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Hajj J, Schneider ALC, Jacoby D, Schreiber J, Nolfi D, Turk MT. Associations of Neighborhood Environments and Socioeconomic Status With Subclinical Atherosclerosis: An Integrative Review. J Cardiovasc Nurs 2024:00005082-990000000-00216. [PMID: 39148151 DOI: 10.1097/jcn.0000000000001125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
BACKGROUND A limited understanding exists on the associations of neighborhood environment with subclinical atherosclerosis and its progression. PURPOSE The purpose of this integrative review was to explore associations of neighborhood environments and socioeconomic status (SES) with subclinical atherosclerosis and its long-term progression. RESULTS Three themes were identified: environmental exposure affects the natural history of atherosclerosis, neighborhood characteristics are associated with subclinical atherosclerosis, and individual SES is associated with development and progression of subclinical atherosclerosis more so than neighborhood SES. Some variations in results were noted based on the vascular site examined. CLINICAL IMPLICATIONS Disadvantaged neighborhoods and low SES are associated with greater subclinical atherosclerosis. Inconsistencies in a few studies seemed to be related to lack of coronary artery progression among the relatively young adults. This suggests further examination is needed of the contextual associations of neighborhood and SES with markers of generalized atherosclerosis, such as carotid intima-media thickness.
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Osude N, Pagidipati NJ. A New Age for Secondary Prevention: Optimal Medical Therapy for Stable Ischemic Heart Disease Among Patients with Diabetes and/or Obesity. Med Clin North Am 2024; 108:469-487. [PMID: 38548458 DOI: 10.1016/j.mcna.2023.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Patients with type 2 diabetes and/or obesity and established cardiovascular disease are at increased risk for recurrent cardiovascular events. The indications of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors have been expanded in the last decade due to benefit in cardiovascular outcome trials and are now considered guideline-recommended therapy for patients with type 2 diabetes and cardiovascular disease. Emerging data have begun to suggest that GLP-1RAs can decrease major adverse cardiovascular events among patients with obesity without diabetes. Overall, prescription of these agents remains low, despite being key to improve disparities in recurrent cardiovascular events. In this review, we discuss optimal medical therapy for secondary prevention for stable ischemic heart disease.
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Affiliation(s)
- Nkiru Osude
- Cardiovascular Division, Duke University, 2301 Erwin Road, Durham, NC 27710, USA.
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Kähönen E, Korpimäki S, Juonala M, Kähönen M, Lehtimäki T, Hutri-Kähönen N, Raitakari OT, Kivimäki M, Vahtera J. Neighbourhood deprivation in childhood and adulthood and risk of arterial stiffness: the Cardiovascular Risk in Young Finns study. Blood Press 2023; 32:2220037. [PMID: 37300298 DOI: 10.1080/08037051.2023.2220037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/09/2023] [Accepted: 05/25/2023] [Indexed: 06/12/2023]
Abstract
Purpose: Individual socioeconomic status is associated with increased arterial stiffness, but limited data are available on the relations of neighbourhood deprivation with this vascular measure. We prospectively examined whether neighbourhood deprivation in childhood and adulthood predicts arterial stiffness indicated by pulse wave velocity (PWV).Materials and methods: The study population comprised 1,761 participants aged 3-18 years at baseline (1980) from the longitudinal Cardiovascular Risk in Young Finns cohort study. PWV was measured in 2007 by whole-body impedance cardiography at ages 30-45 years. Cumulative lifetime neighbourhood deprivation was assessed using data from socioeconomic circumstances in participants' lifetime residential neighbourhoods, categorised as low versus high deprivation.Results: High deprivation in childhood and adulthood was associated with higher PWV in adulthood after adjustment for age, sex, and place of birth (mean difference = 0.57 m/s, 95%CI = 0.26-0.88, P for trend = 0.0004). This association was attenuated but remained statistically significant after further adjustment for childhood parental socioeconomic status and adulthood individual socioeconomic status (mean difference = 0.37 m/s, 95%CI = 0.05-0.70, P for trend 0.048). Also, low individual socioeconomic status in adulthood was associated with higher PWV when adjusted for age, sex, place of birth, parental socioeconomic status in childhood, and lifetime neighbourhood deprivation (mean difference = 0.54 m/s, 95%CI = 0.23-0.84, P for trend 0.0001).Conclusion: These findings suggest that lifetime neighbourhood deprivation and low adulthood socioeconomic status are independent risk factors for increased arterial stiffness in adulthood.
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Affiliation(s)
- Erika Kähönen
- Department of Clinical Physiology and Nuclear Medicine, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Satu Korpimäki
- Department of Clinical Physiology and Nuclear Medicine, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Markus Juonala
- Department of Medicine, Division of Medicine, University of Turku, Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology and Nuclear Medicine, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, Finland
- Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, Finland
| | - Terho Lehtimäki
- Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, Finland
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Mika Kivimäki
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- UCL Brain Sciences, University College London, London, United Kingdom
| | - Jussi Vahtera
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland
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Chu DY, Adluru N, Nair VA, Choi T, Adluru A, Garcia-Ramos C, Dabbs K, Mathis J, Nencka AS, Gundlach C, Conant L, Binder JR, Meyerand ME, Alexander AL, Struck AF, Hermann B, Prabhakaran V. Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy. Epilepsia 2023; 64:2484-2498. [PMID: 37376741 PMCID: PMC10530287 DOI: 10.1111/epi.17702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 06/25/2023] [Accepted: 06/26/2023] [Indexed: 06/29/2023]
Abstract
OBJECTIVE Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality. METHODS Participants including 74 TLE patients (47 male, mean age = 39.2 years) and 45 healthy controls (27 male, mean age = 31.9 years) from the Epilepsy Connectome Project were classified into ADI-defined low and high disadvantage groups. Graph theoretic metrics were applied to multishell connectome diffusion-weighted imaging (DWI) measurements to derive 162 × 162 structural connectivity matrices (SCMs). The SCMs were harmonized using neuroCombat to account for interscanner differences. Threshold-free network-based statistics were used for analysis, and findings were correlated with ADI quintile metrics. A decrease in cross-sectional area (CSA) indicates reduced white matter integrity. RESULTS Sex- and age-adjusted CSA in TLE groups was significantly reduced compared to controls regardless of disadvantage status, revealing discrete aberrant white matter tract connectivity abnormalities in addition to apparent differences in graph measures of connectivity and network-based statistics. When comparing broadly defined disadvantaged TLE groups, differences were at trend level. Sensitivity analyses of ADI quintile extremes revealed significantly lower CSA in the most compared to least disadvantaged TLE group. SIGNIFICANCE Our findings demonstrate (1) the general impact of TLE on DWI connectome status is larger than the association with neighborhood disadvantage; however, (2) neighborhood disadvantage, indexed by ADI, revealed modest relationships with white matter structure and integrity on sensitivity analysis in TLE. Further studies are needed to explore this relationship and determine whether the white matter relationship with ADI is driven by social drift or environmental influences on brain development. Understanding the etiology and course of the disadvantage-brain integrity relationship may serve to inform care, management, and policy for patients.
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Affiliation(s)
- Daniel Y Chu
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Nagesh Adluru
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Veena A Nair
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Timothy Choi
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Anusha Adluru
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Camille Garcia-Ramos
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Kevin Dabbs
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Jedidiah Mathis
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Andrew S Nencka
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Carson Gundlach
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Lisa Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Mary E Meyerand
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Andrew L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Aaron F Struck
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- William S. Middleton Veterans Hospital, Madison, Wisconsin, USA
| | - Bruce Hermann
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Vivek Prabhakaran
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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Fukuda H, Hyohdoh Y, Ninomiya H, Ueba Y, Ohta T, Kawanishi Y, Kadota T, Hamada F, Fukui N, Nonaka M, Kawada K, Fukuda M, Nishimoto Y, Matsushita N, Nojima Y, Kida N, Hayashi S, Izumidani T, Nishimura H, Moriki A, Ueba T. Impact of areal socioeconomic status on prehospital delay of acute ischaemic stroke: retrospective cohort study from a prefecture-wide survey in Japan. BMJ Open 2023; 13:e075612. [PMID: 37620264 PMCID: PMC10450073 DOI: 10.1136/bmjopen-2023-075612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/09/2023] [Indexed: 08/26/2023] Open
Abstract
OBJECTIVES To examine whether the Areal Deprivation Index (ADI), an indicator of the socioeconomic status of the community the patient resides in, is associated with delayed arrival at the hospital and poor outcomes in patients with acute ischaemic stroke from a prefecture-wide stroke database in Japan. DESIGN Retrospective study. SETTING Twenty-nine acute stroke hospitals in Kochi prefecture, Japan. PARTICIPANTS Nine thousand and six hundred fifty-one patients with acute ischaemic stroke who were urgently hospitalised, identified using the Kochi Acute Stroke Survey of Onset registry. Capital and non-capital areas were analysed separately. PRIMARY AND SECONDARY OUTCOME MEASURES Prehospital delay defined as hospital arrival ≥4-hour after stroke onset, poor hospital outcomes (in-hospital mortality and discharge to a nursing facility) and the opportunities of intravenous recombinant tissue plasminogen activator (rt-PA) and endovascular reperfusion therapy. RESULTS In the overall cohort, prehospital delay was observed in 6373 (66%) patients. Among individuals residing in non-capital areas, those living in municipalities with higher ADI (more deprived) carried a significantly higher risk of prehospital delay (per one-point increase, OR (95% CI) 1.45 (1.26 to 1.66)) by multivariable logistic regression analysis. In-hospital mortality (1.45 (1.02 to 2.06)), discharge to a nursing facility (1.31 (1.03 to 1.66)), and delayed candidate arrival ≥2-hour of intravenous rt-PA (2.04 (1.30 to 3.26)) and endovascular reperfusion therapy (2.27 (1.06 to 5.00)), were more likely to be observed in the deprived areas with higher ADI. In the capital areas, postal-code-ADI was not associated with prehospital delay (0.97 (0.66 to 1.41)). CONCLUSIONS Living in socioeconomically disadvantaged municipalities was associated with prehospital delays of acute ischaemic stroke in non-capital areas in Kochi prefecture, Japan. Poorer outcomes of those patients may be caused by delayed treatment of intravenous rt-PA and endovascular reperfusion therapy. Further studies are necessary to determine social risk factors in the capital areas. TRIAL REGISTRATION NUMBER This article is linked to a clinical trial to UMIN000050189, No.: R000057166 and relates to its Result stage.
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Affiliation(s)
- Hitoshi Fukuda
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Yuki Hyohdoh
- Centre of Medical Information Science, Kochi University, Kochi, Japan
| | - Hitoshi Ninomiya
- Department of Integrated Centre for Advanced Medical Technologies, Kochi Medical School Hospital, Nankoku, Japan
| | - Yusuke Ueba
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Tsuyoshi Ohta
- Department of Neurosurgery, Kochi Health Sciences Centre, Kochi, Japan
| | - Yu Kawanishi
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Tomohito Kadota
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Fumihiro Hamada
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Naoki Fukui
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Motonobu Nonaka
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
| | - Kei Kawada
- Department of Pharmacy, Kochi Medical School Hospital, Nankoku, Japan
| | - Maki Fukuda
- Department of Neurosurgery, Kochi Health Sciences Centre, Kochi, Japan
| | - Yo Nishimoto
- Department of Neurosurgery, Chikamori Hospital, Kochi, Japan
| | | | - Yuji Nojima
- Department of Neurosurgery, Hata Kenmin Hospital, Sukumo, Japan
| | - Namito Kida
- Department of Neurosurgery, Aki General Hospital, Kochi, Japan
| | - Satoru Hayashi
- Department of Neurosurgery, Chikamori Hospital, Kochi, Japan
| | | | | | - Akihito Moriki
- Department of Neurosurgery, Mominoki Hospital, Kochi, Japan
| | - Tetsuya Ueba
- Department of Neurosurgery, Kochi Medical School Hospital, Nankoku, Japan
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Towfighi A, Berger RP, Corley AMS, Glymour MM, Manly JJ, Skolarus LE. Recommendations on Social Determinants of Health in Neurologic Disease. Neurology 2023; 101:S17-S26. [PMID: 37580147 DOI: 10.1212/wnl.0000000000207562] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 05/09/2023] [Indexed: 08/16/2023] Open
Abstract
Social determinants of health (SDOH) are increasingly recognized as important drivers of inequities in neurologic disease and outcomes. However, our understanding of the biopsychosocial mechanisms by which SDOH affect neurologic disease remains in its infancy. The most robust epidemiologic research has been on the associations between education, schooling, and place-based social determinants on cognition, dementia, and cerebrovascular disease later in life. Further research is needed to more deeply understand the complex interplay of SDOH on neurologic disease. Few SDOH screening tools have been validated in populations with neurologic disease. In addition, comparison across studies and populations is hampered by lack of standardized common data elements. Experiences of populations historically underrepresented in research should be centered in future research studies, and changes should be made in recruitment expectations and measurement choices. For research on inequities, it is critical to support and incentivize institutional infrastructure to foster meaningful engagement with populations affected by research. Finally, it remains to be seen whether individual-level health or behavioral interventions or place-level, systemic or policy interventions to reduce population burden will be most effective in reducing inequities in neurologic disease and outcomes. Although numerous clinical trials have focused on addressing downstream SDOH such as health literacy and health behaviors (e.g., medication adherence, physical activity, diet), few have addressed upstream, structural determinants which may have a more profound impact on addressing inequities in neurologic disease. Ultimately, further research is needed to determine which specific SDOH should be targeted and how, when, and by whom they should be addressed to improve neurologic outcomes.
