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Rappazzo KM, Egerstrom NM, Wu J, Capone AB, Joodi G, Keen S, Cascio WE, Simpson RJ. Fine particulate matter-sudden death association modified by ventricular hypertrophy and inflammation: a case-crossover study. Front Public Health 2024; 12:1367416. [PMID: 38835616 PMCID: PMC11148389 DOI: 10.3389/fpubh.2024.1367416] [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: 01/08/2024] [Accepted: 04/23/2024] [Indexed: 06/06/2024] Open
Abstract
Background Sudden death accounts for approximately 10% of deaths among working-age adults and is associated with poor air quality. Objectives: To identify high-risk groups and potential modifiers and mediators of risk, we explored previously established associations between fine particulate matter (PM2.5) and sudden death stratified by potential risk factors. Methods Sudden death victims in Wake County, NC, from 1 March 2013 to 28 February 2015 were identified by screening Emergency Medical Systems reports and adjudicated (n = 399). Daily PM2.5 concentrations for Wake County from the Air Quality Data Mart were linked to event and control periods. Potential modifiers included greenspace metrics, clinical conditions, left ventricular hypertrophy (LVH), and neutrophil-to-lymphocyte ratio (NLR). Using a case-crossover design, conditional logistic regression estimated the OR (95%CI) for sudden death for a 5 μg/m3 increase in PM2.5 with a 1-day lag, adjusted for temperature and humidity, across risk factor strata. Results Individuals having LVH or an NLR above 2.5 had PM2.5 associations of greater magnitude than those without [with LVH OR: 1.90 (1.04, 3.50); NLR > 2.5: 1.25 (0.89, 1.76)]. PM2.5 was generally less impactful for individuals living in areas with higher levels of greenspace. Conclusion LVH and inflammation may be the final step in the causal pathway whereby poor air quality and traditional risk factors trigger arrhythmia or myocardial ischemia and sudden death. The combination of statistical evidence with clinical knowledge can inform medical providers of underlying risks for their patients generally, while our findings here may help guide interventions to mitigate the incidence of sudden death.
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Affiliation(s)
- Kristen M Rappazzo
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Research Triangle Park, NC, United States
| | - Nicole M Egerstrom
- Gillings Global School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jianyong Wu
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, United States
| | - Alia B Capone
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Family Medicine, University of Maryland Medical Center, Baltimore, MD, United States
| | - Golsa Joodi
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Division of Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Susan Keen
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cardiovascular Medicine, Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
| | - Wayne E Cascio
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Research Triangle Park, NC, United States
| | - Ross J Simpson
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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Conners KM, Avery CL, Syed FF. Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina. N C Med J 2024; 85:10.18043/001c.91424. [PMID: 38938760 PMCID: PMC11208038 DOI: 10.18043/001c.91424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysfunction. By identifying accelerated cardiac aging from the ECG, AI offers novel insights into risk assessment and prevention.
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Affiliation(s)
- Katherine M Conners
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Faisal F Syed
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina
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Sefton C, Keen S, Tybout C, Lin FC, Jiang H, Joodi G, Williams JG, Simpson RJ. Characteristics of sudden death by clinical criteria. Medicine (Baltimore) 2023; 102:e33029. [PMID: 37083784 PMCID: PMC10118332 DOI: 10.1097/md.0000000000033029] [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: 12/15/2022] [Accepted: 01/30/2023] [Indexed: 04/22/2023] Open
Abstract
Sudden death is a leading cause of deaths nationally. Definitions of sudden death vary greatly, resulting in imprecise estimates of its frequency and incomplete knowledge of its risk factors. The degree to which time-based and coronary artery disease (CAD) criteria impacts estimates of sudden death frequency and risk factors is unknown. Here, we apply these criteria to a registry of all-cause sudden death to assess its impact on sudden death frequency and risk factors. The sudden unexpected death in North Carolina (SUDDEN) project is a registry of out of-hospital, adjudicated, sudden unexpected deaths attended by Emergency Medical Services. Deaths were not excluded by time since last seen or alive or by prior symptoms or diagnosis of CAD. Common criteria for sudden death based on time since last seen alive (both 24 hours and 1 hour) and prior diagnosis of CAD were applied to the SUDDEN case registry. The proportion of cases satisfying each of the 4 criteria was calculated. Characteristics of victims within each restrictive set of criteria were measured and compared to the SUDDEN registry. There were 296 qualifying sudden deaths. Application of 24 hour and 1 hour timing criteria compared to no timing criteria reduced cases by 25.0% and 69.6%, respectively. Addition of CAD criteria to each timing criterion further reduced qualifying cases, for a total reduction of 81.8% and 90.5%, respectively. However, characteristics among victims meeting restrictive criteria remained similar to the unrestricted population. Timing and CAD criteria dramatically reduces estimates of the number of sudden deaths without significantly impacting victim characteristics.
