A meta-analysis assessing the effectiveness of demand-side interventions for sustainable food consumption and food waste reduction

Abstract

Shifting consumers towards more sustainable food consumption and avoiding food waste have been identified as key levers in mitigating food systems-related climate change impacts. Here we conducted a machine-learning-assisted systematic review and meta-analysis of 306 effect sizes from 110 articles, covering over 2.4 million observations, to assess the effectiveness of demand-side interventions targeting actual or incentivized behaviours. On average, we find small effect sizes across both food consumption and food waste interventions. Effect sizes vary substantially across intervention types, with certain choice architecture interventions, such as availability and defaults, driving much of the overall effect in both domains, while incentives also show promise in reducing food waste. These effects remain robust even after accounting for severe publication bias, which notably reduces average estimates for other intervention types. Sensitivity analyses further underscore the need for future research to systematically identify when, how and why interventions are effective.