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Associations of breakfast skipping with obesity and health-related quality of life: evidence from a national survey in Taiwan

Abstract

Objective:

This study investigated the associations of breakfast skipping with obesity and health-related quality of life (QOL). We also tested the hypothesis that there is a dose-dependent relationship between frequency of breakfast consumption and prevalence of obesity.

Subjects and Design:

This cross-section study used a national representative sample (n=15 340) from the 2005 Taiwan National Health Interview Survey. Breakfast skippers were defined as those who ate breakfast about once a week or less often and those who never ate breakfast. Individuals were classified as ‘obese’ if their body mass index was 27. Health-related QOL was assessed using the Medical Outcome Studies 36-Item Short-Form (SF-36) Health Survey. Logistic regression was used to examine the odds ratio of obesity and associated 95% confidence intervals (CIs) in breakfast skippers compared with breakfast eaters. Multivariable logistic regression modeling was used to adjust all risk estimates for covariates.

Results:

The unadjusted odds ratio of obesity in breakfast skippers was 1.23 (95% CI: 1.06, 1.43). The odds of developing obesity for breakfast skippers was 1.34 (95% CI: 1.15, 1.56) controlling for age, sex, marital status, educational level, monthly income, smoking, alcohol, betel nut chewing and exercise habit. The Cochran–Armitage trend test revealed that the prevalence rate of obesity decreased as the frequency of breakfast consumption increased (P=0.005). Breakfast skippers had significantly worse health-related QOL than breakfast eaters (P<0.001). Moreover, breakfast skippers had significantly lower scores in 5 out of 8 domain scores of the SF-36, namely general health perceptions (P<0.001), vitality (P<0.001), social functioning (P=0.036), emotional role (P<0.001) and mental health (P<0.001).

Conclusion:

The findings from this study add support to the potential role of breakfast eating in obesity prevention.

Introduction

The obesity epidemic has become a significant public health concern worldwide.1, 2, 3, 4, 5, 6 The prevalence rates of overweight and obesity in Taiwanese adults have increased in recent years, particularly in the male population.7, 8 Obesity is a risk factor of several major health problems including hypertension, diabetes, heart disease, certain cancers and other chronic diseases.9, 10 Thus, finding the factors contributing to obesity is of utmost importance.

Undesirable lifestyles have been implicated as causes of obesity. Eating patterns that may influence body weight include eating frequency,11, 12, 13 breakfast skipping12, 13, 14, 15, 16, 17, 18 and the frequency of meals eaten away from home.12 Among these, breakfast skipping has received a lot of attention recently. Cross-sectional studies have shown that breakfast skipping is associated with increased prevalence of overweight and obesity.12, 13, 14, 15 A prospective study also found that skipping breakfast was associated with weight gain.16 However, others have found contradictory results regarding the association of breakfast skipping with body mass index (BMI),17 or with overweight/obesity.18 The discrepancy may be due to differences in the definitions of breakfast skippers among studies. Therefore, it is important to explore whether the prevalence of obesity decreases as the frequency of breakfast consumption increases. In addition, most of the studies examined the relationship between breakfast consumption and body weight in adolescents and school-age children. Only a few studies investigated this relationship in the adult population. There has been a paucity of data elucidating the association of breakfast consumption with the prevalence of obesity in Taiwan. The primary aim of this study was to investigate the association between breakfast skipping and obesity in the Taiwanese adult population. In particular, the age- and sex-adjusted odds ratio and multivariate-adjusted odds ratio for obesity in breakfast skippers compared with breakfast eaters was examined. Moreover, we tested the hypothesis that there is a significant ‘dose-dependent’ relationship between the frequency of breakfast consumption and obesity as a binary response variable. Finally, the association of breakfast skipping with health-related quality of life (QOL) was examined.

Subjects and methods

This cross-sectional study used data from the 2005 National Health Interview Survey in Taiwan conducted by the National Health Research Institutes, National Bureau of Controlled Drugs and Bureau of Health Promotion, Department of Health, Taiwan. The 2005 National Health Interview Survey used a multistaged stratified systematic sampling scheme. The sampling unit of the first stage was the neighborhood (or village) within each city or county, the second stage was ‘Lin’ (the smallest unit for household registration in Taiwan) and the third stage was person. The target population for the original survey was 22 615 307 individuals whose households were registered in any one of the 23 counties or cities in Taiwan in the year 2004. A total of 187 neighborhoods (or villages) and 30 680 persons were sampled, resulting in a 1.35% sampling rate. Among them, 24 726 persons completed the survey (80.6% response rate). Excluding those individuals who were younger than 18 (n=3900) and older than 64 (n=2727), a total of 15 798 individuals were included in this study where individuals aged between 18 and 64. Among them, 458 were excluded from this analysis (455 subjects had missing values in any one or more investigated variables and 3 subjects had a BMI of greater than 50). The final sample size was 15 340.

