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The association between and among food patterns, health perceptions, and stage of self-identity development in predicting health perceptions using a newly designed cross-cultural health inventory algorithm

Posted on:2002-06-01Degree:Ph.DType:Dissertation
University:Texas Woman's UniversityCandidate:Luna Hollen, Mary LouiseFull Text:PDF
GTID:1464390011498291Subject:Health Sciences
Abstract/Summary:
Objective. To determine if health perceptions are predictable using a newly designed oral cross-cultural health inventory algorithm.; Design. A predictive index measured physical, mental, and social health using population group, food adequacy indicators, and stage of self-identity as predictors.; Subjects/setting. 212 Hispanos from Guzman, Jalisco, Mexico and 177 Hispanos/Latinos from Fort Worth, Texas, USA between 13 and 90 years of age recruited by supporting organizations and community leaders in both the English and Spanish language, using predominately word of mouth to advertise in Hispano/Latino neighborhoods among family, youth, adult, and elderly groups.; Statistical analyses. Pearson Chi-Square tested for independence, logistic regression developed a predictive index, and diagnostic measures determined model appropriateness using the Statistical Package for the Social Sciences 10.0 (SPSS, 2000, Chicago, Illinois).; Results. The Pearson Chi-Square test indicated that physical, mental, and social health perceptions were dependent (P < .0001). Statistical evidence also indicated dependence for each pairwise combination among food adequacy markers respectively (P < .0001; P < .01; P < .0001). The predictive model for physical health found that population group, Latin Food Pyramid, and self view statistically predicted health (P < .01; P < .0001; P < .05). The predictive model for mental health found that cultural, self, and societal view statistically predicted health (P < .001; P < .05; P < .0001). Finally, the predictive model for social health found that cultural and self view statistically predicted health (P < .01). The diagnostics measuring model appropriateness were highly significant (P < .0001) and indicated that the reduced transformed model was similar to the full prediction model. The researcher recommends repeated measures to validate the oral instrument designed and to confirm the diagnostics presented.
Keywords/Search Tags:Health, Designed, Using, Model, Food, Predictive, Among
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