1. Top of page
  2. Abstract
  6. Acknowledgements

Controversies exist with respect to the mortality of patients undergoing liver transplantation at the extremes of the body mass index (BMI). For pediatric liver transplantation, weight is usually the only factor considered in survival analysis. A review of the United Network for Organ Sharing database (1987-2007) revealed 9701 pediatric patients (<18 years old) who underwent primary liver transplantation. Patients were stratified into 5 BMI categories established by the World Health Organization according to their Z score, which was based on age, gender, and BMI: −3, −2, 0, +2, and +3. The survival rates in these 5 categories were compared with Kaplan-Meier survival curves and log-rank testing. Patients with thinness (Z score = −2) and severe thinness (Z score = −3) had significantly (P < 0.0001) lower survival at 1 year (84.4%) versus the survival (88.7%) of the normal and overweight groups (Z score = 0 and Z score = + 2, respectively). For patients with obesity (Z score = +3), there was no significant difference in survival early after transplantation, but their mortality gradually increased in the later years after transplantation. By 12 years after liver transplantation, the obese group had significantly (P = 0.04) lower survival (72%) than the normal and overweight groups (77%). In conclusion, liver transplantation holds increased risk for obese pediatric patients. Thin pediatric patients experience early mortality after liver transplantation, and obese pediatric patients experience late mortality after liver transplantation. Transplant management can be modified to optimize the care of these patients. Liver Transpl 16:1296-1302, 2010. © 2010 AASLD.

Childhood obesity is a serious public health problem worldwide. According to the World Health Organization, the prevalence of obesity has been increasing at an alarming rate. Approximately 22 million children less than 5 years old are overweight worldwide.1 In the United States, it is estimated that 17% of children between the ages of 2 and 19 years are overweight.2 Obesity has been shown to have a negative impact on perioperative morbidity and mortality for a range of surgical procedures.3-5

Interestingly, the most common cause of liver disease in children between the ages of 2 and 19 years in the United States is nonalcoholic fatty liver disease.6 With the growing incidence of childhood obesity and with nonalcoholic fatty liver disease being the leading cause of pediatric liver disease in the United States, the transplantation of obese children will become a major health problem. In adults, numerous studies have shown conflicting results for the impact of obesity on post–liver transplant outcomes.7-10 We have recently reported that obesity is a significant indicator of poor survival in adults after liver transplantation.3 We have also found that liver transplant recipients who are severely underweight are also at risk for poor survival.

Very little has been reported on the impact of the body mass index (BMI) on children and adolescents undergoing liver transplantation. Hanevold et al.11 reviewed the North American Pediatric Renal Transplant Cooperative Study database (1987-2002) and found that pretransplant obesity had a negative impact on children undergoing renal transplantation. The aim of our study was to assess the impact of pretransplant BMI on post–liver transplant patient survival for children (≤18 years old). We hypothesized that children who undergo liver transplantation at the extremes of BMI have poorer survival after liver transplantation than children with more moderate BMIs.


  1. Top of page
  2. Abstract
  6. Acknowledgements

After approval by the institutional review board of the University of Washington, we conducted a retrospective review of the United Network for Organ Sharing (UNOS) database to identify a historical cohort of pediatric patients (≤18 years old) who underwent primary liver transplantation. Our data analysis covered the period of 1987-2007. Data were analyzed to assess survival according to BMI at the time of transplantation. BMI is calculated by the division of a person's weight (kg) by the height squared (m2). Because the height of children is commonly measured in centimeters, an alternative calculation formula is used. For the calculation of pediatric BMI, the weight (kg) is divided by the height squared (cm2), and this result is converted to a Z score according to the World Health Organization classification.12 Patients are stratified into 5 categories that are based on their Z scores. The categories include severe thinness (Z score = −3), thinness (Z score = −2), normal weight (Z score = 0), overweight (Z score = +2), and obesity (Z score = +3). For our study, BMI data were obtained from the transplant recipient registration forms. Missing data or conflicting information (ie, confusion about pounds versus kilograms or centimeters versus inches) was corroborated with the transplant candidate registration form. Patients with no BMI or no follow-up form were excluded from our study.

