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A prospective study of associations between accelerated biological aging and twenty musculoskeletal disorders
Wenming Wei1, Xin Qi1,2, Bolun Cheng1
1Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
Background:
Musculoskeletal disorders pose major public health challenges, and accelerated biological aging may increase their risk. This study investigates the association between biological aging and musculoskeletal disorders, with a focus on sex-related differences.
Methods:
We analyzed data from 172,332 UK Biobank participants (mean age of 56.03 ± 8.10 years). Biological age was calculated using the KDM-BA and PhenoAge algorithms based on blood biomarkers. Musculoskeletal disorders were diagnosed using the ICD-10 criteria, with sample sizes ranging from 1,182 to 23,668. Logistic regression assessed cross-sectional associations between age acceleration (AA) metrics and musculoskeletal disorders. Accelerated Failure Time (AFT) model was used for survival analysis to evaluate the relationships between AAs and musculoskeletal disorders onset. Models were adjusted for demographic, lifestyle, and socio-economic covariates. The threshold of P-values were set by the Holm-Bonferroni correction.
Results:
Cross-sectional analyses reveal significant associations between AAs and fourteen musculoskeletal disorders. Survival analyses indicate that AAs significantly accelerate the onset of nine musculoskeletal disorders, including inflammatory polyarthropathies (RTKDM-BA = 0.993; RTPhenoAge = 0.983), systemic connective tissue disorders (RTKDM-BA = 0.987; RTPhenoAge = 0.980), spondylopathies (RTPhenoAge= 0.994), disorders of bone density and structure (RTPhenoAge= 0.991), gout (RTPhenoAge= 0.968), arthritis (RTPhenoAge= 0.991), pain in joint (RTPhenoAge= 0.989), low back pain (RTPhenoAge= 0.986), and osteoporosis (RTPhenoAge= 0.994). Sensitivity analyses are consistent with the primary findings. Sex-specific variations are observed, with AAs accelerating spondylopathies, arthritis, and low back pain in females, while osteoporosis is accelerated in males.
Conclusion:
Accelerated biological aging is significantly associated with the incidence of several musculoskeletal disorders. These insights highlight the importance of biological age assessments in gauging musculoskeletal disorder risk, aiding early detection, prevention, and management.
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