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Affiliation(s)
- Amytis Towfighi
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL.
| | - Rachel P Berger
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL
| | - Alexandra M S Corley
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL
| | - M Maria Glymour
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL
| | - Jennifer J Manly
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL
| | - Lesli E Skolarus
- From the Departments of Neurology and Population and Public Health Sciences (A.T.), University of Southern California, Los Angeles; Department of Pediatrics (R.P.B.), Children's Hospital of Pittsburgh, University of Pittsburg Medical Center (UPMC), PA; Division of General and Community Pediatrics (A.M.S.C.), Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, OH; The Center for Health and Community (M.M.G.), University of California, San Francisco; Department of Neurology (J.J.M.), Vagelos College of Physicians and Surgeons, Columbia University, New York; and Department of Neurology (L.S.), Northwestern University, Chicago, IL
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Wong MS, Brown AF, Washington DL. Inclusion of Race and Ethnicity With Neighborhood Socioeconomic Deprivation When Assessing COVID-19 Hospitalization Risk Among California Veterans Health Administration Users. JAMA Netw Open 2023; 6:e231471. [PMID: 36867407 PMCID: PMC9984969 DOI: 10.1001/jamanetworkopen.2023.1471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/04/2023] Open
Abstract
IMPORTANCE Despite complexities of racial and ethnic residential segregation (hereinafter referred to as segregation) and neighborhood socioeconomic deprivation, public health studies, including those on COVID-19 racial and ethnic disparities, often rely on composite neighborhood indices that do not account for residential segregation. OBJECTIVE To examine the associations by race and ethnicity among California's Healthy Places Index (HPI), Black and Hispanic segregation, Social Vulnerability Index (SVI), and COVID-19-related hospitalization. DESIGN, SETTING, AND PARTICIPANTS This cohort study included veterans with positive test results for COVID-19 living in California who used Veterans Health Administration services between March 1, 2020, and October 31, 2021. MAIN OUTCOMES AND MEASURES Rates of COVID-19-related hospitalization among veterans with COVID-19. RESULTS The sample available for analysis included 19 495 veterans with COVID-19 (mean [SD] age, 57.21 [17.68] years), of whom 91.0% were men, 27.7% were Hispanic, 16.1% were non-Hispanic Black, and 45.0% were non-Hispanic White. For Black veterans, living in lower-HPI (ie, less healthy) neighborhoods was associated with higher rates of hospitalization (odds ratio [OR], 1.07 [95% CI, 1.03-1.12]), even after accounting for Black segregation (OR, 1.06 [95% CI, 1.02-1.11]). Among Hispanic veterans, living in lower-HPI neighborhoods was not associated with hospitalization with (OR, 1.04 [95% CI, 0.99-1.09]) and without (OR, 1.03 [95% CI, 1.00-1.08]) Hispanic segregation adjustment. For non-Hispanic White veterans, lower HPI was associated with more frequent hospitalization (OR, 1.03 [95% CI, 1.00-1.06]). The HPI was no longer associated with hospitalization after accounting for Black (OR, 1.02 [95% CI, 0.99-1.05]) or Hispanic (OR, 0.98 [95% CI, 0.95-1.02]) segregation. Hospitalization was higher for White (OR, 4.42 [95% CI, 1.62-12.08]) and Hispanic (OR, 2.90 [95% CI, 1.02-8.23]) veterans living in neighborhoods with greater Black segregation and for White veterans in more Hispanic-segregated neighborhoods (OR, 2.81 [95% CI, 1.96-4.03]), adjusting for HPI. Living in higher SVI (ie, more vulnerable) neighborhoods was associated with greater hospitalization for Black (OR, 1.06 [95% CI, 1.02-1.10]) and non-Hispanic White (OR, 1.04 [95% CI, 1.01-1.06]) veterans. CONCLUSIONS AND RELEVANCE In this cohort study of US veterans with COVID-19, HPI captured neighborhood-level risk for COVID-19-related hospitalization for Black, Hispanic, and White veterans comparably with SVI. These findings have implications for the use of HPI and other composite neighborhood deprivation indices that do not explicitly account for segregation. Understanding associations between place and health requires ensuring composite measures accurately account for multiple aspects of neighborhood deprivation and, importantly, variation by race and ethnicity.
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Affiliation(s)
- Michelle S. Wong
- Veterans Affairs (VA) Health Services Research and Development Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California
| | - Arleen F. Brown
- Division of General Internal Medicine and Health Services Research, Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles (UCLA)
- Olive View–UCLA Medical Center, Sylmar, California
| | - Donna L. Washington
- Veterans Affairs (VA) Health Services Research and Development Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California
- Division of General Internal Medicine and Health Services Research, Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles (UCLA)
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Alvarado F, Hercules A, Wanigatunga M, Laurent J, Payne M, Allouch F, Crews DC, Mills KT, He J, Gustat J, Ferdinand KC. Influence of neighborhood-level social determinants of health on a heart-healthy lifestyle among Black church members: A mixed-methods study. AMERICAN HEART JOURNAL PLUS : CARDIOLOGY RESEARCH AND PRACTICE 2023; 27:100273. [PMID: 38511101 PMCID: PMC10946005 DOI: 10.1016/j.ahjo.2023.100273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 02/13/2023] [Accepted: 02/13/2023] [Indexed: 03/22/2024]
Abstract
Background Few church-based health interventions have evaluated the influence of neighborhood-level social determinants of health (SDOH) on adopting heart-healthy lifestyles; none has occurred in Louisiana. We aimed to characterize neighborhood-level SDOH that may influence the ability to adopt a heart-healthy lifestyle among Black community church members in New Orleans, LA. Methods This mixed methods study used quantitative data (surveys) and qualitative data (focus groups) to explore SDOH at the neighborhood- and church-area- level, including factors related to the physical (e.g., walkability, accessibility to recreational facilities) and social (e.g., social cohesion, perceived safety) environments. Descriptive analyses were conducted for quantitative data. Qualitative data were coded and analyzed using grounded theory and thematic analysis. Results Among survey respondents (n = 302, 77 % female, 99 % Black), most reported having walkable neighborhood sidewalks and high neighborhood social cohesion. Two-thirds did not feel violence was a problem in their neighborhood and felt safe walking, day, or night. Focus group participants (n = 27, 74 % female, 100 % Black) reported facilitators to heart-healthy living, including social support promoting physical activity, intentionality in growing, buying, and preparing produce, and the neighborhood-built environment. Reported barriers included: crime, the COVID-19 pandemic, individual-level factors limiting physical activity, and city-wide disparities influencing health. Participants discussed strategies to promote healthy living, centered around the theme of establishing and rebuilding community relationships. Conclusions Future health interventions aimed at improving cardiovascular outcomes among church communities should continue to inquire about neighborhood-level SDOH and tailor interventions, as appropriate, to address barriers and leverage facilitators within these communities.
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Affiliation(s)
- Flor Alvarado
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA 70112, USA
| | - Amanda Hercules
- Department of Health Policy and Management, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Melanie Wanigatunga
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA 70112, USA
| | - Jodie Laurent
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Marilyn Payne
- Payne and Associates Counseling and Consulting Services, 2371 Lark St, New Orleans, LA, USA
| | - Farah Allouch
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Deidra C. Crews
- Department of Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - Katherine T. Mills
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Jeanette Gustat
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street, Ste 2001, New Orleans, LA 70112, USA
| | - Keith C. Ferdinand
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA 70112, USA
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Favorable Neighborhood Walkability is Associated With Lower Burden of Cardiovascular Risk Factors Among Patients Within an Integrated Health System: The Houston Methodist Learning Health System Outpatient Registry. Curr Probl Cardiol 2023; 48:101642. [PMID: 36773946 DOI: 10.1016/j.cpcardiol.2023.101642] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 02/04/2023] [Indexed: 02/12/2023]
Abstract
This is the first study to investigate the relationship between neighborhood walkability and cardiovascular (CV) risk factors in the United States using a large population-based database. Cross-sectional study using data from 1.1 million patients over the age of 18 in the Houston Methodist Learning Health System Outpatient Registry (2016-2022). Using the 2019 WalkScore, patients were assigned to one of the 4 neighborhood walkability categories. The burden of CV risk factors (hypertension, diabetes, obesity, dyslipidemia, and smoking) was defined as poor, average, or optimal (>3, 1-2, 0 risk factors, respectively). We included 887,654 patients, of which 86% resided in the two least walkable neighborhoods. The prevalence of CV risk factors was significantly lower among participants in the most walkable neighborhoods irrespective of ASCVD status. After adjusting for age, sex, race/ethnicity, and socioeconomic factors, we found that adults living in the most walkable neighborhoods were more likely to have optimal CV risk profile than those in the least walkable ones (RRR 2.77, 95% CI 2.64-2.91). We observed an inverse association between neighborhood walkability and the burden of CV risk factors. These findings support multilevel health system stakeholder engagements and investments in walkable neighborhoods as a viable tool for mitigating the growing burden of modifiable CV risk factors.
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Henderson K, Kaufman B, Rotter JS, Stearns S, Sueta CAA, Foraker R, Ho PM, Chang PP. Socioeconomic status and modification of atherosclerotic cardiovascular disease risk prediction: epidemiological analysis using data from the atherosclerosis risk in communities study. BMJ Open 2022; 12:e058777. [PMID: 36343998 PMCID: PMC9644311 DOI: 10.1136/bmjopen-2021-058777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE Examine whether the relationship between the pooled cohort equations (PCE) predicted 10-year risk for atherosclerotic cardiovascular disease (ASCVD) and absolute risk for ASCVD is modified by socioeconomic status (SES). DESIGN Population-based longitudinal cohort study-Atherosclerosis Risk in Communities (ARIC)-investigating the development of cardiovascular disease across demographic subgroups. SETTING Four communities in the USA-Forsyth County, North Carolina, Jackson, Mississippi, suburbs of Minneapolis, Minnesota and Washington County, Maryland. PARTICIPANTS We identified 9782 ARIC men and women aged 54-73 without ASCVD at study visit 4 (1996-1998). PRIMARY OUTCOME MEASURES Risk ratio (RR) differences in 10-year incident hospitalisations or death for ASCVD by SES and PCE predicted 10-year ASCVD risk categories to assess for risk modification. SES measures included educational attainment and census-tract neighbourhood deprivation using the Area Deprivation Index. PCE risk categories were 0%-5%, >5%-10%, >10%-15% and >15%. SES as a prognostic factor to estimate ASCVD absolute risk categories was further investigated as an interaction term with the PCE. RESULTS ASCVD RRs for participants without a high school education (referent college educated) increased at higher PCE estimated risk categories and was consistently >1. Results indicate education is both a risk modifier and delineates populations at higher ASCVD risk independent of PCE. Neighbourhood deprivation did modify association but was less consistent in direction of effect. However, for participants residing in the most deprived neighbourhoods (referent least deprived neighbourhoods) with a PCE estimated risk >10%-15%, risk was significantly elevated (RR 1.65, 95% CI 1.05 to 2.59). Education and neighbourhood deprivation inclusion as an interaction term on the PCE risk score was statistically significant (likelihood ratio p≤0.0001). CONCLUSIONS SES modifies the association between PCE estimated risk and absolute risk of ASCVD. SES added into ASCVD risk prediction models as an interaction term may improve our ability to predict absolute ASCVD risk among socially disadvantaged populations.
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Affiliation(s)
- Kamal Henderson
- Cardiology Section, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA
- Department of Cardiology, University of Colorado Denver School of Medicine, Aurora, Colorado, USA
| | - Brystana Kaufman
- Department of Population Health Sciences, Duke University, Durham, North Carolina, USA
| | - Jason S Rotter
- Mathematica Policy Research Inc, Washington, District of Columbia, USA
| | - Sally Stearns
- Health Policy & Management, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - Carla A A Sueta
- Department of Cardiology, University of North Carolina, School of Medicine, Chapel Hill, North Carolina, USA
| | - Randi Foraker
- Division of General Medical Sciences, Washington University, School of Medicine, St Louis, Missouri, USA
- Brown School of Public Health, Washington University, St Louis, MO, USA
| | - P Michael Ho
- Cardiology Section, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA
- Department of Cardiology, University of Colorado Denver School of Medicine, Aurora, Colorado, USA
| | - Patricia P Chang
- Department of Cardiology, University of North Carolina, School of Medicine, Chapel Hill, North Carolina, USA
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Xiao Q, Heiss G, Kucharska-Newton A, Bey G, Love SAM, Whitsel EA. Life-Course Neighborhood Socioeconomic Status and Cardiovascular Events in Black and White Adults in the Atherosclerosis Risk in Communities Study. Am J Epidemiol 2022; 191:1470-1484. [PMID: 35419583 PMCID: PMC9989355 DOI: 10.1093/aje/kwac070] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 03/24/2022] [Accepted: 04/05/2022] [Indexed: 01/28/2023] Open
Abstract
It has been reported that residents of low-socioeconomic-status (SES) neighborhoods have a higher risk of developing cardiovascular disease (CVD). However, most of the previous studies focused on 1-time measurement of neighborhood SES in middle-to-older adulthood and lacked demographic diversity to allow for comparisons across different race/ethnicity and sex groups. We examined neighborhood SES in childhood and young, middle, and older adulthood in association with CVD risk among Black and White men and women in the Atherosclerosis Risk in Communities Study (1996-2019). We found that lower neighborhood SES in young, middle, and older adulthood, but not in childhood, was associated with a higher risk of CVD later in life. When compared with the highest quartile, the lowest quartile of neighborhood SES in young, middle, and older adulthood was associated with 18% (hazard ratio (HR) = 1.18, 95% confidence interval (CI): 1.02, 1.36), 21% (HR = 1.21, 95% CI: 1.04, 1.39), and 12% (HR = 1.12, 95% CI: 0.99, 1.26) increases in the hazard of total CVD, respectively. The association between lower neighborhood SES in older adulthood and higher CVD hazard was particularly strong among Black women. Our study findings support the role of neighborhood SES in cardiovascular health in both Black and White adults.
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Affiliation(s)
- Qian Xiao
- Correspondence to Dr. Qian Xiao, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77225 (e-mail: )
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12
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Yadav RS, Chaudhary D, Avula V, Shahjouei S, Azarpazhooh MR, Abedi V, Li J, Zand R. Social Determinants of Stroke Hospitalization and Mortality in United States' Counties. J Clin Med 2022; 11:jcm11144101. [PMID: 35887865 PMCID: PMC9320068 DOI: 10.3390/jcm11144101] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/29/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022] Open
Abstract
(1) Background: Stroke incidence and outcomes are influenced by socioeconomic status. There is a paucity of reported population-level studies regarding these determinants. The goal of this ecological analysis was to determine the county-level associations of social determinants of stroke hospitalization and death rates in the United States. (2) Methods: Publicly available data as of 9 April 2021, for the socioeconomic factors and outcomes, was extracted from the Centers for Disease Control and Prevention. The outcomes of interest were “all stroke hospitalization rates per 1000 Medicare beneficiaries” (SHR) and “all stroke death rates per 100,000 population” (SDR). We used a multivariate binomial generalized linear mixed model after converting the outcomes to binary based on their median values. (3) Results: A total of 3226 counties/county-equivalents of the states and territories in the US were analyzed. Heart disease prevalence (odds ratio, OR = 2.03, p < 0.001), blood pressure medication nonadherence (OR = 2.02, p < 0.001), age-adjusted obesity (OR = 1.24, p = 0.006), presence of hospitals with neurological services (OR = 1.9, p < 0.001), and female head of household (OR = 1.32, p = 0.021) were associated with high SHR while cost of care per capita for Medicare patients with heart disease (OR = 0.5, p < 0.01) and presence of hospitals (OR = 0.69, p < 0.025) were associated with low SHR. Median household income (OR = 0.6, p < 0.001) and park access (OR = 0.84, p = 0.016) were associated with low SDR while no college degree (OR = 1.21, p = 0.049) was associated with high SDR. (4) Conclusions: Several socioeconomic factors (e.g., education, income, female head of household) were found to be associated with stroke outcomes. Additional research is needed to investigate intermediate and potentially modifiable factors that can serve as targeted interventions.