Collected recipient factors included age, sex, UNOS region of transplant, era of transplantation (1987-1997 or 1998-2007), and causes of end-stage liver disease (autoimmune hepatitis, cholestasis, metabolic disease, cirrhosis, acute hepatic necrosis, tumor, and other). Factors concerning patient status at the time of transplantation were also collected; these included the bilirubin level (mg/dL), serum creatinine level (mg/dL), albumin level (g/dL), requirement for any form of life support, number of days waiting for transplantation, location of the patient at the time of transplantation (in or outside the hospital), and intensive care unit (ICU) status at the time of transplantation. Collected donor factors included the type of donor (living donor or deceased) and age. Collected posttransplant factors included patient survival, length of stay, retransplantation, and cause of death.

Statistical Analysis

Continuous variables were expressed as means and standard deviations, and categorical variables were expressed as proportions. The Student t test or nonparametric tests, as appropriate, were used for continuous variables, and the chi-square test was used for categorical variables. Kaplan-Meier analysis with log-rank testing was used for comparing survival between the various BMI categories. The Cox proportional hazards model was used to determine significant univariates and multivariates for predicting post–liver transplant mortality rates. A P value ≤ 0.05 was considered significant for all analyses. To account for confounders (race, ascites, and age) or effect modification, we computed the adjusted effect of BMI on mortality while we controlled for race, ascites, and age by regression analysis. Data were analyzed with JPM 8.0.1 statistical software (SAS Institute, Cary, NC).


  1. Top of page
  2. Abstract
  6. Acknowledgements

From 1987 to 2007, 9701 pediatric patients underwent liver transplantation in the United States. There were 1759 patients for whom BMI data were missing and who were subsequently excluded from our study. Table 1 lists recipient demographics and clinical and donor data. Our final study population, therefore, consisted of 7942 pediatric patients. The majority of the recipients were 5 years old or younger; 61.1% of the patients had a normal Z score. The most common reason for transplantation was liver disease secondary to a cholestatic disorder. At the time of transplantation, the majority of the patients had been waiting less than 3 months and were not hospitalized. The majority of the donors were between the ages of 1 and 17 years.

Table 1. Demographics and Clinical and Donor Factors of the Study Population (n = 7942)
 Age [n (%)]
  <1 year2339 (29.5)
  ≥1 year, <5 years2579 (32.5)
  ≥5 years, <10 years1110 (14)
  ≥10 years1914 (24.1)
 Male [n (%)]3793 (47.8)
 Z score [n (%)]
  −3542 (6.8)
  −2563 (7.1)
  04851 (61.1)
  +21332 (16.8)
  +3654 (8.2)
 Acute hepatic necrosis [n (%)]992 (12.5)
 Autoimmune [n (%)]270 (3.4)
 Cholestasis [n (%)]4250 (53.5)
 Cirrhosis [n (%)]442 (5.6)
 Metabolic disease [n (%)]969 (12.2)
 Other [n (%)]657 (8.3)
 Tumor, primary [n (%)]362 (4.6)
Recipient condition at transplant
 Bilirubin (mg/dL)11.7 ± 11.6
 Serum creatinine (mg/dL)0.51 ± 0.7
 Albumin (g/dL)3.2 ± 0.8
 Any form of life support [n (%)]736 (9.3)
 Waiting for transplant [n (%)]
  0-60 days4151 (52.3)
  61-160 days1881 (23.7)
  >160 days1910 (24)
 Not in hospital at time of transplant [n (%)]4417 (55.6)
 In hospital at time of transplant [n (%)]1447 (18.2)
 In ICU at time of transplant [n (%)]2078 (26.2)
Donor data at transplant
 Living [n (%)]968 (12.2)
 Age [n (%)]
  ≤1 year1589 (20)
  >1 year, ≤17 years3679 (46.4)
  >17 year, ≤40 years2097 (26.4)
  >40 years570 (7.2)

Survival Analysis

The Kaplan-Meier survival curves reveal a statistically significant decrease in 1-year survival for children with Z scores of −3 and −2 in comparison with patients with Z scores of 0 and +2 (Fig. 1). There is also a statistically significant decrease in long-term survival (starting 5 years after transplantation) for patients with a Z score of +3 versus patients with a Z score of 0 or +2 (Fig. 1). Because of these significant differences in survival among the Z scores, patients with a Z score of 0 or +2 were assigned to our control group because they had similar survival rates. Patients with a Z score of −2 or −3 were assigned to the thin group, and those with a Z score of +3 were assigned to the obese group. There were 6183 patients in our control group, 1105 patients in our thin group, and 654 patients in our obese group. The median follow-up for our cohort was 3.9 years [interquartile range (IQR) = 0.6-8.7 years], and the maximum follow-up was 20 years. The median follow-up for our control, thin, and obese patients was 3.9 (IQR = 0.7-8.4 years), 4 (IQR = 0.5-9.7 years), and 3.9 years (IQR = 0.6-8.9 years), respectively.

