生态学研究中的空间队列贝叶斯模型

D. Catelan, A. Biggeri, E. Dreassi, C. Lagazio
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引用次数: 11

摘要

研究了“低教育水平”与肺癌死亡率之间的生态关系,两者都记录在市级。从1905年到1940年,保留了六个出生队列。教育数据来源于1921-91年的人口普查。教育得分被定义为受教育程度较低的人的普遍程度,并以相对规模进行衡量,在每次人口普查中定义不同的“低教育水平”阈值。确定了4个可能相关的首次暴露年龄(20岁、30岁、40岁、50岁),以探讨疾病的时间模式。因此,每个队列的死亡率与不同时期的相对教育程度相匹配,对应于不同的首次接触年龄。评估了每个初次接触年龄的相关性以及教育程度与肺癌死亡率之间的关联程度(男性,托斯卡纳,1971-99),定义了一组分层贝叶斯模型,每个模型对应不同的病因学假设。结果表明,低教育程度与肺癌死亡率呈负相关,其强度随队列的增加而降低,在最后一个队列中变为正相关。这种关联在20-30岁的首次接触年龄范围内更为明显。这些结果与风险因素在社会经济阶层之间的流行病学转变是一致的,并且与引发致癌物的生物学模型是一致的。
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Space-cohort Bayesian models in ecological studies
The ecological association between ‘low educational level′ and lung cancer mortality, both recorded at municipality level, is investigated. Six birth cohorts were retained from 1905 to 1940. Education data were derived from censuses of the period 1921-91. The education score was defined as prevalence of less educated people and was measured on a relative scale, defining a different threshold for ‘low educational level′ at each census. Four potentially relevant ages at first exposure were defined (20, 30, 40,50) to explore the temporal pattern of the disease. Thus, mortality in each cohort was matched to relative education at different periods corresponding to different ages at first exposure. The relevance of each age at first exposure and the degree of association between education and lung cancer mortality (males, Tuscany, 1971-99) were evaluated, defining a set of hierarchical Bayesian models, each corresponding to a different aetiologic hypothesis. Results show an inverse relationship between low education score and mortality for lung cancer, whose intensity decreases by cohort and becomes positive in the last one. This association was more evident for age at first exposure in the range 20-30 years. These results are consistent with the epidemiological transition of risk factors among socioeconomic classes and are coherent with the biological model of initiating carcinogen agents.
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