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Affiliation(s)
- Christopher Sefton
- Internal Medicine Residency Program, Cleveland Clinic Foundation, Cleveland, OH
| | - Susan Keen
- Heart and Vascular Institute, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Caroline Tybout
- Department of Anesthesiology, The Ohio State University Wexner Medical Center, Columbus, OH
| | - Feng-Chang Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Huijun Jiang
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC
| | - Golsa Joodi
- Division of Cardiology, University of California, Los Angeles, CA
| | | | - Ross J. Simpson
- Division of Cardiology, University of North Carolina, Chapel Hill, NC
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4
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Barnes JW, Massing M, Dugyala S, Cottoms N, Pursell IW. Design of a Novel Intervention Model to Address Cardiovascular Health Disparities in the Rural Underserved Community of Phillips County Arkansas. Health Equity 2022; 6:248-253. [PMID: 35402777 PMCID: PMC8985529 DOI: 10.1089/heq.2021.0175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2022] [Indexed: 11/30/2022] Open
Abstract
Devastating health-related disparities driven by an entanglement of factors disproportionately impact the underserved, low-wealth, and minority community of Phillips county (PC) in the Arkansas Delta Region (ADR). Cardiovascular disease continues to increase with widespread consequences on the local economy, health care systems, and population. Health care and community-based systems have been unsuccessful in reducing out-of-hospital cardiac death, particularly in the ADR, for many reasons. Herein, we share the strategy behind, planning, and goals of The Arkansas Lincoln Project, a novel neighborhood-based strategy bridging the gap between residents, social resources, and health care services in PC.
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Affiliation(s)
- Jessica W. Barnes
- Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Mark Massing
- Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Sushma Dugyala
- Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Naomi Cottoms
- Tri County Rural Health Network Helena, West Helena, Arkansas, USA
| | - Irion W. Pursell
- Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
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5
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Ford J, Bushnell G, Griffith AM, Joodi G, Ashoka A, Patel N, Husain M, Pursell IW, Sears SF, Mounsey JP, Simpson RJ. Mental Disorders, Substance Use Disorders, and Psychotropic Medication Use Among Sudden-Death Victims. Psychiatr Serv 2021; 72:378-383. [PMID: 33593102 DOI: 10.1176/appi.ps.201900389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE The authors sought to estimate the prevalence of mental and substance use disorders and psychotropic medication prescriptions among working-age sudden-death victims. METHODS Using a written protocol, the authors screened for sudden deaths attended by emergency medical services (EMS) in a large metropolitan county in North Carolina from March 1, 2013, to February 28, 2015. Sudden-death cases were adjudicated by three cardiologists. Mental health and chronic disease diagnoses and treatments were abstracted from EMS, medical examiner, toxicology, and autopsy reports and from clinical records for the past 5 years before death. RESULTS Sudden death was identified for 399 adults ages 18-64 years, 270 of whom had available medical records. Most sudden-death victims were White (63%) and male (65%), had a comorbid condition such as hypertension or respiratory disease, and had a mean±SD age of death of 53.6±8.8 years. Most victims (59%) had at least one mental health or substance use disorder documented in a recent medical record; 76%-78% of victims with a mental disorder had a documented psychotropic medication prescription. However, fewer than one-half (41%) had a documented referral to a mental health professional. The most common diagnostic categories were depressive, anxiety, and alcohol-related disorders. Almost one-half (46%) of the victims had a recent psychotropic prescription, most commonly antidepressants (29%) and benzodiazepines (19%). CONCLUSIONS Mental illness, substance use disorders, and psychotropic medication prescriptions were prevalent among sudden-death victims. The health care needs of these individuals may be better addressed by collaborative care for general medical and mental disorders.
