Evidence map›Paper›PMID 41503600›Full record

ArticleSSM - population health2026

Nonlinear associations and threshold effects between built environment features and schizophrenia incidence: Implications for healthy city planning.

Jian Song, Peng Li, Jun Cheng, Chao Wang, Rong Song, Weizhuo Yi, Rubing Pan, Xiaoyu Jin, Xulai Zhang, Hong Su

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Article in SSM - population health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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10 authors.

Jian SongDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Peng LiDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Jun ChengSchool of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, 230032, China.
Chao WangSchool of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, 230032, China.
Rong SongDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Weizhuo YiDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Rubing PanDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Xiaoyu JinDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
Xulai ZhangAnhui Clinical Center for mental and psychological diseases, Hefei Fourth People's Hospital, Hefei, Anhui, 230022, China.
Hong SuDepartment of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The built environment is a key intervenable target for public health, yet its nonlinear and threshold relationships with schizophrenia incidence remain poorly understood. Methods: We analyzed township-level schizophrenia incidence (2019-2023) in Anhui, China, using data from the National Severe Mental Disorder Registration System. Built environment features were derived from multi-source geographic data. We characterized spatiotemporal patterns and modeled associations using Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR), and an interpretable XGBoost model explained by SHAP values. Results: The mean annual incidence was 13.46 per 100,000, with significant spatial clustering (Moran's I = 0.47, P < 0.001). The SHAP-XGBoost model outperformed both OLS and GWR. Key built environment predictors included population density, NDVI, distance to blue space, street connectivity, and blue space area. These factors exhibited complex nonlinear relationships with schizophrenia risk; for example, population density showed a U-shaped association with a risk threshold around 15,000 persons/km Conclusion: This study provides robust evidence that the built environment is significantly and nonlinearly linked to schizophrenia incidence. The identified thresholds and interactions offer concrete, actionable guidance for urban planning aimed at mental health promotion.

Identifiers

PMID41503600
PMCPMC12768946

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.