Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-28T17:11:37.910Z Has data issue: false hasContentIssue false

Associations between deprivation, attitudes towards eating breakfast and breakfast eating behaviours in 9–11-year-olds

Published online by Cambridge University Press:  01 June 2007

Graham F Moore*
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Katy Tapper
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Simon Murphy
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Rebecca Lynch
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Larry Raisanen
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Claire Pimm
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
Laurence Moore
Affiliation:
Cardiff Institute of Society, Health and Ethics, Cardiff University, 53 Park Place, Cardiff, CF10 3AT, UK
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objectives

To examine school-level relationships between deprivation and breakfast eating behaviours (breakfast skipping and the healthfulness of foods consumed) in 9–11-year-old schoolchildren and to examine whether attitudes towards eating breakfast mediated these relationships.

Design

Cross-sectional survey.

Setting

One hundred and eleven primary schools in Wales.

Subjects

Year 5 and 6 pupils within the 111 primary schools. Measures were completed by 4314 children. Analysis was conducted at the group (school) level, with each school representing one group.

Results

Deprivation was positively associated with breakfast skipping and consumption of ‘unhealthy’ items (i.e. sweet snacks, crisps) for breakfast. A significant negative association was found between deprivation and consumption of ‘healthy’ items (i.e. fruit, bread, cereal, milk). Deprivation was significantly inversely associated with attitudes towards eating breakfast. The relationships between deprivation and (1) breakfast skipping and (2) consumption of ‘healthy’ items for breakfast were mediated by attitudes towards eating breakfast. The hypothesis that attitudes mediated the relationship between deprivation and consumption of ‘unhealthy’ breakfast items was unsupported.

Conclusions

Deprivation is associated with adverse breakfast eating behaviours amongst children aged 9–11 years, in terms of breakfast skipping and the quality of breakfasts consumed. Socio-economic differences in attitudes towards eating breakfast are apparent amongst this age group, and appear to relate to social gradients in breakfast eating behaviours. Research is needed to examine the causal nature of these trends and to elucidate factors underlying the development of socio-economic differences in eating-related cognitions.

Type
Research Paper
Copyright
Copyright © The Authors 2007

In recent years, the gap between rich and poor in terms of chronic disease morbidity and life expectancy has widened, increasing awareness of the need to identify and address social inequalities in the determinants of healthReference Exworthy, Blane and Marmot1, Reference Wanless2. Whilst a number of structural, social and environmental factors contribute to this gradientReference von Rueden, Gosch, Rajmil, Bisegger and Ravens-Sieberer3Reference Deeming6, health behaviours appear to be important factorsReference Schnohr, Hojbjerre, Riegels, Ledet, Larsen and Schultz-Larsen7. Higher rates of smokingReference Graham, Francis, Inskip and Harman8, physical inactivity and alcohol consumption are typically observed in groups of lower socio-economic status (SES)Reference Schnohr, Hojbjerre, Riegels, Ledet, Larsen and Schultz-Larsen7. Class discrepancies in nutritional behaviours are observed throughout the life course, developing in childhood before tracking into adolescence and beyondReference James, Nelson, Ralph and Leather9. Intervention to support health-enhancing nutritional behaviours in childhood may therefore form an important part of a wider strategy to address inequalities in health.

Childhood nutritional interventions often target the school environment due to the capacity of this approach to reach large numbers of children simultaneously. Much school-based intervention, both in the USAReference Taras10 and the UKReference Tapper, Murphy, Moore, Lynch and Clark11, has centred around the provision of breakfast. There are a number of compelling justifications for this decision. Recent research suggests that skipping breakfast may have a variety of detrimental effects such as dental cariesReference Bruno-Ambrosius, Swanholm and Twetman12, dysmenorrhoeaReference Fujiwara13 and reduced weight controlReference Berkey, Rockett, Gillman, Field and Colditz14. Breakfast eating appears to contribute to the overall nutritional adequacy of the dietReference Nicklas, Bao, Webber and Berenson15, Reference Sjoberg, Hallberg, Hoglund and Hulthen16 and may provide an opportunity to consume foods such as grain products and fruits, widely regarded as important in the prevention of chronic disease17, Reference Liu, Sesso, Manson, Willett and Buring18. Furthermore, substantial evidence suggests that eating breakfast acutely improves cognitive performance in terms of concentration and memoryReference Pollitt, Gersovitz and Gargiulo19Reference Rampersaud, Pereira, Girard, Adams and Metzl21, with potential implications for educational attainment.

