Ideal cardiovascular health metrics have better identification of arthritis

Abstract

Abstract Background This study aimed to explore the association between ideal cardiovascular health metrics (ICVHM) and arthritis (AR), as well as the interactions of various indicators in ICVHM on AR in US adults. Methods We involved 17,041 participants who were interviewed by NHANES from 2011 to 2018. AR included osteoarthritis or degenerative arthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis and other arthritis (Other AR). Logistic regression was applied to analyze the association between AR and ICVHM. Mixed graphical model (MGM) was used to explore the interaction between variables in ICVHM. Results Higher ICVHM scores had a protective effect on AR. Compared to “≤1” score, the ORs of AR in participants with 2, 3, 4, and ≥5 were 0.586, 0.472, 0.259, and 0.130, respectively. Similar results were also found in different types of AR. ICVHM has a maximum area under the curve value of 0.765 and the interaction between blood pressure and total cholesterol was 0.43. Conclusions ICVHM correlates significantly with AR and is better at identifying AR than individual indicators. ICVHM can be better improved by controlling the indicators with stronger interactions. Our findings provide guidance for promoting health factors, which have important implications for identification and prevention of AR.

Keywords

• Arthritis
• Different types of arthritis
• Forest plot
• Ideal Cardiovascular Health Metrics
• Mixed graphical model