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Forrester SN, Baek J, Hou L, Roger V, Kiefe CI. A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study. J Am Heart Assoc 2024; 13:e032847. [PMID: 38606769 DOI: 10.1161/jaha.123.032847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 03/04/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Accelerated biological aging is an increasingly popular way to track the acceleration of biology over time that may not be captured by calendar time. Biological aging has been linked to external and internal chronic stressors and has the potential to be used clinically to understand a person's personalized functioning and predict future disease. We compared the association of different measures of biological aging and incident cardiovascular disease (CVD) overall and by race. METHODS AND RESULTS We used multiple informants models to compare the strength of clinical marker-derived age acceleration, 5 measures of epigenetic age acceleration (intrinsic and extrinsic epigenetic age acceleration, GrimAge acceleration, and PhenoAge acceleration), and 1 established clinical predictor of future CVD, Framingham 10-year risk score, with incident CVD over an 11-year period (2007-2018). Participants were 913 self-identified Black or White (41% and 59%, respectively) female or male (51% and 49%, respectively) individuals enrolled in the US-based CARDIA (Coronary Artery Risk Development in Young Adults) cohort study. The analytic baseline for this study was the 20-year follow-up examination (2005-2006; median age 45 years). We also included race-specific analysis. We found that all measures were modestly correlated with one another. However, clinical marker-derived age acceleration and Framingham 10-year risk score were more strongly associated with incident CVD than all the epigenetic measures. Clinical marker-derived age acceleration and Framingham 10-year risk score were not significantly different than one another in their association with incident CVD. CONCLUSIONS The type of accelerated aging measure should be taken into consideration when comparing their association with clinical outcomes. A multisystem clinical composite shows associations with incident CVD equally to a well-known clinical predictor.
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Affiliation(s)
- Sarah N Forrester
- Division of Epidemiology, Department of Population and Quantitative Health Sciences University of Massachusetts Chan Medical School Worcester MA
| | - Jonggyu Baek
- Division of Biostatistics and Health Services, Department of Population and Quantitative Health Sciences University of Massachusetts Chan Medical School Worcester MA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine Northwestern University Chicago IL
| | - Veronique Roger
- Laboratory of Heart Disease Phenomics National Heart, Lung, and Blood Institute Bethesda MD
| | - Catarina I Kiefe
- Department of Population and Quantitative Health Sciences University of Massachusetts Chan Medical School Worcester MA
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2
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Metlock FE, Addison S, McKoy A, Yang Y, Hope A, Joseph JJ, Zhang J, Williams A, Gray DM, Gregory J, Nolan TS. More than Just a Number: Perspectives from Black Male Participants on Community-Based Interventions and Clinical Trials to Address Cardiovascular Health Disparities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:449. [PMID: 38673360 PMCID: PMC11050149 DOI: 10.3390/ijerph21040449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 03/18/2024] [Accepted: 03/22/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND Black Americans remain significantly underrepresented and understudied in research. Community-based interventions have been increasingly recognized as an effective model for reckoning with clinical trial participation challenges amongst underrepresented groups, yet a paucity of studies implement this approach. The present study sought to gain insight into Black male participants' perception of clinical trials before and after participating in a community-based team lifestyle intervention in the United States. METHODS Black Impact, a 24-week community-based lifestyle intervention, applied the American Heart Association's Life's Simple 7 (LS7) framework to assess changes in the cardiovascular health of seventy-four Black male participants partaking in weekly team-based physical activities and LS7-themed education and having their social needs addressed. A subset of twenty participants completed an exit survey via one of three semi-structured focus groups aimed at understanding the feasibility of interventions, including their perceptions of participating in clinical trials. Data were transcribed verbatim and analyzed using a content analysis, which involved systematically identifying, coding, categorizing, and interpreting the primary patterns of the data. RESULTS The participants reported a positive change in their perceptions of clinical trials based on their experience with a community-based lifestyle intervention. Three prominent themes regarding their perceptions of clinical trials prior to the intervention were as follows: (1) History of medical abuse; (2) Lack of diversity amongst research teams and participants; and (3) A positive experience with racially concordant research teams. Three themes noted to influence changes in their perception of clinical trials based on their participation in Black Impact were as follows: (1) Building trust with the research team; (2) Increasing awareness about clinical trials; and (3) Motivating participation through community engagement efforts. CONCLUSIONS Improved perceptions of participating in clinical trials were achieved after participation in a community-based intervention. This intervention may provide a framework by which to facilitate clinical trial participation among Black men, which must be made a priority so that Black men are "more than just a number" and no longer "receiving the short end of the stick".
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Affiliation(s)
- Faith E. Metlock
- Johns Hopkins School of Nursing (Formerly The Ohio State University College of Nursing), Baltimore, MD 21205, USA;
| | - Sarah Addison
- Washington University School of Medicine (Formerly The Ohio State University College of Medicine), St. Louis, MO 63110, USA;
| | - Alicia McKoy
- OhioHealth (Formerly The Ohio State University Center for Cancer Health Equity), Columbus, OH 43202, USA;
| | - Yesol Yang
- The Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA; (Y.Y.); (J.Z.)
| | - Aarhea Hope
- Nell Hodgson Woodruff School of Nursing (Formerly The Ohio State University College of Nursing), Atlanta, GA 30322, USA;
| | - Joshua J. Joseph
- The Ohio State University College of Medicine, Columbus, OH 43210, USA; (J.J.J.); (A.W.)
| | - Jing Zhang
- The Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA; (Y.Y.); (J.Z.)
| | - Amaris Williams
- The Ohio State University College of Medicine, Columbus, OH 43210, USA; (J.J.J.); (A.W.)
| | - Darrell M. Gray
- Gray Area Strategies LLC (Formerly The Ohio State University College of Medicine), Columbus, OH 43210, USA;
| | - John Gregory
- The African American Male Wellness Agency, National Center for Urban Solutions, Columbus, OH 43205, USA;
| | - Timiya S. Nolan
- University of Alabama at Birmingham Heersink School of Medicine (Formerly The Ohio State University College of Nursing and The Ohio State University Comprehensive Cancer Center), Birmingham, AL 35233, USA
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Beaudoin JR, Curran J, Alexander GC. Impact of Race on Classification of Atherosclerotic Risk Using a National Cardiovascular Risk Prediction Tool. AJPM FOCUS 2024; 3:100200. [PMID: 38440670 PMCID: PMC10910235 DOI: 10.1016/j.focus.2024.100200] [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] [Indexed: 03/06/2024]
Abstract
Introduction The use of race in clinical risk prediction tools may exacerbate racial disparities in healthcare access and outcomes. This study quantified the number of individuals reclassified for primary prevention of cardiovascular disease owing to a change in their race alone on the basis of a commonly used risk prediction tool. Methods This is a cross-sectional analysis of individuals aged 40-75 years without a history of cardiovascular events, diabetes, or other high-risk features using the 2005-2018 National Health and Nutritional Examination Survey. Authors compared atherosclerotic cardiovascular disease risk scores using the American Heart Association/American College of Cardiology equation recommended for White individuals or individuals of other races with that recommended for Black individuals. Results A total of 2,946 White individuals; 1,361 Black individuals; and 2,495 individuals of other races were included in the analysis. Using the American Heart Association/American College of Cardiology equation, the mean 10-year atherosclerotic cardiovascular disease risk was 5.80% (95% CI=5.54, 6.06) for White individuals, 7.04% (956% CI=6.69, 7.39) for Black individuals, and 4.93% (95% CI=4.61, 5.24) for individuals of other races. When using the American Heart Association/American College of Cardiology equation designated for the opposite race (White/other race versus Black), the mean atherosclerotic cardiovascular disease risk score increased by 1.02% (95% CI=0.90, 1.13) for White individuals, decreased by 1.82% (95% CI= -1.67, -1.96) for Black individuals, and increased by 0.98% (95% CI=0.85, 1.10) for individuals of other races. When using clinical atherosclerotic cardiovascular disease categories of <7.5%, 7.5%-10%, and >10%, 16.93% of all individuals were reclassified when using the American Heart Association/American College of Cardiology's equation designated for the opposite race. Conclusions Changing race within a commonly used cardiovascular risk prediction tool results in significant changes in risk classification among eligible White and Black individuals in the U.S.
