Efforts to improve the diets of children have largely focused on the school environment(Reference Carter and Swinburn1, Reference Bere, Veierod and Bjelland2). Reports of foods popularly sold in schools have bolstered concerns about the impact of the school environment on children’s nutrition overall(Reference Bell and Swinburn3). School environments may be influenced by government policy with regard to both what may be sold on the premises and curriculum content. However, children only attend school on about one-half of the days of the year (190–200 d for New Zealand (NZ) children)(4). In addition, only approximately one-third of children’s nutrient and energy intakes are consumed during school hours(Reference Regan, Parnell and Gray5). Meals are not provided by NZ schools, although food items are usually available for purchase at tuck shops/canteens, a situation similar to Australia and Denmark. This means that it is particularly important to consider the role of the non-school environment, lunches sourced from home, on overall intake.
The times and patterns of children’s eating on schooldays and non-schooldays (day category) differ, and therefore it might be expected that nutrient intakes also differ between day categories. However, there are very few published data describing and comparing intakes by day category, and where data are available they are from countries in which school meals are provided(Reference Cullen, Lara and de Moor6–Reference Cameron, Macdiarmid and Craig8). Texan children (9–12 years) consumed less energy and a slightly higher energy from fat on weekends(Reference Cullen, Lara and de Moor6). US children (6–11 years; 1994–1996 Continuing Survey of Food Intakes by Individuals) had no difference for energy intake, energy from fat or carbohydrate, but a lower intake of protein as a percentage of energy (%E), on Fridays and weekends(Reference Haines, Hama and Guilkey7). A small survey of Scottish children (5–17 years) found no difference in the intake of energy, fat, saturated fat (%E) or non-milk extrinsic sugars between term time v. holidays, or weekends v. weekdays(Reference Cameron, Macdiarmid and Craig8). However, data about foods consumed and intake of other nutrients have not been addressed in any of these studies.
Although nutrient intakes of NZ children are reported as satisfactory for most nutrients(Reference Parnell, Scragg and Wilson9) (nutrients of concern include calcium, iron and vitamin A(Reference Parnell, Scragg and Wilson9)), there is a need to explore whether day category has any association with intake of these nutrients. There is a high prevalence of overweight (21 %) and obesity (10 %) in NZ children(Reference Parnell, Scragg and Wilson9) and dietary efforts to address this issue have focused on making ‘healthy’ food choices in the school environment(10) but have not addressed the equally important non-school environment.
The present study of a nationally representative sample of children compares nutrient and food intake on schooldays v. non-schooldays, with ethnic comparisons.
Methods
The present study is a secondary analysis of the NZ 2002 Children’s Nutrition Survey, a cross-sectional survey of a national sample of children (5 –14 years), during the 2002 school year.
A school-based sampling frame was used, with an oversampling of Māori and Pacific children to allow for ethnic-specific analyses. Of the 190 schools sampled, 172 (91 %) participated in the study. Recruitment from each school was in proportion to the number of students on the school roll. Children were assigned to one of three ethnic categories: Māori, Pacific or New Zealand European and others (NZEO), with a different probability of selection by ethnicity, based on their distribution from the 2001 school rolls. Of the 4728 children invited to participate, 3275 (69 %) participated in the study.
Socio-economic status was assigned using the New Zealand Index of Deprivation (NZDep01), derived from the child’s residential address, and based on eight dimensions, including income, access to a car and living space(Reference Salmond and Crampton11). Details of the survey methodology are described elsewhere(Reference Parnell, Scragg and Wilson9). All thirteen NZ regional health ethics committees gave approval for the survey.
Trained interviewers collected dietary intake data using a computer-assisted three-pass 24 h dietary recall in children’s homes. Children recalled all food/drinks consumed in the 24 h before the interview. Nutrient intakes were calculated (NZ Food Composition database(12)). Foods consumed were coded to food groups for calculation of prevalence of consumption (Appendix).
Non-schooldays included weekends, national public holidays and school holidays(4). Children recalled intake during the 24 h before the interview; thus, recalls that included both schooldays and non-schooldays (n 703) were not included in these analyses. The remaining recalls were categorized by day category, as schooldays only or non-schooldays only.
Height and weight were taken at each child’s school using portable standardized equipment. BMI was calculated and the reference cut-off values of Cole et al.(Reference Cole, Bellizzi and Flegal13) were used to categorize children as normal, overweight or obese. BMI category was available for 2393 (93 %) children with recalls included in the present analysis.
