| Abstract|| |
Malnutrition (MN) in hemodialysis patients (HDP) is prevalent worldwide. However, data regarding the nutritional status among HDP living in Jeddah, Saudi Arabia, is lacking. The purpose of this study was to detect MN in HDP at the Jeddah Kidney Center, with an inexpensive nutritional assessment protocol consisting of anthropometric body mass index (BMI), triceps skin fold (TSF), mid-arm muscle circumference (MAMC) and biochemical (albumin) blood measurements and the seven-point subjective global assessment (SGA). A cross-sectional study assessed 269 HDP for MN through a questionnaire, SGA and anthropometric and biochemical measurements. Spearman's rank correlation coefficients were determined between SGA and anthropometric and biochemical measurements as well as the relative odds of MN. Statistical significance was P <0.05. These HDP were 48.7% moderately and 6.3% severely malnourished. Albumin, BMI, TSF and MAMC correlated positively with the seven-point SGA (r s = 0.16, P = 0.007; r s = 0.33, P <0.001; r s = 0.29, P <0.001; and r s = 0.34, P <0.001, respectively). Those HDP who were female (Odds ratio [OR] = 2.04, P = 0.036), older (≥55 years) (OR = 1.70, P = 0.087), uneducated (OR = 1.80, P = 0.072), with a lower BMI (<18 kg/m 2) (OR = 2.00, P = 0.077) and thinner TSF (OR = 1.45, P = 0.041) had a greater risk of MN. The high prevalence of MN was detected with an inexpensive protocol. Women with thinner TSF were more likely to be malnourished. The implementation of this protocol is warranted along with dietary education and counseling to decrease MN in HDP.
|How to cite this article:|
Alharbi K, Enrione EB. Malnutrition is prevalent among hemodialysis patients in Jeddah, Saudi Arabia. Saudi J Kidney Dis Transpl 2012;23:598-608
|How to cite this URL:|
Alharbi K, Enrione EB. Malnutrition is prevalent among hemodialysis patients in Jeddah, Saudi Arabia. Saudi J Kidney Dis Transpl [serial online] 2012 [cited 2023 Feb 8];23:598-608. Available from: https://www.sjkdt.org/text.asp?2012/23/3/598/95856
| Introduction|| |
Protein-energy wasting (PEW) is a relatively common problem among adult hemodialysis patients (HDP).  As the presence of PEW is one of the strongest predictors of morbidity and mortality in HDP, it is critical that dietitians accurately assess malnutrition (MN) in these patients. , This is especially true in Saudi Arabia, where in 2010, 11,437 patients were treated with hemodialysis and, based on an 7.9% average annual increase, projected to exceed 12,000 in 2011.  These HDP seem to have a tendency toward MN, although it is not well documented. ,, Appropriate and consistent assessment of MN in Saudi Arabian HDP is rare because of the inconsistent methods applied while assessing MN. Therefore, a method that could accurately and inexpensively detect MN is warranted.
Several methods have been adopted to evaluate nutritional status in HDP for MN, such as the subjective global assessment (SGA), anthropometric parameters, biochemical blood/urine values, bioelectrical impedance analysis and dual energy X-ray absorptiometry. These methods vary from study to study due to ease of application, expense, availability and practicality. While some techniques may work well in research situations, they are often not practical in clinical situations because they require expensive equipment or too much time. Therefore, this study offers a recommendation for detecting MN economically by combining methods (e.g., SGA, anthropometric measures and biochemical blood/urine values) in a clinical setting. ,,
The goal of the study was to determine, with an inexpensive nutritional assessment protocol, the prevalence of MN among HDP in a Saudi Arabian population at the Jeddah Kidney Center, located within the King Fahd General Hospital in Jeddah, Saudi Arabia. The protocol consisted of anthropometric measurements, a biochemical blood measurement and the seven-point SGA.
| Materials and Methods|| |
This was a cross-sectional study conducted to assess the nutritional status of HDP who had end-stage renal disease and were on regular hemodialysis at the Jeddah Kidney Center.
