海岱地区大汶口文化时期人口死亡年龄的统计分布特征

Statistical Distribution of Age at Death of the Dawenkou Human in the Haidai Area

人口死亡年龄是揭示一个族群健康状况和社会经济条件的重要指标。本文根据海岱地区大汶口文化时期九个墓地人骨遗存的发掘报告,运用定量统计的方法检验了人口死亡年龄分布特征。发现该区大汶口文化时期人口的死亡年龄分布近似服从正态分布。最后探讨了造成人口低死亡年龄的可能原因,并给出了这一概率分布的数学意义以及在史前人口学中的应用前景。

Average life expectancy is an important measure of the physical and socio-economic conditions in modern demography. A common approach to the calculations of the average life expectancy is the life table. However, recent work calls into question the usefulness of this method in prehistoric demography because of poor burial and conservation conditions for infants and younger age groups, making the skeletal data incomplete and underrepresentative. Remarkable theoretical progress in demographic statistics sheds new light on skeletal remains from Neolithic graveyards in terms of survival analysis. If the age at death can be treated as a continuous random variable that follows a specific probability distribution function, then the mortality probability at any age of death can be derived within the framework of survival analysis, which would allow a calculation the average life expectancy. Although few studies on the average life expectancy of Neolithic man in East China have been conducted using the life table method, little is known about the characteristics of probability distribution of age at death for this prehistoric population. In this study, we investigated 44 excavation reports on human skeletal remains from the Dawenkou Cultures, Haidai area. Among these sites, nine graveyards had a large sample size, and therefore were selected for statistical analysis of age at death. Histogram, P-P probability plots, skewness, and kurtosis were used to test the normality of the probability distribution of age at death of Dawenkou man. Our results show that age at death of these nine archaeological sites closely follow the normal distribution rather than the Weibull distribution. We also discussed potential applications of normality of age at death in archaeological demography.