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Updated: Jun 26, 2026

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
07:56

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

Sex-Specific Biological Predictors for Identifying Individuals With Low Bone Mineral Density Using the Taiwan Biobank

Yu-Hsu Chen1,2,3, Yu-Pao Hsu1, Ming-Te Cheng1,4,5

  • 1Department of Orthopedic Surgery, Ministry of Health and Welfare, Taoyuan General Hospital, Taoyuan, Taiwan, tygh.gov.tw.

Journal of Osteoporosis
|June 25, 2026
PubMed
Summary

Related Concept Videos

Bone Disorders01:29

Bone Disorders

Aging and its effect on bone remodeling is the most common cause of bone disorders. In young and healthy people, bone deposition and resorption happen at an equal rate to maintain optimal bone health.
Bone deposition is also affected by the levels of sex hormones like estrogen and testosterone that promote osteoblast activity and bone matrix synthesis. When the level of these hormones decreases due to aging, it causes a reduction in bone deposition. As a result, bone resorption by osteoclasts...

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Low bone mineral density (BMD) predictors vary by sex in Taiwan. Machine learning identified age, menopausal status, and BMI for women, and age, BMI, and waist circumference for men, guiding personalized osteoporosis prevention.

Area of Science:

  • Gerontology and Bone Metabolism
  • Biostatistics and Machine Learning Applications
  • Public Health and Epidemiology

Background:

  • Taiwan faces rising osteoporosis rates due to an aging population.
  • Understanding sex-specific factors influencing low bone mineral density (BMD) is crucial but under-researched.
  • Existing knowledge gaps necessitate exploring unique biological predictors for men and women.

Purpose of the Study:

  • To identify sex-specific predictors of low bone mineral density (BMD) using machine learning.
  • To analyze population data from the Taiwan Biobank for demographic, laboratory, and physical examination variables.
  • To differentiate predictive patterns for low BMD between men and women.

Main Methods:

  • Retrospective cross-sectional study of 19,868 adults (≥40 years) from the Taiwan Biobank (2020-2022).

Related Experiment Videos

Last Updated: Jun 26, 2026

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
07:56

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

  • Utilized the Extreme Gradient Boosting (XGBoost) model to identify low BMD predictors.
  • Applied SHapley Additive exPlanations (SHAP) for visualizing and interpreting predictor contributions.

    • Main Results:

    • 44% of participants had low BMD; women comprised 63%.
    • Top predictors for women: age, postmenopausal status, BMI (AUC=0.75).
    • Top predictors for men: age, BMI, waist circumference (AUC=0.63).
    • Hematological, metabolic, uric acid, liver, and renal function markers also showed associations, with sex-specific importance.

    Conclusions:

    • Significant sex-specific patterns exist in predictors of low bone mineral density (BMD).
    • Key determinants include age, menopausal status, BMI, and waist circumference, varying by sex.
    • Findings are essential for developing targeted prevention and early intervention strategies for osteoporosis.