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Stages of change for reducing dietary fat to 30% of energy or less.

Authors :
Greene GW
Rossi SR
Reed GR
Willey C
Prochaska JO
Source :
Journal of the American Dietetic Association [J Am Diet Assoc] 1994 Oct; Vol. 94 (10), pp. 1105-10; quiz 1111-2.
Publication Year :
1994

Abstract

Objective: To develop an algorithm that defines a person's stage of change for fat intake < or = 30% of energy. The Stages of Change Model describes when and how people change problem behaviors; change is defined as a dynamic variable with five discrete stages.<br />Design: A stage of change algorithm for determining dietary fat intake < or = 30% of energy was developed using one sample and was validated using a second sample.<br />Subjects: Sample 1 was a random sample of 614 adults who responded to mailed questionnaires. Sample 2 was a convenience sample of 130 faculty, staff, and graduate students.<br />Statistics: Subjects in sample 1 were initially classified in a stage of change using an algorithm based on their behavior related to avoiding high-fat foods. Dietary markers were selected for a Behavioral algorithm using logistic regression analyses. Sensitivity, specificity, and predictive value of the Behavioral algorithm were determined, then compared between samples using the Z test.<br />Results: The following dietary markers predicted intake < or = 30% of fat (chi 2 = 131; P < .0001): low-fat cheese, breads without added fat, chicken without skin, low-calorie salad dressing, and vegetables for snacks. The specificity of the Behavioral algorithm was validated; the algorithm classified subjects consuming > 30% of energy from fat with 93% specificity in sample 1 and 87% in sample 2 (Z = 1.36; P > .05). Predictive value was also validated; 64% and 58% of subjects meeting the behavioral criteria had fat intakes < or = 30% of energy (Z = 1.1; P > .05). The algorithm was not sensitive, however; most subjects with fat intakes < or = 30% of energy from fat failed to meet the behavioral criteria. The sensitivity differed between samples 1 and 2 (44% and 27%, respectively; Z = 3.84; P < .0001).<br />Applications: The Behavioral algorithm determines stage of change for fat reduction to < or = 30% of energy in populations with high fat intakes. The algorithm could be used in dietary counseling to tailor interventions to a patient's stage of change.

Details

Language :
English
ISSN :
0002-8223
Volume :
94
Issue :
10
Database :
MEDLINE
Journal :
Journal of the American Dietetic Association
Publication Type :
Academic Journal
Accession number :
7930314
Full Text :
https://doi.org/10.1016/0002-8223(94)91127-4