The frequency of breakfast eating was assessed by the following question: ‘Typically, how many days a week do you eat breakfast?’. The five response categories were: (1) never, (2) about once a week or less often, (3) 2–3 days a week, (4) 4–5 days a week and (5) every day or almost every day. Breakfast skippers were defined as those who ate breakfast about once a week or less often and those who never ate breakfast. For trend analysis, the frequency of breakfast consumption was reclassified into three categories: ‘once a week or less often’, ‘2–3 days a week’ and ‘4 days a week or more often’. BMI was calculated using the following formula: weight (kg)/height2 (m2). Individuals were classified as ‘obese’ whether their BMI was equal to or greater than 27 based on the BMI cutoffs suggested by the Department of Health in Taiwan.

Health-related QOL was assessed using the Medical Outcome Studies 36-Item Short-Form (SF-36) Health Survey, which contains 36 items that yield eight domain scores.19 Physical functioning (10 items) measures limitations in physical activities, such as walking and climbing stairs. The physical role (four items) and emotional role (three items) domains assess problems with work or other daily activities because of physical health or emotional problems. The bodily pain (two items) domain examines limitations as a result of pain, and the vitality domain (four items) assesses energy and tiredness. The social functioning domain (two items) measures the effect of physical and emotional health on normal social activities, and mental health (five items) assesses happiness, nervousness and depression. The general health perceptions domain (five items) assesses personal health and the expectation of changes in health. All domains were scored on a scale from 0 to 100, where 100 represents the best possible health-related QOL.

Health-related habitual behaviors included in the current analysis were cigarette smoking, alcohol drinking, betel nut chewing and exercise. The presence of these habits was identified by four yes–no questions. These were the following: ‘Currently, are you drinking (alcohol-containing beverages)?’; ‘Have you ever smoked cigarettes?’; ‘Have you ever chewed betel quid?’ and ‘During the past 2 weeks, have you ever performed any exercise?’.

Demographic variables that were analyzed in this study included age in years, sex, marital status, educational level and monthly income in 1000 Taiwan dollars ( approximately US $30) (NT).

Continuous variables were presented as mean values and standard deviation. Categorical variables were presented as frequencies. Chi-square, Fisher’s exact and Mann–Whitney U-tests were used to compare the differences in demographic variables, body weight, BMI, health-related habitual behaviors and domain scores of SF-36 between groups (breakfast skippers versus eaters). Logistic regression was used to examine the risk (odds ratio) of obesity and associated 95% confidence intervals (CIs) in breakfast skippers compared with breakfast eaters. Multivariable logistic regression modeling was used to adjust all risk estimates for covariates (that is, age, sex, marital status, educational level, monthly income, cigarette smoking, alcohol consumption, betel quid chewing and exercise habit). The Cochran–Armitage test for trend was performed to determine whether there is a significant ‘dose-dependent’ relationship between the frequency of breakfast consumption and obesity as a binary response variable.

Results

The sample of this study included 7829 men and 7511 women aged 18–64 years (mean=38.69±12.65). Among them, 1239 persons were breakfast skippers and 14 101 persons ate breakfast regularly. Approximately, 8.1% of Taiwanese adults were breakfast skippers.

Among the entire sample, 2468 individuals (16.09%) were classified as obese. Of the female sample 12.53% were obese, whereas 19.50% of the men were obese. The age- and sex-specific prevalence rates of obesity are illustrated in Figure 1. In both sexes, the prevalence rate of obesity was higher in middle-aged adults (men: 21.86% and women: 20.40%) than in young adults (men: 18.28% and women: 8.12%).

Figure 1
figure1

Prevalence of obesity by sex according to age group.

