Published online Oct 15, 2023. doi: 10.4239/wjd.v14.i10.1551
Peer-review started: August 1, 2023
First decision: August 16, 2023
Revised: August 22, 2023
Accepted: September 6, 2023
Article in press: September 6, 2023
Published online: October 15, 2023
Processing time: 69 Days and 10.5 Hours
The trend of prediabetes progressing to type 2 diabetes mellitus (T2DM) is prominent, and effective intervention can lead to a return to prediabetes. Exploring the factors influencing the outcome of prediabetes is helpful to guide clinical intervention. The weight change in patients with prediabetes has not attracted much attention.
To explore the interaction between body weight and the factors affecting the progression of prediabetes to T2DM.
We performed a retrospective analysis of 236 patients with prediabetes and 50 with normal glucose tolerance (NGT), and collected clinical data and follow-up results of all patients. Based on natural blood glucose outcomes, we classified 66 patients with progression to T2DM into the disease progression (DP) group, and 170 patients without progression to T2DM into the disease outcome (DO) group. We analyzed the factors that influenced prediabetes outcome and the influence of body weight on prediabetes blood glucose outcome by unconditional logistic regression. A general linear model (univariate) was used to analyze the inter-action between body weight and independent influencing factors.
There were 98 cases of impaired fasting glucose (IFG), 90 cases of impaired glucose tolerance (IGT), and 48 cases of coexistent IFG and IGT. The body weight, waist circumference, body mass index, fasting blood glucose, and 2 h plasma glucose of patients with IFG, IGT, and coexistent IFG and IGT were higher than those in patients with NGT (P < 0.05). Logistic regression analysis showed that body weight, glycosylated hemoglobin, uric acid, fasting insulin, and homeostatic model assessment for insulin resistance were independent factors affecting progression of prediabetes to T2DM (P < 0.05). Receiver operating characteristic curve analysis showed that the area under the curve predicted by the above indicators combined was 0.905 [95% confidence interval (CI): 0.863-0.948], which was greater than that predicted by each indicator alone. Logistic regression analysis with baseline body weight as an independent variable showed that compared with body weight 1, the odds ratio (95%CI) of body weight 3 was 1.399 (1.142-2.126) (P = 0.033). There was a multiplicative interaction between body weight and uric acid (β = 1.953, P = 0.005).
High body weight in patients with prediabetes is an independent risk factor for progression to T2DM, and the risk of progression is increased when coexisting with high uric acid level.
Core Tip: Progression of prediabetes to type 2 diabetes mellitus (T2DM) is severe, but effective interventions can delay or even reverse progression. High body weight is a common phenomenon in people with prediabetes. Unilateral weight-loss intervention may not be sufficient. We analyzed the interaction between body weight and the factors affecting prediabetes progression to T2DM and explored the influence of body weight and other factors, to better guide clinical intervention and reduce progression of prediabetes to T2DM.