Children with cerebral palsy (CP) and other medical complexity comprise an outsized proportion of health care use. In this review, we describe the current science of assessment of nutritional status for children with CP, outline a systematic approach to assessing their nutritional status, delineate ramifications of malnutrition on hospitalization-associated outcomes, and identify knowledge gaps and means of addressing those gaps using quality improvement and clinical research tools. Methods to accurately assess body composition and adiposity in this population by using skinfolds, age, sex, and activity level are available but are not widely used. There are limitations in our current method of estimating energy needs in children with CP, who are at higher risk of both obesity and micronutrient deficiencies. There is some evidence of an association between malnutrition, defined as either underweight or obesity, and hospitalization-associated outcomes in children generally, although we lack specific data for CP. The gaps in our current understanding of optimal nutritional status and between current science and practice need to be addressed to improve health outcomes for this vulnerable patient population.

Children with medical complexity account for a significant and increasing proportion of acute care hospitalizations, and they have unique nutritional needs.1,2  Improving our understanding of their nutritional status and how to optimize nutritional intake may help reduce unnecessary hospitalizations, reduce morbidity during hospitalizations, and improve clinical outcomes for these children. The time period of a hospitalization provides a critical window in which to optimize and potentially change the trajectory of their nutritional status. In this review, we propose an approach to addressing the nutritional status of children with medical complexity, identify knowledge gaps and potential means of addressing those gaps using quality improvement and clinical research tools, and, finally, describe the potential ramifications of both under- and overnutrition on hospitalization. We used the literature on children with cerebral palsy (CP) as a proxy for the broader group of children with medical complexity.

CP is a motor impairment caused by a brain injury or malformation during development.3  Not all children with CP are medically complex. The Gross Motor Function Classification System (GMFCS) uses a I to V scale that corresponds to increasing levels of motor impairment, and, for many children, this level is also used to approximate their degree of medical complexity.4  Some children with CP, particularly those with a higher GMFCS, have impaired oral-motor function, placing them at increased risk of malnutrition and associated morbidities.5  The increased use of gastrostomy tubes (G-tubes) and other enteral feeding tubes for providing nutrition to children with impaired oral-motor function has improved their health-related quality of life.6  More recently, excess adiposity has been recognized as a potential risk for children receiving supplemental nutrition,7  and adults with CP are increasingly recognized as having a higher risk of obesity-associated chronic diseases.8 

Nutrition affects health via critical immunologic and biochemical pathways. There are several mechanisms by which nutritional status may affect acute hospitalization outcomes in this population. Protein calorie malnutrition impairs the cellular immune system, puts the child at an increased risk of infection and morbidity associated with infectious diseases, and decreases the response to vaccinations.9  Obesity influences the immune system via multiple mechanisms, including endocrine effects of leptin on T-cell metabolism and function.10,11  Micronutrient deficiencies have clinical effects ranging from hematologic (eg, folate) to more wide ranging (fatigue, muscle pain [eg, carnitine]).12,13  Secondary to their impaired oral-motor function and reliance on enteral feeds, children with more severe CP have an increased risk of malnutrition and these clinical sequelae.

Nutrition in children with CP is complicated by varying levels of function, ability to eat by mouth, and tolerance of different food types and textures. The feeding history should include, but is not limited to, route of food administration (oral versus G-tube or other enteral feeding tubes); type, texture, and concentration of food or formula, along with any fluid supplementation; vitamin and mineral supplementation; medications and caregiver report of usual dietary intake by 24 hour recall, diet log, or daily tube-feeding regimen with interruptions in regimen noted. Caregivers may inaccurately report energy intake in children with CP, and meticulous attention to detail in the feeding history is critical.14  Patients with epilepsy and, in particular, those taking valproic acid should be asked about carnitine supplementation. Obtaining specific information on multivitamin and supplement use can be helpful in assisting a dietitian in their assessment, given the heterogeneity in components. Bowel function and the medicines caregivers use to address any dysfunction are important because they may affect absorption and transit time.

