| Title: | An exploration of how the neighbourhood environment, personal characteristics and genetic variations contribute to geographical variation in the prevalence of diabetes and obesity |
| Lead Institution: | University of Bristol |
| Principal investigator: | Miss Yunqi Zhou |
Application 58421
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
The causes of chronic diseases such as diabetes and obesity have been widely studied and related to various factors including individual behaviours and genetics, as well as to the neighbourhood environments in which people live. Less studied is the possibility that these causes and their effects are themselves modified according to a wider geographical context, creating geographical variations in health outcomes and their causes. This study will adopt methods of spatial analysis and of geographical modelling to explore geographical variations in the prevalence of diabetes and obesity, and whether their causes vary from places to places. It aims to understand if and how geographical context plays an important role in generating health disparities and to examine the potentially geographically varying relationships between various types of risk factors (including the neighourhood environment, personal factors and genetic variations). It will consider how lifestyles, personal characteristics and neighbourhood environment attenuate or increase any genetic predisposition to chronic diseases and whether that attenuation or increase is more characteristic of some places more than others. Particular attention will be paid to how the neighbourhood environment, such as household deprivation interacts with genetic variations and how these interactions vary over space. The fours aims of the study are: Aim 1: To quantify and to visualize the geographical variation of two chronic diseases - diabetes and obesity Aim 2: To explore the extent to which the geographical variation in the prevalence of these diseases can be explained by the neighbourhood (built environment) and lifestyle factors Aim 3: To look at how and if genetic factors interact with environmental and personal lifestyle factors to explain the geographical variation Aim 4: To investigate how the modelled relationships may themselves vary geographically; for example, does an unhealthy lifestyle matter more in one city compared with another? This project duration is 36 months for the PhD thesis under the supervision of Professor Richard Harris and Dr Emmanouil Tranos. By better understanding the geographically varying correlates of diabetes and of obesity, the study can help inform better prevention strategies, especially for vulnerable groups and high-risk regions, avoiding "one-size-fit-all" interventions.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 7798 | Where Is the Geography? A Study of the Predictors of Obesity Using UK Biobank Data and Machine Learning | Yunqi Zhou (+2) | 2023 | Journal of Geovisualization and Spatial Analysis |
Enabling scientific discoveries that improve human health