Mapping of the adherence to the planetary health diet in 11 European countries: comparison of different diet quality indices as a result of the PLAN’EAT project

Introduction The Planetary Health Diet (PHD) is a nutritional approach integrating public health and environmental sustainability aspects. This study, conducted within the European PLAN’EAT project, aimed to assess adherence to PHD in 11 European countries. Methods Three dietary quality indices were used: the EAT-Lancet index; the original WISH; and a newly developed version, WISH 2.0. This last index incorporates two additional food categories: processed meat and alcoholic beverages. The inclusion of these categories was driven by their recognized public health and environmental relevance. The food consumption data was retrieved from the EFSA Comprehensive European Food Consumption Database. Scores were calculated and normalized to carry out descriptive and comparative analyses. Cluster analyses were also performed to examine dietary pattern differences by country and gender. Results Low adherence to PHD was observed across all countries. However, Southern European countries such as Italy, Greece, and Spain showed comparatively higher adherence, particularly among women. Cluster analyses, based on EAT-Lancet and WISH 2.0 scores, highlighted regional and gender patterns. These findings emphasize the cultural specificity of dietary behaviors. The two indices have different discriminating capacities. From the EAT-Lancet index, higher average normalized scores were obtained. WISH 2.0 could distinguish between different dietary patterns and was better aligned with actual food consumption data, demonstrating an enhanced capacity to better detect national dietary patterns more accurately. Discussion These results underscore the potential of WISH 2.0 as a comprehensive and practical instrument for mapping and monitoring dietary quality in Europe. Additionally, the findings indicate that adapting global dietary guidelines to local contexts may be essential to improve population-level adherence and policy relevance.