Statistical analyses were carried out using the STATA statistical software package version 10·01SE (StataCorp, College Station, TX, USA). Survey commands used sampling weights and primary sampling units (schools) ensuring that the results were representative of the NZ population. Variables whose distributions were not normal were transformed to logarithms. Multiple linear regression was used to examine the relationship between day category and nutrient intake. Because age, sex, ethnicity, NZDep01 and obesity have been associated with food choices and/or nutrient intake, these variables were included in the model. Age was considered a categorical variable (5–6, 7–10 and 11–14 years) and NZDep01 status as quintiles. We estimated the adjusted mean nutrient intake for day categories based on these models. Logistic regression was used for estimating the prevalence (95 % CI) of consumers of food groups by day category, and interactions between day category, sex, age, ethnicity and BMI category were tested using the standard statistical techniques embedded in STATA. A P value of <0·05 was considered statistically significant.
Results
There were 2034 children whose 24 h dietary recall period covered schooldays; 538 children recalled non-schooldays (Table 1).
Characteristics of children
NZEO, New Zealand European and others.
*Non-schooldays are weekends, national and school holidays.
†BMI category was not available for 179 children.
Nutrient intake
Energy and micronutrient intake did not differ by day category. However, cholesterol intake on non-schooldays was slightly higher than on schooldays. The available carbohydrate, starch, sucrose and dietary fibre intakes were higher on schooldays than on non-schooldays (Table 2).
Mean daily nutrient intake, by schooldays and non-schooldays
Significant interaction between the effect of day category and BMI categorya and ethnicityb.
Nutrient intake is log transformed for skewness; data are presented as geometric means.
*Linear regression controlled for ethnicity, age, sex, New Zealand Index of Deprivation (NZDep01), BMI category, adjusted for survey weighting.
There was an interaction between BMI category and the effect of day category on vitamin C intake and on protein intake. Mean protein intake was higher on schooldays for obese children, but did not differ significantly by day category for normal/overweight. Obese children had higher vitamin C intake on non-schooldays, but intake by normal/overweight did not differ by day category. There was an interaction between ethnicity and day category on fructose and glucose intake; intakes were lower on non-schooldays for Pacific children, but did not differ significantly by day category for NZEO/Māori children.
Food groups
Table 3 lists all food groups in which at least 10 % of children consumed an item from the food group by day category, and presents the proportion of consumers of selected food groups. On schooldays, children were more likely to consume sandwiches, biscuits/crackers and fruit than on non-schooldays.
Proportion of children consuming selected food groups by day category and the OR for schoolday consumption
Significant interaction between the effect of day category and ethnicitya, BMI categoryb and sexc (see text).
*Logistic regression controlled for ethnicity, age, sex, New Zealand Index of Deprivation (NZDep01), BMI category, adjusted for survey weighting.
Collectively contribute †64 % daily starch, ‡67 % daily vitamin C, §65 % daily sucrose, ∥57 % daily fructose.
¶Just one child in the obese category on a non-schoolday consumed a snack bar.
There was a difference in the effect of day category on snack foods consumption, by ethnicity; while all ethnicities had a greater likelihood of consuming snack foods on a schoolday than a non-schoolday, the effect was more pronounced for Māori children.
There was a difference by day category in the consumption of snack bars by BMI category. Prevalence of intake did not differ by day category for overweight children, but snack bar consumption was higher on schooldays for normal and obese children.
On non-schooldays, more children consumed confectionery compared with schooldays. Hot chips consumption did not differ by day category for Pacific children, but more NZEO/Māori children consumed hot chips on non-schooldays than on schooldays.
There was a difference by day category on soft drink consumption, by ethnicity. There was no difference for Pacific children; NZEO/Māori children were less likely to have soft drinks on schooldays.
There was no difference in the odds of consuming pies/sausage rolls, cakes/muffins/puddings or ice cream by day category.
Discussion
To our knowledge, this is the first study to compare the intake of food and nutrients between schooldays and non-schooldays in a nationally representative sample of children. Despite differences in the proportion of consumers of some food groups between schooldays and non-schooldays, the majority of nutrient intakes (including energy) did not differ by day category.
The intake of carbohydrate was lower on non-schooldays. Sucrose intake was lower perhaps because fewer children consumed fruit and biscuits/crackers on non-schooldays, or because there was a difference in the quantity of sucrose-rich items being consumed. Sucrose intake on non-schooldays was lower despite 10 % more children consuming confectionery.