Breakfast skipping is more commonly observed in children of lower-SES parentsReference Keski-Rahkonen, Kaprio, Rissanen, Virkkunen and Rose22, Reference Hulshof, Brussaard, Kruizinga, Telman and Lowik23, with potential implications for inequalities in health. Furthermore, given the aforementioned educational benefits of breakfast eating, socio-economic differences in breakfast eating behaviours may also contribute to inequalities in educational attainment, which in turn appear to be intrinsically associated with health behavioursReference Laaksonen, Prattala, Helasoja, Uutela and Lahelma24Reference Koivusilta, Rimpela and Rimpela26. Examining the nature of associations between deprivation and breakfast eating behaviours and exploring factors which may mediate these trends are therefore of significant interest from both public health and educational perspectives.

Whilst most studies into cognitive determinants of children's health behaviour have been conducted with older samplesReference Rimal27, associations between health attitudes and behaviours have been demonstrated in children aged as young as 9 yearsReference Martin, Jacobsen, Lucas, Branch and Ferron28. A number of recent attempts have been made to explore cognitive correlates of children's breakfast eating behaviours. Data for the present study are derived from the evaluation of the Welsh Assembly Government's Free School Breakfast InitiativeReference Tapper, Murphy, Moore, Lynch and Clark11. A recent study focusing upon a sub-sample from this evaluation found that, amongst children aged 9–11 years, attitudes towards eating breakfast were significantly associated with the likelihood of skipping breakfastReference Tapper, Murphy, Lynch, Clark, Moore and Moore29. Furthermore, attitudes were associated with the quality of breakfast consumed, in that they were positively correlated with the total number of fruits, bread, cereals and milk products consumed and negatively correlated with the total numbers of sweet items and crisps. Similarly, a recent study demonstrated amongst 12–14-year-old children that attitudes towards eating breakfast were predictive of breakfast consumption, with both attitudes and subjective norms predicting intentions to eat breakfast more regularly in the next six monthsReference Martens, van Assema and Brug30.

In adults, cognitive and motivational determinants of eating behaviour have been described as mediators of the social gradient in health behaviours such as dietReference Wardle, Herrera, Cooke and Gibson31. That is, low SES leads to the formation of adverse cognitive structures relating to health behaviours, which in turn predict poorer health behaviours. Whilst little such research has been conducted with children, there is strong plausibility in the hypothesis that lower SES may be associated with less positive health-related cognitions in childhood, with implications for childhood nutritional inequalities. Whilst cognitions can be viewed as intrinsic to the individual, they are not static entities and external factors contribute to their formation and maintenance. Eating can essentially be viewed as a learned behaviourReference Hupkens, Knibbe, Van Otterloo and Drop32 developed through interaction with the social environment, and research supports the view that children from more deprived backgrounds typically interact with an environment which is less supportive of positive health-related cognitions and behaviours than their wealthier peers.

Social Learning TheoryReference Bandura33 provides a theoretical framework for understanding the role of social interactions in determining individual cognitions and behaviours. A central aspect of this theory is the importance of behavioural modelling, or vicarious learning through the examples of significant others. Consistent with this notion, research demonstrates that perceptions of parental eating behaviour such as breakfast eating habits are highly influential in determining the cognitions and behaviours of the childReference Rimal27, Reference Martens, van Assema and Brug30, Reference Tinsley34. Given that adults of lower SES tend to consume less healthful dietsReference Inglis, Ball and Crawford35, parental behavioural modelling may be expected to result in more adverse cognitive belief structures and behaviours in their offspring. Research has also identified class differences in food rules applied by mothers as relating to social class differences in children's nutritional behaviourReference Hupkens, Knibbe, Van Otterloo and Drop32. The provision of positive feedback for adherence to prescribed behaviours, or conversely negative feedback for breaking prescribed food rules, likely imparts messages about the perceived importance and outcome expectancies associated with eating behaviour, shaping and reinforcing beliefs and behaviours.

Studies applying ecological perspectives to the study of inequalities in adults' health behaviours have described SES as indicative of a broad social context which supports the development of poor health behavioursReference Grzywacz and Marks36. According to these perspectives, SES may impact upon behaviour by influencing the daily contexts of the individual, such as home and work environments (or in the case of children, school environments), the wider physical environment and macrosystemic influences. Furthermore, experiences of these daily contexts may influence behaviour through shaping the proximal cognitive determinants of behaviourReference Grzywacz and Marks36 such as attitudes. However, little such research has been conducted with children.

The present paper examines relationships between deprivation and breakfast eating behaviours, in terms of both breakfast skipping and the quality of breakfast. It is hypothesised that increased levels of deprivation will be associated with increased levels of breakfast skipping and consumption of less healthful breakfasts. Deprivation is also expected to be associated with more negative attitudes towards eating breakfast. Furthermore, it is hypothesised that attitudes towards eating breakfast will mediate the relationship between deprivation and breakfast eating behaviours. That is, deprivation leads to the formation of negative attitudes towards eating breakfast, which in turn leads to less healthful breakfast eating behaviours.

