Examining the Spatial Varying Effects of Sociodemographic Factors on Adult Cochlear Implantation Using Geographically Weighted Poisson Regression

被引:1
|
作者
Lee, Melissa S. [1 ]
Lin, Vincent Y. [2 ,3 ,6 ]
Mei, Zhen [4 ]
Mei, Jannis [4 ]
Chan, Emmanuel [5 ]
Shipp, David [3 ]
Chen, Joseph M. [2 ,3 ]
Le, Trung N. [2 ,3 ]
机构
[1] Univ British Columbia, Fac Med, Vancouver, BC, Canada
[2] Sunnybrook Hlth Sci Ctr, Dept Otolaryngol Head & Neck Surg, Toronto, ON, Canada
[3] Sunnybrook Hlth Sci Ctr, Sunnybrook Cochlear Implant Program, Toronto, ON, Canada
[4] Manifold Data Min Inc, N York, ON, Canada
[5] Sunnybrook Res Inst, Evaluat Clin Sci Platform, Toronto, ON, Canada
[6] 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
关键词
Cochlear implant; GWPR; Public policy; Sociodemographic factors; Spatial modeling; QUALITY-OF-LIFE; OLDER-ADULTS; HEARING-LOSS; HEALTH-CARE; ACCESS; BARRIERS; IMPACT;
D O I
10.1097/MAO.0000000000003861
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
ObjectiveTo (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 DesignRetrospective study of provincial CI Program database.SettingAcademic hospital.PatientsAdults 18 years or older who received a CI from 2020 to 2021.Intervention(s)Cochlear implant.Main Outcome Measure(s)CI incidence based on income level, education attainment, age at implantation, and distance from center, and spatial autocorrelation across census metropolitan areas.ResultsAdult 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.ConclusionsAdult 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.
引用
收藏
页码:E287 / E294
页数:8
相关论文
共 50 条
  • [1] Exploring Spatial Non-Stationarity and Varying Relationships between Crash Data and Related Factors Using Geographically Weighted Poisson Regression
    Shariat-Mohaymany, Afshin
    Shahri, Matin
    Mirbagheri, Babak
    Matkan, Ali Akbar
    TRANSACTIONS IN GIS, 2015, 19 (02) : 321 - 337
  • [2] Examining the spatially varying effects of factors on PM2.5 concentrations in Chinese cities using geographically weighted regression modeling
    Wang, Jieyu
    Wang, Shaojian
    Li, Shijie
    ENVIRONMENTAL POLLUTION, 2019, 248 : 792 - 803
  • [3] Modeling the Spatial Effects of Land-Use Patterns on Traffic Safety Using Geographically Weighted Poisson Regression
    Chengcheng Xu
    Yuxuan Wang
    Wei Ding
    Pan Liu
    Networks and Spatial Economics, 2020, 20 : 1015 - 1028
  • [4] Modeling the Spatial Effects of Land-Use Patterns on Traffic Safety Using Geographically Weighted Poisson Regression
    Xu, Chengcheng
    Wang, Yuxuan
    Ding, Wei
    Liu, Pan
    NETWORKS & SPATIAL ECONOMICS, 2020, 20 (04): : 1015 - 1028
  • [5] Examining the effects of station-level factors on metro ridership using multiscale geographically weighted regression
    Li, Mengya
    Kwan, Mei-Po
    Hu, Wenyan
    Li, Rui
    Wang, Jun
    JOURNAL OF TRANSPORT GEOGRAPHY, 2023, 113
  • [6] Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression
    Helmy, Helina
    Kamaluddin, Muhammad Totong
    Iskandar, Iskhaq
    Suheryanto
    TROPICAL MEDICINE AND INFECTIOUS DISEASE, 2022, 7 (09)
  • [7] Examining Spatial Variation in the Effects of Japanese Red Pine (Pinus densiflora) on Burn Severity Using Geographically Weighted Regression
    Lee, Hyun-Joo
    Kim, Eujin-Julia
    Lee, Sang-Woo
    SUSTAINABILITY, 2017, 9 (05)
  • [8] Spatial heterogeneity analysis of macro-level crashes using geographically weighted Poisson quantile regression
    Tang, Jinjun
    Gao, Fan
    Liu, Fang
    Han, Chunyang
    Lee, Jaeyoung
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 148 (148):
  • [9] Spatial heterogeneity of urban illegal parking behavior: A geographically weighted Poisson regression approach
    Zhou, Xizhen
    Ding, Xueqi
    Yan, Jie
    Ji, Yanjie
    JOURNAL OF TRANSPORT GEOGRAPHY, 2023, 110
  • [10] Modelling urban spatial structure using Geographically Weighted Regression
    Noresah, M. S.
    Ruslan, R.
    18TH WORLD IMACS CONGRESS AND MODSIM09 INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: INTERFACING MODELLING AND SIMULATION WITH MATHEMATICAL AND COMPUTATIONAL SCIENCES, 2009, : 1950 - 1956