Home About us Current issue Back issues Submission Instructions Advertise Contact Login   

Search Article 
  
Advanced search 
 
Saudi Journal of Kidney Diseases and Transplantation
Users online: 3249 Home Bookmark this page Print this page Email this page Small font sizeDefault font size Increase font size 
 


 
ORIGINAL ARTICLE Table of Contents   
Year : 2010  |  Volume : 21  |  Issue : 5  |  Page : 846-851
Malnutrition predicting factors in hemodialysis patients


1 Shefa Neuroscience Research Center, Tehran, Iran
2 Department of Nutrition and Biochemistry, Tehran University of Medical Sciences, Tehran, Iran
3 Department of Epidemiology, Tehran University of Medical Sciences, Tehran, Iran
4 Urology Research Center, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran

Click here for correspondence address and email

Date of Web Publication31-Aug-2010
 

   Abstract 

Malnutrition is a predictor of increased mortality in chronic hemodialysis (HD) patients. Various factors may contribute to malnutrition in these patients including energy and protein intake, inflammation, and comorbidity. To determine the importance of these factors in malnutrition of chronic HD patients, we studied 112 chronic HD patients in two centers was evaluated with the Dialysis Malnutrition Score (DMS) and anthropometric and biochemical indices. Seventy six (67.8%) patients were classified as malnourished. According to DMS score, poor protein intake (r= -0.34, P< 0.01), comorbidities (r= -0.24, P< 0.05), poor energy intake (r= - 0.18, P< 0.005), and inflammation (r= -0.16, P< 0.05) were significant predictors of malnutrition in descending order of importance. Multiple regression analysis showed that only poor protein intake was the explanatory variable of anthropometric measurements decline including body mass index, triceps skin fold thick-ness, mid arm circumference, mid arm muscle circumference, fat free mass, fat mass, albumin, creatinine and transferrine. None of the mentioned factors predicted the decrease of biochemical markers. We conclude that the frequency of malnutrition is high in our population and poor protein intake is the primary contributing factor for this condition. There­fore, providing enough protein may be a simple and effective way in preventing malnutrition in these patients.

How to cite this article:
Jahromi SR, Hosseini S, Razeghi E, Meysamie Ap, Sadrzadeh H. Malnutrition predicting factors in hemodialysis patients. Saudi J Kidney Dis Transpl 2010;21:846-51

How to cite this URL:
Jahromi SR, Hosseini S, Razeghi E, Meysamie Ap, Sadrzadeh H. Malnutrition predicting factors in hemodialysis patients. Saudi J Kidney Dis Transpl [serial online] 2010 [cited 2019 Aug 25];21:846-51. Available from: http://www.sjkdt.org/text.asp?2010/21/5/846/68878

   Introduction Top


Malnutrition is common among chronic hemo­hemodialysis (HD) patients [1],[2] and is associated with higher rates of morbidity and mortality. [3],[4],[5],[6] Various factors may contribute to malnutrition in these patients. Deterioration in the nutri­tional status of HD patients may be caused by disturbances in protein and energy metabo­lism, hormonal derangement, and reduction in energy and protein intake. [7] Due to co-morbid conditions, HD patients may become malnou­rished despite adequate dialysis and enough protein intake. [8] Malnutrition is also associated with inflammation in HD patients. [9],[10]

There is a paucity of studies that compare the degree of effect of inflammation, co-morbi­dity, and protein and energy intake on the nutritional status of HD patients in addition to the primary cause of malnutrition in this po­pulation.

We aim from this study to determine the significant factors that cause malnutrition in HD patients and their order of importance.


   Patients and Methods Top


We studied 112 stable chronic HD in two Iranian dialysis centers (Sina and Amiralam) (during 9 months). We excluded from the study patients with age less than 19 years, HD for less than three months, severe sepsis, multiple organ failure, clinical or surgical hospitaliza­tion in previous month, ongoing entral or pa­rentral nutrition, and active disease. The study was approved by the Ethics Committee of Tehran University of Medical Science and in­formed consent was obtained from the study patients.