All of these variables are measured at the school level, with deprivation assessed in terms of the percentage of children within the school receiving free school meals. Exploring school-level trends in relation to dietary behaviours is useful as intervention largely occurs at this level, and hence identification of characteristics which determine school-level need for intervention may be of use in informing such intervention.

Methods

Participants

Participants were Year 5 and 6 (i.e. 9–11-year-old) primary-school children from 111 schools in nine Local Education Authorities across Wales. In each school, one class from Year 5 and one from Year 6 were randomly selected to complete the attitudes and recall questionnaires. Measures were completed by 4314 children in total. Initial data screening revealed substantial missing data for 103 children. These children were excluded from analysis, resulting in a sample size of 4211 children.

Measures

Socio-economic deprivation

Socio-economic deprivation was assessed using details of the percentage of children within each school receiving free school meals. This information was provided by the Welsh Assembly Government.

Attitudes towards eating breakfast

Attitudes were assessed using a questionnaire containing 13 statements referring to a variety of domains, such as concentration and behaviour, energy, and the general importance placed on breakfast. Children were asked to indicate the extent to which they agreed or disagreed with each statement by placing a tick in one of five boxes (agree a lot/agree a bit/don't agree or disagree/disagree a bit/disagree a lot). This measure was developed and validated with an independent sample prior to administration and further examination of validity and reliability was conducted using a sub-sample of participants from the present study. The measure demonstrated good construct and convergent validityReference Rimal27, and in the present study the measure demonstrated acceptable internal consistency (α = 0.753). For a fuller description, see Tapper et al. Reference Tapper, Murphy, Lynch, Clark, Moore and Moore29.

Dietary recall questionnaire

The questionnaire was a modified version of the Day in the Life QuestionnaireReference Edmunds and Ziebland37. Children were asked to list all foods and drinks consumed at chronologically ordered time points throughout the day (e.g. at home before school, on the way to school, at school before class started). Details of breakfast on the day of reporting (i.e. any foods consumed before the start of classes) were collected first, followed by details of the previous day's dietary intake. Only data relating to the two breakfast occasions were analysed for the purposes of the present study. Food-related questions were embedded within items related to the child's activities (e.g. ‘Did you watch television at home yesterday morning before school started?’ preceding the item ‘Did you have anything to eat or drink at home yesterday morning before school started?’) Activity-related items served a twofold purpose: first acting as prompts to enhance recall and second as distractions from the researcher's interest in eating behaviours, hence minimising social desirability biases. Children's accounts of portion size are generally unreliableReference Livingstone and Robson38, Reference Lytle, Nichaman, Obarzanek, Glovsky, Montgomery and Nicklas39 and these details were therefore not requested. This helped keep the questionnaire brief and easy to administer in large group settings with minimal supervision. As the questionnaire requests details of only two breakfast occasions (i.e. the morning of reporting and the previous morning) it is therefore most likely to be of most use at the group rather than individual level. This measure has been validated against 24-hour recall interviews with a sub-sample of children from the present study and offers an acceptable level of validity and reliability. For a fuller description of the measure and coding procedures, see Moore et al. Reference Moore, Tapper, Murphy, Lynch, Clark and Moore40.

Procedure

Parents were informed of the research in advance by means of a letter and information sheet sent home with children and were asked to contact the school if they did not wish their child to participate in the study. At each data collection, children were also informed that they were under no obligation to participate. Parents of 15 children requested that their child be excluded. The study received ethical approval from the Cardiff University Social Science Ethics Committee.

Both measures were completed in the morning as a supervised classroom exercise with a maximum class size of 40 children. For the attitudes questionnaire, to minimise conferring and ensure that children worked at the same pace and did not distract one another, the researcher read out the statements one by one and children marked their response for each statement after it was read out. For the dietary recall measure, the researcher read out the instructions and asked children to complete the questionnaire independently from one another. Children were asked to put their hands up when they had finished or if they needed help with spelling or further clarification of questions. Three members of the research team were present to assist children.

Statistical analysis

For each of six food categories (fruit, bread, cereal, milk products, sweet items and crisps), school-level mean intakes were calculated for each school, by adding intakes for each child during both breakfast occasions combined and dividing by the number of children within the school. Relationships between deprivation and each food category were then explored. Spearman's rank correlation was used for comparisons involving the variables fruit, sweet items and crisps, as data for these variables were positively skewed. Pearson's product moment correlation was used for all remaining comparisons, as data for these variables were normally distributed.

School-level mean attitudes scores were calculated for each school, by summing attitudes scores for each child and dividing the total by the number of children within the school. Exploration was then made of the relationship between attitudes towards eating breakfast and each of the six food categories, using Spearman's correlation for comparisons involving fruit, sweet items and crisps, and Pearson's correlation for all other comparisons.