A convenience sample of 315 male and female patients was recruited for the study during May 2009. All those who participated met the following inclusion criteria: (1) age 18 years or older; (2) hemodialyzed for at least six months with continuing dialysis three-times a week; (3) not hospitalized; and (4) absence of enteral or parenteral feeding.
Assessment Instruments and Measures
Personal, health and diet questionnaire
A personal, health and diet questionnaire was developed to elicit general information about the patients. It consisted of 19 questions, ten of which were related to patient demographics, three regarding health and six pertaining to diet and fluid restrictions. Demographic parameters were sex, age, marital status, ownership of residence, residential location, nationality, education level, employment, income and number of people living in the same household. The questions pertaining to health status included the number of years the patient has lived with kidney disease, the number of years on hemodialysis and comorbid diseases. Lastly, each patient was asked if a dietitian or a physician had prescribed diet and/or fluid guidelines. To assess diet and fluid compliance, the validated Dialysis Diet and Fluid Non-Adherence questionnaire was administered.  The instrument includes four questions. The first question asks how many days the patient did not follow the diet guidelines in the past 14 days, and the patient responds with a number. In the second question, the digression is assessed on a five-point Likert scale (0 = no deviation, 1 = mild deviation, 2 = moderate deviation, 3 = severe deviation, 4 = very severe deviation). Similar questions are posed to the patient regarding fluid guidelines.
Seven-Point Subjective Global Assessment
The seven-point SGA has been indicated as a reliable and valid tool for the nutritional assessment of HDP. ,,,, It includes two major categories: history and physical examination. The history portion of the seven-point SGA is comprised of five sections: weight/weight change; dietary intake; gastrointestinal symptoms; functional capacity; and disease state/comorbidities as related to nutritional status. For weight/weight change, the patient's weight loss from the preceding six months was recorded along with the current weight. All information regarding weight for the SGA was acquired from the patient's medical record. Other information required for the SGA was obtained by interviewing the patient. To obtain dietary intake, the patient was asked to recall all foods and beverages consumed during the previous 24 h. Gastrointestinal symptoms such as nausea, vomiting and/or diarrhea were recorded from the patient's self report. The gastrointestinal symptoms were considered significant if most or all symptoms had persisted for at least two weeks. Short-term or intermittent symptoms were not considered significant. To assess physical functional status, patients were asked to describe their physical capabilities. Changes in physical function needed to be associated with nutritional status (e.g., anemia, low dietary intake) and have occurred within the past six months. The final part of the history addressed comorbid diseases related to nutrition (e.g., hypertension, diabetes).
The second major category of the seven-point SGA is the physical examination. This includes an evaluation of the patient for fat and muscle wasting and edema. The areas below the eye and around the triceps and biceps muscles were evaluated to determine subcutaneous fat loss. Muscle wasting was assessed by examining the temporalis muscle, prominence of the clavicles, the contour of the shoulders (rounded indicated well nourished; squared indicated MN), visibility of the scapula, interosseous muscle between the thumb and forefinger, and the gastrocnemius muscle. The area around the ankles was evaluated to determine edema. Weight change and edema were assessed in tandem to determine if fluid retention masks tissue wasting.
Each section of the seven-point SGA was rated on a scale from one to seven. On the basis of subjective consideration of all the scores from each category, an overall number was assigned to each patient. A six or seven rating indicated a very mild risk of MN and/or well nourished; a three, four or five rating indicated mild to moderate MN; and a one or two rating indicated severe MN. From those ratings, patients were then classified into one of three groups: 1 = well-nourished; 2 = moderate MN; and 3 = severe MN.
Anthropometric measurements Anthropometric parameters are reliable and valid measurements that indicate nutritional status in HDP. ,, Several anthropometric measurements were obtained. Pre- and post-dialysis weight, height, triceps skin-fold (TSF) and mid-arm circumference (MAC) were measured and, from these, the interdialytic weight gain (IWG), body mass index (BMI) and mid-arm muscle circumference (MAMC) were calculated.
