In the year 2000, Wong et al.1 published a landmark study determining that mortality risk in chronic kidney disease (CKD) is associated with body mass index (BMI) in a U-shaped curve. Additionally, they reported that for each standard deviation score (SDS) of negative one below the average height of pediatric norms, mortality risk increased by 14%. Poor height velocity (rate of growth) was similarly associated.
Since this time, knowledge of anthropometry and its complexities have moved beyond those simple associations. Growth in pediatric kidney disease is complicated by changes in hormonal milieu, physical activity changes, adipose tissue and lean mass alterations, impaired appetite, uremia and many other factors.2-5
Unique concerns such as disease-related linear growth impairment, complications determining euvolemic or “dry” weight, and skewed estimations of malnutrition or obesity add to anthropometric challenges.2,5
Close anthropometric measurement is especially important in the youngest children with CKD or end stage renal disease (ESRD) as they are the most vulnerable to poor intake, and negative cognitive and final stature outcomes may occur when growth is poor in the early years.2,3,5
It is well established that CKD impairs linear growth. Optimizing nutritional status is an important first step in treating growth delays.2,4,5 The insulin-like-growth-factor-I (IGF-I)- growth hormone axis is altered partially due to impaired binding protein excretion. Growth hormone, which stimulates IGF-I production, can be given via injection and has been shown to substantially improve growth. Improvement of kidney function post-transplant often improves growth, however, growth hormone may remain necessary for those who do not improve or who were substantially stunted prior.4 Malnutrition or protein energy wasting (PEW) and untreated acidosis can impair growth as well.2,5,6
Specific clinical tools may aid in growth assessment. For example, mid-parental height is helpful to determine the genetic potential of the child with CKD.2,4,5 Also, growth charts for some concurrent co-morbid conditions may aid in comparing “apples to apples” when considering linear potential.2,5 Lastly, knowing best surrogate measures for height for children who cannot stand well can help provide accuracy in this population for which height is such an important measurement. 5,7-12
Weight, a simple determination in most populations, is not as simple in CKD, and, especially dialysis.
Especially young children with non-glomerular diseases (congenital conditions) such as renal dysplasia often have great sodium and fluid losses, which, without treatment, can cause these children to be below euvolemic weight.
Additionally, as urine output declines, children with a variety of original renal conditions can retain fluid.2,5,13 Excess thirst, common with the “dry mouth” that accompanies renal disease, excess sodium intake, inadequate dialysis and poor analysis of true “dry” weight can all lead to volume overload.
Knowing blood pressure norms for age height and gender is important for determining dry weight, as well as physical, dietary and biochemical assessment.2,5
BMI and Body Composition:
In 2016, Ku et al.14 reaffirmed the original work by Wong1, also reporting that this U-shaped curve applied to likelihood of receiving a renal transplant. Historically seen as a disease of small size, the anthropometric picture of pediatric CKD is changing. Obesity and overweight rates in North America are similar to the general population.5 As obesity and overweight are epidemic in “western” countries, this trend is not necessarily true of other parts of the world.15
Interestingly, children with CKD tend to have weights that are comparable to healthy norms. Short stature often contributes to BMI’s that are consistent with overweight and obesity.5 However, over-treatment of obesity may lead to nutritional inadequacy.2
BMI is recommended by the KDOQI pediatric nutrition guidelines and the Pediatric Renal Nutrition Taskforce (PRNT) assessment clinical practice recommendations for assessing weight to height or length ratio.2,5 However, large studies have determined that children with CKD tend to have high adiposity compared to lean mass, worsening as CKD advances. Central adiposity is common.5,16,17
BMI does not capture information about body composition. Unfortunately, the number of children with CKD meeting physical activity recommendations is 13%, half of the number of healthy children, and 98% exceed recommendations for screen time. Further, poor muscle mass is seen even in those who are physically active and rates of adequate physical activity decline as individuals’ progress toward ESRD.
Unfortunately, little improvement is seen post-transplant in many of these children.18 Additionally, PEW is present in 7-20% of children with non-ESRD CKD and overfeeding these individuals may lead to obesity, making correction a tedious process. 5,19
Tools such as subjective global nutritional assessment (SGNA), which has been validated in the general pediatric population, has often proved useful in CKD.20 Further studies and pediatric renal specific tools are needed.
Emerging data for mid-upper-arm circumference (MUAC) has promise for nutritional and anthropometric trending in pediatric CKD and dialysis.5,21,22 Improved determination of adiposity versus lean tissue, protein-energy wasting, and interventions to improve growth outcomes are needed in this field.