Fruit was consumed by more children on schooldays, contributing to the greater fructose and vitamin C intake on schooldays. Other food items more commonly consumed on schooldays included sandwiches, snack foods and snack bars. An Australian survey found similar items in children’s lunchboxes; typically containing ‘about one sandwich, two biscuits, a piece of fruit, a snack of either a muesli/fruit bar or some other packaged snack’(Reference Sanigorski, Bell and Kremer14). The most significant contributors to NZ children’s energy intakes on schooldays (09.00–12.00 hours) were snack foods (22 %) and biscuits (20 %); at lunchtime, sandwiches (33 %) and fruit (12 %)(Reference Regan, Parnell and Gray5). These data support 84 % of children’s statements that they bring ‘most’ of their food consumed at school from home(Reference Parnell, Scragg and Wilson9), as in Australia(Reference Regan16).
Consumption of ‘unhealthy’ foods is ubiquitous. For Australian children, fast foods, including hot chips and pies/sausage rolls, contributed ∼10 % energy at school and 11·8 % out of school(Reference Bell and Swinburn15). In NZ, the ‘villains’ of the tuck shop are considered to include pies/sausage rolls, hot chips and soft drinks/sweetened beverages. However, these are just as likely to be consumed on a non-schoolday. Hot chips are twice as likely to be consumed on a non-schoolday, and intake during school hours is negligible(Reference Regan16). Soft drinks and other sweetened beverages are considered to contribute to obesity(Reference Taylor, Scragg and Quigley17), but as the intake of powdered drinks/cordials did not vary by day category, and soft drink consumption was higher on non-schooldays for Māori/NZEO, the issues could not be adequately addressed by focusing solely on foods available on the school premises. This is in spite of the strenuous efforts by health professionals to encourage schoolchildren to choose water or milk to drink. It appears that, in agreement with previous research, children obtain or choose the foods that they prefer and foods that are readily available at home, and foods that they and their families and/or peers find convenient and affordable(Reference Larson and Story18). The data presented indicate that a hungry child in search of hot food in NZ, whether on a schoolday or non-schoolday, can more readily access hot chips or a pie than soup or a rice-based dish. In order to influence the food choices and nutrition of NZ schoolchildren, affordable and accessible food alternatives need to be available at home, in shopping malls and convenience stores and in school tuck shops. Pasta and rice-based dishes need to be stored in home refrigerators, sold in the context of fast-food outlets and as part of the offerings in the school environment. This has the potential to increase intakes of calcium and vitamin A among schoolchildren without increasing energy or fat intake.
The present study has some limitations: the classification of food groups means that the prevalence of consumption of some foods may be under-reported. For example, vegetable/meat/cheese fillings in sandwiches will not be counted. It is difficult to compare consumption within ‘school hours’ between day categories because patterns of consumption throughout the day are likely to vary, particularly in the oldest age group. For example, many teenagers may rise later on non-schooldays. While distribution of children’s characteristics (sex, ethnicity) varies by day category, this is accounted for in the regression.
Altering the school environment is one avenue to effect a positive change in children’s diets. However, as only approximately one-third of a child’s daily energy intake is consumed during school hours(Reference Regan, Parnell and Gray5, Reference Bell and Swinburn15) this is only a partial solution. The public health focus has been on the foods consumed by children at school, with emphasis on the regulation of foods sold at school tuck shops/canteens. Schools can influence on-site provision and policies can affect food choice such as prohibiting leaving school grounds during school hours. Schools may provide guidance on what may or may not be brought to school. However, the present study reinforces the fact that the family environment and what is provided from home is the mainstay of nutrition for NZ children. Where improvement is needed to children’s diets, attention must be made to the foods provided by parents, regardless of where they are consumed. Parents who are time constrained need to be able to provide for their children, directly or indirectly, a wider range of hot food items.
Acknowledgements
The Ministry of Health funded the 2002 Children’s Nutrition Survey (CNS). Other principal investigators for the survey came from the University of Auckland (David Schaaf, Robert Scragg) and Massey University (Eljon Fitzgerald). The authors declare that they have no competing interests. W.R.P. and N.C.W. were both principal investigators on the 2002 Children’s Nutrition Survey. N.C.W. and W.R.P. conceived the initial idea for the analysis. J.E.R. and P.M.L.S. managed the data. J.E.R. performed the statistical analyses and drafted the initial and final manuscripts. J.E.R. and A.R. performed relevant literature searches. W.R.P., N.C.W., P.M.L.S. and A.R. provided a detailed critical review. The authors thank Andrew Gray, Department of Social and Preventive Medicine, University of Otago, for his advice on statistical methodology. The authors also thank all participants in the CNS 2002.
Appendix
Food group definitions*
*Full list in Parnell et al.(Reference Parnell, Scragg and Wilson9)
