Breathing new life into death certificates: Extracting handwritten cause of death in the LIFE-M project.

The demographic and epidemiological transitions of the past 200 years are well documented at an aggregate level. Understanding differences in individual and group risks for mortality during these transitions requires linkage between demographic data and detailed individual cause of death information. This paper describes the digitization of almost 185,000 causes of death for Ohio to supplement demographic information in the Longitudinal, Intergenerational Family Electronic Micro-database (LIFE-M). To extract causes of death, our methodology combines handwriting recognition, extensive data cleaning algorithms, and the semi-automated classification of causes of death into International Classification of Diseases (ICD) codes. Our procedures are adaptable to other collections of handwritten data, which require both handwriting recognition and semi-automated coding of the information extracted.

Exploring agent-level calculations of risk and returns in relation to observed land-use changes in the US Great Plains, 1870-1940.

Land-use change in the U.S. Great Plains since agricultural settlement in the second half of the nineteenth century has been well documented. While aggregate historical trends are easily tracked, the decision-making of individual farmers is difficult to reconstruct. We use an agent-based model to tell the history of the settlement of the West by simulating farm-level agricultural decision making based on historical data about prices, yields, farming costs, and environmental conditions. The empirical setting for the model is the period between 1875 and 1940 in two townships in Kansas, one in the shortgrass region and the other in the mixed grass region. Annual historical data on yields and prices determine profitability of various land uses and thereby inform decision-making, in conjunction with the farmer's previous experience and randomly assigned levels of risk aversion. Results illustrating the level of agreement between model output and unique and detailed household-level records of historical land use and farm size suggest that economic behavior and natural endowments account for land change processes to some degree, but are incomplete. Discrepancies are examined to identify missing processes through model experiments, in which we adjust input and output prices, crop yields, agent memory, and risk aversion. These analyses demonstrate how agent-based modeling can be a useful laboratory for thinking about social and economic behavior in the past.

Determinants of tubal ligation in Puebla, Mexico.

Tubal ligation provides an effective and reliable method by which women can choose to limit the number of children they will bear. However, because of the irreversibility of the procedure and other potential disadvantages, it is important to understand factors associated with women's choice of this method of birth control. Between May 1999 and August 2000, data were collected from 755 women aged 40 to 60 years from a cross-section of neighborhoods of varying socio-economic make-up in Puebla, Mexico, finding a tubal ligation rate of 42.2%. Multiple logistic regression models were utilized to examine demographic, socio-economic, and reproductive history characteristics in relation to women's choice of tubal ligation. Regression analyses were repeated with participants grouped by age to determine how the timing of availability of tubal ligation related to the decision to undergo the procedure. The results of this study suggest that younger age, more education, use of some forms of birth control, and increased parity were associated with women's decisions to undergo tubal ligation. The statistically significant difference of greater tubal ligation and lower hysterectomy rates across age groups reflect increased access to tubal ligation in Mexico from the early 1970s, supporting the idea that women's choice of tubal ligation was related to access.

Drug- and Alcohol-Associated Deaths in U.S. Jails.

Drugs and alcohol are the third leading cause of death in U.S. jails. We analyzed 2000 to 2013 national jail mortality data by coding text data. We identified 1,442 deaths associated with drugs and alcohol. Drug-associated deaths were more than double alcohol-associated deaths during 2009 to 2013 when drug type was available for drug-associated mortality. Only 18% of deaths within 7 days of arrest for alcohol intoxication were officially coded as involving drugs/alcohol intoxication. Among the 103 deaths associated with substance withdrawal, 66 involved alcohol, 21 involved drugs (primarily opioids), and 16 could not be determined. Drugs and alcohol likely contribute to more deaths in jails than has been recognized due to how deaths are coded. Alcohol and opioid withdrawal represent a small but underappreciated contributor to jail deaths.