Journal of Renal Nutrition
Volume 16, Issue 1 , Pages 27-35, January 2006

Nutritional Parameters and Mortality in Incident Hemodialysis Patients

  • Isabel Cristina de Araújo, MS

      Affiliations

    • Renal Research Dietitian, Nutrition Program, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Maria Ayako Kamimura, MS

      Affiliations

    • Renal Research Dietitian, Nutrition Program, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Sérgio Antônio Draibe, MD, PhD

      Affiliations

    • Associate Professor, Division of Nephrology, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Maria Eugênia Fernandes Canziani, MD, PhD

      Affiliations

    • Affiliate Professor, Division of Nephrology, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Silvia Regina Manfredi, MS

      Affiliations

    • Coordinator of the Nurse Group, Division of Nephrology, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Carla Maria Avesani, PhD

      Affiliations

    • Renal Research Dietitian, Nutrition Program, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Ricardo Sesso, MD, PhD

      Affiliations

    • Associate Professor, Division of Nephrology, Federal University of Sao Paulo, Sao Paulo, Brazil
    • ,
  • Lilian Cuppari, PhD

      Affiliations

    • Coordinator of the Renal Research Nutrition Group, Affiliate Professor, Division of Nephrology, Federal University of Sao Paulo, Sao Paulo, Brazil
    • Corresponding Author InformationAddress reprint requests to Lilian Cuppari, PhD, Federal University of Sao Paulo, Nutrition Program, Rua Pedro de Toledo, 282, Sao Paulo, Brazil.

Article Outline

Objective

To evaluate the impact of nutritional parameters at the time of initiation of hemodialysis (HD) on mortality.

Design

Retrospective study.

Setting

Dialysis Unit of the Federal University of Sao Paulo, Oswaldo Ramos Foundation.

Patients

Three hundred forty-four incident HD patients (60.5% male, 26% diabetic) with the first nutritional evaluation performed before completing 3 months of onset of HD were included.

Methods

The study consisted of baseline measurements of several nutritional parameters (triceps skinfold thickness [TSF], midarm muscle circumference [MAMC], body mass index [BMI], serum albumin, serum creatinine, and protein and energy intake assessed by 3-day food diary) and records of outcome (death) over a period of 10 years.

Results

Muscle and/or fat depletion was observed in 51% of the studied patients, according to the percent standard of MAMC and TSF, respectively. Presence of diabetes, age over 60 years, serum albumin < 3.5 g/dL, MAMC adequacy < 90%, protein intake < 1.0 g/kg/d, and energy intake < 25 kcal/kg/d were associated with worse survival. When patients were analyzed according to tertiles of dialysis vintage, BMI ≥ 25 (calculated as kg/m2) had a negative impact on survival only in the highest tertile (>2.45 years). Patients with BMI < 25 and MAMC adequacy ≥ 90% showed the best survival over the study period, and those with BMI ≥ 25 but MAMC adequacy < 90% had the worst survival (P = .004). In the multivariate survival analysis adjusting for diabetes, advanced age, and hypoalbuminemia, the reduced MAMC (P = .008) and the low energy intake (P = .03) were independent predictors of death in incident HD patients.

Conclusions

Reduced MAMC and low energy intake at the beginning of chronic dialysis are risk factors for mortality. A negative effect of high BMI on survival was associated with reduced MAMC and longer dialysis vintage.

 

THE MORTALITY RATE OF dialysis patients remains unacceptably high.1 Among several risk factors contributing to this condition, such as cardiovascular disease, advanced age, and diabetes, malnutrition has been shown to be strongly correlated with risk of death.2, 3 The prevalence of protein and energy depletion in patients undergoing long-term dialysis therapy is elevated varying from 29% to 65% among the series published.4, 5 Similarly, in patients initiating dialysis, a high prevalence of malnutrition (42% to 55%) is observed.6, 7, 8 Although numerous reports have associated malnutrition with risk of death in prevalent dialysis patients, the extent to which the poor nutritional markers at the time of initiation of dialysis (incident patients) can contribute to high mortality has been scarcely studied. Pupim et al9 have recently shown that patients initiating hemodialysis (HD) therapy with signs of malnutrition, suggested by low serum albumin and creatinine, were at increased risk for hospitalization. In addition, a study by Beddhu et al10 showed that regardless of body mass index (BMI) values, the reduced muscle mass, as evaluated by creatinine production, was related to worse survival in incident HD patients.