From original individual-level data, the six food categories were then collapsed to form two variables: (i) total number of ‘healthy’ items consumed for breakfast across the two breakfast occasions (i.e. cereals, bread, milk products, fruit) and (ii) total number of ‘unhealthy’ items consumed for breakfast across the two breakfast occasions (i.e. sweet items and crisps). School-level means for each of these two variables were then calculated and analysed as dependent variables. A further dependent variable, (iii) percentage of breakfasts skipped, was calculated for each school. In calculating this variable, breakfast occasions where non-codable responses had been recorded were excluded. Data for variable (i) were normally distributed. However, data for variable (ii) and (iii) were positively skewed and log transformations were used to improve the distributions of these variables in preparation for the construction of regression models.

The hypothesised relationships between deprivation and each of the dependent variables, and the mediating influence of attitudes upon these relationships, were tested using a series of simple and multiple linear regression models in accordance with the procedures for mediational analysis set out by Baron and KennyReference Baron and Kenny41. First, the hypothesised mediator variable (attitudes) was regressed on the independent variable (deprivation). Each dependent variable (‘healthy’ items, ‘unhealthy’ items and percentage of breakfasts skipped) was then regressed on the independent variable. Each dependent variable was then regressed on the mediator variable.

Where exploratory analysis revealed significant relationships between (1) the independent variable (deprivation) and the hypothesised mediator variable (attitudes), (2) the independent variable and the dependent variable and (3) the hypothesised mediator variable and the dependent variable, multiple regression models were constructed, with deprivation and attitudes entered as independent variables. Where the significance of the contribution of deprivation was reduced by entry of the mediator variable, but both items remained significant, this was interpreted as partial mediation. Where entry of the hypothesised mediator variable lowered the significance of deprivation beyond the 5% level, with the mediator remaining significant, this was considered full mediation.

Results

Sample description

The percentage of children in each school entitled to free school meals ranged from 3.1% to 65.9% with the mean (26.1, standard deviation (SD) = 13.5) being higher than the national average of 17%. Mean scores of attitudes towards breakfast ranged from 3.03 to 4.09 (mean = 3.69, SD = 0.17). As a score of 3 corresponded to a neutral score, with anything above reflecting more positive than negative responses and vice versa, this indicates that school-level average responses were generally somewhat positive. Mean and SD intakes of foods from each of the six food categories are summarised in Table 1.

Table 1 Mean and standard deviation (SD) school-level consumption of items from each of six food categories, across two breakfast occasions (n=111)

Associations between deprivation, attitudes towards eating breakfast and breakfast food categories

Correlation coefficients for the associations between school-level mean consumption of items from each of the six food categories and (1) deprivation and (2) attitudes towards eating breakfast are displayed in Table 2. These indicate that deprivation was inversely associated with consumption of fruit and cereal for breakfast, so that as deprivation increases intakes of these foods decrease, and positively associated with consumption of sweet items and crisps. Similarly, attitudes towards eating breakfast were positively associated with consumption of cereals and fruit and inversely associated with consumption of sweet items and crisps. Neither deprivation nor attitudes was significantly associated with consumption of milk or bread for breakfast.

Table 2 Correlations between school-level deprivation and consumption of items from six food categories at breakfast and between attitudes towards breakfast and consumption of items from six food categories at breakfast (n=111)

* Pearson's product moment correlation.

Spearman's rank correlation coefficient.

Correlation is significant at the 5% level.

§ Correlation is significant at the 1% level.

Association between deprivation and attitudes towards eating breakfast

A simple linear regression model demonstrated that deprivation was significantly associated with attitudes towards eating breakfast, such that as deprivation increased, attitudes towards eating breakfast became increasingly negative (β = − 0.005, P < 0.001). Deprivation explained 15.4% of the variance in attitudes towards eating breakfast.

Mediation of the relationship between deprivation and consumption of ‘healthy’ items by attitudes towards eating breakfast

Simple regression models indicated: (1) a significant negative association between deprivation and the school-level mean number of healthy items eaten for breakfast (β = − 0.007, P < 0.05), so that as deprivation increased, consumption of healthy items for breakfast decreased; and (2) a significant positive association between attitudes towards eating breakfast and consumption of healthy items for breakfast (β = 0.822, P < 0.001). Entry of both deprivation and attitudes as independent variables in a multiple regression model resulted in a reduction of the significance of deprivation (see Table 3), with attitudes emerging as the sole predictor. The hypothesis that attitudes towards eating breakfast significantly mediated the relationship between deprivation and the consumption of healthy breakfast items was therefore supported.

Table 3 Linear regression model summary for prediction of healthy items consumed for breakfast by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)

SE – standard error.

Step 1 – R 2 = 0.079; Step 2 – R 2 = 0.18.