The BMI was calculated using the patient's post-dialysis weight (kg) divided by the patient's height (cm) squared. Height was measured to the nearest 0.1 cm. Dry weight was measured to the nearest 0.1 kg with a calibrated Seca medical scale (Hamburg, Germany). To determine IWG, the patient's weight at the beginning of the hemodialysis session on the day of the data collection was subtracted from the patient's weight after the previous hemodialysis session.
MAC was measured with a flexible, non-stretchable measuring tape. The patient was asked to stand with his/her feet together, shoulders relaxed and arms hanging freely at the sides. The fistula free arm was located to avoid the possibility of an inaccurate measurement due to fluid retention in the arm with the fistula. The midpoint on the posterior aspect of the upper arm was established between the acromial and olecranon and marked with a pencil. The measuring tape was placed around the upper arm at midpoint and pulled snugly enough to ensure contact with the arm. The measurement was recorded to the nearest 1 cm. Three measurements of MAC were obtained and then the average was calculated.
TSF was measured with a body fat caliper (Lange Skinfold Calipers, Power System, Tennessee, USA). At the mid-point where the skin was marked, a fold of skin with subcutaneous adipose tissue was grasped gently with the thumb and forefinger. With the jaws of the caliper perpendicular to the length of the fold, they were closed around the skin-fold. The skin-fold thickness was measured to the nearest 1 mm. The measurement was repeated thrice and the average was calculated and converted to centimeters.
The MAMC was calculated from the MAC and the TSF by the following formula: MAMC (cm) = MAC (cm) - (3.1415 × TSF [cm]). 
Serum albumin was obtained, as several studies have demonstrated that albumin is a valid indicator of nutritional status in HDP. ,, According to the National Kidney Foundation (NKF), serum albumin equal to or greater than 4 g/dL is the outcome goal for HDP.  All albumin values were categorized into either optimal (≥4 g/dL) or sub-optimal (<4 g/dL).
Patients were asked to participate in the study when they came to the Jeddah Kidney Center for dialysis. The purpose of the study was explained to each patient and then the patient was given the choice to accept or decline to participate. If a patient expressed interest in participating, he/she was asked his/her age and the length of time on hemodialysis to ascertain whether the patient met the inclusion criteria. Those patients who did not meet the inclusion criteria were thanked for their time.
Data were collected in two phases: pre-dialysis and post-dialysis. During the pre-dialysis phase, the patient read and signed the consent form. However, if the patient was illiterate, the caregiver read the consent form to him/her and the patient made a mark or thumbprint on the consent form.
After obtaining consent, the patient was asked the personal, health and diet questionnaire. With the patient's permission, the patient's file was examined to acquire the necessary anthropometric and biochemical data such as height, pre-dialysis weight and post-dialysis dry weight from the previous dialysis treatment, as well as serum albumin. Lastly, a 24-h dietary recall was obtained from the patient and recorded on a food data sheet. The second phase of the data collection commenced after dialysis. The seven-point SGA was completed and the anthropometric measurements (post-dialysis dry weight, TSF and MAC) were taken. The anthropometric measurements were obtained after dialysis in order to eliminate edema from affecting the accuracy of the measurements.
| Statistical Analysis|| |
All data were analyzed with SPSS® (SPSS Inc., version 17, Chicago, IL, USA). Frequencies (n) and percentages (%) were determined for categorical variables and means and standard deviations (mean ± SD) were calculated for all continuous variables. Because the frequency of severely malnourished was very small, it was combined with moderately malnourished when compared with well nourished. Cross-tabulations with chi-square tests determined differences between the seven-point SGA (well nourished, moderately to severely malnourished) and the categorical variables of gender and age (<55 years and ≥55 years). T-tests compared the continuous variables (albumin, BMI, TSF, MAMC, IWG) by nutritional status, gender and age group. Spearman's rank correlation coefficients were calculated to determine bivariate relationships between results of the seven-point SGA and albumin, BMI, TSF, MAMC, IWG and diet and fluid deviation. The statistical significance for these tests was set at P <0.05. Logistic regression was performed to estimate the magnitude of association between the response variable of MN and the explanatory variables (albumin, BMI, TSF, MAMC, IWG, gender, age, education and hemodialysis vintage). Odds ratios were tested to estimate the likelihood risk of MN with the explanatory variables. Variables with P <0.1 were considered significant.
