Development and Evaluation of a New Infant Nutrition Screening Tool
Conditions: Malnutrition, Paediatric Failure to Thrive
Sponsor: University of Glasgow

 
01/09/2010                                                                                                            Version 1 
 
Development and Evaluation of a New Infant Nutrition Screening Tool  
 
 (Infant Yorkhill Malnutrition Score) 
 
 
Introduction  
A large number of children experience undernutrition related to or resulting from their 
illness. Hospitalized children are at a high risk of developing malnutrition particularly 
children with underlying disease and clinical conditions ( Joosten KF and Hulst JM, 
2008, 2010).  In addition malnutrition has been associated with an increase in length of 
hospital stay and consequently the cost of providing health care (Campanozzi A et al, 
2009). Therefore, the identification of children at risk of undernutrition is an important 
part of any programme for providing optimal health and treating of hospitalized patients. 
Quality Improvement Scotland has recently published standards for Food Fluid and 
Nutritional Care, which state that all patients should be screened for undernutrition on 
admission and periodically during their stay at hospital (NHS QIS 2003). 
 
Common methods of assessing nutritional status in children include a combination of 
dietary, anthropometric, biochemical measures and clinical signs. It is not possible for all 
admitted patients to have a complete nutritional assessment, but nutritional screening 
aims to identify those who are malnourished or at risk of becoming so to allow them to be 
assessed in more detail. In terms of anthropometric measures, the three most commonly 
used anthropometric indices are weight-for-height, height-for-age, and weight-for-age; 
According to WHO criteria, (WHO technical report, 1995) SD-scores<-2 for weight-for-
height and height-for-age describe acute and chronic malnutrition respectively. BMI as a 
new indicator has been developed by WHO for the first time to assess (the thinness of a 
child and hence its probability to indicate malnutrition of children) the weight of children 
(De Onis M et al, 2006). Weight-for-height index has been suggested as valid criteria for 
the identification and treatment progress of severe acute malnutrition in children (Isanaka 
S et al, 2009). These indexes can be used for screening of chronic and acute malnutrition 
but their diagnostic value is limited when attempting to identify children at early stages of 
undernutrition or patients at risk of deterioration in nutritional status as the result of 
medical condition.      
There is no agreement concerning the most appropriate criteria to be used. What is 
needed is a valid and accessible tool to establish the early identification and desirable 
management of nutritional risk in children. . There remains a great variation in the criteria 
used to define malnutrition, with each method having its own limitations.  
  
Pre-existing paediatric nutrition screening tools 
Recently a variety of nutritional screening tools have been developed for assessment of 
nutritional status of children in hospital setting, including; SGNA (Subjective Global 
Nutritional Assessment) (Secker and Jeejeebhoy, 2007), STAMP (Screening Tool for the 
Assessment of Malnutrition in Paediatric) (McCarthy H, et al. 2008 and More J, 2008), 

STRONG kids (Screening Tool Risk on Nutritional Status and Growth) (Jessi M. Hulst et 
al., 2010), and PYMS (Paediatric Yourkhill Malnutrition Score). These all use the 
internationally recognized predictors of undernutrition: clinical assessment, dietary intake 
and anthropometric measurements.  Each of these components bears a nutrition risk 
score, and overall score corresponds to the overall undernutrition risk of the patient.    
Although, recent studies have attempted to develop appropriate nutritional screening 
tools for children on admission, they are not useful for infants as they have not been 
validated except of STRONG kids (Screening Too Risk on Nutritional Status and 
Growth) which has been developed for hospitalized children as well as infants. 
  
Development of the infant Paediatric Yorkhill Malnutrition Score (iPYMS)  
A project team, consisting of senior nursing, dietetic, research academic and medical staff 
have developed a preliminary tool that would be both simple and quick to use.   
The infant nutritional screening tool will consist of four fields; 
   
1. Weight centile (using admission weight) 
2. Poor weight gain (by parental report)  
3. Reduced intake  
4. Effect on nutrition of current illness 
On admission this tool would be completed by the nurse (researcher initially). A score of 
0 or 1 classify patient at a low and median risk of undernutrition and a score of 2 or more 
reflects a high risk of undernutrition. 
 
