The study covered in this summary was published on medRxiv.org as a preprint and has not yet been peer-reviewed.
Key Takeaway
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Geographic variation in the incidence of bipolar disorder, schizophrenia, and major depressive disorder can be determined using a longitudinal medical-records database.
Why This Matters
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Researchers can use geographic variations in the distribution of mental illnesses to pinpoint genetic or environmental factors that contribute to disease.
Study Design
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The team analyzed data from electronic health records and identified 16,295 people who received a primary diagnosis of bipolar disorder, schizophrenia, or major depressive disorder at a psychiatric hospital in Caldas, Colombia.
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Researchers examined the effect of travel time to that hospital on the incidence of these psychiatric diseases, and used spatial-scan statistics to identify clusters of patients stratified by diagnosis and disease severity.
Key Results
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A significate correlation between travel time to the hospital and incidence was observed for outpatients with mild disease (relative risk [RR], 0.80; 95% CI, 0.71 – 0.89; P < .001), but not for in-patients with severe disease. This observation was mostly driven by patients with major depressive disorder.
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Seven distinct clusters of severe mental illness were identified, all of which had significant over-representation of bipolar disorder.
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The first cluster around the hospital, which is located in a metropolitan area, had the highest likelihood for each of the three mental disorders and had the greatest over-representation of major depressive disorder (RR, 5.47; P < .001).
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The second cluster, located 1.5 hours from the hospital, had the greatest over-representation of severe bipolar disorder (RR, 5.83; P < .001), and has one of the highest annual worldwide frequencies, at 8.7 inpatients per 10,000 residents.
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Other hotspots demonstrated patterns of over-representation differentiated by diagnosis.
Limitations
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The location of residence prior to a patient’s first recorded hospital visit, which is needed to investigate the impact of environmental factors, such as displacement, was not assessed in the analysis.
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The study focused on the primary diagnosis, and does not account for variability in disease trajectories.
Disclosures
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This study was supported by NIH grants R01MH113078, R01MH123157, R00MH116115, and R56 AI152759.
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The authors have declared no competing interest.
This is a summary of a preprint research study, Geospatial analysis reveals distinct hotspots of severe mental illness, written by Janet Song, BSc, from the Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, and colleagues, published on medRxiv.org and provided to you by Medscape. This study has not yet been peer-reviewed. The full text of the study can be found on medRxiv.org.
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