Every year millions of people throughout the world suffer from osteoporotic fracture and these fractures are associated with decreased quality of life, increased mortality and high health care costs. Chronic inflammation (CI) can be induced by aging, low sex hormones, obesity, diet and smoking and is typically featured with low level of inflammation throughout the body. Evidence showed that T cells persistently produced by CI can directly activate osteoclastogenesis and together with pro-inflammatory cytokines accelerate bone resorption and thus CI is considered to increase risk of osteoporosis and fragility fractures in the elderly. Thus, it is important to explore preventive strategies that may impact inflammatory level and can be modified by intervention. One such modifiable lifestyle factor is diet which has been shown to regulate inflammation through both pro-inflammatory and anti-inflammatory mechanisms. The general aim of this project is to identify biomarkers of dietary patterns (DPs) and osteoporosis in a cross-sectional design by using the metabolomics data of SMCC. Multivariate modelling will be used to identify biomarkers associated with bone mineral density, bone mineral area and lean mass. The association of each biomarker with outcomes will be assessed by linear regression. Dietary patterns will be established by AIDI index, factor analysis and reduced rank regression. Dietary biomarkers will be selected by multivariate modelling of DPs. These metabolites of DPs will be applied for PCA and the observation scores will be used to correlate with dietary patterns (and food groups) as well as to generate beta coefficients in linear regression. A superimposed triplot will be used to visualize the association of diet and osteoporosis. This study could be of help to find new biomarkers of osteoporosis and understand how dietary intake influences bone phenotypes and provide interventional strategies for individuals at high risk of developing osteoporosis.