Pediatric Original Article

International Journal of Obesity (2012) 36, 925–930; doi:10.1038/ijo.2011.262; published online 10 January 2012

Location of breakfast consumption predicts body mass index change in young Hong Kong children

S P P Tin1, S Y Ho1, K H Mak2, K L Wan2 and T H Lam1

  1. 1School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong SAR, Hong Kong
  2. 2Student Health Service, Department of Health, Hong Kong SAR, Hong Kong

Correspondence: Dr SY Ho, School of Public Health, The University of Hong Kong SAR, 21 Sassoon Road, Pokfulam, Hong Kong. E-mail: syho@hku.hk

Received 17 May 2011; Revised 18 November 2011; Accepted 5 December 2011
Advance online publication 10 January 2012

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Abstract

Objective:

 

An association between weight gain and breakfast skipping has been reported, but breakfast location was rarely considered. We investigated the prospective associations between breakfast location, breakfast skipping and body mass index (BMI) change in a large cohort of Chinese children.

Design:

 

Our baseline cohort consisted of 113457 primary 4 (US grade 4) participants of the Hong Kong Department of Health Student Health Service in 1998–2000. Of these, 68606 (60.5%) had complete records and were successfully followed-up 2 years later. Data on breakfast consumption and location were collected at both time points along with other lifestyle characteristics. BMI was derived from objectively measured height and weight. Associations between breakfast habits and BMI change were assessed by multivariable linear regression, adjusting for demographic, socioeconomic and lifestyle characteristics.

Results:

 

At baseline, 85.3, 9.4 and 5.2% of children had breakfast at home, away from home and skipped breakfast, respectively. Prospectively, having breakfast away from home (vs at home) predicted a greater BMI increase over two years (β=0.15; 95% CI: 0.11–0.18). Breakfast skipping had a comparable, slightly smaller effect (0.13; 0.09–0.18).

Conclusion:

 

Both breakfast skipping and eating breakfast away from home predict greater increases in BMI during childhood, the effect being slightly stronger in the latter. Having breakfast, particularly at home, could have important implications for weight management and reducing obesity in children. Further research is required to gain insight into potential underlying mechanisms.

Keywords:

breakfast; body mass index; children; public health; hong kong

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Introduction

Childhood obesity is a major public health concern.1 Various studies have found an association between skipping breakfast and elevated body mass index (BMI).2, 3, 4, 5 However, to the best of our knowledge, the association between breakfast location and weight status is largely unexplored. Although meals away from home have been linked to weight gain,6, 7 research focused on breakfast is lacking. It is also unclear whether breakfast skipping or breakfast location is more strongly associated with weight status.

Eating away from home is more common among working adults and those with children,8 possibly due to time constraints and greater financial capacity. Parents’ eating habits may influence their children's9 and subsequently encourage them to eat away from home more often. The rush of modern living and extensive advertising of breakfast by fast-food restaurants makes it imperative to clarify the influence of breakfast location on weight status. As dietary habits track from a young age10 and affect health outcomes later in life,11 it is particularly important to focus the investigation on young children.

Hong Kong is a densely populated, fast-paced city where inexpensive fast food is easily accessible and widely promoted, making it a convenient and attractive alternative to eating at home. Typical local away-from-home breakfasts (for example, instant noodles and bread/buns with high sugar and fat content) are likely to be less nutritious and more calorie-dense than home-prepared food. This, coupled with increasing rates of childhood obesity demonstrated by the rise in prevalence of overweight among primary school children from 17.6% in 2001/02 to 21.3% in 2007/08 (Student Health Service (SHS), personal communication), makes Hong Kong an ideal location in which to investigate prospective associations between breakfast skipping, breakfast location and changes in BMI during childhood.

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Methods

Study sample

Methods and procedures of using data provided by the SHS, Department of Health, Hong Kong SAR were previously reported.12, 13 Briefly, SHS participants attended free annual appointments at 1 of 12 SHS centres located in different districts of Hong Kong. From primary 4 (P4; US grade 4), participants completed a biennial self-administered standardised health and lifestyle assessment questionnaire in Chinese. The data were stored and longitudinally linked with unique identity numbers in the SHS computerised database.