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Affiliation(s)
- Randhir Sagar Yadav
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA; (R.S.Y.); (D.C.); (S.S.)
- Department of Pediatrics, University of Florida College of Medicine, Jacksonville, FL 32207, USA
| | - Durgesh Chaudhary
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA; (R.S.Y.); (D.C.); (S.S.)
- Department of Neurology, Penn State Health Milton S. Hershey Medical Center, Hershey, PA 17033, USA
| | - Venkatesh Avula
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA 17822, USA; (V.A.); (J.L.)
| | - Shima Shahjouei
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA; (R.S.Y.); (D.C.); (S.S.)
| | - Mahmoud Reza Azarpazhooh
- Departments of Clinical Neurological Sciences and Epidemiology, University of Western Ontario, London, ON N6A 3K7, Canada;
| | - Vida Abedi
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA 17033, USA;
| | - Jiang Li
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, PA 17822, USA; (V.A.); (J.L.)
| | - Ramin Zand
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA; (R.S.Y.); (D.C.); (S.S.)
- Department of Neurology, Penn State Health Milton S. Hershey Medical Center, Hershey, PA 17033, USA
- Neuroscience Institute, The Pennsylvania State University, Hershey, PA 17033, USA
- Correspondence:
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13
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Liang LJ, Casillas A, Longstreth WT, PhanVo L, Vassar SD, Brown AF. Fishing for health: Neighborhood variation in fish intake, fish quality and association with stroke risk among older adults in the Cardiovascular Health Study. Nutr Metab Cardiovasc Dis 2022; 32:1410-1417. [PMID: 35346546 PMCID: PMC9472873 DOI: 10.1016/j.numecd.2022.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND AND AIMS Fish consumption has been associated with better health outcomes. Dietary patterns may vary substantially by neighborhood of residence. However, it is unclear if the benefits of a healthy diet are equivalent in different communities. This study examines associations of fish consumption with stroke incidence and stroke risk factors, and whether these differ by neighborhood socioeconomic status (NSES). METHODS AND RESULTS We studied 4007 participants in the Cardiovascular Health Study who were 65 years or older and recruited between 1989 and 1990 from 4 US communities. Outcomes included fish consumption type (bakes/broiled vs. fried) and frequency, stroke incidence, and stroke risk factors. Multilevel regressions models were used to estimate fish consumption associations with clinical outcomes. Lower NSES was associated with higher consumption of fried fish (aOR = 1.47, 95% CI: 1.10-1.98) and lower consumption of non-fried fish (0.64, 0.47-0.86). Frequent fried fish (11.9 vs. 9.2 person-years for at least once weekly vs. less than once a month, respectively) and less frequent non-fried fish (17.7 vs. 9.6 person-years for less than once a month vs. at least once weekly, respectively) were independently associated with an increased risk of stroke (p-values < 0.05). However, among those with similar levels of healthy fish consumption, residents with low NSES had less benefit on stroke risk reduction, compared with high NSES. CONCLUSION Fish consumption type and frequency both impact stroke risk. Benefits of healthy fish consumption differ by neighborhood socioeconomic status.
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Affiliation(s)
- Li-Jung Liang
- Division of General Internal Medicine and Health Services Research, University of California, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024, USA.
| | - Alejandra Casillas
- Division of General Internal Medicine and Health Services Research, University of California, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024, USA
| | - W T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, 908 Jefferson St, Seattle, WA 98104, USA
| | - Lynn PhanVo
- Division of General Internal Medicine and Health Services Research, University of California, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024, USA
| | - Stefanie D Vassar
- Division of General Internal Medicine and Health Services Research, University of California, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024, USA
| | - Arleen F Brown
- Division of General Internal Medicine and Health Services Research, University of California, 1100 Glendon Avenue, Suite 850, Los Angeles, CA 90024, USA
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14
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Santos CJ, Paciência I, Ribeiro AI. Neighbourhood Socioeconomic Processes and Dynamics and Healthy Ageing: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19116745. [PMID: 35682327 PMCID: PMC9180257 DOI: 10.3390/ijerph19116745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/26/2022] [Accepted: 05/30/2022] [Indexed: 02/05/2023]
Abstract
Elderly citizens are concentrated in urban areas and are particularly affected by the immediate residential environment. Cities are unequal and segregated places, where there is an intensification of urban change processes such as gentrification and displacement. We aimed to understand how neighbourhood socioeconomic processes and dynamics influence older people’s health. Three bibliographic databases—PubMed, Web of Science, and Scopus—were used to identify evidence of the influence of neighbourhood socioeconomic deprivation, socio-spatial segregation, urban renewal, and gentrification on healthy ageing. We followed the method of Arksey and O’Malley, Levac and colleagues, the Joanna Briggs Institute, and the PRISMA-ScR. The included studies (n = 122) were published between 2001 and 2021. Most evaluated neighbourhood deprivation (n = 114), followed by gentrification (n = 5), segregation (n = 2), and urban renewal (n = 1). Overall, older people living in deprived neighbourhoods had worse healthy ageing outcomes than their counterparts living in more advantaged neighbourhoods. Older adults pointed out more negative comments than positive ones for gentrification and urban renewal. As to segregation, the direction of the association was not entirely clear. In conclusion, the literature has not extensively analysed the effects of segregation, gentrification, and urban renewal on healthy ageing, and more quantitative and longitudinal studies should be conducted to draw better inferences.
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Affiliation(s)
- Cláudia Jardim Santos
- EPIUnit-Instituto de Saúde Pública, Universidade do Porto, 4050-600 Porto, Portugal;
- Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), 4050-600 Porto, Portugal
- Correspondence: ; Tel.: +351-222-061-820
| | - Inês Paciência
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, P.O. Box 5000, 90570 Oulu, Finland;
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90570 Oulu, Finland
| | - Ana Isabel Ribeiro
- EPIUnit-Instituto de Saúde Pública, Universidade do Porto, 4050-600 Porto, Portugal;
- Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), 4050-600 Porto, Portugal
- Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, Portugal
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15
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Rakhmatullin A, Kutlubaev M, Kutlubaeva R, Ozerova A. Socioeconomic factors and stroke. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:45-51. [DOI: 10.17116/jnevro202212203245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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16
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Stroke Disparities. Stroke 2022. [DOI: 10.1016/b978-0-323-69424-7.00015-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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17
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Mital R, Bayne J, Rodriguez F, Ovbiagele B, Bhatt DL, Albert MA. Race and Ethnicity Considerations in Patients With Coronary Artery Disease and Stroke: JACC Focus Seminar 3/9. J Am Coll Cardiol 2021; 78:2483-2492. [PMID: 34886970 DOI: 10.1016/j.jacc.2021.05.051] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 01/29/2023]
Abstract
Notable racial and ethnic differences and disparities exist in coronary artery disease (CAD) and stroke epidemiology and outcomes despite substantial advances in these fields. Racial and ethnic minority subgroups remain underrepresented in population data and clinical trials contributing to incomplete understanding of these disparities. Differences in traditional cardiovascular risk factors such as hypertension and diabetes play a role; however, disparities in care provision and process, social determinants of health including socioeconomic position, neighborhood environment, sociocultural factors, and racial discrimination within and outside of the health care system also drive racial and ethnic CAD and stroke disparities. Improved culturally congruent and competent communication about risk factors and symptoms is also needed. Opportunities to achieve improved and equitable outcomes in CAD and stroke must be identified and pursued.
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Affiliation(s)
- Rohit Mital
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Joseph Bayne
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Fatima Rodriguez
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine, Stanford University, Stanford, California, USA
| | - Bruce Ovbiagele
- Department of Neurology, University of California-San Francisco, San Francisco, California, USA
| | - Deepak L Bhatt
- Brigham and Women's Hospital Heart and Vascular Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Michelle A Albert
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology, Department of Medicine, University of California-San Francisco, San Francisco, California, USA.
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18
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Man S, Bruckman D, Tang AS, Uchino K, Schold JD. The Association of Socioeconomic Status and Discharge Destination with 30-Day Readmission after Ischemic Stroke. J Stroke Cerebrovasc Dis 2021; 30:106146. [PMID: 34644664 DOI: 10.1016/j.jstrokecerebrovasdis.2021.106146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/04/2021] [Accepted: 09/26/2021] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVES This study aimed to explore the association of socioeconomic status and discharge destination with 30-day readmission after ischemic stroke. MATERIALS AND METHODS We examined 30-day all-cause readmission among patients hospitalized for ischemic stroke in states of Arkansas, Iowa, and Wisconsin in 2016 and 2017 and New York in 2016 using Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases. RESULTS Among the 52301 patients included, 51.1% were female. The 30-day readmission rates were 10.2%, 8.2%, 9.3%, 10.4%, 11.6%, and 11.2% for age group 18-34, 35-44, 45-54, 55-64, 65-74, and ≥75 years, respectively (p<0.001). In Generalized Estimating Equation analysis, patients with Medicare and Medicaid insurance were more likely to be readmitted, compared with private insurance, (adjusted Odds Ratio [aOR] 1.37, 95% CI 1.23-1.53; and aOR 1.26, 95% CI 1.09-1.45, respectively). Patients in the bottom quartile of zip code level median household income had higher 30-day readmission rate (12.4%) than those in the 2nd, 3rd and 4th quartile (10.3%, 10.1%, and 10.7%, respectively, p<0.001). Compared with those discharged home with self-care which had the lowest readmission rate (8.4%), patients who left against medical advice had the highest readmission rate (18.6%; aOR 2.23, 95% CI 1.75-2.83), followed by rehabilitation and skilled nursing facilities (13.2%; aOR 1.33, 95% CI 1.22-1.46), and home with home health care (11.3%, aOR 1.18, 95% CI 1.08-1.28). CONCLUSIONS Socioeconomic status and discharged destination affect readmission after stroke. These results provide evidence to inform vulnerable patient population as targets for readmission prevention.
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Affiliation(s)
- Shumei Man
- Department of Neurology, Neurological Institute, Cleveland Clinic, United States; Cerebrovascular Center, Neurological Institute, Cleveland Clinic, United States.
| | - David Bruckman
- Center for Populations Health Research, Department of Quantitative Health Sciences, Cleveland Clinic, United States
| | - Anne S Tang
- Center for Populations Health Research, Department of Quantitative Health Sciences, Cleveland Clinic, United States
| | - Ken Uchino
- Cerebrovascular Center, Neurological Institute, Cleveland Clinic, United States
| | - Jesse D Schold
- Center for Populations Health Research, Department of Quantitative Health Sciences, Cleveland Clinic, United States
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Nezwek TA, Braun SV, Menendez ME, Grussing ED, Shabin ZM. Area Deprivation Index and Magnitude of Scoliosis at Presentation to a Tertiary Referral Scoliosis Clinic in Massachusetts. J Pediatr Orthop 2021; 41:e712-e716. [PMID: 34354029 DOI: 10.1097/bpo.0000000000001869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND There is growing interest in identifying predictors of large scoliosis curves at initial presentation, but few data to guide such preventive efforts. The association of neighborhood socioeconomic deprivation with curve magnitude in this context has not been previously evaluated. The purpose of our study was to determine the correlation of socioeconomic deprivation with scoliosis curve magnitude at initial presentation. Secondarily, we assessed the correlation of body mass index (BMI) with curve severity. METHODS We retrospectively identified 202 patients presenting with adolescent idiopathic scoliosis to a single tertiary care center in Massachusetts from January 2015 to August 2018. The Area Deprivation Index (ADI), a validated composite measure of neighborhood socioeconomic deprivation, was calculated for each patient. Curve magnitude, age, sex, BMI, race, and insurance status were recorded. Pearson correlation was used to determine the association of the ADI and BMI with scoliosis severity. RESULTS There was no correlation between the ADI and the magnitude of scoliosis at presentation (r=0.055; P=0.43). Greater BMI was moderately correlated with increased scoliosis curve magnitude (r=0.28; P<0.001). There was no association between curve magnitude and patient age, sex, race, or insurance status. CONCLUSIONS The finding that neighborhood socioeconomic deprivation did not correlate with greater scoliosis severity at presentation may be suggestive of equitable access to specialized scoliosis care. Future research should determine whether this reassuring finding is unique to Massachusetts--a state with high rates of health insurance coverage--or generalizable to other US states. In addition, our study further corroborates the notion that greater BMI is associated with larger scoliosis curves, and calls for targeted interventions to facilitate early scoliosis detection in the growing childhood obese population. LEVEL OF EVIDENCE Level II-prognostic study and retrospective study.
