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| Year : 2010 | Volume
: 21
| Issue : 5 | Page : 846-851 |
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| Malnutrition predicting factors in hemodialysis patients |
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Soodeh Razeghi Jahromi1, Saeed Hosseini2, Effat Razeghi3, Ali pasha Meysamie4, Haleh Sadrzadeh2
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
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| Date of Web Publication | 31-Aug-2010 |
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 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 2020 Dec 4];21:846-51. Available from: https://www.sjkdt.org/text.asp?2010/21/5/846/68878 |
| Introduction | |  |
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 | | |
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 | | |
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 | | |
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.
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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.
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[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.
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 | Table 4 :Correlation between inflammation and co-morbidities, anthropometric and biochemical indices
of hemodialysis patients.
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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 | | |
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.
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Correspondence Address:
Soodeh Razeghi Jahromi
Shefa Neuroscience Research Center, Tehran
Iran
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PMID: 20814118 
[Table 1], [Table 2], [Table 3], [Table 4] |
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