Multiple regression analysis of the relationship between some predictors of socioeconomic status and developmental instability

Authors : Barış ÖZENER, Berna ERTUĞRUL

Pages : 18-25

View : 18 | Download : 5

Publication Date : 2010-06-30

Article Type : Research Paper

Abstract :Fluctuating asymmetry insert ignore into journalissuearticles values(FA); is thought to be the outcome of developmental instability, the impressive expression of design due to perturbations during development. Early interest in FA has been centered on its potential as an indicator of environmental stress. The aim of this study is to determine the effect of socioeconomic status on the level of FA in Turkish young males. The study examined 350 young males insert ignore into journalissuearticles values(mean age = 8.65±0.58); who live under different socioeconomic conditions in Ankara. Family size, mother’s education, father’s education, mother’s job, father’s job, number of siblings and number of rooms were assessed. The hand length, hand width, elbow width, wrist width, knee width, ankle width, foot length, foot width, ear height and ear width of the subjects were measured with a Vernier digital caliper of 0.01 mm sensitivity. According to multiple regression analysis, relationship between composite fluctuating asymmetry and family size, mother’s education, father’s education, mother’s job, father’s job, number of siblings, number of rooms were statistically significant insert ignore into journalissuearticles values(R2 = 0.41, F = 17.95, P < 0.001);. Standardized coefficients-β values showed that the mother’s and father’s educations had higher correlations even when the effects of other predictors were controlled. We conclude that fluctuating asymmetry was found to increase with the improving living standards. However, when the effects of the SES variables were considered separately, mother’s education and then father’s job were found to have greater effects on developmental stability.
Keywords : Developmental instability, fluctuating asymmetry, socioeconomic predictors, multiple regression analysis