The role of postural and plantar pressure asymmetries predicting pain in aging adults

BackgroundResearch lacks an integrated approach that incorporates body composition, postural asymmetries, plantar pressure distribution, and sex comparisons to comprehensively understand the complex relationship between these variables and pain levels.MethodsThe study employed an observational cross-sectional design. The study sample comprised 52 participants of both sexes. The average age of participants was 57.35 years for males and 64.69 years for females. Pain levels were assessed using the numeric pain rating scale. Group comparisons (t-test) and machine learning algorithms were employed for analysis.FindingsThe results indicated sex differences in height, weight, lean mass percentage, basal metabolism, shoe size, left foot area, podal axis, and distance between foot and body center of pressure (COPs). Significant differences between sexes were also observed in shoulder angles (p = 0.002). Machine learning analysis revealed that neck left deviation and left knee angle were predictive of participants' pain levels.InterpretationIn conclusion, this study highlights differences in baropodometry and anthropometrics between sexes, with neck deviation and left knee angle identified as predictors of pain levels.

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Publication Details

Journal
AIMS Biophysics
Published
2025-01-01
DOI
https://doi.org/10.3934/biophy.2025009
Primary Topic
Musculoskeletal pain and rehabilitation
Type
article
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article

The role of postural and plantar pressure asymmetries predicting pain in aging adults

Samuel Encarnação, Dulce Esteves, Pedro Miguel Forte, Svitlana Dikhtyarenko
AIMS Biophysics
Musculoskeletal pain and rehabilitation
article

The role of postural and plantar pressure asymmetries predicting pain in aging adults

Samuel Encarnação, Dulce Esteves, Pedro Miguel Forte, Svitlana Dikhtyarenko
article en

Abstract

BackgroundResearch lacks an integrated approach that incorporates body composition, postural asymmetries, plantar pressure distribution, and sex comparisons to comprehensively understand the complex relationship between these variables and pain levels.MethodsThe study employed an observational cross-sectional design. The study sample comprised 52 participants of both sexes. The average age of participants was 57.35 years for males and 64.69 years for females. Pain levels were assessed using the numeric pain rating scale. Group comparisons (t-test) and machine learning algorithms were employed for analysis.FindingsThe results indicated sex differences in height, weight, lean mass percentage, basal metabolism, shoe size, left foot area, podal axis, and distance between foot and body center of pressure (COPs). Significant differences between sexes were also observed in shoulder angles (p = 0.002). Machine learning analysis revealed that neck left deviation and left knee angle were predictive of participants' pain levels.InterpretationIn conclusion, this study highlights differences in baropodometry and anthropometrics between sexes, with neck deviation and left knee angle identified as predictors of pain levels.

AIMS BiophysicsVol. 12(2)
University of Beira Interior (PT), Universidade Politécnica de Bragança (PT), Universidad Autónoma de Madrid (ES)
Zero hunger
Openalex Percentile: Top 93%
Musculoskeletal pain and rehabilitation
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The role of postural and plantar pressure asymmetries predicting pain in aging adults — Samuel Encarnação, Dulce Esteves, et al. · AIMS Biophysics (2025) | TGRS Research Map | TGRS