Growth trajectories in lipid profile and fasting blood sugar in prediabetic people over a 16- year follow-up and future risk of type2 diabetes mellitus: A latent growth modeling approach
| Autor: | Awat Feizi, Fahimeh Haghighatdoost, Parisa Zakeri, Ashraf Aminorroaya, Masoud Amini |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Alexandria Journal of Medicine, Vol 58, Iss 1, Pp 52-59 (2022) |
| Druh dokumentu: | article |
| ISSN: | 20905068 2090-5076 2090-5068 |
| DOI: | 10.1080/20905068.2022.2062958 |
| Popis: | Introduction The current study aimed to investigate whether the pattern of changes in lipid profile and fasting blood sugar (FBS) can predict the future risk of type 2 diabetes mellitus (T2DM) incidence in prediabetic people.Methods In a prospective cohort study, 1228 prediabetic patients were followed from 2003 until 2019 and longitudinal data on lipid indices (CHOL: cholesterol; HDL: high-density lipoprotein; LDL: low-density lipoprotein; TG: triglyceride) and fasting blood sugar (FBS) were recorded. The latent class growth model (LCGM) was used to estimate growth trajectories and to determine distinct subgroups (latent class) with a similar trajectory for lipid profile and FBS over time. The incidence of T2DM in extracted latent classes was compared.Results Finally, 946 people with complete data were included in statistical analysis. Two latent classes were identified based on the change in FBS including high-risk and low-risk classes (class size: 5.2% vs. 94.8%) with T2DM incidence rates 100% and 35.9%, respectively (P 0.05).Conclusions We identified two subgroups with high and low risk of future T2DM based on the changes in FBS and lipid profile by applying LCGM. The incidence of T2DM in extracted latent classes was significantly different. LCGM is a reliable approach for predicting the risk of T2DM incidence based on trajectories of risk factors. |
| Databáze: | Directory of Open Access Journals |
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