Interviewer Error Within the Face-to-Face Food Frequency Questionnaire in Large Multisite Epidemiologic Studies

Abstract

Interviewer error has long been recognized in face-to-face surveys, but little is known about interviewer error within face-to-face food frequency questionnaires, particularly in large multisite epidemiologic studies. Using dietary data from the China Multi-Ethnic Cohort (2018-2019), in which all field interviews were audio recorded, we identified a potentially error-prone sample by outlier detection and further examined the interviewer errors by reviewing these error-prone interviews. Among 174,012 questions for 5,025 error-prone interviews, 13,855 (7.96%) questions were identified with interviewer error, which mainly came from falsification (37.53%), coding error (31.71%), and reading deviation (30.76%). We found that 98.29% of interviewers and 73.71% of respondents had at least 1 error, and half of the errors could be attributed to 21.94% of interviewers or to 13.77% of respondents. Higher error risk was observed in complicated questions, such as questions assessing food quantification or referring to seasonally supplied food groups. After correcting the errors, the means and standard deviations of estimated food intakes all decreased. These findings suggested that interviewer error should not be ignored within face-to-face food frequency questionnaires and that more efforts are needed to monitor error-prone interviewers and respondents and reduce survey burdens in questionnaire design.

Keywords: audio recording; data quality; food frequency questionnaire; interviewer error; multivariate outlier detection.