An overall assessment of muscle and fat stores and specific signs of micronutrient deficiency should be noted on a thorough physical examination (Table 1). The American Society for Parenteral and Enteral Nutrition and the Academy of Nutrition and Dietetics propose the use of nutrition-focused physical examination techniques to assess for micronutrient deficiencies as well as overall muscle and fat stores. A general inspection of the patient should be done, noting if there is evidence of significant weight change demonstrated by signs of muscle mass loss or subcutaneous fat loss: areas of the body to focus on for fat loss include the face, arms, chest, and buttocks. For muscle wasting, areas of focus include the temple, clavicle, shoulder, scapula, thigh, knee, and calf.12  In Table 1, we identify additional clinical findings of nutritional deficiencies.

TABLE 1

Physical Examination Findings of Nutritional Deficiencies and Prevalence of Deficiencies Identified in Children With CP

Nutritional DeficiencySitePhysical Examination FindingPrevalence of Deficiency
Iron54    54%–60%13,19,55  
 Skin Pallor 
 Nails Beau lines, koilonychia (spoon-nails), onychomadesis, loss of nail 
Zinc12,54,56    0%–56%13,55  
 Hair Alopecia, poor hair quality 
 Skin Diaper dermatitis that affects the perineum, acral surfaces, chins, and cheeks but spares the upper lip 
Copper56,57    0%–86%19,58, 59  
 Hair Abnormally formed hair 
 Skin Depigmentation of the skin 
 Bones Spontaneous rib fracture 
 Neuro Myelopathy, spastic gait, sensory ataxia 
Vitamin A12,54    20%–74%13,55  
 Hair Corkscrew hair 
 Skin Phrynoderma (follicular hyperkeratosis) 
 Eyes Bitot’s spots 
Vitamin C12,54,56    5%–29%13,55  
 Hair Corkscrew hair 
 Skin Perifollicular petechiae, hemorrhages, pallor 
 Bones Long bone tenderness 
 Mucosa Gingival bleeding, epistaxis 
Selenium12,56    57%–62%19,55  
 Hair Loss of hair pigment, alopecia 
 Muscle Skeletal muscle tenderness 
Nutritional DeficiencySitePhysical Examination FindingPrevalence of Deficiency
Iron54    54%–60%13,19,55  
 Skin Pallor 
 Nails Beau lines, koilonychia (spoon-nails), onychomadesis, loss of nail 
Zinc12,54,56    0%–56%13,55  
 Hair Alopecia, poor hair quality 
 Skin Diaper dermatitis that affects the perineum, acral surfaces, chins, and cheeks but spares the upper lip 
Copper56,57    0%–86%19,58, 59  
 Hair Abnormally formed hair 
 Skin Depigmentation of the skin 
 Bones Spontaneous rib fracture 
 Neuro Myelopathy, spastic gait, sensory ataxia 
Vitamin A12,54    20%–74%13,55  
 Hair Corkscrew hair 
 Skin Phrynoderma (follicular hyperkeratosis) 
 Eyes Bitot’s spots 
Vitamin C12,54,56    5%–29%13,55  
 Hair Corkscrew hair 
 Skin Perifollicular petechiae, hemorrhages, pallor 
 Bones Long bone tenderness 
 Mucosa Gingival bleeding, epistaxis 
Selenium12,56    57%–62%19,55  
 Hair Loss of hair pigment, alopecia 
 Muscle Skeletal muscle tenderness 

Dietitians are nutrition experts uniquely trained to evaluate adequacy of growth, body composition, and nutritional intake. Early screening for nutritional risk is crucial for timely intervention and nutrition management. Some hospitals do not have standardized protocols or indices for dietitian consultation. In one study, the frequency and reason for dietitian consult was evaluated with 39 patients with CP identified at potential for nutrition risk, and only 58% received a dietitian consultation, and the average time to see a dietitian was >5 days.15 

The European Society for Pediatric Gastroenterology Hepatology and Nutrition (ESPAGN) has suggested the use of 5 risk factors to identify children with neurologic impairment at high risk of malnutrition.16  These risk factors include (1) physical signs of underweight, including a physical examination of skin and peripheral circulation; (2) weight-for-age z scores <−2 SDs on standard growth charts; (3) triceps skinfold thickness <10th percentile for age and sex; (4) mid–upper arm fat or muscle area <10th percentile; and (5) faltering weight and/or failure to thrive. Increasing GMFCS is associated with a greater number of risk indicators.17  Risk of low weight for age was increased with a history of using antiepileptic drugs, dysphagia, and the presence of a gastrostomy tube. Other nutritional risk factors include rapid weight gain, overweight (defined as BMI ≥85th percentile), obesity (defined as BMI ≥95th percentile), or excess adiposity found either by physical examination, skinfold thickness, or abdominal circumference.18  In another study, we found that children with CP identified as having at least 1 ESPAGN nutrition risk factor suffered from weight loss 6 months after follow-up, indicating that risk factors were not addressed in clinical practice.17 

