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Pediatric obesity has become a significant public health concern. The historical focus in pediatric liver transplant (LT) has been undernutrition, with limited knowledge regarding obesity. Therefore, we sought to determine the prevalence of obesity in pediatric LT, compare it to NHANES data and identify risk factors for obesity in pediatric LT. SPLIT, which collects pediatric LT data at 39 centers, was queried for subjects ages 2–18 years at follow up, LT between1995–2007, and with at least 1 BMI measured 1–5 years post-LT. Of 1706 subjects included, 44% had biliary atresia (47 % male, 58 % white, mean age LT 4.6 years). Of these subjects, 19% were obese at 1 year and 18% at 3 years, higher than in the general pediatric population reported by 2003–2004 NHANES, while 11% obesity at 5 years post-LT was similar to NHANES data. Using logistic regression, Hispanic ethnicity (OR=1.8, 95% CI: 1.19–2.23), steroid use at follow up (CI=1.48, 95% CI 1.23–1.77), overweight (OR 4.34, 95% CI 2.91–6.68) and obesity (OR 10.62, 95% CI 5.9–19.65) at LT independently predicted post-LT obesity. These findings suggest a need to broaden standard care to include obesity assessment and intervention in routine pre and post-transplant care.
Pediatric obesity, defined as a body mass index (BMI) greater than the 95% for age and gender, is an escalating public health crisis(1). National Health and Nutrition Examination Surveys (NHANES) data highlight alarming trends in pediatric obesity. NHANES data from 1971–1974 reported obesity rates of 5% in 2–5 year olds, 4% in 6–11 year olds and 6.1% in 12–19 year olds. The latest NHANES data from 2007–2008 reports that 10.4% of 2–5 year olds, 19.6 % of 6–11 year olds and 18.1% of 12–19 year olds are obese, with a 16.9% overall prevalence of pediatric obesity (2). Racial and gender disparities exist in the prevalence of obesity, with non-Hispanic black males, Hispanic American males and non-Hispanic black females most affected (2).
Obese patients are known to suffer from significant medical and psychosocial co-morbidities. These include diabetes, impaired glucose tolerance, hypertension, hyperlipidemia, non-alcoholic fatty liver disease, the metabolic syndrome, cardiovascular disease and depression. Significant weight gain and obesity after liver transplant in adults has been widely reported, ranging from 17–43% (3–7). There is a paucity of literature regarding obesity in the pediatric liver transplant population.
Therefore, the objectives of this study were to 1) determine the prevalence of obesity in the pediatric liver transplant population and compare it to the general pediatric population of the United States and 2) characterize and determine risk factors for obesity in pediatric liver transplant recipients.
Data were queried from the Studies of Pediatric Liver Transplantation (SPLIT) database, which prospectively collects data on children receiving liver transplants at 39 centers in the United States and Canada. The study population included patients who received a liver transplant between 1995–2007, were ages 2–18 years at follow up, and had BMI data available on at least one occasion between years 1 and 5 post liver transplant.
Overweight was defined as a BMI between the 85–95% for age and gender(1). Obesity was defined as a BMI ≥ 95% for age and gender (1). Throughout this study, the term obesity encompasses both obesity and severe obesity unless otherwise specified. Severe obesity was defined as a BMI ≥ 99% for age and gender, in keeping with recommendations by an expert committee convened by the American Medical Association, the Centers for Disease Control and Prevention and the Department of Health and Human Services (1, 8).
Chi-squared tests were performed to compare baseline categorical variables between obese and non-obese patients.
The generalized estimating equation (GEE) approach was used to perform logistic regression on longitudinal data to identify risk factors for obesity and to calculate odds ratios and 95% confidence intervals (CI) associated with risk factors. The initial multivariate model included risk factors with a p < 0.10 level in univariate analysis. Prior to including time invariant factors identified on univariate GEE analysis into the multivariate model, individual GEE analyses with repeated measures were performed to examine interactions between the factor and time to determine if an interaction effect should be included in the multivariate model. The final multivariate model was derived using a stepwise backward elimination procedure. Factors remaining significant at the p ≤ 0.05 level were considered statistically significant and entered the final model. For both the univariate and multivariate GEE analyses, Robust Standard Error Estimates were used to provide odds ratios, 95% confidence interval, and p values.