The prevalence of obesity was significantly higher in breakfast skippers than in breakfast eaters (P=0.007; Table 1). The odds ratio of obesity in breakfast skippers was 1.23 (95% CI: 1.06, 1.43) compared with breakfast eaters (Table 2). The age- and sex-adjusted odds ratio for obesity in breakfast skippers was 1.38 (95% CI: 1.18, 1.60). The odds ratio of developing obesity for breakfast skippers was 1.34 (95% CI: 1.15, 1.56) controlling for age, sex, marital status, educational level, monthly income, smoking, alcohol, betel nut chewing and exercise habit. The unadjusted and adjusted odds ratios of obesity for individuals who ate breakfast once a week or less often and for those who ate 2–3 times a week compared with those who ate 4 times a week or more often are also presented in Table 2. The Cochran–Armitage trend test revealed that the prevalence rate of obesity decreased as the frequency of breakfast consumption increased (P=0.005; Figure 2). As seen in Table 1, breakfast skippers and breakfast eaters were significantly different in smoking, alcohol consumption, betel quid chewing and exercise habits (all P's<0.001).

Table 1 Demographic data of breakfast skippers and breakfast eaters
Table 2 Breakfast skipping in predicting obesity
Figure 2
figure2

Percentage of obesity by breakfast consumption. Test for trend: P=0.005.

A comparison of the SF-36 scores between breakfast skippers and breakfast eaters showed that those who regularly skipped breakfast had a significantly worse health-related QOL than those who regularly ate breakfast (P<0.001; Table 3). Moreover, breakfast skippers had significantly lower scores in 5 out of 8 domain scores of the SF-36, namely general health perceptions (P<0.001), vitality (P<0.001), social functioning (P=0.036), emotional role (P<0.001) and mental health (P<0.001). There were no statistically significant differences in all three physical domains of health including physical functioning, physical role and bodily pain between groups.

Table 3 Health status domain scores of breakfast skippers and breakfast eaters

Discussion

The findings from this study showed that skipping breakfast was associated with the increased likelihood of obesity in the Taiwanese adults even after controlling those variables frequently associated with obesity. The salient finding from this study was that in the Taiwanese adult population the prevalence of obesity decreased as the frequency of breakfast consumption increased. This finding supports our hypothesis that there is a dose-dependent relationship between the frequency of breakfast consumption and obesity.

Although the prevalence of breakfast skipping was only 8.1% in Taiwanese adults, the prevalence of obesity (16.09%) in this population has reached an epidemic proportion especially in the middle-aged men (21.86%) and women (20.40%). The finding that there was a dose-dependent relationship between the frequency of breakfast consumption and the risk of obesity not only underscores the protective role of eating breakfast in preventing obesity but also highlights breakfast skipping as a potential target for intervention in combating the obesity pandemic. Moreover, it is suggested that a recommendation to eat breakfast should be included in future weight loss programs.

Although the mechanism through which breakfast skipping contributes to the development of obesity remains undetermined, several potential mechanisms have been proposed including decreased energy expenditure, increased daily total energy intake and increased energy storage. Breakfast skippers were found to have lower levels of physical activity than breakfast eaters in adolescents,20 suggesting that decreased energy expenditure may very likely be a mediating mechanism of the association between breakfast skipping and obesity. In this study, breakfast skipping was associated with increased odds of developing obesity after controlling those variables frequently associated with obesity, including exercise habit, revealing that in addition to decreased energy expenditure there might be other factors mediating the association between breakfast skipping and weight gain in adult population.

Meal skipping results in extended periods of fasting that may induce a preprandial rise in ghrelin and in turn trigger subsequent meal initiation.21, 22 It has thus been suggested that increased daily total energy intake is a possible mechanism mediating the relationship between breakfast skipping and overweight/obesity. However, this notion was not supported by previous findings as total daily energy intakes of breakfast skippers were found to be either lower than23 or comparable with15 those of breakfast eaters in studies of adolescent or preschool populations.

An inverse relationship between meal frequency and prevalence of obesity has been shown in cross-sectional studies of adult populations,12, 13 whereas a prospective study of men revealed contradictory evidence that an increasing number of eating occasions was associated with a higher risk of weight gain.16 Another line of evidence suggests an association between consumption of snacks and skipping meals in adolescents,24 and an inverse association between consumption of snacks and overweight in female adolescents25 or obesity in female adults.13 More specifically, breakfast skippers were found to consume higher energy intakes from snacks, particularly higher energy intakes at afternoon and evening snacks in preschool children.15 It is thus likely that skipping breakfast results in weight gain through increased food intake later in the day when the body is less likely to expend the energy consumed and consequently increasing energy storage.