We recommend implementation of a risk factor–based approach to quickly identify hospitalized children at risk to facilitate timely consultation with a dietitian, similar to the approach proposed by ESPAGN, with the additional inclusion of obesity in addition to inadequate adiposity as a risk factor. The measurement of obesity should not use BMI; instead, use weight-for-age charts specific to CP in the short-term while the emerging research on skinfold-based equations to estimate percentage of body fat outlined in Table 2 are being examined. Although this review is focused on CP, all children with medical complexity could benefit from a standardized approach.

TABLE 2

Measures for Nutritional Assessment in Children With CP

Normal ParametersData Specific to Children With CPPros and Cons
Anthropometrics    
 BMI Normal between fifth and 85th percentile for age and sex60  Poor association with percentage of body fat in children with CP18  Challenging to measure height accurately; does not differentiate fat mass and fat-free mass 
 Wt-for-age growth charts for CP Normal between 20th and 80th percentile for sex and GMFCS level Derived from >25 000 children with CP at various levels; examined mortality associated with growth strata46  Represents how children with CP grew, rather than ideal growth patterns; stratified by GMFCS level and by tube feeding for GMFCS V 
 DXA 10%–25% body fat for boys; 15%–30% body fat for girls (typically developing reference) 47%–64% of children with CP had excess body fat29,31 ; 4% had low body fat Criterion standard for body composition; challenging to measure in hospital; also dependent on fat-free mass, elevating the percentage of fat 
 BIA Body fat percentage as above; total body water: 53%–63% for ages 6 mo to 11 y (typically developing children) Kushner and Fjeld equations are valid for estimating total body water in children with CP.61,62  Quick and noninvasive; lack of equipment available in most hospitals; requires accurate height measures; relies on total body water and hydration status 
 Tibia length Estimated stature = (3.26 × tibia length [in centimeters]) + 30.8 Data revealing strong correlation (0.97) with height in children <12 y of age27,28  Easy to measure; measured from superomedial aspect of tibia to inferior aspect of medial malleolus 
 MUAC CDC normal values based on NHANES data60  95% sensitivity of MUAC <10th percentile for severe malnutrition64 ; poor correlation with DXA in CP Easy to measure; not widely used in current practice 
 FMI30 : fat mass (rather than total body mass) adjusted for height squared No clear standards yet established Limited data; higher FMI in CP compared to typical development30  Benefit of not overestimating fat percentage, given the lower muscle mass in CP 
 Body composition equations by using skinfolds31,40,65  Slaughter equation uses the subscapular and triceps skin folds; Gurka equations correct for CP, sex, and level of motor impairment. Slaughter equation significantly underestimates body fat. Correction with the Gurka equation improved estimation of body fat with only a 0.8% mean difference from DXA. Gurka equation allows you to correct for CP, sex, and level of motor impairment. Gurka equation has data for a population from 8 to 18 y old. 
Laboratory tests    
 Prealbumin and albumin Prealbumin; low: <16 mg/d; borderline: 16–20 mg/dL; adequate: >20 mg/dL Prealbumin and albumin do not have a significant relationship with anthropometric measures of nutritional status (including height, midarm fat, and skinfolds).66  Indicator of overall illness, rather than specific to nutritional status6668  
 Vitamin D69  25(OH)D levels; deficient: ≤12 ng/mL; insufficient: 12–20 ng/mL; sufficient: >20 Children with CP are at risk for vitamin D deficiency, with researchers identifying 34% of participants having Vitamin D deficiency. Children with CP and being nonambulatory, with epilepsy, intellectual delay, teeth problems, or growth retardation are at higher risk of deficiency. 
