College Students’ Perception of Current and Projected 30-Year Cardiovascular Disease Risk Using Cluster Analysis with Internal Validation
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Cardiovascular risk factors in young adults at a national level are less than ideal specifically for hypercholesterolemia, hypertension, and diabetes. Explore college students’ perception of their 30-year cardiovascular disease (CVD) risk using cluster analysis technique with internal validation. This is a descriptive and cross-sectional study. A total of 133 college students, aged 20–36 with no known history of CVD, were recruited and used to perform cluster analysis with internal validation. The mean age of the sample was 24.85 and predominately female (59.5%). The mean score for perception of cardiovascular risk factors was 21.20 ranging from 12 to 34 points on a Likert scale. The mean score for the 30-year CVD risk assessment was 5.23 ranging from 1 to 22%. Five clusters emerged from the cluster analysis. However, two of the clusters, the highest risk with moderate perception and low risk and lowest perception, were identified as areas for potential intervention as there were discrepancies between subjects’ perceived risk and their actual 30-year risk. The national data and literature has indicated a lack of awareness of CVD risk among this population which our study also concurred. Identifying the discrepancies between the perceived and projected CVD risk are useful for researchers and clinicians such as nurses to take the initiative to focus on and begin to intervene in this population to reduce potential adverse events of CVD.
KeywordsCluster analysis Students Cardiovascular risk Perception
Compliance with Ethical Standards
Conflict of interest
The author declared no conflicts of interest related to this manuscript.
- 1.Akhtar, P. C., Haw, S. J., Currie, D. B., Zachary, R., & Currie, C. E. (2009). Smoking restrictions in the home and secondhand smoke exposure among primary schoolchildren before and after introduction of the scottish smoke-free legislation. Tobacco Control, 18(5), 409–415. https://doi.org/10.1136/tc.2009.030627.CrossRefGoogle Scholar
- 7.Davidson, P. M., Salamonson, Y., Rolley, J., Everett, B., Fernandez, R., Andrew, S., et al. (2011). Perception of cardiovascular risk following a percutaneous coronary intervention: A cross sectional study. International Journal of Nursing Studies, 48(8), 973–978. https://doi.org/10.1016/j.ijnurstu.2011.01.012.CrossRefGoogle Scholar
- 10.Greene, G. W., Schembre, S. M., White, A. A., Hoerr, S. L., Lohse, B., Shoff, S., et al. (2011). Identifying clusters of college students at elevated health risk based on eating and exercise behaviors and psychosocial determinants of body weight. Journal of the American Dietetic Association, 111(3), 394–400.CrossRefGoogle Scholar
- 14.Liu, Y., Li, Z., Xiong, H., Gao, X., & Wu, J. (2010). Understanding of internal clustering validation measures. In Paper presented at IEEE 10th international conference on data mining (ICDM), pp. 911–916.Google Scholar
- 19.Tovar, E. G., Rayens, M. K., Clark, M., & Nguyen, H. (2010). Development and psychometric testing of the health beliefs related to cardiovascular disease scale: Preliminary findings. Journal of Advanced Nursing, 66(12), 2772–2784. https://doi.org/10.1111/j.1365-2648.2010.05443.x.CrossRefGoogle Scholar
- 24.Zaki, S. M., Ajabnoor, M. A., Aziz, M. A., & Hassan, R. M. (2013). Relation of body composition to dietary habits and lifestyles among male college students with possible blood pressure affection: A cross section study. Wulfenia Journal, 20(4), 231–244.Google Scholar