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Affiliation(s)
- Jessica Ford
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Greta Bushnell
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Ashley M Griffith
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Golsa Joodi
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Ankita Ashoka
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Neil Patel
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Mariya Husain
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Irion W Pursell
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Samuel F Sears
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - John Paul Mounsey
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
| | - Ross J Simpson
- Department of Psychology, East Carolina University, Greenville, North Carolina (Ford, Griffith, Sears); Mental and Behavioral Health Service Line, Greenville Health Care Center, Durham U.S. Department of Veterans Affairs Medical Center, Greenville, North Carolina (Ford); Department of Biostatistics and Epidemiology, Rutgers University, New Brunswick, New Jersey (Bushnell); School of Medicine, Yale University, New Haven, Connecticut (Joodi); School of Medicine, University of Arizona, Tucson (Ashoka); Department of Cardiology and Cardiac Electrophysiology, University of North Carolina, Chapel Hill (Patel, Husain, Simpson); Department of Medical Specialties, University of Arkansas for Medical Sciences, Little Rock (Pursell, Mounsey)
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6
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Sadaf MI, Caldwell M, Young LA, Mirzaei M, Chen S, Joodi G, Lin FC, Wu Y, Simpson RJ. High Prevalence of Diabetes Mellitus and Mental Illness Among Victims of Sudden Death. South Med J 2021; 114:86-91. [PMID: 33537789 DOI: 10.14423/smj.0000000000001213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVES Diabetes mellitus (DM) increases the risk of cardiovascular disease and is associated with sudden death. Mental illness among individuals with DM may confound medical care. This study assessed the association of mental illness with DM and poorly controlled DM in sudden death victims. METHODS We screened out-of-hospital deaths ages 18 to 64 years in Wake County, North Carolina from 2013 to 2015 to adjudicate sudden deaths. We abstracted demographics and clinical characteristics from health records. Mental illness included anxiety, schizophrenia, bipolar disorder, or depression. Poorly controlled DM was defined as a hemoglobin A1c >8 or taking ≥3 medications for glycemic control. Logistic regression assessed the association between DM and mental illness. RESULTS Among victims with available records, 109 (29.4%) had DM. Of those, 62 (56.9%) had mental illness. Mental illness was present in 53.42% and 63.89% of victims with mild and poorly controlled DM, respectively. Mental illness was associated with DM (adjusted odds ratio 2.46, 95% confidence interval 1.57-3.91). Victims with poorly controlled DM were more likely to have mental illness (adjusted odds ratio 2.66, 95% confidence interval 1.14-6.18). CONCLUSIONS DM is a common comorbid condition in sudden death victims. Among victims, mental illness is associated with the control of DM. Early management of comorbid mental illnesses may improve the care of patients with DM and reduce the incidence of sudden death.
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Affiliation(s)
- Murrium I Sadaf
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Marie Caldwell
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Laura A Young
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Mojtaba Mirzaei
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Sarah Chen
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Golsa Joodi
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Feng-Chang Lin
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Yunhan Wu
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Ross J Simpson
- From the Department of Internal Medicine, Yale-New Haven Medical Center, Waterbury, Connecticut, the Department of Medicine, Division of Endocrinology, Maine Medical Partners Endocrinology & Diabetes Center, Scarborough, Maine, the Department of Medicine, Division of Endocrinology, University of North Carolina, Chapel Hill, the Department of Medicine, Division of Cardiology, University of North Carolina, Chapel Hill, the Division of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, and the Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
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Abstract
INTRODUCTION Since the 1950s, heart disease deaths have declined in the United States, but recent reports indicate a plateau in this decline. Heart disease death rates increased in Maine from 2011-2015. We examined reasons for the trend change in Maine's heart disease death rates, including the contributing types of heart disease. METHODS We obtained Maine's annual heart disease death data for 1999-2017 from CDC's Wide-ranging Online Data for Epidemiologic Research (CDC WONDER). We used joinpoint regression to determine changes in trend and annual percentage change (APC) in death rates for heart disease overall and by demographic groups, types of heart disease, and geographic area. RESULTS Joinpoint modeling showed that Maine's age-adjusted heart disease death rates decreased during 1999-2010 (-4.2% APC), then plateaued during 2010-2017 (-0.1% APC). Death rates flattened for both sexes and age groups ≥45 years. Although death rates for acute myocardial infarction (AMI) decreased through 2017, hypertensive heart disease (HHD) and heart failure death rates increased. Death rates attributable to diabetes-related heart disease and non-AMI ischemic heart disease (IHD) plateaued. CONCLUSION Declines in Maine's heart disease death rates have plateaued, similar to national trends. Flattening rates appear to be driven by adverse trends in HHD, heart failure, diabetes-related heart disease, and non-AMI IHD. Increased efforts to address cardiovascular disease risk factors, chronic heart disease, and access to care are necessary to continue the decrease in heart disease deaths in Maine.
