Chen ZQ, Luo L, Chen XX, Zhang XY, Yin SQ, Xiao GH, Xu N, Liu Q, Su CY. Dietary nutrient intake and nutritional status in maintenance hemodialysis patients: a multicenter cross-sectional survey.
Ren Fail 2024;
46:2363589. [PMID:
38874093 PMCID:
PMC11182067 DOI:
10.1080/0886022x.2024.2363589]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 05/30/2024] [Indexed: 06/15/2024] Open
Abstract
PURPOSE
To investigate the dietary nutrient intake of Maintenance hemodialysis (MHD) patients, identify influencing factors, and explore the correlation between dietary nutrient intake and nutritional and disease control indicators.
METHODS
This was a multicenter cross-sectional study. A dietary survey was conducted using a three-day dietary record method, and a self-designed diet management software was utilized to calculate the daily intake of dietary nutrients. The nutritional status and disease control indicators were assessed using subjective global assessment, handgrip strength, blood test indexes, and dialysis adequacy.
RESULTS
A total of 382 MHD patients were included in this study. Among them, 225 (58.9%) and 233 (61.0%) patients' protein and energy intake did not meet the recommendations outlined in the National Kidney Foundation's Kidney Disease Outcomes Quality Initiative Clinical Practice Guideline for Nutrition in Chronic Kidney Disease (2020 update). The average protein and energy intake for these patients were 0.99 ± 0.32 g/kg/d and 29.06 ± 7.79 kcal/kg/d, respectively. Multiple linear regression analysis showed that comorbidity-diabetes had a negative influence on normalized daily energy intake (nDEI = DEI / ideal body weight) (B = -2.880, p = 0.001) and normalized daily protein intake (nDPI = DPI / ideal body weight) (B = -0.109, p = 0.001). Pearson correlation analysis revealed that dietary DPI (r = -0.109, p < 0.05), DEI (r = -0.226, p < 0.05) and phosphorus (r = -0.195, p < 0.001) intake were statistically correlated to Kt/V; dietary nDPI (r = 0.101, p < 0.05) and sodium (r = -0.144, p < 0.001) intake were statistically correlated to serum urea nitrogen; dietary DPI (r = 0.200, p < 0.001), DEI (r = 0.241, p < 0.001), potassium (r = 0.129, p < 0.05), phosphorus (r = 0.199, p < 0.001), and fiber (r = 0.157, p < 0.001) intake were statistically correlated to serum creatinine; dietary phosphorus (r = 0.117, p < 0.05) and fiber (r = 0.142, p < 0.001) intake were statistically correlated to serum phosphorus; dietary nDPI (r = 0.125, p < 0.05), DPI (r = 0.135, p < 0.05), nDEI (r = 0.116, p < 0.05), DEI (r = 0.125, p < 0.05), potassium (r = 0.148, p < 0.001), and phosphorus (r = 0.156, p < 0.001) intake were statistically correlated to subjective global assessment scores; dietary nDPI (r = 0.215, p < 0.001), DPI (r = 0.341, p < 0.001), nDEI (r = 0.142, p < 0.05), DEI (r = 0.241, p < 0.001), potassium (r = 0.166, p < 0.05), phosphorus (r = 0.258, p < 0.001), and fiber (r = 0.252, p < 0.001) intake were statistically correlated to handgrip strength in males; dietary fiber (r = 0.190, p < 0.05) intake was statistically correlated to handgrip strength in females.
CONCLUSIONS
The dietary nutrient intake of MHD patients need improvement. Inadequate dietary nutrient intake among MHD patients could have a detrimental effect on their blood test indexes and overall nutritional status. It is crucial to address and optimize the dietary intake of nutrients in this patient population to enhance their health outcomes and well-being.
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