A spatial analysis of the determinants of pneumonia and influenza hospitalizations in Ontario (1992-2001)
A spatial analysis of the determinants of pneumonia and influenza hospitalizations in Ontario (1992-2001)
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DOI：
10.1016/j.socscimed.2006.12.001
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发表时间：
2007-04-01
影响因子：
5.4
通讯作者：
Upshur, Ross
中科院分区：
文献类型：
--
作者：
Crighton, Eric J.;Elliott, Susan J.;Upshur, Ross
以前关于肺炎和流感决定因素的研究主要集中在个人生物和行为风险因素的作用，导致部分解释和主要治疗方法，以减少疾病负担。本研究探讨了肺炎和流感住院的地理模式，以及广泛的生态水平因素在决定这些因素中的作用。我们对加拿大安大略省1992年至2001年（N = 241，803）的肺炎和流感住院病例进行了一项县级回顾性生态研究，控制了数据的空间依赖性。非空间和空间回归模型估计使用一系列的环境，社会，经济，行为和医疗保健预测。结果显示，在所有年龄组和性别中，教育程度低与住院率呈正相关。在大多数模型中，土著人口变量也呈正相关，但65岁以上年龄组除外。行为因素（每日吸烟和大量饮酒），环境因素（被动吸烟，住房条件差，温度）和医疗保健因素（流感疫苗接种）在不同的年龄和性别特异性模型中均显着相关。空间误差回归模型的使用允许无偏估计的回归参数及其显着性水平。这些研究结果表明，广泛的年龄和性别特定的人口水平的因素在确定肺炎和流感住院治疗的重要性，并说明需要考虑到这些因素的地方和人口的具体政策。(c)2006爱思唯尔有限公司保留所有权利。
Previous research on the determinants of pneumonia and influenza has focused primarily on the role of individual level biological and behavioural risk factors resulting in partial explanations and largely curative approaches to reducing the disease burden. This study examines the geographic patterns of pneumonia and influenza hospitalizations and the role that broad ecologic-level factors may have in determining them. We conducted a county level, retrospective, ecologic study of pneumonia and influenza hospitalizations in the province of Ontario, Canada, between 1992 and 2001 (N = 241,803), controlling for spatial dependence in the data. Non-spatial and spatial regression models were estimated using a range of environmental, social, economic, behavioural, and health care predictors. Results revealed low education to be positively associated with hospitalization rates over all age groups and both genders. The Aboriginal population variable was also positively associated in most models except for the 65 + -year age group. Behavioural factors (daily smoking and heavy drinking), environmental factors (passive smoking, poor housing, temperature), and health care factors (influenza vaccination) were all significantly associated in different age and gender-specific models. The use of spatial error regression models allowed for unbiased estimation of regression parameters and their significance levels. These findings demonstrate the importance of broad age and gender-specific population-level factors in determining pneumonia and influenza hospitalizations, and illustrate the need for place and population-specific policies that take these factors into consideration. (c) 2006 Elsevier Ltd. All rights reserved.