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Figure 1. Patient survival for all 3 Z score groups.

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Thin Versus Control

A comparison of the recipient, donor, and follow-up variables for the control and thin groups is illustrated in Table 2. In comparison with our control group, the thin patients were more likely to be less than 1 year old and have a cholestatic reason for end-stage liver disease. The thin patients were sicker, as demonstrated by their higher bilirubin levels, lower albumin levels, and presence in the hospital at the time of transplantation. The thin patients also had longer lengths of stay and were more likely to require retransplantation secondary to infectious complications. They were also more likely to die from cardiac or hemorrhagic complications (Table 3).

Table 2. Comparison of Recipient, Donor, and Follow-Up Variables Between Control and Thin Patients and Between Control and Obese Patients
VariableNormal/Overweight (n = 6183): Z = 0 to Z = +2Thin (n = 1105): Z = −2/Z = −3P*Obese (n = 654): Z = +3P*
  • *

    P ≤ 0.05 was significant.

 Age (%)
  <1 year25.8055.20<0.00120.200.002
  ≥1 year, <5 years34.6019<0.00134.701
  ≥5 years, <10 years13.2013.20122.80<0.001
  ≥10 years26.4012.60<0.00122.300.03
 Male (%)46.4050.900.00655.70<0.001
 Acute hepatic necrosis (%)12.309.900.0218.80<0.001
 Autoimmune (%)3.600.80<0.0015.700.01
 Cholestasis (%)53.2063.60<0.00139.30<0.001
 Cirrhosis (%)5.704.200.036.400.5
 Metabolic disease (%)12.1011.800.814.100.1
 Other (%)
 Tumor, primary (%)4.902.500.0045.200.7
Recipient condition at transplant
 Bilirubin (mg/dL)11.4 ± 11.613 ± 11.4<0.00112.3 ± 11.60.05
 Serum creatinine (mg/dL)0.5 ± 0.70.4 ± 0.5<0.0010.58 ± 0.80.002
 Albumin (g/dL)3.2 ± 0.83.1 ± 0.70.0073.2 ± 0.81
 Any form of life support (%)8.6010.100.0914.40<0.001
 Waiting for transplant (days)143 ± 267143 ± 3010.6147 ± 3020.001
 Not in hospital at time of transplant (%)57.3048.50<0.001520.01
 In hospital at time of transplant (%)17.7023.30<0.00114.400.03
 In ICU at time of transplant (%)2528.200.0233.60<0.001
Donor data at transplant
 Living (%)12.2014.400.048.700.01
 Age (%)
  ≤1 year18.9028.10<0.00117.500.4
  >1 year, ≤17 years47.1043.200.0244.700.2
  >17 years, ≤40 years26.60240.0728.900.2
  >40 years7.404.800.0018.900.2
Posttransplant data
 Length of stay after transplantation (days)28.6 ± 79.833.1 ± 53.5<0.00131.9 ± 81.40.4
 Required retransplantation (%)15.3015.500.916.400.5
  Vascular thrombosis31.4032.100.222.900.09
  Biliary tract complications86.200.740.2
  Chronic rejection31.8027.800.625.800.5
  Recurrent hepatitis4.
  Acute rejection6.705.8014.900.6
  Other causes8.2012.900.0610.700.5
Table 3. Causes of Death in Control, Thin, and Obese Patients
Cause of DeathNormal/Overweight (n = 6183): Z = 0 to Z = +2Thin (n = 1105): Z = −2/Z = −3P*Obese (n = 654): Z = +3P
Cardiac (%)0.952.30<0.0011.400.3
Graft failure (%)2.402.500.82.600.8
Respiratory (%)0.700.800.71.200.2
Renal failure (%)0.0600.90.201
Hemorrhagic (%)0.801.500.041.700.03
Infection (%)33.500.43.101
Cancer (%)0.800.8010.000.04
Intraoperative (%)0.300.500.60.500.7
Cerebrovascular disease (%)0.901.200.50.500.3
PTLD (%)0.700.800.70.600.9

