| Title: | Associations between physical activity patterns and measures of physical function in South Asians and White Europeans |
| Lead Institution: | University of Leicester |
| Principal investigator: | Professor Thomas Yates |
Application 36371
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
South Asians (SAs) form the largest ethnic minority group in the UK. It has been established that SAs are at elevated risk of developing chronic diseases (e.g. diabetes/cardiovascular disease). The aim of the proposed study is to investigate levels and prevalence of physical behaviours and function within SAs, whether these differ compared to white Europeans and whether observed differences are independent of sociodemographic factors. We will investigate whether physical behaviours/function and markers of metabolic health are associated with markers of cardiometabolic health in SAs and whether differences in these factors can help explain differences in health profiles between ethnicities. The proposed study is important as it will provide new quantified evidence comparing physical behaviours/patterns between SAs and WEs, the extent to which differences in these factors are independent or modified by sociodemographic factors and whether they contribute to the increased risk of chronic disease in SAs. Further understanding the role that physical behaviours/function have in contributing to the health status of SAs will help to better tailor and refine lifestyle interventions for this population and reduce the current health inequality seen across SA communities. This application will identify all those listed as SA within UK Biobank. We will then investigate levels and prevalence of physical behaviours/function in SAs and how this compares to the majority WE population. Regression analysis will examine the extent to identified differences in these factors are independent or modified by sociodemographic factors (e.g. education level, employment status, social deprivation) and whether they contribute to worse cardiometabolic health profiles within SAs. This analysis will aim to use the full cohort where possible. The cohort with accelerometer data will also be used.6 Publications
Enabling scientific discoveries that improve human health