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Affiliation(s)
- Teron A Nezwek
- Department of Orthopaedic Surgery, Tufts Children's Hospital, Tufts University School of Medicine, Boston, MA
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Brooks MS, Bennett A, Lovasi GS, Hurvitz PM, Colabianchi N, Howard VJ, Manly J, Judd SE. Matching participant address with public records database in a US national longitudinal cohort study. SSM Popul Health 2021; 15:100887. [PMID: 34401464 PMCID: PMC8358447 DOI: 10.1016/j.ssmph.2021.100887] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/09/2021] [Accepted: 08/02/2021] [Indexed: 11/17/2022] Open
Abstract
Background Epidemiological studies utilize residential histories to assess environmental exposure risk. The validity from using commercially-sourced residential histories within national longitudinal studies remains unclear. Our study assessed predictors of non-agreement between baseline addresses from the commercially-sourced LexisNexis database and participants in the national longitudinal study, REasons for Geographic and Racial Differences in Stroke (REGARDS). Additionally, we assessed differences in stroke risk by neighborhood socioeconomic score (nSES) based on participant reported address compared to nSES from LexisNexis/REGARDS matched baseline address. Methods From January 2003–October 2007, REGARDS enrolled 30,239 black and white adults aged 45 and older within the continental United States and collected their baseline address. ArcGIS Desktop 10.5.1 with ESRI 2016 Business Analyst Data was used to geocode baseline addresses from LexisNexis and REGARDS. Logistic regression was used to estimate the likelihood that LexisNexis address matched REGARDS baseline address for each participant. Survival analysis was used to estimate association between nSES and incident stroke. Results Approximately 91% of REGARDS participants had a LexisNexis address. Of these geocoded addresses, 93% of REGARDS baseline addresses matched LexisNexis addresses. Odds of agreement between LexisNexis and REGARDS was higher for older-aged participants (OR = 1.02 per year, 95% CI: 1.01, 1.02), blacks compared to whites (OR = 1.16, 95% CI: 1.05, 1.29), females compared to males (OR = 1.15, 95% CI: 1.04, 1.26), participants with an income of $34k-74k compared to an income less than $20k (OR = 1.62, 95% CI: 1.39, 1.89). Odds of agreement were lower for residents in Midwest compared to residents in the south (OR = 0.82, 95% CI: 0.73, 0.94). No significant differences in nSES-stroke associations were observed between REGARDS only and LexisNexis/REGARDS matched addresses; however, differences in interactions were observed. Conclusion Agreement between LexisNexis and REGARDS addresses varied by sociodemographic groups, potentially introducing bias in studies reliant on LexisNexis alone for residential address data. Approximately 9% of REGARDS participants did not have a LexisNexis address history available. Of participants with both REGARDS and LexisNexis addresses available, 93% of these addresses matched. Agreement between REGARDS and LexisNexis address varied by socio-demographics—potentially biasing environmental exposures. Compared to LexisNexis, REGARDS addresses may be valuable in detecting interactions contributing to stroke disparities.
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Affiliation(s)
- Marquita S Brooks
- Department of Biostatistics, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Aleena Bennett
- Department of Biostatistics, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Gina S Lovasi
- Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Philip M Hurvitz
- Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA
| | - Natalie Colabianchi
- Environment and Policy Lab, University of Michigan School of Kinesiology, Ann Arbor, MI, USA
| | | | - Jennifer Manly
- Neurology at Gertrude H. Sergievsky Center and the Taub Institute for Research in Aging and Alzheimer's Disease, Columbia University, New York, NY, USA
| | - Suzanne E Judd
- Department of Biostatistics, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
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21
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Kim Y, Twardzik E, Judd SE, Colabianchi N. Neighborhood Socioeconomic Status and Stroke Incidence: A Systematic Review. Neurology 2021; 96:897-907. [PMID: 33766995 PMCID: PMC8166445 DOI: 10.1212/wnl.0000000000011892] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 02/02/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To summarize overall patterns of the impact of neighborhood socioeconomic status (nSES) on stroke incidence and uncover potential gaps in the literature, we conducted a systematic review of studies examining the association between nSES and stroke incidence, independent of individual SES. METHODS Four electronic databases and reference lists of included articles were searched, and corresponding authors were contacted to locate additional studies. A keyword search strategy included the 3 broad domains of neighborhood, SES, and stroke. Eight studies met our inclusion criteria (e.g., nSES as an exposure, individual SES as a covariate, and stroke incidence as an outcome). We coded study methodology and findings across the 8 studies. RESULTS The results provide evidence for the overall nSES and stroke incidence association in Sweden and Japan, but not within the United States. Findings were inconclusive when examining the nSES-stroke incidence association stratified by race. We found evidence for the mediating role of biological factors in the nSES-stroke incidence association. CONCLUSIONS Higher neighborhood disadvantage was found to be associated with higher stroke risk, but it was not significant in all the studies. The relationship between nSES and stroke risk within different racial groups in the United States was inconclusive. Inconsistencies may be driven by differences in covariate adjustment (e.g., individual-level sociodemographic characteristics and neighborhood-level racial composition). Additional research is needed to investigate potential intermediate and modifiable factors of the association between nSES and stroke incidence, which could serve as intervention points.
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Affiliation(s)
- Yeonwoo Kim
- From the Department of Kinesiology (Y.K.), University of Texas at Arlington, TX; School of Kinesiology (E.T.), University of Michigan, MI; Department of Biostatistics (S.E.J.), University of Alabama at Birmingham, AL; School of Kinesiology (N.C.), University of Michigan, MI
| | - Erica Twardzik
- From the Department of Kinesiology (Y.K.), University of Texas at Arlington, TX; School of Kinesiology (E.T.), University of Michigan, MI; Department of Biostatistics (S.E.J.), University of Alabama at Birmingham, AL; School of Kinesiology (N.C.), University of Michigan, MI
| | - Suzanne E Judd
- From the Department of Kinesiology (Y.K.), University of Texas at Arlington, TX; School of Kinesiology (E.T.), University of Michigan, MI; Department of Biostatistics (S.E.J.), University of Alabama at Birmingham, AL; School of Kinesiology (N.C.), University of Michigan, MI
| | - Natalie Colabianchi
- From the Department of Kinesiology (Y.K.), University of Texas at Arlington, TX; School of Kinesiology (E.T.), University of Michigan, MI; Department of Biostatistics (S.E.J.), University of Alabama at Birmingham, AL; School of Kinesiology (N.C.), University of Michigan, MI.
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Ejike CO, Woo H, Galiatsatos P, Paulin LM, Krishnan JA, Cooper CB, Couper DJ, Kanner RE, Bowler RP, Hoffman EA, Comellas AP, Criner GJ, Barr RG, Martinez FJ, Han MK, Martinez CH, Ortega VE, Parekh TM, Christenson SA, Thakur N, Baugh A, Belz DC, Raju S, Gassett AJ, Kaufman JD, Putcha N, Hansel NN. Contribution of Individual and Neighborhood Factors to Racial Disparities in Respiratory Outcomes. Am J Respir Crit Care Med 2021; 203:987-997. [PMID: 33007162 DOI: 10.1164/rccm.202002-0253oc] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Rationale: Black adults have worse health outcomes compared with white adults in certain chronic diseases, including chronic obstructive pulmonary disease (COPD).Objectives: To determine to what degree disadvantage by individual and neighborhood socioeconomic status (SES) may contribute to racial disparities in COPD outcomes.Methods: Individual and neighborhood-scale sociodemographic characteristics were determined in 2,649 current or former adult smokers with and without COPD at recruitment into SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). We assessed whether racial differences in symptom, functional, and imaging outcomes (St. George's Respiratory Questionnaire, COPD Assessment Test score, modified Medical Research Council dyspnea scale, 6-minute-walk test distance, and computed tomography [CT] scan metrics) and severe exacerbation risk were explained by individual or neighborhood SES. Using generalized linear mixed model regression, we compared respiratory outcomes by race, adjusting for confounders and individual-level and neighborhood-level descriptors of SES both separately and sequentially.Measurements and Main Results: After adjusting for COPD risk factors, Black participants had significantly worse respiratory symptoms and quality of life (modified Medical Research Council scale, COPD Assessment Test, and St. George's Respiratory Questionnaire), higher risk of severe exacerbations and higher percentage of emphysema, thicker airways (internal perimeter of 10 mm), and more air trapping on CT metrics compared with white participants. In addition, the association between Black race and respiratory outcomes was attenuated but remained statistically significant after adjusting for individual-level SES, which explained up to 12-35% of racial disparities. Further adjustment showed that neighborhood-level SES explained another 26-54% of the racial disparities in respiratory outcomes. Even after accounting for both individual and neighborhood SES factors, Black individuals continued to have increased severe exacerbation risk and persistently worse CT outcomes (emphysema, air trapping, and airway wall thickness).Conclusions: Disadvantages by individual- and neighborhood-level SES each partly explain disparities in respiratory outcomes between Black individuals and white individuals. Strategies to narrow the gap in SES disadvantages may help to reduce race-related health disparities in COPD; however, further work is needed to identify additional risk factors contributing to persistent disparities.
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Affiliation(s)
- Chinedu O Ejike
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Han Woo
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Panagis Galiatsatos
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Laura M Paulin
- Section of Pulmonary and Critical Care, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine, Hanover, New Hampshire
| | - Jerry A Krishnan
- Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois, Chicago, Illinois
| | - Christopher B Cooper
- Department of Medicine and.,Department of Physiology, University of California, Los Angeles, School of Medicine, Los Angeles, California
| | - David J Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Richard E Kanner
- Division of Pulmonary and Critical Care, University of Utah School of Medicine, Salt Lake City, Utah
| | - Russell P Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, Colorado
| | - Eric A Hoffman
- Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Gerard J Criner
- Division of Pulmonary and Critical Care, Temple University Hospital, Philadelphia, Pennsylvania
| | - R Graham Barr
- Division of Pulmonary, Allergy and Critical Care Medicine, Presbyterian Hospital, Columbia University Medical Center, New York, New York
| | - Fernando J Martinez
- Department of Internal Medicine, Weill Cornell Medical College, New York, New York
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, Michigan
| | - Carlos H Martinez
- Division of Pulmonary and Critical Care, Oaklawn Hospital, Marshall, Michigan
| | - Victor E Ortega
- Center for Genomics and Personalized Medicine Research, Wake Forest University, Winston-Salem, North Carolina
| | - Trisha M Parekh
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Stephanie A Christenson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California; and
| | - Neeta Thakur
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California; and
| | - Aaron Baugh
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California; and
| | - Daniel C Belz
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Sarath Raju
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Amanda J Gassett
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington
| | - Joel D Kaufman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
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23
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Hunt JFV, Vogt NM, Jonaitis EM, Buckingham WR, Koscik RL, Zuelsdorff M, Clark LR, Gleason CE, Yu M, Okonkwo O, Johnson SC, Asthana S, Bendlin BB, Kind AJH. Association of Neighborhood Context, Cognitive Decline, and Cortical Change in an Unimpaired Cohort. Neurology 2021; 96:e2500-e2512. [PMID: 33853894 DOI: 10.1212/wnl.0000000000011918] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 02/24/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To test the hypothesis that neighborhood-level disadvantage is associated with longitudinal measures of neurodegeneration and cognitive decline in an unimpaired cohort. METHODS Longitudinal MRI and cognitive testing data were collected from 601 cognitively unimpaired participants in the Wisconsin Registry for Alzheimer's Prevention Study and the Wisconsin Alzheimer's Disease Research Center clinical cohort. Area Deprivation Index was geospatially determined based on participant residence geocode and ranked relative to state of residence. Linear regression models were fitted to test associations between neighborhood-level disadvantage and longitudinal change in cortical thickness and cognitive test performance. Mediation tests were used to assess whether neurodegeneration and cognitive decline were associated with neighborhood-level disadvantage along the same theoretical causal path. RESULTS In our middle- to older-aged study population (mean baseline age 59 years), living in the 20% most disadvantaged neighborhoods (n = 19) relative to state of residence was associated with cortical thinning in Alzheimer signature regions (p = 0.002) and decline in the Preclinical Alzheimer's Disease Cognitive Composite (p = 0.04), particularly the Trail-Making Test, part B (p < 0.001), but not Rey Auditory Verbal Learning Test (p = 0.77) or Story Memory Delayed Recall (p = 0.49) subtests. Associations were attenuated but remained significant after controlling for racial and demographic differences between neighborhood-level disadvantage groups. Cortical thinning partially mediated the association between neighborhood-level disadvantage and cognitive decline. CONCLUSIONS In this longitudinal study of cognitively unimpaired adults, living in the most highly disadvantaged neighborhoods was associated with accelerated degeneration in Alzheimer signature regions and cognitive decline. This study provides further evidence for neighborhood-level disadvantage as a risk factor for preclinical neurodegeneration and cognitive decline in certain populations. Limitations of the present study, including a small number of participants from highly disadvantaged neighborhoods and a circumscribed geographic setting, should be explored in larger and more diverse study cohorts.
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Affiliation(s)
- Jack F V Hunt
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Nicholas M Vogt
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Erin M Jonaitis
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - William R Buckingham
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Rebecca L Koscik
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Megan Zuelsdorff
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Lindsay R Clark
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Carey E Gleason
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Menggang Yu
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Ozioma Okonkwo
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Sterling C Johnson
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Sanjay Asthana
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI
| | - Barbara B Bendlin
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI.
| | - Amy J H Kind
- From the Wisconsin Alzheimer's Disease Research Center (J.F.V.H., N.M.V., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Wisconsin Alzheimer's Institute (E.M.J., R.L.K., O.O., S.C.J., S.A., B.B.B.), Department of Medicine, Geriatrics Division (W.R.B., M.Z., L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), Health Services and Care Research Program (W.R.B., A.J.H.K.), and Department of Biostatistics & Medical Informatics (M.Y.), University of Wisconsin School of Medicine and Public Health; University of Wisconsin School of Nursing (M.Z.); and Geriatric Research Education and Clinical Center (GRECC) (L.R.C., C.E.G., O.O., S.C.J., S.A., B.B.B., A.J.H.K.), William S. Middleton Hospital, United States Department of Veterans Affairs, Madison, WI.
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Kostelanetz S, Di Gravio C, Schildcrout JS, Roumie CL, Conway D, Kripalani S. Should We Implement Geographic or Patient-Reported Social Determinants of Health Measures In Cardiovascular Patients. Ethn Dis 2021; 31:9-22. [PMID: 33519151 DOI: 10.18865/ed.31.1.9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Objectives To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD). Design Prospective cohort. Setting Academic medical center. Participants Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015. Methods Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing. Primary Outcome All-cause mortality, up to 5 years follow-up. Results The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-reported variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively). Conclusions The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD.
