|LEMACKS, JENNIFER - University Of Southern Mississippi|
|HUYE, HOLLY - University Of Southern Mississippi|
|RUPP, RENEE - University Of Southern Mississippi|
|CONNELL, CAROL - University Of Southern Mississippi|
Submitted to: Preventive Medicine Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/8/2015
Publication Date: 6/24/2015
Citation: Lemacks, J.L., Huye, H., Rupp, R., Connell, C.L. 2015. The relationship between interviewer-respondent race match and reporting of energy intake using food frequency questionnaires in the rural South United States. Preventive Medicine Reports. 2:533-537.
Interpretive Summary: Researchers needed to see if information gathered from participants was less accurate if the person collecting the information was not the same race as the person the information was collected from. This is very important when you consider the race relationship in the southern part of the country, where our study took place. Our study shows there is a possibility that race of a person may contribute to less accurate data. As a result of these findings, researchers should consider this potential social issue in the future to potentially alleviate this concern and its impact on the data collected.
Technical Abstract: The purpose of the observational study was to determine whether interviewer race influences food frequency questionnaire (FFQ) reporting accuracy in a Deep South, largely African American cohort. A secondary analysis was conducted to investigate the influence of interviewer race on energy reporting of 319 African Americans who participated in the Mississippi Communities for Healthy Living intervention in May–June 2011, a community-based and USDA-funded project. Reported energy intake was compared to total energy expenditure to identify normal (ENR), under-(EUR) and over-reporters (EOR). Multivariate logistic regression models determined the relationship between race match and energy misreporting, accounting for confounding variables (educational level, health status perception, BMI, gender, and age) identified using chi-square/correlation analyses. The sample included 278 African Americans with 165 EURs, 26 EORs, and 87 ENRs identified. Logistic regression analyses revealed that there was no relationship between race-matched participants and EUR or EOR; controlling factors, BMI and perceived health status were significant in the model. This study is the first to our knowledge to examine whether race influences dietary intake reporting which may influence assessment data used for comparison with health outcomes. This may have important implications for research conducted in health disparate populations, particularly rural, Southern populations.