Histogram-based Sub-classification of Serum Triglycerides and Hypertriglyceridemia Prevalence Across Gender and Age Groups: A Cross-sectional Study

Introduction: The ICMR-Indiab study (2014) and National Centres for Environmental Prediction (NCEP) (2001) guidelines recommended a healthy cut-off for serum triglycerides of <150 mg/dL. The European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) guidelines (2019) proposed a cut-off between moderate hypertriglyceridemia and severe hypertriglyceridemia at 885 mg/dL. There are currently no studies addressing the cut-off values and prevalence of moderate and severe hypertriglyceridemia within the Indian population. These requirements are addressed through the use of the histogram method for calculating cut-off levels and prevalence of hypertriglyceridemia, which is unique to the present study. Aim: To sub-classify serum triglyceride concentrations using histogram regions and to calculate the percentage of hypertriglyceridemia from these histogram regions across gender and age groups for the upper cut-off level. Materials and Methods: The present study was an observational cross-sectional study conducted at the Department of Biochemistry, Amala Cancer Research Centre, Amala Institute of Medical Sciences, Amala Nagar, Thrissur, Kerala, India on healthy individuals and those with dyslipidemic conditions. Serum triglyceride data was collected from the clinical biochemistry laboratory from September 2018 to March 2022. Samples were partitioned according to gender and age groups of <18, 18 to 25, 26 to 50 and >50 years. Triglycerides were assayed using an enzymatic method. The histogram was divided into healthy (<150 mg/dL), positively skewed and outlier regions. Sample distribution before and after outlier removal was represented by the histogram and analysed using the ShapiroWilk and Jarque-Bera tests. Gender differences were analysed using the Mann-Whitney U test with Statistical Package for Social Sciences (SPSS) software. Results: The number of samples increased with age. In the histogram, the sample number decreased sequentially from the healthy region to the positively skewed and finally to the outlier region across all age groups. The p-value for distributions before the removal of outliers was <0.001. Males had higher mean triglyceride levels, with p-values ranging from <0.001 to 0.029 and exhibited a higher prevalence of hypertriglyceridemia in all groups. The histogram method allowed for the differentiation between the highly prevalent multifactorial moderate hypertriglyceridemia and the rare severe single-gene defects. Conclusion: The study partitioned triglyceride concentrations using a histogram into healthy, positively skewed and outlier regions. The histogram of hypertriglyceridemia can be clinically utilised to differentiate between the highly prevalent, multifactorial moderate hypertriglyceridemia and the rare, severe monogenic hypertriglyceridemia.