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      Association between hemoglobin variability and incidence of hypertension over 40 years: a Korean national cohort study

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          Abstract

          Hemoglobin level determines blood viscosity and as hemoglobin level rises, blood pressure rises. However, hemoglobin level in individuals is not fixed and change in hemoglobin is affected by various clinical conditions. The purpose of this study is to investigate whether the hemoglobin variability affects the development of hypertension using Korean cohort database. This study was conducted with 94,798 adults (age ≥ 40 years) who visited the health screening in 2006 or 2007 (index year) and had at least 3 health screenings from 2002 to 2007. Hemoglobin variability was assessed by 3 indices of coefficient of variation (CV), standard deviation, and variability independent of the mean. Cox proportional hazard regression analysis was performed for each index of quartile groups (Q1–Q4). A total of 29,145 participants (30.7%) had the incidence of hypertension during a median follow-up of 7.4 ± 2.5 years. In the multivariable adjusted model, the hazard ratio and 95% confidence interval for incidence of hypertension of Q2, Q3, and Q4 compared with Q1 of hemoglobin variability CV were 1.014 [0.981–1.047], 1.064 [1.030–1.099] and 1.094 [1.059–1.131] respectively. The results were consistent in various sensitivity and subgroup analyses. This study showed that hemoglobin variability could be associated with hypertension development.

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          Data Resource Profile: The National Health Information Database of the National Health Insurance Service in South Korea

          Data resource basics The National Health Information Database (NHID) is a public database on health care utilization, health screening, socio-demographic variables, and mortality for the whole population of South Korea, formed by the National Health Insurance Service. The population included in the data is over 50 million, and the participation rate in the health screening programs was 74.8% in 2014. The NHID covers data between 2002 and 2014. Those insured by NHI pay insurance contributions and receive medical services from their health care providers. The NHIS, as the single insurer, pays costs based on the billing records of health care providers (Figure 1). To govern and carry out these processes in the NHI, the NHIS built a data warehouse to collect the required information on insurance eligibility, insurance contributions, medical history, and medical institutions. In 2012, the NHIS formed the NHID using information from medical treatment and health screening records and eligibility data from an existing database system. Figure 1. The governance of the National Health Insurance of South Korea. Data collected The eligibility database includes information about income-based insurance contributions, demographic variables, and date of death. The national health screening database includes information on health behaviors and bio-clinical variables. The health care utilization database includes information on records on inpatient and outpatient usage (diagnosis, length of stay, treatment costs, services received) and prescription records (drug code, days prescribed, daily dosage). The long-term care insurance database includes information about activities of daily living and service grades. The health care provider database includes data about the types of institutions, human resources, and equipment. In the NHID, de-identified join keys replacing the personal identifiers are used to interlink these databases. Data resource use Papers published covered various diseases or health conditions like infectious diseases, cancer, cardiovascular diseases, hypertension, diabetes mellitus, and injuries and risk factors such as smoking, alcohol consumption, and obesity. The impacts of health care and public health policies on health care utilization have been also explored since the data include all the necessary information reflecting patterns of health care utilization. Reasons to be cautious First, information on diagnosis and disease may not be optimal for identifying disease occurrence and prevalence since the data have been collected for medical service claims and reimbursement. However, the NHID also collects prescription data with secondary diagnosis, so the accuracy of the disease information can be improved. Second, the data linkage with other secondary national data is not widely available due to privacy issues in Korea. Governmental discussions on the statutory reform of data linkage using the NHID are under way. Collaboration and data access Access to the NHID can be obtained through the Health Insurance Data Service home page (http://nhiss.nhis.or.kr). An ethics approval from the researchers’ institutional review board is required with submission of a study proposal, which is reviewed by the NHIS review committee before providing data. Further inquiries on data use can be obtained by contacting the corresponding author. Funding and competing interests This work was supported by the NHIS in South Korea. The authors declare no competing interests.
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            Cardiovascular disease and risk factors in Asia: a selected review.

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              Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study.

              A high visit-to-visit variability in cholesterol levels has been suggested to be an independent predictor of major adverse cardiovascular events in patients with coronary artery disease (CAD). Because whether this notion applies to general population is not known, we aimed to investigate the associations between total cholesterol (TC) variability and the risk of all-cause mortality, myocardial infarction (MI), and stroke.
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                Author and article information

                Contributors
                cardiopark@gmail.com
                syang@gist.ac.kr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 July 2020
                21 July 2020
                2020
                : 10
                Affiliations
                [1 ]ISNI 0000 0001 1033 9831, GRID grid.61221.36, Department of Biomedical Science and Engineering, , Gwangju Institute of Science and Technology, ; 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005 Republic of Korea
                [2 ]ISNI 0000 0001 1033 9831, GRID grid.61221.36, School of Mechanical Engineering, , Gwangju Institute of Science and Technology, ; 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005 Republic of Korea
                [3 ]ISNI 0000 0001 2218 7142, GRID grid.255166.3, Division of Cardiology, Department of Internal Medicine, , Dong-A University College of Medicine, ; Daesingongwon 26, Seo-gu, Busan, 49201 Republic of Korea
                Article
                69022
                10.1038/s41598-020-69022-x
                7374722
                32694597
                d99bb8b4-159d-4c32-9395-38e78b7911e3
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: NRF-2016M3A7B4910556
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                cardiology,diseases,medical research,risk factors
                Uncategorized
                cardiology, diseases, medical research, risk factors

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