• 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • Hypromellose br Information about the participant s diet was


    Information about the participant's diet was collected using a three day food diary. Parents or participants were asked to record all they ate and drank on three consecutive days (2 weekdays and 1 weekend day). Participants were given written and verbal in-structions to complete the diary and were asked to record the time, type, brand, portion size of all food and drink. At the end of the recording period, the Hypromellose diary was checked for completeness and any clarification of entries was sought from parents of the child participating. These data were analysed using FoodWorks® 7 Pro. From these dietary data, the mean daily energy intakes were calculated and expressed as a percentage of their estimated energy requirement (EER). The age-appropriate Schofield equation was used to predict basal metabolic rate [27] and the physical activity level (PAL) from physical activity diaries (described below) was used to calculate estimated energy requirements. The intake for energy from fat, Hypromellose and protein was assessed against the Acceptable Macronutrient Distribution Range (AMDR) and the mean daily nutrient intake was calculated and expressed as a percent of their age-appropriate estimated average requirement (EAR) [28].
    1.2.3. Physical activity and screen time
    Physical activity was measured via a three-day self-reported diary, using a simplified version of activity dairies as described previously and collected on the same days as the dietary intake diaries [29]. Subjects were given verbal and written instructions with an example of how to complete the diary. At the end of the recording period, the diary was checked with a researcher for completeness and any clarification of recorded activities was sought from parents of the child participating. Each day was divided into 96 15 min intervals and the subjects were asked to record their activities on each day. On completion, these activities were categorised into nine levels according to their average energy costs, representing multiples of their respective metabolic equiva-lents (METs) [30]. Total daily METs values were calculated and averaged over the three days to give a PAL value for each subject. Time spent in daily moderate to vigorous intense activity and screen time daily was averaged across the three days. Results were compared to the recommendations that ‘Children and young peo-ple should accumulate at least 60 min of moderate to vigorous intensity physical activity every day’ and ‘limit their screen time to no more than 2 h per day’ [31].
    1.3. Statistical analysis
    Descriptive statistics were used to characterise the CCS. For the dietary and physical activity data, the control subjects did not have dietary intake or physical activity data recorded, so the proportion of the CCS sample who did not meet the physical activity
    guidelines, AMDR and EAR was assessed. The body composition of the CCS and controls were compared using independent t-tests and chi-squared for categorical data. Correlational analysis examined the clinical, dietary and physical activity variables associated with body composition, adjusting for age and sex. When multiple vari-ables were found to be significantly associated to the outcome variables (p < 0.05), a multivariable linear regression model was created, retaining only those predictors that were statistically significant.
    Table 2
    Comparison between body composition of survivors and controls.d,e
    BMI Z score
    Percent fat, % g
    Seventy-four children, adolescents and young adults between 6.5 and 24.7 years were recruited to the study between 2012 and 2014. The participants were treated for cancer during the period of 1995e2011, with the mean age at diagnosis of 4.3 ± 3.8 years and mean time since treatment of 9.4 ± 3.3 years. There were 53 sub-jects diagnosed with a haematological malignancy and 21 subjects with a solid tumour. Subject characteristics are presented in Table 1.
    Anthropometry and body composition results for the CCS and controls are reported in Table 2. There was no significant difference in the mean weight Z-score (p ¼ 0.63) and mean BMI Z-score (p ¼ 0.30) between the CCS and the healthy controls, however the CCS had significantly lower mean height Z-scores than the controls (p ¼ 0.03). According to BMI, 8% were underweight, 67% were normal weight, 23% were overweight and 2% were obese. Ninety-two percent of the matched controls were normal weight and 8% were overweight. There was a significant difference between the BCM of the CCS and the age and sex matched controls, with the CCS having a significantly lower BCMI (p ¼ 0.02) and BCMI Z-score (p ¼ 0.0001). The CCS had a significantly higher %FM (p ¼ 0.002) and FMI (p ¼ 0.003) than the controls. There was no significant difference in the FFMI (p ¼ 0.09) between the CCS and the controls.
    When CCS were separated based on BCMI Z-score into well-nourished and under nourished groups, 59% of CCS were consid-ered under nourished. The only significant difference in clinical, physical activity and dietary variables between the well-nourished and under nourished groups was for PAL, with malnourished sub-jects having a significantly lower PAL (1.39 ± 0.19) than well-