Relationship between Glycaemic Parameters and Mean Platelet Volume among Pre-Diabetics and Non-Diabetics in a Predominantly Tribal Population BC18-BC22
Dr. Manoj Kumar Dash,
Assistant Professor, Department of Community Medicine, PRM Medical College, PO-Laxmiposi, Baripada-757107, Odisha, India.
Introduction: Pre-diabetics are considered an important risk set within the population who though ‘apparently normal’ are at the highest risk of progression to clinical diabetes. Interventions in this subset can reduce or delay the onset of many dreaded complications of hyperglycaemia, especially cardiovascular complications, which are one of the leading causes of morbidity and mortality.
Aim: The study was designed and carried out to determine the relationship between Mean Platelet Volume (MPV) and glycaemic parameters in non-diabetics of predominantly tribal origin.
Materials and Methods: The study subjects were selected on the principle of convenient and consecutive sampling. Adult patients self-reporting to the Central Laboratory of a medical college hospital located in a predominantly tribal district of Odisha. Blood samples were collected for routine haematological and biochemical parameters. Based on the fasting plasma glucose, the patients were divided into normoglycaemics and pre-diabetics. The linear relationship between the quantitative variables was evaluated by computing the Pearson’s correlation coefficients. The independent relationship between MPV and the other study variables was analysed by multiple linear regressions.
Results: The study was conducted with a total of 109 individuals (62 males and 47 females). Glycaemic parameters were significantly different between pre-diabetics and normoglycaemics with higher level in the pre-diabetics compared to normoglycaemics. Fasting Plasma Glucose (FPG) and Post Prandial Plasma glucose (PPPG) showed modest (r<0.5) positive correlation with MPV with variable statistical significance, but blood insulin level showed strong (r>0.5) positive correlation that was robustly significant. MPV was regressed on FPG, PPPG, insulin, cholesterol and total platelet count. The adjusted r square of the model varied between 0.415 and 0.637 for all the datasets with the highest value (0.637) for the pre-diabetics group. The strongest and statistically significant independent correlation was seen between MPV and insulin in all the datasets, with highest values in the prediabetics group (standardised beta coefficient=0.680).
Conclusion: The glycaemic parameters especially fasting blood glucose, PPPG, and insulin were found to be correlated with MPV in both normoglycaemics as well as pre-diabetics. The pre-diabetics showed higher levels than normoglycaemics. Thus, MPV may serve as an important marker in early detection of cardiovascular complications, in the non-diabetics.