Authors: Pary Hadi 1 & Zida Karim 2
1Food Technology Department, College of Agricultural Engineering Sciences, Salahaddin University, Erbil, Iraq
2Food Technology Department, College of Agricultural Engineering Sciences, Salahaddin University, Erbil, Iraq
Abstract: The prevalence of the metabolic syndrome is rising worldwide. This study aimed to demonstrate the association between major dietary patterns with metabolic syndrome components and the related lifestyle factors among adults in Erbil city. In this cross-sectional study, the participants were selected by applying convenience sampling method among healthy adults by means of lack of chronic diseases and not being pregnant. The study was conducted on a group of n=378 healthy adults filled the form consisted of the 3 sections (sociodemographic, physical activity questionnaire and food frequency questionnaire) in Tishk international university and Brayati neighborhood. among 378 participants, only n=203 participants responded to the practical part, n=113 females and n=90 males, aged between 19 to 60 years. Biochemical tests, anthropometrics, and blood pressure measurements were performed. factor analysis with a principal component PCA method was used to identify dietary patterns. Three major dietary patterns were identified and designed as healthy, western, and traditional with the factor loads (29.66, 20.56 and 17.56) respectively. A high score in western dietary pattern ranges was most correlated with a higher risk of abnormal blood glucose, HbA1c, cholesterol, and low-density lipoprotein concentration p-values (0.002, 0.022,0.015, and 0.008) respectively. The participants were determined to be %69.5 physically inactive. A significant association exists between dietary patterns and related lifestyle factors and metabolic syndrome risks among Erbil adults.
Keywords: Dietary Patterns, Metabolic Syndrome, Lifestyle, Factor Analysis, Adults
Published: January 10, 2023
Alidadi, Y., Metanati, M., & Ataie-Jafari, A. (2019). The validity of a bioelectrical impedance analyzer, Xiaomi MI scale 2, for measurement of body composition.
Aroian, K., Uddin, N., & Blbas, H. (2017). Longitudinal study of stress, social support, and depression in married Arab immigrant women. Health care for women international, 38(2), 100-117.
Baxter, J. B., Walker, A. M., Van Ommering, K., & Aydil, E. S. (2006). Synthesis and characterization of ZnO nanowires and their integration into dye-sensitized solar cells. Nanotechnology, 17(11), S304.
Cornier, M. A., Dabelea, D., Hernandez, T. L., Lindstrom, R. C., Steig, A. J., Stob, N. R., … & Eckel, R. H. (2008). The metabolic syndrome. Endocrine reviews, 29(7), 777-822.
Craig, C., Marshall, A., Sjostrom, M., Bauman, A., Lee, P., Macfarlane, D., … & Stewart, S. (2017). International physical activity questionnaire-short form. J Am Coll Health, 65(7), 492-501.
Dumith, S. C., Hallal, P. C., Reis, R. S., & Kohl III, H. W. (2011). Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Preventive medicine, 53(1-2), 24-28.
Eckel, R. H., Grundy, S. M., & Zimmet, P. Z. (2005). The metabolic syndrome. The lancet, 365(9468), 1415-1428.
Garcia, A., Abboud, P., Sylvestre, E., Jouniaux, F., Darcel, N. N., Higgs, S., & Davidenko, O. (2021, March). Social modeling of low and high energy density starters and desserts. In The British Feeding and Drinking Group (BFDG) 45th Annual Meeting.
Gibson, R. S., & Gibson, R. S. (2005). Principles of nutritional assessment. Oxford university press, USA.
He, D., Xi, B., Xue, J., Huai, P., Zhang, M., & Li, J. (2014). Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies. Endocrine, 46(2), 231-240.
Ibrahim, R. I., Mushatat, S. A., & Abdelmonem, M. G. (2015). Erbil. Cities, 49, 14-25.
Johnson, R. A., & Wichern, D. W. (2002). Applied multivariate statistical analysis. Upper Saddle River, NJ: Prentice hall, 5(8).
Kadam, P., & Bhalerao, S. (2010). Sample size calculation. International journal of Ayurveda research, 1(1), 55.
Kylin, E. (1923). Studien ueber das Hypertonie-Hyperglyka” mie-Hyperurika” miesyndrom. Zentralblatt für innere Medizin, 44, 105-127.
Lemmer, I. L., Willemsen, N., Hilal, N., & Bartelt, A. (2021). A guide to understanding endoplasmic reticulum stress in metabolic disorders. Molecular metabolism, 47, 101169.
Lüders, S., Krüger, R., Zemmrich, C., Forstner, K., Sturm, C. D., & Bramlage, P. (2012). Validation of the Beurer BM 44 upper arm blood pressure monitor for home measurement, according to the European Society of Hypertension International Protocol 2002. Blood Pressure Monitoring, 17(6), 248-252.
Mulligan, A. A., Luben, R. N., Bhaniani, A., Parry-Smith, D. J., O’Connor, L., Khawaja, A. P., … & Khaw, K. T. (2014). A new tool for converting food frequency questionnaire data into nutrient and food group values: FETA research methods and availability. BMJ open, 4(3), e004503.
Newby, P. K., & Tucker, K. L. (2004). Empirically derived eating patterns using factor or cluster analysis: a review. Nutrition reviews, 62(5), 177-203.
Peiris, C., Harding, K., Porter, J., Shields, N., Gilfillan, C., & Taylor, N. (2022). Understanding the hidden epidemic of metabolic syndrome in people accessing community rehabilitation: a cross-sectional study of physical activity, dietary intake, and health literacy. Disability and Rehabilitation, 1-9.
Roberts, L. B. (1967). The normal ranges, with statistical analysis for seventeen blood constituents. Clinica Chimica Acta, 16(1), 69-78.
Tang, K., Beaton, D. E., Amick, B. C., Hogg-Johnson, S., Côté, P., & Loisel, P. (2013). Confirmatory factor analysis of the Work Limitations Questionnaire (WLQ-25) in workers’ compensation claimants with chronic upper-limb disorders. Journal of occupational rehabilitation, 23(2), 228-238.
Trichia, E., Luben, R., Khaw, K. T., Wareham, N. J., Imamura, F., & Forouhi, N. G. (2020). The associations of longitudinal changes in consumption of total and types of dairy products and markers of metabolic risk and adiposity: findings from the European Investigation into Cancer and Nutrition (EPIC)–Norfolk study, United Kingdom. The American journal of clinical nutrition, 111(5), 1018-1026.
Vague, J. (1947). La différentiation sexuelle facteur déterminant des formes de l’obésité. Presse med, 30, 339-340.