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Affiliation(s)
- Jennifer A Sinatra
- Epidemic Intelligence Service, Division of Scientific Education and Professional Development, Centers for Disease Control and Prevention, Atlanta, Georgia
- Maine Department of Health and Human Services, 286 Water St, 8th Floor, 11 State House Station, Augusta, ME 04333.
| | - Sara L Huston
- Maine Department of Health and Human Services, Augusta, Maine
- University of Southern Maine, Portland, Maine
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Paratz ED, Rowsell L, Zentner D, Parsons S, Morgan N, Thompson T, James P, Pflaumer A, Semsarian C, Smith K, Stub D, La Gerche A. Cardiac arrest and sudden cardiac death registries: a systematic review of global coverage. Open Heart 2020; 7:e001195. [PMID: 32076566 PMCID: PMC6999684 DOI: 10.1136/openhrt-2019-001195] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/16/2019] [Accepted: 01/02/2020] [Indexed: 12/27/2022] Open
Abstract
Background Sudden cardiac death (SCD) is a major global health problem, accounting for up to 20% of deaths in Western societies. Clinical quality registries have been shown in a range of disease conditions to improve clinical management, reduce variation in care and improve outcomes. Aim To identify existing cardiac arrest (CA) and SCD registries, characterising global coverage and methods of data capture and validation. Methods Biomedical and public search engines were searched with the terms ‘registry cardio*’; ‘sudden cardiac death registry’ and ‘cardiac arrest registry’. Registries were categorised as either CA, SCD registries or ‘other’ according to prespecified criteria. SCD registry coordinators were contacted for contemporaneous data regarding registry details. Results Our search strategy identified 49 CA registries, 15 SCD registries and 9 other registries (ie, epistries). Population coverage of contemporary CA and SCD registries is highly variable with registries densely concentrated in North America and Western Europe. Existing SCD registries (n=15) cover a variety of age ranges and subpopulations, with some enrolling surviving patients (n=8) and family members (n=5). Genetic data are collected by nine registries, with the majority of these (n=7) offering indefinite storage in a biorepository. Conclusions Many CA registries exist globally, although with inequitable population coverage. Comprehensive multisource surveillance SCD registries are fewer in number and more challenging to design and maintain. Challenges identified include maximising case identification and case verification. Trial registration number CRD42019118910.
