Title

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

Document Type

Article

Date of Original Version

1-1-1994

Abstract

Objective To develop an algorithm that defines a person's stage of change for fat intake ≤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. Design A stage of change algorithm for determining dietary fat intake ≤30% of energy was developed using one sample and was validated using a second sample. 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. 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. Results The following dietary markers predicted intake ≤30% of fat (Ξ2 = 131; P < .0001): low-fat cheese, breads without addded 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 ≤30% of energy (Z = 1.1; P > .05). The algorithm was not sensitive, however; most subjects with fat intakes ≤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). Applications The Behavioral algorithm determines stage of change for fat reduction to ≤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. © 1994 Health Management Resources.

Publication Title

Journal of the American Dietetic Association

Volume

94

Issue

10

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