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03.05.2024 | Research
Comprehensive spatial distribution of patients with first-episode psychosis (FEP) and its relation to socio-economic factors
Erschienen in: Social Psychiatry and Psychiatric Epidemiology
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Background
The functional-cognitive impact of first-episode psychosis (FEP) is extremely relevant and implies dysfunction from early life stages like adolescence and youth. Like other illnesses, FEP incidence is also influenced by environmental factors. It is necessary to attend to this age group with early interventions and to act on the environmental factors that the literature correlates with increased FEP incidence: socio-economic aspects, social adversity, bullying at school or cannabis use. In this context, identifying the areas of cities where FEP patients concentrate is important to perform early interventions. The spatial analysis of patient distribution in a whole city is one way to identify the most vulnerable areas and to propose psycho-social interventions for the possible prevention and/or early detection of FEP by improving urban mental health.
Methods
An epidemiological study of point patterns to determine the areas of a city with a higher incidence of patients with FEP. To do so, the addresses of FEP cases were georeferenced from 1 January 2016 to 31 October 2022, and 109 FEP patients were analysed. Data from a random sample of 383 controls, comprising their addresses, age, and sex, were randomly obtained from the official city council database. By GIS, the areas with higher FEP incidence were analysed to see if they coincided with the zones where inhabitants with lower incomes lived.
Results
The risk ratio of the FEP patients was compatible with the constant risk ratio in Albacete (p = 0.22). When performing the process separately with cases and controls only in men and women, the results were not significant for both distributions (p value: 0.12 and 0.57, respectively). Nonetheless, areas within the city had a significantly higher risk. These groups of cases coincided with those who had lower income and more inequality for women, but this pattern was not clear for men.
Conclusions
Classifying city areas per income can help to determine the zones at higher risk of FEP, which would allow early healthcare and preventive measures for these zones.