Analysis of factors related to diabetic retinopathy in patients with newly diagnosed type 2 diabetes: a cross-sectional study.

Aim: To investigate the related factors of diabetic retinopathy (DR) and explore the correlation between smoking and DR in patients with newly diagnosed type 2 diabetes mellitus (T2DM).

Design: A single-centre cross-sectional study.

Setting: Tianjin 4th Central Hospital.

Participants: Patients with newly diagnosed T2DM who visited the outpatient department of the hospital from December 2018 to April 2019.

Methods: A total of 947 patients were enrolled in the study. They were divided into two groups according to whether they were diagnosed with DR (diabetic retinopathy group, DR group; non-diabetic retinopathy group, NDR group). The smoking index (SI) was calculated to assess smoking status. Factors such as sex, age, hypertension, T2DM diagnosed age, family history of diabetes, drinking history, haemoglobin A1c (HbA1c), body mass index (BMI) and smoking status were compared between the two groups. Logistic regression was used to analyse the relationship between DR and the above factors.

Results: There was no statistically significant difference between the two groups in sex, age, hypertension, DM diagnosed age, family history of diabetes, drinking history and HbA1c. BMI was significantly higher in DR patients (27.7±4.2 vs 26.7±4.4, p=0.004). Smoking status was also different between the two groups (χ=6.350, p=0.042). BMI was shown to be a related factor for DR in patients with newly diagnosed diabetes (OR=0.592, p=0.004). When BMI was ≥28 kg/m, heavy smoking was significantly associated with DR (OR=2.219, p=0.049), and there was a negative correlation between DR and the age of diagnosis of diabetes ≥60 years (OR=0.289, p=0.009).

Conclusions: Heavy smoking was an important related factor for DR in patients with newly diagnosed diabetes mellitus when BMI was ≥28 kg/m. Delaying the age of diabetes might prevent the occurrence of DR. To elucidate the correlation, long-term cohort studies with large samples are needed.