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      Factors Predicting Nutrition and Physical Activity Behaviors Due to Cardiovascular Disease in Tehran University Students: Application of Health Belief Model

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          Abstract

          Background:

          Disease preventing methods focus mostly on lifestyle factors such as physical activity, healthy diet and not smoking. Previous studies verified using theory and models to change unhealthy behaviors, so that health belief model (HBM) is a useful framework for describing the healthy nutrition behavior.

          Objectives:

          This study aimed to predict factors related to unhealthy nutrition and inactive life in students of Tehran University, Tehran, Iran based on the Health Belief Model (HBM).

          Patients and Methods:

          In this cross sectional study, proportional quota sampling from three different educational levels was conducted from October to December 2012. A self-administered validated instrument based on the Health Belief Model (HBM) with 69 items and four sections was used to collect data. In this study through using linear and logistic regression, the effect of body mass index, age, gender, marriage, self-efficacy, cues to action, knowledge, perceived severity, susceptibility, benefits and barriers on nutrition and physical activity behavior were assessed. SPSS version 18 was used to analyze data.

          Results:

          Totally, 368 students including 318 female students (86.4%) and 50 male students (13.6%) with a mean age of 24.9 years (SD = 4.55) took part in the study. Among all independent variables, gender (P < 0.001), knowledge (P = 0.023) and perceived barriers (P = 0.004) predicted nutrition behavior. In case of physical activity, knowledge (P = 0.011), perceived severity (P = 0.009), perceived barriers (P = 0.019) and self-efficacy (P = 0.033) had significance association with physical activity behavior.

          Conclusions:

          This study indicated that health belief model contrasts could predict the risky behavior of university students due to heart disease. However, more researches are needed to verify the predictors of high risky behaviors in students.

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          Most cited references34

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          Prevalence of metabolic syndrome in an urban population: Tehran Lipid and Glucose Study.

          Fereidoun Azizi, Payam Salehi, Arash Etemadi … (2003)
          The aim of the present investigation was to determine the prevalence of the metabolic syndrome among 103,68 of the adults (4,397 men and 5,971 women) aged 20 years and over, participating in the Tehran Lipid and Glucose Study. The metabolic syndrome was defined by the presence of three or more of the following components: abdominal obesity, hypertriglyceridemia, low HDL-C, high blood pressure, and high fasting glucose. The unadjusted prevalence of metabolic syndrome in the study population was 30.1% (CI 95%: 29.2-31.0) and age-standardized prevalence was 33.7% (CI 95%: 32.8-34.6). The prevalence increased with age in both sexes. The metabolic syndrome was more commonly seen in women than in men (42% vs. 24%, P<0.001). Low HDL-C was the most common metabolic abnormality in both sexes. Except for high FPG, all abnormalities were more common in women than in men (P<0.001). Most of those with metabolic syndrome had three components of the syndrome (58%), 33% had four, and 9% had five components. This report on the metabolic syndrome from Iran shows a high prevalence of this disorder. Efforts on promoting healthy diets, physical activity, and blood pressure control must be undertaken.
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            Evaluation of newer risk markers for coronary heart disease risk classification: a cohort study.

            Francesco U. S. Mattace-Raso, Charlotte H. B. S. van den Berg, Ewout W. Steyerberg … (2012)
            Whether newer risk markers for coronary heart disease (CHD) improve CHD risk prediction remains unclear. To assess whether newer risk markers for CHD risk prediction and stratification improve Framingham risk score (FRS) predictions. Prospective population-based study. The Rotterdam Study, Rotterdam, the Netherlands. 5933 asymptomatic, community-dwelling participants (mean age, 69.1 years [SD, 8.5]). Traditional CHD risk factors used in the FRS (age, sex, systolic blood pressure, treatment of hypertension, total and high-density lipoprotein cholesterol levels, smoking, and diabetes) and newer CHD risk factors (N-terminal fragment of prohormone B-type natriuretic peptide levels, von Willebrand factor antigen levels, fibrinogen levels, chronic kidney disease, leukocyte count, C-reactive protein levels, homocysteine levels, uric acid levels, coronary artery calcium [CAC] scores, carotid intima-media thickness, peripheral arterial disease, and pulse wave velocity). Adding CAC scores to the FRS improved the accuracy of risk predictions (c-statistic increase, 0.05 [95% CI, 0.02 to 0.06]; net reclassification index, 19.3% overall [39.3% in those at intermediate risk, by FRS]). Levels of N-terminal fragment of prohormone B-type natriuretic peptide also improved risk predictions but to a lesser extent (c-statistic increase, 0.02 [CI, 0.01 to 0.04]; net reclassification index, 7.6% overall [33.0% in those at intermediate risk, by FRS]). Improvements in predictions with other newer markers were marginal. The findings may not be generalizable to younger or nonwhite populations. Among 12 CHD risk markers, improvements in FRS predictions were most statistically and clinically significant with the addition of CAC scores. Further investigation is needed to assess whether risk refinements using CAC scores lead to a meaningful change in clinical outcome. Whether to use CAC score screening as a more routine test for risk prediction requires full consideration of the financial and clinical costs of performing versus not performing the test for both persons and health systems. Netherlands Organization for Health Research and Development (ZonMw).
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              Social Cognitive Determinants of Nutrition and Physical Activity Among Web-Health Users Enrolling in an Online Intervention: The Influence of Social Support, Self-Efficacy, Outcome Expectations, and Self-Regulation

