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Rogers BJ, Alphonso SR, Neally SJ, Deng Y, Moniruzzaman M, Tamura K. The Role of the Perceived Neighborhood Social Environment on Adolescent Sedentary Behavior and Physical Activity: Findings from Add Health. J Community Health 2024:10.1007/s10900-024-01332-x. [PMID: 38374312 DOI: 10.1007/s10900-024-01332-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/29/2024] [Indexed: 02/21/2024]
Abstract
Few studies have examined the role of perceived neighborhood characteristics such as neighborhood safety, social cohesion, and contentedness on sedentary behavior (SB) and physical activity (PA) among adolescents. Furthermore, no studies have investigated how these associations are moderated by gender and race. This study aimed to examine the associations of the perceived neighborhood social environment with (SB) and moderate-to-vigorous physical activity (MVPA). Data from 6504 adolescents (aged 15.4 ± 0.03 years) who participated in the National Longitudinal Study of Adolescent Health was used. SB and PA were considered continuously and dichotomously. PNSE variables include safety, social cohesion, and contentedness, where higher values of PNSE indicate a more favorable neighborhood perception. Weighted linear and logistic regression models were used to examine the association of PNSE with continuous total SB (hours/week) and MVPA (bouts/week), and binary excessive SB (14 h/week) and meeting MVPA guidelines (≥ 5 bouts/week), respectively. Associations were stratified by gender and race to test moderation effects. Models were adjusted for demographic, health, parental, and neighborhood covariates. This study found that neighborhood safety and contentedness were negatively associated with SB, whereas neighborhood social cohesion and contentedness were positively associated with PA. Gender-specific and race-specific results remained somewhat consistent with overall findings; however, neighborhood safety was not associated with SB among female and non-White adolescents, respectively. Similarly, neighborhood safety and contentedness were not associated with MVPA for non-White adolescents. Findings suggest that an adolescent's neighborhood environment, gender, and race should be considered when implementing strategies to reduce SB and increase PA.
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Affiliation(s)
- Breanna J Rogers
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Building 3 Rm 5W21, 3 Center Dr, Bethesda, MD, 20892, USA
| | - Sophie R Alphonso
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Building 3 Rm 5W21, 3 Center Dr, Bethesda, MD, 20892, USA
| | - Sam J Neally
- Department of Epidemiology, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, USA
| | - Yangyang Deng
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Building 3 Rm 5W21, 3 Center Dr, Bethesda, MD, 20892, USA
| | - Mohammad Moniruzzaman
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Building 3 Rm 5W21, 3 Center Dr, Bethesda, MD, 20892, USA
| | - Kosuke Tamura
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Building 3 Rm 5W21, 3 Center Dr, Bethesda, MD, 20892, USA.
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2
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Baumer Y, Pita MA, Turner BS, Baez AS, Ortiz-Whittingham LR, Gutierrez-Huerta CA, Neally SJ, Farmer N, Mitchell VM, Collins BS, Powell-Wiley TM. Neighborhood socioeconomic deprivation and individual-level socioeconomic status are associated with dopamine-mediated changes to monocyte subset CCR2 expression via a cAMP-dependent pathway. Brain Behav Immun Health 2023; 30:100640. [PMID: 37251548 PMCID: PMC10220312 DOI: 10.1016/j.bbih.2023.100640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 05/12/2023] [Indexed: 05/31/2023] Open
Abstract
Social determinants of health (SDoH) include socioeconomic, environmental, and psychological factors that impact health. Neighborhood socioeconomic deprivation (NSD) and low individual-level socioeconomic status (SES) are SDoH that associate with incident heart failure, stroke, and cardiovascular mortality, but the underlying biological mechanisms are not well understood. Previous research has demonstrated an association between NSD, in particular, and key components of the neural-hematopoietic-axis including amygdala activity as a marker of chronic stress, bone marrow activity, and arterial inflammation. Our study further characterizes the role of NSD and SES as potential sources of chronic stress related to downstream immunological factors in this stress-associated biologic pathway. We investigated how NSD, SES, and catecholamine levels (as proxy for sympathetic nervous system activation) may influence monocytes which are known to play a significant role in atherogenesis. First, in an ex vivo approach, we treated healthy donor monocytes with biobanked serum from a community cohort of African Americans at risk for CVD. Subsequently, the treated monocytes were subjected to flow cytometry for characterization of monocyte subsets and receptor expression. We determined that NSD and serum catecholamines (namely dopamine [DA] and norepinephrine [NE]) associated with monocyte C-C chemokine receptor type 2 (CCR2) expression (p < 0.05), a