General and demographic information (age, gender, diagnosis, co morbidities, and clinical and dialysis history) were collected. Anthropo­metric and biochemical parameters were as­sessed and the Dialysis Malnutrition Score (DMS) was calculated. Anthropometric indices included post dialysis weight (dry weight), height, fat mass (FM), fat free mass (FFM), mid arm circumference (MAC), mid arm muscle circumference (MAMC), triceps skin fold thick­ness (TSF), and body mass index (BMI). Bio­chemical parameters include serum albumin, transferrin, creatinine and prealbumin.

For measuring the amount of energy and pro­tein intake, three-day dietary recall was used. C-reactive protein (CRP) more than 10 mg/L was considered as an indicator of inflamma­tion (CRP was measured by sensitive ELAIZA method).

The DMS questionnaire consisted of two parts. In the first part information was collected about recent weight loss, food intake, gastrointestinal symptoms, functional status, and influence of disease on nutritional needs. The second part contained a brief physical examination. The score of 7 to 14 was considered to be well nourished, 15 to 21 and 22 to 35 were inter­preted as mild-to-moderate and severe malnu­trition respectively.

Blood samples were obtained after an over­night fasting and before HD and promptly sent to the laboratory. Then anthropometric measure­ments and bioimpedance analysis (BIA) were conducted after HD. Conventional (single­current) whole-body BIA was assessed by the BIA-Quantum II apparatus using the fluids software (RJL Systems, Clinton Twp, MI, USA).


   Statistical Analysis Top


Statistical values are presented as the mean ± SD. Pearson's correlation coefficient was used to examine the relationship between energy and protein intake and anthropometric and bio­chemical parameters. Chi-square test was uti­lized to assess the relationship between co­morbiditiy, inflammation, anthropometric, and biochemical factors. Multiple regression ana­lysis was used to compare the effect of energy and protein intake, inflammation, and comor­bid condition on nutritional status parameters.


   Results Top


Of 112 participants, 64 (57.1%) patients were men and their mean age was 59.5 ± 14.4 years (range, 24-85), which did not differ signifi­cantly from women. The mean duration of HD was 32.1 ± 31.2 months (range, 3-166). Co­morbidities were noted in 46 (40.4%) patients and inflammation in 35 (31.2%). The mean amount of energy intake was 31.34 ± 15.33 kilocalories per kilogram adjusted body weight with 77 (68.8%) patients receiving less than 35 kcal/kg. The mean amount of protein intake was 1.5 ± 0.5 gram per kilogram adjusted body weight; 56 (50%) patients consumed less than 1.2 gram/kg. There was no significant diffe­rence between men and women in inflam­mation, comorbidities and in the mean amount of protein and energy intake per kilogram ad­justed body weight. General anthropometric and biochemical findings are shown in [Table 1].
Table 1 :General anthropometric and biochemical findings of hemodialysis patients.

Click here to view


The mean of DMS was 16.6 ± 5.19 (range 7­27). Thirty six (32.1%) patients were classified as well nourished, 55 (49.1%) as mildly to mo­derately malnourished, and the 21 (18.8%) as severely malnourished. [Table 2] shows the data about the correlation patients' parameters with DMS; protein malnutrition was the primary determining factor (r= -0.48), while energy intake, comorbidities, and inflammation ranked second, third, and fourth, respectively.
Table 2 :Correlation between dialysis malnutrition score and co-morbidities, inflammation, and protein
and energy intake of hemodialysis patients.


Click here to view


[Table 3] shows that energy and protein intake had significant relationship with BMI, TSF, AMC, MAMC, FM and FFM, serum albumin, creatinine and transferring. [Table 4] shows the correlation between comorbidities and inflam­mation and dependent factors. There was a sig­nificant correlation between inflammation and MAMC, FFM, and FM.
Table 3 :Correlation between energy and protein intake and anthropometric and biochemical indices of
hemodialysis patients.


Click here to view
Table 4 :Correlation between inflammation and co-morbidities, anthropometric and biochemical indices
of hemodialysis patients.


Click here to view


We found a significant correlation between protein intake and BMI, TSF, and AMC using multiple regression models. According to the anthropometric and biochemical indices, pro­tein intake was the strongest determining fac­tor of malnutrition.


