Using linked data to investigate the living environment factors associated with depression in a local population
PHE ePoster Library. Jones S. 09/12/19; 274367; 172
Samuel Jones
Samuel Jones
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Rate & Comment (0)
Abstract BackgroundDepression affects about one in 10 people at some point during their life and, according to the GP Patient Survey, Tower Hamlets has the highest rate of depression in London. The Whole Systems Data Project (WSDP) aims to establish an integrated health, social care and wider determinants of health dataset across Tower Hamlets. The WSDP will help us quantitatively investigate the association of heath outcomes and wider determinants.
Using the WSDP integrated dataset, indirectly standardised rates have been calculated for GP-recorded depression. These have been calculated for the overall population, and for segmented cohorts based on household structure and housing environment.We will also aggregate counts to lower super output area, along with a full range of clustered variables. This will allow for multi-variable regression analysis which we will present in our poster.
Initial results show that residents in single-person households are more at risk of being diagnosed with depression than the overall population.Single Parent Households have the highest standardised rate of GP-recorded depression, whilst rates are also significantly higher for Single Adult Households when different household composition types are compared to the overall Borough rate.
The use of integrated dataset has allowed for us to investigate the links between mental health and a range of living environment factors at a level of detail which was previously not possible. This will help us to target resource allocation based on the needs of populations under the principles of proportionate universalism. External funding details
    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.

Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.

Save Settings