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Affiliation(s)
- Sophia Kostelanetz
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Chiara Di Gravio
- Department of Biostatistics, Vanderbilt University, Nashville, TN
| | | | - Christianne L Roumie
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Douglas Conway
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | - Sunil Kripalani
- Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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Salwi S, Kelly KA, Patel PD, Fusco MR, Mistry EA, Mistry AM, Chitale RV. Neighborhood Socioeconomic Status and Mechanical Thrombectomy Outcomes. J Stroke Cerebrovasc Dis 2020; 30:105488. [PMID: 33276300 DOI: 10.1016/j.jstrokecerebrovasdis.2020.105488] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 11/02/2020] [Accepted: 11/16/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/PURPOSE Our study aimed to assess the impacts of neighborhood socioeconomic status on mechanical thrombectomy (MT) outcomes for acute ischemic stroke (AIS). METHODS We conducted a prospective observational study of consecutive adult AIS patients treated with MT at one US comprehensive stroke center from 2012 to 2018. A composite neighborhood socioeconomic score (nSES) was created using patient home address, median household income, percentage of households with interest, dividend, or rental income, median value of housing units, percentage of persons 25 or older with high school degrees, college degrees or holding executive, managerial or professional specialty occupations. Using this score, patients were divided into low, middle and high nSES tertiles. Outcomes included 90-day functional independence, in-hospital mortality, length of hospital stay, discharge location, time to recanalization, successful recanalization, and symptomatic intracranial hemorrhage (sICH). RESULTS 328 patients were included. Between the three nSES groups, proportion of White patients, time-to-recanalization and admission NIH stroke scale differed significantly (p<0.05). Patients in the high nSES tertile were more likely to be functionally dependent at 90 days (unadjusted OR, 95% CI, 1.91 [1.10, 3.36]) and were less likely to die in the hospital (unadjusted OR, 95% CI, 0.46, [0.20, 0.98]). Further, patients in the high nSES tertile had decreased times to recanalization (median time in minutes, low=335, mid=368, high=297, p=0.04). However, after adjusting for variance in race and severity of stroke, the differences in clinical outcomes were not significant. CONCLUSION This study highlights how unadjusted neighborhood socioeconomic status is significantly associated with functional outcome, mortality, and time-to-recanalization following MT for AIS. Since adjustment modifies the significant association, the socioeconomic differences may be influenced by differences in pre-hospital factors that drive severity of stroke and time to recanalization. Better understanding of the interplay of these factors may lead to timelier evaluation and improvement in patient outcomes.
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Affiliation(s)
- Sanjana Salwi
- School of Medicine, Vanderbilt University, Nashville, TN, United States.
| | - Katherine A Kelly
- School of Medicine, Vanderbilt University, Nashville, TN, United States.
| | - Pious D Patel
- School of Medicine, Vanderbilt University, Nashville, TN, United States.
| | - Matthew R Fusco
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, United States.
| | - Eva A Mistry
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.
| | - Akshitkumar M Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, United States.
| | - Rohan V Chitale
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, United States.
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26
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An J, Zhang Y, Muntner P, Moran AE, Hsu JW, Reynolds K. Recurrent Atherosclerotic Cardiovascular Event Rates Differ Among Patients Meeting the Very High Risk Definition According to Age, Sex, Race/Ethnicity, and Socioeconomic Status. J Am Heart Assoc 2020; 9:e017310. [PMID: 33222592 PMCID: PMC7763778 DOI: 10.1161/jaha.120.017310] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background The risk for atherosclerotic cardiovascular disease (ASCVD) events may differ by sociodemographic factors among patients meeting the definition of very high risk according to the 2018 American Heart Association/American College of Cardiology cholesterol guideline, leading to treatment disparities. We estimated the risk for recurrent ASCVD events among adults meeting the definition of very high risk by age, sex, race/ethnicity, and socioeconomic status in a US integrated healthcare system. Methods and Results The study cohort included Kaiser Permanente Southern California members aged ≥21 years with a history of clinical ASCVD on September 30, 2009. Very high risk for recurrent ASCVD was defined by a history of ≥2 major ASCVD events or a history of 1 major event along with ≥2 high‐risk conditions. Patients were followed through 2015 for a first recurrent ASCVD event. Of 77 101 patients with ASCVD, 50.8% met the definition for very high risk. Among patients meeting the definition of very high risk, recurrent ASCVD rates were higher in older (>75 years) versus younger patients (21–40 years) (sex‐adjusted hazard ratio [HR] [95% CI] 1.85; 1.23–2.79), non‐Hispanic Black patients versus non‐Hispanic White patients (age‐, sex‐adjusted HR, 1.32; 1.23–1.41), those who lived in neighborhoods with lower (<$35k) versus higher annual household income (≥$80k) (HR, 1.20; 1.11–1.30), or with lower (≥31.2%) versus higher education levels (<8.8% high school or lower) (HR, 1.26; 1.19–1.34). Conclusions Disparities in the risk for recurrent ASCVD events were present across sociodemographic factors among very high risk patients. The addition of sociodemographic factors to current definitions of very high risk could reduce health disparities.
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Affiliation(s)
- Jaejin An
- Kaiser Permanente Southern California Pasadena CA.,Kaiser Permanente School of Medicine Pasadena CA
| | - Yiyi Zhang
- Division of General Medicine Columbia University Medical Center New York NY
| | | | - Andrew E Moran
- Division of General Medicine Columbia University Medical Center New York NY
| | - Jin-Wen Hsu
- Kaiser Permanente Southern California Pasadena CA
| | - Kristi Reynolds
- Kaiser Permanente Southern California Pasadena CA.,Kaiser Permanente School of Medicine Pasadena CA
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27
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Identifying and assessing the impact of key neighborhood-level determinants on geographic variation in stroke: a machine learning and multilevel modeling approach. BMC Public Health 2020; 20:1666. [PMID: 33160324 PMCID: PMC7648288 DOI: 10.1186/s12889-020-09766-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 10/26/2020] [Indexed: 12/31/2022] Open
Abstract
Background Stroke is a chronic cardiovascular disease that puts major stresses on U.S. health and economy. The prevalence of stroke exhibits a strong geographical pattern at the state-level, where a cluster of southern states with a substantially higher prevalence of stroke has been called the stroke belt of the nation. Despite this recognition, the extent to which key neighborhood characteristics affect stroke prevalence remains to be further clarified. Methods We generated a new neighborhood health data set at the census tract level on nearly 27,000 tracts by pooling information from multiple data sources including the CDC’s 500 Cities Project 2017 data release. We employed a two-stage modeling approach to understand how key neighborhood-level risk factors affect the neighborhood-level stroke prevalence in each state of the US. The first stage used a state-of-the-art Bayesian machine learning algorithm to identify key neighborhood-level determinants. The second stage applied a Bayesian multilevel modeling approach to describe how these key determinants explain the variability in stroke prevalence in each state. Results Neighborhoods with a larger proportion of older adults and non-Hispanic blacks were associated with neighborhoods with a higher prevalence of stroke. Higher median household income was linked to lower stroke prevalence. Ozone was found to be positively associated with stroke prevalence in 10 states, while negatively associated with stroke in five states. There was substantial variation in both the direction and magnitude of the associations between these four key factors with stroke prevalence across the states. Conclusions When used in a principled variable selection framework, high-performance machine learning can identify key factors of neighborhood-level prevalence of stroke from wide-ranging information in a data-driven way. The Bayesian multilevel modeling approach provides a detailed view of the impact of key factors across the states. The identified major factors and their effect mechanisms can potentially aid policy makers in developing area-based stroke prevention strategies. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-020-09766-3.
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28
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Hunt JFV, Buckingham W, Kim AJ, Oh J, Vogt NM, Jonaitis EM, Hunt TK, Zuelsdorff M, Powell R, Norton D, Rissman RA, Asthana S, Okonkwo OC, Johnson SC, Kind AJH, Bendlin BB. Association of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume. JAMA Neurol 2020; 77:451-460. [PMID: 31904767 DOI: 10.1001/jamaneurol.2019.4501] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Importance Identifying risk factors for brain atrophy during the aging process can help direct new preventive approaches for dementia and cognitive decline. The association of neighborhood socioeconomic disadvantage with brain volume in this context is not well known. Objective To test whether neighborhood-level socioeconomic disadvantage is associated with decreased brain volume in a cognitively unimpaired population enriched for Alzheimer disease risk. Design, Setting, and Participants This study, conducted from January 6, 2010, to January 17, 2019, at an academic research neuroimaging center, used cross-sectional data on 951 participants from 2 large, ongoing cohort studies of Alzheimer disease (Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center clinical cohort). Participants were cognitively unimpaired based on National Institute on Aging-Alzheimer's Association workgroup diagnostic criteria for mild cognitive impairment and Alzheimer disease, confirmed through a consensus diagnosis panel. The cohort was enriched for Alzheimer disease risk based on family history of dementia. Statistical analysis was performed from April 3 to September 27, 2019. Main Outcomes and Measures The Area Deprivation Index, a geospatially determined index of neighborhood-level disadvantage, and cardiovascular disease risk indices were calculated for each participant. Linear regression models were fitted to test associations between relative neighborhood-level disadvantage (highest 20% based on state of residence) and hippocampal and total brain tissue volume, as assessed by magnetic resonance imaging. Results In the primary analysis of 951 participants (637 women [67.0%]; mean [SD] age, 63.9 [8.1] years), living in the 20% most disadvantaged neighborhoods was associated with 4.1% lower hippocampal volume (β = -317.44; 95% CI, -543.32 to -91.56; P = .006) and 2.0% lower total brain tissue volume (β = -20 959.67; 95% CI, -37 611.92 to -4307.43; P = .01), after controlling for intracranial volume, individual-level educational attainment, age, and sex. Robust propensity score-matched analyses determined that this association was not due to racial/ethnic or demographic characteristics. Cardiovascular risk score, examined in a subsample of 893 participants, mediated this association for total brain tissue but not for hippocampal volume. Conclusions and Relevance For cognitively unimpaired individuals, living in the most disadvantaged neighborhoods was associated with significantly lower cerebral volumes, after controlling for maximal premorbid (total intracranial) volume. This finding suggests an association of community socioeconomic context, distinct from individual-level socioeconomic status, with brain volume during aging. Cardiovascular risk mediated this association for total brain tissue volume but not for hippocampal volume, suggesting that neighborhood-level disadvantage may be associated with these 2 outcomes via distinct biological pathways.
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Affiliation(s)
- Jack F V Hunt
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - William Buckingham
- Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison
| | - Alice J Kim
- Department of Psychology, University of Southern California, Los Angeles
| | - Jennifer Oh
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - Nicholas M Vogt
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison
| | - Tenah K Hunt
- Wisconsin Center for Education Research, University of Wisconsin-Madison
| | - Megan Zuelsdorff
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison
| | - Ryan Powell
- Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison
| | - Derek Norton
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison
| | - Robert A Rissman
- Department of Neurosciences, University of California, San Diego
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatrics Division, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, Wisconsin
| | - Ozioma C Okonkwo
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatrics Division, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, Wisconsin
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatrics Division, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, Wisconsin
| | - Amy J H Kind
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Health Services and Care Research Program, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatrics Division, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, Wisconsin
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatrics Division, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, Wisconsin
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29
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Juarez PD, Tabatabai M, Burciaga Valdez R, Hood DB, Im W, Mouton C, Colen C, Al-Hamdan MZ, Matthews-Juarez P, Lichtveld MY, Sarpong D, Ramesh A, Langston MA, Rogers GL, Phillips CA, Reichard JF, Donneyong MM, Blot W. The Effects of Social, Personal, and Behavioral Risk Factors and PM 2.5 on Cardio-Metabolic Disparities in a Cohort of Community Health Center Patients. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3561. [PMID: 32438697 PMCID: PMC7277630 DOI: 10.3390/ijerph17103561] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Revised: 03/30/2020] [Accepted: 05/15/2020] [Indexed: 12/26/2022]
Abstract
(1) Background: Cardio-metabolic diseases (CMD), including cardiovascular disease, stroke, and diabetes, have numerous common individual and environmental risk factors. Yet, few studies to date have considered how these multiple risk factors together affect CMD disparities between Blacks and Whites. (2) Methods: We linked daily fine particulate matter (PM2.5) measures with survey responses of participants in the Southern Community Cohort Study (SCCS). Generalized linear mixed modeling (GLMM) was used to estimate the relationship between CMD risk and social-demographic characteristics, behavioral and personal risk factors, and exposure levels of PM2.5. (3) Results: The study resulted in four key findings: (1) PM2.5 concentration level was significantly associated with reported CMD, with risk rising by 2.6% for each µg/m3 increase in PM2.5; (2) race did not predict CMD risk when clinical, lifestyle, and environmental risk factors were accounted for; (3) a significant variation of CMD risk was found among participants across states; and (4) multiple personal, clinical, and social-demographic and environmental risk factors played a role in predicting CMD occurrence. (4) Conclusions: Disparities in CMD risk among low social status populations reflect the complex interactions of exposures and cumulative risks for CMD contributed by different personal and environmental factors from natural, built, and social environments.
