Pediatric Annals

Special Issue Article 

A New Approach to Comprehensive Growth and Nutrition Assessment in Children

Timothy Sentongo, MD

Abstract

A new approach to comprehensive growth and nutrition assessment of infants, children, and adolescents that is etiology based and relatively simple to implement is now available. It encompasses five domains: anthropometry (growth measurements), assessment of change in growth (growth dynamism), duration of the growth abnormalities, etiology of the nutritional imbalance, and impact of the nutritional state on functional outcomes. Its increased use will help to standardize the screening, diagnosis, and documentation of malnutrition in both ambulatory and hospitalized patients. [Pediatr Ann. 2019;48(11):e425–e433.]

Abstract

A new approach to comprehensive growth and nutrition assessment of infants, children, and adolescents that is etiology based and relatively simple to implement is now available. It encompasses five domains: anthropometry (growth measurements), assessment of change in growth (growth dynamism), duration of the growth abnormalities, etiology of the nutritional imbalance, and impact of the nutritional state on functional outcomes. Its increased use will help to standardize the screening, diagnosis, and documentation of malnutrition in both ambulatory and hospitalized patients. [Pediatr Ann. 2019;48(11):e425–e433.]

A child's growth status is one of the most reliable indicators of wellness, disease, and response to therapy. The term malnutrition is generally applied to undernourishment with lack of growth and/or weight loss; however, overweight/obesity is similarly detrimental to health and, therefore, should be viewed as a form of malnutrition. Both undernutrition and overweight/obesity are imbalances between nutrient requirements and intake resulting in cumulative deficits or excesses in energy, protein, and/or micronutrients that negatively impact growth and functional capacity and cause increased risk of morbidity and death.1,2 The morbidities and mortality from overweight/obesity are much later in onset; therefore, childhood provides a good opportunity for prevention and early intervention.3 The negative effects of chronic malnutrition extend beyond stunted growth to delays in gross motor development, poor cognitive ability, underachievement in school, and poor socialization skills.4,5 Thus, the complications of malnutrition may be difficult to reverse depending on the severity, timing of onset, and duration of nutritional problems. The current prevalence of undernutrition in North America is unknown partly because of different and inconsistent methods of documentation used by different health care providers. Therefore, the need for a uniform definition and documentation of pediatric malnutrition led to a multidisciplinary team of health care providers who created an etiology-based approach that relies on domains judged to be most relevant after extensive review of the literature. Thus, a new approach to comprehensive growth and nutrition assessment in infants, children, and adolescents that is relatively simple to implement is now available.6,7 The domains of comprehensive growth and nutrition assessment include the following five domains: (1) anthropometry, (2) assessing dynamism of growth, (3) determining of duration of growth abnormalities, (4) determining etiology of the nutritional imbalance, and (5) assessing impact of the nutritional state on functional outcomes (Table 1).

Key Domains to Be Encompassed During Comprehensive Nutrition Assessment

Table 1:

Key Domains to Be Encompassed During Comprehensive Nutrition Assessment

Domain A: Anthropometry

Anthropometric assessment refers to measurements of body dimensions and composition. The values are then compared with available growth standards or norms based on reference data for that population. The anthropometric parameters routinely measured during assessment and monitoring of childhood growth are weight, length/height, head circumference, mid-upper arm circumference, and triceps skinfold. The remainder of the assessment should involve a careful physical examination that screens for mineral/micronutrient deficiencies as well as indicators for metabolic syndrome (eg, acanthosis nigricans (Table 2).

Nutrition Concerns Based on Physical ExaminationNutrition Concerns Based on Physical Examination

Table 2:

Nutrition Concerns Based on Physical Examination

Preterm Infants

Newborn term and preterm infants are classified based on their birth weight and/or gestational age estimated based on last menstrual period, prenatal ultrasound, or the Ballard newborn maturational examination.8 All infants with birth weight <2,500 g regardless of gestational age are classified as low birth weight. Small for gestational age (SGA) and intrauterine growth restriction (IUGR) refer to newborns with birth weight <10th percentile for gestational age. The causes of SGA include genetic or chromosomal anomalies, toxin exposure, deficient substrate supply, and normal variant with identifiable pathology.9 SGA infants with proportional reductions in weight, length, and head circumference measurements may also be referred to as having symmetrical IUGR, proportional IUGR, or stunted IUGR. These infants have a similar body composition at birth to weight-matched infants born appropriate for gestational age. In general, symmetrical SGA arises from factors intrinsic to the fetus with onset during the first trimester of pregnancy. Asymmetrical, disproportional, or wasted IUGR refers to SGA infants with low birth weight for gestation age but with relatively normal body length and head circumference. Asymmetrical SGA indicates that although growth in weight was retarded, linear growth and gross brain growth were spared. The causes of asymmetrical IUGR are normally factors extrinsic to the infant occurring during the second and third trimester. Infants with asymmetrical IUGR are more likely to exhibit normal catch-up growth during the first 6 to 12 months of life and normal catch-up in cognitive development. Preterm infants born with symmetrical SGA have higher mortality, are more likely to continue with slow growth postnatally, and more like to have impaired cognitive and school outcomes compared to infants born with symmetrical SGA.10 Large for gestational age (LGA) refers to newborns with a birth weight >90th percentile for gestational age. The causes of LGA include maternal diabetes, Beckwith-Wiedemann syndrome, and genetic disorders. Children born LGA have a higher risk of developing overweight/obesity during school age compared to children born with normal birth weight.11

