Characterising the reproducibility and reliability of dietary patterns among Yup'ik Alaska Native people

• Published in: British Journal of Nutrition
• Main Authors: Ryman, Tove K., Boyer, Bert B., Hopkins, Scarlett, Philip, Jacques, O'Brien, Diane, Thummel, Kenneth, Austin, Melissa A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press (CUP) 2015
• Subjects: Nutrition and Dietetics; Medicine (miscellaneous); Yup'ik; Alaska
• Online Access: http://dx.doi.org/10.1017/s0007114514003596; https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0007114514003596

FFQ data can be used to characterise dietary patterns for diet–disease association studies. In the present study, we evaluated three previously defined dietary patterns – ‘subsistence foods’, market-based ‘processed foods’ and ‘fruits and vegetables’ – among a sample of Yup'ik people from Southwest Alaska. We tested the reproducibility and reliability of the dietary patterns, as well as the associations of these patterns with dietary biomarkers and participant characteristics. We analysed data from adult study participants who completed at least one FFQ with the Center for Alaska Native Health Research 9/2009–5/2013. To test the reproducibility of the dietary patterns, we conducted a confirmatory factor analysis (CFA) of a hypothesised model using eighteen food items to measure the dietary patterns ( n 272). To test the reliability of the dietary patterns, we used the CFA to measure composite reliability ( n 272) and intra-class correlation coefficients for test–retest reliability ( n 113). Finally, to test the associations, we used linear regression ( n 637). All factor loadings, except one, in CFA indicated acceptable correlations between foods and dietary patterns ( r >0·40), and model-fit criteria were >0·90. Composite and test–retest reliability of the dietary patterns were, respectively, 0·56 and 0·34 for ‘subsistence foods’, 0·73 and 0·66 for ‘processed foods’, and 0·72 and 0·54 for ‘fruits and vegetables’. In the multi-predictor analysis, the dietary patterns were significantly associated with dietary biomarkers, community location, age, sex and self-reported lifestyle. This analysis confirmed the reproducibility and reliability of the dietary patterns in the present study population. These dietary patterns can be used for future research and development of dietary interventions in this underserved population.