It is not known whether anthropometric parameters, such as triceps skinfold thickness (TSF) and midarm muscle circumference (MAMC), as well as dietary intake at the start of dialysis, are related to risk of death during the subsequent time on therapy. Additionally, studies regarding the time effect of BMI on survival of dialysis patients are limited. Thus, in the present study we aimed to evaluate the impact of those nutritional variables on the mortality of incident HD patients.

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Patients and Methods 

Patients 

This study was based on nutritional data collected from incident HD patients treated at the Dialysis Unit of the Federal University of Sao Paulo, Oswaldo Ramos Foundation, Sao Paulo, Brazil. In this setting, a prospective nutritional protocol is currently used to evaluate and monitor nutritional status and to provide adequate dietary advice for all patients admitted to our dialysis center. Anthropometric and food intake data are routinely collected by trained dietitians.

This retrospective study was conducted in a cohort of incident HD patients and consisted of baseline measurements of several nutritional parameters and records of outcome (death) over a period of 10 years, from January 1992 to December 2002. During this period, the database included initial nutritional data from 614 incident HD patients with age ≥ 18 years. Because the goal of the study was to evaluate the impact of nutritional parameters at the time of initiation of HD on mortality, only patients with the first nutritional evaluation performed before completing 3 months of HD therapy were included, a total of 344 incident HD patients. The interval between the first HD session and the nutritional evaluation was 1.8 ± 0.6 months, and the majority of the patients (80%) had their initial nutritional data collected before completing 2 months of HD. The study was approved by the Human Investigation Review Committee of the University.

Nutritional Data 

The anthropometric evaluation was performed after the end of the HD session (15 to 30 minutes). The evaluation included body weight, height, BMI, TSF, and MAMC. BMI was calculated as body weight divided by squared height. TSF was measured using the Lange caliper (Cambridge Instruments, Cambridge, MD). The measurement was performed on the opposite side of the vascular access. MAMC was calculated using the following equation: MAMC (cm) = (arm circumference − 0.314) × TSF. Percent standard of TSF and MAMC was obtained using the National Health and Nutrition Examination Survey percentile distribution tables adapted by Frisancho,11 and the cutoff point of 90% was used to determine the adequacy of those measurements. The Metropolitan Life Insurance tables adapted by Grant were used for estimating the ideal body weight.12

Dietary intake was evaluated using 3-day food diaries, 1 HD day and 2 nondialysis days, in which patients were instructed by dietitians to register all foods and the amounts consumed. Energy and protein intake were evaluated using a software developed at our University that contains a nutrient database from the United States Department of Agriculture (1963) as well as from foods typically consumed in Brazil. The cutoff values of 25 kcal/kg/d for energy and 1.0 g/kg/d for protein were adopted for statistical analysis based on median values obtained in our studied population.

Laboratory Data 

Database laboratory parameters consisted of samples collected for routine examinations. Blood samples were drawn before an HD session in a nonfasting state. Biochemical determinations included serum urea, serum creatinine (standard autoanalyzer), total cholesterol (enzymatic method), and serum albumin (bromcresol green). All measurements were performed at the specialized chemistry laboratory of the Oswaldo Ramos Foundation. Adequacy of dialysis (Kt/V) was determined according to Daugirdas.13

Statistical Analysis 

The outcome of interest in the present study was mortality. Continuous variables were expressed as mean ± standard deviation, with the comparisons between groups performed by the unpaired Student t test for normally distributed variables and the Mann-Whitney test for nonnormally distributed variables. Categorical variables were described using proportions and were analyzed by the χ2 test. Odds ratios and 95% confidence interval were calculated. The Kaplan-Meier method was used to calculate cumulative survival probabilities, and the difference between survival curves was assessed by the log rank test. Cox proportional hazard analysis was used to evaluate independent predictors of survival. The variables that significantly affected survival in the univariate analysis were subsequently tested in multivariate models using a forward stepwise procedure with a probability to entry of 0.05 and a probability to removal of 0.10. Hazard ratios and 95% confidence interval were calculated. All tests were performed using the statistical software True Epistat 5.0 (Tracy L. Gustaffson, Epistat Services, Richardson, TX). Differences were considered statistically significant when two-tailed P value was less than .05.