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Affiliation(s)
- Jarett R. Beaudoin
- Department of Family and Community Medicine, University of California, Davis, California
| | - Jill Curran
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - G. Caleb Alexander
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Division of General Internal Medicine, Johns Hopkins Medicine, Baltimore, Maryland
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Liu J, Cepeda M, Frangaj B, Shimbo D. The Burden of Cardiovascular Disease in the Post-COVID Era. Prim Care 2024; 51:1-11. [PMID: 38278564 DOI: 10.1016/j.pop.2023.08.001] [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: 01/28/2024]
Abstract
In 2019, before the COVID-19 pandemic, cardiovascular disease (CVD) was the leading cause of death. Since 2020, the pandemic has had far-reaching effects on the landscape of health care including CVD prevention and management. Recent decreases in life expectancy in the United States could potentially be explained by issues related to disruptions in CVD prevention and control of CVD risk factors from the COVID-19 pandemic. This article reviews the effects of the SARS-CoV-2 virus and the accompanying pandemic on CVD risk factor prevention and management in the United States. Potential solutions are also proposed for these patients.
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Affiliation(s)
- Justin Liu
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, 60 Haven Avenue (Tower 1), Level B2 (Lobby Level) - Office Suite B234, New York, NY 10032, USA
| | - Maria Cepeda
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, 60 Haven Avenue (Tower 1), Level B2 (Lobby Level) - Office Suite B234, New York, NY 10032, USA
| | - Brulinda Frangaj
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, 60 Haven Avenue (Tower 1), Level B2 (Lobby Level) - Office Suite B234, New York, NY 10032, USA
| | - Daichi Shimbo
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center, 60 Haven Avenue (Tower 1), Level B2 (Lobby Level) - Office Suite B234, New York, NY 10032, USA.
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Williams A, Nolan TS, Luthy J, Brewer LC, Ortiz R, Venkatesh KK, Sanchez E, Brock GN, Nawaz S, Garner JA, Walker DM, Gray DM, Joseph JJ. Association of Socioeconomic Status With Life's Essential 8 in the National Health and Nutrition Examination Survey: Effect Modification by Sex. J Am Heart Assoc 2024; 13:e030805. [PMID: 38348807 PMCID: PMC11010082 DOI: 10.1161/jaha.123.030805] [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: 07/25/2023] [Accepted: 01/12/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Higher scores for the American Heart Association Life's Essential 8 (LE8) metrics, blood pressure, cholesterol, glucose, body mass index, physical activity, smoking, sleep, and diet, are associated with lower risk of chronic disease. Socioeconomic status (SES; employment, insurance, education, and income) is associated with LE8 scores, but there is limited understanding of potential differences by sex. This analysis quantifies the association of SES with LE8 for each sex, within Hispanic Americans, non-Hispanic Asian Americans, non-Hispanic Black Americans, and non-Hispanic White Americans. METHODS AND RESULTS Using cross-sectional data from the National Health and Nutrition Examination Survey, years 2011 to 2018, LE8 scores were calculated (range, 0-100). Age-adjusted linear regression quantified the association of SES with LE8 score. The interaction of sex with SES in the association with LE8 score was assessed in each racial and ethnic group. The US population representatively weighted sample (13 529 observations) was aged ≥20 years (median, 48 years). The association of education and income with LE8 scores was higher in women compared with men for non-Hispanic Black Americans and non-Hispanic White Americans (P for all interactions <0.05). Among non-Hispanic Asian Americans and Hispanic Americans, the association of SES with LE8 was not different between men and women, and women had greater LE8 scores than men at all SES levels (eg, high school or less, some college, and college degree or more). CONCLUSIONS The factors that explain the sex differences among non-Hispanic Black Americans and non-Hispanic White Americans, but not non-Hispanic Asian Americans and Hispanic Americans, are critical areas for further research to advance cardiovascular health equity.
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Affiliation(s)
- Amaris Williams
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine The Ohio State University Wexner Medical Center Columbus OH
| | - Timiya S Nolan
- The Ohio State University College of Nursing Columbus OH
| | - Jacsen Luthy
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine The Ohio State University Wexner Medical Center Columbus OH
| | - LaPrincess C Brewer
- Division of Preventive Cardiology, Department of Cardiovascular Medicine Mayo Clinic College of Medicine Rochester MN
- Center for Health Equity and Community Engagement Research Mayo Clinic Rochester MN
| | - Robin Ortiz
- Institute for Excellence in Health Equity New York University Langone Health New York NY
- Departments of Pediatrics and Population Health New York University, Grossman School of Medicine New York NY
| | - Kartik K Venkatesh
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology The Ohio State University Columbus OH
| | | | - Guy N Brock
- Division of Biostatistics, College of Public Health The Ohio State University Columbus OH
| | - Saira Nawaz
- The Ohio State University College of Public Health Columbus OH
| | - Jennifer A Garner
- The School of Health and Rehabilitation Sciences The Ohio State University College of Medicine Columbus OH
- John Glenn College of Public Affairs The Ohio State University Columbus OH
| | | | - Darrell M Gray
- Elevance Health (formerly with The Ohio State University Wexner Medical Center) Indianapolis IN
| | - Joshua J Joseph
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine The Ohio State University Wexner Medical Center Columbus OH
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [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: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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7
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Khan SS, Matsushita K, Sang Y, Ballew SH, Grams ME, Surapaneni A, Blaha MJ, Carson AP, Chang AR, Ciemins E, Go AS, Gutierrez OM, Hwang SJ, Jassal SK, Kovesdy CP, Lloyd-Jones DM, Shlipak MG, Palaniappan LP, Sperling L, Virani SS, Tuttle K, Neeland IJ, Chow SL, Rangaswami J, Pencina MJ, Ndumele CE, Coresh J. Development and Validation of the American Heart Association's PREVENT Equations. Circulation 2024; 149:430-449. [PMID: 37947085 PMCID: PMC10910659 DOI: 10.1161/circulationaha.123.067626] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 11/03/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.
