Adult Weight Management

AWM: Eating Frequency and Patterns (2013)


Howarth NC, Huang TT, Roberts SB, Lin BH, McCrory MA. Eating patterns and dietary composition in relation to BMI in younger and older adults. Int J Obes (Lond). 2007; 31(4): 675-684.

PubMed ID: 16953255
Study Design:
Cross-Sectional Study
D - Click here for explanation of classification scheme.
Quality Rating:
Neutral NEUTRAL: See Quality Criteria Checklist below.
Research Purpose:

To conduct an analysis of eating patterns, dietary composition and their relative associations with BMI in younger and older adult participants in a US national survey. The study hypothesis was that older subjects (aged 60 to 90 years) would have weaker associations of dietary factors with BMI compared to younger subjects (20 to 59 years).

Inclusion Criteria:

Data from participants in the USDA Continuing Survey of Food Intake by Individuals (CSFII) collected from 1994 to 1996 were used, a survey of 16,103 non-institutionalized individuals aged two to 90 years residing in the United States.

Exclusion Criteria:
  • Pregnant or lactating women
  • Individuals who were self-reported as food insecure (on welfare or Meals on Wheels or did not have sufficient or suitable food)
  • On medically related diets
  • Only completed one 24-hour recall
  • Did not provide height, weight or time of consumption for all eating occasions.
Description of Study Protocol:


Data from the USDA Continuing Survey of Food Intake by Individuals (CSFII) collected from 1994 to 1996 was used. This was a survey of 16,103 non-institutionalized individuals aged two to 90 years residing in the US that contained information on dietary intake by one or two non-consecutive multiple-pass 24-hour recalls (day one in person; day two in person or by telephone); socioeconomic, demographic and health parameters; and self-reported height and weight.


Cross-sectional study.

Statistical Analysis

  • Descriptive demographics and dietary variables were calculated and independent T-tests and X2 tests were used to compare characteristics between younger and older subjects
  • Energy and dietary composition variables across eating occasions were compared within and between age groups by analysis of variance (ANOVA) with Bonferroni adjustments for multiple comparisons
  • Multiple regression analysis was conducted to determine associations between energy intake and BMI in each age group. Multiple regression was also used to determine the relative associations of dietary composition and eating pattern variables with BMI in each age group.
  • Regression analyses were also conducted on the subset of individuals without self-reported chronic disease
  • The unweighted mean variation of rEI/pER x 100% and weighted partial R2s from regression analyses were calculated using SAS
  • T-tests, R2 and X2 tests and linear regression analyses were performed using SUDAAN v.8 and weighted for sampling design with alpha set at 0.05.
Data Collection Summary:

Timing of Measurements

Data collected from 1994 to 1996.

Dependent Variables

  • Body mass index (BMI)
  • Height and weight were self-reported.

Independent Variables

  • Eating patterns and dietary composition
  • One or two non-consecutive multiple-pass 24-hour recalls (day one in person, day two in person or by telephone)
  • Subjects self-reported the type of eating occasion at which each food was consumed: breakfast, brunch, lunch, dinner, supper or snack
  • Meal coding was standardized so there was no more than one each of breakfast, lunch and dinner, but multiple snacks were allowed.

Control Variables

  • Age
  • Sex
  • Race
  • TV viewing
  • Current smoking
  • Education
  • US region
  • Urbanicity
  • Income
  • Self-reported chronic disease.
Description of Actual Data Sample:
  • Initial N: 16,103 non-institutionalized individuals aged two to 90 years
  • Attrition (final N): 2,685 total respondents, including 1,792 younger aged 20 to 59 years and 893 older aged 60 to 90 years
  • Age: Younger adults aged 20 to 59 years and older adults aged 60 to 90 years
  • Ethnicity: 84% younger Caucasians (20 to 59 years) and 91% older Caucasians (60 to 90 years)
  • Other relevant demographics: 57% younger males and 55% older males
  • Anthropometrics: 65% of older individuals had disease, 13% of older individuals were current smokers and 58% of older individuals had less than a high school education
  • Location: Data collected from across the United States.
Summary of Results:

Key Findings

  • Mean reported energy intake was 96% and 95% of predicted energy requirements in younger and older subjects, respectively
  • Older subjects were less likely to skip meals, but meal skipping was associated with a higher snacking frequency in both age groups
  • In the younger group, skipping breakfast (β=0.20±0.09, P=0.03) and dinner (β=0.32±0.11, P<0.02) and in the older group, skipping breakfast (β=0.73±0.19, P<0.001) and lunch (β=0.33±0.11, P<0.001) were independently associated with increased snack frequency after controlling for socioeconomic and lifestyle factors
  • The percentage of subjects who ate less than 3, 3.5 to 6 and more than six times a day, did not differ significantly between age groups, being 15%, 75% and 10% in the younger group and 14%, 77% and 9% in the older group
  • Both age groups consumed the highest proportion of their total energy intake at dinner and while the younger group's lowest proportion of their total energy intake was consumed at breakfast the older group's lowest proportion of their total energy intake was consumed in snacks
  • Dinner was also highest in fiber density (g per mJ) for younger subjects, while breakfast was highest in fiber density for older subjects
  • Snacks were the least fiber-dense eating occasions in both age groups
  • A higher BMI in both age groups was associated with a higher total daily energy intake, and higher energy intakes at all eating occasions
  • In both age groups, eating frequency was positively associated with energy intake, and eating more than three times a day was associated with being overweight or obese.

 Other Findings

  • When energy intakes at all meals and snacks were entered simultaneously in a model predicting BMI, all were independently and positively associated with BMI in both the younger and older groups (P<0.0001 for all)
  • Fiber density was inversely associated with BMI and examination of the fiber density by percent energy from fat interaction indicated that a low fiber density coupled with a high percent energy from fat was positively associated with BMI.


Author Conclusion:

While no one eating occasion contributes more than any other to excess adiposity, eating more often than three times a day may play a role in overweight and obesity in both younger and older persons.  The data from this study suggests that a reduction in eating frequency may be one way to reduce excess energy intake in overweight and obese persons of all ages, while in younger persons additional advice on increasing dietary fiber and reducing dietary fat is warranted. Furthermore, older people may be less sensitive to satiety cues than younger people, despite having somewhat more regular eating patterns and choosing a more fiber-dense diet.

Funding Source:
Government: USDA/ERS/FANRP Grant number 43-3AEM-2-80088
Reviewer Comments:

Authors note the following limitations:

  • The previous analysis in younger subjects suggests that there may be differences between men and women in dietary composition relationships with BMI
  • The method of recording meals may have misclassified meals as snacks or vice versa
  • Regarding physical activity, we did not have a good measure but relied on TV viewing hours per day as a proxy of inactivity level
  • While the CSFII 1994 to 1996 may be considered somewhat out of date, it is a very rich data set with two days of dietary intake per participant compared with more recent surveys that contain only one day of dietary intake per person or rely upon the less precise food frequency questionnaires to determine intake.
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) N/A
  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) N/A
  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? 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%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  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.) No
  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? Yes
  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? 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? No
  7.1. Were primary and secondary endpoints described and relevant to the question? N/A
  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? No
  7.5. Was the measurement of effect at an appropriate level of precision? ???
  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