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Affiliation(s)
- Elizabeth Davida Paratz
- Baker Heart Research Institute - BHRI, Melbourne, Victoria, Australia.,Cardiology Department, St Vincent's Hospital, Melbourne, VIC, Australia.,Cardiology, The Alfred Hospital, Melbourne, VIC, Australia
| | - Luke Rowsell
- Baker Heart Research Institute - BHRI, Melbourne, Victoria, Australia
| | - Dominica Zentner
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Department of Cardiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Sarah Parsons
- Victorian Institute of Forensic Medicine, Southbank, Victoria, Australia
| | - Natalie Morgan
- Victorian Institute of Forensic Medicine, Southbank, Victoria, Australia
| | - Tina Thompson
- Department of Cardiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Paul James
- Department of Cardiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia.,Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Andreas Pflaumer
- Department of Cardiology, Royal Childrens Hospital Melbourne, Parkville, Victoria, Australia.,Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | | | - Karen Smith
- Research & Evaluation, Ambulance Victoria, Blackburn North, Victoria, Australia.,Community Emergency Health & Paramedic Practice, Monash University, Melbourne, VIC, Australia
| | - Dion Stub
- Cardiology, The Alfred Hospital, Melbourne, VIC, Australia.,Public Health & Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Andre La Gerche
- Baker Heart Research Institute - BHRI, Melbourne, Victoria, Australia.,Cardiology Department, St Vincent's Hospital, Melbourne, VIC, Australia.,Cardiology, The Alfred Hospital, Melbourne, VIC, Australia.,Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
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Rappazzo KM, Joodi G, Hoffman SR, Pursell IW, Mounsey JP, Cascio WE, Simpson RJ. A case-crossover analysis of the relationship of air pollution with out-of-hospital sudden unexpected death in Wake County, North Carolina (2013-2015). THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 694:133744. [PMID: 31756798 PMCID: PMC6876709 DOI: 10.1016/j.scitotenv.2019.133744] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 07/10/2019] [Accepted: 08/01/2019] [Indexed: 05/30/2023]
Abstract
Out-of-hospital sudden unexpected deaths are non-accidental deaths that occur without obvious underlying causes and may account for 10% of natural deaths before age 65. Short-term exposure to ambient air pollution is associated with all-cause (non-accidental) and cause-specific (e.g., cardiovascular) mortality, and with immediate exposures often yielding the highest magnitude risk estimates. Few studies have focused on short-term exposure to air pollution and sudden unexpected deaths. Using the University of North Carolina Sudden Unexpected Death in North Carolina population, we examine associations between short-term criteria air pollutant exposures with sudden unexpected deaths using a time-stratified case-crossover design, with data on criteria air pollutants from the Environmental Protection Agency's Air Quality System. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression with air pollutant exposures scaled to roughly inter-quartile ranges; models were adjusted for average temperature and relative humidity on event day and preceding 3 days. Potential for confounding by co-pollutants were examined in two pollutant models. ORs for PM2.5 at lag day 1 were elevated (adjusted OR for 5 μg/m3 increase: 1.17 (0.98, 1.40)), and were robust to co-pollutant adjustment. Elevated odds were observed for SO2 at lag day 0, and reduced odds for O3 at lag day 0; however, these associations were somewhat attenuated toward the null (SO2) or were not robust (O3) to co-pollutant adjustment. This analysis in a racially and socioeconomically diverse cohort, with a more inclusive definition of sudden unexpected death than is typically employed offers evidence that PM2.5 may be a clinically relevant trigger of sudden unexpected deaths in susceptible individuals.
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Affiliation(s)
- Kristen M Rappazzo
- U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, 27711, NC, USA.
| | - Golsa Joodi
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, 27514, NC, USA
| | - Sarah R Hoffman
- Oak Ridge Associated Universities, contractor to U.S. Environmental Protection Agency, Research Triangle Park, 27711, NC, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, 27514, NC, USA
| | - Irion W Pursell
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, 27514, NC, USA
| | - J Paul Mounsey
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, 27514, NC, USA
| | - Wayne E Cascio
- U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, 27711, NC, USA
| | - Ross J Simpson
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, 27514, NC, USA
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Mirzaei M, Joodi G, Bogle B, Chen S, Simpson RJ. Years of Life and Productivity Loss Because of Adult Sudden Unexpected Death in the United States. Med Care 2019; 57:498-502. [PMID: 31107395 PMCID: PMC6565486 DOI: 10.1097/mlr.0000000000001129] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND Few studies have evaluated the years of life lost (YLL) and productivity loss due to sudden unexpected death (SUD). The burden of SUD on society is undetermined because of lack of population-based studies and comprehensive adjudication methods. OBJECTIVE We estimated YLL and productivity loss from SUD in working-age adults and compared it with the leading causes of death in the United States. METHODS We screened all out of hospital deaths among people aged 20-64 in Wake County, NC from 2013 to 2015 to adjudicate SUDs. We extrapolated Wake County incidence to estimate the age-standardized and sex-standardized rate of SUD in the United States. YLL was calculated based on the remaining life expectancy of the victims. Incorporating market and housekeeping value estimated the present value of lifetime productivity loss because of SUD. RESULTS SUD incidence rates in the US adults aged 20-64 were 49.3 (95% confidence interval, 41.2-58.3) and 21.7 (95% confidence interval, 16.5-27.8) per 100,000 among men and women, respectively. SUD resulted in the loss of 2 million years of life, accounting for 10.0% of YLL from all causes of death. Among natural causes of death, YLL from SUD was only lower than that from all cancers combined and heart disease. Lifetime productivity loss because of SUD was ~$51 billion, exceeding productivity loss from any individual cancer. CONCLUSION SUD is an important source of YLL and productivity loss among adults aged 20-64. Such a high burden on society justifies prioritizing health policies and interventions toward preventing SUD.