The baseline cohort consisted of 113457 P4 SHS participants from academic years 1998/1999 and 1999/2000. Attendance rates were 76.8% and 78.5%, respectively, of which 68606 children with complete records were successfully followed-up 2 years later in primary 6 (P6; US grade 6) and were included in the present analyses. A total of 30098 (26.5%) children were lost to follow-up. A further group of 14753 (13%) children were excluded because of missing data. At baseline, among those lost to follow-up, 81.9% ate breakfast at home, 10.7% ate breakfast away from home and 7.4% skipped breakfast. This distribution was similar to that of the 68606 children included in the present analysis, with a small Cohen's effect size14 of 0.04, indicating minimal differences in breakfast habits between the two groups.

Of the 68606 P4 children analysed, 50.8% were female, mean age was 9.85 (s.d.=0.61) years and mean BMI was 17.31 (s.d.=2.99) kgm−2. In addition, 81% of children were in Tanner stage 1 of pubertal development. Most children had parents with at least secondary school education (72.4%) and 96.7% had at least one employed parent.

Procedures and measures

The questionnaire included 20 close-ended questions, each with four possible responses. Some items of the questionnaire received a fairly narrow range of responses, thus, to avoid small number of subjects within response categories, the questionnaire variables concerned were dichotomised for the present analysis.

Breakfast habits were assessed by the question ‘I usually have breakfast at…’ Children who selected ‘fast food stall/cafeteria/restaurant’ or ‘some other places’ were considered to have eaten breakfast ‘away’ from home. Other available responses included eating at ‘home’ or having ‘no breakfast at all’, and the latter was considered as skipping breakfast.

Four baseline diet-related variables, including lunch consumption habit and frequency of fruit/vegetable, junk food (for example, confectionaries, fries) and milk intake, were considered during analyses. Two baseline physical activity/inactivity-related variables were also taken into account, including the frequency of extra-curricular physical activity (‘<3 times/week’ vs ‘greater than or equal to3 times/week’),15, 16 and the average daily hours of television watching (‘>2h vs ‘less than or equal to2h).17

Questionnaire validity and reliability

A total of 101 primary 5 (P5; US grade 5) SHS participants (93.1% breakfast eaters and 6.9% skippers) were recruited at a SHS centre to take part in a validation study. These children completed the 20-item health and lifestyle questionnaire described above. A parent of each child also completed the same questionnaire in relation to their child's health and lifestyle behaviours. The breakfast assessment question yielded an agreement of 83.2%, demonstrating acceptable validity of the question for our main study variable.

We also examined the test-retest reliability of the questions of interest. Two weeks after the validation study, 82 (81%) of the P5 participants were successfully contacted via telephone and completed the questionnaire for the second time. Each responded to the same 20 questions from the previous questionnaire for the second time. The breakfast assessment question yielded an agreement of 91.5% and a moderately high intra-class correlation coefficient (ICC) (0.575, 95% CI: 0.411–0.704, P<0.001). Moderate ICCs were observed for questions assessing other lifestyle characteristics (0.431–0.580, all P<0.001).

Information on sex, age, weight status, pubertal development and socioeconomic status (SES) were also available in the SHS database. Weight (to the nearest 0.1kg) and height (to the nearest 0.1cm) were measured by trained nurses using calibrated equipment during annual SHS appointments. The weight status of subjects was defined according to International Obesity Task Force18 standards, which provide age- and sex-specific BMI cutoff values that classify individuals as underweight, normal weight, overweight or obese.18, 19

Pubertal development was assessed in P5 by SHS doctors using Tanner stages I–V. In this study, pubic hair development was used as an indicator of pubertal development. Information on the highest parental education level (no schooling/kindergarten/primary, secondary/matriculation, tertiary) and occupational status (unemployed, manual job, clerical job/service industry, managerial/professional positions) was obtained when subjects first joined the SHS (usually primary 1 or grade 1). Both were used as proxies of SES.

