Overweight, smoking add to rheumatoid arthritis risk

By Lynda Williams, Senior medwireNews Reporter

Lifestyle changes could reduce the risk for rheumatoid arthritis (RA) in patients predisposed to the condition, Dutch researchers suggest.

The team found that individuals with RA-specific autoantibodies, but no symptoms, were significantly more likely to develop arthritis if they had ever smoked (hazard ratio [HR]=9.6) or were overweight (HR=5.6) than nonsmokers or individuals of a healthy weight.

"These results show the importance of life style factors in development of RA and should be critically evaluated in future clinical research aimed at disease prevention," say Danielle Gerlag (Academic Medical Center/University of Amsterdam) and co-authors.

The team followed up 55 individuals positive for the RA markers immunoglobulin M rheumatoid factor (n=19), anti-citrullinated protein antibodies (n=22), or both (n=14).

Over a median of 13 months, 27% of the group developed arthritis, defined as a swollen and painful joint.

Patients with a body mass index (BMI) of 25 kg/m2 or above were significantly more likely to develop arthritis than those whose BMI was below 25 kg/m2 (87 vs 45%). Ever smokers were significantly more likely to develop arthritis than never smokers (93 vs 53%), with both past and current smokers at higher risk than never smokers (38 and 43% versus 5%, respectively).

The overall risk for arthritis in the group was 27%, rising after 27 months to 60% among smokers who were overweight, the researchers report in the Annals of Rheumatic Diseases.

"This observation was made in a relatively small cohort, suggesting that the effects of smoking and overweight are strong," the team writes.

"In comparison, the risk for developing arthritis in never smokers with normal weight was only 2%, showing that life style modification might have important consequences for arthritis development in RA-prone individuals."

Gerlag et al conclude: "The results of this study, if confirmed in larger, independent cohorts, may also help to better define a population at high risk of developing RA based on the presence of RA-specific autoantibodies, smoking history, and overweight. Improved prediction models may facilitate studies aimed at prevention of RA by targeted intervention during the preclinical phase."

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