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      The effect of transportation modality to dialysis facilities on health-related quality of life among hemodialysis patients: results from the Japanese Dialysis Outcomes and Practice Pattern Study

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          Abstract

          Background

          For hemodialysis (HD) patients, travel to the dialysis facility is an issue that can affect their quality of life (QOL), both physically and mentally. However, evidence on this association of transportation modality with health-related QOL (HRQOL) is scarce.

          Methods

          We conducted a cohort study among maintenance HD patients participating in the Japanese Dialysis Outcomes and Practice Pattern Study Phase 5. The study included patients who were functionally independent and able to walk. The primary exposure was the means of transportation to the dialysis facility, categorized into three groups, namely transportation by other drivers (Group 1), transportation via self-driving (Group 2) and transportation by bicycle or walking with or without public transportation (Group 3). The primary outcomes were physical and mental health composite scores (PCS and MCS) in the 12-item Short Form at 1 year after study initiation.

          Results

          Among 1225 eligible patients (Group 1, 34.4%; Group 2, 45.0%; Group 3, 20.7%), 835 were analyzed for the primary outcomes. Linear regression analyses revealed that patients in Groups 2 and 3 had significantly higher PCS and MCS at 1 year than those in Group 1 {adjusted mean differences of PCS 1.42 [95% confidence interval (CI) 0.17–2.68] and 1.94 [95% CI 0.65–3.23], respectively, and adjusted mean differences of MCS 2.53 [95% CI 0.92–4.14] and 2.20 [95% CI 0.45–3.95], respectively}.

          Conclusions

          Transportation modality was a significant prognostic factor for both PCS and MCS after 1 year in maintenance HD patients.

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          Most cited references 21

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            Reallocating time to sleep, sedentary behaviors, or active behaviors: associations with cardiovascular disease risk biomarkers, NHANES 2005-2006.

            Sleep and sedentary and active behaviors are linked to cardiovascular disease risk biomarkers, and across a 24-hour day, increasing time in 1 behavior requires decreasing time in another. We explored associations of reallocating time to sleep, sedentary behavior, or active behaviors with biomarkers. Data (n = 2,185 full sample; n = 923 fasting subanalyses) from the cross-sectional 2005-2006 US National Health and Nutrition Examination Survey were analyzed. The amounts of time spent in sedentary behavior, light-intensity activity, and moderate-to-vigorous physical activity (MVPA) were derived from ActiGraph accelerometry (ActiGraph LLC, Pensacola, Florida), and respondents reported their sleep duration. Isotemporal substitution modeling indicated that, independent of potential confounders and time spent in other activities, beneficial associations (P < 0.05) with cardiovascular disease risk biomarkers were associated with the reallocation of 30 minutes/day of sedentary time with equal time of either sleep (2.2% lower insulin and 2.0% lower homeostasis model assessment of β-cell function), light-intensity activity (1.9% lower triglycerides, 2.4% lower insulin, and 2.2% lower homeostasis model assessment of β-cell function), or MVPA (2.4% smaller waist circumference, 4.4% higher high-density lipoprotein cholesterol, 8.5% lower triglycerides, 1.7% lower glucose, 10.7% lower insulin, and 9.7% higher homeostasis model assessment of insulin sensitivity. These findings provide evidence that MVPA may be the most potent health-enhancing, time-dependent behavior, with additional benefit conferred from light-intensity activities and sleep duration when reallocated from sedentary time.
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              Association among SF36 quality of life measures and nutrition, hospitalization, and mortality in hemodialysis.

              Patients on maintenance hemodialysis (MHD) often show substantial reductions in quality of life (QoL). The SF36 (Short Form with 36 questions), a well-documented, self-administered QoL scoring system that includes eight independent scales and two main dimensions, has been widely used and validated. In 65 adult outpatients on MHD, the SF36 and its scales and dimensions, scored as a number between 0 and 100, and the nutritional and inflammatory state measured by subjective global assessment, near-infrared (NIR) body fat, body mass index (BMI), and pertinent laboratory values, including hemoglobin, albumin, and C-reactive protein were assessed. Twelve-month prospective hospitalization rates and mortality were used as the clinical outcomes. Multivariate (case-mix) adjusted correlation coefficients were statistically significant between SF36 scores and serum albumin and hemoglobin concentrations. There were significant inverse correlations between SF36 scores and the BMI and NIR body fat percentage. Hypoalbuminemic, anemic, and obese patients on MHD had a worse QoL. Prospective hospitalizations correlated significantly with the SF36 total score and its two main dimensions (r between -0.28 and -0.40). The Cox proportional regression relative risk of death for each 10 unit decrease in SF36 was 2.07 (95% CI, 1.08 to 3.98; P = 0.02). Of the eight components and two dimensions of the SF36, the Mental Health dimension and the SF36 total score had the strongest predictive value for mortality. Thus, in patients on MHD the SF36 appears to have significant associations with measures of nutritional status, anemia, and clinical outcomes, including prospective hospitalization and mortality. Even though obesity, unlike undernutrition, is not generally an indicator of poor outcome in MHD, the SF36 may detect obese patients on MHD at higher risk for morbidity and mortality.
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                Author and article information

                Journal
                Clin Kidney J
                Clin Kidney J
                ckj
                Clinical Kidney Journal
                Oxford University Press
                2048-8505
                2048-8513
                August 2020
                11 September 2019
                11 September 2019
                : 13
                : 4
                : 640-646
                Affiliations
                [1 ] Division of Nephrology and Hypertension, Department of Internal Medicine, St. Marianna University School of Medicine , Kawasaki, Japan
                [2 ] Department of Innovative Research and Education for Clinicians and Trainees, Fukushima Medical University Hospital , Fukushima, Japan
                [3 ] Department of Metabolism, Endocrinology, and Molecular Medicine, Osaka City University Graduate School of Medicine , Osaka, Japan
                [4 ] Department of Nephrology, Nara Medical University , Kashihara, Nara, Japan
                [5 ] Department of Clinical Epidemiology, Graduate School of Medicine, Fukushima Medical University , Fukushima, Japan
                Author notes
                Correspondence and offprint requests to: Kenji Omae; E-mail: omae416@ 123456fmu.ac.jp
                Article
                sfz110
                10.1093/ckj/sfz110
                7467582
                © The Author(s) 2019. Published by Oxford University Press on behalf of ERA-EDTA.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                Page count
                Pages: 7
                Product
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                Original Articles
                AcademicSubjects/MED00340

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