| Results|| |
Subject demographics Of the 315 patients asked to participate, 269 participated in the study. Thirty-one patients did not complete the study and 15 others declined to participate. The sample consisted of 162 males and 107 females, with the majority of patients being Saudi [Table 1]. Of the 269 who participated, 186 (69.1%) were younger than 55 years, while the remaining 83 (30.9%) were 55 years and older. Almost three-fourths (73.2%) of the patients were married. Nearly all the patients (94.4%) resided in Jeddah, and over half of the patients (51.7%) rented their homes. More than one-third of the patients were uneducated and only one-eighth of the patients had more than a high school education [Table 1]. The majority of the patients (80.3%) did not earn an income (retired, housewife, student, unemployed), and about half of the patients had monthly incomes of less than 3000 riyals [Table 1]. Over half of the patients (51.7%) lived with five or more people [Table 1]. More than half of the patients had kidney disease and had been on hemodialysis for five years or more [Table 1]. Most patients (>80%) had a chronic disease in addition to end stage renal disease, such as hypertension (54.5%, n = 147), diabetes (2.2%, n = 6) or hypertension and diabetes combined (17.4%, n = 47).
|Table 1: Demographic characteristics of hemodialysis patients at the Jeddah Kidney Center, Jeddah, Saudi Arabia (n = 269).|
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Diet and fluid prescription and deviation
A physician or a dietitian prescribed a diet to a majority of the patients (85.5%, n = 230). Also, a majority of the patients (82.5%, n = 222) received instructions for a fluid restriction from a physician or dietitian. Over half of the patients (58.7%) self-reported deviating from their diet restrictions. However, less than half (48.3%) self-reported deviating from their fluid restrictions.
Prevalence of malnutrition
More than half of the patients (54.3%) had some form of MN according to their SGA score, either mildly to moderately malnourished (48.7%, n = 131) or severely malnourished (5.6%, n = 15). Only 45.7% (n = 123) were well nourished. Albumin, BMI, TSF, MAMC and IWG were significantly lower in malnourished patients [Table 2].
|Table 2: Comparison of albumin, BMI, TSF, MAMC and IWG between well-nourished and malnourished hemodialysis patients at the Jeddah Kidney Center, Jeddah, Saudi Arabia (n = 269).|
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A significantly higher percentage of females (66.4%, n = 71) were malnourished when compared with males (46.3%, n = 75) (P = 0.001). Women had lower BMI, thicker skin folds and smaller MAMC when compared with men [Table 3]. These females also gained less interdialytic weight than the males. Albumin did not differ significantly between females and males [Table 3]. A significantly higher percentage of patients aged ≥55 years (66.3%, n = 55) were malnourished than those aged <55 years (48.9%, n = 91) (P = 0.008). Older patients (≥55 years) gained less interdialytic weight when compared with younger patients (<55 years) [Table 4]. A significant difference was not found for albumin, BMI, TSF and MAMC between older and younger patients [Table 4].
|Table 3: Comparison of albumin, BMI, TSF, MAMC and IWG between male and female hemodialysis patients at the Jeddah Kidney Center, Jeddah, Saudi Arabia (n = 269).|
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|Table 4: Comparison of albumin, BMI, TSF, MAMC, and IWG between hemodialysis patients aged <55 years old and ≥55 years old at Jeddah Kidney Center, Jeddah, Saudi Arabi (n = 269).|
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Albumin, BMI, TSF, MAMC and IWG correlated positively with the seven-point SGA (r s = 0.16, P = 0.007; r s = 0.33, P <0.001; r s = 0.29, P <0.001; r s = 0.34, P <0.001; and r s = 0.19, P = 0.002, respectively). However, diet and fluid deviation did not correlate with the seven-point SGA (r s = 0.03, P <0.615; and r s = -0.01, P = 0.925, respectively).