Weight and Length/Height

Weight in infants (age <12 months) should be measured without diapers to the nearest 0.01 kg. Older children should be measured to the nearest 0.1 kg while wearing little or no outer clothing and no shoes.12 Linear growth in children age younger than 24 months and older children who are unable to stand erect is assessed by measuring length with the child laying supine on a firm length board. Use of flexible tapes to measure length in children is notoriously inaccurate and therefore should be avoided. Height in children older than age 2 years should be measured with the child standing upright with their heels, buttocks, and back against a wall mounted stadiometer.12 Linear growth is greatly influenced by hereditary factors; therefore, interpretation is improved by making comparisons with mid-parental height. The mid-parental height may be estimated using the Tanner-Goldstein-Whitehouse13 approach as follows: for girls subtract 13 cm from father's height, and for boys add 13 cm to the mother's height; then, divide into half to get the mid-parental height ±8.5 cm. This represents median mid-parental height ±2 SD (3rd to 97th percentile). Thereafter, plot the value of mid-parental height ±8.5 cm at the end of the height line (ie, age 20 years on the 2–20 years growth percentile chart). The child's expected height should fall within the percentile range of ±8.5 cm of the value obtained for mid-parental height. Children with length/height percentiles that fall outside mid-parental height ±8.5 cm should be considered growing outside their genetic potential and thus referred for further evaluation.

Weight-for-Length and BMI

Weight-for-length (WFL) and body mass index (BMI) (weight [kg]/height2 [m2]) are used to categorize wasting, normal body composition, and overweight/obesity. Wasting refers to emaciation due to depletion of body fat and loss of muscle mass, whereas obesity refers to excess body fat that is strongly associated with health risks.14 WFL is useful for identifying wasting, severity of malnutrition, and correlations with risk of death. Children presenting with WFL z-scores < −3 are regarded as severely malnourished with a 9-fold increased risk for death from malnutrition or acquired illness.1 WFL charts are only available for children younger than age 24 months whereas BMI standards and reference data are available from birth to age 20 years. The range of normal BMI varies with age; therefore, percentiles or z-scores, but not the actual calculated BMI, should be the basis for interpreting underweight, normal weight, or overweight/obesity. Infant BMI is much better than WFL at predicting risk for early childhood overweight and obesity.15 Morbidity and cardiovascular risk are linked to the excess body fat and not lean tissue. BMI is inadequate for differentiating between increased weight from excess body fat mass (adiposity) versus increased lean tissue or both. However, BMI values >95th percentile for age are highly correlated with increased body weight due to excess fat.14

Head Circumference

Head circumference is a proxy measure of brain size and growth. Brain growth occurs most rapidly during the first 3 years of life then slows down. Head circumference is measured using a nonstretchable measuring tape12 and plotted using the World Health Organization (WHO) international growth standards. Decreased head circumference is among the sequelae of severe chronic malnutrition and predicts delays in learning and psychomotor development.16

Mid-Upper Arm Circumference

Mid-upper arm circumference (MUAC) is a composite measure of muscle, fat, and bone at the mid-upper arm.12 MUAC is easy to obtain in recumbent patients and minimally affected by fluid status, edema, or therapy with steroids. MUAC measurements of <125 to 130 mm in children age 6 to 59 months or a MUAC value <110 mm regardless of age are the most sensitive and specific tool used by the WHO to screen for severe malnutrition associated with increased risk of death.1 The MUAC increases by only 0.5 cm per year; therefore, whereas reliable as a screening tool, it is less helpful in monitoring short-term growth or quick response to therapy. MUAC z-scores are available for children age 1 to 18 years.17

Triceps Skinfold

Triceps skinfold (TSF) is also the best single anthropometric indicator of percentage body fat (%BF) in children age 6 to 12 years. TSF thickness is a measure of subcutaneous fat at the mid-arm. Fat mass is an indicator of the body's energy reserves. Fat stores at the mid-arm get depleted during starvation and rapidly replenished during nutritional therapy.12,18 Therefore, measuring TSF thickness is useful at baseline and in monitoring response to nutritional intervention. More detailed instructions about technique used to accurately measure TSF can be found in National Institutes of Health anthropometry procedures manual.19