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Affiliation(s)
- Mojtaba Mirzaei
- Department of Medicine, Division of Cardiology, University
of North Carolina at Chapel Hill
| | - Golsa Joodi
- Department of Medicine, Division of Cardiology, University
of North Carolina at Chapel Hill
| | - Brittany Bogle
- Department of Epidemiology, Gillings School of Public
Health, University of North Carolina at Chapel Hill
| | - Sarah Chen
- Department of Medicine, Division of Cardiology, University
of North Carolina at Chapel Hill
| | - Ross J Simpson
- Department of Medicine, Division of Cardiology, University
of North Carolina at Chapel Hill
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Hosadurg N, Bogle BM, Joodi G, Sadaf MI, Pursell I, Mendys PM, Mounsey JP, Simpson RJ. Lipid Profiles in Out-of-Hospital Sudden Unexpected Death. Mayo Clin Proc Innov Qual Outcomes 2018; 2:257-266. [PMID: 30225459 PMCID: PMC6132208 DOI: 10.1016/j.mayocpiqo.2018.06.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2018] [Revised: 06/24/2018] [Accepted: 06/27/2018] [Indexed: 11/18/2022] Open
Abstract
Objective To determine the association between serum lipid measurements and the occurrence of out-of-hospital sudden unexpected death (OHSUD). Patients and Methods We compared 139 OHSUD cases (43 female patients [30.9%]) and 968 controls (539 female patients [55.7%]) from Wake County, North Carolina, from March 1, 2013, through February 28, 2015. Individuals were included if they were aged 18 to 64 years and had lipid measurements in the 5 years before their death (cases) or the most recent health care encounter (controls). Covariates were abstracted from medical records for all subjects, and those with triglyceride (TG) levels greater than 400 mg/dL (to convert to mmol/L, multiply by 0.0259) were excluded for low-density lipoprotein (LDL)–related analyses. Results By linear regression using age- and sex-adjusted models, cases of OHSUD had lower adjusted mean total cholesterol (170.3±52.2 mg/dL vs 188.9±39.7 mg/dL; P<.001), LDL cholesterol (90.9±39.6 mg/dL vs 109.6±35.2 mg/dL; P<.001), and non–high-density lipoprotein (HDL) (121.6±49.8 mg/dL vs 134.3±39.6 mg/dL; P<.001) levels and a higher adjusted TG/HDL-C ratio (4.7±7 vs 3±2.7; P<.001) than did controls. By logistic regression using age- and sex-adjusted models, the odds of OHSUD were elevated per unit increase in TG/HDL-C ratio (1.08; 95% CI, 1.03-1.12). Conclusion Out-of-hospital sudden unexpected death cases had more favorable levels of total cholesterol, LDL cholesterol, and non-HDL, possibly indicating a lack of association between traditional lipid cardiovascular risk factors and sudden unexpected death. A comparatively elevated TG/HDL-C ratio in cases may corroborate an evolving hypothesis of how vasoactive and prothrombotic remnant-like lipoprotein particles contribute to sudden unexpected death.
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Affiliation(s)
- Nisha Hosadurg
- Department of Internal Medicine, Tufts University School of Medicine, Boston, MA
- Correspondence: Address to Nisha Hosadurg, MD, Department of Internal Medicine, Tufts Medical Center, 800 Washington St, Boston, MA 02111.