   Discussion Top


Factors such as age, comorbidity, inflamma­tion and malnutrition may cause serious com­plications and increase mortality rate in dia­lysis patients. [11],[12],[13] Deterioration of anthropome­tric and biochemical parameters cannot be dis­entangled from a larger and more complex context, including malnutrition, inflammation, and cardiovascular disease. [14],[15],[16]

According to Panzetta et al energy intake of 35 kcal/kg/day and protein intake of 1.2 g/kg/ day are ideal for hemodialysis populations. [17] In our study, about 69% of patients received less than 35 kcal/kg energy and 50% consumed less than 1.2 gram protein/kg. Therefore, energy and protein intake fall behind the recommenda­tions in a great number of our patients. In the study of Valenzuela et al, 74% of the patients consumed less than 35 Kcal/kg/ day and 47% of the patients consumed less than 1.2 g/Kg/ day, very similar to our findings. [18] Nevertheless, we cannot rule out underreporting of energy and protein intake from some patients.

The DMS revealed that 32.1% of our patients were well nourished, 49.1% and 18.8% had mild-to-moderate and severe malnutrition, res­pectively. several studies reported higher preva­lence of malnutrition than that in our study. [19],[20] However, in the study of Hartley et al, the pre­valence of malnutrition was less than 30% in England, which was far less than our study. [21] According to DMS score, poor protein intake, comorbidities, poor energy intake, and inflam­mation were the predictors of malnutrition in descending order of importance. Kalantar-zadeh et al found a significant relationship between CRP and DMS, close to our findings. [22] DMS is a modified SGA (subjective global assessment). In the study of Kuhlmann et al prescription of 45 kcal/kg/d and 1.5 g protein/kg/d improved SGA score in patients undergoing hemodia­lysis, similar to our study. [23] According to Morais et al study, comorbidity had significant corre­lation with SGA, similar to our findings. [24]

Anthropometric measurements (BMI, MAC, MAMC, TSF and FFM) were significantly lo­wer in our patients who received lower amount of energy and/or inflammation. However, we did not find a significant correlation between co-morbidity and these measurements. These observations coincide with the findings with other studies. [25],[26] Our findings were similar to the results of Kaizu study in which inflam­mation was associated with muscle wasting indices. [27] Up to our knowledge, no study com­pared the effect of mentioned factors on all the anthropometric parameters.

Regarding our results, changes in the albumin, creatinine, and transferrin concentration were shown to have significant correlations with both energy and protein intake. Significant co­rrelation was noted in some studies. Similar to our findings, some studies found a correlation between protein intake and serum albumin[28] and transferrin, [29] while others found no signi­ficant correlation between protein intake and biochemical indices, [30] Which may be due to higher protein intake.

In our study, co-morbidity did not correlate with any biochemical indices, while in two other studies, atherosclerotic patients showed lower level of biochemical parameters. [16],[31] Our findings differ from previous studies, probably due to small number of patients who suffered from co-morbid disease.

According to our findings, there was no sig­nificant relationship between inflammation and biochemical parameters. Similar to our study, Owen et al found no significant correlation between CRP and serum creatinine. [32] while dif­ferent from present study, Menon et al found a significant correlation between serum albumin and CRP. [10] The finding of poor correlation bet­ween inflammation and biochemical parame­ters in our study may be due to using statins in hyperlipidemic patients, which decrease CRP level. Moreover, CRP concentration changes over the time and repeating CRP measure­ments may be needed. None of the indepen­dent factors had significant correlation with the biochemical parameters in multiple regre­ssion models. However, poor protein intake had the strongest correlation with decline of albumin, transferring, and creatinine.

We concluded that the frequency of malnu­trition is high in our population. Poor protein intake has the strongest correlation with mal­nutrition in HD patients. The influence of poor protein intake on nutritional status of HD pa­tients is greater than inflammation, morbidities and decreased energy intake. Providing, enough protein may be an effective way in preventing malnutrition in these patients.