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Affiliation(s)
- Paul D. Juarez
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA; (W.I.); (P.M.-J.)
| | - Mohammad Tabatabai
- School of Graduate Studies and Research, Meharry Medical College, Nashville, TN 37208, USA;
| | - Robert Burciaga Valdez
- RWJF Professor, Department of Family & Community Medicine AND Economics, University of New Mexico, Albuquerque, NM 87131, USA;
| | - Darryl B. Hood
- Department of Environmental Health Sciences, College of Public Health, Ohio State University, Columbus, OH 43210, USA;
| | - Wansoo Im
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA; (W.I.); (P.M.-J.)
| | - Charles Mouton
- Department of Family Medicine, University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Cynthia Colen
- Department of Sociology, Ohio State University, Columbus, OH 43210, USA;
| | - Mohammad Z. Al-Hamdan
- Universities Space Research Association, NASA Marshall Space Flight Center, Huntsville, AL 35805, USA;
| | - Patricia Matthews-Juarez
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA; (W.I.); (P.M.-J.)
| | - Maureen Y. Lichtveld
- Department of Environmental Health Sciences, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA;
| | - Daniel Sarpong
- Department of Biostatistics, Xavier University, Cincinnati, OH 45207, USA;
| | - Aramandla Ramesh
- Department of Biochemistry, Cancer Biology, Neuroscience & Pharmacology, Meharry Medical College, Nashville, TN 37208, USA;
| | - Michael A. Langston
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA; (M.A.L.); (C.A.P.)
| | - Gary L. Rogers
- National Institute for Computational Sciences, University of Tennessee, Knoxville, TN 37996, USA;
| | - Charles A. Phillips
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA; (M.A.L.); (C.A.P.)
| | - John F. Reichard
- Department of Environmental Health, Risk Science Center, University of Cincinnati, Cincinnati, OH 45221, USA;
| | - Macarius M. Donneyong
- Division of Outcomes and Translational Sciences, College of Pharmacy, Ohio State University, Columbus, OH 43210, USA;
| | - William Blot
- Center for Population-based Research, Vanderbilt University, Nashville, TN 37235, USA;
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30
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Gary-Webb TL, Egnot NS, Nugroho A, Dubowitz T, Troxel WM. Changes in perceptions of neighborhood environment and Cardiometabolic outcomes in two predominantly African American neighborhoods. BMC Public Health 2020; 20:52. [PMID: 31937271 PMCID: PMC6961335 DOI: 10.1186/s12889-019-8119-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 12/22/2019] [Indexed: 01/24/2023] Open
Abstract
Background Perceived neighborhood characteristics, including satisfaction with one’s neighborhood as a place to live, are associated with lower obesity rates and more favorable cardiovascular risk factor profiles. Yet, few studies have evaluated whether changes in perceived neighborhood characteristics over time may be associated with cardiometabolic health indicators. Methods Changes in perception of one’s neighborhood (2013–2016) were determined from a cohort of residents who lived in one of two low-income urban neighborhoods. Changes were categorized into the following: improvement vs. no change or worsening over the three-year time-period. Multivariable linear regression was used to measure the association between perceived improvement in each of the neighborhood characteristics with cardiometabolic outcomes (BMI, SBP, DBP, HbA1c, HDL-c) that were assessed in 2016, and compared with those who perceived no change or worsening of neighborhood characteristics. Models were adjusted for age, sex, income, education, marital status, physical function, neighborhood, and years spent in neighborhood. To examine potential sex differences, follow-up models were conducted and stratified by sex. Results Among the 622 individuals who remained in the same neighborhood during the time period, 93% were African American, 80% were female, and the mean age was 58 years. In covariate-adjusted models, those who perceived improvement in their neighborhood safety over the time period had a significantly higher BMI (kg/m2) than those who perceived no improvement or worsening (β = 1.5, p = 0.0162); however, perceived improvement in safety was also significantly associated with lower SBP (mmHg) (β = − 3.8, p = 0.0361). When results were stratified by sex, the relationship between improved perceived neighborhood safety and BMI was only evident in females. Conclusions These findings suggest that perceived neighborhood characteristics may impact cardiometabolic outcomes (BMI, SBP), but through differing pathways. This highlights the complexity of the associations between neighborhood characteristics and underscores the need for more longitudinal studies to confirm the associations with cardiometabolic health in African American populations.
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Affiliation(s)
- Tiffany L Gary-Webb
- Departments of Behavioral and Community Health Sciences and Epidemiology, University of Pittsburgh Graduate School of Public Health 130 DeSoto St, Rm 6135 Public Health Building, Pittsburgh, PA, 15261, USA.
| | - Natalie Suder Egnot
- Departments of Behavioral and Community Health Sciences and Epidemiology, University of Pittsburgh Graduate School of Public Health 130 DeSoto St, Rm 6135 Public Health Building, Pittsburgh, PA, 15261, USA
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Billings ME, Hale L, Johnson DA. Physical and Social Environment Relationship With Sleep Health and Disorders. Chest 2019; 157:1304-1312. [PMID: 31870910 DOI: 10.1016/j.chest.2019.12.002] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 11/11/2019] [Accepted: 12/09/2019] [Indexed: 12/14/2022] Open
Abstract
Sleep health is a multidimensional construct that includes adequate duration, quality, and appropriately timed sleep that may be influenced by environmental factors. In this review, we focus on how an individual's living and sleeping environment, both the surrounding neighborhood physical and social features and the atmosphere around them, may impact their sleep health. We explore the associations of the physical environment (urban density, recreational facilities, green space, mixed land use, and healthy food stores), neighborhood deprivation (disadvantage and disorder), and the social environment (social cohesion, safety, and stigma) with sleep in both adult and pediatric populations. We investigate how physical and social environmental features may lead to alterations in the timing, duration, and quality of sleep and contribute to the most prevalent sleep disorders: insomnia, sleep apnea, and circadian rhythm disorders. We also review how ambient factors such as artificial light, environmental noise, and air pollution may contribute to sleep pathology. We have included key studies and recent emerging data regarding how the differential distribution of environmental factors that may affect sleep health may contribute to sleep health disparities.
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Affiliation(s)
- Martha E Billings
- Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, WA.
| | - Lauren Hale
- Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY
| | - Dayna A Johnson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
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Utilization of Census Tract-Based Neighborhood Poverty Rates to Predict Non-adherence to Screening Colonoscopy. Dig Dis Sci 2019; 64:2505-2513. [PMID: 30874988 DOI: 10.1007/s10620-019-05585-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 03/08/2019] [Indexed: 12/09/2022]
Abstract
OBJECTIVES Efforts to improve colorectal cancer (CRC) screening rates include recognizing predictors of colonoscopy non-adherence and identifying these high-risk patient populations. Past studies have focused on individual-level factors but few have evaluated the influence of neighborhood-level predictors. We sought to assess the effect of census tract-based neighborhood poverty rates on scheduled screening colonoscopy non-adherence. METHODS In this prospective observational cohort study, data from electronic medical records and appointment tracking software were collected in 599 patients scheduled to undergo outpatient CRC screening colonoscopy at two academic endoscopy centers between January 2011 and December 2012. Non-adherence was defined as failure to attend a colonoscopy appointment within 1 year of the date it was electronically scheduled. Neighborhood poverty rate was determined by matching patients' self-reported home address with their corresponding US census tract. Individual factors including medical comorbidities and prior appointment adherence behavior were also collected. RESULTS Overall, 17% (65/383) of patients were non-adherent to scheduled colonoscopy at 1-year follow-up. Neighborhood poverty rate was a significant predictor of non-adherence to scheduled screening colonoscopy in multivariate modeling (OR 1.53 per 10% increase in neighborhood poverty rate, 95% CI 1.21-1.95, p < 0.001). By incorporating the neighborhood poverty rate, screening colonoscopy non-adherence was 31% at the highest quartile compared to 14% at the lowest quartile of neighborhood poverty rates (p = 0.006). CONCLUSIONS Census tract-based neighborhood poverty rates can be used to predict non-adherence to scheduled screening colonoscopy. Targeted efforts to increase CRC screening efficiency and completion among patients living in high-poverty geographic regions could reduce screening disparities and improve utilization of endoscopy unit resources.
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Lee CY, Lee YH. Measurement of Socioeconomic Position in Research on Cardiovascular Health Disparities in Korea: A Systematic Review. J Prev Med Public Health 2019; 52:281-291. [PMID: 31588697 PMCID: PMC6780291 DOI: 10.3961/jpmph.19.094] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Accepted: 08/05/2019] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVES The validity of instruments measuring socioeconomic position (SEP) has been a major area of concern in research on cardiovascular health disparities. The purpose of this systematic review is to identify the current status of the methods used to measure SEP in research on cardiovascular health disparities in Korea and to provide directions for future research. METHODS Relevant articles were obtained through electronic database searches with manual searches of reference lists and no restriction on the date of publication. SEP indicators were categorized into compositional, contextual, composite, and life-course measures. RESULTS Forty-eight studies published from 2003 to 2018 satisfied the review criteria. Studies utilizing compositional measures mainly relied on a limited number of SEP parameters. In addition, these measures hardly addressed the time-varying and subjective features of SEP. Finding valid contextual measures at the organizational, community, and societal levels that are appropriate to Korea's context remains a challenge, and these are rarely modeled simultaneously. Studies have rarely focused on composite and life-course measures. CONCLUSIONS Future studies should develop and utilize valid compositional and contextual measures and appraise social patterns that vary across time, place, and culture using such measures. Studies should also consider multilevel influences, adding a focus on the interactions between different levels of intertwined SEP factors to advance the design of research. More attention should be given to composite and life-course measures.
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Affiliation(s)
| | - Yong-Hwan Lee
- Department of Economics, Seoul National University, Seoul, Korea
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Mendelson SJ, Aggarwal NT, Richards C, O'Neill K, Holl JL, Prabhakaran S. Racial disparities in refusal of stroke thrombolysis in Chicago. Neurology 2018; 90:e359-e364. [PMID: 29298854 PMCID: PMC10681073 DOI: 10.1212/wnl.0000000000004905] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Accepted: 08/24/2017] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate race differences in tissue plasminogen activator (tPA) refusal among eligible patients with acute ischemic stroke (AIS) in Chicago. METHODS Using the Get With The Guidelines-Stroke registry data from 15 primary stroke centers between January 2013 and June 2015, we performed a retrospective analysis of patients with AIS presenting to the emergency department within 4.5 hours from symptom onset. Patient or proxy refusal was captured as a reason for nonadministration of tPA to eligible patients in the registry. We assessed whether tPA refusal differed by race using logistic regression. RESULTS Among 704 tPA-eligible patients with AIS, tPA was administered to 86.2% (black race, 82.5% vs nonblack race, 89.5%; p < 0.001). Fifty-three (7.5%) tPA refusals were documented. Refusal was more common in black vs nonblack patients (10.6% vs 4.8%; p = 0.004). In multivariable analysis, the following were associated with tPA refusal: black race (adjusted odds ratio [OR] 2.5, 95% confidence interval [CI] 1.3-4.6), self-pay status (adjusted OR 3.23, 95% CI 1.2-8.71), prior stroke (adjusted OR 2.11, 95% CI 1.14-3.90), age (adjusted OR 1.04, 95% CI 1.02-1.07), and NIH Stroke Scale score (adjusted OR 0.94, 95% CI 0.90-0.99). CONCLUSIONS Among tPA-eligible patients with AIS in Chicago, over 7% refused tPA. Refusal was more common in black patients and accounted for the apparent lower rates of tPA use in black vs nonblack patients. Further research is needed to understand barriers to consent and overcome race-ethnic disparities in tPA treatment for AIS.
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Affiliation(s)
- Scott J Mendelson
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL.
| | - Neelum T Aggarwal
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL
| | - Christopher Richards
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL
| | - Kathleen O'Neill
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL
| | - Jane L Holl
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL
| | - Shyam Prabhakaran
- From the Department of Neurology (S.J.M., S.P.), Department of Emergency Medicine (C.R.), and Center for Healthcare Studies (J.L.H.), Northwestern University Feinberg School of Medicine; Department of Neurologic Sciences and the Rush Alzheimer's Disease Center (N.T.A.), Rush University Medical Center; and American Heart Association (K.O.), Midwest Affiliate, Chicago, IL
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Nkoy FL, Stone BL, Knighton AJ, Fassl BA, Johnson JM, Maloney CG, Savitz LA. Neighborhood Deprivation and Childhood Asthma Outcomes, Accounting for Insurance Coverage. Hosp Pediatr 2018; 8:hpeds.2017-0032. [PMID: 29317461 DOI: 10.1542/hpeds.2017-0032] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Collecting social determinants data is challenging. We assigned patients a neighborhood-level social determinant measure, the area of deprivation index (ADI), by using census data. We then assessed the association between neighborhood deprivation and asthma hospitalization outcomes and tested the influence of insurance coverage. METHODS A retrospective cohort study of children 2 to 17 years old admitted for asthma at 8 hospitals. An administrative database was used to collect patient data, including hospitalization outcomes and neighborhood deprivation status (ADI scores), which were grouped into quintiles (ADI 1, the least deprived neighborhoods; ADI 5, the most deprived neighborhoods). We used multivariable models, adjusting for covariates, to assess the associations and added a neighborhood deprivation status and insurance coverage interaction term. RESULTS A total of 2270 children (median age 5 years; 40.6% girls) were admitted for asthma. We noted that higher ADI quintiles were associated with greater length of stay, higher cost, and more asthma readmissions (P < .05 for most quintiles). Having public insurance was independently associated with greater length of stay (β: 1.171; 95% confidence interval [CI]: 1.117-1.228; P < .001), higher cost (β: 1.147; 95% CI: 1.093-1.203; P < .001), and higher readmission odds (odds ratio: 1.81; 95% CI: 1.46-2.24; P < .001). There was a significant deprivation-insurance effect modification, with public insurance associated with worse outcomes and private insurance with better outcomes across ADI quintiles (P < .05 for most combinations). CONCLUSIONS Neighborhood-level ADI measure is associated with asthma hospitalization outcomes. However, insurance coverage modifies this relationship and needs to be considered when using the ADI to identify and address health care disparities.
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Affiliation(s)
- Flory L Nkoy
- Division of Pediatric Inpatient Medicine, University of Utah, Salt Lake City, Utah;
| | - Bryan L Stone
- Division of Pediatric Inpatient Medicine, University of Utah, Salt Lake City, Utah
| | | | - Bernhard A Fassl
- Division of Pediatric Inpatient Medicine, University of Utah, Salt Lake City, Utah
| | - Joseph M Johnson
- Utah Valley Hospital, Intermountain Healthcare, Salt Lake City, Utah
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Shin J, Choi Y, Kim SW, Lee SG, Park EC. Cross-level interaction between individual socioeconomic status and regional deprivation on overall survival after onset of ischemic stroke: National health insurance cohort sample data from 2002 to 2013. J Epidemiol 2017; 27:381-388. [PMID: 28688749 PMCID: PMC5549246 DOI: 10.1016/j.je.2016.08.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 08/19/2016] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION The literature on stroke mortality and neighborhood effect is characterized by studies that are often Western society-oriented, with a lack of racial and cultural diversity. We estimated the effect of cross-level interaction between individual and regional socioeconomic status on the survival after onset of ischemic stroke. METHODS We selected newly diagnosed ischemic stroke patients from 2002 to 2013 using stratified representative sampling data of 1,025,340 subjects. A total of 37,044 patients over the 10 years from 2004 to 2013 had newly diagnosed stroke. We calculated hazard ratios (HR) of 12- and 36-month mortality using the Cox proportional hazard model, with the reference group as stroke patients with high income in advantaged regions. RESULTS For the middle income level, the patients in advantaged regions showed low HRs for overall mortality (12-month HR 1.27; 95% confidence interval [CI], 1.13-1.44; 36-month HR 1.25; 95% CI, 1.14-1.37) compared to the others in disadvantaged regions (12-month HR 1.36; 95% CI, 1.19-1.56; 36-month HR 1.30; 95% CI, 1.17-1.44). Interestingly, for the low income level, the patients in advantaged regions showed high HRs for overall mortality (12-month HR 1.27; 95% CI, 1.13-1.44; 36-month HR 1.33; 95% CI, 1.22-1.46) compared to the others in disadvantaged regions (12-month HR 1.25; 95% CI, 1.09-1.43; 36-month HR 1.30; 95% CI, 1.18-1.44). CONCLUSION Although we need to perform further investigations to determine the exact mechanisms, regional deprivation, as well as medical factors, might be associated with survival after onset of ischemic stroke in low-income patients.
