Hallie J. Kintner

Determinants of temporal and areal variation in infant mortality in Germany, 1871–1933

This article investigates how sociodemographic, economic, medical, and public health factors influence infant mortality by using data about German administrative areas from 1871 to 1933. Marital fertility has the largest impact on infant mortality, followed by illegitimacy, medical care, urbanization, and infant welfare centers. The variables considered here account for most of the variation in infant mortality. Some of the unexplained variance is due to factors associated with regions, such as breastfeeding patterns, and with time periods, such as national health insurance. The analyses found no evidence that advances in medical technology affected infant mortality or that the influence of economic development changed over time.

The Mortality Transition in Germany, 1860–1935; Evidence by Region

T he mortality transition is an integral part of the larger process of the demographic transition from high to low levels of both fertility and mortality. Historical progress in reducing death rates since the nineteenth century has been one of the most significant achievements of the modern era. More recently, the discussion has widened to include both mortality and morbidity, and the process has been renamed the Health Transition (Caldwell et al. 1990). It has also been shown historically that morbidity and mortality did not necessarily move synchronously over time and that death rates may not provide an entirely satisfactory indicator of general healthiness (Riley 1989). Nonetheless, death rates do furnish effective indices of overall socioeconomic progress and development. The World Bank (1991), for example, includes five mortality measures (the crude death rate, the infant mortality rate, 4(5), the expectation of life at birth, and the female expectation of life at birth) among its social indicators of development. Much remains to be learned about the historical antecedents of different mortality declines or “epidemiological transitions” to use Oman’s terminology (1971). Controversy continues about the relative roles of socioeconomic development (especially nutrition) compared with medicdscientific advances, public health measures, and changes in personal health habits. Much of the controversy stems from the well-known work of Thomas McKeown (1976,1979), who asserted the importance of improvements in nutrition and the general standard of living before the 1930s. His argument was based on a process of elimination: ecobiological factors were not important (with the exception of one or two diseases). Medical science made little direct contribution until well into the twentieth century. Therefore, it must have been a residual explanation-some combination of improved standard of living and public health measures. He was equivocal about the precise mix of the socioeconomic and public health factors, at one point assigning to public health a role of about 25 percent of the English mortality decline over the period 1838-1901. This emphasis on nutrition and standard of living has been subjected to criticisms on the grounds that social interventions in the form of public health measures (e.g., clean water supplies, proper sanitary sewage disposal, quarantine, vaccination and inoculation, child care health education, programs to ensure pure food and drink [especially milk], improved education and licensing of medical and health care personnel, and so forth) have done much to explain mortality declines as well as mortality differentials at points in time (see, for example, Johansson 1994; Johansson and Mosk 1987; Mercer 1990; Szreter 1988; Ruzicka and Kane 1990). Although it is difficult in practice to disentangle those causal factors, additional detailed information on specific mortality transitions will certainly be necessary. One important dimension is space. Geographic variation can reveal much. It is clear that urbanization was critical to differential mortality. In the nineteenth century, urban death rates were most often substantially higher than rural death rates because of the unfavorable effects of crowding and poor urban sanitation and housing conditions (Weber 1899, 343-67; Davis 1973; Preston and Haines 1991). For example, for Prussia in 1876177, the urban infant mortality rate was 21 percent higher than the rural rate. This differential had disappeared (and slightly reversed) by 1908-12 (Knodel 1974, 169). The urban mortality transition was thus more rapid and often earlier than the rural decline in death rates. Germany as a whole moved from approximately 36 percent urban in 1871 to 60 percent in 1910 to 70 percent by 1939. The proportion of the labor force in the primary sector (agriculture, forestry, and fisheries) declined from about 42 percent in 1882 to about 18 percent in 1939 (Knodel 1974, 4). Therefore, the industrial and urban revolutions had a decisive impact on the German economy, population, and society in that era, especially relative to urban-

Measurement errors in census counts and estimates of intercensal net migration.

The authors present a method for generating confidence intervals around estimates of intercensal net migration made using the life table survival method that incorporate estimates of census measurement errors. The life table survival method applies a life table to a census count to project survivors at some past or future time points. Net migration is then estimated as the difference between the projected number of survivors and the enumerated population at that time. The authors present confidence intervals based on mean square error the sum of the variance and squared bias. It is assumed that random variation in the number of net migrants in an age-sex group is due to random variation in mortality rates and to measurement errors in census counts. The authors illustrate the technique using data from a small area in Alaska. (authors)

Representation and Analysis Challenges in Design for Part-Reuse: An Automotive Case Study

Product Platform and Product Family Design is reshaping the way that many companies develop products. But how well are the CAD and PLM technologies keeping pace with this advancement? This paper presents data from a three month ethnographic study of an expert automotive body engineer. His assignment is to modify the design of an existing body structural member for use in the next-generation vehicle. The modification was necessitated by manufacturability issues. Observations and subsequent interviews revealed that manipulation time, model reuse and representation of part interfaces (such as welds) presented challenges to the body engineer and collaborating analysis engineers. Despite re-use of a physical part, the engineer had to create a new CAD model. The redesign involved breaking the original part into two pieces. The engineer sketched initial design concepts on paper because manipulation time in the CAD system was so lengthy. After determining the design concept, the engineer created a new CAD model, including new weld locations, and passed it along to analysis engineers for stiffness and crashworthiness FEA testing. Hand-offs between design and analysis engineers were challenged by the PLM system. The paper ends by making recommendations for improving CAD and PLM tools.Copyright

Ties that bind: A case study of the link between employers, families, and health benefits

Most US residents receive health benefits from their employer. Groups of employees and their families are therefore the basis for health care financing. Health care costs rose dramatically during the 1980s and employers looked for ways to control them. One approach is to control the size of the group provided health benefits by an employer. This paper uses a demographic perspective to explore the determinants of change in an employers group. It examines the linkages among employer policies, employee turnover, and family dynamics. How much control does an employer have over group size? We identify the relative contributions of employment and demographic processes to changing group size. We use a decomposition technique based on matching individual records between consecutive years. We apply this technique to a case study of the health benefits group consisting of General Motors salaried employees and their families. We find that employers face limits to the control that they can exert over the size of the health benefits group associated with their active workforce. Demographic processes unrelated to employee turnover or transfers to layoff or retirement accounted for a large portion of the population change in the case study.

MEAN SQUARE ERROR CONFIDENCE INTERVALS FOR MEASURING UNCERTAINTY IN INTERCENSAL NET MIGRATION ESTIMATES: A CASE STUDY OF ARKANSAS, 1980-1990

Estimates of net migration are virtually always constructed from the standpoint that the mortality underlying a survived population is not stochastic and the census counts framing the intercensal period are error free. There is compelling evidence however that mortality should be viewed as a random variable and census counts contain systematic errors. This evidence suggests that net migration accuracy is affected both by random error and bias. We explore the estimation of net migration accuracy by placing Mean Square Error (MSE) confidence intervals around 1980-1990 net migration estimates for Arkansas made using the Forward Life Table Survival Method....We argue that the MSE intervals provide an accurate description of the uncertainty in net migration estimates.... (EXCERPT)