Strategies to Address Misestimation of Energy Intake Based on Self-Report Dietary Consumption in Examining Associations Between Dietary Patterns and Cancer Risk

• Main Authors: Nathan M. Solbak, Ala Al Rajabi, Alianu K. Akawung, Geraldine Lo Siou, Sharon I. Kirkpatrick, Paula J. Robson
• Format: Article
• Language: English
• Published: MDPI AG 2019-11-01
• Series: Nutrients
• Subjects: dietary patterns; energy misestimation; alberta’s tomorrow project; revised goldberg method; cancer incidence; diet-disease associations
• Online Access: https://www.mdpi.com/2072-6643/11/11/2614

The objective of this study was to determine the influence of strategies of handling misestimation of energy intake (EI) on observed associations between dietary patterns and cancer risk. Data from Alberta&#8217;s Tomorrow Project participants (<i>n</i> = 9,847 men and 16,241 women) were linked to the Alberta Cancer Registry. The revised-Goldberg method was used to characterize EI misestimation. Four strategies assessed the influence of EI misestimation: Retaining individuals with EI misestimation in the cluster analysis (Inclusion), excluding before (ExBefore) or after cluster analysis (ExAfter), or reassigning into ExBefore clusters using the nearest neighbor method (InclusionNN). Misestimation of EI affected approximately 50% of participants. Cluster analysis identified three patterns: Healthy, Meats/Pizza and Sweets/Dairy. Cox proportional hazard regression models assessed associations between the risk of cancer and dietary patterns. Among men, no significant associations (based on an often-used threshold of <i>p</i> &lt; 0.05) between dietary patterns and cancer risk were observed. In women, significant associations were observed between the Sweets/Dairy and Meats/Pizza patterns and all cancer risk in the ExBefore (HR (95% CI): 1.28 (1.04&#8722;1.58)) and InclusionNN (HR (95% CI): 1.14 (1.00&#8722;1.30)), respectively. Thus, strategies to address misestimation of EI can influence associations between dietary patterns and disease outcomes. Identifying optimal approaches for addressing EI misestimation, for example, by leveraging biomarker-based studies could improve our ability to characterize diet-disease associations.