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Results 

A total of 344 patients on HD therapy, three times weekly for 4 hours, were studied. The causes of end-stage renal disease (ESRD) were hypertensive nephrosclerosis, 23%; diabetic nephropathy, 21.8%; undetermined, 21.8%; chronic glomerulonephritis, 15.7%; polycystic kidney disease, 6.7%; and others, 11%. Twenty-six percent of the patients had diabetes. Regarding HD access, 53.5% of the patients had a native arteriovenous fistula, 45.9% had a central venous catheter, and 0.6% had a vascular prosthesis. Forty-three percent of the patients had been previously on conservative treatment for chronic kidney disease. Demographic, laboratory, and nutritional data of the incident HD patients are presented in Table 1. The patients’ ages were 18 to 90 years old, and the majority of patients were male (60.2%). Fifty-nine percent (n = 204) of the patients had a BMI between 18.5 and 25, 35% (n = 120) were overweight or obese (BMI ≥ 25), and only 6% (n = 20) were underweight. Comparing male and female groups, serum creatinine and blood urea nitrogen were significantly lower in the female group. In contrast, total cholesterol and Kt/V were higher in this group. No difference was observed in serum albumin concentration. Although the percent TSF tended to be lower in the female group (P = .053), the percent MAMC was significantly lower in the male group. Dietary intake was similar between male and female groups, and both had energy and protein intake below the recommendation (30 to 35 kcal/kg/d for energy and 1.2 g/kg/d for protein according to the National Kidney Foundation-Dialysis Outcomes Quality Initiative Nutrition Guidelines).14

Table 1. Demographic, Laboratory, and Nutritional Characteristics of the Patients
ParametersTotal (n = 344)Male (n = 207)Female (n = 137)
Age (y)50.4±16.050.7±15.850.0±16.3
Serum creatinine (mg/dL)8.9±3.69.5±3.78.1±3.1⁎
Blood urea nitrogen (mg/dL)69.4±23.671.4±24.066.3±22.7⁎
Total cholesterol (mg/dL)189.6±50.7179.7±44.3205.5±56.4⁎
Serum albumin (g/dL)3.8±0.53.8±0.63.7±0.5
Kt/V1.17±0.311.08±0.261.28±0.34⁎
Body weight (kg)63.3±13.367.3±12.957.1±11.3⁎
Height (cm)162.2±9.8167.8±6.9153.8±7.2⁎
Body mass index23.9±4.323.8±4.224.1±4.5
MAMC (%)90.6±14.085.7±9.997.6±16.1⁎
TSF (%)98.1±52.6104.3±57.088.6±43.8
Energy intake (kcal/kg/d)26.2±8.626.7±8.925.4±8.2
Protein intake (g/kg/d)0.99±0.371.01±0.390.94±0.33

Note: Values are expressed as mean ± SD. To convert serum creatinine in mg/dL to μmol/L, multiply by 88.4; urea nitrogen in mg/dL to mmol/L, multiply by 0.357; total cholesterol in mg/dL to mmol/L, multiply by 0.02586; serum albumin in g/dL to g/L, multiply by 10.0

Abbreviations: MAMC, midarm muscle circumference; TSF, triceps skinfold thickness.

⁎ P<0.05

Patients’ Survival and Causes of Death 

At the end of the study period of 10 years, 105 patients (30.5%) had died, 64 patients (18%) had received kidney transplants, 98 patients (28.5%) had been transferred to other facilities or moved to peritoneal dialysis, and 79 patients (23%) were still on HD treatment. The median survival time of the patients was 4.5 years (95% confidence interval: 3.5 to 5.5 years), median dialysis vintage was 1.6 years (range: 2.2 months to 9.5 years). The main cause of death was cardiovascular disease (49.5%), followed by infection (29.5%), undetermined causes (13%), and others (7%). Mortality was 13.9% per patient-year at risk.

