Strengthening Qualitative Research through Methodological Innovation and Integration: A Longitudinal Analysis of Human Mortality

SES编号：0961304 PI：苏珊·伦纳德里根大学19世纪末到20世纪初，美国死亡率的急剧下降导致预期寿命的增加。人们普遍接受的解释是，天花和霍乱等传染病造成的死亡人数在减少，而心脏病和癌症等退行性疾病造成的死亡人数在增加，但疾病名称的变化使验证这一假设变得困难。本研究旨在开发一个数据库，系统地分析死亡原因，将死亡分类，并提供有关标准化和分类的质量，可靠性和重要性的信息，以了解死亡率的长期趋势。该数据库将包含1850年至1912年马萨诸塞州的霍利奥克和北安普顿的个人死亡记录，以及两种替代的死亡原因分类，一种是基于原始记录中给出的死亡原因的标准化，另一种是基于将死亡分配给早期的国际死亡原因分类。 这些数据还将包括衡量分类的可靠性，以及分类是否会对死亡率趋势产生重大影响。更广泛的影响：该数据库将以适合历史死亡率研究人员和公众用户（例如系谱学家）使用的形式向公众提供。有了这些数据，研究人员将能够更好地了解控制传染病在降低总体死亡率方面的作用。用于创建数据库的方法也将对在其他环境中工作的研究人员有用，这些环境中死亡原因的含义可能不清楚。

SES#: 0961304PI: Susan LeonardUniversity of MichiganDramatically falling death rates lead to increased life expectancy in the US between the late 19th century and the early 20th century. The widely accepted explanation is that deaths from infectious diseases such as smallpox and cholera were on the wane and deaths from degenerative diseases like heart disease and cancer were on the rise, but changes in the names of diseases make testing this hypothesis difficult. This study aims to develop a database that systematically standardizes the causes of death, groups deaths into categories, and provides information about the quality, reliability, and importance of standardization and classification to understanding long-term trends in death rates. The database will contain individual death records from Holyoke and Northampton, Massachusetts from 1850 to 1912 and two alternate cause of death classifications, one based on a standardization of the causes of death given in the original records and the other based on assigning deaths to the early International Classification of Causes of Death. The data will also include measurements of how reliable the classifications are, and whether classification makes a significant difference in mortality trends. BROADER IMPACTS: The database will be made available to the public in a form suitable for use by historical mortality researchers and public users for example, genealogists. With this data, researchers will be able to better understand the role of controlling infectious disease in lowering overall death rates. The methods used to create the database will also be useful for researchers working in other settings where the meaning of causes of death may be unclear.