The curvilinear relationship between Framingham Steatosis Index and depression: insights from a nationwide study.

Background: The Framingham Steatosis Index (FSI) serves as a diagnostic metric for fatty liver. While research has established a link between depression and fatty liver, the association with the Framingham Steatosis Index (FSI) remains undocumented. The aim of this study is to explore the potential correlation between FSI and depression, addressing this research void.

Methods: Our data originates from the National Health and Nutrition Examination Survey (NHANES) database. We employed the PHQ-9 questionnaire for the evaluation of depressive symptoms. We investigated the association between FSI and depression using a weighted multiple logistic regression model and stratified analysis. Non-linear associations were explored using fitted smooth curves. A recursive method was employed to identify inflection points. Subgroup analyses were conducted to examine differences in the association between FSI and depression within subgroups.

Results: Our research encompassed a total of 19,697 participants. Multivariate logistic regression analysis, adjusted for potential confounding factors, demonstrated a significant positive association between FSI and depression, with OR of 1.14 (95% CI: 1.10, 1.18). Stratified analysis indicated that a significant positive correlation exists between FSI and depression among all groups except those with BMI below 30. The non-linear relationship was further confirmed by the restricted cubic splines analysis, which revealed an inflection point at an FSI value of 29.72. Below this threshold, there was no significant correlation, while above it, a positive correlation was observed. Subgroup analysis revealed statistically significant interactions between FSI and depression within the educational attainment groups.

Conclusion: Our study's discovery is the curvilinear relationship between FSI and depression. Factors such as inflammation, hormonal levels, and metabolic disruptions could be the underlying mechanisms driving this relationship. This finding offers valuable insights that could inform the development of comprehensive intervention strategies for managing depression in clinical settings.