 
   References Top

1.Canada-USA (CANUSA) Peritoneal Dialysis Study Group. Adequacy of dialysis and nutrition in continuous peritoneal dialysis: association with clinical outcomes. J Am Soc Nephrol 1996;7:198-207.  Back to cited text no. 1  [PUBMED]  [FULLTEXT]  
2.Qureshi AR, Alvestrand A, Danielsson A, et al. Factors predicting malnutrition in hemodia­lysis patients: a cross-sectional study. Kidney Int 1998;53:773-82.  Back to cited text no. 2  [PUBMED]  [FULLTEXT]  
3.Duranti E, Imperiali P, Sasdelli M. Is hyper­tension a mortality risk factor in dialysis? Kidney Int Suppl 1996;55:S173-4.  Back to cited text no. 3  [PUBMED]    
4.Pifer TB, McCullough KP, Port FK, et al. Mor­tality risk in hemodialysis patients and changes in nutritional indicators: DOPPS. Kidney Int 2002;62:2238-45.  Back to cited text no. 4  [PUBMED]  [FULLTEXT]  
5.Jansen MA, Korevaar JC, Dekker FW, Jager KJ, Boeschoten EW, Krediet RT. Renal func­tion and nutritional status at the start of chronic dialysis treatment. J Am Soc Nephrol 2001;12: 157-63.  Back to cited text no. 5      
6.Avram MM, Fein PA, Bonomini L, et al. Pre­dictors of survival in continuous ambulatory peritoneal dialysis patients: a five-year pros­pective study. Perit Dial Int 1996;16:S190-4.  Back to cited text no. 6  [PUBMED]  [FULLTEXT]  
7.Ikizler TA, Greene JH, Wingard RL, Parker RA, Hakim RM. Spontaneous dietary protein intake during progression of chronic renal fai­lure. J Am Soc Nephrol 1995;6:1386-91.  Back to cited text no. 7  [PUBMED]  [FULLTEXT]  
8.Chazot C, Laurent G, Charra B, et al. Malnut­rition in long-term haemodialysis survivors. Nephrol Dial Transplant 2001;16:61-9  Back to cited text no. 8      
9.Kaizu Y, Ohkawa S, Odamaki M, et al. Asso­ciation between inflammatory mediators and muscle mass in long-term hemodialysis pa­tients. Am J Kidney Dis 2003;42:295-302.  Back to cited text no. 9  [PUBMED]  [FULLTEXT]  
10.Menon V, Wang X, Greene T, et al. Relation­ship between C-reactive protein, albumin, and cardiovascular disease in patients with chronic kidney disease. Am J Kidney Dis 2003;42:44­-52.  Back to cited text no. 10  [PUBMED]  [FULLTEXT]  
11.Laws RA, Tapsell LC, Kelly J. Nutritional status and its relationship to quality of life in a sample of chronic hemodialysis patients. J Ren Nutr 2000;10:139-47.  Back to cited text no. 11  [PUBMED]  [FULLTEXT]  
12.Pifer TB, McCullough KP, Port FK, et al. Mortality risk in hemodialysis patients and changes in nutritional indicators: DOPPS. Kidney Int 2002;62:2238-45.  Back to cited text no. 12  [PUBMED]  [FULLTEXT]  
13.Prichard SS. Comorbidities and their impact on outcome in patients with end-stage renal disease. Kidney Int 2000;57(suppl74):S100­04.  Back to cited text no. 13      
14.Danielski M, Ikizler TA, McMonagle E, et al. Linkage of hypoalbuminemia, inflammation, and oxidative stress in patients receiving main­tenance hemodialysis therapy. Am J Kidney Dis 2003;42:286-94.  Back to cited text no. 14  [PUBMED]  [FULLTEXT]  
15.Sezer S, Ozdemir FN, Arat Z, Turan M, Haberal M. Triad of malnutrition, inflammation, and atherosclerosis in hemodialysis patients. Nephron 2002;91:456-62.  Back to cited text no. 15  [PUBMED]  [FULLTEXT]  
16.Kalantar-Zadeh K, Stenvinkel P, Pillon L, Kopple JD. Inflammation and nutrition in renal insufficiency. Adv Ren Replace Ther 2003;10:155-69.  Back to cited text no. 16  [PUBMED]  [FULLTEXT]  
17.Panzetta G, Maschio G. Dietary problems of the dialysis patient. Blood 1985;3:63-74.  Back to cited text no. 17      
18.Valenzuela RG, Giffoni AG, Cuppari L, Can­ziani ME. Nutritional status in patients with chronic renal failure undergoing hemoddialysis in Amazonas. Rev Med Bras 2003;49:72-8.  Back to cited text no. 18      