Purpose of the Study 
The purpose of this study is to evaluate a proposed malnutrition screening scheme for 
infants - the infant Paediatric Yorkhill Malnutrition Screening(iPYMS)score to discover 
how well it distinguishes infants who are well-nourished from those undernourished or at 
risk of undernutrition (discriminant validity).  
We also need to compare it with results of other reputable nutritional measurements 
(concurrent validity). 
  
Hypotheses 
1. Most infants with low fat levels or at high risk of undernutrition with Paediatric 
Global Nutritional Assessment (PGNA) will be identified by a high infant 
Yorkhill Malnutrition Score (sensitivity). 
2. Infants with high infant Yorkhill Malnutrition Score will have lower fat levels 
than infants with low score (discriminant validity). 
3. There will be a moderate to good agreement and concordance between infants 
who have been screened with iPYMS and STRONG kids. 
4. Explore the utility of bioelectrical impedance and an infant eating behaviour scale 
in detecting infants with malnutrition 
5. Relate the malnutrition risk to length of hospital stay 
       
Method 
The researcher will pilot the study and this will be the opportunity receive feedback on 
the study design. The researcher will first complete the iPYMS scoring sheet for each 

child and then the questionnaires (SGNA and Infant EBQ) will be completed by the main 
carer of patient.   
The Paediatric Yorkhill Malnutrition Score ( PYMS) for infants must be able to 
distinguish those who are well-nourished from those malnourished or at risk of becoming 
so. It is based on internationally recognized predictors or symptoms of undernutrition 
(weight gain, reduced dietary intake), and therefore has face validity. However we need 
to compare it with results of other reputable nutritional measurements (concurrent 
validity), and its diagnostic value to screen the same patients with other currently used 
methods of undernutrition has to be tested (criterion validity). Accuracy is also important, 
considering how well the tool performs in detecting infants who really have problems and 
correctly identifying those who do not (sensitivity and specificity). So, we need further 
measurements to consider its sensitivity and the discriminant validity of the tool. We will 
study all screen positive and a sample of screen negative infants, using skinfolds and 
previous weight measurements and a parentally completed eating behaviour 
questionnaire. We will use this data to test the utility of PYMS score, growth trajectory, 
body mass index and behaviour questionnaire as predictors of low adiposity and stunting. 
The discriminant validity of the screening tool will be tested using body 
composition measurement using triceps (TSF) and subscapular skinfold thickness and the 
mid upper arm circumference (MUAC) and SGNA (Subjective Global Nutritional 
Assessment). To test the concurrent validity, the results from the infant screening tool 
will be compared with the results of STRONG kids (Screening Tool Risk on Nutritional 
Status and Grow). 
Reliability is also essential as the tool must produce similar results with repeat 
testing in the same circumstances and with different users where the patient’s state has 
not changed. User-group may affect tool performance; for example, whether doctors, 
nurses or dieticians conducted the screening. Thus, the reliability of the tool needs to be 
tested in future. 
 
Subjects 
Participant of the study will be all patients newly admitted to selected wards (medical and 
general surgical wards) at the Royal Hospital for Sick Children (and possibly RAH 
Paisley). An average of 8 patients per day are admitted to the relevant wards and we will 
aim to recruit a total of 200 over a 4 month period, after an initial pilot with up to 20 
patients. Children aged 1 -24 months are the subjects of this study because the purpose of 
this study is to develop a screening tool for infants.  
 
Exclusions 
 Patients in the short stay ward, intensive care or high dependency unit, Oncology 
unit, NICI and PICM, Cardiology (SA), 
 Patient who have been transferred from neonatal units and PICM and NICM. 
 
Sample Size- Power Calculation 
Using the Altman monogram 45 subjects in each group (135 it total) would give 90% 
power to detect a difference of 0.66SD (1 centile space) in skinfolds between any two of 
the 3 groups. 70 subjects in each group (210) gives 80% power to detect a difference of 
0.5SD in skinfolds between any two of the 3 groups.  

It is likely that not all children will have complete measures so we will aim to recruit 200 
subjects. 
 