The Hosmer and Lemeshow goodness of fit test indicated that the data fit the model (χ2 = 9.8, df = 8, P = 0.28). The model prediction did not differ significantly from the observed, the model correctly predicted 70% of the cases. Odds ratios were significant for gender, TSF, age, education and BMI. The risk of MN was two-times greater for females than for males [Table 5]. When the TSF decreased by 1 mm, the patient was nearly one and a half times more likely to be malnourished. The older (≥55 years) and uneducated HDP were nearly twice as likely to be malnourished. The odds of MN for underweight HDP were two-times higher than for those HDP whose BMI was ≥18 kg/m 2.
|Table 5: Logistic regression analysis for variables predicting malnutrition in hemodialysis patients at the Jeddah Kidney Center, Jeddah, Saudi Arabia (n = 269).|
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| Discussion|| |
In Saudi Arabia, the prevalence of MN in HDP has been documented only in the capital city of Riyadh. ,, This study was the first to detect MN among HDP in Jeddah, Saudi Arabia, with an inexpensive nutritional assessment protocol consisting of the seven-point SGA, albumin and anthropometric measurements (BMI, TSF, MAMC and IWG). Notably, the majority of patients at the Jeddah Kidney Center were moderately to severely malnourished.
These patients were Saudi, young (<55 years), poor (<3000 riyals/month) with no employment and little or no education. The age of these HDP is reflective of the young (55 years or younger) population of Saudi Arabia and the Saudi Arabian patients who are on hemodialysis. , In 2010, the prevalence of hypertension (29.9%) and diabetes/hypertension (30.6%) was higher in Saudi HDP than diabetes (12%).  In this study, the largest proportion of patients were hypertensive and diabetic/hypertensive, with a smaller proportion diabetic, reflective of the prevalence of these diseases in the overall Saudi HDP population. As many of these HDP in Jeddah had comorbid diseases, this would contribute to their MN because HDP with comorbid diseases tend to be malnourished. , Therefore, it is important that MN is accurately diagnosed and treated in this young population. More patients seem to have deviated from their diet restrictions than from their fluid restrictions. However, the majority of patients did not adhere to either their diet or fluid restrictions. It has been reported that 38-80% of HDP fail to adhere to prescribed diets or fluid restrictions. ,,, The non-adherence may be attributed to a rigid and complex diet, which may affect a patient's food preferences and alter his/her lifestyle; the patient's perception of the usefulness of a therapeutic diet being outweighed by traditional beliefs and values; and a patient not asking questions about the diet or fluid restrictions because he/she was embarrassed or did not have enough knowledge to know what to ask. These factors may have contributed to the high number of patients not adhering to their diet and fluid restrictions in this study. Additionally, at the time of the study, the center did not employ a dietitian; therefore, consistent and frequent dietary education and counseling was unavailable to these patients, and this may have led to a lack of understanding about the significance of dietary and fluid restrictions, resulting in non-compliance. Over half (n = 146) the HDP in this sample were malnourished. Two Riyadh studies determined that HDP were malnourished with BMI, albumin and protein and energy intake; however the sample sizes were small (32 and 61 HDP), and a comprehensive assessment protocol was not developed and utilized to detect MN. , The most recent Riyadh study at the Prince Salman Center for Kidney Disease (PSCKD), Al-Saran et al identified only 32% of 200 HDP as malnourished with the original SGA, blood biochemical parameters and BMI.  The differences between the percent MN in the PSCKD and this study may be related to hemodialysis vintage. The patients at PSCKD were on dialysis for no more than 2.5 years, whereas the majority of patients at the Jeddah Kidney Center were on hemodialysis five years or more. Dialysis vintage has been indicative of a decrease in the nutritional status of patients. ,
The biochemical and anthropometric measures differed significantly between well nourished and malnourished patients, indicating all are necessary in determining the nutritional status of HDP. One single measure is not a comprehensive approach of indicating MN. A single assessment parameter does not identify different aspects of MN that include energy and protein intake, visceral and somatic protein status and muscle and fat mass. Dietary interview and diaries provide quantitative information concerning intake of protein, energy and other nutrients. Albumin levels may indicate visceral protein status in HDP. Evaluation of somatic protein can be performed through measuring the MAMC to measure muscle mass. BMI and TSF are generally assessed to indicate body fat mass.