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Affiliation(s)
- Jaeyong Shin
- Department of Preventive Medicine, Yonsei University, College of Medicine, Seoul, South Korea; Institute of Health Services Research, Yonsei University, College of Medicine, Seoul, South Korea; Department of Public Health, Yonsei University Graduate School, Seoul, South Korea
| | - Young Choi
- Institute of Health Services Research, Yonsei University, College of Medicine, Seoul, South Korea; Department of Public Health, Yonsei University Graduate School, Seoul, South Korea
| | - Seung Woo Kim
- Department of Neurology, Yonsei University, College of Medicine, Seoul, South Korea
| | - Sang Gyu Lee
- Department of Hospital Management, Yonsei University Graduate School of Public Health, Seoul, South Korea
| | - Eun-Cheol Park
- Department of Preventive Medicine, Yonsei University, College of Medicine, Seoul, South Korea; Institute of Health Services Research, Yonsei University, College of Medicine, Seoul, South Korea.
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Mirowsky JE, Devlin RB, Diaz-Sanchez D, Cascio W, Grabich SC, Haynes C, Blach C, Hauser ER, Shah S, Kraus W, Olden K, Neas L. A novel approach for measuring residential socioeconomic factors associated with cardiovascular and metabolic health. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2017; 27:281-289. [PMID: 27649842 PMCID: PMC5373927 DOI: 10.1038/jes.2016.53] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 07/18/2016] [Indexed: 05/22/2023]
Abstract
Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health; however, residential area-level characteristics may also independently contribute to health status. In the current study, we used hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. We assigned 2254 cardiac catheterization patients to these clusters based on residence at first catheterization. After controlling for individual age, sex, smoking status, and race, there were elevated odds of patients being obese (odds ratio (OR)=1.92, 95% confidence intervals (CI)=1.39, 2.67), and having diabetes (OR=2.19, 95% CI=1.57, 3.04), congestive heart failure (OR=1.99, 95% CI=1.39, 2.83), and hypertension (OR=2.05, 95% CI=1.38, 3.11) in a cluster that was urban, impoverished, and unemployed, compared with a cluster that was urban with a low percentage of people that were impoverished or unemployed. Our findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health.
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Affiliation(s)
- Jaime E. Mirowsky
- Curriculum in Toxicology, University of North Carolina, Chapel Hill, North Carolina, USA
- Center for Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Robert B. Devlin
- National Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
| | - David Diaz-Sanchez
- National Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
| | - Wayne Cascio
- National Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
| | - Shannon C. Grabich
- National Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
| | - Carol Haynes
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - Elizabeth R. Hauser
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA
- Cooperative Studies Program Epidemiology Center, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
| | - Svati Shah
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
- Division of Cardiology, Department of Medicine, School of Medicine, Duke University, Durham, North Carolina, USA
| | - William Kraus
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA
- Division of Cardiology, Department of Medicine, School of Medicine, Duke University, Durham, North Carolina, USA
| | - Kenneth Olden
- National Center for Environmental Assessment, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
| | - Lucas Neas
- National Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA
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Carlsson AC, Li X, Holzmann MJ, Ärnlöv J, Wändell P, Gasevic D, Sundquist J, Sundquist K. Neighborhood socioeconomic status at the age of 40 years and ischemic stroke before the age of 50 years: A nationwide cohort study from Sweden. Int J Stroke 2017; 12:815-826. [PMID: 28387158 DOI: 10.1177/1747493017702663] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objective We aimed to study the association between neighborhood socioeconomic status at the age of 40 years and risk of ischemic stroke before the age of 50 years. Methods All individuals in Sweden were included if their 40th birthday occurred between 1998 and 2010. National registers were used to categorize neighborhood socioeconomic status into high, middle, and low and to retrieve information on incident ischemic strokes. Hazard ratios and their 95% confidence intervals were estimated. Results A total of 1,153,451 adults (women 48.9%) were followed for a mean of 5.5 years (SD 3.5 years), during which 1777 (0.30%) strokes among men and 1374 (0.24%) strokes among women were recorded. After adjustment for sex, marital status, education level, immigrant status, region of residence, and neighborhood services, there was a lower risk of stroke in residents from high-socioeconomic status neighborhoods (hazard ratio 0.87, 95% confidence interval 0.78-0.96), and an increased risk of stroke in adults from low-socioeconomic status neighborhoods (hazard ratio 1.16, 95% confidence interval 1.06-1.27), compared to their counterparts living in middle-socioeconomic status neighborhoods. After further adjustment for hospital diagnoses of hypertension, diabetes, heart failure, and atrial fibrillation prior to the age of 40, the higher risk in neighborhoods with low socioeconomic status was attenuated, but remained significant (hazard ratio 1.12, 95% confidence interval 1.02-1.23). Conclusions In a nationwide study of individuals between 40 and 50 years, we found that the risk of ischemic stroke differed depending on neighborhood socioeconomic status, which calls for increased efforts to prevent cardiovascular diseases in low socioeconomic status neighborhoods.
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Affiliation(s)
- Axel C Carlsson
- 1 Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden.,2 Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Xinjun Li
- 3 Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Martin J Holzmann
- 4 Department of Emergency Medicine, Karolinska University Hospital, Stockholm, Sweden.,5 Department of Internal Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Johan Ärnlöv
- 1 Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden.,6 School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - Per Wändell
- 1 Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden
| | - Danijela Gasevic
- 7 Usher Institute of Population Health Sciences and Informatics, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - Jan Sundquist
- 3 Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Kristina Sundquist
- 3 Center for Primary Health Care Research, Lund University, Malmö, Sweden
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Osypuk TL, Ehntholt A, Moon JR, Gilsanz P, Glymour MM. Neighborhood Differences in Post-Stroke Mortality. Circ Cardiovasc Qual Outcomes 2017; 10:CIRCOUTCOMES.116.002547. [PMID: 28228449 DOI: 10.1161/circoutcomes.116.002547] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 12/22/2016] [Indexed: 01/06/2023]
Abstract
BACKGROUND Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher poststroke mortality, and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke. METHODS AND RESULTS Health and Retirement Study participants aged ≥50 years without stroke at baseline (n=15 560) were followed ≤12 years for incident stroke (1715 events over 159 286 person-years) and mortality (5325 deaths). Baseline neighborhood characteristics included objective measures based on census tracts (family income, poverty, deprivation, residential stability, and percent white, black, or foreign-born) and self-reported neighborhood social ties. Using Cox proportional hazard models, we compared neighborhood mortality effects for people with versus people without a history of stroke. Most neighborhood variables predicted mortality for both stroke patients and the general population in demographic-adjusted models. Neighborhood percent white predicted lower mortality for stroke survivors (hazard ratio, 0.75 for neighborhoods in highest 25th percentile versus below, 95% confidence interval, 0.62-0.91) more strongly than for stroke-free adults (hazard ratio, 0.92; 95% confidence interval, 0.83-1.02; P=0.04 for stroke-by-neighborhood interaction). No other neighborhood characteristic had different effects for people with versus without stroke. Neighborhood-mortality associations emerged within 3 months after stroke, when associations were often stronger than among stroke-free individuals. CONCLUSIONS Neighborhood characteristics predict mortality, but most effects are similar for individuals without stroke. Eliminating disparities in stroke survival may require addressing pathways that are not specific to traditional poststroke care.
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Affiliation(s)
- Theresa L Osypuk
- From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.).
| | - Amy Ehntholt
- From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.)
| | - J Robin Moon
- From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.)
| | - Paola Gilsanz
- From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.)
| | - M Maria Glymour
- From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis (T.L.O.); Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA (A.E., P.G., M.M.G.); SBH Health System, Bronx Partners for Healthy Communities, NY (J.R.M.); and Department of Epidemiology & Biostatistics, University of California, San Francisco (P.G., M.M.G.)
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Barber S, Hickson DA, Wang X, Sims M, Nelson C, Diez-Roux AV. Neighborhood Disadvantage, Poor Social Conditions, and Cardiovascular Disease Incidence Among African American Adults in the Jackson Heart Study. Am J Public Health 2016; 106:2219-2226. [PMID: 27736207 PMCID: PMC5105010 DOI: 10.2105/ajph.2016.303471] [Citation(s) in RCA: 86] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/30/2016] [Indexed: 01/31/2023]
Abstract
OBJECTIVES To examine the impact of neighborhood conditions resulting from racial residential segregation on cardiovascular disease (CVD) risk in a socioeconomically diverse African American sample. METHODS The study included 4096 African American women (n = 2652) and men (n = 1444) aged 21 to 93 years from the Jackson Heart Study (Jackson, Mississippi; 2000-2011). We assessed neighborhood disadvantage with a composite measure of 8 indicators from the 2000 US Census. We assessed neighborhood-level social conditions, including social cohesion, violence, and disorder, with self-reported, validated scales. RESULTS Among African American women, each standard deviation increase in neighborhood disadvantage was associated with a 25% increased risk of CVD after covariate adjustment (hazard ratio = 1.25; 95% confidence interval = 1.05, 1.49). Risk also increased as levels of neighborhood violence and physical disorder increased after covariate adjustment. We observed no statistically significant associations among African American men in adjusted models. CONCLUSIONS Worse neighborhood economic and social conditions may contribute to increased risk of CVD among African American women. Policies directly addressing these issues may alleviate the burden of CVD in this group.
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Affiliation(s)
- Sharrelle Barber
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - DeMarc A Hickson
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Xu Wang
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Mario Sims
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Cheryl Nelson
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Ana V Diez-Roux
- Sharrelle Barber, Xu Wang, and Ana V. Diez-Roux are with Drexel University School of Public Health, Department of Epidemiology and Biostatistics, and Center for Integrative Approaches to Health Disparities, Philadelphia, PA. DeMarc A. Hickson and Mario Sims are with University of Mississippi Medical Center, Jackson. Cheryl Nelson is with National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
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Howard VJ, McClure LA, Kleindorfer DO, Cunningham SA, Thrift AG, Diez Roux AV, Howard G. Neighborhood socioeconomic index and stroke incidence in a national cohort of blacks and whites. Neurology 2016; 87:2340-2347. [PMID: 27742815 DOI: 10.1212/wnl.0000000000003299] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 08/19/2016] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To assess the relationship between neighborhood socioeconomic characteristics and incident stroke in a national cohort of black and white participants. METHODS The study comprised black (n = 10,274, 41%) and white (n = 14,601) stroke-free participants, aged 45 and older, enrolled in 2003-2007 in Reasons for Geographic and Racial Differences in Stroke (REGARDS), a national population-based cohort. A neighborhood socioeconomic score (nSES) was constructed using 6 neighborhood variables. Incident stroke was defined as first occurrence of stroke over an average 7.5 (SD 3.0) years of follow-up. Proportional hazards models were used to estimate associations between nSES score and incident stroke, adjusted for demographics (age, race, sex, region), individual socioeconomic status (SES) (education, household income), and other risk factors for stroke. RESULTS After adjustment for demographics, compared to the highest nSES quartile, stroke incidence increased with each decreasing nSES quartile. The hazard ratio (95% confidence interval) ranged from 1.28 (1.05-1.56) in quartile 3 to 1.38 (1.13-1.68) in quartile 2 to 1.56 (1.26-1.92) in quartile 1 (p < 0.0001 for linear trend). After adjustment for individual SES, the trend remained marginally significant (p = 0.085). Although there was no evidence of a differential effect by race or sex, adjustment for stroke risk factors attenuated the association between nSES and stroke in both black and white participants, with greater attenuation in black participants. CONCLUSIONS Risk of incident stroke increased with decreasing nSES but the effect of nSES is attenuated through individual SES and stroke risk factors. The effect of neighborhood socioeconomic characteristics that contribute to increased stroke risk is similar in black and white participants.
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Affiliation(s)
- Virginia J Howard
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia.
| | - Leslie A McClure
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
| | - Dawn O Kleindorfer
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
| | - Solveig A Cunningham
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
| | - Amanda G Thrift
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
| | - Ana V Diez Roux
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
| | - George Howard
- From the Department of Epidemiology (V.J.H.), School of Public Health, University of Alabama at Birmingham; Department of Epidemiology and Biostatistics (L.A.M., G.H.), Dornsife School of Public Health (A.V.D.R.), Drexel University, Philadelphia, PA; Department of Neurology (D.O.K.), University of Cincinnati College of Medicine, OH; Hubert Department of Global Health and Department of Sociology (S.A.C.), Emory University, Atlanta, GA; Epidemiology & Prevention Division (A.G.T.), Stroke and Ageing Research (STARC), Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton; and The Florey Institute of Neuroscience and Mental Health (A.G.T.), Melbourne University, Heidelberg, Australia
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Kotlęga D, Gołąb-Janowska M, Masztalewicz M, Ciećwież S, Nowacki P. The emotional stress and risk of ischemic stroke. Neurol Neurochir Pol 2016; 50:265-70. [DOI: 10.1016/j.pjnns.2016.03.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Revised: 03/08/2016] [Accepted: 03/14/2016] [Indexed: 10/22/2022]
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Howard G, Moy CS, Howard VJ, McClure LA, Kleindorfer DO, Kissela BM, Judd SE, Unverzagt FW, Soliman EZ, Safford MM, Cushman M, Flaherty ML, Wadley VG. Where to Focus Efforts to Reduce the Black-White Disparity in Stroke Mortality: Incidence Versus Case Fatality? Stroke 2016; 47:1893-8. [PMID: 27256672 PMCID: PMC4927373 DOI: 10.1161/strokeaha.115.012631] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 04/18/2016] [Indexed: 12/21/2022]
Abstract
BACKGROUND AND PURPOSE At age 45 years, blacks have a stroke mortality ≈3× greater than their white counterparts, with a declining disparity at older ages. We assess whether this black-white disparity in stroke mortality is attributable to a black-white disparity in stroke incidence versus a disparity in case fatality. METHODS We first assess if black-white differences in stroke mortality within 29 681 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort reflect national black-white differences in stroke mortality and then assess the degree to which black-white differences in stroke incidence or 30-day case fatality after stroke contribute to the disparities in stroke mortality. RESULTS The pattern of stroke mortality within the study mirrors the national pattern, with the black-to-white hazard ratio of ≈4.0 at age 45 years decreasing to ≈1.0 at age 85 years. The pattern of black-to-white disparities in stroke incidence shows a similar pattern but no evidence of a corresponding disparity in stroke case fatality. CONCLUSIONS These findings show that the black-white differences in stroke mortality are largely driven by differences in stroke incidence, with case fatality playing at most a minor role. Therefore, to reduce the black-white disparity in stroke mortality, interventions need to focus on prevention of stroke in blacks.