Comparison Between Survivors and Nonsurvivors 

All characteristics of the survivor and nonsurvivor patients are presented in Table 2. About 59% of the survivors and 62% of the nonsurvivors were male. Sex did not differ between the groups. However, the frequency of diabetes and age was significantly higher in the nonsurvivor group. Serum creatinine and albumin were significantly lower in the nonsurvivor group. Blood urea nitrogen and total cholesterol did not differ between survivors and nonsurvivors. There were also no differences regarding body weight, height, BMI, and percent TSF between the groups. However, the percent MAMC was significantly lower among nonsurvivors. In addition, the energy and protein intake were also significantly lower in this group.

Table 2. Comparison Between Survivor and Nonsurvivor Patients
ParameterSurvivors (n = 239)Nonsurvivors (n = 105)P
Sex (M/F)142/9765/40NS
Diabetes (n/%)49/2140/38.001
Age (y)47.6±15.956.9±14.2<.001
Serum creatinine (mg/dL)9.2±3.78.1±3.10.01
Blood urea nitrogen (mg/dL)70.9±24.665.8±20.5NS
Total cholesterol (mg/dL)190.0±4.8188.7±55.1NS
Serum albumin (g/dL)3.9±0.53.6±0.5.001
Kt/V1.18±0.311.13±0.32NS
Body mass index23.8±4.024.2±4.9NS
MAMC (%)92.1±14.187.3±13.2<.01
TSF (%)98.9±52.996.0±52.2NS
Energy intake (kcal/kg/d)27.4±8.923.5±7.4<.001
Protein intake (g/kg/d)1.01±0.380.92±0.34.02

Note: Values are expressed as mean ± SD. To convert serum creatinine in mg/dL to μmol/L, multiply by 88.4; urea nitrogen in mg/dL to mmol/L, multiply by 0.357; total cholesterol in mg/dL to mmol/L, multiply by 0.02586; serum albumin in g/dL to g/L, multiply by 10.0

Abbreviations: MAMC, midarm muscle circumference; NS, no significance; TSF, triceps skinfold thickness.

The influence of initial variables on mortality of the patients is shown in Table 3. Age over 60 years, presence of diabetes, and serum albumin lower than 3.5 g/dL were significantly associated with increased mortality. BMI lower than 25 and TSF < 90% did not influence mortality. In contrast, MAMC < 90% was associated with higher mortality. Finally, energy intake lower than 25 kcal/kg/d and protein intake lower than 1.0 g/kg/d were also related to worse survival.

Table 3. Influence of Baseline Variables on Mortality
ParametersOdds Ratio95% CIP
Sex0.900.55-1.48NS
Age (>60 y)0.460.27-0.77.002
Diabetes2.381.39-4.07.001
Kt/V (<1.2)1.250.70-2.26NS
Serum albumin(<3.5 g/dL)2.341.33-4.10.002
Body mass index (<25)0.760.46-1.25NS
MAMC (<90%)2.141.30-3.52.002
TSF (<90%)1.220.75-2.00NS
Energy intake(<25 kcal/kg/d)2.121.36-3.78.001
Protein intake(<1.0 g/kg/d)2.121.24-3.64.004

Note: To convert serum albumin in g/dL to g/L, multiply by 10.0.

Abbreviations: CI, confidence interval; MAMC, midarm muscle circumference; NS, no significance; TSF, triceps skinfold thickness.

Kaplan-Meier Survival Analysis 

Concerning the anthropometrics parameters, MAMC < 90% was associated with higher mortality (Fig. 1). Although a trend of lower survival was observed in patients with BMI ≥ 25, this association reached a borderline statistical significance (P = .07).

  • View full-size image.
  • Figure 1. 

    Survival curves for patients with midarm muscle circumference (MAMC) adequacy above and below 90%. In parentheses is the number of patients at risk at the beginning of each interval.

