Predicting the factors influencing the turnout of community members for cosmetic procedures and surgeries using binary logistic regression

Abstract

The statistical method known as binary logistic regression, which is widely used in various social, medical, marketing, and other fields, was used to predict the most important demographic, social, health, economic, and psychological factors affecting the widespread turnout by members of society of both sexes, ages 20 years and over, for non-invasive cosmetic procedures and surgeries. Therapeutic Data were collected for more than 100 questionnaire forms that were distributed electronically for the privacy of the respondents to visitors of a group of beauty centers in Baghdad. The results of the statistical analysis using the SPSS program revealed the importance of 8 factors out of 12 factors included in the study, which are (gender, age), demographic factors, and (marital status, Level of education) Social factors (profession, offers from beauty centers) Among the economic factors (resistance to the effects of aging, dissatisfaction with the image of one's figure and body) and psychological factors, the factors that were not statistically significant in the prediction equation were monthly income, treatment of birth defects, exposure to an accident, and bullying.