Skipping breakfast has been found to be associated with undesirable health outcomes such as insomnia,26 increased blood pressure27 and cluster with health-compromising behaviors such as smoking, alcohol and lack of exercise.20 In accordance with previous findings, the results from this study showed that breakfast skipping often coexists with other undesirable health-related habitual behaviors, as we found that breakfast skippers had higher rates of smoking, alcohol consumption, betel quid chewing and lack of exercise. In addition to the association of breakfast skipping with health-promising behaviors, psychosocial domains of health-related QOL were decreased in breakfast skippers in this study. Taken together, skipping breakfast may not be taken as a ‘cause’ of obesity per se, but evidence supports that it can be regarded as a health-compromising behavior or a behavior associated with poor health status.

Several limitations of this study must be addressed. First, this study did not account for the effect of daily energy intake on BMI because there was no information on daily calorie consumption available for analysis. Second, information on temporal distribution of the meals, food consumption frequency, daily consumption of snacks and daily energy expenditure were not available for analysis. Thus, the mechanism through which breakfast skipping causes weight gain remains to be elucidated. Finally, the effect of chronic illness on body weight was not controlled for when examining the relationship between breakfast consumption and obesity. Nevertheless, a comparison of the health-related QOL revealed that breakfast skippers and breakfast eaters were not significantly different in all three physical domains of health including physical functioning, difficulties in role performance because of physical health and limitations because of pain. Thus, the possibility that the association between breakfast consumption and obesity was influenced by the presence of chronic illness can be neglected. Despite these study limitations, this study included a national representative sample. Thus, the findings from this study add to the evidence to support the role of breakfast eating in the prevention of obesity.

References

  1. 1

    Katzmarzyk PT . The Canadian obesity epidemic: an historical perspective. Obes Res 2002; 10: 666–674.

    Article  Google Scholar 

  2. 2

    Kim Y, Suh YK, Choi H . BMI and metabolic disorders in South Korean adults: 1998 Korea National Health and Nutrition Survey. Obes Res 2004; 12: 445–453.

    Article  Google Scholar 

  3. 3

    Lissner L, Johansson SE, Qvist J, Rossner S, Wolk A . Social mapping of the obesity epidemic in Sweden. Int J Obes Relat Metab Disord 2000; 24: 801–805.

    CAS  Article  Google Scholar 

  4. 4

    Lee ZS, Critchley JA, Ko GT, Anderson PJ, Thomas GN, Young RP et al. Obesity and cardiovascular risk factors in Hong Kong Chinese. Obes Rev 2002; 3: 173–182.

    CAS  Article  Google Scholar 

  5. 5

    Reynolds K, Gu D, Whelton PK, Wu X, Duan X, Mo J et al., InterASIA Collaborative Group. Prevalence and risk factors of overweight and obesity in China. Obesity 2007; 15: 10–18.

    Article  Google Scholar 

  6. 6

    Flegal KM, Carroll MD, Ogden CL, Johnson CL . Prevalence and trends in obesity among US adults, 1999–2000. JAMA 2002; 288: 1723–1727.

    PubMed  PubMed Central  Google Scholar 

  7. 7

    Lin YC, Yen LL, Chen SY, Kao MD, Tzeng MS, Huang PC et al. Prevalence of overweight and obesity and its associated factors: findings from National Nutrition and Health Survey in Taiwan, 1993–1996. Prev Med 2003; 37: 233–241.

    Article  Google Scholar 

  8. 8

    Huang KC . Obesity and its related diseases in Taiwan. Obes Rev 2008; 1: 32–34.

    Article  Google Scholar 

  9. 9

    Bray GA, Bellanger T . Epidemiology, trends, and morbidities of obesity and the metabolic syndrome. Endocrine 2006; 29: 109–117.

    CAS  Article  Google Scholar 

  10. 10

    Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX et al. American Heart Association; Obesity Committee of the Council on Nutrition, Physical Activity, Metabolism, Obesity, and Cardiovascular Disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 2006; 113: 898–918.

    Article  Google Scholar 

  11. 11

    Bellisle F, McDevitt R, Prentice AM . Meal frequency and energy balance. Br J Nutr 1997; 77 (Suppl 1): S57–S70.

    CAS  Article  Google Scholar 

  12. 12

    Ma Y, Bertone ER, Stanek 3rd EJ, Reed GW, Hebert JR, Cohen NL et al. Association between eating patterns and obesity in a free-living US adult population. Am J Epidemiol 2003; 158: 85–92.

    Article  Google Scholar 

  13. 13

    Marín-Guerrero AC, Gutiérrez-Fisac JL, Guallar-Castillón P, Banegas JR, Rodríguez-Artalejo F . Eating behaviours and obesity in the adult population of Spain. Br J Nutr 2008; 100: 1142–1148.