In order to compare SPLIT and NHANES obesity data, SPLIT follow up visits were divided into 3 groups based on calendar year of follow up, in keeping with NHANES data reports (1999–2000, 2001–2002 and 2003–2004). In cases of multiple visits by one subject, the time point reflecting the last collected BMI was used for data analysis. The proportion of obese individuals was then calculated for each group (1999–2000, 2001–2002 and 2003–2004) in parallel to published NHANES data (2).
Testing for differences in the proportion of obese subjects in the SPLIT and NHANES samples requires calculation of standard error (SE) under the assumption that the true proportion is the same in both groups. This would require calculation of a pooled SE combining information from both the SPLIT and NHANES samples. Data required to calculate the pooled SEs are not included in data from the NHANES cohort reported by Ogden et al (2). Therefore, a 95% confidence interval (CI) approach was used, which does not require assumptions about equality of proportions. The SE for the NHANES sample proportion is available, which can be combined with the SPLIT SE to determine the SE for the difference and calculate the 95% CI. This CI can be used to understand whether the two sample proportions are significantly different; if the value 0 is absent from the CI, then the data suggest that the true proportions are different.
All statistical analyses were performed using SAS for Windows, version 9.2 (SAS Institute Inc. Cary, NC).
Demographic data for the 1706 subjects included in the study are presented in Table 1. Figure 1 demonstrates the weight status of this cohort from 1 to 5 years post liver transplant. The majority of children are of healthy weight over the follow up period. However, at 1, 2, and 3 years post-transplant, 19.2% (of whom 10.5% were severely obese), 17.6% (of whom 9.1% were severely obese), and 17.5% (of whom 8.9% were severely obese) of subjects were obese, respectively. At 4 years post transplant, 12.7% of patients were obese (of whom 5.8% were severely obese) and at 5 years post-transplant, 10.9% of subjects were obese (of whom 4.6% were severely obese). Children were more likely to be obese 1 year post-transplant (OR 1.34, 95% CI: 1.09–1.65; p=0.005) and less likely to obese 5 years post-transplant (OR 0.63, 95%CI: 1.48–0.84; p=0.002) than at the time of transplant, with no differences noted 2 to 4 years post-transplant. Rejection in the first 3 months post-transplant, biliary and vascular complications, diabetes, and full time school attendance were similar among overweight/obese children and those of a healthy weight.
Figure 2 shows the prevalence of overweight and obesity in the post-transplant population over time compared to the general pediatric population of the United States from 2003–2004(2). At 1 and 3 years after liver transplant, patients were statistically more likely to be overweight or obese, as compared to the general pediatric population, At 5 years post-transplant, however, the degree of overweight and obesity was similar to the general pediatric population.
The prevalence of obesity in the liver transplant population was compared to NHANES data for three time periods (1999–2000, 2001–2002 and 2003–2004). According to NHANES data, 13.9% of children ages 2–19 years old were obese in 1999–2000, 15.4% in 2001–2002 and 17.1% in 2003–2004 (2, 9). As seen in Table 2, a similar proportion of the overall liver transplant patients and the general pediatric population were obese across all periods studied. However, there was a significantly increased prevalence of obesity in 2–5 year olds in transplant follow up compared to the general population across all periods studied. The percentage of obese blacks, Hispanics and whites were similar in the post-transplant and NHANES population.
A univariate analysis was conducted to identify risk factors for obesity after liver transplantation, at a significance level of ≤ 0.1. Identified factors included ALT, age less than 2 years or 2–5 years at transplant, Hispanic ethincity, Medicaid insurance, overweight, obese or severely obese weight status at the time of transplant, height deficit (height z score < −2) at transplant, steroid use at follow up, and elapsed time interval between transplant and follow up. Children who were 5 years old or younger when transplanted did not, however, have shorter lengths of follow up, p=NS. Non-significant factors included gender, primary diagnosis, year of transplant, primary immunosuppression (cyclosporine versus tacrolimus) at transplant, early rejection post transplant, donor organ type, and AST, total bilirubin and INR at time of BMI measurement. This study had insufficient power to determine the impact steroid use at transplant had on obesity as 93% of all subjects received steroids at transplant.
