Association of Disease Knowledge, Comorbidity, and Biochemical Parameters in Adults with Type 2 Diabetes

Abstract

Purpose: This study examines how disease-related knowledge is associated with comorbidities, metabolic and anthropometric indicators, and dietary patterns in individuals with Type 2 diabetes.

Methods: This cross-sectional study included 184 adults with Type 2 diabetes. Data were collected using sociodemographic questionnaires, the Diabetes Knowledge Scale for Adults, and a food frequency questionnaire. Anthropometric and biochemical data were also obtained. Participants were grouped by median knowledge score (low or high). Mann–Whitney U and chi-square tests were used to analyze the data. Structural equation modeling (SEM) was used to model the effect of disease knowledge on health indicators.

Results: Participants with higher knowledge had lower total cholesterol, triglycerides, body weight, BMI, and neck circumference, and demonstrated better dietary compliance (p < 0.05). Retinopathy was more common in the high-knowledge group, while hypertension was more prevalent in the low-knowledge group (p=0.037 and p=0.002, respectively). SEM analysis revealed a weak yet directional relationship between knowledge level and health indicators.

Conclusion: The level of knowledge about the disease positively affects specific metabolic and behavioral indicators. Therefore, educational programmes aimed at increasing patients’ knowledge and supporting behavioural change should be developed and implemented at the primary care level.

Plain Language Summary: People with Type 2 diabetes who know more about their condition tend to have healthier body weight, lower cholesterol levels, and better eating habits. This study highlights that learning about diabetes and following nutrition advice can improve everyday health and help prevent complications.

Keywords: Biochemical parameters, comorbidities, disease knowledge, structural equation modeling, type 2 diabetes