Sample Selection 
Quota sampling will be used to obtain three equal groups of patients with different 
undernutrition scores (low, medium, high), until the desirable number of patients in each 
group is achieved. We will oversample high risk patients (expected to be only 10-20% of 
all patients) if necessary by screening all eligible patients using iPYMS and proceeding to 
full assessment for only those scoring high risk. In other word. a) The majority of patients 
screened at high risk of undernutrition. b) Every third child screened at medium risk of 
undernutrition. c) Every tenth child screened at low risk of undernutition (Gerasimidis K 
et al, 2010).   
We expect that malnutrition will be identified in between 10-30% of infant studied.  If 
previously unrecognised this means they can then be referred for further assessment. 
 
Recruitment 
The researcher will identify those patients eligible for screening by visiting the wards 
daily and obtaining details of new admissions from the nursing staff. She will then give 
an information leaflet to the patient’s carer to read and answer any immediate questions. 
After at least one hour she will return to the ward and if the carer is happy to participate, 
the researcher will ask him/her to complete a consent form. A copy of the consent form 
will be given to the carers and another will be placed in the child’s medical notes. 
The material will be in written in a form suitable for anyone who can read English. We 
will not be able to include those infants where neither carer was able to read English. 
Due to short admission periods usually most of the children will be discharged during the 
first day of stay. We aim to complete assessment on the next day after admission 
 
Outcome Measurements 
 
Parental questionnaires  
1. Global Nutritional Assessment for infants (SGNA) 
The researcher will ask the main carers of patients to complete the eating behavior 
questionnaire about the infant’s diet (type of milk. supplementary feeding and 
weaning diet), weight loss (poor weight gain), gastrointestinal symptoms, and daily 
activity. A rough visual assessment of the child’s muscle stores and fat will be carried 
out by the researcher. This is a global nutritional assessment procedure recently 
validated in paediatric patients as a measure of current and future nutrition risk 
(Secker & Jeejeebhoy, 2007). A copy of the assessment form and the article that 
describes this method is attached for the ethics committee attention. 
2. Infant EBQ 
This questionnaire has been developed using population data from a cohort study and 
is designed to identify infants at risk of weight faltering. This will be completed by 
the main carers of patients to assess the patient’s general appetite and eating 
behaviour 
 
Measurements 

3. Triceps (TSF) and subscapular skinfold thickness 
 Measurement of the thickness of the skin of the arm (triceps) and shoulder blade 
(subscapular) will be done as a measure of fat store. Briefly the parent will take off 
their top clothing and the researcher will measure the skinfold thickness with Holtain 
calipers. This measurement will be to some extent inconvenient for patients 
particularly those who are <1 year of age. 
4. Weight and length 
Weight will have been measured on admission. The researcher will re weight and 
measure length using the ward scales and recumbents stadiometer or our own portable 
equipment. 
5. Mid upper arm circumference (MUAC) 
The researcher will measure the circumference of their mid upper arm using a simple 
measuring tape. 
6. Bioelectrical impedance (BIA)  
This has been developed for assessment of nutritional status in children based on 
indices of lean and fat adjusted for body size (Wright CM et al, 2008). We want to 
discover whether this method is practical and effective in this young age range and 
how it relates to nutrition score. Self adhesive electrodes are attached to the right 
wrist and ankle while the child lies on the bed.  Three reading are taken, while, the 
electrodes are attached 
The infants may become briefly upset by being measured.  If they become very upset and 
uncooperative that measurement will be abandoned.    
 
Additional elements  
7. STRONG kids (Screening Tool Risk on Nutritional Status and Growth) 
The researcher will extract equivalent items for SGNA about the child’s food intake, 
diarrhoea, vomiting, weight loss or poor weight gain or no weight gain, during the 
few days before admission.  An observational assessment of patients will be also 
carried out by researcher in terms of diminished subcutaneous fat,  muscle mass and 
hollow face (subjective clinical assessment- the same as b). In addition, the researcher 
will use information recorded in the medical notes of the patient to assess patients’ 
underlying illness with a risk of malnutrition (Anorexia nervosa, Celiac disease, 
Cystic fibrosis, cardiac disease, and trauma). 
8. Length of hospital stay (LOS)  
Length of hospital stay as a secondary outcome will also be collected from hospital 
admissions statistics or through the notes.  
9. Growth trajectory  
Patients’ birth weight will be collected by the maternal report in order to calculate 
weight trajectory. 
 
Analysis-Statistics 
Data will be entered into the electronic database of SPSS v15. The paper data will have 
names and dates of birth recorded in order to allow linkage to hospital discharge data.The 
electronic data will have only enough personal information to link it uniquely with the 
paper record. The anonymised electronic data will be stored on the password protected 
university network. 