Obese Versus Control

Table 2 shows a comparison of recipient, donor, and follow-up variables for the control and obese patients. In comparison with the controls, the obese patients were more likely to be between the ages of 5 and 10 years, be male, and have a diagnosis of autoimmune hepatitis or acute hepatic necrosis as a reason for end-stage liver disease. The obese patients were also sicker, as demonstrated by their higher bilirubin and serum creatinine levels and their requirement for life support at the time of transplantation. Obese patients were less likely to receive livers from living donors and waited longer on the deceased donor waiting list. In the posttransplant period, obese patients were more likely to have died from hemorrhagic complications (Table 3). After adjustments for ascites, obesity was still an independent predictor of poor long-term survival.

Long-Term Mortality

Table 4 reveals the results of our univariate and multivariate Cox proportional hazards analyses for mortality 5 years after liver transplantation. All factors from the univariate analysis were used in the multivariate analysis. No interactions were found in the multivariate analysis. The multivariate analysis showed that recipient factors for mortality 5 years after transplantation included age >10 years [relative risk (RR) = 2.5, P < 0.01], a Z score of +3 (RR = 1.5, P < 0.05), a diagnosis of autoimmune hepatitis (RR = 2.3, P < 0.01), a diagnosis of other (RR = 2.7, P < 0.01), and the log serum creatinine value (RR = 1.4, P = 0.02). The only donor factor at the time of transplantation that affected patient mortality was donor age >40 years (RR = 1.7, P < 0.04). We controlled for both the era of transplantation and the UNOS region in the multivariate analysis.

Table 4. Significant Factors for Long-Term Mortality After Liver Transplantation: Univariate and Multivariate Analyses (n = 3468)
VariablePatient Mortality After 5 Years
Univariate AnalysisMultivariate Analysis
  <1 year1.10.7  
  ≥1 year, <5 yearsReference   
  ≥5 years, <10 years1.90.02  
  ≥10 years5.3<0.012.5<0.01
 Z score
 Acute hepatic necrosis1.60.07  
 Metabolic disease0.90.6  
 Tumor, primary1.20.8  
Recipient condition at transplant
 Log bilirubin10.5  
 Log serum creatinine2<
 Log albumin0.50.06  
 Any form of life support1.30.3  
 Waiting for transplant
  0-60 days1.20.3  
  61-160 days1.40.1  
  >160 daysReference   
 Not in hospital at time of transplantReference   
 In hospital at time of transplant10.8  
 In ICU at time of transplant1.30.1  
Donor data at transplant
  ≤1 year0.4<0.0001  
  >1 year, ≤17 yearsReference   
  >17 years, ≤40 years1.30.2  
  >40 years2.70.00041.70.04


  1. Top of page
  2. Abstract
  6. Acknowledgements

Thus far, this is the largest study reporting on the impact of pretransplant BMI on post–liver transplant survival in the pediatric population. In the adult population, we have shown in previous studies that liver transplantation at the extremes of BMI has a negative impact on post–liver transplant survival.3 Interestingly, we have observed that the negative impact of liver transplantation on obese children presents in a delayed fashion, that is, in the long term (>5 years after transplantation) rather than in the short term.

The impact of pretransplant obesity on transplant patient and graft survival remains controversial. In the pediatric renal transplant population, Hanevold et al.11 showed that in comparison with nonobese children, obese children had a higher risk of death and increased graft loss secondary to graft thrombosis after renal transplantation. Mitsnefes et al.13 also showed in their retrospective study that pretransplant obesity had a negative impact on the glomerular filtration rate at 1 year, and they suggested that this might be due to preexisting hypertension or the development of hypertension after transplantation. The significant observation in our liver transplant study is that obesity had a slight impact on early patient survival but had a significantly negative impact on long-term patient survival (>5 years after transplantation). It has been shown that obesity-related complications are not apparent early on.14 This may be due to the time that it takes for the long-term complications of obesity [eg, diabetes, hypertension, and hyperlipidemia (all components of metabolic syndrome) and cancer] to develop.15-19 In our study, obese patients died from hemorrhagic complications. In our previous study on adult liver transplantation, significant causes of death in obese patients undergoing liver transplantation were hemorrhagic complications and cancer.3