Body Composition

Dual-energy X-ray absorptiometry (DXA) is one of the most accurate methods available for measuring body composition (ie, fat mass [FM]) and fat-free mass (FFM), also referred to as lean tissues. The percent body fat (%BF) is calculated as the quotient of FM (in kilograms) divided by total body weight and multiplied by 100. The %BF percentile charts based on DXA measurements of body composition in children and adolescents age 8 to 19 years have been published by the Centers for Disease Control and Prevention (CDC).20 The cut-off to define excess body fat and increased risk of dyslipidemia is %BF >75th percentile.20 However, the %BF may be normal in overweight/obese children with both increased FM and FFM. Also, and increased %BF must be differentiated from cachectic obesity and sarcopenic obesity, which both represent a spuriously increased %BF in patients with disorders that disproportionately deplete muscle mass (sarcopenia), such as juvenile rheumatoid arthritis, Crohn's disease, end-stage renal disease, and cancer.21 The importance of determining body composition is that both obesity and sarcopenia are associated with higher rates of toxicity from chemotherapy and poorer outcomes. Therefore, some treatments like chemotherapy may be more appropriately dosed when based on actual FM and not just total body weight or surface area.22

Growth Standards, References, Percentiles, and z-Scores

Anthropometric measurements should be compared with the age- and gender-appropriate growth standard or reference chart. A growth standard prescribes how a healthy child should grow. The 2006 WHO/CDC growth charts for birth to age 24 months are based on growth in healthy, exclusively breast-fed infants who meet the criteria of a growth standard.23 The 2000 CDC growth charts for age 2 to 20 years based on growth in a representative population of children judged to be healthy meets the criteria of a growth reference. The 2013 revised Fenton and Kim24 gender-specific weight, length. and head circumference growth charts with a smoothed transition to 2006 WHO/CDC growth standards are the most frequently used growth references in preterm infants post-conception age 22 to 50 weeks. These charts assume that the ideal velocity of weight gain should be equivalent to fetal growth, and the curves section from 40 to 50 weeks corresponds with the equivalent aged term-born infants represented in the 2006 WHO/CDC growth standards. These growth charts may be accessed at http://www.cdc.gov/growthcharts/cdc_charts.htm

Percentile and z-scores. Percentiles are adequate for monitoring growth in children with weight, length/height, head circumference, WFL, and BMI that fall within the normal range (ie, 3rd to 97th percentile). However, percentiles are unable to quantify the severity of impaired growth when measurements are outside the range of normal. z-Scores (SD scores) are helpful in quantifying how far growth is deviated from the 50th percentile (median). Therefore, z-score values of −2, 0, and +2 correspond to the 3rd, 50th, and 97th percentiles, respectively (Table 3). z-Scores are calculated as follows: [observed value subtract median value for the reference population] divided by the standard deviation. Automatic conversion from percentiles to z-scores is now readily available on most computerized growth charts and monitoring programs (Table 4). Children with WFL z-score < −3 (severe malnutrition) have a higher risk of developing refeeding syndrome and more than 9-fold increased risk of death compared to children who are less malnourished.1,2

Comparison of Percentiles, z-Scores, and Definitions of Growth Status

Table 3:

Comparison of Percentiles, z-Scores, and Definitions of Growth Status

Classification of Preterm and Newborn Infants by Birth Weight and Growth Percentile

Table 4:

Classification of Preterm and Newborn Infants by Birth Weight and Growth Percentile

Disease-Specific Growth Reference Charts

Cerebral palsy. Growth references for children with cerebral palsy are categorized based on the level of motor disability and whether or not the child has a feeding tube. The classification system for motor disability in children with cerebral palsy is the 5-level gross motor function classification system (GMF-CS) presented in Table 5. The growth goals and expectations in children with cerebral palsy are influenced by the severity of disability. Children with GMF-CS levels I and II (less severe disability) weigh more than those with GMF-CS levels III through V (more severe disability). Growth charts are available at: http://www.LifeExpectancy.org/articles/GrowthCharts.shtml. Growth charts are also available for upper arm length and lower leg lengths of children with quadriplegic cerebral palsy.25

Gross Motor Function Classification System

Table 5:

Gross Motor Function Classification System

Genetic disorders. Disease-specific growth reference charts for several genetic disorders including Down syndrome, achondroplasia, Marfan syndrome, Williams syndrome, and fragile X syndrome have been compiled26 and are free to access online ( http://www.interscience.wiley.com/ajmg).

Domain B: Dynamic Aspects of Growth

Normal growth in healthy children is expected to be sustained at stable rates (ie, remain within the same percentile or z-score range throughout childhood and adolescence). In children younger than age 2 years, the growth velocities of weight, length, and head circumference are characterized by high variability when consecutive measurements are obtained over short durations (ie, days or weeks). It is not unusual for the growth velocity of weight or length to be at the 95th velocity percentile one month and then the 20th percentile in the successive month yet on average continue to track along the same percentile. Also, healthy children may go through brief periods of weight losses or slow gains (related to acute illness or otherwise) over several days or weeks followed by higher velocities, indicating catch-up growth. WHO gender-based weight, length, and head circumference growth velocity charts are available for children age birth to 24 months in intervals of 1, 2, 3, 4, and 6 months. These growth velocity charts may be accessed at http://www.who.int/childgrowth/standards/en/.

