Identifying Cardio-Metabolic Subtypes of Prediabetes Using Latent Class Analysis
Nuskabayeva G. Saruarov Y. Sadykova K. Zhunissova M. Nurdinov N. Babayeva K. Li M. Zhailkhan A. Kabibulatova A. Sarria-Santamera A.
December 2025Multidisciplinary Digital Publishing Institute (MDPI)
Medical sciences
2025#13Issue 4
Background/Objectives: Prediabetes (PreDM) is a heterogeneous condition, impacting hundreds of millions worldwide, associated with a substantially high risk of Type 2 Diabetes Mellitus (T2DM) and cardiovascular complications. Early identification of subgroups within the PreDM population may support tailored prevention strategies. Methods: We conducted a cross-sectional study using data from annual health check-ups of 419 university staff (aged 27–69) in Kazakhstan. Latent Class Analysis (LCA) was applied to identify subgroups of individuals with PreDM based on cardiovascular risk factors. Differences in glucose metabolism markers (fasting glucose, OGTT, HOMA-IR, HOMA-β) were compared across identified classes. Results: PreDM prevalence was 43.4%. LCA revealed four distinct classes: Class 1: healthy, low-risk individuals; Class 2: overweight with moderate metabolic risk; Class 3: older, overweight individuals with high cardio-metabolic risk; and Class 4: obese, middle-aged to older individuals with very high cardio-metabolic risk. Significant differences were found in glucose metabolism profiles across the classes. IFG predominated in Class 1 (95%), while Classes 3 and 4 had higher rates of β-cell dysfunction and combined IFG/IGT patterns. HOMA-β differed significantly between classes (p < 0.001), while HOMA-IR did not. Conclusions: PreDM is highly prevalent in this working-age Kazakh population and demonstrates marked heterogeneity. Based on easily obtainable cardiovascular risk factors, we have identified four subgroups with distinct glucose profiles that may inform personalized interventions. These distinct subgroups may require differentiated prevention strategies, moving beyond a one-size-fits-all approach.
cardiovascular risk , glucose metabolism , insulin resistance , Kazakhstan , latent class analysis , prediabetes , β-cell function
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Department of Special Clinical Disciplines, Medical Faculty, Khoja Akhmet Yassawi International Kazakh-Turkish University, Bekzat Sattarkhanov Street No. 29, Turkistan, 161200, Kazakhstan
Department of Fundamental Sciences, Medical Faculty, Khoja Akhmet Yassawi International Kazakh-Turkish University, Bekzat Sattarkhanov Street No. 29, Turkistan, 161200, Kazakhstan
Department of Biomedical Sciences, Nazarbayev University School of Medicine, Astana, 010000, Kazakhstan
Department of Special Clinical Disciplines
Department of Fundamental Sciences
Department of Biomedical Sciences
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