An In-Depth Regression Analysis on Anthropometric Indices Influencing Subjective Weight Perception

Background: Subjective weight perception significantly impacts overall health and is influenced by various factors. This study aims to develop predictive models using anthropometric indices to estimate subjective weight perception in women. Methods: This descriptive cross-sectional study involved a random sample of ۲۸۷ women, aged ۱۸-۴۵, with a body mass index (BMI), ranging from ۱۸.۵ to ۴۰.۰ kg/m۲ who were referred to a nutrition clinic in Ardabil city between May and September ۲۰۲۳.  Weight, BMI, waist-to-hip ratio (WHR), waist circumference (WC), waist-to-height ratio (WHtR), body adipocyte index (BAI), abdominal volume index (AVI), and conicity index (CI) were measured using standardized procedures. Subjective weight was assessed using a subscale of the Multidimensional Body Self-Relation Questionnaire. Regression analysis was employed to develop prediction models. Results: The predictive equation for subjective weight was ۲.۵۴۸ + (-۰.۳۰۳ × weight in kg) + (۰.۰۸۹ × BMI in kg/m۲) + (۲۷.۷۷۳ × WHR) + (۱.۰۳۲ × WC in cm) + (-۱۰۹.۲۵۶ × WHR) + (۰.۵۴۰ × BAI in %) + (-۰.۲۶۰ × AVI in m۲) + (-۳۹.۴۲۳ × CI in m۳/۲kg− ۱/۲). The model accounted for ۷۸.۵۰% of the variance and significantly predicted subjective weight perception (F (۸, ۲۷۹) = ۱۰۴.۶۰۴, and p < ۰.۰۰۱). Weight, WHR, WC, WHtR, BAI, and CI significantly contributed to the model (p < ۰.۰۵). Conclusion: The findings underscore the importance of considering multiple anthropometric indices to understand individual differences in subjective weight perception. This understanding will be essential for developing more effective approaches to overall health.

کلیدواژه ها:

Anthropometry ، regression analysis ، weight perception ، women