A change in growth z-score of ±1 is equivalent to crossing over 1 major percentile curve (3rd, 15th, 50th, 85th, or 97th) on the WHO or CDC growth monitoring charts.27 Catch-up growth is when children with history of weight loss or linear growth retardation because of malnutrition, illness, or a hormonal deficiency state experience a period of increased growth velocity after nutritional rehabilitation and therapy. Rapid weight gain or “upward centile crossing” corresponds to a z-score change of ≥0.67 compared to a previous measurement. The excessively rapid weight gain occurring during the first 2 years of life is mostly explained by accruing a higher percentage of body fat11 and has been associated with an increased long-term risk of developing obesity and noncommunicable disease.3,11,28

Domain C: Duration of the Growth Abnormalities

Duration of Abnormal Growth, Illness, or Injury (Acute vs Chronic)

An acute medical condition refers to an illness or injury that lasts fewer than 3 months or that is first noticed less than 3 months before date of assessment, whereas a chronic condition refers to durations longer than 3 months.29 Malnutrition may likewise be classified as acute versus chronic depending on whether the duration is shorter or longer than 3 months.6 Acute malnutrition disproportionately impacts weight while sparing length/height and thus presents as wasting (ie, decreased WFL and BMI percentiles/z-scores). Acute malnutrition is completely reversible without long-term sequel. Chronic malnutrition, in addition to negatively impacting weight, affects linear growth resulting in downward crossing of height percentiles or growth below the 3rd percentile (stunting). Chronic malnutrition may exert irreversible long-term negative effects on linear growth if it occurs during infancy or immediately prior to the pubertal growth spurt.

Domain D: Etiology and Pathogenesis of Abnormal Growth

Screening for the Mechanism of Malnutrition

The strongest predicator of malnutrition is the presence of an underlying disease.6 Therefore, nutrition assessment should also include a description of the mechanisms leading to malnutrition. Malnutrition may develop as a consequence of inadequate dietary intake, increased nutrient requirements, nutrient malabsorption, and/or altered nutrient utilization. Patients with systemic inflammation often present with decreased appetite, poor food intake, and muscle wasting secondary to cytokine-driven anorexia and catabolism.30 Malnutrition in patients with systemic inflammation is poorly responsive to nutritional therapy without treating the underlying disease.31 Serum concentrations of zinc, selenium, vitamins A, B6, C, and D, retinol binding protein, transthyretin (prealbumin), and other nutritional biomarkers are often suppressed when there is active systemic inflammation.32 This is because of interleukin-6–mediated downregulated synthesis of their respective carrier proteins (negative acute phase proteins)32,33 and upregulated synthesis of C-reactive protein and other acute phase inflammatory proteins. Therefore, interpreting nutritional laboratory results during illness requires concurrent measurement of serum C-reactive protein to determine whether or not the abnormal serum levels should be attributed to the inflammatory response or a true deficiency.

Domain E: Assessing Impact of Malnutrition on Functional Status

This domain assesses the consequence of the nutritional state on functional outcomes. Malnutrition is associated with impaired function at the cellular, tissue, and organ levels that manifests as loss of total body protein, decreased muscle mass, slow recovery from surgery, poor wound healing, and delayed weaning from mechanical ventilation. However, none of the anthropometric parameters directly applies to specific body functions. Therefore, measuring hand grip strength (HGS) provides a dynamic indicator of muscle function. Decreased HGS correlates with muscle dysfunction from malnutrition-related loss of total body protein.34 However, measuring HGS is impractical in young children in whom impaired muscle function manifests as delayed development of motor skills, thus delaying opportunities for actions independent of a caregiver.35 Children who are moderately to severely malnourished have delayed sitting, standing, walking, speech, language, and socialization compared to healthy children.36 Therefore, nutrition intervention in children needs to be combined with therapies that improve function, development, and socialization. Malnourished children who receive nutritional supplements combined with participation in therapies and psychosocial stimulation achieve better long-term growth, cognitive development, and socialization compared to those being treated only with nutritional supplements.5,37

Illustrative Case

You are asked to evaluate a 9-month-old infant who was readmitted to the hospital because of persistent vomiting and poor growth. He was born at term with a birth weight of 3,100 g (27th percentile, z-score −0.6) and initially presented at age 5 months with cough, feeding difficulty, vomiting, and poor growth with a weight of 6.1 kg (3rd percentile; z-sore of −1.90); length of 64.5 cm (23rd percentile; z-score of −0.74), and head circumference of 41.4 cm (15th percentile; z-score of −1.02). At that time, the patient was hospitalized for comprehensive evaluation that included gastrointestinal testing, which showed gastroesophageal reflux, and a video oral pharyngeal motor study, which showed pharyngeal dysphagia with aspiration. Therefore, the patient was started on nasogastric tube feeds, ranitidine for gastroesophageal reflux, and feeding therapy. He gained 300 g during the 1-week he stayed in the hospital, and he was discharged home with instructions to follow up with a pediatrician in 2 weeks; however, the family did not follow-up.

