Service by

Home Journal Issues Instructions for Authors Editorial Board About Journal Aims & Scope


Original Research 
RMJ. 2018; 43(3): 385-387


Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan

Naseem Asghar, Sohail Akhtar, Nasir Shaheen.

Abstract
Objective: To identify the most significant risk factors of cardiovascular disease (CVD) in district Swat.
Methodology: This cross sectional study was carried out in District Swat. A sample of 600 households from diverse union councils was included through probability sampling techniques to establish significant risk factors of cardiovascular disease. Logistic regression was applied using SPSS to examine the data and to choice the best fitted model.
Results: Among 600 interviewed individuals, 210 (35%) were CVD positive and 390 (65%) were CVD negative. There were 334 (56.66%) males while 266 (44.33%) were females. Of 266 females, only 93 (34.96%) had CVD. Out of 334 males, 117 (35.02%) had CVD. The results from binomial logistic regression showed that age, marital status, stress, and blood sugar were the most significant risk factors of CVD.
Conclusion: This study showed that blood sugar, stress, marital status and age are highly significant factors associated with the risk of CVD.

Key words: Risk factors, cardiovascular disease, logistic regression


 
ARTICLE TOOLS
Abstract
PDF Fulltext
Print this article Print this Article
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Naseem Asghar
Articles by Sohail Akhtar
Articles by Nasir Shaheen
on Google
on Google Scholar
Article Statistics
 Viewed: 156
Downloaded: 83
Cited: 0


How to Cite this Article
Pubmed Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. RMJ. 2018; 43(3): 385-387.


Web Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. http://www.rmj.org.pk/?mno=277512 [Access: November 17, 2018].


AMA (American Medical Association) Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. RMJ. 2018; 43(3): 385-387.



Vancouver/ICMJE Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. RMJ. (2018), [cited November 17, 2018]; 43(3): 385-387.



Harvard Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen (2018) Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. RMJ, 43 (3), 385-387.



Turabian Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. 2018. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. Rawal Medical Journal, 43 (3), 385-387.



Chicago Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. "Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan." Rawal Medical Journal 43 (2018), 385-387.



MLA (The Modern Language Association) Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen. "Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan." Rawal Medical Journal 43.3 (2018), 385-387. Print.



APA (American Psychological Association) Style

Naseem Asghar, Sohail Akhtar, Nasir Shaheen (2018) Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. Rawal Medical Journal, 43 (3), 385-387.




Instructions for Authors

AUTHOR LOGIN

REVIEWER LOGIN

Indexed In

WHO Index Medicus IMEMR,
Emromedex,
Pakmedinet,
ExtraMED and
Scopus

Approved by the Higher Education Commission of Pakistan and Pakistan Medical and Dental Council



The articles in Rawal Medical Journal are open access articles licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-sa/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.