Keywords
FISI
Hyperlipidemia
Dyslipidemia
NHANES
Categories
Data Availability Statement
NHANES data are publicly available from the U.S. Centers for Disease Control and Prevention National Center for Health Statistics website.
How to Cite
Abstract
Background: Dietary inflammation has been associated with dyslipidemia, but the relationship between the newer Food Inflammation Scores of Individuals (FISI) and hyperlipidemia has not been well characterized. Methods: We analyzed 11,805 adults aged 20 years or older from five NHANES cycles (2009-2018). FISI34, FISI26-USDA, FISI26-CHINA, and a Dietary Inflammatory Index calculated without alcohol (DII) were derived from 24-h dietary recall data. Associations with hyperlipidemia were examined using survey-weighted logistic regression. Restricted cubic spline models, sex-stratified analyses, and prespecified subgroup analyses were performed. Results: In the fully adjusted model, higher FISI26-USDA and FISI26-CHINA scores were associated with greater odds of hyperlipidemia (OR 1.08, 95% CI 1.01-1.14, P=0.016; and OR 1.10, 95% CI 1.02-1.18, P=0.015, respectively). Compared with Q1, Q4 ORs were 1.35 (95% CI 1.11-1.64; P=0.003) for FISI26-USDA and 1.26 (95% CI 1.03-1.54; P=0.024) for FISI26-CHINA. FISI34 was not consistently associated with hyperlipidemia (continuous P=0.210; P for trend=0.075). The continuous DII association was weaker (P=0.072), although Q3 and the trend test remained significant. Restricted cubic splines supported approximately linear associations for FISI26-USDA, FISI26-CHINA, and DII (P for nonlinearity>0.05), whereas no overall association was detected for FISI34. In sex-stratified analyses, the FISI26 associations were more consistent among women. No significant interaction was observed across the FISI26-USDA subgroup analyses (all P for interaction>0.05). Conclusions: FISI26-USDA and FISI26-CHINA were positively associated with hyperlipidemia in U.S. adults, whereas FISI34 showed no consistent association, and the DII association was less robust after multivariable adjustment. These findings support further prospective evaluation of FISI26-based measures in cardiometabolic research.
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