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Affiliation(s)
- Sadiya S. Khan
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA (S Khan)
| | - Kunihiro Matsushita
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K Matsushita, Y Sang, SH Ballew, ME Grams, A Surapaneni, J Coresh)
| | - Yingying Sang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K Matsushita, Y Sang, SH Ballew, ME Grams, A Surapaneni, J Coresh)
| | - Shoshana H Ballew
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K Matsushita, Y Sang, SH Ballew, ME Grams, A Surapaneni, J Coresh)
| | - Morgan E. Grams
- New York University Grossman School of Medicine, Department of Medicine, Division of Precision Medicine, New York, New York, USA (M Grams, A Surapaneni)
| | - Aditya Surapaneni
- New York University Grossman School of Medicine, Department of Medicine, Division of Precision Medicine, New York, New York, USA (M Grams, A Surapaneni)
| | - Michael J. Blaha
- Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Baltimore, MD (M Blaha)
| | - April P. Carson
- University of Mississippi Medical Center, Jackson (A Carson)
| | - Alexander R. Chang
- Departments of Nephrology and Population Health Sciences, Geisinger Health, Danville, Pennsylvania (AR Chang)
| | - Elizabeth Ciemins
- AMGA (American Medical Group Association), Alexandria, Virginia, USA (E Ciemins)
| | - Alan S. Go
- Division of Research, Kaiser Permanente Northern California, Oakland, California; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California; Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco, California; Department of Medicine (Nephrology), Stanford University School of Medicine, Palo Alto, California (A Go)
| | - Orlando M. Gutierrez
- Departments of Epidemiology and Medicine, University of Alabama at Birmingham, Birmingham, AL (OM Gutierrez)
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute, Framingham, Massachusetts (SJ Hwang)
| | - Simerjot K. Jassal
- Division of General Internal Medicine, University of California, San Diego and VA San Diego Healthcare, San Diego, California (SK Jassal)
| | - Csaba P. Kovesdy
- Medicine-Nephrology, Memphis Veterans Affairs Medical Center and University of Tennessee Health Science Center, Memphis, Tennessee (CP Kovesdy)
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois (DM Lloyd-Jones)
| | - Michael G. Shlipak
- Department of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco, and San Francisco VA Medical Center, San Francisco (M Shlipak)
| | - Latha P. Palaniappan
- Center for Asian Health Research and Education and the Department of Medicine, Stanford University School of Medicine, Stanford, California, USA. (LP Palaniappan)
| | - Laurence Sperling
- Department of Cardiology, Emory University, Atlanta, GA (L Sperling)
| | - Salim S. Virani
- Department of Medicine, The Aga Khan University, Karachi, Pakistan; Texas Heart Institute and Baylor College of Medicine, Houston, Texas (SS Virani)
| | - Katherine Tuttle
- Providence Medical Research Center, Providence Inland Northwest Health, Spokane, WA, USA; Kidney Research Institute and Institute of Translational Health Sciences, University of Washington, Seattle, WA, USA (K Tuttle)
| | - Ian J. Neeland
- UH Center for Cardiovascular Prevention, Translational Science Unit, Center for Integrated and Novel Approaches in Vascular-Metabolic Disease (CINEMA), Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA (I Neeland)
| | - Sheryl L. Chow
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA (SL Chow)
| | - Janani Rangaswami
- Washington DC VA Medical Center and George Washington University School of Medicine, Washington, DC (J Rangaswami)
| | - Michael J. Pencina
- Department of Biostatistics, Duke University Medical Center, Durham, North Carolina (MJ Pencina)
| | - Chiadi E. Ndumele
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA (C Ndumele)
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (K Matsushita, Y Sang, SH Ballew, ME Grams, A Surapaneni, J Coresh)
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8
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Liu M, Patel VR, Salas RN, Rice MB, Kazi DS, Zheng Z, Wadhera RK. Neighborhood Environmental Burden and Cardiovascular Health in the US. JAMA Cardiol 2024; 9:153-163. [PMID: 37955891 PMCID: PMC10644252 DOI: 10.1001/jamacardio.2023.4680] [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] [Received: 08/11/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023]
Abstract
Importance Cardiovascular disease is the leading cause of death in the US. However, little is known about the association between cumulative environmental burden and cardiovascular health across US neighborhoods. Objective To evaluate the association of neighborhood-level environmental burden with prevalence of cardiovascular risk factors and diseases, overall and by levels of social vulnerability. Design, Settings, and Participants This was a national cross-sectional study of 71 659 US Census tracts. Environmental burden (EBI) and social vulnerability indices from the US Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry were linked to the 2020 CDC PLACES data set. Data were analyzed from March to October 2023. Exposures The EBI, a measure of cumulative environmental burden encompassing 5 domains (air pollution, hazardous or toxic sites, built environment, transportation infrastructure, and water pollution). Main Outcomes and Measures Neighborhood-level prevalence of cardiovascular risk factors (hypertension, diabetes, and obesity) and cardiovascular diseases (coronary heart disease and stroke). Results Across the US, neighborhoods with the highest environmental burden (top EBI quartile) were more likely than those with the lowest environmental burden (bottom EBI quartile) to be urban (16 626 [92.7%] vs 13 414 [75.4%]), in the Midwest (5191 [28.9%] vs 2782 [15.6%]), have greater median (IQR) social vulnerability scores (0.64 [0.36-0.85] vs 0.42 [0.20-0.65]), and have higher proportions of adults in racial or ethnic minority groups (median [IQR], 34% [12-73] vs 12% [5-30]). After adjustment, neighborhoods with the highest environmental burden had significantly higher rates of cardiovascular risk factors than those with the lowest burden, including hypertension (mean [SD], 32.83% [7.99] vs 32.14% [6.99]; adjusted difference, 0.84%; 95% CI, 0.71-0.98), diabetes (mean [SD], 12.19% [4.33] vs 10.68% [3.27]; adjusted difference, 0.62%; 95% CI, 0.53-0.70), and obesity (mean [SD], 33.57% [7.62] vs 30.86% [6.15]; adjusted difference, 0.77%; 95% CI, 0.60-0.94). Similarly, neighborhoods with the highest environmental burden had significantly higher rates of coronary heart disease (mean [SD], 6.66% [2.15] vs 6.82% [2.41]; adjusted difference, 0.28%; 95% CI, 0.22-0.33) and stroke (mean [SD], 3.65% [1.47] vs 3.31% [1.12]; adjusted difference, 0.19%; 95% CI, 0.15-0.22). Results were consistent after matching highest and lowest environmentally burdened neighborhoods geospatially and based on other covariates. The associations between environmental burden quartiles and cardiovascular risk factors and diseases were most pronounced among socially vulnerable neighborhoods. Conclusions and Relevance In this cross-sectional study of US neighborhoods, cumulative environmental burden was associated with higher rates of cardiovascular risk factors and diseases, although absolute differences were small. The strongest associations were observed in socially vulnerable neighborhoods. Whether initiatives that address poor environmental conditions will improve cardiovascular health requires additional prospective investigations.
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Affiliation(s)
- Michael Liu
- Section of Health Policy and Equity, Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Renee N. Salas
- Harvard Medical School, Boston, Massachusetts
- Center for Social Justice and Health Equity, Department of Emergency Medicine, Massachusetts General Hospital, Boston
- C-CHANGE, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Harvard Global Health Institute, Boston, Massachusetts
| | - Mary B. Rice
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Dhruv S. Kazi
- Section of Health Policy and Equity, Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - ZhaoNian Zheng
- Section of Health Policy and Equity, Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Rishi K. Wadhera
- Section of Health Policy and Equity, Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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9
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Magnani JW, Ning H, Wilkins JT, Lloyd-Jones DM, Allen NB. Educational Attainment and Lifetime Risk of Cardiovascular Disease. JAMA Cardiol 2024; 9:45-54. [PMID: 37910110 PMCID: PMC10620672 DOI: 10.1001/jamacardio.2023.3990] [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] [Received: 03/24/2023] [Accepted: 09/11/2023] [Indexed: 11/03/2023]
Abstract
Importance Education is a social determinant of health. Quantifying its association with lifetime cardiovascular disease (CVD) risk has public health importance. Objective To calculate lifetime risk estimates of incident CVD and CVD subtypes and estimate years lived with and without CVD by education. Design, Setting, and Participants Included community-based cohort studies with adjudicated cardiovascular events used pooled individual-level data from 1985 to 2015 of 6 prospective cohort studies. The study team assessed the association between education and lifetime CVD risk with modified Kaplan-Meier and Cox models accounting for competing risk of noncardiovascular death. The study team estimated years lived with and without CVD by education with the Irwin restricted mean and the utility of adding educational attainment to CVD risk assessment. Participants (baseline 40 to 59 years old and 60 to 79 years old) were without CVD at baseline and had complete education, cardiovascular risk factors, and prospective CVD outcomes data. Data were analyzed from January 2022 to September 2022. Exposures Educational attainment (less than high school, high school completion, some college, or college graduate). Main outcome and measures Cardiovascular events (fatal and nonfatal coronary heart disease, heart failure, and stroke; CVD-related deaths; and total CVD encompassing any of these events). Results There were 40 998 participants (23 305 female [56.2%]) with a mean (SD) age of 58.1 (9.7) years for males and 58.3 (9.9) years for females. Compared with college graduates, those with less than high school or high school completion had higher lifetime CVD risks. Among middle-aged men, the competing hazard ratios (HRs) for a CVD event were 1.58 (95% CI, 1.38-1.80), 1.30 (95% CI, 1.10-1.46), and 1.16 (95% CI, 1.00-1.34) in those with less than high school, high school, and some college, respectively, compared with those with college completion. Among women, these competing HRs were 1.70 (95% CI, 1.49-1.95), 1.19 (95% CI, 1.05-1.35), and 0.98 (95% CI, 0.83-1.15). Individuals with higher education had longer duration of life prior to incident CVD. Education provided limited contribution toward enhancing CVD risk prediction. Conclusions and relevance Lower education was associated with lifetime CVD risk across adulthood; higher education translated to healthy longevity. Educational policy initiatives may associate with long-term health benefits.
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Affiliation(s)
- Jared W. Magnani
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Center for Research on Health Care, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Hongyan Ning
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - John T. Wilkins
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Norrina B. Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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10
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Kershaw KN, Magnani JW, Diez Roux AV, Camacho-Rivera M, Jackson EA, Johnson AE, Magwood GS, Morgenstern LB, Salinas JJ, Sims M, Mujahid MS. Neighborhoods and Cardiovascular Health: A Scientific Statement From the American Heart Association. Circ Cardiovasc Qual Outcomes 2024; 17:e000124. [PMID: 38073532 DOI: 10.1161/hcq.0000000000000124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.