The raw measurements of body composition, height, weight. Skinfolds and mid upper 
arm circumference will be converted into standard deviation scores.  
 Height and weight will be converted into standard deviation scores according to 
the UK 1990 reference data. 
 Skinfolds and mid upper arm circumference will be converted into standard 
deviation scores according to the World Health Organization reference values. A 
value less than -2 standard deviation scores denotes a patient at high risk of 
undernutrition.  
Patient iPYMS outcome (nutrition risk), will be cross-tabulated with the respective 
nutrition risk from the Paediatric Subjective Global Nutrition Assessment or, body 
composition assessment. The proportion of patients at risk of undernutrition (according to 
body composition assessment and/or the Paediatric Subjective Global Nutrition 
Assessment) who were not identified by the iPYMS will be recorded as false negatives. 
On the contrary, the proportion of patients at low risk of undernutrition (according to 
body composition assessment and/or the Paediatric Subjective Global Nutrition 
Assessment) who were screened as at high risk of undernutrition by the iPYMS will be 
recorded as false positives. 
The mean values per group compared using t-test and anova and the categorical data 
compared using chi squared and logistic regression analysis. 
We will use this data to test the utility of PYMS score, growth trajectory, body mass 
index and behaviour questionnaire as predictors of low adiposity and stunting 
K-statistics will be used for Agreement of the methods.  
 
References  
Campanozzi A, Russo M, Catucci A, Rutigliano I, Canestrino G, Giardino I, Romondia 
A, Pettoello-Mantovani M (2009) Hospital-acquired malnutrition in children with mild 
clinical conditions. Nutrition; 25(5): 540-7.   
 
Cole T J, Freeman J V, Preece MA (1995) Body mass index reference curves for the UK, 
1990. Arch Dis Child ; 73(1): 25-29. 
 
De Onis, M. Onyango, A.W. Borghi, E. Garza, C and Yang, H. (2006), Comparison of 
the worlds health organization child growth standards and the national centre for health 
statistics/WHO international growth reference: implications for child health programmes, 
Public Health Nutrition, vol. 9/7, pp 942-947. 
 
Gerasimidis K, Keane O, Macleod I, Flynn DM, Wright CM (2010) A four-stage 
evaluation of the Paediatric Yorkhill Malnutrition Score in a tertiary paediatric hospital 
and a district general hospital.Br J Nutr; 19: 1-6.   
 
Hulst J M, Zwart H, Hop W C, Joosten FM (2010) Dutch national Survey to test the 
STRONG kids nutritional risk screening tool in hospitalized children. Clinical Nutrition; 
29, 106-111. 
 
Isanaka S, Villamor E, Shepherd S, Grais R F (2009) Assessing the impact of the 
introduction of the World Health Organization Growth Standards and weight-for-height 

z-score criterion on the response to treatment of severe acute malnutrition in children: 
secondary data analysis. Pediatrics; 123, e54-e59. 
    
Joosten KF and Hulst JM (2010) Malnutrition in pediatric hospital patients: Current 
issues. Nutrition; Aug 12,( abstract).     
      
Joosten KF and Hulst JM (2008) Prevalence of malnutrition in pediatric hospital patients. 
Curr Opin Pediatr; 20(5): 590-6. 
 
NHS Quality Improvement Scotland (2003) Clinical Standards: Food, Fluid and 
Nutritional Care in Hospitals ISBN 1-84404-194-8. 
 
 
More J. (2008) Don’t forget the undernourished children in our midst. J Fam Health Care; 
18(5): 159-60, (abstract).  
 
Secker D J and Jeejeebhoy KN (2007) Subjective Global Nutritional Assessment for 
children. American Journal Clinical Nutrition; 85(4): 1083-9. 
 
WHO Technical Report Series, Report of a WHO Expert Committee (1995), Physical 
Status: The Use and Interpretation of Anthropometry. World Health Organization. 
 
Wright C M, Sherriff A, Ward SCG, McColl J H, Reilly J J, Ness AR (2008) 
Development of bioelectrical impedance-derived indices of fat and fat-free mass for 
assessment of nutritional status in childhood. European Journal of Clinical Nutrition; 62, 
210-217.