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Affiliation(s)
- George Howard
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.).
| | - Claudia S Moy
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Virginia J Howard
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Leslie A McClure
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Dawn O Kleindorfer
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Brett M Kissela
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Suzanne E Judd
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Fredrick W Unverzagt
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Elsayed Z Soliman
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Monika M Safford
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Mary Cushman
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Matthew L Flaherty
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
| | - Virginia G Wadley
- From the Departments of Biostatistics (G.H., S.E.J.) and Epidemiology (V.J.H.), University of Alabama at Birmingham School of Public Health; Office of Clinical Research, NINDS/NIH, Bethesda, MD (C.S.M.); Department of Epidemiology and Biostatistics, Dornsife School of Public Health at Drexel University, Philadelphia, PA (L.A.M.); Department of Neurology, University of Cincinnati, OH (D.O.K., B.M.K., M.L.F.); Department of Psychology, Indiana University, Indianapolis (F.W.U.); Department of Epidemiology, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.); Department of General Internal Medicine, Weill Cornell School of Medicine, New York, NY (M.M.S., V.G.W.); and Department of Medicine, University of Vermont School of Medicine, Burlington (M.C.)
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Rosso AL, Flatt JD, Carlson MC, Lovasi GS, Rosano C, Brown AF, Matthews KA, Gianaros PJ. Neighborhood Socioeconomic Status and Cognitive Function in Late Life. Am J Epidemiol 2016; 183:1088-97. [PMID: 27257114 DOI: 10.1093/aje/kwv337] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Accepted: 12/02/2015] [Indexed: 11/12/2022] Open
Abstract
Neighborhood socioeconomic status (NSES) is associated with cognitive function, independently of individual demographic, health, and socioeconomic characteristics. However, research has been largely cross-sectional, and mechanisms of the association are unknown. In 1992-1993, Cardiovascular Health Study participants (n = 3,595; mean age = 74.8 years; 15.7% black) underwent cognitive testing and magnetic resonance imaging of white matter hyperintensities (WMH), and their addresses were geocoded. NSES was calculated using 1990 US Census data (block groups; 6 measures of wealth, education, and occupation). The Modified Mini-Mental State Examination (3MS) was used to assess general cognition, and the Digit Symbol Substitution Test (DSST) was used to assess speed of processing annually for 6 years. Associations of race-specific NSES tertiles with 3MS, DSST, and WMH were estimated using linear mixed-effects models accounting for geographic clustering, stratified by race, and adjusted for demographic, health, and individual socioeconomic status (education, income, lifetime occupational status) variables. In fully adjusted models, higher NSES was associated with higher 3MS scores in blacks (mean difference between highest and lowest NSES = 2.4 points; P = 0.004) and whites (mean difference = 0.7 points; P = 0.02) at baseline but not with changes in 3MS over time. NSES was marginally associated with DSST and was not associated with WMH. Adjustment for WMH did not attenuate NSES-3MS associations. Associations of NSES with cognition in late adulthood differ by race, are not explained by WMH, and are evident only at baseline.
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Shin J, Cho KH, Choi Y, Lee SG, Park EC, Jang SI. Combined effect of individual and neighborhood socioeconomic status on mortality in patients with newly diagnosed dyslipidemia: A nationwide Korean cohort study from 2002 to 2013. Nutr Metab Cardiovasc Dis 2016; 26:207-215. [PMID: 26895648 DOI: 10.1016/j.numecd.2015.12.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Revised: 11/09/2015] [Accepted: 12/14/2015] [Indexed: 10/22/2022]
Abstract
BACKGROUND AND AIM The study aims to determine whether dyslipidemia patients living in less affluent neighborhood are at a higher risk of mortality compared to those living in more affluent neighborhoods. METHODS AND RESULTS A population-based cohort study was conducted using a stratified representative sampling from the National Health Insurance claim data from 2002 to 2013. The target subjects comprise patients newly diagnosed with dyslipidemia receiving medication. We performed a survival analysis using the Cox proportional hazard model. Of 11,946 patients with dyslipidemia, 1053 (8.8%) subjects died during the follow-up period. Of the dyslipidemia patients earning a middle-class income, the adjusted HR in less affluent neighborhoods was higher than that in the more affluent neighborhoods compared to the reference category of high individual SES in more affluent neighborhoods (less affluent; hazard ratio (HR) = 1.64, 95% confidence interval (CI): 1.35-1.99 vs. more affluent; HR = 1.48, 95% CI: 1.20-1.81, respectively). We obtained consistent results in patients with lower income, wherein the adjusted HR in less affluent neighborhoods was higher than that in more affluent neighborhoods (less affluent; HR = 1.52, 95% CI: 1.16-1.97 vs. more affluent; HR = 1.41, 95% CI: 1.04-1.92, respectively). CONCLUSION Living in a less affluent neighborhood contributes to higher mortality among dyslipidemia patients. The individual- and neighborhood-level variables cumulatively affect individuals such that the most at-risk individuals include those having both individual- and neighborhood-level risk factors. These findings raise important clinical and public health concerns and indicate that neighborhood SES approaches should be essentially considered in health-care policies similar to individual SES.
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Affiliation(s)
- J Shin
- Institute of Health Services Research, College of Medicine, Yonsei University, South Korea; Department of Preventive Medicine, College of Medicine, Yonsei University, South Korea
| | - K H Cho
- Department of Public Health, Graduate School, Yonsei University, South Korea; Institute of Health Services Research, College of Medicine, Yonsei University, South Korea
| | - Y Choi
- Department of Public Health, Graduate School, Yonsei University, South Korea; Institute of Health Services Research, College of Medicine, Yonsei University, South Korea
| | - S G Lee
- Institute of Health Services Research, College of Medicine, Yonsei University, South Korea; Department of Hospital Management, Graduate School of Public Health, Yonsei University, South Korea
| | - E-C Park
- Institute of Health Services Research, College of Medicine, Yonsei University, South Korea; Department of Preventive Medicine, College of Medicine, Yonsei University, South Korea
| | - S-I Jang
- Institute of Health Services Research, College of Medicine, Yonsei University, South Korea; Department of Preventive Medicine, College of Medicine, Yonsei University, South Korea.
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Lower Neighborhood Socioeconomic Status Associated with Reduced Diversity of the Colonic Microbiota in Healthy Adults. PLoS One 2016; 11:e0148952. [PMID: 26859894 PMCID: PMC4747579 DOI: 10.1371/journal.pone.0148952] [Citation(s) in RCA: 98] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Accepted: 12/22/2015] [Indexed: 12/14/2022] Open
Abstract
In the United States, there are persistent and widening socioeconomic gaps in morbidity and mortality from chronic diseases. Although most disparities research focuses on person-level socioeconomic-status, mounting evidence suggest that chronic diseases also pattern by the demographic characteristics of neighborhoods. Yet the biological mechanisms underlying these associations are poorly understood. There is increasing recognition that chronic diseases share common pathogenic features, some of which involve alterations in the composition, diversity, and functioning of the gut microbiota. This study examined whether socioeconomic-status was associated with alpha-diversity of the colonic microbiota. Forty-four healthy adults underwent un-prepped sigmoidoscopy, during which mucosal biopsies and fecal samples were collected. Subjects’ zip codes were geocoded, and census data was used to form a composite indicator of neighborhood socioeconomic-status, reflecting household income, educational attainment, employment status, and home value. In unadjusted analyses, neighborhood socioeconomic-status explained 12–18 percent of the variability in alpha-diversity of colonic microbiota. The direction of these associations was positive, meaning that as neighborhood socioeconomic-status increased, so did alpha-diversity of both the colonic sigmoid mucosa and fecal microbiota. The strength of these associations persisted when models were expanded to include covariates reflecting potential demographic (age, gender, race/ethnicity) and lifestyle (adiposity, alcohol use, smoking) confounds. In these models neighborhood socioeconomic-status continued to explain 11–22 percent of the variability in diversity indicators. Further analyses suggested these patterns reflected socioeconomic variations in evenness, but not richness, of microbial communities residing in the sigmoid. We also found indications that residence in neighborhoods of higher socioeconomic-status was associated with a greater abundance of Bacteroides and a lower abundance of Prevotella, suggesting that diet potentially underlies differences in microbiota composition. These findings suggest the presence of socioeconomic variations in colonic microbiota diversity. Future research should explore whether these variations contribute to disparities in chronic disease outcomes.
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Yan T, Liang LJ, Vassar S, Katz MC, Escarce JJ, Longstreth WTJ, Merkin SS, Brown AF. Neighborhood Characteristics are Associated with Racial and Gender Variation in Walking among Older Adults: the Cardiovascular Health Study. Ethn Dis 2016; 26:17-26. [PMID: 26843792 DOI: 10.18865/ed.26.1.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE To examine variation by race and gender in the association between neighborhood socioeconomic status and walking among community-dwelling older adults. DESIGN Cross-sectional. SETTING Cardiovascular Health Study, a longitudinal population-based cohort. PARTICIPANTS 4,849 adults, aged > 65 years. MEASUREMENTS Participants reported the number of city blocks walked in the prior week. Neighborhood socioeconomic status (NSES) was measured at the level of the census tract. Negative binominal regression models were constructed to test the association between NSES and blocks walked. In the fully adjusted models, we included two-way and three-way interaction terms among race, gender, and NSES. RESULTS In adjusted analyses, among White residents in the lowest NSES quartile (most disadvantaged), men walked 64% more than women (P<.001), while in the highest NSES (most advantaged), men walked 43% more than women (P<.001). Among African American residents in the lowest NSES quartile, men walked 196% more blocks than women (P<.001). CONCLUSIONS Female gender is more strongly associated with walking for African Americans than for Whites in low SES neighborhoods but had a similar association with walking for both African Americans and Whites in high SES neighborhoods.
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Affiliation(s)
| | - Li-Jung Liang
- UCLA Geffen School of Medicine, Department of Medicine, Division of General Internal Medicine and Health Services Research
| | - Stefanie Vassar
- UCLA Geffen School of Medicine, Department of Medicine, Division of General Internal Medicine and Health Services Research
| | | | - Jose J Escarce
- UCLA Geffen School of Medicine, Department of Medicine, Division of General Internal Medicine and Health Services Research
| | | | | | - Arleen F Brown
- UCLA Geffen School of Medicine, Department of Medicine, Division of General Internal Medicine and Health Services Research
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48
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Howard G, Howard VJ. Stroke Disparities. Stroke 2016. [DOI: 10.1016/b978-0-323-29544-4.00014-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Linton SL, Cooper HLF, Kelley ME, Karnes CC, Ross Z, Wolfe ME, Des Jarlais D, Semaan S, Tempalski B, DiNenno E, Finlayson T, Sionean C, Wejnert C, Paz-Bailey G. HIV Infection Among People Who Inject Drugs in the United States: Geographically Explained Variance Across Racial and Ethnic Groups. Am J Public Health 2015; 105:2457-65. [PMID: 26469638 PMCID: PMC4638266 DOI: 10.2105/ajph.2015.302861] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2015] [Indexed: 11/04/2022]
Abstract
OBJECTIVES We explored how variance in HIV infection is distributed across multiple geographical scales among people who inject drugs (PWID) in the United States, overall and within racial/ethnic groups. METHODS People who inject drugs (n = 9077) were recruited via respondent-driven sampling from 19 metropolitan statistical areas (MSAs) for the Centers for Disease Control and Prevention's 2009 National HIV Behavioral Surveillance system. We used multilevel modeling to determine the percentage of variance in HIV infection explained by zip codes, counties, and MSAs where PWID lived, overall and for specific racial/ethnic groups. RESULTS Collectively, zip codes, counties, and MSAs explained 29% of variance in HIV infection. Within specific racial/ethnic groups, all 3 scales explained variance in HIV infection among non-Hispanic/Latino White PWID (4.3%, 0.2%, and 7.5%, respectively), MSAs explained variance among Hispanic/Latino PWID (10.1%), and counties explained variance among non-Hispanic/Latino Black PWID (6.9%). CONCLUSIONS Exposure to potential determinants of HIV infection at zip codes, counties, and MSAs may vary for different racial/ethnic groups of PWID, and may reveal opportunities to identify and ameliorate intraracial inequities in exposure to determinants of HIV infection at these geographical scales.
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Affiliation(s)
- Sabriya L Linton
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Hannah L F Cooper
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Mary E Kelley
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Conny C Karnes
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Zev Ross
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Mary E Wolfe
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Don Des Jarlais
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Salaam Semaan
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Barbara Tempalski
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Elizabeth DiNenno
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Teresa Finlayson
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Catlainn Sionean
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Cyprian Wejnert
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
| | - Gabriela Paz-Bailey
- Sabriya L. Linton, Hannah L. F. Cooper, Mary E. Kelley, Conny C. Karnes, and Mary E. Wolfe are with The Rollins School of Public Health at Emory University, Atlanta, GA. Zev Ross is with ZevRoss SpatialAnalysis, Ithaca, NY. Don Des Jarlais is with The Baron Edmond de Rothschild Chemical Dependency Institute, Mount Sinai Beth Israel, New York, NY. Barbara Tempalski is with The Institute for Infectious Disease Research, National Development and Research Institutes, New York, NY. Salaam Semaan, Elizabeth DiNenno, Teresa Finlayson, Catlainn Sionean, Cyprian Wejnert, and Gabriela Paz-Bailey are with the Centers for Disease Control and Prevention, Atlanta
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Nayyar D, Hwang SW. Cardiovascular Health Issues in Inner City Populations. Can J Cardiol 2015; 31:1130-8. [DOI: 10.1016/j.cjca.2015.04.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Revised: 04/06/2015] [Accepted: 04/06/2015] [Indexed: 11/28/2022] Open
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