In HDP, gender and age are related to nutritional status. Poor nutritional status in HDP varies between genders. ,,, In the present study, a higher percentage of females were malnourished. This may be due to the socio-economic status and life styles of this particular patient sample as the sample was not randomly selected. Although more HDP were young, a higher percentage of older HDP were malnourished. Studies have indicated that older HDP (≥55 years) tend to be malnourished. ,,, Albumin did not differ significantly between males and females or between age groups; however, for all groups, the serum albumin concentrations were <4 g/dL, which the NKF considers sub-optimal and predictive of mortality risk. 
MN is prevalent at the Jeddah Kidney Center and needs to be assessed and treated. Particular attention to the nutritional status of older HDP and female HDP is warranted to decrease the prevalence of MN.
Anthropometric measurements (BMI, TSF, MAMC and IWG) and albumin correlated significantly with the seven-point SGA, confirming that they are predictors of the nutritional status of HDP. As BMI, TSF, MAMC and albumin decreased, the HDP became malnourished. Several studies in both eastern and western cultures corroborate these findings. ,,,,,,,, Also, as IWG increased, the severity of MN decreased. This has been demonstrated in other studies, which found that the greater the IWG the better the nutritional status of HDP. ,, The results in the present study substantiate the importance of using SGA in conjunction with other nutritional assessment parameters to obtain a comprehensive representation of nutritional status.
Anthropometrics, age, gender and education were associated with the risk of MN. In Jeddah, those HDP who were female, older (≥55 years), uneducated, had a lower BMI and thinner TSF were at greater risk for MN, and a plan for dietary intervention needs to be implemented. As these risk factors may be predictors of MN, they need to be considered collectively when assessing the nutritional status of HDP.
This study was implemented in one dialysis center, which limited the number of patients and the socioeconomic diversity of the HDP; therefore, results cannot be generalized to other HDP in Saudi Arabia. The study population should be expanded to include HDP from other areas of Saudi Arabia, as well as public and private hospitals, to obtain a comprehensive understanding of the nutritional status of HDP in this country. Dietitians need to be hired and trained to implement this inexpensive nutritional assessment protocol and to provide nutrition education and counseling to these patients.
In summary, this nutrition assessment protocol is easy and quick to perform, inexpensive and reliable, which enables malnourished HDP to be identified and triaged for appropriate nutrition intervention. The nutritional status of HDP in Saudi Arabia needs more attention by permanent renal dietitians and regular periodic nutrition assessment, education and counseling.
It is clear that the prevalence of MN exists among Saudi Arabian HDP and needs to be assessed regularly.
| Acknowledgments|| |
This study was conducted at the Jeddah Kidney Center, Jeddah, with special permission from Dr. Faissal Shaheen, Director General of Saudi Center for Organ Transplantation (SCOT), Riyadh, and the Director, Jeddah Kidney Center (JKC), Jeddah. The authors are extremely indebted to Dr. Faissal Shaheen.
The authors are also grateful to Ms. Linda McCann, RD, CSR and Satellite Healthcare Inc., San Jose, CA, USA for the provision of extensive one-on-one, hands-on SGA training within the Satellite Dialysis centers and for sharing the techniques and tools that Satellite Registered Dietitians use in performing SGA. The authors would like to thank Paulette Johnson, PhD, for statistical consultation and analysis.