During the current presentation it was learned that the family had discontinued nasogastric tube feeds. The patient's anthropometric parameters were weight of 6.5 kg (<3rd%; z-score −2.88), length of 68.3 cm (3th percentile; z-score −1.83), weight-for-length <3rd% (z-score −2.9), and head circumference of 44 cm (13th%; z-score −1.14). He was unable to sit without support. The current laboratory results show prealbumin of 19 mg/dL (normal >21), and C-reactive protein <0.5 mg/dL (normal).

Nutrition Assessment

Domains A, B, and C: growth assessment. Patient is a 9-month-old male infant with chronic moderate malnutrition (chronic malnutrition). Diagnosis of moderate malnutrition is based on z-scores for weight and of WFL < −2 but > −3. Chronic malnutrition is supported on basis of duration of growth problems ≥3 months and >1 SD decline in length gain (change at age 5 to 9 months in length z-score [−0.73 to −1.83])

Domain D: pathogenesis. Reflux and feeding dysfunction led to inadequate calorie intake. Environmental factors included parents/caregivers not administering supplemental feeds. Inadequate calorie intake is supported by decreased serum prealbumin.

Domain E: impact on functional outcomes. Malnutrition has led to motor developmental delays (ie, not yet sitting without support).

Diagnosis

Final diagnosis is a 9-month-old male infant with chronic moderate malnutrition attributable to inadequate protein calorie intake secondary to reflux, dysphagia/feeding problems, and noncompliance with supplemental nasogastric tube feeds. Patient also has gross motor developmental delays that may be a complication of chronic malnutrition.

Conclusion

Comprehensive growth and nutrition assessment of infants, children, and adolescents encompasses five domains that include anthropometry, assessment of growth dynamism, determining duration of growth abnormalities, etiology of growth abnormalities, and impact of the nutritional state on functional outcomes. It is relatively simple to implement, and increased use will lead to more uniform definitions of pediatric malnutrition and improve the ability to monitor outcomes of therapy.

