Approved research

Ultraviolet radiation, vitamin D and osteoporosis

Lay summary

Osteoporosis is a progressive bone disease that is characterised by a decrease in bone mass and density which can lead to an increased risk of fracture. Osteoporosis is common in the UK with three million sufferers, and 300,000 receiving treatment for fragility fractures with the NHS. Although several observational studies show an association between vitamin D measured through 25(OH)D and osteoporosis risk, supplementation has very little benefit on bone mineral density. We aimed to investigate the effect of a 25(OH)D latent variable on bone mineral density, osteoporosis, falls and fractures. The Biobank cohort was designed to advance the prevention, diagnosis and treatment of common diseases. The proposed research will generate findings that can be used to develop hypotheses for the prevention of osteoporosis in middle and old age. Given the high prevalence of osteoporosis and the scarcity of information on optimal diet and lifestyle, the research question warrants investigation and can be best answered in this large population-based cohort. Osteoporosis is a complex disease with multiple factors responsible for differing risk of diagnosis. Structural equation modelling (SEM) is a technique used to evaluate these complex relationships. Direct, indirect and total effects can be estimated simultaneously using SEM. A direct effect could be the influence of outdoor activity (OA) on osteoporosis. An indirect effect may be the influence of OA through total ultraviolet radiation exposure (composed of OA, ambient UVR, sunscreen use etc.). A total effect is the combination of direct and indirect effects. SEM will be used to define the most important factors responsible for the development of osteoporosis. We seek to use the full cohort as this will ensure that there will be most variation in ambient environmental exposures such as ambient ultraviolet radiation. In addition we will use structural equation models consisting of traditional regressions (linear and logistic) with participants with osteoporosis as the cases and those without as the controls, so the sample is defined by the number of participants who have the outcome measures of interest (i.e. bone mineral density, osteoporosis and fractures, musculoskeletal trauma)