Evidence map›Paper›PMID 40634401›Full record

ArticleScientific reports2025

Bioelectrical impedance analysis of bone mineral content based on dual-energy X-ray absorptiometry: evaluation of age-stratified optimized models.

YoungJin Moon, Zheng Dong, Sang Ki Lee, Hwi-Yeol Yun, JuWon Song, Min Ju Shin, DuBin Im, JiaHao Xu, XuanRu Wang

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

YoungJin MoonDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
Zheng DongDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea. dongzheng622@naver.com.
Sang Ki LeeDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
Hwi-Yeol YunCollege of Pharmacy, Chungnam National University, Daejeon, Republic of Korea.
JuWon SongDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
Min Ju ShinDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
DuBin ImDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
JiaHao XuDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.
XuanRu WangDepartment of Sport Science, Chungnam National University, Daejeon, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone mineral content (BMC) is a crucial indicator of skeletal health, influencing growth and development in younger individuals and fracture risk in older adults. This study aimed to evaluate the consistency of bioelectrical impedance analysis (BIA) compared with dual-energy X-ray absorptiometry (DXA) for assessing BMC in healthy populations. Additionally, it explored the potential to improve prediction accuracy by optimizing regression equations tailored to specific age groups, providing valuable insights for skeletal health monitoring and personalized healthcare. A total of 302 healthy Korean participants (148 men and 154 women; mean ages 24.87 ± 12.43 and 34.98 ± 22.24 years, respectively) underwent body composition measurements via BIA and DXA. Basic variables such as age, height, and weight, along with a range of BIA parameters, were utilized to refine predictive models for BMC. Age-specific regression models significantly enhanced prediction accuracy, with the adjusted R

Indexed as

Absorptiometry, PhotonBone DensityElectric ImpedanceAdultAgedAge FactorsBody CompositionFemaleHumansMaleMiddle AgedYoung AdultAge-related bone healthBioelectrical impedance analysisBone health managementBone mineral contentDual-energy X-ray absorptiometryEarly screening for osteoporosis

Identifiers

PMID40634401
PMCPMC12241644

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.