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. Methods 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. Results 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. Conclusions 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
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. Methods 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. Results 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. Conclusions 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
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