To evaluate the short-term and long-term effect of BMI on mortality, patients were analyzed according to tertiles of dialysis vintage: first tertile (<1.13 years) included 114 patients; second tertile (1.13 to 2.45 years), 115 patients; and third tertile (>2.45 years), 115 patients. There was no difference in survival curves comparing patient groups with BMI (calculated as kg/m2) < or ≥ 25, both on the first tertile (P = .62) and second tertile (P = .56) of dialysis vintage. However, as can be seen in Figure 2, in the third tertile of dialysis vintage, BMI ≥ 25 was significantly related to worse survival (P = .029). Additionally, to analyze the effect of BMI and muscle mass on mortality, patients were stratified according to specific values of these variables. Patients with a BMI < 25 were subdivided in groups according to MAMC < or ≥ 90%. Similarly, those patients with a BMI ≥ 25 were also classified according to MAMC < or ≥ 90%. As can be seen in Figure 3, the best survival was observed in the group of patients with BMI < 25 and MAMC ≥ 90%. Patients with a BMI ≥ 25 and MAMC < 90% had the worst survival.

  • View full-size image.
  • Figure 3. 

    Survival curves according to body mass index (BMI) and midarm muscle circumference (MAMC) adequacy. In parentheses is the number of patients at risk at the beginning of each interval. Group 1 versus 2 (P = .046), group 1 versus 3 (P = .006), group 1 versus 4 (P > .05), group 2 versus 3 (P < .001), group 2 versus 4 (P > .05), group 3 versus 4 (P = .012).

Energy intake lower than 25 kcal/kg/d and protein intake lower than 1.0 g/kg/d negatively influenced the survival, as shown in Figure 4.

Cox Proportional Hazard Analysis 

In the multivariate analysis percent MAMC, serum albumin lower than 3.5 g/dL, age over 60 years, energy intake, and presence of diabetes were the only significant and independent risk factors for mortality that remained in the final model (Table 4).

Table 4. Cox Proportional Hazards Analysis of Factors Predicting Mortality
ParametersHazard Risk95% CIP
MAMC (%)0.970.96-0.99.008
Serum albumin (<3.5 g/dL)1.591.02-2.46.04
Age (>60 y)1.871.22-2.87.004
Energy intake (kcal/kg/d)0.960.92-0.99.03
Diabetes1.931.23-3.04.004

Note: To convert serum albumin in g/dL to g/L, multiply by 10.0. MAMC (%) and energy intake were tested as continuous variables.

Abbreviations: CI, confidence interval; MAMC, midarm muscle circumference.

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Discussion 

The current study aimed to evaluate the impact of nutritional parameters at the time of initiation of HD on mortality. We observed that in addition to the well-recognized risk factors for mortality, such as diabetes, advanced age, and hypoalbuminemia, the reduced MAMC and the low energy intake were also independent predictors of death in incident HD patients.

The nutritional status of patients initiating dialysis therapy is poorly characterized. Studies with patients initiating peritoneal dialysis showed that 42% to 55% of the patients were malnourished according to the subjective global assessment.6, 7, 8 Accordingly, in chronic kidney disease patients close to the start of dialysis, a high prevalence of malnutrition has been observed.15, 16 In fact, with the decrease of renal function, a spontaneous decline in food intake and a subsequent reduction in nutritional indices have been previously reported in predialysis patients.17, 18, 19 In the present study, half of the incident HD patients had signs of muscle and/or fat depletion according to the adequacy of MAMC and TSF, respectively.

The negative impact of poor nutritional markers on clinical outcome is well established among prevalent HD patients.2, 3, 20 However, in incident HD patients this relationship has been scarcely investigated. A recent study by Pupim et al9 showed that patients initiating HD therapy with evidence of malnutrition, suggested by low serum albumin and creatinine, were at increased risk for hospitalization over the subsequent 12 months. Although morbidity was not analyzed in our study, we ascertained the association of low serum albumin and creatinine concentration with worse survival in incident HD patients. This finding is in agreement with that observed in prevalent HD patients.21 In patients initiating peritoneal dialysis, malnutrition assessed by subjective global assessment was related to a 2.7-fold risk of death, which increased 3.3 times when comorbidity was associated.8

Anthropometric measurements of muscle and fat mass are frequently used to indicate protein-energy nutritional status. Their relationships with mortality were first shown by Marckmann (1989), who found that reduced MAMC and TSF were closely associated with increased mortality in prevalent dialysis patients.3 However, a subsequent study with a larger sample of HD patients found no association between those anthropometric parameters and mortality.21 These conflicting findings could be explained by the differences in the studied sample size and length of follow up. In our study with a representative number of patients and monitoring of mortality over a period of 10 years, the MAMC measurement obtained in the beginning of HD therapy was an independent predictor of death.