 Ferritin and iron13,55  Low iron stores: <12 µg/L ferritin Approximately one-half of patients with CP have low iron stores or inadequate iron intake when compared with estimated average requirement. Easy to measure and to replenish with oral supplement. Many participants’ highest proportion of energy source came from milk or a milk-based drink, which was a poor source of iron. 
 Copper58,59,70  All ages: 0.7–1.5 mg/L Copper serum levels were lower in children with CP compared with controls in one study from Ghana; no deficiencies were noted in two US studies. Copper is a vital cofactor for enzyme antioxidants in defense against reactive oxygen species, and copper deficiency has been shown to lead to lower defense against oxidative stress. 
 Folate13,71  Children: 4–20 ng/mL25  Children with CP who are tube fed have higher levels of folate compared with those who are not. Children with CP on antiepileptic drugs are at increased risk of folate deficiency, which may result in increased homocysteine levels. Folate supplementation for children with CP on AEDs may prevent elevated homocysteine and resulting health risks.24  
 Selenium59,70  All ages: 7–15 mg/L Asmah et al59  found selenium levels higher in children with CP, compared with controls. Hals et al19  found selenium levels low in 62% of their cohort. High selenium levels have been associated with increased oxidative stress. 
 Thiamine13  All ages: 55–125 nmol/L Children with CP who take a multivitamin have higher thiamine levels and are less likely to be deficient. Easy to supplement with a multivitamin 
 Vitamin B1213  Infant: 160–1300 pg/mL; child: 200–835 pg/mL25  Children with CP who take a multivitamin supplement have higher B12 levels and are less likely to be deficient. Children with CP on antiepileptic medications are at increased risk of B12 deficiency. Easy to supplement with multivitamin; B12 supplementation for children with CP on AEDs may prevent elevated homocysteine and, thus, the risk for cerebrovascular events or heart disease. 
 Zinc59  All ages: 70–120 ug/dL72  Zinc levels were detected at lower levels in the blood in children 0–5 y of age with CP compared with controls. Zinc deficiency leads to lower defense against oxidative stress. High daily zinc intake risks inhibiting intestinal absorption of copper, leading to copper deficiency. 
Normal ParametersData Specific to Children With CPPros and Cons
Anthropometrics    
 BMI Normal between fifth and 85th percentile for age and sex60  Poor association with percentage of body fat in children with CP18  Challenging to measure height accurately; does not differentiate fat mass and fat-free mass 
 Wt-for-age growth charts for CP Normal between 20th and 80th percentile for sex and GMFCS level Derived from >25 000 children with CP at various levels; examined mortality associated with growth strata46  Represents how children with CP grew, rather than ideal growth patterns; stratified by GMFCS level and by tube feeding for GMFCS V 
 DXA 10%–25% body fat for boys; 15%–30% body fat for girls (typically developing reference) 47%–64% of children with CP had excess body fat29,31 ; 4% had low body fat Criterion standard for body composition; challenging to measure in hospital; also dependent on fat-free mass, elevating the percentage of fat 
 BIA Body fat percentage as above; total body water: 53%–63% for ages 6 mo to 11 y (typically developing children) Kushner and Fjeld equations are valid for estimating total body water in children with CP.61,62  Quick and noninvasive; lack of equipment available in most hospitals; requires accurate height measures; relies on total body water and hydration status 
 Tibia length Estimated stature = (3.26 × tibia length [in centimeters]) + 30.8 Data revealing strong correlation (0.97) with height in children <12 y of age27,28  Easy to measure; measured from superomedial aspect of tibia to inferior aspect of medial malleolus 
