3
|
Bielinski SJ, Manemann SM, Lopes GS, Jiang R, Weston SA, Reichard RR, Norman AD, Vachon CM, Takahashi PY, Singh M, Larson NB, Roger VL, St Sauver JL. The Importance of Estimating Excess Deaths Regionally During the COVID-19 Pandemic. Mayo Clin Proc 2024; 99:437-444. [PMID: 38432749 PMCID: PMC10914321 DOI: 10.1016/j.mayocp.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 10/24/2023] [Accepted: 11/14/2023] [Indexed: 03/05/2024]
Abstract
National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality.
Collapse
Affiliation(s)
- Suzette J Bielinski
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
| | - Sheila M Manemann
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Guilherme S Lopes
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Susan A Weston
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - R Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Aaron D Norman
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Celine M Vachon
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Paul Y Takahashi
- Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Mandeep Singh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Nicholas B Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Véronique L Roger
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN; Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Jennifer L St Sauver
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| |
Collapse
|
4
|
Moser ED, Manemann SM, Larson NB, St Sauver JL, Takahashi PY, Mielke MM, Rocca WA, Olson JE, Roger VL, Remaley AT, Decker PA, Killian JM, Bielinski SJ. Association Between Fluctuations in Blood Lipid Levels Over Time With Incident Alzheimer Disease and Alzheimer Disease-Related Dementias. Neurology 2023; 101:e1127-e1136. [PMID: 37407257 PMCID: PMC10513892 DOI: 10.1212/wnl.0000000000207595] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 05/12/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Prevention strategies for Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD. METHODS All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD. RESULTS The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk. DISCUSSION In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed.
Collapse
Affiliation(s)
- Ethan D Moser
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Sheila M Manemann
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Nicholas B Larson
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Jennifer L St Sauver
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Paul Y Takahashi
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Michelle M Mielke
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Walter A Rocca
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Janet E Olson
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Véronique L Roger
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Alan T Remaley
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Paul A Decker
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Jill M Killian
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
| | - Suzette J Bielinski
- From the Department of Quantitative Health Sciences (E.D.M., S.M.M., N.B.L., J.L.S.S., M.M.M., W.A.R., J.E.O., V.L.R., P.A.D., J.M.K., S.J.B.); Division of Community Internal Medicine (P.Y.T.), Department of Medicine, Mayo Clinic; Department of Neurology (M.M.M., W.A.R.), Rochester, MN; Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Mayo Clinic Women's Health Research Center (W.A.R.); Department of Cardiovascular Medicine (V.L.R.), Mayo Clinic, Rochester, MN; Epidemiology and Community Branch (V.L.R.), National Heart, Lung, and Blood Institute, National Institutes of Health; and Lipoprotein Metabolism Laboratory (A.T.R.), Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
| |
Collapse
|
7
|
Manemann SM, Weston SA, Jiang R, Larson NB, Roger VL, Takahashi PY, Chamberlain AM, Singh M, St Sauver JL, Bielinski SJ. Health Care Utilization and Death in Patients With Heart Failure During the COVID-19 Pandemic. Mayo Clin Proc Innov Qual Outcomes 2023; 7:194-202. [PMID: 37229286 PMCID: PMC10099179 DOI: 10.1016/j.mayocpiqo.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/31/2023] [Accepted: 04/05/2023] [Indexed: 05/27/2023] Open
Abstract
Objective To compare the 1-year health care utilization and mortality in persons living with heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. Patients and Methods Residents of a 9-county area in southeastern Minnesota aged 18 years or older with a HF diagnosis on January 1, 2019; January 1, 2020; and January 1, 2021, were identified and followed up for 1-year for vital status, emergency department (ED) visits, and hospitalizations. Results We identified 5631 patients with HF (mean age, 76 years; 53% men) on January 1, 2019, 5996 patients (mean age, 76 years; 52% men) on January 1, 2020, and 6162 patients (mean age, 75 years; 54% men) on January 1, 2021. After adjustment for comorbidities and risk factors, patients with HF in 2020 and patients with HF in 2021 experienced similar risks of mortality compared with those in 2019. After adjustment, patients with HF in 2020 and 2021 were less likely to experience all-cause hospitalizations (2020: rate ratio [RR], 0.88; 95% CI, 0.81-0.95; 2021: RR, 0.90; 95% CI, 0.83-0.97) compared with patients in 2019. Patients with HF in 2020 were also less likely to experience ED visits (RR, 0.85; 95% CI, 0.80-0.92). Conclusion In this large population-based study in southeastern Minnesota, we observed an approximately 10% decrease in hospitalizations among patients with HF in 2020 and 2021 and a 15% decrease in ED visits in 2020 compared with those in 2019. Despite the change in health care utilization, we found no difference in the 1-year mortality between patients with HF in 2020 and those in 2021 compared with those in 2019. It is unknown whether any longer-term consequences will be observed.