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11
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Khan SS, Coresh J, Pencina MJ, Ndumele CE, Rangaswami J, Chow SL, Palaniappan LP, Sperling LS, Virani SS, Ho JE, Neeland IJ, Tuttle KR, Rajgopal Singh R, Elkind MSV, Lloyd-Jones DM. Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement From the American Heart Association. Circulation 2023; 148:1982-2004. [PMID: 37947094 DOI: 10.1161/cir.0000000000001191] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.
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12
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Reynolds AJ, Varshney N, Ou SR, Kritzik R, Loveman-Brown M. Early Childhood Education and Midlife Ideal Cardiovascular Health in a Prospective Urban Cohort. JAMA Pediatr 2023; 177:1350-1352. [PMID: 37843853 PMCID: PMC10580152 DOI: 10.1001/jamapediatrics.2023.4010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 07/19/2023] [Indexed: 10/17/2023]
Abstract
This cohort study assesses whether preschool is associated with long-term cardiovascular health as measured by the American Heart Association’s Ideal Cardiovascular Health Index.
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Affiliation(s)
- Arthur J Reynolds
- Human Capital Research Collaborative, University of Minnesota, Minneapolis
| | - Nishank Varshney
- Humphrey School of Public Affairs, University of Minnesota, Minneapolis
- Now with Munroe-Myer Institute, University of Nebraska Medical Center, Omaha
| | - Suh-Ruu Ou
- Institute of Child Development, University of Minnesota, Minneapolis
| | - Rachel Kritzik
- Institute of Child Development, University of Minnesota, Minneapolis
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13
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Khan SS, Petito LC, Huang X, Harrington K, McNeil RB, Bello NA, Merz CNB, Miller EC, Ravi R, Scifres C, Catov J, Pemberton V, Varagic J, Zee PC, Yee LM, Ray M, Kim JK, Lane-Cordova A, Lewey J, Theilen LH, Saade GR, Greenland P, Grobman WA. Body Mass Index, Adverse Pregnancy Outcomes, and Cardiovascular Disease Risk. Circ Res 2023; 133:725-735. [PMID: 37814889 PMCID: PMC10578703 DOI: 10.1161/circresaha.123.322762] [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: 03/07/2023] [Accepted: 09/08/2023] [Indexed: 10/11/2023]
Abstract
BACKGROUND Obesity is a well-established risk factor for both adverse pregnancy outcomes (APOs) and cardiovascular disease (CVD). However, it is not known whether APOs are mediators or markers of the obesity-CVD relationship. This study examined the association between body mass index, APOs, and postpartum CVD risk factors. METHODS The sample included adults from the nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be) Heart Health Study who were enrolled in their first trimester (6 weeks-13 weeks 6 days gestation) from 8 United States sites. Participants had a follow-up visit at 3.7 years postpartum. APOs, which included hypertensive disorders of pregnancy, preterm birth, small-for-gestational-age birth, and gestational diabetes, were centrally adjudicated. Mediation analyses estimated the association between early pregnancy body mass index and postpartum CVD risk factors (hypertension, hyperlipidemia, and diabetes) and the proportion mediated by each APO adjusted for demographics and baseline health behaviors, psychosocial stressors, and CVD risk factor levels. RESULTS Among 4216 participants enrolled, mean±SD maternal age was 27±6 years. Early pregnancy prevalence of overweight was 25%, and obesity was 22%. Hypertensive disorders of pregnancy occurred in 15%, preterm birth in 8%, small-for-gestational-age birth in 11%, and gestational diabetes in 4%. Early pregnancy obesity, compared with normal body mass index, was associated with significantly higher incidence of postpartum hypertension (adjusted odds ratio, 1.14 [95% CI, 1.10-1.18]), hyperlipidemia (1.11 [95% CI, 1.08-1.14]), and diabetes (1.03 [95% CI, 1.01-1.04]) even after adjustment for baseline CVD risk factor levels. APOs were associated with higher incidence of postpartum hypertension (1.97 [95% CI, 1.61-2.40]) and hyperlipidemia (1.31 [95% CI, 1.03-1.67]). Hypertensive disorders of pregnancy mediated a small proportion of the association between obesity and incident hypertension (13% [11%-15%]) and did not mediate associations with incident hyperlipidemia or diabetes. There was no significant mediation by preterm birth or small-for-gestational-age birth. CONCLUSIONS There was heterogeneity across APO subtypes in their association with postpartum CVD risk factors and mediation of the association between early pregnancy obesity and postpartum CVD risk factors. However, only a small or nonsignificant proportion of the association between obesity and CVD risk factors was mediated by any of the APOs, suggesting APOs are a marker of prepregnancy CVD risk and not a predominant cause of postpartum CVD risk.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Rupa Ravi
- Columbia University Irving Medical Center
| | | | | | | | | | | | - Lynn M Yee
- Northwestern University Feinberg School of Medicine
| | - Mitali Ray
- University of Pittsburgh School of Medicine
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14
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Lennon MJ, Lam BCP, Lipnicki DM, Crawford JD, Peters R, Schutte AE, Brodaty H, Thalamuthu A, Rydberg-Sterner T, Najar J, Skoog I, Riedel-Heller SG, Röhr S, Pabst A, Lobo A, De-la-Cámara C, Lobo E, Bello T, Gureje O, Ojagbemi A, Lipton RB, Katz MJ, Derby CA, Kim KW, Han JW, Oh DJ, Rolandi E, Davin A, Rossi M, Scarmeas N, Yannakoulia M, Dardiotis T, Hendrie HC, Gao S, Carrière I, Ritchie K, Anstey KJ, Cherbuin N, Xiao S, Yue L, Li W, Guerchet MM, Preux PM, Aboyans V, Haan MN, Aiello AE, Ng TP, Nyunt MSZ, Gao Q, Scazufca M, Sachdev PSS. Use of Antihypertensives, Blood Pressure, and Estimated Risk of Dementia in Late Life: An Individual Participant Data Meta-Analysis. JAMA Netw Open 2023; 6:e2333353. [PMID: 37698858 PMCID: PMC10498335 DOI: 10.1001/jamanetworkopen.2023.33353] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/28/2023] [Indexed: 09/13/2023] Open
Abstract
Importance The utility of antihypertensives and ideal blood pressure (BP) for dementia prevention in late life remains unclear and highly contested. Objectives To assess the associations of hypertension history, antihypertensive use, and baseline measured BP in late life (age >60 years) with dementia and the moderating factors of age, sex, and racial group. Data Source and Study Selection Longitudinal, population-based studies of aging participating in the Cohort Studies of Memory in an International Consortium (COSMIC) group were included. Participants were individuals without dementia at baseline aged 60 to 110 years and were based in 15 different countries (US, Brazil, Australia, China, Korea, Singapore, Central African Republic, Republic of Congo, Nigeria, Germany, Spain, Italy, France, Sweden, and Greece). Data Extraction and Synthesis Participants were grouped in 3 categories based on previous diagnosis of hypertension and baseline antihypertensive use: healthy controls, treated hypertension, and untreated hypertension. Baseline systolic BP (SBP) and diastolic BP (DBP) were treated as continuous variables. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-Analyses of Individual Participant Data reporting guidelines. Main Outcomes and Measures The key outcome was all-cause dementia. Mixed-effects Cox proportional hazards models were used to assess the associations between the exposures and the key outcome variable. The association between dementia and baseline BP was modeled using nonlinear natural splines. The main analysis was a partially adjusted Cox proportional hazards model controlling for age, age squared, sex, education, racial group, and a random effect for study. Sensitivity analyses included a fully adjusted analysis, a restricted analysis of those individuals with more than 5 years of follow-up data, and models examining the moderating factors of age, sex, and racial group. Results The analysis included 17 studies with 34 519 community dwelling older adults (20 160 [58.4%] female) with a mean (SD) age of 72.5 (7.5) years and a mean (SD) follow-up of 4.3 (4.3) years. In the main, partially adjusted analysis including 14 studies, individuals with untreated hypertension had a 42% increased risk of dementia compared with healthy controls (hazard ratio [HR], 1.42; 95% CI 1.15-1.76; P = .001) and 26% increased risk compared with individuals with treated hypertension (HR, 1.26; 95% CI, 1.03-1.53; P = .02). Individuals with treated hypertension had no significant increased dementia risk compared with healthy controls (HR, 1.13; 95% CI, 0.99-1.28; P = .07). The association of antihypertensive use or hypertension status with dementia did not vary with baseline BP. There was no significant association of baseline SBP or DBP with dementia risk in any of the analyses. There were no significant interactions with age, sex, or racial group for any of the analyses. Conclusions and Relevance This individual patient data meta-analysis of longitudinal cohort studies found that antihypertensive use was associated with decreased dementia risk compared with individuals with untreated hypertension through all ages in late life. Individuals with treated hypertension had no increased risk of dementia compared with healthy controls.
