Articles

Risk of Diabetes in Geriatric Rheumatoid Arthritis: Using Data from the Korean Genome and Epidemiology Study (KoGES)


AUTHOR
Ji Young Kim
INFORMATION
page. 209~229 / No 3

e-ISSN
p-ISSN
1226-2641

ABSTRACT

Rheumatoid arthritis (RA) is one of representative geriatric diseases caused by a combination of various genetic and acquired factors. Chronic progressive systemic inflammation caused by RA is closely associated to the inflammatory pathway underlying the pathogenesis of diabetes mellitus. However, most studies to investigate the association have been conducted mainly in foreign countries, and the study results have been inconsistent. Thus, this study attempted to look at the factors affecting both the pre-diabetes stage and the development of diabetes in RA patients in Korea, and also sought to find risk factors for the development. For this purpose, data from RA patients aged 40 to 69 (n=501) were used among the community-based cohort data from the Korean Genome Epidemiology Study of the Korea Disease Control and Prevention Agency. Simple logistic regression was used to investigate factors influencing the development of pre-diabetes and diabetes. As a result, the prevalence of both pre-diabetes and diabetes in RA patients was found to be higher than that in the general population. RA patients’ risk of developing diabetes was higher if they were female, older, less educated, or had a larger waist circumference, higher body mass index, higher blood pressure, lower triglycerides, and lower high-density lipoprotein cholesterol. However, no association between RA and diabetes was found in factors such as marital status, income, occupation, fatigue, sleep time, smoking, and physical activity. The reason why the association was not found in factors such as the physical activity was discussed in the context of statistical errors made in the process of categorizing the raw data. Despite such weaknesses, the significance of this study was that it was an attempt to pursue the association between RA and diabetes based on demographic, physical measurement, and hematologic data.