Collapse
Affiliation(s)
- Sheila M Manemann
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Susan A Weston
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Nicholas B Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Véronique L Roger
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
- National Institutes of Health, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Paul Y Takahashi
- Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN
| | - Alanna M Chamberlain
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mandeep Singh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | | |
Collapse
|
10
|
Pongdee T, Manemann SM, Decker PA, Larson NB, Moon S, Killian JM, Liu H, Kita H, Bielinski SJ. Rethinking blood eosinophil counts: Epidemiology, associated chronic diseases, and increased risks of cardiovascular disease. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. GLOBAL 2022; 1:233-240. [PMID: 36466741 PMCID: PMC9718542 DOI: 10.1016/j.jacig.2022.09.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Background The distribution and determinants of blood eosinophil counts in the general population are unclear. Furthermore, whether elevated blood eosinophil counts increase risk for cardiovascular disease (CVD) and other chronic diseases, other than atopic conditions, remains uncertain. Objective We sought to describe the distribution of eosinophil counts in the general population and determine the association of eosinophil count with prevalent chronic disease and incident CVD. Methods A population-based adult cohort was followed from January 1, 2006, to December 31, 2020. Electronic health record data regarding demographic characteristics, prevalent clinical characteristics, and incident CVD were extracted. Associations between blood eosinophil counts and demographic characteristics, chronic diseases, laboratory values, and risks of incident CVD were assessed using chi-square test, ANOVA, and Cox proportional hazards regression. Results Blood eosinophil counts increased with age, body mass index, and reported smoking and tobacco use. The prevalence of chronic obstructive pulmonary disease, hypertension, cardiac arrhythmias, hyperlipidemia, diabetes mellitus, chronic kidney disease, and cancer increased as eosinophil counts increased. Eosinophil counts were significantly associated with coronary heart disease (hazard ratio [HR], 1.44; 95% CI, 1.12-1.84) and heart failure (HR, 1.62; 95% CI, 1.30-2.01) in fully adjusted models and with stroke/transient ischemic attack (HR, 1.37; 95% CI, 1.16-1.61) and CVD death (HR, 1.49; 95% CI, 1.10-2.00) in a model adjusting for age, sex, race, and ethnicity. Conclusions Blood eosinophil counts differ by demographic and clinical characteristics as well as by prevalent chronic disease. Moreover, elevated eosinophil counts are associated with risk of CVD. Further prospective investigations are needed to determine the utility of eosinophil counts as a biomarker for CVD risk.
Collapse
Affiliation(s)
- Thanai Pongdee
- Division of Allergic Diseases, Mayo Clinic, Rochester, Minn
| | - Sheila M. Manemann
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minn
| | - Paul A. Decker
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minn
| | - Nicholas B. Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minn
| | - Sungrim Moon
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minn
| | - Jill M. Killian
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minn
| | - Hongfang Liu
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minn
| | - Hirohito Kita
- Division of Allergy, Asthma and Clinical Immunology, Mayo Clinic, Scottsdale, Ariz
- Department of Immunology, Mayo Clinic, Rochester, Minn
- Department of Immunology, Mayo Clinic, Scottsdale
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minn
| |
Collapse
|