Gender Differences in Obesogenic Behaviour, Socioeconomic and Metabolic Factors in a Population-based Sample of Iranians: the IHHP Study

Overview

Journal J Health Popul Nutr

Publisher Biomed Central

Specialties Nutritional Sciences
Public Health

Date 2011 Jan 26

PMID 21261206

Citations 13

Authors

Ali Akbar Tavassoli

Mojgan Gharipour

Alireza Khosravi

Roya Kelishadi

Zahra Dana Siadat

Ahmad Bahonar

Gholam Hosein Sadri

Masoumeh Sadeghi

Katayoun Rabiei

Firouzeh Sajjadi

Sonia Zarfeshani

Babak Eshrati

Shahin Shirani

Nizal Sarrafzadegan

Affiliations

Soon will be listed here.

Abstract

This study investigated the gender differences in association of some behavioural and socioeconomic factors with obesity indices in a population-based sample of 12,514 Iranian adults. The mean body mass index (BMI), waist circumference (WC), and the waist-to-hip ratio (WHR) were significantly higher in women than in men. Current and passive smoking had an inverse association with BMI among males whereas current smoking, transportation by a private car, and longer duration of watching television (TV) had a positive association with BMI among females. Current and passive smoking, cycling, and Global Dietary Index (GDI) had an inverse association with WC among males. Higher consumption of fruits and vegetables, current and passive smoking, duration of daily sleep, and GDI had an inverse association with WC among females. Using a private car for transportation had a significant positive association with WHR among both males and females. Living in an urban area, being married, and having a higher education level increased the odds ratio of obesity among both the genders. Non-manual work also increased this risk among males whereas watching TV and current smoking increased this risk among females. Such gender differences should be considered for culturally-appropriate interventional strategies to be implemented at the population level for tackling obesity and associated cardiometabolic risk factors.

Citing Articles

Application of the Marginal Beta-Binomial Model in Estimation the Overall Odds of Obesity Among Iranian Adults: Meta-Analysis Method.

Zeinolabedini A, Biglarian A, Seifi B, Bakhshi E Int J Endocrinol Metab. 2019; 17(1):e68404.

PMID: 30881467 PMC: 6408730. DOI: 10.5812/ijem.68404.

Coronary atherosclerosis evaluation among Iranian patients with zero coronary calcium score in computed tomography coronary angiography.

Moradi M, Varasteh E Adv Biomed Res. 2016; 5:24.

PMID: 26962526 PMC: 4770603. DOI: 10.4103/2277-9175.175920.

Inequality of obesity and socioeconomic factors in Iran: a systematic review and meta- analyses.

Djalalinia S, Peykari N, Qorbani M, Larijani B, Farzadfar F Med J Islam Repub Iran. 2016; 29:241.

PMID: 26793632 PMC: 4715390.

Effect of age on the phenotype of metabolic syndrome in developing country.

Gharipour M, Sadeghi M, Hosseini M, Andalib E, Boroujeni M, Sarrafzadegan N Adv Biomed Res. 2015; 4:103.

PMID: 26261805 PMC: 4513307. DOI: 10.4103/2277-9175.157796.

The metabolic syndrome and associated lifestyle factors among the Iranian population.

Gharipour M, Sarrafzadegan N, Sadeghi M, Khosravi A, Hoseini M, Khosravi-Boroujeni H Adv Biomed Res. 2015; 4:84.

PMID: 26015910 PMC: 4434446. DOI: 10.4103/2277-9175.156645.

References

Nakamura Y, Turin T, Kita Y, Tamaki S, Tsujita Y, Kadowaki T . Associations of obesity measures with metabolic risk factors in a community-based population in Japan. Circ J. 2007; 71(5):776-81. DOI: 10.1253/circj.71.776. View

Mohammadifard N, Kelishadi R, Safavi M, Sarrafzadegan N, Sajadi F, Sadri G . Effect of a community-based intervention on nutritional behaviour in a developing country setting: the Isfahan Healthy Heart Programme. Public Health Nutr. 2009; 12(9):1422-30. DOI: 10.1017/S1368980008004230. View

