METHODS: The HD-HEI tool adapted the Malaysian Dietary Guidelines 2010 framework according to HD-specific nutrition guidelines. This HD-HEI was applied to 3-day dietary records of 382 HD patients. Relationships between HD-HEI scores and nutritional parameters were tested by partial correlations. Binary logistic regression models adjusted with confounders were used to determine adjusted odds ratio (adjOR) with 95% confidence interval (CI) for nutritional risk based on HD-HEI scores categorization.
RESULTS: The total HD-HEI score (51.3 ± 10.2) for this HD patient population was affected by ethnicity (Ptrend < .001) and sex (P = .003). No patient achieved "good" DQ (score: 81-100), while DQ of 54.5% patients were classified as "needs improvement" (score: 51-80) and remaining as "poor" (score: 0-51). Total HD-HEI scores were positively associated with dietary energy intake (DEI), dietary protein intake (DPI), dry weight, and handgrip strength, but inversely associated with Dietary Monotony Index (DMI) (all P
METHODS: An à posteriori approach examined 3-day dietary recalls of 382 multiethnic Malaysian patients on HD, leading to short-listing of 31 food groups. Dietary patterns were derived through principal component analysis. Sociodemographic and lifestyle characteristics together with nutritional parameters were examined for associations with specific dietary patterns.
RESULTS: Four dietary patterns emerged, namely, "Home Food," "Eating Out (EO)-Rice," "EO-Sugar sweetened beverages," and "EO-Noodle." Younger patients, male gender, Malay, and patients with working status were more likely to follow "EO-Rice" and "EO-Sugar sweetened beverages" patterns, while Chinese patients were more likely to consume "EO-Noodle" pattern (all P values
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
METHODS: Using 3 d of dietary records, FA intakes of 333 recruited patients were calculated using a food database built from laboratory analyses of commonly consumed Malaysian foods. Plasma triacylglycerol (TG) and erythrocyte FAs were determined by gas chromatography.
RESULTS: High dietary saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) consumption trends were observed. Patients on HD also reported low dietary ω-3 and ω-6 polyunsaturated fatty acid (PUFA) consumptions and low levels of TG and erythrocyte FAs. TG and dietary FAs were significantly associated respective to total PUFA, total ω-6 PUFA, 18:2 ω-6, total ω-3 PUFA, 18:3 ω-3, 22:6 ω-3, and trans 18:2 isomers (P < 0.05). Contrarily, only dietary total ω-3 PUFA and 22:6 ω-3 were significantly associated with erythrocyte FAs (P < 0.01). The highest tertile of fish and shellfish consumption reflected a significantly higher proportion of TG 22:6 ω-3. Dietary SFAs were directly associated with TG and erythrocyte MUFA, whereas dietary PUFAs were not.
CONCLUSION: TG and erythrocyte FAs serve as biomarkers of dietary PUFA intake in patients on HD. Elevation of circulating MUFA may be attributed to inadequate intake of PUFAs.