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. 2016 Nov;146(11):2343-2350.
doi: 10.3945/jn.116.236729. Epub 2016 Oct 5.

Harmonization of Food-Frequency Questionnaires and Dietary Pattern Analysis in 4 Ethnically Diverse Birth Cohorts

Russell J de Souza  1   2   3 , Michael A Zulyniak  4 , Dipika Desai  5 , Mateen R Shaikh  6 , Natalie C Campbell  4 , Diana L Lefebvre  4 , Milan Gupta  4   3 , Julie Wilson  7 , Gita Wahi  8 , Stephanie A Atkinson  8 , Koon K Teo  4 , Padmaja Subbarao  9 , Allan B Becker  10 , Piushkumar J Mandhane  11 , Stuart E Turvey  12 , Malcolm R Sears  4 , Sonia S Anand  6   4   5 ; NutriGen Alliance Investigators
Affiliations
Free article

Harmonization of Food-Frequency Questionnaires and Dietary Pattern Analysis in 4 Ethnically Diverse Birth Cohorts

Russell J de Souza et al. J Nutr. 2016 Nov.
Free article

Abstract

Background: Canada is an ethnically diverse nation, which introduces challenges for health care providers tasked with providing evidence-based dietary advice.

Objectives: We aimed to harmonize food-frequency questionnaires (FFQs) across 4 birth cohorts of ethnically diverse pregnant women to derive robust dietary patterns to investigate maternal and newborn outcomes.

Methods: The NutriGen Alliance comprises 4 prospective birth cohorts and includes 4880 Canadian mother-infant pairs of predominantly white European [CHILD (Canadian Healthy Infant Longitudinal Development) and FAMILY (Family Atherosclerosis Monitoring In earLY life)], South Asian [START (SouTh Asian birth cohoRT)-Canada], or Aboriginal [ABC (Aboriginal Birth Cohort)] origins. CHILD used a multiethnic FFQ based on a previously validated instrument designed by the Fred Hutchinson Cancer Research Center, whereas FAMILY, START, and ABC used questionnaires specifically designed for use in white European, South Asian, and Aboriginal people, respectively. The serving sizes and consumption frequencies of individual food items within the 4 FFQs were harmonized and aggregated into 36 common food groups. Principal components analysis was used to identify dietary patterns that were internally validated against self-reported vegetarian status and externally validated against a modified Alternative Healthy Eating Index (mAHEI).

Results: Three maternal dietary patterns were identified-"plant-based," "Western," and "health-conscious"-which collectively explained 29% of the total variability in eating habits observed in the NutriGen Alliance. These patterns were strongly associated with self-reported vegetarian status (OR: 3.85; 95% CI: 3.47, 4.29; r2 = 0.30, P < 0.001; for a plant-based diet), and average adherence to the plant-based diet was higher in participants in the fourth quartile of the mAHEI than in the first quartile (mean difference: 46.1%; r2 = 0.81, P < 0.001).

Conclusion: Dietary data collected by using FFQs from ethnically diverse pregnant women can be harmonized to identify common dietary patterns to investigate associations between maternal dietary intake and health outcomes.

Keywords: FFQ; PCA; dietary patterns; ethnicity; food frequency questionnaire; harmonization; multiethnic; principal component analysis; prospective cohort.

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