Psychiatric disorders are a major health concern with numerous social and financial burdens (WHO, 2012). Disorders such as anxiety and depression are common all over the world and estimated lifetime prevalence rates range between 21%-29% (Kessler et al., 2005). Likewise, psychiatric disorders such as depression are associated with poorer physical health such as cardiovascular, metabolic and lung diseases, as well as being comorbid with other diseases such as anxiety (Bishop et al., 2004; Hessler, 2006). Understandably, there has been a great emphasis to try to understand the aetiology of these disorders in a bid to develop interventions and enhance existing treatments. Additionally, many psychiatric diseases that occur later in life (e.g., adolescence/early adulthood) originate from early life, and research has focussed on identifying potential risk factors with an end for developing treatments and interventions at an early stage (Bould et al., 2014). To date, much of the research on psychiatric disorders have used measures on depression, anxiety, temperament and wellbeing. Given the wealth of this type of data within ALSPAC, it seems rationale to concentrate on these phenotypes and build upon existing research.

There are many exposures that have been found to be associated with both immediate depression and depression at a later stage of life. Such exposures range from stress, relationships to job loss and financial difficulties (to name but a few). However, one important exposure for depression is the impact of neighbourhoods (Diez Roux and Mair, 2010; Mair et al., 2008; Matheson et al., 2006). To date, a wealth of longitudinal and cross-sectional data has investigated the impact of neighbourhoods on depression and mostly found that neighbourhoods are associated with increased depression (Graif et al., 2016; Kim, 2008). However, there is evidence that suggests that the neighbourhood may also protect against depression as well in certain contexts (Blair et al., 2014). Much of the research to date on neighbourhoods and depression has centred on certain aspects of the neighbourhood such as proximity to crime (Cutrona et al., 2005) or the urban environment (Gariepy et al., 2015). These are important stratifications to be made as it is still unclear how much these varying aspects like crime or urban build within an environment contribute to psychiatric disorders like depression. Nevertheless, it appears that the impact of the neighbourhood is important in the aetiology of depression and warrants further research. What remains unclear are the mechanisms that may underpin this association and what causal pathways lie on this association between neighbourhoods and depression.

Identifying causal pathways to disease are vital for developing effective treatments and interventions. Many cross-sectional studies suffer from confounding which make it hard to establish true effects along these pathways. However, through the use of longitudinal data, we can account for some of this confounding which can aid in understanding and identification of these causal pathways. A recent systematic review of the literature identified only 14 longitudinal studies investigating the association between neighbourhoods and depression (Blair et al., 2014). Many of these studies used small sample sizes are were mainly homogeneous to the USA. In order to fully understand the association between neighbourhoods and depression, more studies need to use longitudinal data that can incorporate confounding variables that can in turn detect true and meaningful effects.

Finally, whilst research into the effects of neighbourhoods on depression have uncovered important findings, there are still a lot of unexplained variance in the data that has yet to be explained. One potential explanation for this is the role of genetics. It is well established that both genetics and the environment contribute to psychiatric disorders such as depression (Munafò, 2015). Recent research has identified a role for the genetics of schizophrenia predicting neighbourhood deprivation (Gage et al., 2016). Promisingly, findings conducted from a recent GWAS have identified genetics associated with depression and neuroticism (Obkay et al., 2016). In order to fully understand the effects of neighbourhoods on depression, it is important to establish if and how genetics can influence this relationship. This project will utilise data from the ALSPAC study to investigate the impact of the neighbourhood on depression whilst taking into account both genetic and environmental data.