Pediatric Weight Management


Lin BH, Morrison RM. Higher fruit consumption linked with lower body mass index. Food Review, 2002;25:28-32.
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 determine if people who eat more fruits and vegetables are thinner than those who eat lesser amounts.

Inclusion Criteria:

Not specified.

Exclusion Criteria:
2% of adults were underweight and were excluded from the analysis
Description of Study Protocol:


  • Cluster sampling designed to be representative of the US population as a whole (not described in article).


  • Participants from the Continuing Survey of Food Intake by Individuals 1994-96 and Supplemental CSFII Children’s Survey 1998.

Statistical Analysis

  • Compared average consumption by weight status
  • Regression analysis used to examine the effect of fruit and vegetable consumption on BMI, controlling for other variables.
Data Collection Summary:


  • No blinding.

Dependent Variables

  • Condition of being overweight or obese (BMI calculated from self-reported height and weight gathered in face-to-face interview).

Independent Variables

  • Fruit and vegetable consumption as servings per day (conversion of grams of food into servings, using USDA ARS pyramid servings database)
    • Examined total fruit (including juices)
    • Total vegetables (including juices)
    • White potatoes
    • Vegetables, excluding white potatoes (“other” vegetables)
  • Two-day diet record.

Control variables

  • Age classes for children and teens (divided by gender): five to nine, 10 to 12, 13+ years (self-reported)
  • Age for adults: Used age squared to control for BMI increase in young adults and decline among seniors (self-reported)
  • Gender (self-reported)
  • Race (self-reported).
Description of Actual Data Sample:

Final sample

  • 4,709 men
  • 4,408 women
  • 883 teens
  • 2,181 children
  • Total N=12,181.

Original Sample

  • Not described.


  • Teens: 13-18 years
  • Children: Five to 12 years.


  • Ethnically diverse but not specified in paper.


  • US-nationally representative.
Summary of Results:

Weak correlation with vegetable consumption

  • Overweight boys consumed less total vegetables (2.5 servings) than the three servings of at-risk and healthy weight boys and also less white potatoes
  • No differences among men
  • No differences among women, except overweight women ate more non-potato vegetables than healthy weight or obese
  • Potato consumption is positively correlated with BMI for both men and women
  • Higher consumption of “other” vegetables was associated with lower BMI for adult women
  • Similar findings for percentage of recommended vegetables.

Fruit Consumption

  • Fruit consumption was a more accurate predictor of body weight status than vegetable consumption
    • Diets with more fruit were correlated with lower BMIs for all subgroups, except children ages five to nine and girls ages 10-12
    • Overweight children (95th percentile) and obese adults (both genders) consumed significantly less fruit than healthy weight counterparts, e.g., 1.3 servings of fruit for overweight girls vs. 1.5 servings of fruit for other girls.
    • At risk girls also consumed less.
  • When compared to percentage of fruits or vegetables needed
    • No differences in general for vegetables
    • Healthy weight boys and men consumed significantly more fruit than either overweight or obese individuals, e.g., obese men ate 39% of recommended servings of fruit vs. 51% for healthy weight men.
    • At risk girls consumed 53% vs. 64% for healthy-weight girls
    • Obese women consumed 51% vs. 57% by other women.
Author Conclusion:

We found a negative relationship, or inverse association, between fruit consumption and body mass index: People who eat more servings of fruits each day have lower body mass indexes. Surprisingly, we found no consistent relationship between vegetable consumption and body mass index, especially among children.

[Note: Authors speculate that Americans may be eating fruits relatively untainted by added fat ingredients, but may be frying and topping vegetables with high-fat additions or including them in fatty mixed dishes.]

Funding Source:
Reviewer Comments:


  • Large national data set
  • Dietary data collected in a standardized way by well-trained interviewers
  • Controlled for several important variables including age relating to puberty for youth and aging adults
  • Good discussion section on possible reasons why no association was found with vegetables
  • Race/ethnicity in the regression model, but no data was presented examining differences among groups.


  • Correlation findings, not causal
  • Statistical methodology not described
  • Using the Pyramid database to assign foods to fruit and vegetable servings includes fruit and vegetables that would not be considered NCI 5-a-Day fruit and vegetable servings, e.g., fruit in a fruit tart. For measure of average consumption as a share of recommended servings, they did not take into account the individual’s activity level, but instead based recommended servings on individual’s reported calorie intake.
  • It is not always clear from the text, which body weight classes the authors are comparing.
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? No
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? No
  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? N/A
  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? 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%.) N/A
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? N/A
  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? 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? No
  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? No
  7.5. Was the measurement of effect at an appropriate level of precision? No
  7.6. Were other factors accounted for (measured) that could affect outcomes? No
  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? No
  8.1. Were statistical analyses adequately described and the results reported appropriately? No
  8.2. Were correct statistical tests used and assumptions of test not violated? ???
  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? No
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? No
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