ISSN 0303-5212
 
2026, Vol: 51, Issue: 2
51 / 2Current Issue Online FirstArchiveAims and ScopeAbstracting & IndexingMost Accessed ArticlesMost Downloaded ArticlesMost Cited Articles
Required files to be uploaded

Author_Certificate-old
Bank Reciept

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
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

How to Cite this Article
Pubmed Style

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

Web Style

Asghar N, Akhtar S, Shaheen N. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. https://www.rmj.org.pk/?mno=277512 [Access: June 27, 2026].

AMA (American Medical Association) Style

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


Vancouver/ICMJE Style

Asghar N, Akhtar S, Shaheen N. Statistical modeling in cardiovascular disease based on cross sectional survey from District Swat, Pakistan. RMJ. (2018), [cited June 27, 2026]; 43(3): 385-387.


Harvard Style

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


Turabian Style

Asghar, Naseem, Sohail Akhtar, and 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

Asghar, Naseem, Sohail Akhtar, and 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

Asghar, Naseem, Sohail Akhtar, and 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

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


Author LoginReviewer LoginEditorial PoliciesConflict of Interest PolicyPlagiarism PolicyAdvertising Policy

About Rawal Medical Journal

Publication, subscription and Editorial office PMA House G/220-B Liaquat Road, Rawalpindi. Phone: 051-555-9812, Fax: 051-553-7088 Email: drnkhokhar@ya ... Read more.



For best results, please use Internet Explorer or Google Chrome.

Contact Information