The protocol for this study was approved by the Department of Health Ethics Committee (L/M 381/2006) and the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 06–408 T/1432). Given that cases were not identifiable from the SHS data, informed consent from participants and families was not required for the present secondary analysis.

Statistical analysis

Data analysis was performed using SPSS (version 17.0;. SPSS Inc., Chicago, IL, USA).

In cross-sectional analysis, the association between breakfast location and various anthropometric, demographic, socioeconomic and lifestyle characteristics of subjects were examined. The significance of each association was assessed using one-way ANOVA and the χ2-test.

Any potential bias introduced as a result of characteristic differences between children included and excluded from longitudinal analyses was examined. The two groups were compared in terms of baseline breakfast habit and other demographic, anthropometric, socioeconomic and lifestyle characteristics. Descriptive statistics were derived and Cohen's effect size, as a standardised measure of the difference between included and excluded children, was calculated.

Baseline breakfast habit was used to predict change in BMI (from P4 to P6) using multivariable linear regression (model 1a). Our decision to use change in BMI rather than BMI z-score as the primary outcome measure was based on several factors. BMI is a popular indicator of weight status for children20, 21 and has been suggested to explain more variance in body weight than BMI z-scores among children aged 10 years and younger.21 Furthermore, research suggests that change in BMI is more powerful and interpretable than change in BMI z-scores when assessing longitudinal changes in BMI.22 Previous longitudinal studies on breakfast habit and body weight have also used BMI change as a marker for weight change.2, 5 To partially account for changes in BMI attributed to normal growth and development, regression models accounted for pubertal development, baseline age and BMI. Models were also adjusted for SES indicators and lifestyle characteristics.

Some children reported a change in breakfast habits from baseline to follow-up. It is plausible that this could affect our results. Thus, we repeated analyses restricted to those children who reported consistent breakfast habits across both time points (n=55342; model 1b). Associations between change in breakfast habits from P4 and P6 (vs eating breakfast at home at both time points) and BMI change was also examined (model 2a). Regression models were adjusted for the same covariates included in model 1a.

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Results

Children included and excluded from final analyses had similar baseline characteristics. Compared with children excluded from the analysis, included children were slightly more likely to eat breakfast at home (85.3% vs 82.2%) and less likely to skip breakfast (5.2% vs 7.2%). There were fewer boys among the included (49.2%) than excluded (53.4%) children. Included children were slightly younger (mean age=9.85 years vs 10.12 years), and had a lower mean BMI (17.31kgm−2) than those who were excluded (17.62kgm−2). Among both groups, 9.9% had parents with at least tertiary education. The Cohen's effect size14 was small for breakfast habit (0.04), sex (0.06), mean BMI (0.10), highest parental education level (0.08) and various other socioeconomic, anthropometric and lifestyle characteristics (0.02–0.10). A moderate Cohen's effect size was observed for age (0.38), although the actual difference was small. Sub-group analysis, based on the breakfast habit response, yielded similar effect sizes between included and excluded children. The sex distribution of included subjects was similar to that of the corresponding Hong Kong population group (49.2% boys in our study sample, 51.5% boys in the general population). The two groups were also comparable in housing type and residential district. All three variables yielded small Cohen's effect size of 0.06, 0.02 and 0.01, respectively.

Cross-sectional analysis

At baseline, skipping breakfast or eating away from home was more common among children who were overweight (17.9%) or obese (23.1%) than those who were normal weight (13.6%; Table 1). Having breakfast at home was slightly more common among girls (85.8%) than boys (84.8%), among children who had parents with at least tertiary education (89.8%) and among those whose parents held a managerial/professional occupational position (87.2%). Breakfast skippers were slightly older (mean age: 9.91 years) than breakfast eaters (mean age: 9.85 years). Children who ate breakfast at home were also more likely to consume more milk, eat less junk food and spend less time watching television compared with those who skipped breakfast or ate away from home (all P<0.001; Table 2).



