Abstract
Obesity and its associated health problems have been considered as a burden to health care providers where treatment may incur tremendous loss of public fund. Recent studies reveal that authentic factors contributed to obesity are very much inconclusive. Magnitude of risks for each factor remains unknown. This paper aims to propose risk values for the selected risk factors contributed to the development of obesity using an approach of ranking fuzzy number. The method of ranking fuzzy numbers based on circumcenter of centroid is proposed. The proposed model, which takes into account spread, area, and distance of trapezoidal fuzzy numbers was implemented to the case of obesity. Three experts were invited to provide qualitative linguistic evaluation over the importance of risk factors toward development of obesity. The risk values obtained from the proposed method unveiled that the factor of family history is the highest risk factor followed by sedentary life style. The results also indicate that gender is lowest risk factor. An implication for the general public is that the importance of knowing the status of family history and also the awareness in practising healthy life style.
Similar content being viewed by others
References
Abbasbandy, S., Hajjari, T.: A new approach for ranking of trapezoidal fuzzy numbers. Com. Math. App. 57, 413–419 (2009)
Abdullah, L., Azman, F.N.: Weights of obesity factors using analytic hierarchy process. Int. J. Res. Rev. App. Sci. 7(1), 57–83 (2011)
Abdullah, L., Ahmad, N.: Chocolate cakes preference using ranking fuzzy numbers. J. Qual. Meas. Anal. 7(2), 65–73 (2011)
Akyar, E., Akyar, H., Düzce, S.A.: Fuzzy risk analysis based on a geometric ranking method for generalized trapezoidal fuzzy numbers. J. Int. Fuzzy Syst. 25(1), 209–217 (2013)
Alsaif, M.A., Hakim, I.A., Harris, R.B., Alduwaihy, M., Al-Rubeaan, K., Al-Nuaim, A.R., Al-Attas, O.S.: Prevalence and risk factors of obesity and overweight in adult Saudi population. Nutr. Res. 22, 1243–1252 (2002)
Ban, O.I.: Fuzzy criteria decision making method applied to selection of the best touristic destinations. Int. J. Math. Mod. Meth. App. Sci. 5, 264–271 (2011)
Bella, S.D., Lucchini, M.: Education and BMI: a genetic informed analysis. Qual Quant (2014). doi:10.1007/s11135-014-0129-1
Chang, S.L., Zadeh, L.A.: On fuzzy mapping and control. IEEE Trans. Syst. Man Cybernet. 2, 30–34 (1972)
Chen, S.J., Hwang, C.L.: Fuzzy Multiple Attribute Decision Making. Springer, Berlin (1992)
Chen, S.H.: Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets Syst. 17, 113–129 (1985)
Chen, S.M., Chen, J.H.: Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. Exp. Syst. App. 36, 6833–6842 (2009)
Cheng, C.H.: A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst. 95, 307–317 (1998)
Chu, T.C., Tsao, C.T.: Ranking fuzzy numbers with an area between the centroid point and original point. Com. Math. App. 43, 111–117 (2002a)
Chu, T.C., Tsao, C.T.: Ranking fuzzy numbers with an area between the centroid point and original point. Comp. Math. Appl. 43, 111–117 (2002b)
De Fonseca, V.M., Sichieri, R., Da Veiga, G.V.: Factors associated with obesity among adolescents. [Fatores associados à obesidade em adolescentes]. Rev. Saude Publica 32(6), 541–549 (1998)
Del, P.A., Chen, K., Gautier, J.F.: Sex differences in the human brain’s response to hunger and satiation. Am. J. Clin. Nutr. 75, 1017–1022 (2002)
Dubois, D., Prade, H.: Ranking of fuzzy numbers in the setting of possibility theory. Inform. Sci. 30, 183–224 (1983)
Duraisamy, C., Usha, B.: Another approach to solution of fuzzy differential equations. App. Math. Sci. 4, 777–790 (2010)
Duzce, S.A.: A new ranking method for trapezial fuzzy numbers and its application to fuzzy risk analysis. J. Intell. Fuzzy Syst. 28(3), 1411–1419 (2015)
Garn, S.M., Clark, D.C.: Problems in the nutritional assessment of Black individuals. Am. J. Pub. Health 66, 262–267 (1976)
Guillaume, M., Lapidus, L., Beckers, F., Lambert, A., Bjorntorp, P.: Familial trends of obesity through three generations: the Belgian-Luxemborg child study. Int. J. Obes. R. Meta. Disord. 3, 5–9 (1995)