 MUAC CDC normal values based on NHANES data60  95% sensitivity of MUAC <10th percentile for severe malnutrition64 ; poor correlation with DXA in CP Easy to measure; not widely used in current practice 
 FMI30 : fat mass (rather than total body mass) adjusted for height squared No clear standards yet established Limited data; higher FMI in CP compared to typical development30  Benefit of not overestimating fat percentage, given the lower muscle mass in CP 
 Body composition equations by using skinfolds31,40,65  Slaughter equation uses the subscapular and triceps skin folds; Gurka equations correct for CP, sex, and level of motor impairment. Slaughter equation significantly underestimates body fat. Correction with the Gurka equation improved estimation of body fat with only a 0.8% mean difference from DXA. Gurka equation allows you to correct for CP, sex, and level of motor impairment. Gurka equation has data for a population from 8 to 18 y old. 
Laboratory tests    
 Prealbumin and albumin Prealbumin; low: <16 mg/d; borderline: 16–20 mg/dL; adequate: >20 mg/dL Prealbumin and albumin do not have a significant relationship with anthropometric measures of nutritional status (including height, midarm fat, and skinfolds).66  Indicator of overall illness, rather than specific to nutritional status6668  
 Vitamin D69  25(OH)D levels; deficient: ≤12 ng/mL; insufficient: 12–20 ng/mL; sufficient: >20 Children with CP are at risk for vitamin D deficiency, with researchers identifying 34% of participants having Vitamin D deficiency. Children with CP and being nonambulatory, with epilepsy, intellectual delay, teeth problems, or growth retardation are at higher risk of deficiency. 
 Ferritin and iron13,55  Low iron stores: <12 µg/L ferritin Approximately one-half of patients with CP have low iron stores or inadequate iron intake when compared with estimated average requirement. Easy to measure and to replenish with oral supplement. Many participants’ highest proportion of energy source came from milk or a milk-based drink, which was a poor source of iron. 
 Copper58,59,70  All ages: 0.7–1.5 mg/L Copper serum levels were lower in children with CP compared with controls in one study from Ghana; no deficiencies were noted in two US studies. Copper is a vital cofactor for enzyme antioxidants in defense against reactive oxygen species, and copper deficiency has been shown to lead to lower defense against oxidative stress. 
 Folate13,71  Children: 4–20 ng/mL25  Children with CP who are tube fed have higher levels of folate compared with those who are not. Children with CP on antiepileptic drugs are at increased risk of folate deficiency, which may result in increased homocysteine levels. Folate supplementation for children with CP on AEDs may prevent elevated homocysteine and resulting health risks.24  
 Selenium59,70  All ages: 7–15 mg/L Asmah et al59  found selenium levels higher in children with CP, compared with controls. Hals et al19  found selenium levels low in 62% of their cohort. High selenium levels have been associated with increased oxidative stress. 
 Thiamine13  All ages: 55–125 nmol/L Children with CP who take a multivitamin have higher thiamine levels and are less likely to be deficient. Easy to supplement with a multivitamin 
 Vitamin B1213  Infant: 160–1300 pg/mL; child: 200–835 pg/mL25  Children with CP who take a multivitamin supplement have higher B12 levels and are less likely to be deficient. Children with CP on antiepileptic medications are at increased risk of B12 deficiency. Easy to supplement with multivitamin; B12 supplementation for children with CP on AEDs may prevent elevated homocysteine and, thus, the risk for cerebrovascular events or heart disease. 
 Zinc59  All ages: 70–120 ug/dL72  Zinc levels were detected at lower levels in the blood in children 0–5 y of age with CP compared with controls. Zinc deficiency leads to lower defense against oxidative stress. High daily zinc intake risks inhibiting intestinal absorption of copper, leading to copper deficiency. 

