Determining the Correlation Between Lipid Profile and the Incidence of Plantar Fasciitis

Research Type: Level 3 - Retrospective cohort study, Case-control study, Meta-analysis of Level 3 studies Introduction/Purpose: Plantar (PF) significantly affects mobility and quality of life. Recent studies suggested an association between elevated lipid profile and inflammatory musculoskeletal disorders, including PF. However, this relationship remains understudied. This study investigates the correlation between lipid profile and PF incidence, and the influence of comorbidities and lipid-lowering medications on this relationship. Understanding the potential role of metabolic factors in PF pathogenesis is crucial, as it could introduce early intervention strategies and personalized treatments, ultimately improving patient outcomes and reducing the economic and social burden of PF. Methods: A retrospective case-control study analyzed data from 157 adults (≥ 18 years) with lipid profiles collected between January 1, 2010, and February 29, 2024, at three Boston-area hospitals (Massachusetts General Hospital (MGH), Newton-Wellesley Hospital (NWH), and Brigham and Women’s hospital (BWH)). Patients were divided into cases with PF (n=70) and controls without PF (n=87). Statistical analysis included the Shapiro-Wilk test for normality, Student’s T-test for between-group comparison of parametric data, Wilcoxon rank-sum test for non-parametric data, and Chi-square Fisher’s exact test for categorical variables. Multivariable logistic regression model evaluated associations between PF presence, lipid profile components (Low-Density Lipoproteins (LDL), High-Density Lipoproteins (HDL), triglycerides (TG) and total cholesterol (Chol)) and relevant demographic variables (age, gender, BMI). Results: No significant differences in lipid profile were observed between the PF group (cases) and non-PF group (controls). However, significant differences were observed for the demographic variable age and BMI. The PF group was significantly younger (51 ± 12.7 vs. 62.2 ± 15.5 years, P< 0.05) and had a significant higher BMI (30.4 ± 7.0kg/m2 vs. 28.1 ± 5.8 kg/m2, P< 0.05) than the control group. Multivariable logistic regression analysis showed that lipid profile parameters were not significantly associated with PF incidence. However, younger age (OR=0.96, 95% CI: 0.93-0.99, P=0.01) and higher BMI (OR=1.08, 95% CI: 1.01-1.16, P=0.03) were significantly associated with increased likelihood of PF. Conclusion: Our study found no significant correlation between lipid profiles and plantar fasciitis (PF) incidence, nor differences in comorbidities or lipid- lowering medication use between groups. Higher age was associated with earlier PF onset, likely due to sedentary lifestyle, while higher BMI increased PF likelihood, possibly from increased plantar fascia stress. These findings suggest BMI reduction in younger patients, who appear more susceptible to PF, may reduce incidence. Results indicate a complex relationship between metabolic factors and PF, highlighting the need for multifaceted approaches and larger population studies to confirm our findings.

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Publication Details

Journal
Foot & Ankle Orthopaedics
Published
2025-10-01
DOI
https://doi.org/10.1177/2473011425s00203
Primary Topic
Tendon Structure and Treatment
Type
article
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article

Determining the Correlation Between Lipid Profile and the Incidence of Plantar Fasciitis

Soheil Ashkani‐Esfahani, Julian J. Hollander, Varun Nukala, Dorien Winckelmans et al.
Foot & Ankle Orthopaedics
Tendon Structure and Treatment
article

Determining the Correlation Between Lipid Profile and the Incidence of Plantar Fasciitis

Soheil Ashkani‐Esfahani, Julian J. Hollander, Varun Nukala, Dorien Winckelmans, Anthony Bhangdia, Gino Kerkhoffs, Mohamad Al Masri
article en

Abstract

Research Type: Level 3 - Retrospective cohort study, Case-control study, Meta-analysis of Level 3 studies Introduction/Purpose: Plantar (PF) significantly affects mobility and quality of life. Recent studies suggested an association between elevated lipid profile and inflammatory musculoskeletal disorders, including PF. However, this relationship remains understudied. This study investigates the correlation between lipid profile and PF incidence, and the influence of comorbidities and lipid-lowering medications on this relationship. Understanding the potential role of metabolic factors in PF pathogenesis is crucial, as it could introduce early intervention strategies and personalized treatments, ultimately improving patient outcomes and reducing the economic and social burden of PF. Methods: A retrospective case-control study analyzed data from 157 adults (≥ 18 years) with lipid profiles collected between January 1, 2010, and February 29, 2024, at three Boston-area hospitals (Massachusetts General Hospital (MGH), Newton-Wellesley Hospital (NWH), and Brigham and Women’s hospital (BWH)). Patients were divided into cases with PF (n=70) and controls without PF (n=87). Statistical analysis included the Shapiro-Wilk test for normality, Student’s T-test for between-group comparison of parametric data, Wilcoxon rank-sum test for non-parametric data, and Chi-square Fisher’s exact test for categorical variables. Multivariable logistic regression model evaluated associations between PF presence, lipid profile components (Low-Density Lipoproteins (LDL), High-Density Lipoproteins (HDL), triglycerides (TG) and total cholesterol (Chol)) and relevant demographic variables (age, gender, BMI). Results: No significant differences in lipid profile were observed between the PF group (cases) and non-PF group (controls). However, significant differences were observed for the demographic variable age and BMI. The PF group was significantly younger (51 ± 12.7 vs. 62.2 ± 15.5 years, P< 0.05) and had a significant higher BMI (30.4 ± 7.0kg/m2 vs. 28.1 ± 5.8 kg/m2, P< 0.05) than the control group. Multivariable logistic regression analysis showed that lipid profile parameters were not significantly associated with PF incidence. However, younger age (OR=0.96, 95% CI: 0.93-0.99, P=0.01) and higher BMI (OR=1.08, 95% CI: 1.01-1.16, P=0.03) were significantly associated with increased likelihood of PF. Conclusion: Our study found no significant correlation between lipid profiles and plantar fasciitis (PF) incidence, nor differences in comorbidities or lipid- lowering medication use between groups. Higher age was associated with earlier PF onset, likely due to sedentary lifestyle, while higher BMI increased PF likelihood, possibly from increased plantar fascia stress. These findings suggest BMI reduction in younger patients, who appear more susceptible to PF, may reduce incidence. Results indicate a complex relationship between metabolic factors and PF, highlighting the need for multifaceted approaches and larger population studies to confirm our findings.

Foot & Ankle OrthopaedicsVol. 10(4)
Gender equality
Openalex Percentile: Top 33%
Tendon Structure and Treatment
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