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Cited by 622

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

What Can Intervention Studies Tell Us about the Relationship between Fruit and Vegetable Consumption and Weight Management?

Rolls, Barbara J., Ello-Martin, Julia A., Tohill, Beth Carlton·2004·Nutrition Reviews

Abstract

Given the recent surge in obesity, effective dietary strategies for weight management are required. Because fruits and vegetables are high in water and fiber, incorporating them in the diet can reduce energy density, promote satiety, and decrease energy intake. Although few interventions have specifically addressed fruit and vegetable consumption, evidence suggests that coupling advice to increase intake of these foods with advice to decrease energy intake is a particularly effective strategy for weight management. This approach may facilitate weight loss because it emphasizes positive messages rather than negative, restrictive messages.

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Crossref · 10.1111/j.1753-4887.2004.tb00001.x

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Metadata

Authors
Rolls, B. J., Ello-Martin, J. A., & Tohill, B. C.
Venue
Nutrition Reviews
Published
2004-01
Volume
62
Issue
1
Pages
1-17
ISSN
  • 0029-6643 (ISSN-L)
  • 1753-4887
OpenAlex
W2129221806
Cited by
622
References
55
FWCI
20.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: What Can Intervention Studies Tell Us about the Relationship between Fruit and Vegetable Consumption and Weight Management? https://app.cochat.ai/papers/10.1111/j.1753-4887.2004.tb00001.x
The paper
Rolls, B. J., Ello-Martin, J. A., & Tohill, B. C. (2004). What Can Intervention Studies Tell Us about the Relationship between Fruit and Vegetable Consumption and Weight Management? Nutrition Reviews. https://doi.org/10.1111/j.1753-4887.2004.tb00001.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.