Volume 13, Issue 1 (1-2024)
JCHR 2024, 13(1): 267-275 |
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Ghannadiasl F. An In-Depth Regression Analysis on Anthropometric Indices Influencing Subjective Weight Perception. JCHR 2024; 13 (1) :267-275
URL: http://jhr.ssu.ac.ir/article-1-1084-en.html
URL: http://jhr.ssu.ac.ir/article-1-1084-en.html
Department of Food Sciences and Technology, University of Mohaghegh Ardabili, Ardabil, Iran , ghannadiasl@uma.ac.ir
Abstract: (89 Views)
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 287 women, aged 18-45, with a body mass index (BMI), ranging from 18.5 to 40.0 kg/m2 who were referred to a nutrition clinic in Ardabil city between May and September 2023. 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 2.548 + (-0.303 × weight in kg) + (0.089 × BMI in kg/m2) + (27.773 × WHR) + (1.032 × WC in cm) + (-109.256 × WHR) + (0.540 × BAI in %) + (-0.260 × AVI in m2) +
(-39.423 × CI in m3/2kg− 1/2). The model accounted for 78.50% of the variance and significantly predicted subjective weight perception (F (8, 279) = 104.604, and p < 0.001). Weight, WHR, WC, WHtR, BAI, and CI significantly contributed to the model (p < 0.05).
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.
Methods: This descriptive cross-sectional study involved a random sample of 287 women, aged 18-45, with a body mass index (BMI), ranging from 18.5 to 40.0 kg/m2 who were referred to a nutrition clinic in Ardabil city between May and September 2023. 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 2.548 + (-0.303 × weight in kg) + (0.089 × BMI in kg/m2) + (27.773 × WHR) + (1.032 × WC in cm) + (-109.256 × WHR) + (0.540 × BAI in %) + (-0.260 × AVI in m2) +
(-39.423 × CI in m3/2kg− 1/2). The model accounted for 78.50% of the variance and significantly predicted subjective weight perception (F (8, 279) = 104.604, and p < 0.001). Weight, WHR, WC, WHtR, BAI, and CI significantly contributed to the model (p < 0.05).
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.
Review: Research |
Subject:
Public Health
Received: 2024/08/17 | Accepted: 2024/12/22 | Published: 2024/12/30
Received: 2024/08/17 | Accepted: 2024/12/22 | Published: 2024/12/30
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