Volume 16, Issue 3 (September 2018)                   Iranian Rehabilitation Journal 2018, 16(3): 307-316 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Yousefi R, Ghayour Mobarhan M, Esmaily H, Saki A, Ashley Anthony Ferns G, Tayefi M. Identifying Factors Associated With Hypertension Using Structural Equation Modeling: A Population-Based Study. Iranian Rehabilitation Journal. 2018; 16 (3) :307-316
URL: http://irj.uswr.ac.ir/article-1-851-en.html
1- Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
2- Endocrinology & Metabolism Research Center, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
3- Research Center for Social Factors Affecting Health, Mashhad University of Medical Sciences, Mashhad, Iran.
4- Division of Medical Education, Brighton & Sussex Medical School, Brighton, England.
Abstract:   (1479 Views)
Objectives: Hypertension is a global major health challenge and mechanisms related to the risk factors associated with it are poorly understood. Therefore, we used structural modeling to test a hypothesized model to identify factors associated with hypertension. 
Methods: A cross-sectional population based survey, was performed and the data related to a random representative sample of 9704 subjects of MASHAD study were used. Then, we determined the relationship between risk factors for hypertension using structural equation modeling technique. The data were analyzed using Amos V. 22. 
Results: The conceptual model was validated by Goodness of Fit Indexes (CFI=0.939, TLI=0.908, NFI=0.935, RMSEA=0.04, SRMR=0.037). Obesity and lack of physical activity had the greatest impact on blood pressure. 
Discussion: Findings show evidences to confirm the conceptual model considered in the risk factors for hypertension that can be helpful in policies for preventing hypertension and consequently, the disabilities that arise from it.
Full-Text [PDF 617 kb]   (645 Downloads) |   |   Full-Text (HTML)  (251 Views)  
Type of Study: Original Research Articles | Subject: Biostatistics
Received: 2018/01/24 | Accepted: 2018/07/20 | Published: 2018/09/1