    Article  Google Scholar 

  14. 14

    Croezen S, Visscher TL, Ter Bogt NC, Veling ML, Haveman-Nies A . Skipping breakfast, alcohol consumption and physical inactivity as risk factors for overweight and obesity in adolescents: results of the E-MOVO project. Eur J Clin Nutr 2009; 63: 405–412.

    CAS  Article  Google Scholar 

  15. 15

    Dubois L, Girard M, Potvin Kent M, Farmer A, Tatone-Tokuda F . Breakfast skipping is associated with differences in meal patterns, macronutrient intakes and overweight among pre-school children. Public Health Nutr 2009; 12: 19–28.

    Article  Google Scholar 

  16. 16

    van der Heijden AA, Hu FB, Rimm EB, van Dam RM . A prospective study of breakfast consumption and weight gain among U.S. Men. Obesity 2007; 15: 2463–2469.

    Article  Google Scholar 

  17. 17

    Williams P . Breakfast and the diets of Australian children and adolescents: an analysis of data from the 1995 National Nutrition Survey. Int J Food Sci Nutr 2007; 58: 201–216.

    Article  Google Scholar 

  18. 18

    Mota J, Fidalgo F, Silva R, Ribeiro JC, Santos R, Carvalho J et al. Relationships between physical activity, obesity and meal frequency in adolescents. Ann Hum Biol 2008; 35: 1–10.

    Article  Google Scholar 

  19. 19

    Tseng HM, Lu JFR, Tsai YJ . Assessment of health-related quality of life in Taiwan(II): Norming and validation of SF-36 Taiwan version. Taiwan J Pub Health 2003; 22: 512–518.

    Google Scholar 

  20. 20

    Keski-Rahkonen A, Kaprio J, Rissanen A, Virkkunen M, Rose RJ . Skipping and health-compromising behaviors in adolescents and adults. Eur J Clin Nutr 2003; 57: 842–853.

    CAS  Article  Google Scholar 

  21. 21

    Toshinai K, Mondal MS, Nakazato M, Date Y, Murakami N, Kojima M et al. Upregulation of Ghrelin expression in the stomach upon fasting, insulin-induced hypoglycemia, and leptin administration. Biochem Biophys Res Commun 2001; 281: 1220–1225.

    CAS  Article  Google Scholar 

  22. 22

    Nakazato M, Murakami N, Date Y, Kojima M, Matsuo H, Kangawa K et al. A role for ghrelin in the central regulation of feeding. Nature 2001; 409: 194–198.

    CAS  Article  Google Scholar 

  23. 23

    Nicklas TA, Reger C, Myers L, O’Neil C . Breakfast consumption with and without vitamin–mineral supplement use favorably impacts daily nutrient intake of ninth-grade students. J Adolesc Health 2000; 27: 314–321.

    CAS  Article  Google Scholar 

  24. 24

    Savige G, Macfarlane A, Ball K, Worsley A, Crawford D . Behaviours of adolescents and their association with skipping meals. Int J Behav Nutr Phys Act 2007; 4: 36.

    Article  Google Scholar 

  25. 25

    Sun Y, Sekine M, Kagamimori S . Lifestyle and overweight among Japanese adolescents: The Toyama Birth Cohort Study. J Epidemiol 2009; 3–0.

  26. 26

    Kaneita Y, Ohida T, Osaki Y, Tanihata T, Minowa M, Suzuki K et al. Insomnia among Japanese adolescents: a nationwide representative survey. Sleep 2006; 29: 1543–1550.

    Article  Google Scholar 

  27. 27

    Kollias A, Antonodimitrakis P, Grammatikos E, Chatziantonakis N, Grammatikos EE, Stergiou GS . High blood pressure prevalence in Greek adolescents. J Hum Hypertens 2009; 23: 385–390.

    CAS  Article  Google Scholar 

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Acknowledgements

This study is based (in part) on data from the National Health Interview Survey Original Database provided by the Bureau of Health Promotion, Department of Health, National Health Research Institutes and National Bureau of Controlled Drugs. The interpretation and conclusions contained herein do not represent those of Bureau of Health Promotion, Department of Health, National Health Research Institutes and National Bureau of Controlled Drugs.

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Correspondence to P-S Tsai.

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Huang, CJ., Hu, HT., Fan, YC. et al. Associations of breakfast skipping with obesity and health-related quality of life: evidence from a national survey in Taiwan. Int J Obes 34, 720–725 (2010). https://doi.org/10.1038/ijo.2009.285

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Keywords

  • breakfast skipping
  • health-related quality of life
  • health-related habitual behaviors

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