Mediation of the relationship between deprivation and consumption of ‘unhealthy’ items by attitudes towards eating breakfast

Simple regression models indicated: (1) a significant positive association between deprivation and the mean number of unhealthy items eaten for breakfast, so that as deprivation increased, consumption of unhealthy items for breakfast increased (β = 0.004, P < 0.001); and (2) a significant negative association between attitudes towards eating breakfast and the number of unhealthy items eaten for breakfast (β = − 0.261, P < 0.01). A multiple regression model with both variables entered as predictors indicated that both were significant independent predictors of the number of unhealthy items eaten for breakfast. Only a negligible reduction in the significance of deprivation was observed after the entry of attitudes (see Table 4). The hypothesis that attitudes towards eating breakfast mediated the relationship between deprivation and consumption of unhealthy items for breakfast was therefore unsupported.

Table 4 Linear regression model summary for prediction of unhealthy items consumed for breakfast by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)

SE – standard error.

Step 1 – R 2 = 0.16; Step 2 – R 2 = 0.19.

Mediation of the relationship between deprivation and breakfast skipping by attitudes towards eating breakfast

Simple regression models indicated: (1) a significant positive association between deprivation and the percentage of breakfasts skipped within the school (β = 0.011, P < 0.01), so that as deprivation increased, breakfast skipping increased; and (2) a significant negative association between attitudes towards eating breakfast and the percentage of breakfasts skipped (β = − 1.152, P < 0.01). A multiple regression model with both variables entered as predictors is summarised in Table 5. In this model, attitudes were the sole significant predictor of breakfast skipping, with the contribution of deprivation reduced below a significant level by the entry of the mediator variable. The hypothesis that attitudes towards eating breakfast mediate the relationship between deprivation and breakfast skipping was therefore supported.

Table 5 Linear regression model summary for prediction of breakfast skipping by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)

SE – standard error.

Step 1 – R 2 = 0.09; Step 2 – R 2 = 0.19.

Discussion

Consistent with previous research, the hypothesis that deprivation is related to increased breakfast skipping in 9–11-year-old schoolchildren was supportedReference Keski-Rahkonen, Kaprio, Rissanen, Virkkunen and Rose22, Reference Hulshof, Brussaard, Kruizinga, Telman and Lowik23. The present study adds to these findings evidence to suggest that deprivation is not only associated with breakfast skipping, but also with a decreased likelihood of consuming healthy breakfast items and an increased likelihood of consuming less healthy items before school. In particular, deprivation appeared to be associated with decreased consumption of fruits and cereals for breakfast and an increased likelihood of consuming sweets and crisps. Interventions aiming to address social inequalities in breakfast eating behaviours must therefore focus not only upon the promotion of breakfast eating per se, but also upon the promotion of healthy breakfast foods.

Attitudes towards eating breakfast were significantly associated with breakfast skipping, consistent with recent researchReference Martens, van Assema and Brug30. Furthermore, attitudes towards eating breakfast were significantly associated with both increased consumption of healthy breakfast items and decreased consumption of unhealthy breakfast items. This reinforces and extends the generalisability of the findings of a recent study investigating these trends in a particularly deprived sub-sample of children participating in the present studyReference Tapper, Murphy, Lynch, Clark, Moore and Moore29. In terms of individual food categories, associations with attitudes were strikingly similar to those observed for deprivation, although with the direction of correlations inverted. Attitudes towards eating breakfast were positively associated with consumption of fruits and cereals and inversely associated with consumption of sweet items and crisps.

Consistent with hypotheses, a strong social gradient in attitudes towards eating breakfast was observed, with high levels of deprivation associated with comparatively negative attitudes towards eating breakfast. Furthermore, the relationships between deprivation and both breakfast skipping and consumption of healthy items were mediated by attitudes towards eating breakfast. The mediating influence of attitudes upon the relationship between deprivation and consumption of less healthful breakfast items was however not significant.

Social gradients in terms of proximal cognitive determinants have not been researched extensively, and previous research has been limited to adultsReference Wardle, Herrera, Cooke and Gibson31. The present study indicates an association between deprivation and attitudes towards eating breakfast which appears to relate to social inequalities in breakfast eating behaviours at a young age. Intervention to improve attitudes towards eating breakfast in childhood may therefore impact significantly upon nutritional inequalities. However, the fact that the relationship between deprivation and consumption of sweet items and crisps consumed for breakfast was not mediated by attitudes perhaps suggests that environmental factors may be more influential in determining intakes of these foods, and such speculation merits further investigation.

Whilst the present study focuses upon a key cognitive determinant of behaviour, this is not intended to undermine the importance of wider social and environmental determinants of nutritional inequalities such as economic factorsReference Darmon, Ferguson and Briend42 and food availabilityReference Story, Neumark-Sztainer and French43. These findings should not be interpreted as indicating that changing eating behaviours is simply a matter of addressing individual differences. Rather, the strength of non-random patterning of attitudes at the school level, between groups defined by overall levels of deprivation, indicates that social and environmental processes associated with deprivation may impact upon the formation of these cognitions relatively early in life. Indeed, an examination of the influence of other variables such as food availability and food preferences on both attitudes towards breakfast and breakfast eating behaviours would be informative.

