An Application of Meta-Analysis in Food Safety Consumer Research to Evaluate Consumer Behaviors and Practices
Patil, S., Morales, R., Cates, S., Anderson, D., & Kendall, D. (2004). An Application of Meta-Analysis in Food Safety Consumer Research to Evaluate Consumer Behaviors and Practices. Journal of Food Protection, 67(11), 2587-2595.
Meta-analysis provides a structured method for combining results from several studies and accounting for and differentiating between study variables. Numerous food safety consumer research studies often focus on specific behaviors among different subpopulations but fail to provide a holistic picture of consumer behavior. Combining information from several studies provides a broader understanding of differences and trends among demographic subpopulations, and thus, helps in developing effective risk communication messages. In the illustrated example, raw/undercooked ground beef consumption and hygienic practices were evaluated according to gender, ethnicity, and age. Percentages of people engaging in each of the above behaviors (referred to as effect sizes) were combined using weighted averages of these percentages. Several measures, including sampling errors, random variance between studies, sample sizes of studies, and homogeneity of findings across studies, were used in the meta-analysis. The statistical significance of differences in behaviors across demographic segments was evaluated using analysis of variance. The meta-analysis identified considerable variability in effect sizes for raw/undercooked ground beef consumption and poor hygienic practices. More males, African Americans, and adults between 30 and 54 years (mid-age) consumed raw/undercooked ground beef than other demographic segments. Males, Caucasians, and Hispanics and young adults between 18 and 29 years were more likely to engage in poor hygienic practices. Compared to traditional qualitative review methods, meta-analysis quantitatively accounts for interstudy differences, allows greater consideration of data from studies with smaller sample sizes, and offers ease of analysis as newer data become available, and thus, merits consideration for its application in food safety consumer research.