Principal Component Analysis of Categorized Parameters Used in the Study of Diabetes Mellitus And Dyslipidaemia in Association with Carotid Intima Medial Thickness

  • Malay Acharyya Department of Cardiology, Midnapore Medical College and Hospital, Midnapore, West Bengal, India
  • Tanushree Mondal Department of Health, Government of West Benga, Salt Lake, Kolkata – 700091, West Bengal, India
Keywords: Dyslipidaemia, Diabetes Mellitus, Carotid thickness


Background: Objective: The present study was attempted for multivariate analysis through principal component analysis for carotid intima medial thickness (CIMT) as dependent variable compared to different independent variables used as parameters in diabetes and dyslipidaemia.

Methods: The biochemical and obese data of total 75 patients were taken from earlier study. The data of six biochemical markers of DM and dyslipidaemia along with one obese marker and CIMT were analysed. Data were analysed for Pearson’s-Spearman correlation coefficients matrix for the relationships between CIMT and parameters of DM as well as dyslipidaemia. Principal component analysis (PCA) was performed to reduce the variables into a smaller number of uncorrelated predictor variables. Individual PC scores were generated from their risk factors loadings for DM and dyslipidaemia separately.

Results: The DM parameters PC loadings scores, which were generated from the individual PC scores, PC-1 (97.10% of the original variation explained) resulted in relatively high loadings for FBS and PPBS, moderately loading for HbA1c, lower loadings for urea and creatinine and least loading for BMI while PC-2 (1.79% of the variation explained) was negatively loaded for the BMI and PPBS but positively loaded for FBS, creatinine, urea and HbA1c. The dyslipidaemia parameters PC loadings scores, which were also generated from the individual PC scores for dyslipidaemia, PC-1 (83.93% of the original variation explained) resulted in relatively high loadings for TC, TG and VLDL while strongly negatively loaded for the BMI and LDL-C and HDL-C but positive loaded for TC, TG and VLDL while PC-2 (7.56% of the variation explained) was strongly negatively loaded for the HDL-C and VLDL but positively loaded for LDL-C followed by TC and BMI but least loading for TG.

Conclusions: This research work may be suitable tool to presents a significant step towards determining complex parameters and clinical biomarkers in DM and dyslipidaemia in association with CIMT that may ultimately play a role in CVD.


Download data is not yet available.


1. Altman DG, Altman E. Practical Statistics for Medical Research. Chapman & Hall/CRC; 1999.
2. Akoglu H. User's guide to correlation coefficients. Turkish Journal of Emergency Medicine. 2018;18:91-93.
3. Gabriel KR, Odoroff CL. Biplots in biomedical research. Statistics in Medicine. 1990;9:469-485.
4. Castelló A, Buijsse B, Martín M, Ruiz A, Casas A, et al. Evaluating the applicability of data-driven dietary patterns to independent samples with a focus on measurement tools for pattern similarity. Journal of the Academy of Nutrition and Dietetics. 2016;116:1914-1916.
5. Zhang Z, Castelló A. Principal components analysis in clinical studies. Annals of Translational Medicine. 2017;5(17):351. doi: 10.21037/atm.2017.07.12
6. Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, et al. Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) study, 1987-1993. American Journal of Epidemiology. 1997;146(6): 483-494.
7. O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, et al. Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. The New England Journal of Medicine. 1999;340(1):14-22.
8. Peters SA, Bots ML. Carotid intima-media thickness studies: study design and data analysis. Journal of Stroke. 2013;15(1):38-48.
9. Jin Y, Kim D, Cho J, Lee I, Choi K, Kang H. Association between obesity and carotid intima-media thickness in Korean office workers: The mediating effect of physical activity. BioMed Research International. 2018; 2018: Article ID 4285038.
10. Acharyya M, Haldar SK. Carotid intima medial thickness as a surrogatemarker for systemic atherosclerosis in type 2 diabetes mellitus. International Archives of Biomedical and Clinical Research. 2019;5(2):23-27.
11. Acharyya, M. Association between carotid intima medial thickness and dyslipidemia. International Archives of Biomedical and Clinical Research. 2019;5(4):GM1-GM5.
12. Abd alamir M, Goyfman M, Chaus A, Dabbous F, Tamura L, et al. The correlation of dyslipidemia with the extent of coronary arterydisease in the multiethnic study of atherosclerosis. Journal of Lipids. 2018; 2018: Article ID 5607349.
13. Łoboz-Rudnicka M, Jaroch J, Bociąga Z, Rzyczkowska B, Uchmanowicz I, et al. Impact of cardiovascular risk factors on carotid intima–media thickness: sex differences. Aging. 2016;11:721-731.
14. Pignoli P. Ultrasonography B mode imaging for arterial wall thickness measurement. Atherosclerosis Review. 1984;12:177-189.
15. Jaffe M. Uber den niederschlag, welchenpikrinsaure in normalenhrnerzeugt und uber eineneue reaction des kreatinins. Z Physiol Chem. 1886;10:391-400.
16. Rock RC, Walker WG, Hennings CD. Nitrogen metabolites and renal function. In: Tietz NW, ed. Fundamentals of Clinical Chemistry, 3rd ed. Philadelphia: WB Saunders. 1987;669-704.
17. Friendewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low density lipoprotein in plasma, without use of preparative ultracentrifuge. Clinical Chemistry. 1972;18:499-502.
18. WHO (World Health Organization). Physical status: The use of interpretation of anthropometry. Report of a WHO Expert Committee, WHO Technical Report Series 854, Geneva: Switzerland, 1995.
19. Liberda EN, Zuk AM, Tsuji LJS. Complex contaminant mixtures and theirassociations with intima-media thickness. BMC Cardiovascular Disorders. 2019; 19:289.
20. Sibal L, Agarwal SC, Home PD. Carotid intima-media thickness as a surrogate marker of cardiovascular disease in diabetes. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2011;4:23-34.
21. Bashir F, Nageen A, Kidwai SS, Ara J. Carotid intima-media thickness and cardiometabolic risk factors in Pakistani type 2 diabetics. Saudi Journal of Health Sciences. 2017;6:145-150.
22. Müller-Scholden L, Kirchhof J, Morbach C, Breunig M, Meijer R, et al. Segment-specific association of carotid-intima-media thickness with cardiovascular risk factors – findings from the STAAB cohort study. BMC Cardiovascular Disorders. 2019;19:84. doi:10.1186/s12872-019-1044-0
23. Burt C. Factor analysis and canonical correlations. British Journal of Psychology. 1948;1:95-106.
How to Cite
Acharyya M, Mondal T. Principal Component Analysis of Categorized Parameters Used in the Study of Diabetes Mellitus And Dyslipidaemia in Association with Carotid Intima Medial Thickness. Int Arch BioMed Clin Res [Internet]. 2020Mar.29 [cited 2020May28];6(1):GM14-GM18. Available from:
ORIGINAL ARTICLES ~ General Medicine