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      Nonapnea Sleep Disorders in Patients Younger than 65 Years Are Significantly Associated with CKD: A Nationwide Population-Based Study

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          Abstract

          Background

          Nonapnea sleep disorders (NASD) and sleep-related problems are associated with poor health outcomes. However, the association between NASD and the development and prognosis of chronic kidney disease (CKD) has not been investigated thoroughly. We explored the association between CKD and NASD in Taiwan.

          Methods

          We conducted a population-based study using the Taiwan National Health Insurance database with1,000,000 representative data for the period from January 1, 2000 to December 31, 2009. We investigated the incidence and risk of CKD in 7,006 newly diagnosed NASD cases compared with 21,018 people without NASD matched according to age, sex, index year, urbanization, region, and monthly income at a 1:3 ratio.

          Results

          The subsequent risk of CKD was 1.48-foldhigher in the NASD cohort than in the control cohort (95% confidence interval [CI] = 1.26–1.73, p< 0.001). Men, older age, type 2 diabetes mellitus, and gout were significant factors associated with the increased risk of CKD (p< 0.001). Among different types of NASDs, patients with insomnia had a 52% increased risk of developing CKD (95%CI = 1.23–1.84; P<0.01), whereas patients with sleep disturbance had a 49%increased risk of subsequent CKD (95% CI = 1.19–1.87; P<0.001). Younger women (aged < 65 years) were at a high risk of CKD with NASD (adjusted hazard ratio, [HR] = 1.81; 95% CI = 1.35–2.40, p< 0.001).

          Conclusions

          In this nationwide population-based cohort study, patients with NASD, particularly men of all ages and women aged younger than 65 years, were at high risk of CKD.

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          Most cited references34

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          Prospective study of the association between sleep-disordered breathing and hypertension.

          Sleep-disordered breathing is prevalent in the general population and has been linked to chronically elevated blood pressure in cross-sectional epidemiologic studies. We performed a prospective, population-based study of the association between objectively measured sleep-disordered breathing and hypertension (defined as a laboratory-measured blood pressure of at least 140/90 mm Hg or the use of antihypertensive medications). We analyzed data on sleep-disordered breathing, blood pressure, habitus, and health history at base line and after four years of follow-up in 709 participants of the Wisconsin Sleep Cohort Study (and after eight years of follow-up in the case of 184 of these participants). Participants were assessed overnight by 18-channel polysomnography for sleep-disordered breathing, as defined by the apnea-hypopnea index (the number of episodes of apnea and hypopnea per hour of sleep). The odds ratios for the presence of hypertension at the four-year follow-up study according to the apnea-hypopnea index at base line were estimated after adjustment for base-line hypertension status, body-mass index, neck and waist circumference, age, sex, and weekly use of alcohol and cigarettes. Relative to the reference category of an apnea-hypopnea index of 0 events per hour at base line, the odds ratios for the presence of hypertension at follow-up were 1.42 (95 percent confidence interval, 1.13 to 1.78) with an apnea-hypopnea index of 0.1 to 4.9 events per hour at base line as compared with none, 2.03 (95 percent confidence interval, 1.29 to 3.17) with an apnea-hypopnea index of 5.0 to 14.9 events per hour, and 2.89 (95 percent confidence interval, 1.46 to 5.64) with an apnea-hypopnea index of 15.0 or more events per hour. We found a dose-response association between sleep-disordered breathing at base line and the presence of hypertension four years later that was independent of known confounding factors. The findings suggest that sleep-disordered breathing is likely to be a risk factor for hypertension and consequent cardiovascular morbidity in the general population.
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            Quantity and Quality of Sleep and Incidence of Type 2 Diabetes

            OBJECTIVE To assess the relationship between habitual sleep disturbances and the incidence of type 2 diabetes and to obtain an estimate of the risk. RESEARCH DESIGN AND METHODS We conducted a systematic search of publications using MEDLINE (1955–April 2009), EMBASE, and the Cochrane Library and manual searches without language restrictions. We included studies if they were prospective with follow-up >3 years and had an assessment of sleep disturbances at baseline and incidence of type 2 diabetes. We recorded several characteristics for each study. We extracted quantity and quality of sleep, how they were assessed, and incident cases defined with different validated methods. We extracted relative risks (RRs) and 95% CI and pooled them using random-effects models. We performed sensitivity analysis and assessed heterogeneity and publication bias. RESULTS We included 10 studies (13 independent cohort samples; 107,756 male and female participants, follow-up range 4.2–32 years, and 3,586 incident cases of type 2 diabetes). In pooled analyses, quantity and quality of sleep predicted the risk of development of type 2 diabetes. For short duration of sleep (≤5–6 h/night), the RR was 1.28 (95% CI 1.03–1.60, P = 0.024, heterogeneity P = 0.015); for long duration of sleep (>8–9 h/night), the RR was 1.48 (1.13–1.96, P = 0.005); for difficulty in initiating sleep, the RR was 1.57 (1.25–1.97, P < 0.0001); and for difficulty in maintaining sleep, the RR was 1.84 (1.39–2.43, P < 0.0001). CONCLUSIONS Quantity and quality of sleep consistently and significantly predict the risk of the development of type 2 diabetes. The mechanisms underlying this relation may differ between short and long sleepers.
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              Chronic kidney disease as a global public health problem: approaches and initiatives - a position statement from Kidney Disease Improving Global Outcomes.

              Chronic kidney disease (CKD) is increasingly recognized as a global public health problem. There is now convincing evidence that CKD can be detected using simple laboratory tests, and that treatment can prevent or delay complications of decreased kidney function, slow the progression of kidney disease, and reduce the risk of cardiovascular disease (CVD). Translating these advances to simple and applicable public health measures must be adopted as a goal worldwide. Understanding the relationship between CKD and other chronic diseases is important to developing a public health policy to improve outcomes. The 2004 Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on 'Definition and Classification of Chronic Kidney Disease' represented an important endorsement of the Kidney Disease Outcome Quality Initiative definition and classification of CKD by the international community. The 2006 KDIGO Controversies Conference on CKD was convened to consider six major topics: (1) CKD classification, (2) CKD screening and surveillance, (3) public policy for CKD, (4) CVD and CVD risk factors as risk factors for development and progression of CKD, (5) association of CKD with chronic infections, and (6) association of CKD with cancer. This report contains the recommendations from the meeting. It has been reviewed by the conference participants and approved as position statement by the KDIGO Board of Directors. KDIGO will work in collaboration with international and national public health organizations to facilitate implementation of these recommendations.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                14 October 2015
                2015
                : 10
                : 10
                : e0140401
                Affiliations
                [1 ]Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
                [2 ]Department of Internal Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
                [3 ]Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
                [4 ]Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
                [5 ]Department of Biotechnology, College of Life Science, Kaohsiung Medical University, Kaohsiung, Taiwan
                [6 ]Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
                [7 ]Institute of Population Sciences, National Health Research Institutes, Miaoli, Taiwan
                National Health Research Institutes, TAIWAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HYL SH. Performed the experiments: CH YC ML. Analyzed the data: MY SL WL. Contributed reagents/materials/analysis tools: HC. Wrote the paper: HYL SH.

                Article
                PONE-D-15-16245
                10.1371/journal.pone.0140401
                4605694
                26466096
                595f2610-f422-4880-b7d3-93d774bcd85e
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 17 April 2015
                : 24 September 2015
                Page count
                Figures: 3, Tables: 4, Pages: 15
                Funding
                These authors have no support or funding to report.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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