1. Lifton RP, Gharavi AG, Geller DS. Molecular mechanisms of human hypertension. Cell. 2001; 104(4):545-56. [DOI:10.1016/S0092-8674(01)00241-0] [DOI:10.1016/S0092-8674(01)00241-0]
2. Kokkinos PF, Giannelou A, Manolis A, Pittaras A. Physical activity in the prevention and management of high blood pressure. Hellenic Journal of Cardiology. 2009; 50(1):52-9. [PMID] [PMID]
3. Venkataraman R, Satish Kumar BP, Kumaraswamy M, Singh R, Pandey M, Tripathi P. Smoking, alcohol and hypertension. International Journal of Pharmacy and Pharmaceutical Sciences. 2013; 5(4):28-32.
4. World Health Organization. A global brief on hypertension: Silent killer, global public health crisis 2016. Geneva: World Health Organization; 2016.
5. Javadi HR. [The prevalence of hypertension in people over 20 years of Qazvin (Persian)]. The Journal of Qazvin University of Medical Sciences. 1999; 3(1):23-9.
6. Erkinjuntti T, Gauthier S. Vascular cause of cognitive impairment-the perspective. London: Martin Dunitz; 2002.
7. Merrill FE, Penelope KE. Blood pressure and disability. Hypertension. 2007; 50(6):1006-8. [DOI:10.1161/HYPERTENSIONAHA.107.100883] [PMID] [DOI:10.1161/HYPERTENSIONAHA.107.100883]
8. Micklesfield LK, Munthali RJ, Prioreschi A, Said-Mohamed R, van Heerden A, Tollman S, et al. Understanding the relationship between socio-economic status, physical activity and sedentary behaviour, and adiposity in young adult South African women using structural equation modelling. International Journal of Environmental Research and Public Health. 2017; 14(10):1271. [DOI:10.3390/ijerph14101271] [PMID] [PMCID] [DOI:10.3390/ijerph14101271]
9. Primatesta P, Falaschetti E, Gupta S, Marmot MG, Poulter NR. Association between smoking and blood pressure: Evidence from the health survey for England. Hypertension. 2001; 37(2):187-93. [DOI:10.1161/01.HYP.37.2.187] [PMID] [DOI:10.1161/01.HYP.37.2.187]
10. Awosan K, Ibrahim M, Essien E, Yusuf A, Okolo A. Dietary pattern, lifestyle, nutrition status and prevalence of hypertension among traders in Sokoto Central market, Sokoto, Nigeria. International Journal of Nutrition and Metabolism. 2014; 6(1):9-17. [DOI:10.5897/IJNAM2013.0158] [DOI:10.5897/IJNAM2013.0158]
11. Bramlage P, Pittrow D, Wittchen HU, Kirch W, Boehler S, Lehnert H, et al. Hypertension in overweight and obese primary care patients is highly prevalent and poorly controlled. American Journal of Hypertension. 2004; 17(10):904-10. [DOI:10.1016/j.amjhyper.2004.05.017] [PMID] [DOI:10.1016/j.amjhyper.2004.05.017]
12. Cois A, Ehrlich R. Analysing the socioeconomic determinants of hypertension in South Africa: A structural equation modelling approach. BMC Public Health. 2014; 14:414. [DOI:10.1186/1471-2458-14-414] [DOI:10.1186/1471-2458-14-414]
13. Hooman HA. [Structural equation modeling with LISREL application (Persian)]. Tehran: SAMT Publication; 2009.
14. Altindag I, Genc A. Bayesian nonlinear structural equation modeling. Journal of Selcuk University Natural and Applied Science. 2015; 4(1):174-92.
15. Song XY, Xia YM, Lee SY. Bayesian semiparametric analysis of structural equation models with mixed continuous and unordered categorical variables. Statistics in Medicine. 2009; 28(17):2253-76. [DOI:10.1002/sim.3612] [PMID] [DOI:10.1002/sim.3612]
16. Ullman JB. Structural equation modeling: Reviewing the basics and moving forward. Journal of Personality Assessment. 2006; 87(1):35-50. [DOI:10.1207/s15327752jpa8701_03] [PMID] [DOI:10.1207/s15327752jpa8701_03]
17. Ghayour-Mobarhan M, Moohebati M, Esmaily H, Ebrahimi M, Parizadeh SM, Heidari-Bakavoli AR, et al. Mashhad stroke and heart atherosclerotic disorder (MASHAD) study: Design, baseline characteristics and 10-year cardiovascular risk estimation. International Journal of Public Health. 2015; 60(5):561-72. [DOI:10.1007/s00038-015-0679-6] [PMID] [DOI:10.1007/s00038-015-0679-6]
18. Joreskog, KG, Sorbom D. PRELIS 2: User's reference guide. Chicago: Scientific Software International; 1999.
19. Jöreskog KG. A general method for estimating a linear structural equation system. ETS Research Bulletin Series. 1970; 1970(2):i-41. [DOI:10.1002/j.2333-8504.1970.tb00783.x]
20. Kaplan D. Structural equation modeling: Foundations and extensions. Thousand Oaks, California: SAGA Publications; 2008.
21. Muthén LK, Muthén BO. Mplus user's guide. Los Angeles, CA: Muthén & Muthén; 2010. [PMCID]
22. Brown RL. Efficacy of the indirect approach for estimating structural equation models with missing data: A comparison of five methods. Structural Equation Modeling: A Multidisciplinary Journal. 1994; 1(4):287-316. [DOI:10.1080/10705519409539983] [DOI:10.1080/10705519409539983]
23. Kim JO, Curry J. The treatment of missing data in multivariate analysis. Sociological Methods & Research. 1977; 6(2):215-40. [DOI:10.1177/004912417700600206] [DOI:10.1177/004912417700600206]
24. Little RJ, Rubin DB. Statistical analysis with missing data. Hoboken, New Jersey: John Wiley & Sons; 2014.
25. Song XY, Lee SY. Analysis of structural equation model with ignorable missing continuous and polytomous data. Psychometrika. 2002; 67(2):261-88. [DOI:10.1007/BF02294846] [DOI:10.1007/BF02294846]
26. Bardenheier BH, Bullard KM, Caspersen CJ, Cheng YJ, Gregg EW, Geiss LS. A novel use of structural equation models to examine factors associated with prediabetes among adults aged 50 years and older: National Health and Nutrition Examination Survey 2001-2006. Diabetes Care. 2013; 36(9):2655-62. [DOI:10.2337/dc12-2608] [PMID] [PMCID] [DOI:10.2337/dc12-2608]
27. Shen BJ, Todaro JF, Niaura R, McCaffery JM, Zhang J, Spiro A, et al. Are metabolic risk factors one unified syndrome? Modeling the structure of the metabolic syndrome X. American Journal of Epidemiology. 2003; 157(8):701-11. [DOI:10.1093/aje/kwg045] [PMID] [DOI:10.1093/aje/kwg045]
28. Nock NL, Wang X, Thompson CL, Song Y, Baechle D, Raska P, et al. Defining genetic determinants of the Metabolic Syndrome in the Framingham heart study using association and structural equation modeling methods. BMC Proceedings. 2009; 3(7):S50. [DOI:10.1186/1753-6561-3-s7-s50] [DOI:10.1186/1753-6561-3-s7-s50]
29. Sadat Mousavian A, Ganbarzadeh M, Namvar F, Shakerian S. [Comparing effect of walking and selected aerobic exercise on blood pressure in overweight postmenopausal women (Persian)]. Journal of Urmia Nursing and Midwifery Faculty. 2014; 12(6):427-35.
30. Yang Q, Zhong Y, Merritt R, Cogswell ME. Trends in high blood pressure among United States adolescents across body weight category between 1988 and 2012. The Journal of Pediatrics. 2016; 169:166-73. [DOI:10.1016/j.jpeds.2015.10.007] [DOI:10.1016/j.jpeds.2015.10.007]

Send email to the article author

Designed & Developed by : Yektaweb