References

  1. Black RE, Cousens S, Johnson HL, et al. Child Health Epidemiology Reference Group of WHO and UNICEF. Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet.2010;375(9730):1969–1987. https://doi.org/10.1016/S0140-6736(10)60549-1 PMID: doi:10.1016/S0140-6736(10)60549-1 [CrossRef]20466419
  2. Olofin I, McDonald CM, Ezzati M, et al. Nutrition Impact Model Study (Anthropometry Cohort Pooling). Associations of suboptimal growth with all-cause and cause-specific mortality in children under five years: a pooled analysis of ten prospective studies. PLoS One. 2013;8(5):e64636. https://doi.org/10.1371/journal.pone.0064636 PMID: doi:10.1371/journal.pone.0064636 [CrossRef]23734210
  3. Cameron N, Demerath EW. Critical periods in human growth and their relationship to diseases of aging. Am J Phys Anthropol. 2002;119(suppl 35):159–184. https://doi.org/10.1002/ajpa.10183 PMID: doi:10.1002/ajpa.10183 [CrossRef]
  4. Hoddinott J, Behrman JR, Maluccio JA, et al. Adult consequences of growth failure in early childhood. Am J Clin Nutr. 2013;98(5):1170–1178. https://doi.org/10.3945/ajcn.113.064584 PMID: doi:10.3945/ajcn.113.064584 [CrossRef]24004889
  5. Walker SP, Chang SM, Powell CA, Simonoff E, Grantham-McGregor SM. Effects of psychosocial stimulation and dietary supplementation in early childhood on psychosocial functioning in late adolescence: follow-up of randomised controlled trial. BMJ. 2006;333(7566):472. https://doi.org/10.1136/bmj.38897.555208.2F PMID: doi:10.1136/bmj.38897.555208.2F [CrossRef]16877454
  6. Mehta NM, Corkins MR, Lyman B, et al. American Society for Parenteral and Enteral Nutrition Board of Directors. Defining pediatric malnutrition: a paradigm shift toward etiology-related definitions. JPEN J Parenter Enteral Nutr. 2013;37(4):460–481. https://doi.org/10.1177/0148607113479972 PMID: doi:10.1177/0148607113479972 [CrossRef]23528324
  7. Becker P, Carney LN, Corkins MR, et al. Academy of Nutrition and Dietetics; American Society for Parenteral and Enteral Nutrition. Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: indicators recommended for the identification and documentation of pediatric malnutrition (undernutrition). Nutr Clin Pract. 2015;30(1):147–161. https://doi.org/10.1177/0884533614557642 PMID: doi:10.1177/0884533614557642 [CrossRef]
  8. Ballard JL, Khoury JC, Wedig K, Wang L, Eilers-Walsman BL, Lipp R. New Ballard score, expanded to include extremely premature infants. J Pediatr. 1991;119(3):417–423. doi:10.1016/S0022-3476(05)82056-6 [CrossRef]1880657
  9. Lapillonne A, Braillon P, Claris O, Chatelain PG, Delmas PD, Salle BL. Body composition in appropriate and in small for gestational age infants. Acta Paediatr. 1997;86(2):196–200. https://doi.org/10.1111/j.1651-2227.1997.tb08868.x PMID: doi:10.1111/j.1651-2227.1997.tb08868.x [CrossRef]9055893
  10. Guellec I, Marret S, Baud O, et al. Intrauterine growth restriction, head size at birth, and outcome in very preterm infants. J Pediatr, 2015;167(5):975–981. doi:10.1016/j.jpeds.2015.08.025 [CrossRef]26384436
  11. Kapral N, Miller SE, Scharf RJ, Gurka MJ, DeBoer MD. Associations between birthweight and overweight and obesity in school-age children. Pediatr Obes. 2018;13(6):333–341. https://doi.org/10.1111/ijpo.12227 PMID: doi:10.1111/ijpo.12227 [CrossRef]
  12. Zemel BS, Riley EM, Stallings VA. Evaluation of methodology for nutritional assessment in children: anthropometry, body composition, and energy expenditure. Annu Rev Nutr. 1997;17(1):211–235. https://doi.org/10.1146/annurev.nutr.17.1.211 PMID: doi:10.1146/annurev.nutr.17.1.211 [CrossRef]9240926
  13. Corkins MR. Why is diagnosing pediatric malnutrition important?Nutr Clin Pract. 2017;32(1):15–18. https://doi.org/10.1177/0884533616678767 PMID: doi:10.1177/0884533616678767 [CrossRef]
  14. Barlow SEExpert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164–S192. https://doi.org/10.1542/peds.2007-2329C PMID: doi:10.1542/peds.2007-2329C [CrossRef]18055651
  15. Roy SM, Spivack JG, Faith MS, et al. Infant BMI or weight-for-length and obesity risk in early childhood. Pediatrics. 2016;137(5):e20153492. https://doi.org/10.1542/peds.2015-3492 PMID: doi:10.1542/peds.2015-3492 [CrossRef]27244803
  16. Park H, Bothe D, Holsinger E, Kirchner HL, Olness K, Mandalakas A. The impact of nutritional status and longitudinal recovery of motor and cognitive milestones in internationally adopted children. Int J Environ Res Public Health. 2011;8(1):105–116. https://doi.org/10.3390/ijerph8010105 PMID: doi:10.3390/ijerph8010105 [CrossRef]21318018
  17. Addo OY, Himes JH, Zemel BS. Reference ranges for midupper arm circumference, upper arm muscle area, and upper arm fat area in US children and adolescents aged 1–20 y. Am J Clin Nutr. 2017;105(1):111–120. https://doi.org/10.3945/ajcn.116.142190 PMID: doi:10.3945/ajcn.116.142190 [CrossRef]
  18. Mascarenhas MR, Zemel B, Stallings VA. Nutritional assessment in pediatrics. Nutrition. 1998;14(1):105–115. https://doi.org/10.1016/S0899-9007(97)00226-8 PMID: doi:10.1016/S0899-9007(97)00226-8 [CrossRef]9437695