              Eileen Anderson-Bill, Richard A. Winett, Janet R Wojcik (2011)
              Background The Internet is a trusted source of health information for growing majorities of Web users. The promise of online health interventions will be realized with the development of purely online theory-based programs for Web users that are evaluated for program effectiveness and the application of behavior change theory within the online environment. Little is known, however, about the demographic, behavioral, or psychosocial characteristics of Web-health users who represent potential participants in online health promotion research. Nor do we understand how Web users’ psychosocial characteristics relate to their health behavior—information essential to the development of effective, theory-based online behavior change interventions. Objective This study examines the demographic, behavioral, and psychosocial characteristics of Web-health users recruited for an online social cognitive theory (SCT)-based nutrition, physical activity, and weight gain prevention intervention, the Web-based Guide to Health (WB-GTH). Methods Directed to the WB-GTH site by advertisements through online social and professional networks and through print and online media, participants were screened, consented, and assessed with demographic, physical activity, psychosocial, and food frequency questionnaires online (taking a total of about 1.25 hours); they also kept a 7-day log of daily steps and minutes walked. Results From 4700 visits to the site, 963 Web users consented to enroll in the study: 83% (803) were female, participants’ mean age was 44.4 years (SD 11.03 years), 91% (873) were white, and 61% (589) were college graduates; participants’ median annual household income was approximately US $85,000. Participants’ daily step counts were in the low-active range (mean 6485.78, SD 2352.54) and overall dietary levels were poor (total fat g/day, mean 77.79, SD 41.96; percent kcal from fat, mean 36.51, SD 5.92; fiber g/day, mean 17.74, SD 7.35; and fruit and vegetable servings/day, mean 4.03, SD 2.33). The Web-health users had good self-efficacy and outcome expectations for health behavior change; however, they perceived little social support for making these changes and engaged in few self-regulatory behaviors. Consistent with SCT, theoretical models provided good fit to Web-users’ data (root mean square error of the approximation [RMSEA] < .05). Perceived social support and use of self-regulatory behaviors were strong predictors of physical activity and nutrition behavior. Web users’ self-efficacy was also a good predictor of healthier levels of physical activity and dietary fat but not of fiber, fruits, and vegetables. Social support and self-efficacy indirectly predicted behavior through self-regulation, and social support had indirect effects through self-efficacy. Conclusions Results suggest Web-health users visiting and ultimately participating in online health interventions may likely be middle-aged, well-educated, upper middle class women whose detrimental health behaviors put them at risk of obesity, heart disease, some cancers, and diabetes. The success of Internet physical activity and nutrition interventions may depend on the extent to which they lead users to develop self-efficacy for behavior change, but perhaps as important, the extent to which these interventions help them garner social-support for making changes. Success of these interventions may also depend on the extent to which they provide a platform for setting goals, planning, tracking, and providing feedback on targeted behaviors.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Iran Red Crescent Med J
                Journal ID (iso-abbrev): Iran Red Crescent Med J
                Journal ID (doi): 10.5812/ircmj
                Journal ID (publisher-id): Kowsar
                Title: Iranian Red Crescent Medical Journal
                Publisher: Kowsar
                ISSN (Print): 2074-1804
                ISSN (Electronic): 2074-1812
                Publication date (Electronic): 20 March 2015
                Publication date Collection: March 2015
                Volume: 17
                Issue: 3
                Electronic Location Identifier: e18879
                Affiliations
                [1 ]Health Research Center, Baqiyatallah University of Medical Sciences, Tehran, IR Iran
                [2 ]Department of Health Educations, Faculty of Medical Sciences, Tarbiat Modaress University, Tehran, IR Iran
                [3 ]Biostatistics Department, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, IR Iran
                [4 ]Department Of Psychology,College of Humanitiec saveh Science and Research Branch Islamic Azad University Saveh, IR Iran
                Author notes
                [* ]Corresponding Author: Sedigheh Sadat Tavafian, Department of Health Educations, Faculty of Medical Sciences, Tarbiat Modaress University, Tehran, IR Iran. Tel: +98-2182884547, Fax: +98-2182884555, E-mail: tavafian@ 123456modares.ac.ir
                Article
                DOI: 10.5812/ircmj.18879
                PMC ID: 4441786
                PubMed ID: 26019896
                SO-VID: d8ac75b8-de82-4b60-acf3-76056f1ff5d3
                Copyright © Copyright © 2015, Iranian Red Crescent Medical Journal.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

                History
                Date received : 11 March 2014
                Date revision received : 07 May 2014
                Date accepted : 25 August 2014
                Categories
                Subject: Research Article

                ScienceOpen disciplines: Medicine
                Keywords: behavior,heart disease,health belief model,physical activity
                Data availability:
                ScienceOpen disciplines: Medicine
                Keywords: behavior, heart disease, health belief model, physical activity

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