AWM: Eating Frequency and Patterns (2013)

Huang CJ, Hu HT, Fan YC, Liao YM, Tsai PS. Associations of breakfast skipping with obesity and health-related quality of life: Evidence from a national survey in Taiwan. Int J Obes. 2010; 34(4): 720-725.
PubMed ID: 20065977
Study Design:
Cross-Sectional Study
D - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:
  • 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. 
  • To study the hypothesis that there is a significant dose-dependent relationship between the frequency of breakfast consumption and obesity as a binary response variable
  • To examine the association of breakfast skipping with health-related quality of life (QOL).
Inclusion Criteria:
  • Taiwanese men and women between the ages of 18 and 64 years
  • Data used 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.
Exclusion Criteria:
  • Individuals who were younger than 18 years and older than 64 years
  • 458 individuals were also excluded because they had missing values in any one or more investigated variables
  • A BMI greater than 50.
Description of Study Protocol:


  • Subject data was used 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 survey used a multi-staged 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.


Cross-sectional study.

Statistical Analysis

  • 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 vs. eaters)
  • Logistic regression was used to examine the risk (odds ratio) of obesity and associated 95% CI in breakfast skippers compared with breakfast eaters
  • Multi-variate logistic regression modeling was used to adjust all risk estimates for covariates (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.


Data Collection Summary:

Timing of Measurements

Data from the 2005 Taiwan National Health and Interview Survey.

Dependent Variables

  • Obesity (classified as obese if BMI is higher than 27kg/m2)
  • Health-related quality of life:
    • Health-related Quality of Life (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
    • 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 plan (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.

Independent Variables

  • Eating breakfast or not
  • The frequency of eating breakfast was assessed by the question. "Typically, how many days a week do you eat breakfast?" The five response categories were:
    • Never
    • About once a week or less often
    • Two or three days a week
    • Four to five days a week
    • Every day or almost every day.

Control Variables

  • Age
  • Sex
  • Marital status
  • Educational level
  • Monthly income
  • Smoking
  • Alcohol
  • Betel nut chewing
  • Exercise habit.
Description of Actual Data Sample:
  • Initial N: 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 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). 
  • Attrition: The final sample size was 15,340 individuals. 458 were excluded from the analysis (455 had missing values in any one or more investigated variables and three subjects had a BMI of greater than 50).
  • Age: Between the ages of 18 and 64
  • Ethnicity: Taiwanese
  • Anthropometrics: Of the female sample 12.53% were obese, whereas 19.5% of men were obese
  • Location: Taipei, Taiwan.
Summary of Results:

Key Findings

d Breakfast Skippers Breakfast Eaters Statistical Significance of Group Difference
Odds of developing obesity

1.23 (95% CI: 1.06, 1.43)


P=0.007 for unadjusted


*1.34 (95% CI: 1.15, 1.56)


P<0.001 for multivariate adjusted

*Controlled for age, sex, marital status, educational level, monthly income, smoking, alcohol intake, betel nut chewing and exercise habit.

Other Findings

  • The unadjusted odds ratio of obesity in breakfast skippers was 1.23 (95% CI: 1.06, 1.43) and adjusted odds ratio was 1.34 (95% CI:  1.15, 1.56)
  • The Cochran-Armitage trend test revealed that the prevalence rate of obesity decreased as the frequency of breakfast consumption increased (P=0.005)
  • A comparison of the SF-36 scores between skippers and eaters showed that those who regularly skipped breakfast had a significantly worse health-related QOL than those who regularly ate breakfast (P<0.001)
  • Breakfast skippers had significantly lower scores in five out of eight domain scores of the SF-36, such as 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.
Author Conclusion:
  • 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. Furthermore, in the Taiwanese adult population the prevalence of obesity decreased as the frequency of breakfast consumption increased. This supports the original hypothesis that there is a dose-dependent relationship between the frequency of breakfast consumption and obesity.
  • The finding that there was a dose-dependent relationship between the frequency of breakfast consumption and the risk of obesity highlights breakfast skipping as a potential target for intervention in combating the obesity pandemic. This has clinical significance because it is suggested that a recommendation to eat breakfast should be included in future weight loss programs.
Funding Source:
Government: Bureau of Health Promotion, Department of Health, National Health Research Institutes and National Bureau of Controlled Drugs
Reviewer Comments:

Large, nationally representative sample. This study had several limitations. First, the study did not account for the effect of daily energy intake on BMI since 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 energy expenditure were not available for analysis. Finally, the effect of chronic illness on body weight was not controlled for when examining the relationship between breakfast consumption and obesity. 

Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) N/A
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) Yes
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) Yes
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? N/A
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? No
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) N/A
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? No
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? Yes
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes