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Mothers of young children cluster into 4 groups based on psychographic food decision influencers
Authors:Carol Byrd-Bredbenner  Jaclyn Maurer Abbot  Ellen Cussler
Affiliation:1. Department of Nutritional Sciences, Rutgers University, New Brunswick, NJ 08901, USA;2. Department of Physiology, University of Arizona, Tucson, AZ 85721, USA
Abstract:This study explored how mothers grouped into clusters according to multiple psychographic food decision influencers and how the clusters differed in nutrient intake and nutrient content of their household food supply. Mothers (n = 201) completed a survey assessing basic demographic characteristics, food shopping and meal preparation activities, self and spouse employment, exposure to formal food or nutrition education, education level and occupation, weight status, nutrition and food preparation knowledge and skill, family member health and nutrition status, food decision influencer constructs, and dietary intake. In addition, an in-home inventory of 100 participants' household food supplies was conducted. Four distinct clusters presented when 26 psychographic food choice influencers were evaluated. These clusters appear to be valid and robust classifications of mothers in that they discriminated well on the psychographic variables used to construct the clusters as well as numerous other variables not used in the cluster analysis. In addition, the clusters appear to transcend demographic variables that often segment audiences (eg, race, mother's age, socioeconomic status), thereby adding a new dimension to the way in which this audience can be characterized. Furthermore, psychographically defined clusters predicted dietary quality. This study demonstrates that mothers are not a homogenous group and need to have their unique characteristics taken into consideration when designing strategies to promote health. These results can help health practitioners better understand factors affecting food decisions and tailor interventions to better meet the needs of mothers.
Keywords:ANOVA, analysis of variance   BMI, body mass index   NAR, nutrient adequacy ratio   UPC, universal product code
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