FMI, fat mass index; MUAC, mean upper arm circumference; NHANES, National Health and Nutrition Examination Survey.

Prealbumin has been used as a measure of nutritional status. The data that this metric lacks value as an indicator of nutrition are now strong. Along with albumin, low levels of prealbumin reflect disease severity and intercompartmental shifts, rather than reduced protein synthesis capacity due to malnutrition (Table 2).

Measurement of adequate intake of important micronutrients can be estimated both by a dietary intake report and laboratory testing.13,19  In few studies have researchers examined micronutrient assessment by laboratory testing in children with CP. The data we do have suggest that multivitamin supplementation and G-tube feeding are associated with fewer deficiencies, in both B vitamins and trace minerals such as selenium.13  Children with CP and epilepsy should have a free carnitine level measured and, if deficient, carnitine supplementation provided in consultation with a dietitian. This population has been found to be at risk for carnitine deficiency, particularly for those taking valproic acid or with multiple anti-epileptic drugs (AEDs), those on enteral formula only, and those with a low body weight.2022 

Low bone mineral density in children with CP may be driven by immobility, antiepileptic drugs, and vitamin D deficiency. In a systematic review published in 2011 to develop evidence-based clinical practice guidelines for children with CP and low bone mineral density, researchers recommended vitamin D supplementation on the basis of baseline vitamin D laboratory testing (25-hydroxyvitamin D).23  There is a rich scientific debate on what a target vitamin D concentration should be, ranging from >12 ng/mL to >20 or even 30 ng/mL.24,25  Given the multiple risk factors most children with CP, particularly those with immobility, have for low bone mineral density, we recommend a target of at least 20 ng/mL, with attention to appropriate dosing because, although low, the potential for toxicity does exist.26 

Supplementation with an age-appropriate multivitamin should be strongly considered in children with CP, given their higher likelihood of these deficiencies, given a lack of variety in their diet and potentially reduced formula intake due to lower energy needs. We recommend that clinicians should consider testing for folate, calcium, and vitamin D deficiencies in children who are not taking an age-appropriate multivitamin. Testing children with abnormal skin and hair findings (Table 1) for micronutrients such as selenium or copper should also be considered.

BMI has significant flaws, given the lower fat-free mass in children with CP and significant challenges in accurate measurement of height. Tibia lengths show a strong correlation with height and can be used to estimate height,27,28  although the limitations of BMI remain. In the current growth charts specific for CP, past trends, rather than ideal growth, are described: in other words, how they have grown rather than how they should grow.

Dual-energy radiograph absorptiometry (DXA) is the standard for body composition analyses (see Table 2 for a comparison of anthropometric indicators). In a study of children with GMFCS III to V, investigators showed that all of the other individual anthropometric indicators had a poor correlation with percentage of body fat using DXA.29  Bioelectric impedance analysis (BIA) uses a small current passed between the hands or feet to estimate the percentage of fat given the known variation in resistance by the percent of body fat. DXA and BIA are not readily available for all hospitalized children and are, currently, primarily research modalities. Another emerging area of research is the use of a fat mass index, which has the benefit of not overestimating the percentage of fat with lower muscle mass.30 

We recommend the use of estimating equations using both skinfold measurements and other variables, such as age and sex, developed by Oeffinger et al.31  These have shown good agreement with DXA, the functional gold standard.31  The widespread use of electronic medical records makes the widespread use of complex skinfold-based equations easier.

To reduce the risk of over- and underfeeding, careful determination of energy requirements is essential. Evaluating the energy needs of children with CP is challenging, and individual needs vary depending on the severity of disability. In general, total energy expenditure, in calories per day, is determined first by estimating resting energy expenditure (REE) and then by using adjustment factors that take into account activity level.

Predictive equations for REE, such as the Schofield, Harris-Benedict, or World Health Organization (WHO) equations, are used in typically developing children; these equations are dependent on age, sex, and accurate measurements of weight and height. It has been shown that the energy needs of children with CP differ from those of typically developing children.32,33  In a recent study, researchers compared the WHO, Harris-Benedict, and Schofield equations, among others, with indirect calorimetry in children with spastic CP and found that these commonly used equations are inaccurate in this population.34  Lee et al35  compared measured energy expenditure by indirect calorimetry with predicted energy expenditure and found that predictive equations significantly overestimated energy needs in children with spastic CP. Children with athetoid CP may have an increased REE.

Attempts at developing equations specific to children with CP have been made.34,36,37  Culley and Middleton36  suggested a method of estimation based on height and the presence of motor dysfunction using a range of 11 to 15 kcal/cm; this method remains stable regardless of age or sex.38  The use of this equation is dependent on accurate height measurement, which is difficult to obtain in the presence of muscle contractures, inability to stand independently, and scoliosis. Using tibia measurements to approximate height and then applying those estimates in this method has not been examined. BIA may be a reliable and accurate method for estimating REE and total energy expenditure in comparison with indirect calorimetry, although, at this time, it requires further study and has some practical barriers to widespread implementation.38 

The current recommendation of expert groups, such as the American Society for Parenteral and Enteral Nutrition and the European Society for Paediatric Gastroenterology, Hepatology and Nutrition, is to use reference equations for typically developing children, adjusting for differences in mobility, muscle tone and body composition, activity level, and growth requirements, as needed for weight gain or loss. These estimates should be used as a starting point for dietary intervention, and frequent monitoring of weight and body composition for reassessment is required.16,39  Understanding that these equations tend to overestimate the needs of children with CP is important. When reducing caloric intake, especially in children exclusively tube fed, there should be careful consideration of protein, essential fatty acids, and micronutrients to prevent deficiency.