receptor known to facilitate recruitment of monocytes towards arterial plaques. Additionally, NSD associated with catecholamine levels, especially DA in individuals of low SES. To further explore the potential role of NSD and the effects of catecholamines on monocytes, monocytes were treated in vitro with epinephrine [EPI], NE, or DA. Only DA increased CCR2 expression in a dose-dependent manner (p < 0.01), especially on non-classical monocytes (NCM). Furthermore, linear regression analysis between D2-like receptor surface expression and surface CCR2 expression suggested D2-like receptor signaling in NCM. Indicative of D2-signaling, cAMP levels were found to be lower in DA-treated monocytes compared to untreated controls (control 29.78 pmol/ml vs DA 22.97 pmol/ml; p = 0.038) and the impact of DA on NCM CCR2 expression was abrogated by co-treatment with 8-CPT, a cAMP analog. Furthermore, Filamin A (FLNA), a prominent actin-crosslinking protein, that is known to regulate CCR2 recycling, significantly decreased in DA-treated NCM (p < 0.05), indicating a reduction of CCR2 recycling. Overall, we provide a novel immunological mechanism, driven by DA signaling and CCR2, for how NSD may contribute to atherogenesis. Future studies should investigate the importance of DA in CVD development and progression in populations disproportionately experiencing chronic stress due to SDoH.
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Affiliation(s)
- Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mario A. Pita
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Briana S. Turner
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S. Baez
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lola R. Ortiz-Whittingham
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Cristhian A. Gutierrez-Huerta
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sam J. Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nicole Farmer
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD, USA
| | - Valerie M. Mitchell
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Billy S. Collins
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tiffany M. Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
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Cornelissen A, Guo L, Neally SJ, Kleinberg L, Forster A, Nair R, Gadhoke N, Ghosh SKB, Sakamoto A, Sato Y, Kawakami R, Mori M, Kawai K, Fernandez R, Dikongue A, Abebe B, Kutys R, Romero ME, Kolodgie FD, Baumer Y, Powell-Wiley TM, Virmani R, Finn AV. Relationships between neighborhood disadvantage and cardiovascular findings at autopsy in subjects with sudden death. Am Heart J 2023; 256:37-50. [PMID: 36372247 DOI: 10.1016/j.ahj.2022.10.086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/19/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Neighborhood disadvantage is associated with a higher risk of sudden cardiac death. However, autopsy findings have never been investigated in this context. Here, we sought to explore associations between neighborhood disadvantage and cardiovascular findings at autopsy in cases of sudden death in the State of Maryland. METHODS State of Maryland investigation reports from 2,278 subjects within the CVPath Sudden Death Registry were screened for street addresses and 9-digit zip codes. Area deprivation index (ADI), used as metric for neighborhood disadvantage, was available for 1,464 subjects; 650 of whom self-identified as Black and 814 as White. The primary study outcome measurements were causes of death and gross and histopathologic findings of the heart. RESULTS Subjects from most disadvantaged neighborhoods (i.e., ADI ≥ 8; n = 607) died at younger age compared with subjects from less disadvantaged neighborhoods (i.e., ADI ≤ 7; n = 857; 46.07 ± 14.10 vs 47.78 ± 13.86 years; P = 0.02) and were more likely Black or women. They were less likely to die from cardiac causes of death (61.8% vs 67.7%; P = 0.02) and had less severe atherosclerotic plaque features, including plaque burden, calcification, intraplaque hemorrhage, and thin-cap fibroatheromas. In addition, subjects from most disadvantaged neighborhoods had lower frequencies of plaque rupture (18.8% vs 25.1%, P = 0.004). However, these associations were omitted after adjustment for traditional risk factors and race. CONCLUSION Neighborhood disadvantage did not associate with cause of death or coronary histopathology after adjustment for cardiovascular risk factors and race, implying that social determinants of health other than neighborhood disadvantage play a more prominent role in sudden cardiac death.
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Affiliation(s)
| | - Liang Guo
- CVPath Institute, Gaithersburg, MD, US
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Institutes of Health, Bethesda, MD, US
| | | | | | | | | | | | | | - Yu Sato
- CVPath Institute, Gaithersburg, MD, US
| | | | | | | | | | | | | | | | | | | | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Institutes of Health, Bethesda, MD, US
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Institutes of Health, Bethesda, MD, US
| | | | - Aloke V Finn
- CVPath Institute, Gaithersburg, MD, US; School of Medicine, University of Maryland School of Medicine, Baltimore, MD, US.