For further discussion of the anthropometric challenges in children with CKD, please watch the Paediatric Renal Nutrition Taskforce webinar titled "Assessment of Nutritional Status in Children with Kidney Diseases".
1. Wong CS, Gipson DS, Gillen DL, et al. Anthropometric measures and risk of death in children with end-stage renal disease. Am J Kidney Dis. 2000;36:811-19.
2. National Kidney Foundation. KDOQI Clinical Practice Guideline for Nutrition in Children with CKD: 2008 update. Am J Kidney Dis. 2009;53(suppl 2):S1-S124.
3. Rees L, Jones H. Nutritional management and growth in children with chronic kidney disease. Pediatr Nephrol. 2013;28:527-36.
4. Mahan JD, Warady BA. Assessment and treatment of short stature in pediatric patients with chronic kidney disease: a consensus statement. Pediatr Nephrol. 2006;917-30.
5.Nelms CL, Shaw V, Greenbaum LA, et al. Assessment of nutritional status in children with kidney diseases-clinical practice recommendations from the Pediatric Renal Nutrition Taskforce. Pediatr Nephrol. 2021;36(4):995-1010.
6. Mak, RH. Cachexia in children with chronic kidney disease: challenges in diagnosis and treatment. Curr Opin Support Palliat Care. 2016;10:293-7.
7. Yabanci N, Kilic S, Simsek II. The relationship between height and arm span, mid-upper arm and waist circumference in children. Ann Hum Biol. 2010;37(1):70-5.
8. Monyeki KD, Sekhotha MM. The relationship between height and arm span, mid-upper arm and waist circumferences and sum of four skinfolds in Ellisras rural children aged 8-18 years. Public Health Nutr. 2015;19(7):1195-99.
9. Forman MR, Zhu Y, Hernandez LM et al. Arm span and ulnar length are reliable and accurate estimates of recumbent length and height in a multiethinic population of infants and children under 6 years of age. J Nutr. 2014;144:1480-7.
10. Bell KL, Davies PSW. Prediction of height from knee height in children with cerebral palsy and non-disabled children. Ann Hum Biol. 2006;33(4):493-9.
11. Haapala H, Peterson MD, Daunter A, Hurvitz EA. Agreement between actual height and estimated height using segmental limb lengths for individuals with cerebral palsy. Am J Phys Rehabil. 2016;94(7):539-46.
12. Duyar I, Pelin C. Body height estimation based on tibia length in different stature groups. Am J Phys Anthropol. 2003;122:23-27.
13. Gunal AI. How to determine ‘dry weight’? Kidney Int. 2013;3(suppl):377-9.
14. Ku E, Glidden DV, Hsu C, Portale AA, Grimes B, Johansen KL. Association of body mass index with patient-centered outcomes in children with ESRD. J Am Soc Nephrol. 2016;27:551-8.
15. Yilmaz D, Sonmez F, Karakas S et al. Evaluation of nutritional status in children during predialysis, or treated by peritoneal dialysis or hemodialysis. J Trop Pediatr. 2016;62:178-84.
16. Rashid R, Neill E, Smith W, et al. Body composition and nutritional intake in children with chronic kidney disease. Pediatr Nephrol. 2006;21:1730-8.
17. Foster BJ, Kalkwarf HJ, Shults J et al. Association of chronic kidney disease with muscle deficits in children. J Am Soc Nephrol. 2011;22:377-86.
18. Clark SL, Denburg MR, Furth SL. Physical activity and screen time in adolescents in the chronic kidney disease in children (CKID) cohort. Pediatr Nephrol. 2016;31:801-8.
19. Abraham AG, Mak RH, Mitsnefes M, et al. Protein energy wasting in children with chronic kidney disease. Pediatr Nephrol. 2015;29(7):1231-8.
20. Secker DJ, Jeejeebhoy KN, How to perform subjective global nutritional assessment in children. J Acad Nutr Diet. 2012;112(3):424-31.
21. Abdel-Rahman SM, Bi C, Thaete K. Construction of Lambda, Mu, Sigma values for determining mid-upper arm circumference z scores in U.S. children aged 2 months through 18 years. Nutr Clin Pract. 2017;32:68-76.
Tower J, Oladitan, L, Abdel-Rahman S. Understanding the role of mid-upper arm circumference in assessing the nutrition status of children on dialysis. Poster presented at: The Annual Dialysis Conference; March 11-14, 2017; Long Beach, CA.