A rapid food screener to assess fat and fruit and vegetable intake
Abstract
Background The U.S. Preventive Services Task Force recommends that Americans lower dietary fat and cholesterol intake and increase fiber and fruit/vegetables to reduce prevalence of heart disease, cancer, stroke, hypertension, obesity, and non-insulin-dependent diabetes mellitus in the United States. To provide preventive services to all, a rapid, inexpensive, and valid method of assessing dietary intake is needed.Methods We used a one-page food intake screener based on national nutrition data. Respondents can complete and score the screener in a few minutes and can receive immediate, brief feedback. Two hundred adults self-administered the food screener. We compared fat, fiber, and fruit/vegetable intake estimates derived from the screener with estimates from a full-length, 100-item validated questionnaire.Results The screener was effective in identifying persons with high-fat intake, or low-fruit/vegetable intake. We found correlations of 0.6-0.7 (p<0. 0001) for total fat, saturated fat, cholesterol, and fruit/vegetable intake. The screener could identify persons with high percentages of calories from fat, total fat, saturated fat, or cholesterol, and persons with low intakes of vitamin C, fiber, or potassium.Conclusions This screener is a useful tool for quickly monitoring patients' diets. The health care provider can use it as a prelude to brief counseling or as the first stage of triage. Persons who score poorly can be referred for more extensive evaluation by low-cost paper-and-pencil methods. Those who still have poor scores at the second stage ultimately can be referred for in-person counseling.
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In Hunter 2008, at six months, participants in the computer intervention arm improved their fibre intake more than control arm participants, as measured by the dietary fibre score (MD 1.3, 95% CI 0.5 to 2.1; P = 0.001; 399 participants).
“Dietary fibre intake was examined in a single study (Hunter 2008), which found that at six months participants in the computer intervention arm improved their fibre intake more than participants in the control arm, as measured by the dietary fibre score (Block 2000) (MD 1.3 (95% 0.5 to 2.1); P = 0.001; 399 participants; Analysis 1.17).”
From Interactive computer-based interventions for weight loss or weight maintenance in overweight or obese people (2012) · cites this paper as Block 2000
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- Authors
- Block, G., Gillespie, C., Rosenbaum, E. H., & Jenson, C.
- Affiliations
- University of California, Berkeley (US)
- Tufts University (US)
- University of California, San Francisco (US)
- Shaklee (United States) (US)
- Corresponding author
- Block, Gladys
- ORCID
- Block, Gladys
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2000-05
- Volume
- 18
- Issue
- 4
- Pages
- 284-288
- ISSN
- 0749-3797 (ISSN-L)
- OpenAlex
- W2093430881
- Cited by
- 565
- References
- 5
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 15 · 2023: 18 · 2022: 28 · 2021: 27 · 2020: 24 · 2019: 30 · 2018: 37 · 2017: 27 · 2016: 30 · 2015: 29 · 2014: 44 · 2013: 32 · 2012: 29
- FWCI
- 6.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Preventive Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- dietary fat intake, saturated fat, cholesterol intake, fruit and vegetable intake, dietary fiber, self-administered questionnaire, screening validity, brief counseling, triage, preventive medicine
- MeSH terms
- Adult, Aged, Aged, 80 and over, Attitude to Health, Diet Surveys, Dietary Fats, Eating, Energy Metabolism, Female, Fruit, Humans, Male, Mass Screening, Middle Aged, Preventive Medicine, Probability, San Francisco, Sensitivity and Specificity, Vegetables, Linear Models
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