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Vijayakumar NP, Neally SJ, Potharaju KA, Curlin K, Troendle JF, Collins BS, Mitchell VM, Tamura K, Ayers C, Pita MA, Tarfa H, Thompson K, Baah FO, Baez AS, Ortiz-Whittingham L, Gallagher JW, McCoy R, Heist M, Gutierrez-Huerta CA, Turner BS, Baumer Y, Farmer N, Wallen GR, Dodge T, Powell-Wiley TM. Customizing Place-Tailored Messaging Using a Multilevel Approach: Pilot Study of the Step It Up Physical Activity Mobile App Tailored to Neighborhood Environment. Circ Cardiovasc Qual Outcomes 2022; 15:e009328. [PMID: 36378765 PMCID: PMC9680010 DOI: 10.1161/circoutcomes.122.009328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Nithya P. Vijayakumar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sam J. Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kameswari A. Potharaju
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kaveri Curlin
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - James F. Troendle
- Office of Biostatistics Research, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Billy S. Collins
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Valerie M. Mitchell
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kosuke Tamura
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Colby Ayers
- Donald W. Reynolds Cardiovascular Clinical Research Center at the University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Mario A. Pita
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hannatu Tarfa
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Keitra Thompson
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Foster Osei Baah
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S. Baez
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lola Ortiz-Whittingham
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer Wills Gallagher
- Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Regina McCoy
- Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Michael Heist
- Connected Health for Applications and Interventions Core, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Cristhian A. Gutierrez-Huerta
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Briana S. Turner
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nicole Farmer
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD, USA
| | - Gwenyth R. Wallen
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD, USA
| | - Tonya Dodge
- Department of Psychological and Brain Sciences, George Washington University, Washington, DC, USA
| | - Tiffany M. Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
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Powell-Wiley TM, Martinez MF, Tamura K, Neally SJ, O'Shea KJ, Curlin K, Albarracin Y, Vijayakumar NP, Morgan M, Ortiz-Chaparro E, Bartsch SM, Osei Baah F, Wedlock PT, Ortiz-Whittingham LR, Scannell S, Potharaju KA, Randall S, Solano Gonzales M, Domino M, Ranganath K, Hertenstein D, Syed R, Weatherwax C, Lee BY. The Impact of a Place-Tailored Digital Health App Promoting Exercise Classes on African American Women's Physical Activity and Obesity: Simulation Study. J Med Internet Res 2022; 24:e30581. [PMID: 35994313 PMCID: PMC9446149 DOI: 10.2196/30581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 12/17/2021] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The increasing prevalence of smartphone apps to help people find different services raises the question of whether apps to help people find physical activity (PA) locations would help better prevent and control having overweight or obesity. OBJECTIVE The aim of this paper is to determine and quantify the potential impact of a digital health intervention for African American women prior to allocating financial resources toward implementation. METHODS We developed our Virtual Population Obesity Prevention, agent-based model of Washington, DC, to simulate the impact of a place-tailored digital health app that provides information about free recreation center classes on PA, BMI, and overweight and obesity prevalence among African American women. RESULTS When the app is introduced at the beginning of the simulation, with app engagement at 25% (eg, 25% [41,839/167,356] of women aware of the app; 25% [10,460/41,839] of those aware downloading the app; and 25% [2615/10,460] of those who download it receiving regular push notifications), and a 25% (25/100) baseline probability to exercise (eg, without the app), there are no statistically significant increases in PA levels or decreases in BMI or obesity prevalence over 5 years across the population. When 50% (83,678/167,356) of women are aware of the app; 58.23% (48,725/83,678) of those who are aware download it; and 55% (26,799/48,725) of those who download it receive regular push notifications, in line with existing studies on app usage, introducing the app on average increases PA and decreases weight or obesity prevalence, though the changes are not statistically significant. When app engagement increased to 75% (125,517/167,356) of women who were aware, 75% (94,138/125,517) of those who were aware downloading it, and 75% (70,603/94,138) of those who downloaded it opting into the app's push notifications, there were statistically significant changes in PA participation, minutes of PA and obesity prevalence. CONCLUSIONS Our study shows that a digital health app that helps identify recreation center classes does not result in substantive population-wide health effects at lower levels of app engagement. For the app to result in statistically significant increases in PA and reductions in obesity prevalence over 5 years, there needs to be at least 75% (125,517/167,356) of women aware of the app, 75% (94,138/125,517) of those aware of the app download it, and 75% (70,603/94,138) of those who download it opt into push notifications. Nevertheless, the app cannot fully overcome lack of access to recreation centers; therefore, public health administrators as well as parks and recreation agencies might consider incorporating this type of technology into multilevel interventions that also target the built environment and other social determinants of health.