We agree with this recommendation of using reference equations for typically developing children, with adjustments as described, with one additional caveat. Using more accurate estimates of body composition, such as the Gurka et al40  equations, would provide a better metric of identifying whether those estimates are over- or underestimating energy requirements for the individual child.

There are several challenges to optimizing nutrition for children with CP who are hospitalized and, by extension, other children with medical complexity. Optimal nutrition can be defined as the dietary intake that results in the optimal growth and development of the individual child while also reducing the risk of disease.41  The inherent circularity of this basic definition presents challenges if optimal growth and development are not fully understood or defined. We need more research, and there are several tangible steps that pediatric hospital medicine as a field can make (Table 3). These children make up a significant proportion of the children we serve, and addressing their nutritional needs can affect their hospitalization outcomes.

TABLE 3

Current State and Recommendations Going Forward for Improving Nutrition for Hospitalized Children With CP

Current StateRecommendationsTools Needed To Implement
Lack of a uniform and standardized approach to involving dieticians in the care of hospitalized patients with CP Develop a standardized approach for involving dieticians in the care of hospitalized children with CP by using a risk factor–based approach that incorporates measures of both insufficient and excess adiposity. Risk factor identification by using EMR tools 
Dietician available for consultation 
Skinfold calipers and training 
Lack of an accurate and accessible measure of body habitus for children with CP Implementation of evidence-based measures of body habitus for children with CP; do not use BMI with typically developing children as the reference for this population. Estimating equations from skinfold measurements 
Quality improvement for implementation 
Imperfect understanding of optimal energy requirements for children across the spectrum of impairment with CP Using reference equations for typically developing children with strong caveat of adjusting on the basis of accurate assessment of body composition; clinical research examining optimal energy requirements Dietitian partnerships 
Medical record adaptation 
Quality improvement for implementation 
Lack of uniform data collection across hospital systems for nutritional status of children with CP Examine data on patients with CP to determine the impact of under- and overnutrition on hospital-based outcomes, morbidity, and mortality. Steps above need to be completed to have better metrics to examine 
Current StateRecommendationsTools Needed To Implement
Lack of a uniform and standardized approach to involving dieticians in the care of hospitalized patients with CP Develop a standardized approach for involving dieticians in the care of hospitalized children with CP by using a risk factor–based approach that incorporates measures of both insufficient and excess adiposity. Risk factor identification by using EMR tools 
Dietician available for consultation 
Skinfold calipers and training 
Lack of an accurate and accessible measure of body habitus for children with CP Implementation of evidence-based measures of body habitus for children with CP; do not use BMI with typically developing children as the reference for this population. Estimating equations from skinfold measurements 
Quality improvement for implementation 
Imperfect understanding of optimal energy requirements for children across the spectrum of impairment with CP Using reference equations for typically developing children with strong caveat of adjusting on the basis of accurate assessment of body composition; clinical research examining optimal energy requirements Dietitian partnerships 
Medical record adaptation 
Quality improvement for implementation 
Lack of uniform data collection across hospital systems for nutritional status of children with CP Examine data on patients with CP to determine the impact of under- and overnutrition on hospital-based outcomes, morbidity, and mortality. Steps above need to be completed to have better metrics to examine 

EMR, electronic medical record.

Estimates of the prevalence of underweight and obesity in children vary as a function of both method of measurement and degree of motor impairment. In studies, researchers using BMI, which has significant limitations as outlined above, as the measure of underweight have found estimates ranging between 7% and 14% of children with CP.4244  In a retrospective cohort study of 587 children with CP GMFCS levels I to III, researchers found that ∼7% of their cohort was underweight according to CDC-based BMI z scores, 74% were healthy, and 19% were either overweight or obese.44  Of note, children with greater motor impairment (higher GMFCS) were more likely to have obesity. In a single center study from a Shriners Hospital in South Carolina, researchers identified a prevalence of 16.5% for obesity in children with CP at GMFCS levels I to III in 2003 to 2004, with an increase from 7.7% in the 1990s.45 

Using a more accurate method, a DXA scanner, a study of 300 children with CP from Germany revealed a prevalence of 17% for excess body fat, with nearly twice the prevalence (20%) in GMFCS level III or V children compared with GMFCS level I or II children (10%).18,44  Using DXA scans in children with GMFCS III or V, a multi-site study from the United States revealed that 64% of children with CP had excess body fat (defined as >25% for boys and >30% for girls).29  Similarly, using height estimated from knee height for children with GMFCS I to III and the same body fat definitions as above, Oeffinger et al31  identified 47% of children as having excess body fat and 4% as having inadequate body fat using DXA.

