Lee MS, Lin VY, Mei Z, Mei J, Chan E, Shipp D, Chen JM, Le TN. Examining the Spatial Varying Effects of Sociodemographic Factors on Adult Cochlear Implantation Using Geographically Weighted Poisson Regression.
Otol Neurotol 2023;
44:e287-e294. [PMID:
36962009 DOI:
10.1097/mao.0000000000003861]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2023]
Abstract
OBJECTIVE
To (i) demonstrate the utility of geographically weighted Poisson regression (GWPR) in describing geographical patterns of adult cochlear implant (CI) incidence in relation to sociodemographic factors in a publicly funded healthcare system, and (ii) compare Poisson regression and GWPR to fit the aforementioned relationship.
STUDY DESIGN
Retrospective study of provincial CI Program database.
SETTING
Academic hospital.
PATIENTS
Adults 18 years or older who received a CI from 2020 to 2021.
INTERVENTIONS
Cochlear implant.
MAIN OUTCOME MEASURES
CI incidence based on income level, education attainment, age at implantation, and distance from center, and spatial autocorrelation across census metropolitan areas.
RESULTS
Adult CI incidence varied spatially across Ontario (Moran's I = 0.04, p < 0.05). Poisson regression demonstrated positive associations between implantation and lower income level (coefficient = 0.0284, p < 0.05) and younger age (coefficient = 0.1075, p < 0.01), and a negative association with distance to CI center (coefficient = -0.0060, p < 0.01). Spatial autocorrelation was significant in Poisson model (Moran's I = 0.13, p < 0.05). GWPR accounted for spatial differences (Moran's I = 0.24, p < 0.690), and similar associations to Poisson were observed. GWPR further identified clusters of implantation in South Central census metropolitan areas with higher education attainment.
CONCLUSIONS
Adult CI incidence demonstrated a nonstationary relationship between implantation and the studied sociodemographic factors. GWPR performed better than Poisson regression in accounting for these local spatial variations. These results support the development of targeted interventions to improve access and utilization to CIs in a publicly funded healthcare system.
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