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Affiliation(s)
- Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - Marie F Martinez
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Kosuke Tamura
- Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Kaveri Curlin
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Yardley Albarracin
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Nithya P Vijayakumar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Matthew Morgan
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Erika Ortiz-Chaparro
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Foster Osei Baah
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Lola R Ortiz-Whittingham
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Sheryl Scannell
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Kameswari A Potharaju
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Samuel Randall
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Mario Solano Gonzales
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Molly Domino
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Kushi Ranganath
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Daniel Hertenstein
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Rafay Syed
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Colleen Weatherwax
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
- Center for Advanced Technology and Communication in Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, United States
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Pita MA, Baumer Y, Turner BS, Gutierrez‐Huerta CA, Neally SJ, Baez AS, Farmer N, Mitchell VM, Collins BS, Powell‐Wiley TM. Dopamine D2‐Like Receptor Signaling and Downregulation of Filamin‐A May Drive the Association Between Neighborhood Socioeconomic Status and CCR2 Expression on Monocytes. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.r4809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk LaboratoryNHLBI/NIHBethesdaMD
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7
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Tamura K, Johnson DA, Neally SJ, Sims M, Powell-Wiley TM. Relationships between neighborhood social stressors and sleep among Jackson Heart Study participants: mediation through physical activity and psychosocial stressors. Sleep Adv 2022; 3:zpac032. [PMID: 37193404 PMCID: PMC10174476 DOI: 10.1093/sleepadvances/zpac032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/07/2022] [Indexed: 05/18/2023]
Abstract
Study Objectives To examine associations between perceived neighborhood social environment (PNSE) and sleep, mediated by physical activity (PA) and psychosocial stressors. Methods A sample (n = 4705) of African Americans (mean age 55.0 years; 63.4% female) enrolled in the 2000-2004 Jackson Heart Study (JHS). Four self-reported sleep outcomes were analyzed: sleep duration (minutes/night), sleep quality (high/low), short sleep (short ≤ 6 h vs recommended = 7-8 h), and long sleep (long ≥ 9 h vs recommended). PNSE factors included violence (e.g. robbery), problems (trash/litter), and social cohesion (trusting neighbors). PA and psychosocial stressors (lifetime and everyday discrimination, perceived stress, and depressive symptoms) were tested as mediators. With bootstrap-generated 95% bias-corrected confidence intervals (BC CIs), linear regression was used to test for mediation adjusting for covariates. Results Neighborhood violence and problems were associated with sleep duration, mediated through PA (B = -1.97, 95%BC CI = -3.76, -0.60; B = -1.23, 95%BC CI = -2.55, -0.27, respectively), lifetime discrimination (B = 2.61, 95%BC CI = 0.93, 4.80; B = 2.25, 95%BC CI = 0.93, 3.94), perceived stress (B = -3.08, 95%BC CI = -6.20, -0.41; B = -2.17, 95%BC CI = -4.33, -0.28), and depressive symptoms (B = -2.22, 95%BC CI = -5.09, -0.25; B = -1.94, 95%BC CI = -4.10, -0.35). Social cohesion was positively associated with sleep duration, mediated through PA, lifetime discrimination, and perceived stress. Similar patterns were demonstrated for binary outcomes. Yet, effect sizes were relatively small. PNSE was neither directly nor indirectly associated with sleep outcomes by everyday discrimination. Conclusions Each PNSE factor was associated with sleep outcomes, mediated by PA and psychosocial stressors. Further research should emphasize effective community efforts to decrease adverse neighborhood conditions and psychosocial factors and increase PA; thereby reducing CVD events for African Americans.