| | - Brittany M. Bogle
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Golsa Joodi
- Division of Cardiology, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Murrium I. Sadaf
- Division of Cardiology, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Irion Pursell
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Philip M. Mendys
- Department of Cardiovascular Sciences, East Carolina University, Greenville, NC
| | - John P. Mounsey
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Ross J. Simpson
- Division of Cardiology, University of North Carolina School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Patel S, Conover MM, Joodi G, Chen S, Simpson RJ, Deyo ZM. Medication Use in Women and Men With Sudden Unexpected Death. Ann Pharmacother 2018; 52:868-875. [PMID: 29652176 DOI: 10.1177/1060028018771061] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND In Wake County, NC, sudden unexpected death accounts for 10% to 15% of all natural deaths in individuals 18 to 64 years old. Medications such as aspirin, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, statins, and β-blockers are recommended in guidelines to reduce cardiovascular events and even sudden death (β-blockers). However, guidelines are often underpracticed, even in high-risk patients, with noted disparities in women. OBJECTIVE We assessed the relation between prescription of evidence-based medications and sudden unexpected death in Wake County, NC. METHODS We analyzed 399 cases of sudden unexpected death for the time period March 1, 2013 to February 28, 2015 in Wake County, NC. Medications were assessed from available medical examiner reports and medical records and grouped using the third level of the Anatomical Therapeutic Chemical Classification System (ATC) codes. This study was reviewed and exempt by the University of North Carolina's institutional review board. RESULTS Among 126 female and 273 male victims, women were prescribed more medications overall than men (6.5 vs 4.3, P = 0.001); however, the use of guideline-directed therapies was not different between genders in the chronic conditions associated with sudden death. Overall, there was remarkably low use of evidence-based medications. CONCLUSIONS Our findings highlight the need to improve prescribing of evidence-based medications and to further explore the relationship between undertreatment and sudden unexpected death.
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Affiliation(s)
- Sonalie Patel
- 1 University of North Carolina Medical Center, Chapel Hill, NC, USA
| | - Mitchell M Conover
- 2 University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Golsa Joodi
- 3 University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Sarah Chen
- 3 University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Ross J Simpson
- 3 University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Zachariah M Deyo
- 1 University of North Carolina Medical Center, Chapel Hill, NC, USA
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Wu J, Rappazzo KM, Simpson RJ, Joodi G, Pursell IW, Mounsey JP, Cascio WE, Jackson LE. Exploring links between greenspace and sudden unexpected death: A spatial analysis. ENVIRONMENT INTERNATIONAL 2018; 113:114-121. [PMID: 29421400 PMCID: PMC5866237 DOI: 10.1016/j.envint.2018.01.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Revised: 01/19/2018] [Accepted: 01/21/2018] [Indexed: 05/05/2023]
Abstract
Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus. Using several spatial techniques, this study explored the relationship between SUD and greenspace. We adjudicated 396 SUD cases that occurred from March 2013 to February 2015 among reports from emergency medical services (EMS) that attended out-of-hospital deaths in Wake County (central North Carolina, USA). We measured multiple greenspace metrics in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations between SUD incidence and these greenspace metrics were examined using Poisson regression (non-spatial) and Bayesian spatial models. The results from both models indicated that SUD incidence was inversely associated with both greenway density (adjusted risk ratio [RR] = 0.82, 95% credible/ confidence interval [CI]: 0.69-0.97) and the percentage of forest (adjusted RR = 0.90, 95% CI: 0.81-0.99). These results suggest that increases in greenway density by 1 km/km2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity. This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress.
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Affiliation(s)
- Jianyong Wu
- Oak Ridge Institute for Science and Education, US EPA, Office of Research and Development, Research Triangle Park, Durham 27711, NC, USA.
| | - Kristen M Rappazzo
- US EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, Durham 27711, NC, USA
| | - Ross J Simpson
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Golsa Joodi
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Irion W Pursell
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; The Department of Cardiovascular Sciences, East Carolina University, Greenville, NC 27834, USA
| | - J Paul Mounsey
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; The Department of Cardiovascular Sciences, East Carolina University, Greenville, NC 27834, USA
| | - Wayne E Cascio
- US EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, Durham 27711, NC, USA
| | - Laura E Jackson
- US EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, Durham 27711, NC, USA.