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Affiliation(s)
- Matthew J. Lennon
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Ben Chun Pan Lam
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- School of Psychology and Public Health, La Trobe University, Melbourne, Australia
| | - Darren M. Lipnicki
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - John D. Crawford
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Ruth Peters
- The George Institute for Global Health, Sydney, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
- School of Public Health, Imperial College London, London, United Kingdom
| | - Aletta E. Schutte
- The George Institute for Global Health, Sydney, Australia
- School of Population Health, University of New South Wales, Sydney, Australia
| | - Henry Brodaty
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- Eastern Suburbs Older Persons’ Mental Health Service, Sydney, Australia
| | - Anbupalam Thalamuthu
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Therese Rydberg-Sterner
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Psychiatry, Cognition and Old Age Psychiatry Clinic, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health at the University of Gothenburg, Gothenburg, Sweden
- Psychiatry, Cognition and Old Age Psychiatry Clinic, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Steffi G. Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Susanne Röhr
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
- School of Psychology, Manawatu Campus, Massey University, Palmerston North, New Zealand
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Alexander Pabst
- Institute of Social Medicine, Occupational Health and Public Health, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Antonio Lobo
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Concepción De-la-Cámara
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Elena Lobo
- Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain
- Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain
| | - Toyin Bello
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oye Gureje
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Akin Ojagbemi
- World Health Organization Collaborating Centre for Research and Training in Mental Health, Neuroscience, and Substance Abuse, Department of Psychiatry, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Mindy J. Katz
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
| | - Carol A. Derby
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Dae Jong Oh
- Workplace Mental Health Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Elena Rolandi
- Golgi Cenci Foundation, Abbiategrasso, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | | | | | - Nikolaos Scarmeas
- First Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
- Department of Neurology, Columbia University, New York, New York
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, School of Health Sciences and Education, Harokopio University, Athens, Greece
| | - Themis Dardiotis
- Department of Neurology, University Hospital of Larissa, Larissa, Greece
- Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
| | - Hugh C. Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
- Indiana Alzheimer Disease Research Center, Indiana Alzheimer Disease Research Center, Indianapolis
| | - Sujuan Gao
- Indiana Alzheimer Disease Research Center, Indiana Alzheimer Disease Research Center, Indianapolis
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis
| | - Isabelle Carrière
- Institut for Neurosciences of Montpellier, University Montpellier, National Institute for Health and Medical Research, Montpellier, France
| | - Karen Ritchie
- Institut for Neurosciences of Montpellier, University Montpellier, National Institute for Health and Medical Research, Montpellier, France
- Institut du Cerveau Trocadéro, Paris, France
| | - Kaarin J. Anstey
- University of New South Wales, School of Psychology, Sydney, Australia
- Ageing Futures Institute, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Sydney, Australia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Maëlenn M. Guerchet
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
| | - Pierre-Marie Preux
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
| | - Victor Aboyans
- National Institute for Health and Medical Research U1094, Institut de Recherche pour le Developpement UMR270, Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, University Limoges, Centre Hospitalier et Universitaire Limoges, Limoges, France
- Department of Cardiology, Dupuytren 2 University Hospital, Limoges, France
| | - Mary N. Haan
- School of Medicine, University of California, San Francisco
| | - Allison E. Aiello
- Robert N. Butler Columbia Aging Center, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Tze Pin Ng
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Geriatric Education and Research Institute, Ministry of Health, Singapore, Singapore
| | - Ma Shwe Zin Nyunt
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qi Gao
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Marcia Scazufca
- Departamento de Psiquiatria, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Perminder S. S. Sachdev
- Faculty of Medicine, University of New South Wales, Sydney, Australia
- Centre for Healthy Brain Aging, Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia
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15
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Fields ND, Choi D, Patel SA. Social and economic factors and black-white disparities in cardiovascular health: A decomposition analysis. SSM Popul Health 2023; 23:101485. [PMID: 37635988 PMCID: PMC10448210 DOI: 10.1016/j.ssmph.2023.101485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 08/04/2023] [Accepted: 08/05/2023] [Indexed: 08/29/2023] Open
Abstract
Background Cardiovascular health (CVH) in Black adults, and particularly in Black women, has lagged behind White adults for decades and contributes to higher mortality rates for Black adults. We quantified the contribution of five social and economic factors to observed racial disparities in CVH by gender. Methods We analyzed data from N = 8,019 adults aged ≥20 years free of cardiovascular disease assessed in the National Health and Nutrition Examination Survey, 2011-2018. Social and economic factors included self-reported education, income, employment, food security, and marital status. CVH was measured using eight behavioral and clinical indicators. We utilized Kitagawa-Blinder-Oaxaca decomposition to quantify gendered racial differences in CVH accounted for by these factors. Results Black women (mean CVH = 79.3) had a lower age-adjusted CVH score compared to White women (mean CVH = 82.3) (mean difference [MD] = -3.01; 95% CI: -5.18, -0.84). Social and economic factors accounted for a 3.26-point disadvantage (95% CI: -4.12, -2.40) and a 0.25-point CVH score advantage due to factors not accounted for in the model. In women, income had the largest coefficient associated with CVH score (b = -1.48; 95% CI: -2.04, -0.92). Among men, social and economic factors accounted for a 2.27-point disadvantage (95% CI: -2.97, -1.56) with educational attainment being the largest coefficient associated with CVH score (b = -1.55; 95% CI: -2.03, -1.06). However, the disadvantage in men was offset by a 1.99 CVH score advantage that was not accounted for by factors in the model resulting in no racial difference in age-adjusted CVH score (MD = -0.28; 95% CI: -3.78, 3.22). Conclusions Racial differences in social and economic factors may contribute a large portion to the observed disparity in CVH between U.S. Black and White women.
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Affiliation(s)
- Nicole D. Fields
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Daesung Choi
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Shivani A. Patel
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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16
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He J, Bundy JD, Geng S, Tian L, He H, Li X, Ferdinand KC, Anderson AH, Dorans KS, Vasan RS, Mills KT, Chen J. Social, Behavioral, and Metabolic Risk Factors and Racial Disparities in Cardiovascular Disease Mortality in U.S. Adults : An Observational Study. Ann Intern Med 2023; 176:1200-1208. [PMID: 37579311 DOI: 10.7326/m23-0507] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Cardiovascular disease (CVD) mortality is persistently higher in the Black population than in other racial and ethnic groups in the United States. OBJECTIVE To examine the degree to which social, behavioral, and metabolic risk factors are associated with CVD mortality and the extent to which racial differences in CVD mortality persist after these factors are accounted for. DESIGN Prospective cohort study. SETTING NHANES (National Health and Nutrition Examination Survey) 1999 to 2018. PARTICIPANTS A nationally representative sample of 50 808 persons aged 20 years or older. MEASUREMENTS Data on social, behavioral, and metabolic factors were collected in each NHANES survey using standard methods. Deaths from CVD were ascertained from linkage to the National Death Index with follow-up through 2019. RESULTS Over an average of 9.4 years of follow-up, 2589 CVD deaths were confirmed. The age- and sex-standardized rates of CVD mortality were 484.7 deaths per 100 000 person-years in Black participants, 384.5 deaths per 100 000 person-years in White participants, 292.4 deaths per 100 000 person-years in Hispanic participants, and 255.1 deaths per 100 000 person-years in other race groups. In a multiple Cox regression analysis adjusted for all measured risk factors simultaneously, several social (unemployment, low family income, food insecurity, lack of home ownership, and unpartnered status), behavioral (current smoking, lack of leisure-time physical activity, and sleep <6 or >8 h/d), and metabolic (obesity, hypertension, and diabetes) risk factors were associated with a significantly higher risk for CVD death. After adjustment for these metabolic, behavioral, and social risk factors separately, hazard ratios of CVD mortality for Black compared with White participants were attenuated from 1.54 (95% CI, 1.34 to 1.77) to 1.34 (CI, 1.16 to 1.55), 1.31 (CI, 1.15 to 1.50), and 1.04 (CI, 0.90 to 1.21), respectively. LIMITATION Causal contributions of social, behavioral, and metabolic risk factors to racial and ethnic disparities in CVD mortality could not be established. CONCLUSION The Black-White difference in CVD mortality diminished after adjustment for behavioral and metabolic risk factors and completely dissipated with adjustment for social determinants of health in the U.S. population. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine; Tulane University Translational Science Institute; and Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana (J.H.)