  19. Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey. Anthropometry procedures manual. https://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf. Accessed October 17, 2019.
  20. Ogden CL, Li Y, Freedman DS, Borrud LG, Flegal KM. Smoothed percentage body fat percentiles for U.S. children and adolescents, 1999–2004. Natl Health Stat Report. 2011;(43):1–7. PMID:22164513
  21. Prado CM, Cushen SJ, Orsso CE, Ryan AM. Sarcopenia and cachexia in the era of obesity: clinical and nutritional impact. Proc Nutr Soc.2016;75(2):188–198. https://doi.org/10.1017/S0029665115004279 PMID: doi:10.1017/S0029665115004279 [CrossRef]26743210
  22. Hilmi M, Jouinot A, Burns R, et al. Body composition and sarcopenia: the next-generation of personalized oncology and pharmacology?Pharmacol Ther. 2019;196:135–159. doi:10.1016/j.pharmthera.2018.12.003 [CrossRef].
  23. Grummer-Strawn LM, Reinold C, Krebs NFCenters for Disease Control and Prevention (CDC). Use of World Health Organization and CDC growth charts for children aged 0–59 months in the United States. MMWR Recomm Rep. 2010;59:1–15. PMID:20829749
  24. Fenton TR, Kim JH. A systematic review and meta-analysis to revise the Fenton growth chart for preterm infants. BMC Pediatr. 2013;13(1):59. https://doi.org/10.1186/1471-2431-13-59 PMID: doi:10.1186/1471-2431-13-59 [CrossRef]23601190
  25. Spender QW, Cronk CE, Charney EB, Stallings VA. Assessment of linear growth of children with cerebral palsy: use of alternative measures to height or length. Dev Med Child Neurol. 1989;31(2):206–214. https://doi.org/10.1111/j.1469-8749.1989.tb03980.x PMID: doi:10.1111/j.1469-8749.1989.tb03980.x [CrossRef]2737373
  26. Hall JG, Allanson JE, Gripp KW, Slavotinek AM. Special Section. Syndrome-specific growth charts. Am J Med Genet A. 2012;158A(11):2645–2646. https://doi.org/10.1002/ajmg.a.35704 PMID: doi:10.1002/ajmg.a.35704 [CrossRef]23038170
  27. Nash A, Dunn M, Asztalos E, Corey M, Mulvihill-Jory B, O'Connor DL. Pattern of growth of very low birth weight preterm infants, assessed using the WHO Growth Standards, is associated with neurodevelopment. Appl Physiol Nutr Metab. 2011;36(4):562–569. https://doi.org/10.1139/h11-059 PMID: doi:10.1139/h11-059 [CrossRef]21854163
  28. Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study. BMJ.2000;320(7240):967–971. https://doi.org/10.1136/bmj.320.7240.967 PMID: doi:10.1136/bmj.320.7240.967 [CrossRef]
  29. Adams PF, Hendershot GE, Marano MACenters for Disease Control and Prevention/National Center for Health Statistics. Current estimates from the National Health Interview Survey, 1996. Vital Health Stat 10. 1999;(200):1–203. PMID:15782448
  30. Delano MJ, Moldawer LL. The origins of cachexia in acute and chronic inflammatory diseases. Nutr Clin Pract. 2006;21(1):68–81. https://doi.org/10.1177/011542650602100168 PMID: doi:10.1177/011542650602100168 [CrossRef]16439772
  31. Jensen GL, Bistrian B, Roubenoff R, Heimburger DC. Malnutrition syndromes: a conundrum vs continuum. JPEN J Parenter Enteral Nutr. 2009;33(6):710–716. https://doi.org/10.1177/0148607109344724 PMID: doi:10.1177/0148607109344724 [CrossRef]19892905
  32. Duncan A, Talwar D, McMillan DC, Stefanowicz F, O'Reilly DS. Quantitative data on the magnitude of the systemic inflammatory response and its effect on micronutrient status based on plasma measurements. Am J Clin Nutr. 2012;95(1):64–71. https://doi.org/10.3945/ajcn.111.023812 PMID: doi:10.3945/ajcn.111.023812 [CrossRef]
  33. Ingenbleek Y, Young V. Transthyretin (prealbumin) in health and disease: nutritional implications. Annu Rev Nutr. 1994;14(1):495–533. https://doi.org/10.1146/annurev.nu.14.070194.002431 PMID: doi:10.1146/annurev.nu.14.070194.002431 [CrossRef]7946531
  34. Norman K, Stobäus N, Gonzalez MC, Schulzke JD, Pirlich M. Hand grip strength: outcome predictor and marker of nutritional status. Clin Nutr.2011;30(2):135–142. https://doi.org/10.1016/j.clnu.2010.09.010 PMID: doi:10.1016/j.clnu.2010.09.010 [CrossRef]
  35. Dwivedi D, Singh S, Singh J, Bajaj N, Singh HP. Neurodevelopmental status of children aged 6–30 months with severe acute malnutrition. Indian Pediatr.2018;55(2):131–133. https://doi.org/10.1007/s13312-018-1245-0 PMID: doi:10.1007/s13312-018-1245-0 [CrossRef]29503269
  36. Abessa TG, Bruckers L, Kolsteren P, Granitzer M. Developmental performance of hospitalized severely acutely malnourished under-six children in low-income setting. BMC Pediatr. 2017;17(1):197. https://doi.org/10.1186/s12887-017-0950-5 PMID: doi:10.1186/s12887-017-0950-5 [CrossRef]29179758
  37. Grantham-McGregor SM, Fernald LC, Kagawa RM, Walker S. Effects of integrated child development and nutrition interventions on child development and nutritional status. Ann N Y Acad Sci. 2014;1308(1):11–32. https://doi.org/10.1111/nyas.12284 PMID: doi:10.1111/nyas.12284 [CrossRef]24673166
  38. Sentongo T. Assessment of nutrition status by age and determining nutrient needs. In: Corkins MR, ed. The A.S.P.E.N. Pediatric Nutrition Support Core Curriculum. 2nd ed. Silver Spring, MD: American Society of Parenteral and Enteral Nutrition; 2015:531–666.

