AWM: Eating Frequency and Patterns (2013)

Study Design:
- Click here for explanation of classification scheme.
Quality Rating:
Research Purpose:

To investigate the relationship between breakfast type, energy intake, and BMI.

Inclusion Criteria:
None stated.
Exclusion Criteria:
  • unreliable dietary recall records (as identified by NHANES III protocol)
  • pregnant women
  • individuals younger than 18
  • subjects whose self-reported ethnicity was not white, African American, or Hispanic.
Description of Study Protocol:

Recruitment NA - NHANES III data was used.

Design Cross-sectional analysis of NHANES III dietary data.  Foods consumed at breakfast were categorized into 10 categories:

  • skippers
  • dairy
  • meat and eggs
  • fruits and vegetables
  • ready-to-eat cereals
  • cooked cereal
  • breads
  • quick breads
  • fats and sweets
  • beverages

  Subjects were assigned to a breakfast category if  all food and beverages consumed at breakfast were either:

  • from that breakfast category, or
  • that category contributed more calories to the meal than those of any other breakfast category.

Blinding used  NA

Intervention NA

Statistical Analysis ANCOVA with <0.01 set as critical p-value, with the following covariates:

  • age
  • gender
  • race
  • poverty level
  • smoking habits
  • alcohol intake
  • physical activity
Data Collection Summary:

Timing of Measurements  NA, cross-sectional

Dependent Variables BMI: measured in health exam

                                    energy intake:  24 hour recall

Independent Variables

 Breakfast type (10 categories):

  • skippers
  • dairy
  • meat and eggs
  • fruits and vegetables
  • ready-to-eat cereals
  • cooked cereal
  • breads
  • quick breads

    Control Variables

    • age
    • gender
    • race
    • poverty level
    • smoking habits
    • alcohol intake
    • physical activity
  • Description of Actual Data Sample:

    Initial N: not specifically stated - 40,000 persons were invited to participate in NHANES III

    Attrition (final N): 16,452 (7687 male, 8765 females).  N for some analyses are less due to missing values in covariates.

    Age: Numbers and percents in 7 age categories are listed.  In general, there are more young subjects and less elderly subjects, with a mean age of 43.9 years

    Ethnicity: 79% non-Hispanic whites, 11% non-Hispanic blacks, 10% Hispanics.

    Other relevant demographics: 18.66% had a Poverty Index Ratio <1.3; 28.52% were smokers.

    Anthropometrics BMI:

      • 2.6% were <18.5
      • 42.63% were 18.5-24.9
      • 32.48% were 25-29.9
      • 22.28% were >30.

    Location: U.S.

    Summary of Results:

    Of the 16,452 participants:

    • 20.05%    breakfast skippers
    • 17.14%    RTE cereals
    • 15.93%    breads
    • 11.93%    quick breads
    • 10.87%    meat and eggs
    • 4.23%      fats and sweets
    • 4.55%      dairy
    • 4.48%      fruits and vegetables
    • 4.76%      cooked cereal
    • 6.06%      beverages

     Other Findings

    • Subjects who ate RTE cereal, cooked cereal, or quick breads had a lower BMI compared to subjects who skipped breakfast or who ate meat and eggs (p<0.01, adjusted BMIs ranging from 25.46 for cooked cereal group to 27.04 for meat and eggs group and 27.11 for dairy products group). 
    • Breakfast skippers and fruit and vegetable eaters had the lowest energy (kcal) intake throughout the day (p<0.01, with values ranging from 2027.9 for breakfast skippers and 2046.0 for fruit and vegetables group to 2324.8 for the cooked cereals group and 2433.7 for the meat and eggs group).
    • The meat and eggs group had one of the highest daily energy intakes (2433.7) and one of the highests BMIs (27.04).
    Author Conclusion:

    People who eat cereal (cooked or ready-to-eat cereal) or quick breads for breakfast have significantly lower BMI than those who skip breakfast or who eat meats and eggs for breakfast.  This anaylsis provides evidence that skipping breakfast is not an effective way to manage weight and also suggests than an "on-the-run" meal style or high-fat food choices may also lead to less healthy weight management.

    Funding Source:
    Kellogg Company
    Food Company:
    University/Hospital: University of California
    Reviewer Comments:
    Interesting study that agrees with extant literature but also adds to the credibility of the findings by adjusting for several variables in a large sample.  Provides further evidence that skipping breakfast is detrimental to body weight, which is particularly interesting since breakfast skippers also reported lower energy intake in this study.  The composition of breakfast also appeared to be important to body weight.
    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) Yes
    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? N/A
      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? N/A
      3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) N/A
      3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? N/A
      3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
      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.) N/A
      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? N/A
      4.1. Were follow-up methods described and the same for all groups? N/A
      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%.) N/A
      4.3. Were all enrolled subjects/patients (in the original sample) accounted for? ???
      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? N/A
      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? N/A
      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? N/A
      6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
      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? N/A
      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? N/A
    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? No
      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