Zhonghua Yi Xue Za Zhi. 2024 Mar 12;104(10):742-750. doi: 10.3760/cma.j.cn112137-20230724-00081.
ABSTRACT
Objective: To evaluate the relationship between different indexes of weight variability and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). Methods: A retrospective cohort study. The clinical data of 2 180 T2DM patients without DKD who underwent case management at Lee’s United Clinic in Taiwan, China from 2002 to 2018 were retrospectively analyzed, including 1 103 females and 1 077 males, with an average age of (64.8±12.4) years. Regular follow-up was conducted for patients for at least 2 years, and their metabolic indexes were monitored annually. BMI variability independent of the mean (BMI-VIM), average yearly mean square successive difference (BMI-ASV), coefficient of variation (BMI-CV) and standard deviation (BMI-SD) were calculated,based on the body mass index (BMI) recorded annually by the patients. Patients were divided into four groups (Q1–Q4) based on the quartiles of the four weight variability indexes. DKD group and non-DKN group(NDKD group) were defined based on the occurrence of DKD at the end of the follow-up. Cox proportional hazards regression models were used to analyze the relationship between the four weight variability indicators and the incidence of DKD. Subgroup analysis was performed by categorizing patients into non-obesity (BMI<28 kg/m2) and obesity groups (BMI≥28 kg/m2) to investigate the impact of the four weight variability indicators on the risk of DKD. Results: After a follow-up of (4.55±2.13) years, 904 patients developed DKD. Compared with the NDKD group, patients in the DKD group had a higher proportion of females, older age, longer duration of diabetes, more insulin users, higher waist-to-hip ratio, higher levels of BMI-VIM, BMI-ASV, BMI-CV, BMI-SD, systolic blood pressure, diastolic blood pressure, and urine albumin–creatinine ratio, a lower proportion of hypoglycemic drugs, estimated glomerular filtration rate, and high-density lipoprotein cholesterol level, with statistically significant differences between the two groups(all P<0.05). Cox proportional hazards regression analysis results revealed that the risk of DKD in T2DM patients increased with the increase in BMI-SD, BMI-CV, BMI-VIM, and BMI-ASV after correcting a series of influencing factors. In the BMI-VIM subgroup, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.4% [HR=1.224 (95%CI:1.008-1.487), P=0.041]. In the BMI-ASV group, compared with the Q1 group, the risk of DKD in the Q4 group increased by 51.1% [HR=1.511 (95%CI:1.240-1.841), P<0.01]. In the BMI-CV group, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.2% [HR=1.222 (95%CI:1.006-1.485), P=0.044]. In the BMI-SD subgroup, compared with the Q1 group, the risk of DKD in the Q4 group increased by 22.2% [HR=1.222 (95%CI:1.002-1.490), P=0.048]. Sub-group analysis showed that when the non-obesity group was grouped by BMI-ASV, after correcting a series of influencing factors, compared with the Q1 group, the highest risk of DKD occurred in the Q4 group [HR=1.551 (95%CI:1.228-1.958), P<0.001];when the obesity group was grouped by BMI-ASV, after correcting a series of influencing factors, compared with the Q1 group, the highest risk of DKD occurred in the Q4 group [HR=1.703 (95%CI:1.168-2.485), P=0.006]. Conclusion: Increases in BMI-VIM, BMI-ASV, BMI-CV, and BMI-SD are associated with an increased risk of DKD in T2DM patients.
PMID:38462354 | DOI:10.3760/cma.j.cn112137-20230724-00081
