In this prospective longitudinal study, we followed 1228 prediabetic patients from 2003 to 2019 and evaluated the changes in serum lipid profile over time using LMM. Two latent states were identified based on the patterns of changes in lipid profiles mean and the states characterized by levels of tendency to progress diabetes (low/ high) with prevalence rates of (74%/ 26%), respectively. We observed that the lipid profile mean; in subjects assigned to “high tendency to progress diabetes” state was more than “low tendency to progress diabetes” state. The transition probability from the low to high tendency state was lower than the transition probability from high to low tendency state.
We did not find any study such as current one, which classified prediabetic patients into homogeneous states based on lipid profile mean over time using LMM. However, there are many studies in this regard among general population, and some specific population with applying simple statistical methods(9, 10, 28, 29).
Previous studies have focused on investigating the association of each lipid profile; TG, CHOL, HDL and LDL with the risk of diabetes in future or concurrently, separately. For instance, in Framingham Heart (30) study, T2DM subjects compared to those without T2DM, had higher plasma TG levels and lower HDL levels. Vineetha et al. in a case control study, was documented statistically significant higher values for TG and lower values for HDL in subjects with PD (31).
It is believed that lipid profile abnormality is a strong risk factor for T2DM in prediabetic patients (17, 32). In the present study, the subjects in high tendency to progress diabetes state had lipid profile abnormality. We observed that the mean of lipid profile abnormality associated with “high/low tendency to progress diabetes” states. This finding is in line with the results of previous studies have emphasized on the association of lipid profile disorders with the risk of diabetes (11, 12, 23, 33–36).
The Bhowmik et al. study obtained similar results with our study in terms of levels of dyslipidemia. Results showed a strong association between serum lipid profile and T2DM and PD. In addition, high levels of TG in combination with low levels of HDL showed the highest association with T2DM and PD. The levels of high CHOL, high TG, and low HDL were more elevated among subjects with T2DM and PD (13).
In the present study, in an irregular pattern, low HDL level was not associated with increased T2DM. In line our study, Hasse et al. reported that genetically reduced HDL was not associated with increased T2DM, suggesting that the corresponding observational association is due to confounding and/or reverse causation(9). In contrast, Hirano in the Hawaii- Los Angeles- Hiroshima study found that HDL is a predictor of T2DM, independent of age and gender in both Japanese-American and native Japanese(37). Janghorbani et al. in a population based longitudinal survey showed that low HDL level was a weak predictor of T2DM independent of age and gender in a cohort of high-risk individuals in Iran(38).
Although numerous researches exist about the risk factors of diabetes, but most research has ignored the complexity of diabetes disease and the reversible of diabetic states. In the current study, the probability for a subject in low tendency to progress diabetic state and to remain in the same condition was more than the probability for a subject in a high tendency to progress diabetic state which to remain in the same condition. Further, the transition probability from the low tendency to progress diabetic state to high tendency to progress diabetic state was lower than the transition probability from the high tendency to progress diabetic state to low tendency to progress diabetic state.
It is important to recognize some strengths and limitations of the present study. A major strength of our study is the applications of latent Markov model for classifying subjects according to the patterns of changes in lipid profile over time, instead of considering them as a single index. Other strengths of this study are population consisting of a large cohort of prediabetic patients, and the long-lasting followed-up of these subjects (16-year) and adjustment for some potential confounders in the analyses. The current findings were drawn from a study population of prediabetic patients; therefore, the results may not be applicable to all populations. We found that states identified based on lipid profile by LMM, in particular “low tendency to progress diabetes” and “high tendency to progress diabetes” are associated with the risk of diabetes in future in prediabetic patients.
In conclusion, abnormality of serum lipid profiles remains a significant and growing problem in prediabetic subjects as high risk population. The reduction in the problem burden will require changes at the policy level as well as at the personal level. Finally, should draw attention to abnormalities of lipid profiles is as an important step in preventing and managing diabetes.