resources in suburban environments, which were consequentially associated with more favorable neighborhood perceptions. Users reporting greater social isolation were also more likely to engage with the app. This association is corroborated by informal feedback from participants, who wanted to see even more robust features within the community forum on the app.Translation to Other SettingsThis pilot study is representative of the process of developing a digital health intervention for communities with high CVD risk burden who are traditionally underrepresented in biomedical research, specifically in dense, urban areas with PA resources in proximity. Through engagement with a community advisory board, future initiatives could develop tailored digital health interventions that directly target barriers to PA as identified by community members themselves. Furthermore, this pilot study provides evidence for the value of incorporating targeted interventions for app engagement and neighborhood perceptions when addressing PA, which are factors often overlooked in digital health studies. This intervention can broadly serve as a model for other CVD interventions that are community-centered and SDoH-informed.Summary of the Experience, Future Directions, and ChallengesIn this pilot study, we identified several neighborhood- and individual-level influences on engagement with a PA app in a population with a high CVD risk. We successfully achieved our goals of testing place-tailored messaging to be implemented in a 6-month, community-engaged PA intervention.4 Findings from this study will be used to further tailor the 6-month intervention utilizing the Step It Up app, which aims to address PA levels among Black women in the Washington, DC area, targeting those who live in urban areas with more unfavorable perceptions of the neighborhood environment. At the neighborhood level, we will add PA resources in DC that fit user preference and accordingly modify place-tailored messaging in the full study. Utilizing what we have learned about app engagement, we are incorporating additional features such as messaging specifically encouraging interaction with the community forum, individualized goal-setting tools to plan PA types over the course of the week, and options to flag unsafe locations to address the relationship between perceived neighborhood safety and app engagement (Figure S2).We also aim to study the impact of community-building measures on social isolation outcomes at the individual level, as increased interaction with fellow participants could possibly lead to improved app engagement. In addition, based on our findings suggesting that positive neighborhood perceptions were associated with greater engagement, we will further clarify the role of the built environment on PA and engagement in the full study and observe whether participants flag unsafe PA resources while in the study. As a limitation of this pilot study, we were only able to recruit participants with access to an Apple iOS smartphone. However, for the future intervention,4 the Step It Up app was designed to also be used with Android phones. Last, we will need to evaluate the effects of the COVID-19 pandemic as a potential barrier to participants’ willingness to engage in the Step It Up PA intervention. Ultimately, we hope the full intervention will successfully address the SDoH that influence PA and app engagement to make a meaningful reduction in CVD risk and improve outcomes with future efforts to integrate similar tailored, digital-health interventions into cardiovascular care.Article InformationAcknowledgmentsWe would like to acknowledge our partners in the Washington DC Cardiovascular Health and Obesity Collaborative community advisory board, study participants, and former students and fellows, without whom none of our work would have been possible. We would also like to thank the NIH staff and clinical teams and our collaborators for their continuous support.Sources of FundingThe statements and contents expressed in this perspective are those of the authors and do not reflect the official position of the NIH, DHHS, and/or the US Government. The Social Determinants of Obesity and Cardiovascular Risk Laboratory is funded by the Division of Intramural Research of the National Heart, Lung, and Blood Institute and Intramural Research Program of the National Institute on Minority Health and Health Disparities. The Translational, Biobehavioral and Health Disparities Branch it funded by the Intramural Research Program of the National Institutes of Health, Clinical Center. The Socio-Spatial Determinants of Health Laboratory is supported by the Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health and by the NIH Distinguished Scholars Programs. This research was made possible through the NIH Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and generous contributions to the Foundation for the NIH from the Doris Duke Charitable Foundation, Genentech, the American Association for Dental Research, the Colgate-Palmolive Company, Elsevier, alumni of student research programs, and other individual supporters via contributions to the Foundation for the National Institutes of Health. CHAI Core: Interventions (University of North Carolina, Chapel Hill) is funded by NIH grant P30-DK06350 to the UNC Nutrition Obesity Research Center and NIH grant P30-CA16086 to the UNC Lineberger Comprehensive Cancer Center.Supplemental MaterialSupplemental MethodsFigure S1 and S2Table S1–S3Disclosures None.Footnotes*Dr Vijayakumar and S.J. Neally contributed equally.Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03288207.Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCOUTCOMES.122.009328.For Sources of Funding and Disclosures, see page 936.Correspondence to: Tiffany M. Powell-Wiley, MD, MPH, Bldg 10, Room 5-5330, 10 Center Dr, Bethesda, MD 20814. Email tiffany.[email protected]govReferences1. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.Circulation. 2019; 140:e596–e646. doi: 10.1161/CIR.0000000000000678LinkGoogle Scholar2. Fleury J, Lee SM. 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Systematic review of the prospective association of daily step counts with risk of mortality, cardiovascular disease, and dysglycemia.Int J Behav Nutr Phys Act. 2020; 17:78. doi: 10.1186/s12966-020-00978-9CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails November 2022Vol 15, Issue 11 Advertisement Article InformationMetrics © 2022 American Heart Association, Inc.https://doi.org/10.1161/CIRCOUTCOMES.122.009328PMID: 36378765 Originally publishedNovember 15, 2022 Keywordsphysical activity interventioncardiovascular diseaseneighborhood adversitysocial determinants of healthobesityPDF download Advertisement SubjectsEpidemiologyExerciseTranslational Studies