ML-Assisted Olfactory Epidemiology Survey Urbanizing China: A Population-Based Study in Yancheng
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Objectives: Urbanization-related air pollution may be associated with olfactory dysfunction (OD) in China, yet population studies are lacking. Methods: We conducted a cross-sectional study of 1500 participants in urbanizing Yancheng, China (2023–2025). Olfactory function was assessed via Sniffin' Sticks. Machine learning (XGBoost, k-means clustering) was used to analyze risk factors and phenotypes. Results: Head trauma (OR = 163.04) and chronic rhinosinusitis (CRS, OR = 161.39) were the dominant risk factors for OD (p < 0.001). Rural residence was associated with a 99% lower OD risk compared to urban residence (OR = 0.011, p < 0.0001). Four OD subtypes emerged: (1) sinusitis-linked generalized impairment; (2) age-related threshold deficit; (3) neurological disorder-associated identification loss; (4) child-specific mild dysfunction. Olfactory ability peaked at the age of 23 years, remained stable among individuals aged 40–60 years, and declined sharply in those aged over 63 years. Anosmia quadrupled from childhood to elderly (7.1% → 28.2%, p < 0.0001). Conclusion: In urbanizing China, head trauma and sinusitis are the most potent risk factors for olfactory dysfunction (OD). Additionally, long-term exposure to air pollution—proxied by urban residence—and the natural aging process are significant contributing factors. Phenotypic stratification enables targeted interventions, thereby urging reforms in environmental policies and enhanced clinical management of high-risk conditions (e.g., head trauma, sinusitis). Level of Evidence: 3.
Details
| Original language | English |
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| Pages (from-to) | 1887-1895 |
| Number of pages | 9 |
| Journal | Laryngoscope |
| Volume | 136 |
| Issue number | 4 |
| Publication status | E-pub ahead of print - 2 Feb 2026 |
| Peer-reviewed | Yes |
External IDs
| ORCID | /0000-0001-9713-0183/work/205992139 |
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Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- air pollution, epidemiology survey, machine learning (ML), OD subtypes, olfactory dysfunction