With the improvements in long-term survival after liver transplantation and with children having a long life expectancy after transplantation, the development of posttransplant metabolic syndrome (PTMS) could contribute to the late morbidity and mortality. Obesity is one of the central factors in the development of metabolic syndrome.20 This leads to increased cardiovascular complications, the leading cause of long-term non–graft-related deaths.21 It has been reported in the literature that the prevalence of PTMS in adult patients after liver transplantation is 43% to 58%.19 This confers a substantial negative impact on long-term survival after transplantation. Obesity serves as a marker for early cardiovascular disease; if it is left uncorrected, it appears that after liver transplantation, obese children will develop the long-term devastating effects of obesity by the time at which they reach adulthood.22

Although immunosuppression has improved patient and allograft survival after solid organ transplantation, its long-term use contributes to and exacerbates the effects of PTMS.20 This leads to increased cardiovascular morbidity and mortality, which negatively affect long-term patient survival. The association of corticosteroids with diabetes, hypertension, and hyperlipidemia after transplantation has been well documented. Calcineurin and mammalian target of rapamycin inhibitors, as well as inhibitors of purine biosynthesis such as mycophenolate mofetil, are also associated with metabolic disorders.23-25 Further research is needed to determine the optimal immunosuppressive regimen (eg, a steroid-free regimen, calcineurin minimization, or immunosuppression withdrawal) for attenuating the effects of PTMS on long-term survival for obese pediatric patients undergoing liver transplantation.

There are significant health consequences of obesity in the pediatric population during adolescence and increased mortality during adulthood. To modify the impending effects of longstanding obesity, greater efforts in the liver transplant follow-up period to lower BMI and subsequently alter the effects of PTMS are crucial to the health of the child and soon-to-be adult. As suggested previously, a novel immunosuppressive regimen is one such strategy. Another potential option for obese children is referral to a multidisciplinary weight loss program, which may include medical management, surgical management, or both after liver transplantation. Ode et al.14 suggested that intense lifestyle modification, including dietary modification and exercise, and pharmacological therapy have significant beneficial effects on cardiovascular health in obese pediatric patients. These studies are based on a single center and small sample sizes, but they have shown significant improvements in BMI, blood pressure, serum lipid levels, and insulin resistance.

In actual practice, these modifications are very difficult to achieve and maintain. Another possible option for patients who have failed organized medical attempts at weight loss is bariatric surgery. A consensus article by Inge et al.22 discussed bariatric surgery as an option in the management of obese adolescents. This approach is often used in the obese adult population. This may seem a radical approach, but with the increasing rate of pediatric obesity in our society, we will have to look at other interventions for improving long-term survival. With a highly skilled and trained multidisciplinary adolescent bariatric team, which includes bariatric surgeons and pediatricians specializing in the care of obese adolescents, and with careful patient selection, gastric bypass after transplantation can offer a viable option for improving the long-term survival of obese pediatric patients.

The major strength of our study is that we used a national transplant database, which provided a large sample size. One of the challenges in using such a database is that, even though the data are collected in a prospective manner, the collected information is not necessarily tailored to the purposes of our particular research.

In summary, pretransplant malnutrition and obesity are predictors of poor post–liver transplant outcomes, but malnourished or obese patients do benefit from transplantation. Obesity in the pediatric population is an alarming issue. With early identification and appropriate and aggressive management, excellent long-term health outcomes and acceptable graft survival can be achieved. Donor organs are a scarce resource, and the goal of transplantation is to maximize long-term patient and graft survival. Pretransplant and posttransplant identification of patients who are malnourished or obese and optimization of their modifiable risk factors will help us to make the best use of this scarce resource and potentially maximize patient and graft survival.


  1. Top of page
  2. Abstract
  6. Acknowledgements

The authors thank Marilyn Carlson for her editorial assistance.


  1. Top of page
  2. Abstract
  6. Acknowledgements