| References|| |
|1.||Dukkipati R, Kopple JD. Causes and prevention of protein-energy wasting in chronic kidney failure. Semin Nephrol 2009;29:39-49. |
|2.||de Mutsert R, Grootendorst DC, Boeschoten EW, et al. Subjective global assessment of nutritional status is strongly associated with mortality in chronic dialysis patients. Am J Clin Nutr 2009;89:787-93. |
|3.||Saudi Center for Orgran Transplantation. Annual Report 2010. Internet: Available from: https://www.scot.org.sa/en/images/stories/pdf/ annual%20report_2010_updated/index.html [Last accessed on 2011 June 12]. |
|4.||Alshatwi AA, Alshmary A, Al-Khalifa A. Nutritional assessment of hemodialysis patients. J Med Sci 2007;7:294-8. |
|5.||Alshatwi AA. A comparative study of nutritional parameters in hemodialysis patients. Bull Fac Agric, Cairo University 2007;58:105-11. |
|6.||Al-Saran KA, Elsayed SA, Molhem AJ, Al-Drees AS, Al-Zara HM. Nutritional assessment of patients in a large Saudi dialysis center. Saudi Med J 2009;30:179-84. |
|7.||National Kidney Foundation - Kidney Disease Outcome Quality Initiative Committee. Adult guidelines. Am J Kidney Dis 2000;35:s17-s104. |
|8.||Saxena S, Sharma RK. An update on methods for assessment of nutritional status in maintenance dialysis patients. Indian J Nephrol 2004;14:61-6. |
|9.||Steiber A, Kalantar-Zadeh K, Secker D, McCarthy M, Sehgal A, McCann L. Subjective global assessment in chronic kidney disease: a review. J Ren Nutr 2004;14:191-200. |
|10.||Vlaminck H, Maes B, Jacobs A, Reyntjens S, Evers G. The dialysis diet and fluid non-adherence questionnaire: validity testing of a self-report instrument for clinical practice. J Clin Nurs 2001;10:707-15. |
|11.||Campbell KL, Ash S, Bauer J, Davies P. Critical review of nutrition assessment tools to measure malnutrition in chronic kidney disease. Nutr & Diet 2007;64:23-303. |
|12.||Visser R, Dekker FW, Boeschoten EW, Stevens P, Krediet RT. Reliability of the 7-point global assessment scale in assessing nutritional status of dialysis patients. Adv Perit Dial 1999;15:222-5. |
|13.||Steiber A, Leon JB, Secker D, et al. Multicenter study of the validity and reliability of subjective global assessment in hemodialysis population. J Ren Nutr 2007;17:336-42. |
|14.||Gurreebun F, Hartley GH, Brown AL, Ward MC, Goodship TH. Nutritional screening in patients on hemodialysis: Is subjective global assessment an appropriate tool? J Ren Nutr 2007;17:114-7. |
|15.||Desbrow B, Bauer J, Blum C, Kandasamy A, McDonald A, Montgomery K. Assessment of nutritional status in hemodialysis patients using patient-generated subjective global assessment. J Ren Nutr 2005;15:211-6. |
|16.||Tayyem RF, Mrayyan MT. Malnutrition, anthropometric and biochemical abnormalities in end-stage renal disease patients. Saudi Med J 2007;28:1575-158. |
|17.||World Health Organization. Country Cooperation Strategy of WHO and Saudi Arabia 2006-2011. Available from: http://www.who.int/ countryfocus/cooperation_strategy/ccs_sau_en.p df [Last accessed on 2011 March 6]. |
|18.||Locatelli F, Fouque D, Heimburger O, et al. Nutritional status in dialysis patients: a European consensus. Nephrol Dial Transplant 2002; 17:563-72. |
|19.||Kalantar-Zadeh K, Ikizler TA, Block G, Avram MM, Kopple JD. Malnutrition-inflammation complex syndrome in dialysis patients: Causes and consequences. Am J Kidney Dis 2003;42: 864-81. |
|20.||Zrinyi M, Juhasz M, Balla J, et al. Dietary self-efficacy: determinant of compliance behaviors and biochemical outcomes in heamodialysis patients. Nephrol Dial Transplant 2003;18: 1869-73. |
