Hi-Ming Ng1,2, Ban-Hock Khor3, Sharmela Sahathevan4, Ayesha Sualeheen5, Karuthan Chinna1, Abdul Halim Abdul Gafor6, Bak-Leong Goh7, Ghazali Ahmad8, Zaki Morad9, Zulfitri Azuan Mat Daud10, Pramod Khosla11, Tilakavati Karupaiah12. 1. School of Medicine, Faculty of Health and Medical Sciences, Taylor's University, Subang Jaya, Selangor, Malaysia. 2. Department of Dietetics & Nutrition Services, Sunway Medical Centre, Petaling Jaya, Selangor, Malaysia. 3. Faculty of Food Science and Nutrition, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia. 4. Department of Allied Health Sciences, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Kampar, Perak, Malaysia. 5. Dietetics Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia. 6. Department of Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Center, Kuala Lumpur, Malaysia. 7. Department of Nephrology, Serdang Hospital, Kajang, Selangor, Malaysia. 8. Department of Cardiology, National Heart Institute, Kuala Lumpur, Malaysia. 9. National Kidney Foundation of Malaysia, Petaling Jaya, Selangor, Malaysia. 10. Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia. 11. Department of Nutrition and Food Science, Wayne State University, Detroit, MI, USA. 12. School of BioSciences, Faculty of Health and Medical Sciences, Taylor's University, Subang Jaya, Selangor, Malaysia. tilly_karu@yahoo.co.uk.
Abstract
PURPOSE: To identify relationships between health-related quality of life (HRQOL) and nutritional status in hemodialysis (HD) patients. METHOD: Secondary data from a cross-sectional survey was utilized. HRQOL was assessed for 379 HD patients using the generic Short Form 36 (SF-36) and disease-specific Kidney-Disease Quality of Life-36 (KDQOL-36). Malnutrition was indicated by malnutrition inflammation score (MIS) ≥ 5, and presence of protein-energy wasting (PEW). The individual nutritional parameters included the domains of physical status, serum biomarkers, and dietary intake. Multivariate associations were assessed using the general linear model. RESULTS: MIS ≥ 5 was negatively associated with SF-36 scores of physical functioning (MIS < 5 = 73.4 ± 8.0 SE vs MIS ≥ 5 = 64.6 ± 7.7 SE, P < 0.001), role-limitation-physical (MIS < 5 = 65.3 ± 14.3 SE vs MIS ≥ 5 = 52.9 ± 14.0 SE, P = 0.006), general health (MIS < 5 = 53.7 ± 7.5 SE vs MIS ≥ 5 = 47.0 ± 7.1 SE, P = 0.003), and PCS-36 (MIS < 5 = 40.5 ± 3.3 SE vs MIS ≥ 5 = 35.9 ± 3.1 SE, P < 0.001); and KDQOL-36 score of symptoms/problems (MIS < 5 = 78.9 ± 5.6 SE vs MIS ≥ 5 = 74.8 ± 5.4 SE, P = 0.022), but not with PEW by any tool. Of individual nutritional parameters, underweight (68.1 ± 5.4 SE, P = 0.031), normal weight (63.8 ± 2.8 SE, P = 0.023), and overweight (64.3 ± 2.9 SE, P = 0.003) patients had significantly higher physical functioning scores compared to obese patients (44.8 ± 5.5 SE). Serum albumin levels were positively associated with physical functioning (P = 0.041) score. HGS was also positively associated with physical functioning (P = 0.036), and vitality (P = 0.041) scores. Greater dietary phosphorus intakes were significantly associated with lower scores for role limitation-physical (P = 0.008), bodily pain (P = 0.043), and PCS-36 (P = 0.024). CONCLUSION: Malnutrition diagnosis by MIS, but not PEW, indicated associations with HRQOL in HD patients. Individual nutritional parameters that related to higher HRQOL were BMI < 30 kg/m2, better dietary phosphorus control, greater muscle strength and higher visceral protein pool.
PURPOSE: To identify relationships between health-related quality of life (HRQOL) and nutritional status in hemodialysis (HD) patients. METHOD: Secondary data from a cross-sectional survey was utilized. HRQOL was assessed for 379 HD patients using the generic Short Form 36 (SF-36) and disease-specific Kidney-Disease Quality of Life-36 (KDQOL-36). Malnutrition was indicated by malnutrition inflammation score (MIS) ≥ 5, and presence of protein-energy wasting (PEW). The individual nutritional parameters included the domains of physical status, serum biomarkers, and dietary intake. Multivariate associations were assessed using the general linear model. RESULTS: MIS ≥ 5 was negatively associated with SF-36 scores of physical functioning (MIS < 5 = 73.4 ± 8.0 SE vs MIS ≥ 5 = 64.6 ± 7.7 SE, P < 0.001), role-limitation-physical (MIS < 5 = 65.3 ± 14.3 SE vs MIS ≥ 5 = 52.9 ± 14.0 SE, P = 0.006), general health (MIS < 5 = 53.7 ± 7.5 SE vs MIS ≥ 5 = 47.0 ± 7.1 SE, P = 0.003), and PCS-36 (MIS < 5 = 40.5 ± 3.3 SE vs MIS ≥ 5 = 35.9 ± 3.1 SE, P < 0.001); and KDQOL-36 score of symptoms/problems (MIS < 5 = 78.9 ± 5.6 SE vs MIS ≥ 5 = 74.8 ± 5.4 SE, P = 0.022), but not with PEW by any tool. Of individual nutritional parameters, underweight (68.1 ± 5.4 SE, P = 0.031), normal weight (63.8 ± 2.8 SE, P = 0.023), and overweight (64.3 ± 2.9 SE, P = 0.003) patients had significantly higher physical functioning scores compared to obese patients (44.8 ± 5.5 SE). Serum albumin levels were positively associated with physical functioning (P = 0.041) score. HGS was also positively associated with physical functioning (P = 0.036), and vitality (P = 0.041) scores. Greater dietary phosphorus intakes were significantly associated with lower scores for role limitation-physical (P = 0.008), bodily pain (P = 0.043), and PCS-36 (P = 0.024). CONCLUSION: Malnutrition diagnosis by MIS, but not PEW, indicated associations with HRQOL in HD patients. Individual nutritional parameters that related to higher HRQOL were BMI < 30 kg/m2, better dietary phosphorus control, greater muscle strength and higher visceral protein pool.
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