In addition, a greater understanding is needed of when and how eating-related cognitions develop, and how the different social contexts experienced by children from more deprived backgrounds impact upon the formation of these cognitions. Future research should focus upon further developing this field of research, applying principles of developmental psychology to understanding the formation and maintenance of these cognitions and identifying points at which they may be most amenable to positive change.

A number of strengths and weaknesses of the present study merit consideration when assessing its contribution to the evidence base. Key strengths include the use of measures of attitudesReference Tapper, Murphy, Lynch, Clark, Moore and Moore29 and dietary behavioursReference Moore, Tapper, Murphy, Lynch, Clark and Moore40 that have been rigorously validated for use with the present sample, and the use of a large, socio-economically diverse sample. Furthermore, analysis of trends relating to a continuous rather than categorical measure of SES is considered a strength as research demonstrates a graded relationship between SES and health outcomesReference Marmot, Ryff, Bumpass, Shipley and Marks44, with health status continuing to decrease as deprivation increasesReference Marmot, Smith, Stansfeld, Patel, North and Head45 in contrast to the lay perception of a dichotomous gap between rich and poor.

Data were however cross-sectional and therefore causal inferences cannot be fully established; thus longitudinal research is needed to explore the causal nature of the relationships reported. Furthermore, analysis was restricted to the group level, and individual sources of variation within these groups were not explored. The interactions between the social contexts associated with deprivation and individual factors in determining nutritional behaviour deserve significant attention and strong inferences about individual-level trends cannot be drawn from aggregate data. Obtaining valid, individual-level dietary data on a large scale is, however, problematic and exploratory findings from group-level data, such as those reported in the present study, are an important step in informing such research.

Acknowledgements

Sources of funding: L.M. is supported by a Public Health Career Scientist Award funded by the Welsh Assembly Government.

Conflict of interest declaration: The authors have no conflicts of interest to declare.

Authorship responsibilities: K.T., S.M., L.M. and R.L. developed the data collection methods. G.F.M., L.R. and C.P. prepared data for analysis. G.F.M. developed the research questions, performed statistical analyses and drafted the manuscript. All authors provided comments on the first draft and approved the final manuscript.

Acknowledgements: We thank Rachel Clark, Emily Harrop, Emily Warren, Iolo Madoc-Jones and Julian Buchanon for help with data collection; Zoe Macdonald, Hannah Lynch and Lorelei Simon for administrative assistance; and Odette Parry for contributions to project management and data collection. We would also like to thank the members of our advisory group and the Welsh Assembly Government for funding the research. In addition, we gratefully acknowledge the cooperation of all school staff, pupils and parents for participating in this study.