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Affiliation(s)
- Kosuke Tamura
- Corresponding author. Kosuke Tamura, PhD, Socio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA.
| | - Dayna A Johnson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mario Sims
- Department of Social Medicine, Population and Public Health, University of California at Riverside, Riverside, CA, USA
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
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Tamura K, Curlin K, Neally SJ, Vijayakumar NP, Mitchell VM, Collins BS, Gutierrez-Huerta C, Troendle JF, Baumer Y, Osei Baah F, Turner BS, Gray V, Tirado BA, Ortiz-Chaparro E, Berrigan D, Mehta NN, Vaccarino V, Zenk SN, Powell-Wiley TM. Geospatial Analysis of Neighborhood Environmental Stress in Relation to Biological Markers of Cardiovascular Health and Health Behaviors in Women: Protocol for a Pilot Study. JMIR Res Protoc 2021; 10:e29191. [PMID: 34292168 PMCID: PMC8367127 DOI: 10.2196/29191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 11/26/2022] Open
Abstract
Background Innovative analyses of cardiovascular (CV) risk markers and health behaviors linked to neighborhood stressors are essential to further elucidate the mechanisms by which adverse neighborhood social conditions lead to poor CV outcomes. We propose to objectively measure physical activity (PA), sedentary behavior, and neighborhood stress using accelerometers, GPS, and real-time perceived ecological momentary assessment via smartphone apps and to link these to biological measures in a sample of White and African American women in Washington, DC, neighborhoods. Objective The primary aim of this study is to test the hypothesis that living in adverse neighborhood social conditions is associated with higher stress-related neural activity among 60 healthy women living in high or low socioeconomic status neighborhoods in Washington, DC. Sub-aim 1 of this study is to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. A secondary objective is to test the hypothesis that residing in adverse neighborhood social environment conditions is related to differences in vascular function. Sub-aim 2 of this study is to test the hypothesis that the association is moderated by objectively measured PA. The third aim of this study is to test the hypothesis that adverse neighborhood social environment conditions are related to differences in immune system activation. Methods The proposed study will be cross-sectional, with a sample of at least 60 women (30 healthy White women and 30 healthy Black women) from Wards 3 and 5 in Washington, DC. A sample of the women (n=30) will be recruited from high-income areas in Ward 3 from census tracts within a 15% of Ward 3’s range for median household income. The other participants (n=30) will be recruited from low-income areas in Wards 5 from census tracts within a 15% of Ward 5’s range for median household income. Finally, participants from Wards 3 and 5 will be matched based on age, race, and BMI. Participants will wear a GPS unit and accelerometer and report their stress and mood in real time using a smartphone. We will then examine the associations between GPS-derived neighborhood variables, stress-related neural activity measures, and adverse biological markers. Results The National Institutes of Health Institutional Review Board has approved this study. Recruitment will begin in the summer of 2021. Conclusions Findings from this research could inform the development of multilevel behavioral interventions and policies to better manage environmental factors that promote immune system activation or psychosocial stress while concurrently working to increase PA, thereby influencing CV health. International Registered Report Identifier (IRRID) PRR1-10.2196/29191
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Affiliation(s)
- Kosuke Tamura
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Kaveri Curlin
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Nithya P Vijayakumar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Valerie M Mitchell
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Billy S Collins
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Cristhian Gutierrez-Huerta
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - James F Troendle
- Office of Biostatistics Research, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Foster Osei Baah
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Briana S Turner
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Veronica Gray
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Brian A Tirado
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Erika Ortiz-Chaparro
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - David Berrigan
- Health Behaviors Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Shady Grove, MD, United States
| | - Nehal N Mehta
- Section of Inflammation and Cardiometabolic Diseases, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States.,Department of Medicine, School of Medicine, Emory University, Atlanta, GA, United States
| | - Shannon N Zenk
- National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, United States
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.,Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States
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Tamura K, Orstad SL, Cromley EK, Neally SJ, Claudel SE, Andrews MR, Ceasar J, Sims M, Powell-Wiley TM. The Mediating role of perceived discrimination and stress in the associations between neighborhood social environment and TV Viewing among Jackson Heart Study participants. SSM Popul Health 2021; 13:100760. [PMID: 33681448 PMCID: PMC7930346 DOI: 10.1016/j.ssmph.2021.100760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 02/08/2021] [Accepted: 02/17/2021] [Indexed: 12/25/2022] Open