We found few studies in which researchers look specifically at the effects of nutritional status on health outcomes in hospitalized children with CP who were underweight. Brooks et al46  conducted a large retrospective analysis of >25 000 outpatient children with CP. They found that children with a weight for age <20th percentile were more likely to have comorbid chronic conditions and a higher risk of death than those with weights >20th percentile, after stratifying by GMFCS level.

These results are supported by a study in 2019 by Kim et al.47  In this large birth cohort study, individuals with CP showed a higher mortality rate than the general population. When taking into account patients whose weight for age was less than the third percentile by using WHO growth charts, the mortality rate was 2 to 5 times higher in a combined population of patients with CP and the general population. They did not conduct a specific analysis within the CP group.

For children generally, the data indicate an increased risk of morbidity and mortality with obesity. In a systematic review through 2012, researchers identified 28 cohort or case-control studies in which the associations between obesity and outcomes of mortality, length of stay, and hospital-acquired infections, including all hospitalized children, were examined.48  Although they identified a significant variation in quality of the studies, larger and higher quality studies revealed an association between obesity and worse outcomes.

Studies in which researchers use administrative data have revealed an association between obesity and morbidity during hospitalizations for children for outcomes of all infections49  and, specifically, lower respiratory tract infections.50  Bechard et al51  showed that malnutrition, defined as either underweight or obesity, was associated with poorer outcomes in all patients in an analysis of 2 large multi-PICU studies. In a retrospective analysis of data from the virtual PICU systems database, it was found that being overweight (defined by using equally distributed BMI z score intervals) was independently associated with increased PICU mortality, after controlling for preexisting conditions and disease severity.52  In this study, researchers also found an increased mortality risk for underweight children; however, this did not hold true after controlling for comorbidities and disease severity.52  This study had a large cohort of children, but, in the analysis only those patients who had weight and height values reported were included, thus potentially not capturing a large proportion of patients at risk with nonambulatory CP. Children with CP are at increased risk of sleep apnea secondary to abnormal muscle tone and control, and excess adiposity would potentially increase the risk of obstructive sleep apnea as well.

In 1 study, researchers looking at postoperative complications in children with CP after orthopedic procedures found that underweight status was an independent predictor of increased complications, whereas no increased risk was found in the overweight or obese cohorts.53  In this study, researchers used BMI as a measurement of patient nutritional status and did not take individual functional status into account. Brooks et al46  found no increased risk of overall mortality for patients with CP whose weight was >80th percentile in their outpatient cohort.

Drawing on the limited data we do have on patients with CP and extrapolating from other populations of patients with medical complexity, we postulate that malnutrition, including both underweight and obesity, contribute to worse outcomes, including more frequent and prolonged hospitalizations. Given the potential benefit for individual children’s morbidity and the outsized impact these children have on the medical system, it is imperative that we address the lack of uniformity of data collection, conduct quality improvement projects targeting improved hospital dietitian assessments and implementing more accurate body composition assessments, and address the scientific gaps in our understanding of energy expenditure for these children.

Dr Foster contributed to the conceptualization of the article, conducted the literature search, and drafted the initial manuscript and revisions; Dr Lane contributed to the initial draft, conducted a literature search, and edited several revisions and the tables; Ms Massey conducted a literature search and contributed to the initial draft and several revisions; Dr Noelck revised several versions of the manuscript and conducted a literature search for subsections; Dr Green contributed to the organization of the article, edited several drafts, and assisted with figure and table development; Dr Austin contributed to the literature search and conceptual organization of the article and edited several revisions; and all authors approved the final manuscript as submitted.

FUNDING: The National Institutes of Health provided funding to Dr Foster via grant K23 DK109199. Funded by the National Institutes of Health (NIH).

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:
Elsevier
;
2018

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.