Data Analysis
Dietary data from the 24-hour recalls was analysed using the FoodWorks
nutrient analysis software program (version 8, 2015; Xyris Software,
Queensland, Australia). For food and drink items missing from the
FoodWorks database, nutrient content was obtained from product nutrition
panels and entered manually. Serves of food group intake (fruits,
vegetables, grains, meat/alternatives and milk/alternatives) were
automatically calculated by FoodWorks dietary analysis software (Xyris
software, Version 8). Foods were then classified as core or
discretionary foods by a researcher according to the 2013 Australian
Dietary Guidelines 34 whereby discretionary foods are
described as higher in energy density, saturated fat, sodium, sugars and
or alcohol). Manual extractions of discretionary foods were required in
some instances. For example, fruit juice is considered a discretionary
item so was separated from fruit intake. Food intake data was compared
to age and sex appropriate recommended serves for Australian children34. Dietary intake results for children in the general
Australian population and were obtained from the 2011-12 Australian
Health Survey 35,36 and used as a comparative norm.
Food group intake was expressed as a percent of serves recommended by
the Australian Dietary Guidelines 34 to allow for
comparisons between age groups.
A nutrient was included for dietary assessment if an appropriate
Nutrient Reference Value or Australian Dietary Guideline recommendation
existed. Incorporating all nutrients possible contributes to a thorough
assessment of dietary quality. Children’s nutrient intake was expressed
as a percentage of their age and sex appropriate estimated average
requirement (EAR) or adequate intake (AI) when EAR was not available37. The estimated energy requirement of each child was
calculated using age appropriate Schofield equations38 multiplied by a physical activity level of 1.5
(sedentary)39. The Schofield equation calculates an
estimation of a person’s basal metabolic rate based on their age, gender
and weight 40. Total energy intake was expressed as a
percentage of estimated energy intake (%EER) for each child which
allowed mean %EER to be calculated. Intake of carbohydrate, protein and
fat was also expressed as a %EER to determine macronutrient
distribution ranges and compare these to the acceptable macronutrient
distribution ranges for reduced risk of chronic disease34. Descriptive statistics for demographic and dietary
intake data were calculated using SPSS statistics (version 21.0, 2012;
IBM Corp., Armonk, NY).
Assumptions of normality did not appear to hold for some variables,
therefore for consistency non-parametric tests were used. Non-parametric
tests (Mann-Whitney and Kruskall-Wallis) were used to compare the
difference in dietary intake between patient sex (male versus female),
diagnosis (ALL versus other) and treatment intensity. As children
treated for ALL are at a higher risk of obesity than other diagnoses21, a comparison of the dietary intake between
children with ALL and other diagnoses was undertaken. Statistical
significance was set at a level of 0.05 with no adjustment for multiple
comparisons.