Numerous studies use BMI as a nutritional marker to establish the association between mortality and nutritional status. In contrast to the reduced BMI, which is associated with an increased risk for morbidity and mortality,2, 23 the high BMI has been suggested to exert a protective effect on the survival of dialysis patients.24, 25, 26 Additionally, some investigators advocate that both extremely high and extremely low values of BMI are associated with an increased risk of death.27 In our study with incident HD patients, a trend of lower survival was observed in those patients with a higher BMI (≥25). When the effect of BMI on survival was evaluated according to dialysis vintage, a significant negative impact of high BMI was observed among patients with longer dialysis vintage. In fact, it has been postulated that elevated values of BMI could have different short-term and long-term effects on mortality. Alternatively, race may confound the effect of body size on mortality. For instance, the protective effect of BMI on survival is more evidenced among African Americans24 than in the Asian27 and European22, 28 population. Finally, it could be argued that the amount of muscle mass is relevant because the presence of greater muscle mass is known to correlate with long-term survival.29 In fact, a recent study that evaluated the influence of BMI on the mortality of incident HD patients by discriminating between muscle and fat mass found that the survival advantage conferred by high BMI was limited to those patients with a high muscle mass, as evaluated by creatinine production.10 In our study, patients with BMI < 25 and adequate MAMC showed the best survival. On the other hand, the group of patients with a higher BMI but low MAMC adequacy had the worst survival. Therefore, it seems reasonable to highlight the important influence of muscle mass at the start of HD therapy on mortality. However, prospective and long-term studies evaluating the association of BMI and lean body mass with clinical outcome in dialysis patients are still needed. Based on the available evidence, it is still not possible to definitely conclude whether interventions on BMI and lean body mass measurements could improve the survival of this population.

The available evidence suggests that the low protein and energy intake frequently observed among chronic kidney disease patients is associated with loss of muscle mass.30, 31 Accordingly, in the present study both protein and energy intake correlated with MAMC measurement (data not shown). Actually, few reports associating food consumption and clinical outcomes are available among the chronic kidney disease population. Some observational studies using nPNA (protein equivalent of total nitrogen appearance) have shown a relationship between low protein intake and high morbidity and mortality,31, 32 whereas others were unable to show such an association.33, 34 Data from the HEMO study have recently shown that low values of protein and energy intake assessed by 2-day food diary and also protein intake estimated by nPNA were associated with indices of comorbidities, especially in those patients older than 50 years.35 In our incident HD patients, low protein and energy intake obtained by 3-day food diary was associated with worse survival, and the latter was an independent predictor of death. To our knowledge, this is the first study evidencing an association between energy intake and mortality in HD patients. This finding is of concern because energy intake has been found to be markedly reduced in chronic HD population.35

The present study may be limited by the lack of data regarding the presence of comorbidities that could have affected the nutritional condition of these incident HD patients. However, regardless of the cause of reduced MAMC and energy intake, these parameters obtained in the beginning of HD therapy were independent predictors of mortality.

In conclusion, a high prevalence of protein and energy depletion was observed among patients at the start of HD therapy, which was closely associated with an increased risk of mortality. MAMC and energy intake in these patients were predictors of death during the 10-year study period. Therefore, interventions to ameliorate such nutritional parameters are of particular importance for chronic kidney disease patients at the initiation of HD treatment. It is possible that early dietary counseling in predialysis stages in association with clinical interventions might contribute to reducing the high mortality rate observed among HD patients. However, this assumption remains to be tested. Additionally, this study showed that the negative impact of a high BMI on survival was associated with reduced MAMC adequacy and longer dialysis vintage.

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PII: S1051-2276(05)00174-3

doi:10.1053/j.jrn.2005.10.003

Journal of Renal Nutrition
Volume 16, Issue 1 , Pages 27-35, January 2006

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