Most children reported eating breakfast at home (85.3% at baseline and 80.9% at follow-up; Table 3). However, the prevalence of breakfast skipping and eating away from home increased over time. The proportion of children who consumed breakfast away from home increased from 9.4% at baseline to 10.1% at follow-up, whereas breakfast skipping increased from 5.2 to 9.0%.


Prospective analysis

Skipping breakfast (β=0.13; 95% CI: 0.09–0.18) or eating away from home (0.15; 0.11–0.18) was associated with significantly larger increases in BMI over the two-year period when compared with eating at home (Table 4, model 1a). Children who skipped breakfast at both time points (0.18; 0.11–0.24) and those who ate away from home (0.21; 0.16–0.26) at both time points showed a significantly greater BMI increase than those who consistently ate at home (Table 4, model 1b).


Compared with children who ate breakfast at home in both P4 and P6, those who ate away or skipped breakfast at either time point showed a significantly greater BMI increase over 2 years (Table 5). Specifically, children who ate at home in P4 but ate away or skipped breakfast in P6 had comparable BMI increases (β=0.19; 95% CI: 0.15–0.23 and 0.18; 0.14–0.23, respectively). Children who ate at home at both time points had the smallest BMI increase (1.22kgm−2), followed by those who skipped breakfast in P4 but ate at home in P6 (1.30kgm−2), and those who ate away in P4 but ate at home in P6 (1.33kgm−2).


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Discussion

Various studies have reported the prevalence of breakfast skipping,2, 12, 23 but few have considered the prevalence by breakfast location. We found that 85.3% and 80.9% of children had breakfast at home in P4 and P6, respectively. Given the fast-paced urban lifestyle in Hong Kong where inexpensive, fast food breakfasts are easily available, the high prevalence of eating breakfast at home is somewhat surprising. However, young children are highly dependent on their parents to supply food.24 Hence, most parents may provide their young children with breakfast at home before going to work and sending their children to school.

In cross-sectional analysis, we found that breakfast skipping was most common among children with less educated parents, whereas having breakfast at home was most common among children with highly educated parents. These findings support the results of previous studies that relate lower SES to unhealthy breakfast habits.25 This observation is not surprising as it is known that young children's dietary habits are influenced by their parents’ nutritional knowledge.26 Parents with higher levels of education tend to make healthier food choices,27 and this is likely to be reflected in their child's dietary patterns. It is likely that financial capacity influences food choices when eating out, thus cheaper, less healthy, convenience food will often be chosen over healthier, more expensive restaurant food. Nutrition education should be targeted at less educated parents, and their children, to encourage eating at home.

We detected no obvious relation between highest parental occupational status and breakfast habit, although breakfast skipping was least common among children with parents who had manual jobs. Breakfast consumption may be more necessary for parents with manual jobs that have high energy requirements,28 a habit which may subsequently be adopted by their children.25, 29

In prospective analysis, breakfast consumption away from home in P4 (vs at home) predicted a greater BMI increase over two years (β=0.15, 95% CI: 0.11–0.18). Breakfast skipping had a comparable (0.13; 0.09–0.18) effect. This is an interesting contribution to the literature. Previously, we found a smaller BMI change difference between breakfast eaters (at and away from home) and skippers (0.11; 0.07–0.16).13 The present study adds to this by demonstrating an association between location of breakfast consumption and BMI change during childhood.

Among children with consistent breakfast habits in both P4 and P6, we found that compared with children who ate at home, those who either ate away or skipped breakfast experienced greater BMI increases. Interestingly, after those who ate at home at both time points, children who skipped breakfast in P4 but ate at home in P6 experienced the smallest BMI increases, followed by those who ate away in P4 but ate at home in P6. These results indicate the potential reversibility of the negative effect that skipping breakfast or eating away from home has on BMI, fulfilling one criterion for causality.

