地方性慢性砷中毒的平均年龄、平均膳食砷剂量和年龄特异性患病率的数学模型:一项人体毒理学研究。

R Zaldívar, G L Ghai
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引用次数: 0

摘要

本研究的目的是建立地方性慢性砷中毒的平均年龄、平均砷膳食剂量和年龄特异性患病率的数学模型。收集了智利北部Antofagasta公社1968-1971年期间地方性慢性砷中毒的平均年龄(岁)、平均膳食砷剂量(mg/kg体重/天)和每10万人中年龄特异性流行率的数据。地方性慢性砷中毒,是指伴有明显或者严重慢性砷中毒症状(如慢性腹泻、肝硬化、慢性支气管炎、支气管扩张、复发性支气管肺炎、心脏肥大、全身动脉闭塞性疾病、脑血栓形成)的慢性砷中毒皮肤病。每10万人年龄患病率与平均砷剂量呈正相关(r = + 0.9593),与平均年龄呈负相关(r = 0.8789)。这些结果表明,患病率随着年龄的增长而下降,随着砷剂量的增加而增加。拟合多元线性回归模型E(y) = alpha + beta X1 + gamma X2,其中y代表每10万人中特定年龄的患病率,X1代表平均砷剂量,X2代表平均年龄。参数(alpha, beta和gamma)的估计值是通过最小化残差平方和sigma(y - alpha - beta X1 - gamma X2)2获得的。得到多元线性回归方程:Y = 202.161 + 8452.455 X1 - 2.394 X2。在患病率的总变异性中,96.22%是由多元回归解释的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical model of mean age, mean arsenic dietary dose and age-specific prevalence rate from endemic chronic arsenic poisoning: a human toxicology study.

The aim of this investigation was to develop a mathematical model of mean age, mean arsenic dietary dose, and age-specific prevalence rate for endemic chronic arsenic poisoning. Data on mean age (years), mean arsenic dietary dose (mg/kg body weight/day), and age-specific prevalence rate per 100,000 population for endemic chronic arsenic poisoning in Antofagasta Commune, northern Chile, for the 1968-1971 period, were collected. Endemic chronic arsenic poisoning means here chronic arsenical dermatosis associated with marked or sever symptoms (or signs) of chronic arsenic poisoning (chronic diarrhoea, hepatic cirrohsis, chronic bronchitis, bronchiectasis, recurrent broncho-pneumonia, cardiomegaly, systemic occlusive arterial disease, cerebral thrombosis, etc.) There was a strong positive correlation between age-specific prevalence rate per 100,000 population and mean arsenic dose (r = + 0.9593) and a negative correlation between prevalence rate and mean age (r = 0.8789). These findings show that the prevalence rate declines with the advancing age and increases with the increase of arsenic dose. A multiple linear regression model E(y) = alpha + beta X1 + gamma X2, where y represents the age-specific prevalence rate per 100,000 population, X1 the mean arsenic dose, and X2 the mean age, was fitted to the data. The estimates of the parameters (alpha, beta, and gamma) were obtained by minimizing the residual sum of squares sigma(y - alpha - beta X1 - gamma X2)2. The following multiple linear regression equation was obtained: Y = 202.161 + 8452.455 X1 - 2.394 X2. Of the total variability in the prevalence rate, 96.22 per cent was accounted for by the multiple regression.

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