Connor S, GUSTAFSON J, Flavell D, Hatcher L, Connor W . The cholesterol/saturated-fat index: an indication of the hypercholesterolaemic and atherogenic potential of food. Lancet. 1986; 1(8492):1229-32. DOI: 10.1016/s0140-6736(86)91384-x. View

DAlton M, Cameron A, Zimmet P, Shaw J, Jolley D, Dunstan D . Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med. 2003; 254(6):555-63. DOI: 10.1111/j.1365-2796.2003.01229.x. View

FRIEDEWALD W, Levy R, Fredrickson D . Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972; 18(6):499-502. View

Schneider H, Glaesmer H, Klotsche J, Bohler S, Lehnert H, Zeiher A . Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab. 2006; 92(2):589-94. DOI: 10.1210/jc.2006-0254. View

Sarraf-Zadegan N, Sadri G, Malek Afzali H, Baghaei M, Mohammadi Fard N, Shahrokhi S . Isfahan Healthy Heart Programme: a comprehensive integrated community-based programme for cardiovascular disease prevention and control. Design, methods and initial experience. Acta Cardiol. 2003; 58(4):309-20. DOI: 10.2143/AC.58.4.2005288. View

Canaan Rezende F, Rosado L, Ribeiro R, de Carvalho Vidigal F, Vasques A, Bonard I . Body mass index and waist circumference: association with cardiovascular risk factors. Arq Bras Cardiol. 2007; 87(6):728-34. DOI: 10.1590/s0066-782x2006001900008. View

Warnick G, Benderson J, Albers J . Dextran sulfate-Mg2+ precipitation procedure for quantitation of high-density-lipoprotein cholesterol. Clin Chem. 1982; 28(6):1379-88. View

10.

McNamara J, Schaefer E . Automated enzymatic standardized lipid analyses for plasma and lipoprotein fractions. Clin Chim Acta. 1987; 166(1):1-8. DOI: 10.1016/0009-8981(87)90188-4. View

11.

Seidell J, Perusse L, Despres J, Bouchard C . Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec Family Study. Am J Clin Nutr. 2001; 74(3):315-21. DOI: 10.1093/ajcn/74.3.315. View

12.

Abolfotouh M, Abdel Aziz M, Alakija W, Al-Safy A, Khattab M, Mirdad S . Smoking habits of King Saud University students in Abha, Saudi Arabia. Ann Saudi Med. 2007; 18(3):212-6. DOI: 10.5144/0256-4947.1998.212. View

13.

Sarraf-Zadegan N, Sayed-Tabatabaei F, Bashardoost N, Maleki A, Totonchi M, Habibi H . The prevalence of coronary artery disease in an urban population in Isfahan, Iran. Acta Cardiol. 1999; 54(5):257-63. View

14.

Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi M, Commerford P . Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005; 366(9497):1640-9. DOI: 10.1016/S0140-6736(05)67663-5. View

15.

Azizi F, Esmaillzadeh A, Mirmiran P, Ainy E . Is there an independent association between waist-to-hip ratio and cardiovascular risk factors in overweight and obese women?. Int J Cardiol. 2005; 101(1):39-46. DOI: 10.1016/j.ijcard.2004.03.011. View

16.

Sniderman A, Kiss R . The strengths and limitations of the apoB/apoA-I ratio to predict the risk of vascular disease: a Hegelian analysis. Curr Atheroscler Rep. 2008; 9(4):261-5. DOI: 10.1007/s11883-007-0031-6. View

17.

Wielgosz A . The decline in cardiovascular health in developing countries. World Health Stat Q. 1993; 46(2):90. View

18.

See R, Abdullah S, McGuire D, Khera A, Patel M, Lindsey J . The association of differing measures of overweight and obesity with prevalent atherosclerosis: the Dallas Heart Study. J Am Coll Cardiol. 2007; 50(8):752-9. DOI: 10.1016/j.jacc.2007.04.066. View

19.

Friedman M, Brownell K . Psychological correlates of obesity: moving to the next research generation. Psychol Bull. 1995; 117(1):3-20. DOI: 10.1037/0033-2909.117.1.3. View

20.

Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F . Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004; 364(9438):937-52. DOI: 10.1016/S0140-6736(04)17018-9. View