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Observational study

Rheumatology · 3 h ago

NHANES analysis links dietary patterns with rheumatoid arthritis status in people with anxiety

A cross-sectional analysis of seven NHANES cycles used machine-learning models to classify rheumatoid arthritis status among participants with medication-defined treated anxiety. Several nutrients and food groups contributed negatively to model predictions, but the findings are associative and need confirmation before they can inform dietary guidance.

Researchers analyzed data from seven NHANES cycles (2005–2018), using dietary recalls and a complementary food-group classification based on the USDA MyPyramid Equivalents Database. Among participants with medication-defined treated anxiety, six machine-learning models were developed to classify rheumatoid arthritis status from dietary features. The MyPyramid analysis reclassified the same NHANES dietary data; it was not an independent validation cohort.

Random Forest had the highest observed area under the receiver operating characteristic curve across both dietary representations. In post-hoc model interpretation, calcium, lycopene, folate and vitamin D were prominent negative contributors to rheumatoid arthritis-positive classification. Fruits, dairy products and seafood rich in omega-3 fatty acids also contributed negatively. The supplied report does not provide participant numbers or AUC values.

These model-derived associations do not establish that specific foods or nutrients prevent rheumatoid arthritis. The cross-sectional design cannot establish temporality or causation, and the authors say prospective cohorts or randomized trials are needed before the findings can inform dietary guidelines.

AI summary · Not yet editor-reviewed

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