Models of association between demographics and the hospital visits by patients with type 2 diabetes mellitus

The purpose of this study is to determine the effect of demographic characteristics on frequency of patients’ visits in type 2 diabetes mellitus (T2DM) by statistical modeling at a tertiary care center, Karachi. An institution-based retrospective analysis of hospital records of T2DM patients reported between October 2005 and March 2013 to the National Institute of Diabetes and Endocrinology (NIDE), Dow University of Health Sciences, Karachi, Pakistan, was performed. Age, gender, marital status, income, education, and occupation were used to evaluate the determinants of hospital/clinic visits using three statistical modeling techniques—ordinary least square (OLS), Poisson regression model (PRM), and negative binomial regression (NBR). All regression analyses were performed using Stata version 11.1 (StataCorp LP, 2010). A total of 8632 (first and subsequent) visit records of T2DM patients between 15 and 92 years age, diagnosed according to the diagnostic criteria of the International Diabetes Federation, were studied. The mean frequency of clinic visits among these T2DM patients was 1.63 ± 3.12 per person per year during the study period, and the mean follow-up period was 52 ± 11 months. Higher age, female gender, middle-income levels (40–50 K Rs.), and education levels (can read/write, primary, graduation, and postgraduation) were found to be the significant predictors influencing number of hospital visits. Education was the most significant factor affecting T2DM patients’ visits to physicians. Patients with higher education were likely to visit physicians more frequently than patients with low education. Despite the presence of overdispersion, the PRM and NB model gave similar regression estimates. These statistical models can be utilized for developing and implementing surveillance program to control and reduce demographic risk factors for T2DM.