Significant risk factors identified on univariate analysis were entered into a stepwise logistic regression model to further understand predictors of obesity after liver transplant. Three time invariant factors were identified as potential risk factors for obesity on univariate analysis: age at transplant, ethnicity, and insurance status. No significant interactions was noted between these factors and time on GEE analyses with repeated measures, and therefore, an interaction term was not included in the multivariate analysis. The results of this multivariate analysis (Table 3) demonstrate that patients of Hispanic ethnicity, those using steroids at follow up, those 3 or fewer years after transplant, and those who were overweight or obese at the time of transplant are at increased risk of post-transplant obesity.
A subgroup analysis was conducted on subjects who were obese 3 and/or 5 yeas post-transplant, as these subjects were unlikely to be affected by post-operative factors and were judged by the authors to be at increased risk for persistent obesity. Follow up BMI data was available at 3 and/or 5 years post-transplant for 564 patients, 117 (20.7%) of whom were obese 3 and/or 5 years after transplant, These patients were predominantly female (52%), white (56%) and transplanted for biliary atresia (61%), primarily before 2001 (79%). Triglycerides were available for 475 patients (84%) at 3 years post transplant. The mean triglycerides were as follows: 77 ± 12 mg/dL in 12 underweight patients; 82 ± 3 mg/dL in 287 healthy weight patients; 81 ± 4 mg/dL in 100 overweight patients; 105 ± 20 mg/dL in 40 obese patients; 88 ± 7 mg/dL in 36 morbidly obese patients (p=NS). Cholesterol values were available for 496 patients (88%) at 3 years post transplant. The mean cholesterol values were as follows: 108 ± 12 mg/dL in 12 underweight patients; 132 ± 2 mg/dL in 301 healthy weight patients; 134 ± 4 mg/dL in 105 overweight patients; 127 ± 6 mg/dL in 40 obese patients; 134 ± 4 mg/dL in 38 morbidly obese patients (p=NS).
A univariate analysis was conducted to identify risk factors for obesity at 3 and/or 5 years after liver transplant, at a significance of p ≤ 0.1. Identified factors included Hispanic ethnicity, metabolic disease requiring transplant, and obesity or severe obesity at transplant. Non-significant risk factors for chronic obesity included age at transplant, gender, choice of primary immunosuppression, insurance coverage, year of transplant, steroid use at the time of transplant or at follow up, early rejection post transplant, height deficit (height z score <−2) at transplant, and AST, ALT, INR and total bilirubin at time of BMI measurement.
The risk factors identified on univariate analysis were entered into a stepwise logistic regression model to further understand predictors of obesity 3 and/or 5 years after liver transplant. The results of this multivariate analysis (Table 3) show that Hispanic patients and those who are obese or morbidly obese at transplant are at increased risk of obesity 3 and/or 5 years after liver transplant.
We have shown in a large, nationally representative cohort of pediatric liver transplant recipients that the prevalence of obesity after transplant is extremely high. In the first year after liver transplant, 19.2% of pediatric liver transplant recipients were obese. Three years after transplant, 17.5% of subjects were obese, and 5 years post transplant 10.9% of subjects remained obese. Surprisingly, we report a higher prevalence of obesity among post-liver transplant patients who are 2–5 years old as compared to a cohort of similar age among the general pediatric population of the United States. The prevalence of obesity after liver transplant in children 6–19 years old, however, is similar to a comparable age group in the general pediatric population. Importantly, the prevalence of obesity in children who are 5 years post-transplant, a sufficient duration after transplant to minimize the impact of factors such as post-transplant medications and activity, is similar to the general pediatric population. Therefore, these findings reveal a disturbing trend in pediatric obesity in a special pediatric population typically perceived as underweight.
Obesity in adult liver transplant recipients has been reported in 17–43% of patients, depending on the definition of obesity used and the duration from transplant captured (3–7). This study illustrates that obesity after pediatric liver transplant, though less prevalent than in adults, is remarkably common. High recipient BMI at the time of transplant influences post-transplant obesity in adults (3, 4, 10). Similarly, in this large pediatric cohort, we have demonstrated that the most prominent predictor of obesity after liver transplant was body habitus at the time of transplant. Liver transplant recipients who were obese were 10 times as likely, and those who were severely obese were 14 times more likely to be obese after transplant than children who were of healthy weight going into transplant. SPLIT does not, however, collect data on pre-transplant medical therapies, such as steroid use, which have the potential to impact pre-transplant BMI. It is also possible that some of these children were misclassified as obese at the time of transplant due to the presence of ascites or anasarca. Unfortunately, SPLIT does not collect data on ascites or anasarca at transplant, nor does it collect anthropometric data such as triceps skin fold or mid-arm circumference, which might allow insight into this potential problem. Clinically, the majority of children at risk of such misclassification are infants or toddlers, and age at transplant (including less than 2 years) was not found to be predictive of obesity. Therefore, body habitus at the time of transplant remains a crucial risk factor for post-liver transplant obesity. In addition, these findings highlight the opportunity for primary care and sub-specialty providers to collaboratively improve the post-transplant health of pediatric patients by focusing on pre-transplant weight optimization when possible.
