Why are paranoia and schizophrenia more common in cities?

Southwyck House in South London is a block of flats so intimidating that it is often mistaken for a prison. Locally known as the Brixton ‘barrier block,’ it has a stark exterior of brick and concrete that literally looms over you, giving the impression that unseen people are staring down through the sparse rectangular windows.

It was built as a social housing project, designed to shield its residents from the noise of a phantom motorway that was intended to run from Blackheath to Battersea. The road was never built due to petty political squabbles, but the building now stands as a seven-story barricade against its illusory traffic.

If you’re not used to the built-up environment of the inner city, the block can certainly feel unsettling. But here, urban alienation may run deeper than mere architecture. The area was found to have the highest rate of diagnosed schizophrenia in a large study of South London, even when compared with directly adjacent neighborhoods.

The research that found this striking variation was led by epidemiologist James Kirkbride, now at University College London. Kirkbride’s work is but one in more than a century of studies that have found higher rates of psychosis in cities and which have sparked an intense debate over whether—to put it in its original terms —‘cities cause madness’ or whether those affected by ‘madness’ just tend to end up in cities.

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A .... take is that the same factors that increase your chance of getting diagnosed with schizophrenia also increase your chances of ending up in living in a deprived urban area. Poverty and neglect might be the obvious candidates but a recent study led by Oxford University epidemiologist Amir Sariaslan using more than two million Swedish health records suggests the effect can be better explained by shared genetic risks which could be common across the whole family.

The idea that genetics could influence something so complex as finding a house might seem counter-intuitive but Sariaslan explains that it is best understood in terms of limiting life choices rather than affecting decision making. “Living in a deprived neighborhood in adulthood partly reflects academic achievements and labor market position, which are in turn largely influenced by cognitive abilities, impulsivity and personality traits” he says, “[all of] which have all been found to be moderately to considerably heritable.”

Kirkbride welcomes the study but cautions against a solely genetic explanation for the high risk of psychosis in more urban, deprived communities. He adds that even if genetic factors are involved in shaping where people live, “it is only through improving our social environment that we can reduce the additional burden of mental health, and break the cycle of socioeconomic disadvantage often faced by families living in such neighborhoods over successive generations.”

For those of us who live in cities, the cause of the urban psychosis effect remains comfortably unconfirmed, but the scientific interest is having wider reaching consequences. Des Fitzgerald, a sociologist at Cardiff University who studies the social impact of neuroscience, has described how this scientific question is motivating researchers to work across disciplinary boundaries with an intensity rarely seen before.

Neighbourhood variation in the incidence of psychotic disorders in Southeast London

  • James B. Kirkbride , Paul Fearon, Craig Morgan, Paola Dazzan, Kevin Morgan, Robin M. Murray, Peter B. Jones

Background: Urbanicity is a risk factor for schizophrenia, but it is unclear whether this risk is homogenous across urban areas.

Aims: To determine whether the incidence of psychotic disorders varied within an urban area, beyond variation attributable to individual-level characteristics.

Methods: All incident cases of ICD-10 psychoses from a large, 2-year, epidemiological study of first-episode psychoses in Southeast London were identified. Incidence rates for 33 wards were standardised for age, sex and ethnicity. Bayesian models produced accurate relative risk estimates that were then mapped.

Results: 295 cases were identified during 565,000 person-years of follow-up. We observed significant heterogeneity in relative risks for broad and non-affective psychoses (schizophrenia), but not for affective psychoses. Highest risks were observed in contiguous wards.

Conclusions: Neighbourhood variation in the incidence of non-affective psychoses could not be explained by individual-level risk, implicating neighbourhood-level socioenvironmental factors in their aetiology. The findings are consistent with classical sociological models of mental disorders.

Keywords: schizophrenia neighbourhood spatial epidemiology bayes geographical variation