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近视可能性及环境风险因素的地理差异:对英国一个队列的多层次交叉分类分析

Geographical Variation in Likely Myopia and Environmental Risk Factors: A Multilevel Cross Classified Analysis of A UK Cohort.

作者信息

Morris Tim T, Guggenheim Jeremy A, Northstone Kate, Williams Cathy

机构信息

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK.

出版信息

Ophthalmic Epidemiol. 2020 Feb;27(1):1-9. doi: 10.1080/09286586.2019.1659979. Epub 2019 Aug 29.

Abstract

: Previous studies have demonstrated positive associations between myopia and environmental risk factors such as urbanization. However, these have failed to account for the clustering of individuals within geographical areas, opening analyses to theoretical and statistical limitations. We demonstrate how a multilevel modelling approach can provide a more nuanced understanding of the relationship between geography and myopia. We examined longitudinal associations between onset of myopia and urban/rural status or population density.: Data were collected over 5 visits during an 8-year period for a UK cohort of 3,512 children. Associations between incident myopia (spherical equivalent ≤ -1.00 diopters) and both urban/rural status and population density were examined using discrete time multilevel hazard models which allow the partitioning of variance into different neighborhood and school areas.: There was evidence for an association between myopia and higher population density (Hazard Ratio = 1.14; 95% CI = 1.032 to 1.26) after adjustment for a range of risk factors. There was no strong evidence that urban/rural status was associated with incident myopia. Only a minor amount of variation in myopia was attributable to geographical areas (<2.2%), and this was not explained by rurality or population density.: Our findings contrast with previous studies and raise the possibility that some of the results reported may have been driven by confounding bias whereby geographical differences in myopia are driven by lifestyle factors that are correlated with geographical setting.

摘要

以往的研究表明,近视与城市化等环境风险因素之间存在正相关关系。然而,这些研究未能考虑到地理区域内个体的聚集情况,从而使分析存在理论和统计上的局限性。我们展示了一种多水平建模方法如何能更细致入微地理解地理因素与近视之间的关系。我们研究了近视发病与城乡状况或人口密度之间的纵向关联。

在8年期间对英国一个由3512名儿童组成的队列进行了5次随访,收集了相关数据。使用离散时间多水平风险模型研究了新发近视(球镜等效度数≤-1.00屈光度)与城乡状况和人口密度之间的关联,该模型可将方差分解到不同的社区和学校区域。

在对一系列风险因素进行调整后,有证据表明近视与较高的人口密度之间存在关联(风险比=1.14;95%置信区间=1.032至1.26)。没有强有力的证据表明城乡状况与新发近视有关。近视中只有少量变异可归因于地理区域(<2.2%),而且这不能用农村或人口密度来解释。

我们的研究结果与以往的研究形成对比,并提出一种可能性,即之前报道的一些结果可能是由混杂偏倚导致的,即近视的地理差异是由与地理环境相关的生活方式因素驱动的。

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