Insulin and bone health in young adults: The mediator role of lean mass
Abstract
BACKGROUND: The positive relationship between lean mass (LM) and bone health is well known, but a positive association between insulin and LM has also been described. Insulin has some anabolic properties on bone through the stimulation of osteoblast differentiation, yet the role of LM as a confounder or mediator in this relationship remains uncertain.
OBJECTIVE: To examine whether the association between insulin levels and bone health is mediated by LM.
METHODS: A cross-sectional study was conducted at the Castilla La Mancha University (Spain) involving 466 young adults (113 young men; 19.5±2.3 years). LM and total-body bone mineral content (BMC) were measured by dual energy x-ray absorptiometry, and insulin was measured in fasting serum samples.
RESULTS: Young adults with high total LM had higher values of total-body BMC than their peers after controlling for age and sex, this relationship persisted after adjusting for insulin levels (p0.05) as indicated by Sobel test values for indirect effect (z = 4.43; p<0.001).
CONCLUSIONS: LM plays an important role in the relationship between insulin levels and bone health, in such a way that while increases in LM have a positive influence on bone health, they are also negatively associated with insulin levels.
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 466 participants or records.
Read the paper
Related studies
- Benign periarticular, bone and joint lipomatous lesions
- A review of the physiological and histological effects of laser osteotomy
- Quality of bone healing: perspectives and assessment techniques
- Effects of bioactive lipids and lipoproteins on bone
- Bone structure and function
- Quantifying bone structure, micro-architecture, and pathophysiology with MRI.
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.