| | - Joshua D Bundy
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Siyi Geng
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Ling Tian
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Hua He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Xingyan Li
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas (X.L.)
| | - Keith C Ferdinand
- Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana (K.C.F.)
| | - Amanda H Anderson
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Kirsten S Dorans
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Ramachandran S Vasan
- University of Texas School of Public Health San Antonio, San Antonio, Texas (R.S.V.)
| | - Katherine T Mills
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, and Tulane University Translational Science Institute, New Orleans, Louisiana (J.D.B., S.G., L.T., H.H., A.H.A., K.S.D., K.T.M.)
| | - Jing Chen
- Department of Medicine, Tulane University School of Medicine; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine; and Tulane University Translational Science Institute, New Orleans, Louisiana (J.C.)
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Jordan KP, Rathod-Mistry T, van der Windt DA, Bailey J, Chen Y, Clarson L, Denaxas S, Hayward RA, Hemingway H, Kyriacou T, Mamas MA. Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study. Eur J Prev Cardiol 2023; 30:1151-1161. [PMID: 36895179 PMCID: PMC10442054 DOI: 10.1093/eurjpc/zwad055] [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: 09/01/2022] [Revised: 12/06/2022] [Accepted: 02/21/2023] [Indexed: 03/11/2023]
Abstract
AIMS Most adults presenting in primary care with chest pain symptoms will not receive a diagnosis ('unattributed' chest pain) but are at increased risk of cardiovascular events. To assess within patients with unattributed chest pain, risk factors for cardiovascular events and whether those at greatest risk of cardiovascular disease can be ascertained by an existing general population risk prediction model or by development of a new model. METHODS AND RESULTS The study used UK primary care electronic health records from the Clinical Practice Research Datalink linked to admitted hospitalizations. Study population was patients aged 18 plus with recorded unattributed chest pain 2002-2018. Cardiovascular risk prediction models were developed with external validation and comparison of performance to QRISK3, a general population risk prediction model. There were 374 917 patients with unattributed chest pain in the development data set. The strongest risk factors for cardiovascular disease included diabetes, atrial fibrillation, and hypertension. Risk was increased in males, patients of Asian ethnicity, those in more deprived areas, obese patients, and smokers. The final developed model had good predictive performance (external validation c-statistic 0.81, calibration slope 1.02). A model using a subset of key risk factors for cardiovascular disease gave nearly identical performance. QRISK3 underestimated cardiovascular risk. CONCLUSION Patients presenting with unattributed chest pain are at increased risk of cardiovascular events. It is feasible to accurately estimate individual risk using routinely recorded information in the primary care record, focusing on a small number of risk factors. Patients at highest risk could be targeted for preventative measures.
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Affiliation(s)
- Kelvin P Jordan
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
| | - Trishna Rathod-Mistry
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Windmill Road, Oxford OX3 7LD, UK
| | - Danielle A van der Windt
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
| | - James Bailey
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
| | - Ying Chen
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
- Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou 215123, Jiangsu, China
| | - Lorna Clarson
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, UK
- Health Data Research UK, University College London, 222 Euston Road, London NW1 2DA, UK
| | - Richard A Hayward
- School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
| | - Harry Hemingway
- Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, Maple House 1st floor, 149 Tottenham Court Road, London W1T 7DN, UK
| | - Theocharis Kyriacou
- School of Computing and Mathematics, Keele University, Staffordshire ST5 5AA, UK
| | - Mamas A Mamas
- Keele Cardiovascular Research Group, School of Medicine, David Weatherall Building, University Road, Keele University, Staffordshire ST5 5BG, UK
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Etti M, Yuan M, Bump JB. Sun, skin and the deadly politics of medical racism. BMJ Glob Health 2023; 8:e013616. [PMID: 37652568 PMCID: PMC10476135 DOI: 10.1136/bmjgh-2023-013616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 08/06/2023] [Indexed: 09/02/2023] Open
Affiliation(s)
- Melanie Etti
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
| | - MyMai Yuan
- Department of Health Policy and Management, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
| | - Jesse B Bump
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
- Bergen Center for Ethics and Priority Setting, University of Bergen, Bergen, Norway
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Choi Y, Jacobs Jr DR, Kramer HJ, Shroff GR, Chang AR, Duprez DA. Racial Differences and Contributory Cardiovascular and Non-Cardiovascular Risk Factors Towards Chronic Kidney Disease Progression. Vasc Health Risk Manag 2023; 19:433-445. [PMID: 37465230 PMCID: PMC10350429 DOI: 10.2147/vhrm.s416395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 07/04/2023] [Indexed: 07/20/2023] Open
Abstract
Background The prevalence of advanced chronic kidney disease (CKD) is higher in Black than in White Americans. We evaluated CKD progression in Black and White participants and the contribution of biological risk factors. We included the study of lung function (measured by forced vital capacity [FVC]), which is part of the emerging notion of interorgan cross-talk with the kidneys to racial differences in CKD progression. Methods This longitudinal study included 2175 Black and 2207 White adult Coronary Artery Risk Development in Young Adults (CARDIA) participants. Estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) were measured at study year 10 (age 27-41y) and every five years for 20 years. The outcome was CKD progression through no CKD, low, moderate, high, or very high-risk categories based on eGFR and UACR in combination. The association between race and CKD progression as well as the contribution of risk factors to racial differences were assessed in multivariable-adjusted Cox models. Results Black participants had higher CKD transition probabilities than White participants and more prevalent risk factors during the 20-year period studied. Hazard ratios for CKD transition for Black (vs White participants) were 1.38 from No CKD into ≥ low risk, 2.25 from ≤ low risk into ≥ moderate risk, and 4.49 from ≤ moderate risk into ≥ high risk. Racial differences in CKD progression from No CKD into ≥ low risk were primarily explained by FVC (54.8%), hypertension (30.9%), and obesity (20.8%). In contrast, racial differences were less explained in more severe transitions. Conclusion Black participants had a higher risk of CKD progression, and this discrepancy may be partly explained by FVC and conventional risk factors.