Abstract
Objectives The aim of this study was to test the mediating role of perceived discrimination and stress on associations between perceived neighborhood social environment (PNSE) and TV viewing. Methods Baseline data were used for 4716 participants (mean age = 55.1 y; 63.4% female) in the Jackson Heart Study (JHS), a large prospective cohort study of African Americans in Jackson, Mississippi. One binary TV viewing outcome was created: ≥4 h/day versus <4 h/day. PNSE variables included neighborhood violence, problems (higher value = more violence/problems), and social cohesion (higher value = more cohesion). Mediators included perceived lifetime discrimination, daily discrimination, and chronic stress (higher value = greater discrimination/stress). Multivariable regression was used with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) to test for mediation adjusting for demographics, health-related and psychosocial factors, and population density. Results Neighborhood violence, problems, and social cohesion were indirectly associated with TV viewing through lifetime discrimination (OR = 1.03, 95%BC CI = 1.00, 1.07; OR = 1.03, 95%BC CI = 0.99, 1.06 [marginal]; OR = 0.98, 95%BC CI = 0.94, 0.99, respectively) and chronic stress (OR = 0.95, 95%BC CI = 0.90, 0.99; OR = 0.96, 95%BC CI = 0.92, 0.99; OR = 1.05, 95%BC CI = 1.01, 1.10, respectively). Daily discrimination was neither directly nor indirectly associated with TV viewing. Conclusions Each PNSE variable was indirectly associated with TV viewing via lifetime discrimination and perceived stress, but not with daily discrimination among JHS participants. Unexpected directionality of mediating effects of lifetime discrimination and chronic stress should be replicated in future studies. Further research is also needed to pinpoint effective community efforts and physical environmental policies (e.g., installing bright street lights, community policing) to reduce adverse neighborhood conditions and psychosocial factors, and decrease TV viewing and subsequent cardiovascular disease risk.
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Affiliation(s)
- Kosuke Tamura
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Stephanie L Orstad
- Department of Medicine, Division of General Internal Medicine and Clinical Innovation, New York University Grossman School of Medicine, 550 Avenue, New York, NY, 10016, USA
| | - Ellen K Cromley
- Institute for Collaboration on Health, Intervention, and Policy (InCHIP), University of Connecticut, 2006 Hillside Road, Unit 1248, Storrs, CT, 06269-1248, USA
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Sophie E Claudel
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Marcus R Andrews
- Department of Health Behavior and Health Education, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Joniqua Ceasar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, 2500 N State St, Jackson, MS, 39216, USA
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA.,Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, 6707 Democracy Boulevard, Bethesda, MD, 20892, USA
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10
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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; 10:e040702. [PMID: 33371027 PMCID: PMC7754642 DOI: 10.1136/bmjopen-2020-040702] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Although physical activity (PA) reduces cardiovascular disease (CVD) risk, physical inactivity remains a pressing public health concern, especially among African American (AA) women in the USA. PA interventions focused on AA women living in resource-limited communities with scarce PA infrastructure are needed. Mobile health (mHealth) technology can increase access to PA interventions. We describe the development of a clinical protocol for a multilevel, community-based, mHealth PA intervention for AA women. METHODS AND ANALYSIS An mHealth intervention targeting AA women living in resource-limited Washington, DC communities was developed based on the socioecological framework for PA. Over 6 months, we will use a Sequential Multi-Assignment, Randomized Trial approach to compare the effects on PA of location-based remote messaging (named 'tailored-to-place') to standard remote messaging in an mHealth intervention. Participants will be randomised to a remote messaging intervention for 3 months, at which point the intervention strategy will adapt based on individuals' PA levels. Those who do not meet the PA goal will be rerandomised to more intensive treatment. Participants will be followed for another 3 months to determine the contribution of each mHealth intervention to PA level. This protocol will use novel statistical approaches to account for the adaptive strategy. Finally, effects of PA changes on CVD risk biomarkers will be characterised. ETHICS AND DISSEMINATION This protocol has been developed in partnership with a Washington, DC-area community advisory board to ensure feasibility and acceptability to community members. The National Institutes of Health Intramural IRB approved this research and the National Heart, Lung, and Blood Institute provided funding. Once published, results of this work will be disseminated to community members through presentations at community advisory board meetings and our quarterly newsletter. TRIAL REGISTRATION NUMBER NCT03288207.
