From the Shelf to the Landfill: The Effect of Socio-Demographic Factors on Wasting Behavior and the Impact of Survey Methods on Food Waste Reporting

Food waste is a global concern with significant economic, environmental, and ethical implications. Household food waste behavior has been studied extensively using techniques such as self-reported surveys, focus groups, food waste diaries, image applications, and waste audits. However, there remains a lack of clarity on the accuracy of measurement methods. For example, self-reporting methods are commonly associated with underreporting biases due to guilt, shame, and a lack of self-awareness surrounding food waste. The uncertainty associated with each method can lead to misallocation of resources and misinformed policy decisions. To address this, the uncertainties associated with each method must be quantified. These uncertainty values can then be applied to statistical models of food waste behavior to improve predictions affected by various stages of state development. Food waste causes, behaviors, and solutions differ based on factors such as socioeconomic status, culture, social pressure, and intention to reduce waste. For instance, forgetting about perishable food, purchasing or cooking excess food, and misunderstanding best-by dates largely contribute to food waste in developed countries. In contrast, upgrades to storage and transportation infrastructure are most effective at reducing food waste in developing countries. This literature review delves into the various drivers of food waste, ranging from individual behavior to sociocultural influences. It examines how demographic and psychographic factors play a crucial role in shaping individuals' food waste behaviors. Additionally, this literature review describes previous data on underreporting biases associated with different data collection methods.

Understanding how specific demographics impact these drivers and factors is vital to designing effective strategies to reduce food waste such as targeted composting programs.