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Affiliation(s)
- Yuni Choi
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - David R Jacobs Jr
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Holly J Kramer
- Departments of Public Health Sciences and Medicine, Loyola University Chicago, Maywood, IL, USA
| | - Gautam R Shroff
- Division of Cardiology and Department of Medicine, Hennepin Healthcare, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Alexander R Chang
- Departments of Population of Health Sciences and Nephrology, Geisinger, Danville, PA, USA
| | - Daniel A Duprez
- Cardiovascular Division, Department of Medicine, University of Minnesota, Minneapolis, MN, USA
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20
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Rossom RC, Crain AL, Waring S, Sperl-Hillen JM, Hooker SA, Miley K, O'Connor PJ. Differential Effects of an Intervention to Reduce Cardiovascular Risk for Patients With Bipolar Disorder, Schizoaffective Disorder, or Schizophrenia: A Randomized Clinical Trial. J Clin Psychiatry 2023; 84:22m14710. [PMID: 37428030 PMCID: PMC10793875 DOI: 10.4088/jcp.22m14710] [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: 07/11/2023]
Abstract
Objective: To measure the impact of a clinical decision support (CDS) tool on total modifiable cardiovascular risk at 12 months separately for outpatients with 3 subtypes of serious mental illness (SMI) identified via ICD-9 and ICD-10 codes: bipolar disorder, schizoaffective disorder, and schizophrenia. Methods: This cluster-randomized pragmatic clinical trial was active from March 2016 to September 2018; data were analyzed from April 2021 to September 2022. Clinicians and patients from 78 primary care clinics participated. All 8,922 adult patients aged 18-75 years with diagnosed SMI, at least 1 cardiovascular risk factor not at goal, and an index and follow-up visit during the study period were included. The CDS tool provided a summary of modifiable cardiovascular risk and personalized treatment recommendations. Results: Intervention patients had 4% relative reduction in total modifiable cardiovascular risk at 12 months compared to controls (relative risk ratio = 0.96; 95% CI, 0.94 to 0.98), with similar intervention benefits for all 3 SMI subtypes. At index, 10-year cardiovascular risk was higher for patients with schizophrenia (mean [SD] = 11.3% [9.2%]) than for patients with bipolar disorder (8.5% [8.9%]) or schizoaffective disorder (9.4% [8.1%]), while 30-year cardiovascular risk was highest for patients with schizoaffective disorder (44% with 2 or more major cardiovascular risk factors, compared to 40% for patients with schizophrenia and 37% for patients with bipolar disorder). Smoking was highly prevalent (47%), and mean (SD) BMI was 32.7 (7.9). Conclusions: This CDS intervention produced a clinically and statistically significant 4% relative reduction in total modifiable cardiovascular risk for intervention patients versus controls at 12 months, an effect observed across all 3 SMI subtypes and attributable to the aggregate impact of small changes in multiple cardiovascular risk factors. Trial Registration: ClinicalTrials.gov Identifier: NCT02451670.
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Affiliation(s)
- Rebecca C Rossom
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
| | - A Lauren Crain
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
| | | | - JoAnn M Sperl-Hillen
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
| | - Stephanie A Hooker
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
| | - Kathleen Miley
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
| | - Patrick J O'Connor
- HealthPartners Institute, Minneapolis, Minnesota (Rossom, Crain, Sperl-Hillen, Hooker, Miley, O'Connor)
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21
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Sauder KA, Glueck DH, Harrall KK, D'Agostino R, Dolan LM, Lane AD, Liese AD, Lustigova E, Malik FS, Marcovina S, Mayer‐Davis E, Mottl A, Pihoker C, Reynolds K, Shah AS, Urbina EM, Wagenknecht LE, Daniels SR, Dabelea D. Exploring Racial and Ethnic Differences in Arterial Stiffness Among Youth and Young Adults With Type 1 Diabetes. J Am Heart Assoc 2023; 12:e028529. [PMID: 36994741 PMCID: PMC10122883 DOI: 10.1161/jaha.122.028529] [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: 10/18/2022] [Accepted: 02/06/2023] [Indexed: 03/31/2023]
Abstract
Background We examined arterial stiffness in individuals with type 1 diabetes, and explored whether differences between Hispanic, non-Hispanic Black (NHB), and non-Hispanic White (NHW) individuals were attributable to modifiable clinical and social factors. Methods and Results Participants (n=1162; 22% Hispanic, 18% NHB, and 60% NHW) completed 2 to 3 research visits from ≈10 months to ≈11 years post type 1 diabetes diagnosis (mean ages of ≈9 to ≈20 years, respectively) providing data on socioeconomic factors, type 1 diabetes characteristics, cardiovascular risk factors, health behaviors, quality of clinical care, and perception of clinical care. Arterial stiffness (carotid-femoral pulse wave velocity [PWV], m/s) was measured at ≈20 years of age. We analyzed differences in PWV by race and ethnicity, then explored the individual and combined impact of the clinical and social factors on these differences. PWV did not differ between Hispanic (adjusted mean 6.18 [SE 0.12]) and NHW (6.04 [0.11]) participants after adjustment for cardiovascular risks (P=0.06) and socioeconomic factors (P=0.12), or between Hispanic and NHB participants (6.36 [0.12]) after adjustment for all factors (P=0.08). PWV was higher in NHB versus NHW participants in all models (all P<0.001). Adjustment for modifiable factors reduced the difference in PWV by 15% for Hispanic versus NHW participants; by 25% for Hispanic versus NHB; and by 21% for NHB versus NHW. Conclusions Cardiovascular and socioeconomic factors explain one-quarter of the racial and ethnic differences in PWV of young people with type 1 diabetes, but NHB individuals still experienced greater PWV. Exploration of pervasive inequities potentially driving these persistent differences is needed.
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Affiliation(s)
- Katherine A. Sauder
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) CenterUniversity of Colorado Anschutz Medical CampusAuroraCO
| | - Deborah H. Glueck
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) CenterUniversity of Colorado Anschutz Medical CampusAuroraCO
| | - Kylie K. Harrall
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) CenterUniversity of Colorado Anschutz Medical CampusAuroraCO
| | - Ralph D'Agostino
- Biostatistics and Data SciencesWake Forest University School of MedicineWinston‐SalemNC
| | - Lawrence M. Dolan
- Pediatrics, Cincinnati Children’s Hospital Medical Center Department of Pediatrics & The University of CincinnatiCincinnatiOH
| | - Abbi D. Lane
- Exercise ScienceUniversity of South Carolina Arnold School of Public HealthColumbiaSC
| | - Angela D. Liese
- Epidemiology and BiostatisticsUniversity of South Carolina Arnold School of Public HealthColumbiaSC
| | - Eva Lustigova
- Research & EvaluationKaiser Permanente Southern CaliforniaPasadenaCA
| | | | | | | | - Amy Mottl
- MedicineUniversity of North Carolina at Chapel HillChapel HillNC
| | | | - Kristi Reynolds
- Research & EvaluationKaiser Permanente Southern CaliforniaPasadenaCA
| | - Amy S. Shah
- Pediatrics, Cincinnati Children’s Hospital Medical Center Department of Pediatrics & The University of CincinnatiCincinnatiOH
| | - Elaine M. Urbina
- Pediatrics, Cincinnati Children’s Hospital Medical Center Department of Pediatrics & The University of CincinnatiCincinnatiOH
| | | | - Stephen R. Daniels
- PediatricsPediatrics, University of Colorado Anschutz Medical CampusAuroraCO
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) CenterUniversity of Colorado Anschutz Medical CampusAuroraCO
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Kim C, Catov J, Schreiner PJ, Appiah D, Wellons MF, Siscovick D, Calderon‐Margalit R, Huddleston H, Ebong IA, Lewis CE. Women's Reproductive Milestones and Cardiovascular Disease Risk: A Review of Reports and Opportunities From the CARDIA Study. J Am Heart Assoc 2023; 12:e028132. [PMID: 36847077 PMCID: PMC10111436 DOI: 10.1161/jaha.122.028132] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
In 1985 to 1986, the CARDIA (Coronary Artery Risk Development in Young Adults) study enrolled 5115 Black or White participants, including 2788 women, aged 18 to 30 years. Over the following 35 years, the CARDIA study amassed extensive longitudinal data on women's reproductive milestones, spanning menarche to menopause. Although not initially conceived as a study of women's health, >75 CARDIA study publications address relationships between reproductive factors and events with cardiovascular and metabolic risk factors, subclinical and clinical cardiovascular disease, and social determinants of health. The CARDIA study was one of the earliest population-based reports to note Black-White differences in age at menarche and associations with cardiovascular risk factors. Adverse pregnancy outcomes, particularly gestational diabetes and preterm birth, have been assessed along with postpartum behaviors, such as lactation. Existing studies have examined risk factors for adverse pregnancy outcomes and lactation, as well as their relationship to future cardiovascular and metabolic risk factors, diagnoses, and subclinical atherosclerosis. Ancillary studies examining components of polycystic ovary syndrome and ovarian biomarkers, such as anti-Müllerian hormone, have facilitated examination of reproductive health in a population-based cohort of young adult women. As the cohort transitioned through menopause, examination of the importance of premenopausal cardiovascular risk factors along with menopause has improved our understanding of shared mechanisms. The cohort is now aged in the 50s to mid-60s, and women will begin to experience a greater number of cardiovascular events as well as other conditions, such as cognitive impairment. Thus, in the next decade, the CARDIA study will provide a unique resource for understanding how the women's reproductive life course epidemiology informs cardiovascular risk, as well as reproductive and chronological aging.