References

1Exworthy, M, Blane, D, Marmot, M. Tackling health inequalities in the United Kingdom: the progress and pitfalls of policy. Health Services Research 2003; 38(6): 1905–21.CrossRefGoogle ScholarPubMed
2Wanless, D. Securing Good Health for the Whole Population. London: HM Treasury, 2004.Google Scholar
3von Rueden, U, Gosch, A, Rajmil, L, Bisegger, C, Ravens-Sieberer, U. Socioeconomic determinants of health related quality of life in childhood and adolescence: results from a European study. Journal of Epidemiology and Community Health 2006; 60(2): 130–5.CrossRefGoogle ScholarPubMed
4Rahkonen, O, Laaksonen, M, Martikainen, P, Roos, E, Lahelma, E. Job control, job demands, or social class? The impact of working conditions on the relation between social class and health. Journal of Epidemiology and Community Health 2006; 60(1): 50–4.CrossRefGoogle ScholarPubMed
5Wheeler, BW, Ben-Shlomo, Y. Environmental equity, air quality, socioeconomic status, and respiratory health: a linkage analysis of routine data from the Health Survey for England. Journal of Epidemiology and Community Health 2005; 59(11): 948–54.CrossRefGoogle Scholar
6Deeming, C. Keeping healthy on a minimum wage. British Medical Journal 2005; 331(7521): 857–8.CrossRefGoogle ScholarPubMed
7Schnohr, C, Hojbjerre, L, Riegels, M, Ledet, L, Larsen, T, Schultz-Larsen, K, et al. . Does educational level influence the effects of smoking, alcohol, physical activity, and obesity on mortality? A prospective population study. Scandinavian Journal of Public Health 2004; 32(4): 250–6.CrossRefGoogle ScholarPubMed
8Graham, H, Francis, B, Inskip, HM, Harman, J; SWSS Study Team. Socioeconomic lifecourse influences on women's smoking status in early adulthood. Journal of Epidemiology and Community Health 2006; 60(3): 228–33.CrossRefGoogle Scholar
9James, WPT, Nelson, M, Ralph, A, Leather, S. Socioeconomic determinants of health – the contribution of nutrition to inequalities in health. British Medical Journal 1997; 314(7093): 1545–9.CrossRefGoogle ScholarPubMed
10Taras, H. Nutrition and student performance at school. Journal of School Health 2005; 75(6): 199213.CrossRefGoogle ScholarPubMed
11Tapper, K, Murphy, S, Moore, L, Lynch, R, Clark, R. Evaluating the Free School Breakfast Initiative in Wales: methodological issues. British Food Journal 2007; in press.CrossRefGoogle Scholar
12Bruno-Ambrosius, K, Swanholm, G, Twetman, S. Eating habits, smoking and toothbrushing in relation to dental caries: a 3-year study in Swedish female teenagers. International Journal of Paediatric Dentistry 2005; 15(3): 190–6.CrossRefGoogle ScholarPubMed
13Fujiwara, T. Skipping breakfast is associated with dysmenorrhea in young women in Japan. International Journal of Food Sciences and Nutrition 2003; 54(6): 505–9.CrossRefGoogle ScholarPubMed
14Berkey, CS, Rockett, HRH, Gillman, MW, Field, AE, Colditz, GA. Longitudinal study of skipping breakfast and weight change in adolescents. International Journal of Obesity and Related Metabolic Disorders 2003; 27(10): 1258–66.CrossRefGoogle ScholarPubMed
15Nicklas, TA, Bao, W, Webber, LS, Berenson, GS. Breakfast consumption affects adequacy of total daily intake in children. Journal of the American Dietetic Association 1993; 93(8): 886–91.CrossRefGoogle ScholarPubMed
16Sjoberg, A, Hallberg, L, Hoglund, D, Hulthen, L. Meal pattern, food choice, nutrient intake and lifestyle factors in The Goteborg Adolescence Study. European Journal of Clinical Nutrition 2003; 57(12): 1569–78.CrossRefGoogle ScholarPubMed
17US Department of Health and Human Services (DHHS). Healthy People 2010; Understanding and Improving Health. Washington, DC: US DHHS, 2000.Google Scholar
18Liu, SM, Sesso, HD, Manson, JE, Willett, WC, Buring, JE. Is intake of breakfast cereals related to total and cause-specific mortality in men? American Journal of Clinical Nutrition 2003; 77(3): 594–9.CrossRefGoogle ScholarPubMed
19Pollitt, E, Gersovitz, M, Gargiulo, M. Educational benefits of the United States school feeding program: a critical review of the literature. American Journal of Public Health 1978; 68(5): 477–81.CrossRefGoogle Scholar
20Pollitt, E. Does breakfast make a difference in school? Journal of the American Dietetic Association 1995; 95(10): 1134–9.CrossRefGoogle ScholarPubMed
21Rampersaud, GC, Pereira, MA, Girard, BL, Adams, J, Metzl, JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. Journal of the American Dietetic Association 2005; 105(5): 743–60.CrossRefGoogle ScholarPubMed
22Keski-Rahkonen, A, Kaprio, J, Rissanen, A, Virkkunen, M, Rose, RJ. Breakfast skipping and health-compromising behaviors in adolescents and adults. European Journal of Clinical Nutrition 2003; 57(7): 842–53.CrossRefGoogle ScholarPubMed
23Hulshof, K, Brussaard, JH, Kruizinga, AG, Telman, J, Lowik, MRH. Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. European Journal of Clinical Nutrition 2003; 57(1): 128–37.CrossRefGoogle ScholarPubMed
24Laaksonen, M, Prattala, R, Helasoja, V, Uutela, A, Lahelma, E. Income and health behaviours. Evidence from monitoring surveys among Finnish adults. Journal of Epidemiology and Community Health 2003; 57(9): 711–7.CrossRefGoogle ScholarPubMed
25Leganger, A, Kraft, P. Control constructs: do they mediate the relation between educational attainment and health behaviour? Journal of Health Psychology 2003; 8(3): 361–72.CrossRefGoogle ScholarPubMed
