Approved Research

Musculoskeletal health refers to the health and functionality of our muscles, joints and bones, which is required for pain-free movement. As such, its maintenance is a key component of healthy ageing, allowing people to remain independent and active in later life.

Age-related declines in musculoskeletal health are a key predictor of disability, frailty and premature death. There is also an important relationship between musculoskeletal health and falls. Falls may be preceded by declines in musculoskeletal health but falls may also in turn contribute to musculoskeletal injuries that can precipitate mobility declines and threaten physical independence.

As impaired musculoskeletal health and falls are highly prevalent among older adults they represent major public health challenges within ageing populations. There is therefore an urgent need to identify novel and effective strategies to promote musculoskeletal health and prevent falls at different life stages.

This 3-year project aims to utilise the rich biomedical, lifestyle and demographic data available within UK Biobank to provide a holistic assessment of key predictors of musculoskeletal health and falls as we age. We will achieve this aim by addressing research questions including: (1). Are indicators of socioeconomic position associated with grip strength? (2). To what extent do early life factors influence the relationship between physical activity levels and muscle and bone health as we age? (3). Do indicators of musculoskeletal health and physical activity measures, including time spent walking, predict falls in both middle-aged and older adults?  (4). Do novel neuroimaging metrics, associated with cognitive and gait impairment in age-related diseases, show similar age-related associations with cognitive function and/or falls in a population-based sample?

Our work will help inform preventative approaches, which aim to maintain good musculoskeletal health throughout life and reduce fall risk through early intervention. In addition, our analyses will generate new neuroimaging and accelerometry-based metrics, of potential use to the wider research community.