Breakfast skipping has been related to a cluster of unhealthy lifestyle characteristics12, 30, 31, 32 such as increased energy intake from high-calorie snacks which may mediate the association between breakfast consumption and BMI change.33, 34 Similarly, food prepared away from home is usually more energy-dense and may contain more total/saturated fat per calorie than home-prepared food.35, 36, 37 Increased frequency of eating out might also be related to unhealthy characteristics leading to weight gain. Our results suggest that the prospective association between breakfast habits and BMI change is independent of various lifestyle characteristics. However, future research investigating the relation between breakfast location and weight should include a more detailed assessment of breakfast and dietary habits (for example, portion sizes and quality of foods consumed at breakfast) to clarify underlying mechanisms.

Dietary habits of young children are influenced by their food environment.25 At home, apart from controlling food availability,38, 39 parents may influence children's food preference and consumption patterns39 by acting as role models.9 Hence, exposure to desirable breakfast habits of parents may have encouraged healthier breakfast consumption behaviour in children who ate at home, making them less susceptible to excessive weight gain. However, without detailed data on the breakfast habits of parents, we are unable to confirm the above speculation. We cannot rule out that children were exposed to unhealthy dietary habits of parents. Further studies should examine how parental breakfast habits affect the association between the breakfast eating location and body weight of children.

The main strength of our study is the large, population-based cohort of Hong Kong primary school children. The SHS is offered to all local primary school children across various districts of Hong Kong. As primary school education is compulsory and the SHS attendance rates are fairly high, our cohort is likely to be highly representative of all primary school children in Hong Kong. Second, although causation cannot be ascertained in this observational study, we have provided strong prospective evidence for the infrequently studied association between breakfast location and BMI. Furthermore, height and weight were objectively measured by trained nurses and we have demonstrated acceptable validity and reliability of our method of assessing breakfast habits.

There are some limitations of our study. First, breakfast habits and lifestyle factors were obtained using a simple questionnaire, making inaccuracy of recall among young children a potential problem.40 However, all items in the questionnaire achieved at least moderate test-retest scores, reinforcing the reliability of the self-report measures. Second, although the single items in the questionnaire were simple and straightforward to understand, a more detailed assessment of breakfast habits, to include, for example, more precise information about the location of breakfast consumption, would have provided a greater insight into the potential mediators of the association between breakfast habits and BMI change. Further studies should consider options including ‘on-the-go breakfasts’, a popular mode of breakfast consumption in Hong Kong partly attributable to the hectic lifestyles. In addition, future research should consider detailed dietary information, including portion sizes and nutritional intake. Third, as we focused on the location of breakfast consumption, not the location of food preparation, we cannot assume that food consumed at home was also prepared at home. Future studies should examine how food prepared at home (vs away from home) will affect the association between breakfast habits and body weight among children. We acknowledge that breakfast practices differ across countries and that our observations represent breakfast habits in Hong Kong, an area where school breakfast programmes are not implemented. Further research in other countries with school meal programmes should take this into consideration when assessing the association between breakfast habit and body weight. Finally, no standard definition of ‘breakfast’ was available. We recognise that some breakfast definitions include breakfast location and that study outcomes may differ according to definitions. However, as the possible responses to our breakfast assessment question contrasted breakfast locations well, we believe that the question adequately captured breakfast eating behaviour for our study purposes. Nevertheless, future studies would benefit by considering the use of standardised and clearly defined breakfast occasions to generate more comparable results.

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Conclusions

We have demonstrated that the location of breakfast consumption is associated with BMI change during childhood. As breakfast consumption location could prove to be a relatively simple behaviour to change, our research findings may have important implications for the prevention of excessive weight gain among children. Not only is it important to promote regular breakfast consumption among children, but also efforts should be made to encourage children to eat breakfast at home wherever possible.

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Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

This study was funded by the Health and Health Services Research Fund, Food and Health Bureau, Hong Kong SAR (05060781). We express our gratitude to all the staff and participants of the Student Health Service for their assistance in this study. We acknowledge Anita Lai for her help with data preparation and Gemma Knowles for her editorial assistance. Funding: Health and Health Services Research Fund (05060781).

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