26Koivusilta, LK, Rimpela, AH, Rimpela, MK. Health-related lifestyle in adolescence – origin of social class differences in health? Health Education Research 1999; 14(3): 339–55.CrossRefGoogle ScholarPubMed
27Rimal, RN. Intergenerational transmission of health: the role of intrapersonal, interpersonal, and communicative factors. Health Education & Behavior 2003; 30(1): 1028.CrossRefGoogle ScholarPubMed
28Martin, SC, Jacobsen, PB, Lucas, DJ, Branch, KA, Ferron, JM. Predicting children's sunscreen use: application of the theories of reasoned action and planned behavior. Preventive Medicine 1999; 29(1): 3744.CrossRefGoogle ScholarPubMed
29Tapper, K, Murphy, S, Lynch, R, Clark, R, Moore, G, Moore, L. Development of a scale to measure 9–11 year olds' attitudes towards breakfast. European Journal of Clinical Nutrition, submitted.Google Scholar
30Martens, MK, van Assema, P, Brug, J. Why do adolescents eat what they eat? Personal and social environmental predictors of fruit, snack and breakfast consumption among 12–14-year-old Dutch students. Public Health Nutrition 2005; 8(8): 1258–65.CrossRefGoogle ScholarPubMed
31Wardle, J, Herrera, ML, Cooke, L, Gibson, EL. Modifying children's food preferences: the effects of exposure and reward on acceptance of an unfamiliar vegetable. European Journal of Clinical Nutrition 2003; 57(2): 341–8.CrossRefGoogle ScholarPubMed
32Hupkens, CLH, Knibbe, RA, Van Otterloo, AH, Drop, MJ. Class differences in the food rules mothers impose on their children: a cross-national study. Social Science & Medicine 1998; 47(9): 1331–9.CrossRefGoogle ScholarPubMed
33Bandura, A. Social Learning Theory. London: Prentice Hall, 1977.Google Scholar
34Tinsley, BJ. Multiple influences on the acquisition and socialization of children's health attitudes and behavior – an integrative review. Child Development 1992; 63(5): 1043–69.CrossRefGoogle ScholarPubMed
35Inglis, V, Ball, K, Crawford, D. Why do women of low socioeconomic status have poorer dietary behaviours than women of higher socioeconomic status? A qualitative exploration. Appetite 2005; 45(3): 334–43.CrossRefGoogle ScholarPubMed
36Grzywacz, JG, Marks, NF. Social inequalities and exercise during adulthood: toward an ecological perspective. Journal of Health and Social Behavior 2001; 42(2): 202–20.CrossRefGoogle ScholarPubMed
37Edmunds, LD, Ziebland, S. Development and validation of the Day in the Life Questionnaire (DILQ) as a measure of fruit and vegetable questionnaire for 7–9 year olds. Health Education Research 2002; 17(2): 211–20.CrossRefGoogle Scholar
38Livingstone, MBE, Robson, PJ. Measurement of dietary intake in children. Proceedings of the Nutrition Society 2000; 59(2): 279–93.CrossRefGoogle ScholarPubMed
39Lytle, LA, Nichaman, MZ, Obarzanek, E, Glovsky, E, Montgomery, D, Nicklas, T, et al. . Validation of 24-hour recalls assisted by food records in 3rd-grade children. The CATCH Collaborative Group. Journal of the American Dietetic Association 1993; 93(12): 1431–6.CrossRefGoogle Scholar
40Moore, GF, Tapper, K, Murphy, S, Lynch, R, Clark, R, Moore, L. Validation of a self-completion measure of breakfast foods, snacks and fruit and vegetables consumed by 9- to 11-year-old schoolchildren. European Journal of Clinical Nutrition 2006 Sep 20; [Epub ahead of print].Google ScholarPubMed
41Baron, RM, Kenny, DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 1986; 51(6): 1173–82.CrossRefGoogle ScholarPubMed
42Darmon, N, Ferguson, EL, Briend, A. A cost constraint alone has adverse effects on food selection and nutrient density: an analysis of human diets by linear programming. Journal of Nutrition 2002; 132(12): 3764–71.CrossRefGoogle ScholarPubMed
43Story, M, Neumark-Sztainer, D, French, S. Individual and environmental influences on adolescent eating behaviors. Journal of the American Dietetic Association 2002; 102(3): S4051.CrossRefGoogle ScholarPubMed
44Marmot, M, Ryff, CD, Bumpass, LL, Shipley, M, Marks, NF. Social inequalities in health: next questions and converging evidence. Social Science & Medicine 1997; 44(6): 901–10.CrossRefGoogle ScholarPubMed
45Marmot, MG, Smith, GD, Stansfeld, S, Patel, C, North, F, Head, J, et al. . Health inequalities among British civil servants: the Whitehall II Study. Lancet 1991; 337(8754): 1387–93.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Mean and standard deviation (SD) school-level consumption of items from each of six food categories, across two breakfast occasions (n=111)

Figure 1

Table 2 Correlations between school-level deprivation and consumption of items from six food categories at breakfast and between attitudes towards breakfast and consumption of items from six food categories at breakfast (n=111)

Figure 2

Table 3 Linear regression model summary for prediction of healthy items consumed for breakfast by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)

Figure 3

Table 4 Linear regression model summary for prediction of unhealthy items consumed for breakfast by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)

Figure 4

Table 5 Linear regression model summary for prediction of breakfast skipping by the independent variable alone (Step 1) and by the independent variable and the mediator variable combined (Step 2) (n=111)