Harijono, A., Puryatni, A., Cahyono, H.A., Yosoprawoto, M.: Prevalence and risk factors of overweight and obesity in adolescents in Malang, East Java-Indonesia. Int. J. Pediatr. Endocr. (2013). doi:10.1186/1687-9856-2013-S1-O50
Haslam, D.W., James, W.P.: Obesity. Lancet 366(9492), 1197–1209 (2005)
Kelishadi, R.: Childhood overweight, obesity, and the metabolic syndrome in developing countries. Epidemiol. Rev. 29, 62–76 (2007)
Klir, G.J., Yuan, B.: Fuzzy Set and Fuzzy Logic: Theory and Applications. Prentice Hall PTR, New Jersey (1995)
Kunesova, M., Vignerova, J., Steflová, A., Parízkova, J., Lajka, J., Hainer, V., Blaha, P., Hlavaty, P., Kalouskova, P., Hlavata, K., Wagenknecht, M.: Obesity of Czech children and adolescents: relation to parental obesity and socioeconomic factors. J. Pub. Health 15(3), 163–170 (2007)
Martínez-González, M.A., Martínez, J.A., Hu, F.B., Gibney, M.J., Kearney, J., et al.: Physical inactivity, sedentary lifestyle and obesity in the European Union. Int. J. Obes. Rel. Met. Dis. 23, 1192–1201 (1999)
Patra, K., Mondal, S.K.: Risk analysis in diabetes prediction based on a new approach of ranking of generalized trapezoidal fuzzy numbers. Cyber. Syst. 43, 623–650 (2012)
Peltzer, K., Pengpid, S.: Overweight and obesity and associated factors among school-aged adolescents in Ghana and Uganda. Int. J. Environ. Res. Public Health 8(10), 3859–3870 (2011)
Puoane, T., Steyn, K., Bradshaw, D.: Obesity in South Africa: the South African demographic and health survey. Obes. Res. 10, 1038–1048 (2002)
Rao, P.P.B., Shankar, N.R.: Ranking fuzzy numbers with a distance method using circumcenter of centroids and index of modality. Adv. Fuzzy Syst. 3, 1–7 (2011)
Rezvani, S.: A new method for ranking in perimeters of two generalized trapezoidal fuzzy numbers. Int. J. App. Oper. Res. 2, 85–92 (2012)
Shankar, N.R., Abdullah, L., Thorani, Y.L.P., Rao, P.P.B.: Fuzzy risk analysis based on a new approach of ranking fuzzy numbers using orthocenter of centroids. Int. J. Com. App. 42, 24–36 (2012)
Sweeting, H.N.: Gendered dimensions of obesity in childhood and adolescence. Nutr. J. 7, 1 (2008)
Thibault, H., Contrand, B., Saubusse, E., Baine, M., Maurice-Tison, S.: Risk factors for overweight and obesity in French adolescents. Physicalactivity, sedentary behavior and parental characteristics. Nutr. 26(2), 192–200 (2010)
Thorani, Y.L.P., Rao, P.P.B., Shankar, N.R.: Ordering generalized trapezoidal fuzzy numbers. Int. J. Cont. Math. Sci. 7, 555–573 (2012)
WHO: Physical inactivity: a global public health problem. World Health Organization. http://www.who.int/dietphysicalactivity/factsheet_inactivity/en/index.html (2009). Accessed 22 Feb 2009
WHO: Global comparisons in obesity. World Health Organization. http://www.wpro.who.int/mediacentre/factsheets/obesity/en/index.html (2013). Accessed 24 Apr 2013
WHO: Obesity: Preventing and Managing the Global Epidemic, Report of a WHO Consultation on Obesity, World Health Organisation, Geneva (1998)
WHO: Obesity: Preventing and Managing the Global Epidemic: Report of a WHO Consultation. WHO Technical Report Series no. 894, WHO, Geneve (2000)
Zellner, D.A., Loaiza, S., Gonzalez, Z.: Food selection changes under stress. Phy. Behav. 87, 789–793 (2006)
Zhang, F., Ignatius, J., Lim, C.P., Zhao, Y.: A new method for ranking fuzzy numbers and its application to group decision making. App. Math. Mod. 38(4), 1563–1582 (2014)
Zimmermann, H.J.: Fuzzy set theory and its application, 4th edn. Kluwer Academic, Boston (2001)
Zou, J., Yu, P., Hu, S., Wang, L.: Incidence of overweight and obesity and the influencing factors among 6020 health examinees in Liuzhou city. Chi. J. Clin. Rehab. 9(3), 22–23 (2005)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Abdullah, L., Azman, F.N. Circumcenter of centroid of fuzzy number for identifying risk factors of obesity: a qualitative evaluation. Qual Quant 50, 2433–2449 (2016). https://doi.org/10.1007/s11135-015-0270-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11135-015-0270-5