|21.||Lee S, Molassiotis A. Dietary and fluid compliance in Chinese hemodialysis patients. Int J Nurs Stud 2002;39:695-704. |
|22.||Durose CL, Holdsworth M, Watson V, Przygrodzka F. Knowledge of dietary restrictions and the medical consequences of noncom-pliance by patients on hemodilaysis are not predictive of dietary compliance. J Am Diet Assoc 2004;104:35-41. |
|23.||Chertow GM, Johansen KL, Lew N, Lazarus JM, Lowrie EG. Vintage, nutritional status, and survival in hemodialysis patients. Kidney Int 2000;57:1176-81. |
|24.||Chazot C, Laurent G, Charra B, et al. Malnutrition in long-term haemodialysis survivors. Nephrol Dial Transplant 2000;116:61-9. |
|25.||Hwang JY, Cho1 JH, Lee YJ, Jang SP, Kim WY. Family history of chronic renal failure is associated with malnutrition in Korean hemo-dialysis patients. Nutr Res Pract 2009;3:247-52. |
|26.||Rutledge C, McMahon LP. Relationship between dialysis and nutritional adequacy in hemodialysis patients. Nephrol 2000;5:27-32. |
|27.||Stenvinkel P, Barany P, Chung SH, Lindholm B, Heimburger O. A comparative analysis of nutritional parameters as predictors of outcome in male and female ESRD patients. Nephrol Dial Transplant 2002;17:1266-74. |
|28.||Basaleem HO, Alwan SM, Ahmed AA, Al-Sakkaf KA. Assessment of the nutritional status of end-stage renal disease patients on maintenance hemodialysis. Saudi J Kidney Dis Transpl 2004;15:455-62. |
|29.||Chauveau P, Combe C, Laville M, et al. Factors influencing survival in hemodialysis patients aged older than 75 years: 2.5-year outcome study. Am J Kidney Dis 2001;37:997-1003. |
|30.||Merkus MP, Jager KJ, Dekker FW, de Haan RJ, Boeschoten EW, Krediet RT. Predictors of poor outcome in chronic dialysis patients: The Netherlands Cooperative Study on the Adequacy of Dialysis. Am J Kidney Dis 2000;35: 69-79. |
|31.||Abbas HN, Rabbani MA, Safdar N, Murtaza G, Maria Q, Ahamd A. Biochemical nutritional parameters and their impact on hemodialysis efficiency. Saudi J Kidney Dis Transpl 2009; 20:1105-9. |
|32.||Enia G, Sicuso C, Alati G, Zoccali C. Subjective global assessment of nutrition in dialysis patients. Nephrol Dial Transplant 1993;8: 1094-8. |
|33.||Quereshi AR, Alvestrand A, Danielsson A, et al. Factors predicting malnutrition in hemodialysis patients: a cross-sectional study. Kidney Int 1998;53:773-82. |
|34.||Morais AA, Silva MA, Faintuch J, et al. Correlation of nutritional status and food intake in hemodialysis patients. Clinics 2005;60:185-92. |
|35.||Afshar R, Sanavi S, Izadi-Khah A. Assessment of nutritional status in patients undergoing maintenance hemodialysis: a single-center study from Iran. Saudi J Kidney Dis Transpl 2007; 18:397-404. |
|36.||Tapiawala S, Vora H, Patel Z, Badve S, Shah B. Subjective global assessment of nutritional status of patients with chronic renal insufficiency and end stage renal disease on dialysis. J Assoc Physicians India 2006;54:923-6. |
|37.||López-Gómez JM, Villaverde M, Jofre R, Rodriguez-Benítez P, Pérez-García R. Inter-dialytic weight gain as a marker of blood pressure, nutrition, and survival in hemodialysis patients. Kidney Int 2005;93:S63-8. |
|38.||Sezer S, Ozdemir FN, Arat Z, Perim O, Turan M, Haberal M. The association of interdialytic weight gain with nutritional parameters and mortality risk in hemodialysis patients. Ren Fail 2002;24:37-48. |
|39.||Testa A, Beaud JM. The other side of the coin: Interdialytic weight gain as an index of good nutrition. Am J Kidney Dis1998;31:830-4. |
Evelyn B Enrione
Department of Dietetics and Nutrition, HLS - 450, Florida International University, Miami, FL 33199
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]