Key Domains to Be Encompassed During Comprehensive Nutrition Assessment

Anthropometric variables   Weight (kg), length (cm), height (cm), head circumference (cm)   Weight-for-length, BMI (kg/m2)   Mid arm circumference (cm)   Triceps skin fold thickness (mm)   Percentile Growth charts: Fenton, WHO growth standard, CDC growth reference   Use of z-scores Dynamism of growth   Change in growth z-score Duration of nutritional abnormalities   Acute (<3 month duration) vs chronic (>3 month duration) Etiology/pathogenesis of nutritional abnormalities   Dietary intakes and mechanism of nutritional imbalance Impact of nutritional abnormalities on the patient's functional outcomes

Nutrition Concerns Based on Physical Examination

Site Physical Examination Potential Nutritional/Metabolic Status
Skin Pallor Dry scaly skin Perifollicular hemorrhages Necklace distribution dermatitis, rough skin Acral distribution dermatitis Peri orifice (oral, vulval/perianal) distribution dermatitis Acanthosis Loss of gluteal fat Edema: swollen feet, ankles, indentation of skin with application of pressure Iron, copper, folate, vitamin B12, riboflavin deficiency Essential fatty acid and biotin deficiency; vitamin A excess or deficiency Vitamin C deficiency (scurvy) Niacin deficiency Zinc deficiency Biotin deficiency Obesity/metabolic syndrome Severe protein energy malnutrition Hypoproteinemia, edematous malnutrition
Nails Kolionychia (spoon-shaped nails) Transverse leukonychia (opaque white band affecting multiple nails) Haplonychia (soft nails) Beau's lines (transverse grooves or depression) Iron deficiency; also deficiency of riboflavin, vitamin C, and niacin (pellagra) PEM, zinc deficiency, pellagra (niacin), and inadequate dietarycalcium Deficiency of vitamins A, B6, C, and D and inadequate dietary calcium Period of severe illness: PEM, pellagra
Neck Enlarged thyroid (goiter, hypothyroidism) Iodine deficiency
Face Moon face Bilateral temporal wasting Apathy Edematous PEM (kwashiorkor) Severe PEM Chronic PEM
Mouth Oral mucocutaneous rash, angular stomatitis, cheilosis Bleeding gums Deficiency of vitamin B complex (riboflavin, niacin, B6, biotin), iron deficiency Vitamin C deficiency
Tongue Atrophic glossitis (burning tongue) Hypogeusia Deficiency of iron, riboflavin, B6, niacin, vitamin B12 Zinc deficiency
Eyes Night blindness, Bitot's spots, corneal keratosis, keratomalacia Vitamin A deficiency
Hair Dull, easily pluckable, hypopigmented Increased lanugo body hair Hypopigmented hair Brittle easily breakable hair Hair loss, alopecia PEM (kwashiorkor) History of significant weight loss PEM, copper deficiency Zinc deficiency Biotin deficiency, low ferritin; vitamin A toxicity
Dentition Excessive dental carries Inadequate fluoride; use of bottle at bedtime; increased consumption of sweet liquids
Abdomen Distension: hepatomegaly Distension: ascites Fatty liver from severe malnutrition Hypoproteinemia; edematous malnutrition
Bones Tibia bowing/genu varum Osteopenia, osteoporosis Rickets, vitamin D deficiency Vitamin D deficiency, copper deficiency
Musculoskeletal Muscle twitching: face vs carpal muscles, Chvostek vs Trosseau signs Enlarged costochondral junctions Vitamin D deficiency with hypocalcemia Rachitic rosary (vitamin D), scorbutic rosary (vitamin C)
Temperature Hypothermia Severe PEM, global malnutrition
Heart rate Low heart rate/bradycardia Tachycardia (cardiomyopathy) Tachycardia, lactic acidosis Severe PEM, global malnutrition Selenium deficiency (Keshan disease) Beriberi (thiamine deficiency)

Comparison of Percentiles, z-Scores, and Definitions of Growth Status

Percentile z-Score Height Weight Weight-for-Length Body Mass Index
≥97th ≥2 Tall stature Overweight Obesity Obesity
85th–97th 1 to 2 Normal Normal Overweight Overweight
3rd–97th −2 to 2 Normal Normal Normal Normal
3rd–16th −2 to −1 Normal At risk for underweight Mild malnutrition At risk for underweight
<3rd −2 to −3 Short stature Moderate underweight Moderate malnutrition Moderate underweight
<3rd < −3 Severe chronic mal-nutrition (stunted) Severe malnutrition (underweight) Severe acute mal-nutrition (wasting) Severe malnutrition (wasting)

Classification of Preterm and Newborn Infants by Birth Weight and Growth Percentile

Category Birth Weight
Term, large for gestation age >4,500 g
Term, normal for gestation age 2,500–4,499 g
Low birth weight <2,500 g
Very low birth weight <1,500 g
Extremely low birth weight <1,000 g
Micronate <750 g
Classification Birth Weight Percentile
Large for gestation age Birth weight >90th percentile
Small for gestation age; intrauterine growth restriction Birth weight <10th percentile

Gross Motor Function Classification System

Class Function
I Walks without limitation
II Walks with limitations
III Walks using a hand-held mobility device
IV Self-mobility with limitations, may use powered mobility
V Transported in a manual wheelchair
Authors

Timothy Sentongo, MD, is an Associate Professor of Pediatric Gastroenterology; the Director, Pediatric Nutrition Support; and the Director, Pediatric Gastrointestinal Endoscopy, Section of Gastroenterology, Hepatology and Nutrition, The University of Chicago Medical Center.

Address correspondence to Timothy Sentongo, MD, Section of Gastroenterology, Hepatology and Nutrition, The University of Chicago Medical Center, 5841 S. Maryland Avenue, Rm C-474, MC 4065, Chicago, IL 60637; email: tsentong@peds.bsd.uchicago.edu.

Disclosure: The author has no relevant financial relationships to disclose.

10.3928/19382359-20191017-01

Sign up to receive

Journal E-contents