Paper
Friday, July 23, 2004
Predictors of Healthy Eating Among Midlife and Older Rural Women
Susan Noble Walker, EdD, RN, FAAN1, Carol H. Pullen, EdD, RN1, Linda S. Boeckner, PhD, RD2, Patricia A. Hageman, PT, PhD3, and Maureen K. Oberdorfer, MPA, BSMT1. (1) College of Nursing, University of Nebraska Medical Center, Omaha, NE, USA, (2) University of Nebraska Research and Extension Center, Scottsbluff, NE, USA, (3) Division of Physical Therapy Education, University of Nebraska Medical Center, Omaha, NE, USA
| Learning Objective #1: Describe some predictors of healthy-eating among midlife and older rural women |
| Learning Objective #2: Discuss the need to design healthy-eating lifestyle change interventions tailored on personal factors and behavior-specific cognitions |
Objective: Poor diet is among the leading causes of morbidity and premature mortality in older women. The purpose was to determine the extent to which personal factors and behavior-specific cognitions explain healthy eating among midlife and older rural women . Design: Descriptive correlational design. Population, Sample, Setting, Years: 225 rural women aged 50-69 enrolled in an NIH-funded lifestyle behavior change project in 2002-2003. Concept or Variables Studied Together: Behavioral determinants were personal factors (age, readiness to change, health status) and behavior-specific cognitions (perceived benefits, barriers, self-efficacy, family & peer interpersonal support) selected from Pender’s Health Promotion Model. Healthy eating behaviors were those recommended in the U.S. Healthy People 2010 Objectives. Methods: At two rural sites in the midwestern U.S., women were supervised in responding to a battery of established reliable and valid questionaires in individual sessions on a computer. Eating was measured by the Block Health Habit and History Questionnaire. Baseline data prior to receiving the behavior change intervention is reported. Findings: Daily eating behaviors (fruit & vegetable servings, grain servings, meat group servings, dairy servings, %Kcal from fat and saturated fat) were used as 6 separate criterion variables in hierarchical regression analyses. Personal factors were entered in a first block and behavior-specific cognitions in a second block. All variables explained from 8% to 26% of variance in eating behaviors. Determinant variables that made an independent contribution to the explanation of one or more indicators of healthy eating were readiness to change, perceived health status, barriers and self-efficacy (Bs from .14 to .35). Age, perceived benefits and family and peer support made no independent contributions. Conclusions and Implications: Both personal factors and behavior-specific cognitions influenced rural midlife and older women’s eating behaviors. These variables will be used in designing tailored dietary lifestyle change messages for these women throughout the intervention project.
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