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Mounsey LA, Lin FC, Pursell I, Joodi G, Lewis ME, Nwosu A, Hodonsky C, Simpson RJ, Mounsey JP. Relation of Household Income to Incidence of Sudden Unexpected Death in Wake County, North Carolina. Am J Cardiol 2017; 119:1030-1035. [PMID: 28187864 DOI: 10.1016/j.amjcard.2016.11.061] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 11/29/2016] [Accepted: 11/29/2016] [Indexed: 11/29/2022]
Abstract
The incidence of out-of-hospital sudden unexpected death (OHSUD) in a racially and socioeconomically diverse population has been inadequately studied. We collated all OHSUDs over a 24-month period among 18- to 64-year olds in Wake County, North Carolina, to investigate geographic and socioeconomic disparity in incidence of OHSUD. An electronic query of Wake County Emergency Medical Services (EMS) identified all EMS attended out-of-hospital deaths. After excluding trauma, expected deaths, and deaths occurring in non-free-living subjects, medical records and medical examiner's reports were reviewed by a committee of cardiologists to make the determination of OHSUD. Victims were geocoded to census tracts, and demographic and socioeconomic data were obtained from the 2014 American Community Survey and 2010 US Census. Incidence was examined by sociodemographic group with univariate analysis and multivariable regression. There were 397 OHSUDs, and 53% of census tracts had >1 event. The incidence of OHSUD was 64 of 100,000; 107 of 100,000 among blacks; and 60 of 100,000 among whites. Census tracts with >1 OHSUD had a higher population of blacks, a greater proportion unmarried, a lower median household income, and a greater proportion residing in a rural area. Only median household income remained a significant predictor of OHSUD after adjustment in multivariable analysis. Low median household income of a community portends a higher incidence of sudden death. In conclusion, interventions to reduce the incidence of sudden death need to be developed with these specific communities in mind.
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Affiliation(s)
- Louisa A Mounsey
- University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Feng-Chang Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Irion Pursell
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Golsa Joodi
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Mary Elizabeth Lewis
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Anthony Nwosu
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Chani Hodonsky
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Ross J Simpson
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - J Paul Mounsey
- Division of Cardiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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Lewis ME, Lin FC, Nanavati P, Mehta N, Mounsey L, Nwosu A, Pursell I, Chung EH, Mounsey JP, Simpson RJ. Estimated incidence and risk factors of sudden unexpected death. Open Heart 2016; 3:e000321. [PMID: 27042316 PMCID: PMC4809187 DOI: 10.1136/openhrt-2015-000321] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Revised: 10/06/2015] [Accepted: 12/21/2015] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE In this manuscript, we estimate the incidence and identify risk factors for sudden unexpected death in a socioeconomically and racially diverse population in one county in North Carolina. Estimates of the incidence and risk factors contributing to sudden death vary widely. The Sudden Unexpected Death in North Carolina (SUDDEN) project is a population-based investigation of the incidence and potential causes of sudden death. METHODS From 3 March 2013 to 2 March 2014, all out-of-hospital deaths in Wake County, North Carolina, were screened to identify presumed sudden unexpected death among free-living residents between the ages of 18 and 64 years. Death certificate, public and medical records were reviewed and adjudicated to confirm sudden unexpected death cases. RESULTS Following adjudication, 190 sudden unexpected deaths including 122 men and 68 women were identified. Estimated incidence was 32.1 per 100 000 person-years overall: 42.7 among men and 22.4 among women. The majority of victims were white, unmarried men over age 55 years, with unwitnessed deaths at home. Hypertension and dyslipidaemia were common in men and women. African-American women dying from sudden unexpected death were over-represented. Women who were under age 55 years with coronary disease accounted for over half of female participants with coronary artery disease. CONCLUSIONS The overall estimated incidence of sudden unexpected death may account for approximately 10% of all deaths classified as 'natural'. Women have a lower estimated incidence of sudden unexpected death than men. However, we found no major differences in age or comorbidities between men and women. African-Americans and young women with coronary disease are at risk for sudden unexpected death.
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Affiliation(s)
- Mary Elizabeth Lewis
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Feng-Chang Lin
- NC TraCS, University of North Carolina, North Carolina, USA
| | - Parin Nanavati
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Neil Mehta
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Louisa Mounsey
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Anthony Nwosu
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Irion Pursell
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Eugene H Chung
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - J Paul Mounsey
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
| | - Ross J Simpson
- Department of Medicine, The University of North Carolina, Cardiac Electrophysiology, North Carolina, USA
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