19.Stojanovic M, Stojanovic D, Stefanovic V. The impact of malnutrition on mortality in patients on maintenance hemodialysis in Serbia. Artif Organs 2008;32(5):398-405.  Back to cited text no. 19      
20.Basaleem HO, Alwan SM, Ahmed AA, Al­Sakkaf KA. Assessment of the nutritional sta­tus of end-stage renal disease patients on main­tenance hemodialysis. Saudi J Kidney Dis Transpl 2004;15(4):455-62  Back to cited text no. 20      
21.Hartley GH, Gilmour ER, Goodship TH. The dietitian role in the management of malnutri­tion in chronic-renal-failure. J Hum Nutr 1995; 8(2):101-4.  Back to cited text no. 21      
22.Kalantar-Zadeh K, Kopple JD, Block G, Humphreys MH. A Malnutrition-Inflammation Score is correlated with morbidity and morta­lity in maintenance hemodialysis patients. Am J Kid Dis 2001;38(6):1251-63.  Back to cited text no. 22      
23.Kuhlmann M, Schmidt F, Kohler H. High Protein/Energy vs. Standard Protein/Energy nutritional regimen in the treatment of mal­nourished hemodialysis patients. Min Elect Met 1999;25:4-6.  Back to cited text no. 23      
24.Morais AA, Comarella AP, Pitanga KC, Faintuch J. Interest of conventional clinical, biochemical and bioimpedance measurements as indicators of mortality risk critical patients. Rev Hosp Clin Fac Med S Paulo 1998;53:176-80.  Back to cited text no. 24  [PUBMED]    
25.Duenhas MR, Draibe SA, Avesani CM, Sesso R, Cuppari L. Influence of renal function on spontaneous dietary intake and on nutritional status of chronic renal insufficiency patients. Eur J Clin Nutr 2003;57(11):1473-8.  Back to cited text no. 25      
26.Beddhu S, Kaysen GA, Yan G, et al. Asso­ciation of serum albumin and atherosclerosis in chronic hemodialysis patients. Am J Kid Dis 2002;40:721-7.  Back to cited text no. 26  [PUBMED]  [FULLTEXT]  
27.Kaizu Y, Ohkawa S, Odamaki M, Ikegaya N, et al. Association between inflammatory me­diators and muscle mass in long-term hemo­dialysis patients. Am J Kidney Dis 2003;42 (2):295-302.  Back to cited text no. 27      
28.Kopple JD, Massry SG, Druml W, Horl WH. High Protein/Energy vs. Standard Protein/ Energy nutritional regimen in the treatment of malnourished hemodialysis patients. Min Elect Met 1999;25:4-6.  Back to cited text no. 28      
29.Hadj-abdolkader M, Alphonse JC, Gueret H. Comparison of two practical attitudes of per­dialytic nutritional complementation. Kidney Int 1999;38:487-94.  Back to cited text no. 29      
30.Talemaitoga AS, Sanders BA, Hinton D, Lynn KL. Nutritional status of home hemodialysis patients. Int Med J 2008;19(4):303-9.  Back to cited text no. 30      
31.Suliman ME, Qureshi AR, Barany P, et al. Hyperhomocysteinemia, nutritional status, and cardiovascular disease in hemodialysis patients. Kidney Int 2000;57:1727-35.  Back to cited text no. 31      
32.Owen WF, Lowrie EG. C-reactive protein as an outcome predictor for maintenance hemo­dialysis patients. Kidney Int 1998;51(4):627-­36.  Back to cited text no. 32      

Top
Correspondence Address:
Soodeh Razeghi Jahromi
Shefa Neuroscience Research Center, Tehran
Iran
Login to access the Email id


PMID: 20814118

Rights and Permissions



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
    Similar in PUBMED
    Search Pubmed for
    Search in Google Scholar for
    Email Alert *
    Add to My List *
* Registration required (free)  
 


 
    Abstract
    Introduction
    Patients and Methods
    Statistical Analysis
    Results
    Discussion
    References
    Article Tables
 

 Article Access Statistics
    Viewed5214    
    Printed118    
    Emailed0    
    PDF Downloaded1380    
    Comments [Add]    

Recommend this journal