Abstract
BACKGROUND: Depression is a significant focus in mental health research, emerging as a pressing public health concern globally. The Planetary Health Diet Index (PHDI), recently proposed by The Lancet to balance health and environmental sustainability, remains unclear in its role in preventing depression-our study aims to investigate this association and seeks to optimize this dietary index. METHODS: A cross-sectional analysis was conducted using 2005-2018 NHANES data from 27,868 participants. Dietary quality was measured using PHDI-US, and depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9; score ≥10 indicating depressive symptoms). Associations between dietary indices and depressive symptoms were analyzed using multivariable logistic regression and restricted cubic splines. Machine learning identified key PHDI-US components, leading to the recalibration of PHDI-US to create PHDI-Fruits. FINDINGS: Except for the Dietary Inflammatory Index (DII), the PHDI-US, HEI-2020, AHEI, and MEDI all demonstrated protective effects against depression. However, the benefits of PHDI-US were weaker compared to the other indices, particularly among participants with high adherence. Among the components of PHDI-US, fruits had the most significant impact. After recalibrating the PHDI-Fruits component, its ability to reduce depression incidence improved substantially, surpassing that of the other dietary indices. INTERPRETATION: Optimizing the preventive effect of PHDI on depression, the recalibrated PHDI-Fruits significantly enhances its ability to prevent depression, effectively improving the applicability of PHDI in populations affected by depression.