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Affiliation(s)
- Catherine Kim
- Departments of Medicine, Obstetrics and Gynecology, and EpidemiologyUniversity of MichiganAnn ArborMI
| | - Janet Catov
- Department of Obstetrics, Gynecology and Reproductive SciencesUniversity of PittsburghPittsburghPA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community HealthUniversity of MinnesotaMinneapolisMN
| | - Duke Appiah
- Department of Public Health, Graduate School of Biomedical SciencesTexas Tech UniversityLubbockTX
| | | | | | | | - Heather Huddleston
- Department of Obstetrics, Gynecology and Reproductive SciencesUniversity of California San FranciscoSan FranciscoCA
| | | | - Cora E. Lewis
- Department of EpidemiologyUniversity of Alabama at BirminghamBirminghamAL
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Shah NS, Huang X, Petito LC, Bancks MP, Ning H, Cameron NA, Kershaw KN, Kandula NR, Carnethon MR, Lloyd-Jones DM, Khan SS. Social and Psychosocial Determinants of Racial and Ethnic Differences in Cardiovascular Health in the United States Population. Circulation 2023; 147:190-200. [PMID: 36334260 PMCID: PMC9852071 DOI: 10.1161/circulationaha.122.061991] [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: 08/05/2022] [Accepted: 10/25/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Social and psychosocial factors are associated with cardiovascular health (CVH). Our objective was to examine the contributions of individual-level social and psychosocial factors to racial and ethnic differences in population CVH in the NHANES (National Health and Nutrition Examination Surveys) 2011 to 2018, to inform strategies to mitigate CVH inequities. METHODS In NHANES participants ages ≥20 years, Kitagawa-Blinder-Oaxaca decomposition estimated the statistical contribution of individual-level factors (education, income, food security, marital status, health insurance, place of birth, depression) to racial and ethnic differences in population mean CVH score (range, 0-14, accounting for diet, smoking, physical activity, body mass index, blood pressure, cholesterol, blood glucose) among Hispanic, non-Hispanic Asian, or non-Hispanic Black adults compared with non-Hispanic White adults. RESULTS Among 16 172 participants (representing 255 million US adults), 24% were Hispanic, 12% non-Hispanic Asian, 23% non-Hispanic Black, and 41% non-Hispanic White. Among men, mean (SE) CVH score was 7.45 (2.3) in Hispanic, 8.71 (2.2) in non-Hispanic Asian, 7.48 (2.4) in non-Hispanic Black, and 7.58 (2.3) in non-Hispanic White adults. In Kitagawa-Blinder-Oaxaca decomposition, education explained the largest component of CVH differences among men (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.36 [0.04] points higher in Hispanic, 0.24 [0.04] points lower in non-Hispanic Asian, and 0.23 [0.03] points higher in non-Hispanic Black participants; P<0.05). Among women, mean (SE) CVH score was 8.03 (2.4) in Hispanic, 9.34 (2.1) in non-Hispanic Asian, 7.43 (2.3) in non-Hispanic Black, and 8.00 (2.5) in non-Hispanic White adults. Education explained the largest component of CVH difference in non-Hispanic Black women (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.17 [0.03] points higher in non-Hispanic Black participants; P<0.05). Place of birth (born in the United States versus born outside the United States) explained the largest component of CVH difference in Hispanic and non-Hispanic Asian women (if distribution of place of birth were similar to non-Hispanic White participants, CVH score would be 0.36 [0.07] points lower and 0.49 [0.16] points lower, respectively; P<0.05). CONCLUSIONS Education and place of birth confer the largest statistical contributions to the racial and ethnic differences in mean CVH score among US adults.
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Affiliation(s)
- Nilay S. Shah
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Xiaoning Huang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Lucia C. Petito
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Michael P. Bancks
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Hongyan Ning
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Natalie A. Cameron
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Kiarri N. Kershaw
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Namratha R. Kandula
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Mercedes R. Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Donald M. Lloyd-Jones
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Sadiya S. Khan
- Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
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Woodward SH. Autonomic regulation during sleep in PTSD. Neurobiol Stress 2022; 21:100483. [DOI: 10.1016/j.ynstr.2022.100483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/01/2022] [Accepted: 08/25/2022] [Indexed: 10/31/2022] Open
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Hu J, Yao J, Deng S, Balasubramanian R, Jiménez MC, Li J, Guo X, Cruz DE, Gao Y, Huang T, Zeleznik OA, Ngo D, Liu S, Rosal MC, Nassir R, Paynter NP, Albert CM, Tracy RP, Durda P, Liu Y, Taylor KD, Johnson WC, Sun Q, Rimm EB, Eliassen AH, Rich SS, Rotter JI, Gerszten RE, Clish CB, Rexrode KM. Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts. Circ Res 2022; 131:601-615. [PMID: 36052690 PMCID: PMC9473718 DOI: 10.1161/circresaha.121.320134] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.
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Affiliation(s)
- Jie Hu
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jie Yao
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
| | - Raji Balasubramanian
- Department of Biostatistics and Epidemiology, University of Massachusetts – Amherst (R.B.)
| | - Monik C. Jiménez
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jun Li
- Division of Preventive Medicine (J.L., N.P.P.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Daniel E. Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
| | - Yan Gao
- Department of Medicine, University of Mississippi Medical Center, Jackson (Y.G.)
| | - Tianyi Huang
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
| | - Oana A. Zeleznik
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
| | - Debby Ngo
- Brigham and Women’s Hospital and Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (D.N.), Harvard Medical School, Boston, MA
| | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI (S.L.)
- Division of Endocrinology, Department of Medicine, Warren Alpert Medical School of Brown University, Providence, RI (S.L.)
| | - Milagros C. Rosal
- Division of Preventive and Behavioral Medicine, Department of Population and Quantitative Sciences, University of Massachusetts Medical School, Worcester (M.C.R.)
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura University, Saudi Arabia (R.N.)
| | - Nina P. Paynter
- Division of Preventive Medicine (J.L., N.P.P.), Harvard Medical School, Boston, MA
| | - Christine M. Albert
- Department of Cardiology, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA (C.M.A.)
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine (R.P.T., P.D.), Larner College of Medicine, University of Vermont, Burlington
- Department of Biochemistry (R.P.T.), Larner College of Medicine, University of Vermont, Burlington
| | - Peter Durda
- Department of Pathology and Laboratory Medicine (R.P.T., P.D.), Larner College of Medicine, University of Vermont, Burlington
| | - Yongmei Liu
- Divisions of Cardiology and Neurology, Department of Medicine, Duke University Medical Center, Durham, NC (Y.L.)
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle (W.C.J.)
| | - Qi Sun
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Eric B. Rimm
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - A. Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine (T.H., O.A.Z., Q.S., E.B.R., A.H.E.), Harvard Medical School, Boston, MA
- Department of Epidemiology (J.H., M.C.J., J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Nutrition (J.L., Q.S., E.B.R., A.H.E.), Harvard T.H. Chan School of Public Health, Boston, MA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville (S.S.R.)
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (J.Y., X.G., K.D.T., J.I.R.)
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (S.D., D.E.C., R.E.G.)
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge (R.E.G., C.B.C.)
| | - Clary B. Clish
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge (R.E.G., C.B.C.)
| | - Kathryn M. Rexrode
- Division of Women’s Health (J.H., M.C.J., K.M.R.), Harvard Medical School, Boston, MA
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Mehta R, Khan SS. Leveraging the Metabolome: Translating Social Risk Into Biological Pathways. Circ Res 2022; 131:616-619. [PMID: 36108054 PMCID: PMC9494892 DOI: 10.1161/circresaha.122.321700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Rupal Mehta
- Division of Nephrology, Department of Medicine (R.M.), Northwestern University Feinberg School of Medicine
| | - Sadiya S Khan
- Division of Cardiology, Department of Medicine (S.S.K.), Northwestern University Feinberg School of Medicine
- Department of Preventive Medicine (S.S.K.), Northwestern University Feinberg School of Medicine
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Carnethon MR, Rodriguez F, Watson KE. Toward a Broader Conceptualization of Disparities and Solutions. Circulation 2022; 146:145-146. [PMID: 35861771 DOI: 10.1161/circulationaha.122.061209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Mercedes R Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (M.R.C.)
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