In the 1950s, researchers showed an association between low socio-economic status (SES) and psychosis. Two competing theories social causation and social drift were proposed to explain the findings. In the intervening years, contrasting evidence emerged as some studies showed no association between SES and schizophrenia. At present, the nature of the relationship is still unclear; currently, there are no reviews in the literature examining the association between social class at birth and psychosis.

To search the literature to clarify the relationship between social class at birth, measured by paternal occupation at birth, and the risk of adult-onset psychosis.

A systematic search of the literature using a combination of keywords in Group 1 together with the keywords in Group 2 was performed in October 2012 in the following online databases: (a) MEDLINE (1946–2012), (b) PubMed, (c) Embase (1980–2012), (d) PsycINFO (1806–2012) and (e) Web of Science (1899–2012). Reference lists were also hand searched. The search provided 3,240 studies; following screening of the titles and abstracts by inclusion and exclusion criteria and quality assessment of the full text, 14 studies were identified to be appropriate for the review. The keywords used for the search were as follows: Group 1 – social class, social status, socioeconomic, socio-economic, SES; Group 2 – psychosis, psychoses, schizophrenia.

Seven studies showed an association between low SES and psychosis. Four studies showed no association, and three studies showed an association with high SES.

There is not enough evidence to support the association between social class and psychosis. While some findings showed an association between low social class and psychosis, there were a number of conflicting studies showing no association or a link with higher social class. Interestingly, the results followed a temporal pattern, as all the studies conducted after 2001 supported an association between low SES at birth and psychosis. Four of the six studies employed a prospective design with large sample populations, indicating the need for further investigation.