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马里的倒睫与地理气候因素

Trichiasis and geoclimatic factors in Mali.

作者信息

Schémann Jean-François, Laffly Dominique, Sacko Doulaye, Zephak Germain, Malvy Denis

机构信息

Institut de Recherche pour le Développement, UR 24, BP 1386, Dakar, Sénégal.

出版信息

Trans R Soc Trop Med Hyg. 2007 Oct;101(10):996-1003. doi: 10.1016/j.trstmh.2007.05.015. Epub 2007 Jul 20.

Abstract

Several trachoma surveys conducted in sub-Saharan countries showed different geographical distributions of active trachoma and trichiasis. Trichiasis is more common in southern regions. We analysed the role of geoclimatic factors in determining the distributions of active trachoma and trichiasis in Mali. In each region a random sample of 30 clusters was examined. The prevalence of active trachoma among children and of trichiasis among women was compared, and geographical, environmental and social risk factors were assessed. Logistic regression models were constructed. Multiple regression analysis was applied and models were used to map the probability of active trachoma and trichiasis. The highest prevalence rates of active trachoma (TF/TI) were found in the northern part of Mali reaching 41.1% among children living north of the 15th parallel. Surprisingly, prevalence rates of trichiasis (TT) among women regularly increased from north to south (1.0% north of the 15th parallel vs. 2.8% south; OR=2.91, 95% CI 2.01-4.24). The two related predictive maps showed a gradient SSE/NNW for TF/TI very different from the gradient NS/SW for TT. These opposite spatial distributions could be explained by differences in the pathogenic agent, the natural history of the disease, population susceptibility, grading process or vulnerable group behaviour.

摘要

在撒哈拉以南国家进行的几次沙眼调查显示,活动性沙眼和倒睫的地理分布各不相同。倒睫在南部地区更为常见。我们分析了地理气候因素在决定马里活动性沙眼和倒睫分布方面的作用。在每个地区,对30个群组进行了随机抽样检查。比较了儿童中活动性沙眼的患病率和妇女中倒睫的患病率,并评估了地理、环境和社会风险因素。构建了逻辑回归模型。应用多元回归分析,并使用模型绘制活动性沙眼和倒睫的概率图。在马里北部发现活动性沙眼(TF/TI)的患病率最高,在北纬15度以北地区的儿童中达到41.1%。令人惊讶的是,妇女中倒睫(TT)的患病率从北到南有规律地增加(北纬15度以北为1.0%,以南为2.8%;比值比=2.91,95%置信区间2.01-4.24)。两张相关的预测图显示,TF/TI的SSE/NNW梯度与TT的NS/SW梯度非常不同。这些相反的空间分布可以通过病原体、疾病自然史、人群易感性、分级过程或弱势群体行为的差异来解释。

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