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Affiliation(s)
- Kosuke Tamura
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Nithya P Vijayakumar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - James F Troendle
- Office of Biostatistics Research, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Kaveri Curlin
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Valerie M Mitchell
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Billy S Collins
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Cristhian A Gutierrez-Huerta
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Rafique Islam
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Briana S Turner
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Marcus R Andrews
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Joniqua N Ceasar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Sophie E Claudel
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Kathryn G Tippey
- University of North Carolina, Nutrition Obesity Research Center, Lineberger Comprehensive Cancer Center, Connected Health Applications and Interventions (CHAI) Core, Chapel Hill, North Carolina, USA
| | - Shayne Giuliano
- University of North Carolina, Nutrition Obesity Research Center, Lineberger Comprehensive Cancer Center, Connected Health Applications and Interventions (CHAI) Core, Chapel Hill, North Carolina, USA
| | - Regina McCoy
- University of North Carolina, Nutrition Obesity Research Center, Lineberger Comprehensive Cancer Center, Connected Health Applications and Interventions (CHAI) Core, Chapel Hill, North Carolina, USA
| | - Jessica Zahurak
- University of North Carolina, Nutrition Obesity Research Center, Lineberger Comprehensive Cancer Center, Connected Health Applications and Interventions (CHAI) Core, Chapel Hill, North Carolina, USA
| | - Sharon Lambert
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia, USA
| | - Philip J Moore
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia, USA
| | | | - Gwenyth R Wallen
- National Institutes of Health Clinical Center, Nursing Department, Bethesda, Maryland, USA
| | - Tonya Dodge
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia, USA
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland, USA
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Tamura K, Langerman SD, Orstad SL, Neally SJ, Andrews MR, Ceasar JN, Sims M, Lee JE, Powell-Wiley TM. Physical activity-mediated associations between perceived neighborhood social environment and depressive symptoms among Jackson Heart Study participants. Int J Behav Nutr Phys Act 2020; 17:91. [PMID: 32650787 PMCID: PMC7350640 DOI: 10.1186/s12966-020-00991-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 06/29/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Little is known about the associations between perceived neighborhood social environment (PNSE) and depressive symptoms among African Americans. Furthermore, the role of physical activity (PA) as a mediator of this association has not been investigated. The two-fold objectives of this study, therefore, were (1) to examine the associations between PNSE and depressive symptoms among African Americans, and (2) to test the degree to which these associations were mediated by total PA. METHODS We used baseline data from the Jackson Heart Study (JHS), a single-site, prospective, community-based study of African-American adults (n = 2209) recruited from Jackson, Mississippi. PNSE variables included scores for neighborhood violence (i.e., higher score = more violence), problems (higher score = more problems), and social cohesion (higher score = more cohesion). Depressive symptoms were measured by the 20-item Center for Epidemiological Studies Depression (CES-D) score. First, multilevel modeling, controlling for census tract clustering effects, was used to estimate associations between each PNSE variable and CES-D score, adjusting for covariates, including demographic, health-related, and population density. Second, validated, self-reported total PA, based on active living, sport, and home indices, was tested as the mediator. Multivariable linear regressions with bootstrap-generated 95% bias-corrected confidence intervals (BC CIs) were estimated to test for significant unstandardized indirect effects, controlling for all covariates. RESULTS Our participants were 64.2% female with a mean age of 52.6 (SD = 12.2) and a mean CES-D score of 10.8 (SD = 8.1). In the fully-adjusted model, neighborhood violence and problems were positively related to depressive symptoms (B = 3.59, 95%CI = 0.93, 6.26, and B = 3.06, 95%CI = 1.19, 4.93, respectively). Neighborhood violence and problems were also indirectly related to depressive symptoms via total PA (B = 0.26, 95%BC CI = 0.05, 0.55; and B = 0.15, 95%BC CI = 0.02, 0.34, respectively). Social cohesion was neither directly nor indirectly related to depressive symptoms. CONCLUSIONS We found that higher levels of perceived neighborhood problems and violence were directly and positively associated with depressive symptoms. These associations may be explained in part by lower total PA levels. Future interventions to reduce depressive symptoms attributed to neighborhood features should consider emphasizing built environment features that facilitate PA increases in conjunction with community efforts to reduce neighborhood violence and problems.
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Affiliation(s)
- Kosuke Tamura
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA.
| | | | - Stephanie L Orstad
- Department of Medicine, Division of General Internal Medicine and Clinical Innovation, New York University Grossman School of Medicine, New York, NY, USA
| | - Sam J Neally
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Marcus R Andrews
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Joniqua N Ceasar
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jae E Lee
- Research Centers in Minority Institutions Translational Research Network Data Coordinating Center, Jackson State University, Jackson, MS, USA
| | - Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20892, USA
- Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
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