Conflicting data exist regarding the impact of calcineurin inhibitor choice on obesity in adult transplant recipients(3, 4, 10, 11), (12). We did not find that choice of calcineurin inhibitor impacted the presence of post-transplant obesity in pediatric liver transplant recipients. Both steroid use at the time of transplant and cumulative prednisone dose have also been shown to impact obesity in adult liver transplant recipients (3, 4, 10). The nearly universal use of steroids at transplant in this population precluded our ability to assess their impact on obesity. The SPLIT database also does not capture data on cumulative steroid dose immediately after transplant. Children who were 3 or less years from transplant, however, were at increased risk for obesity, suggesting a potential role for steroid related weight gain. In addition, the use of steroids in the post-transplant period was noted to be a risk factor for obesity. Therefore, particularly in overweight or obese patients, transplant teams should consider prioritizing a rapid wean of steroids into therapeutic paradigms. Further investigation is necessary to determine optimal immunosuppressive regimens for overweight and obese pediatric patients in the post-transplant period, including steroid free protocols.
In this study, Hispanic ethnicity was also a significant risk factor for post-transplant obesity. This parallels racial trends in obesity seen in 2003–2004 NHANES data, in which 19.2% of Hispanics were obese compared to 16.3% of Caucasians (2). In addition to ethnic disparities, geographic disparities in pediatric obesity exist, with the highest rates seen in the southeastern United States (13). Although SPLIT does not collect data on the geographic area from which patients originate, this too may be an important risk factor. Recognition of these demographic risk factors may allow primary care providers and transplant teams to collectively focus intensive nutritional and exercise counseling into the routine care of high risk groups. In addition, high risk demographic groups may particularly benefit from steroid minimization.
Adults with obesity after transplant are at increased risk for the long term complications of cardiovascular disease, type 2 diabetes, and the metabolic syndrome. In addition, they may have lower overall survival after transplant (14). Children who are obese prior to transplant are reported to have decreased long term survival compared to normal weight or underweight children (15). Our study shows that children who are overweight or obese at transplant are quite likely to remain so after transplant. As such, it is possible that decreased long term survival in obese patients may be related to obesity related co-morbidities. Transplant teams and primary care providers together must remain cognizant of the long term cardiovascular and metabolic risks in these overweight and obese patients (1, 16) We suggest incorporating screening of overweight and obese children for type 2 diabetes mellitus, hypertension and hyperlipidemia into routine transplant follow up as recommended in the 2007 summary report of the Expert Committee on Prevention, Assessment, and Treatment of Child and Adolescent Overweight and Obesity (1) (17), (18). Such screening may be best facilitated by a partnership between primary care providers and transplant teams. Unfortunately, the SPLIT study lacks robust data on these obesity related co-morbidities. Systematic study of these parameters in the future may enhance our ability to understand the impact these potential risk factors have on post-transplant outcomes.
The prevalence of obesity after pediatric liver transplant is high and similar to the general pediatric population. Obesity at the time of liver transplant, a potentially modifiable factor, confers a high risk of post-transplant obesity. These findings suggest a need to broaden standard care to include obesity assessment and intervention in routine pre and post-transplant care. Pediatric transplant teams are accustomed to the malnourished state that is commonplace in many children listed for liver transplant. As such, well accepted treatment algorithms exist to improve nutritional health and BMI in undernourished patients. Our study demonstrates the critical nature of focused attention on the nutritional status of children who are overweight or obese prior to transplant as well. A carefully devised weight loss program, with interventions by both nutritionists and exercise therapists may stimulate pre-transplant weight loss in a rigorous and safe manner. In addition, families should be educated and empowered to make good nutritional choices with their children and emphasize active lifestyles, even as they move forward with transplant.
This work was sponsored by a grant from the NIH U01 DK061693.