Early life exposures and the occurrence and timing of heart disease among the older adult Puerto Rican population

Few studies have examined the effects of early life conditions on the timing of the onset of heart disease. We use the remarkable example of a representative sample of the population of older Puerto Ricans aged 60– 74 who lived in the countryside during childhood (n = 1,438) to examine the effects of seasonal exposures to poor nutrition and infectious diseases during late gestation on the timing of the onset and the probability of ever experiencing adult heart disease. Cox and log logistic hazard models controlling for childhood conditions (self-reported childhood health status and socioeconomic status [SES], rheumatic fever, and knee height) and adult risk factors (adult SES, obesity, smoking, texercise, and self-reported diabetes) showed that the risk of onset of heart disease was 65% higher among those born during high-exposure periods compared with unexposed individuals. However, there were no significant differences in median time of onset for those ever experiencing heart disease. As a comparison, we found that there were no significant seasonality effects for those who lived in urban areas during childhood. We conclude that early exposures in utero have important ramifications for adult heart disease among the older Puerto Rican population. We show, however, that while exposure is associated with the probability of ever experiencing adult heart disease, it is not associated with the timing of onset among those who do experience it.     

Health,wartime stress,and unit cohesion: Evidence from Union Army veterans

We find that Union Army veterans of the American Civil War who faced greater wartime stress (as measured by higher battlefield mortality rates) experienced higher mortality rates at older ages, but that men who were from more cohesive companies were statistically significantly less likely to be affected by wartime stress. Our results hold for overall mortality, mortality from ischemic heart disease and stroke, and new diagnoses of arteriosclerosis. Our findings represent one of the first long-run health follow-ups of the interaction between stress and social networks in a human population in which both stress and social networks are arguably exogenous.     

Knox meets Cox: Adapting epidemiological space-time statistics to demographic studies

Many important questions and theories in demography focus on changes over time, and on how those changes differ over geographic and social space. Space-time analysis has always been important in studying fertility transitions, for example. However, demographers have seldom used formal statistical methods to describe and analyze time series of maps. One formal method, used widely in epidemiology, criminology, and public health, is Knox’s space-time interaction test. In this article, we discuss the potential of the Knox test in demographic research and note some possible pitfalls. We demonstrate how to use familiar proportional hazards models to adapt the Knox test for demographic applications. These adaptations allow for nonrepeatable events and for the incorporation of structural variables that change in space and time. We apply the modified test to data on the onset of fertility decline in Brazil over 1960–2000 and show how the modified method can produce maps indicating where and when diffusion effects seem strongest, net of covariate effects.     

The Migrant–Nonmigrant Differentials in Prenatal Care Utilization: Evidence from Indonesia

Using the 2000 wave of Indonesian Family Life Survey (IFLS3), this study attempts to further complement studies that seek to analyze the relationship between migration and prenatal care utilization in Indonesia. The major conclusion from the multilevel logistic regression suggests that migrants are less likely than non-migrants to seek prenatal care in a public or private hospital but are more likely than non-migrants to initiate prenatal care in their first trimester and to receive four or more prenatal visits. Several measures of child, woman, household and community characteristics are also significant predictors of the location, timing and frequency of prenatal care. It is evident that the design of effective and efficient policies requires a more comprehensive knowledge of the determinants of migration and maternal healthcare services utilization. The assessment of whether the extent of the location, timing and frequency of prenatal care differs between migrants and non-migrants would have important policy implications for both individuals and society at large.     

Birth Outcome Measures and Infant Mortality

Recent studies have proposed alternative birth outcome measures as means of assessing infant mortality risk; nevertheless, there hasn’t yet been an integrated analysis of these approaches. We review 14 strategies, including various combinations of birth weight, gestational age, fetal growth rate, and Apgar scores—as predictors of early neonatal, late neonatal, and postneonatal mortality, and infant mortality. Using the NCHS linked birth/infant death file for 2001, we construct multivariate logit models and assess the associations between each of the 14 key birth outcome measures and four mortality outcomes. We find that all evaluated birth outcome measures are strong predictors, but Apgar scores are the strongest among all models for all outcomes, independent of birth weight and gestational age. Apgar scores’ predictive power is stronger for Mexican-, white-, and female-infants than for black- and male-infants. Second, all birth outcome measures remain significantly associated with mortality, but their predictive power reduces drastically over time. These findings suggest a rule of thumb for predicting infant mortality odds: when available, Apgar scores should always be included along with birth weight (or LBW status) and gestational age. Additionally, these findings argue for the continued study of low birthweight, gestational age, and Apgar scores as independently salient health outcomes.     

Climate change and population migration in Brazil’s Northeast: scenarios for 2025–2050

This research contributes to an understanding of the relationship between climate change, economic impacts and migration. We model the long-term relationship (up to 45 years of projection) between demographic dynamics—particularly migration—driven by changes in the performance of the economy due to climate changes in the Northeast region of Brazil. The region is of particular relevance to the study of climate change impacts given its large human population (28% of Brazil’s population) and high levels of impoverishment, having an extensive semi-dry area which will be severely impacted by growing temperatures. Ultimately, the integrated model generates state- and municipal-level migration scenarios based on climate change impacts on the primary economic sectors and their articulations with other sectors. Results suggest that the predicted climate changes will impact severely the agriculture sector in the region, acting as a potential migration push factor to other regions in the country. Finally, we discuss how the increased vulnerability of some groups, particularly migrants, can be factored into Brazilian public policy and planning.     

Individual and Contextual Correlates of Economic Difficulties in Old Age in Europe

With data drawn from the second public release version of the “Survey of Health, Aging and Retirement in Europe” (SHARE), we scrutinize individual and contextual (regional) correlates of economic difficulties among older Europeans, aged 65 or more. A logistic multi-level regression model with random intercept shows that the risk of being relatively poor varies considerably among the aged. We verified that the factors affecting poverty in each area are not merely the weighted sum of the effect of the more disadvantaged people within the same area, which also exists: poverty appears also significantly influenced by the specific context of residence.     

Teaching Business Demography Using Case Studies

Many faculty members consider using case studies but not all end up using them. We provide a brief review of what cases are intended to do and identify three ways in which they can be used. We then use an example to illustrate how we have used the case study method in teaching business demography. Among other benefits, we note that the case studies method not only encourages the acquisition of skills by students, but can be used to promote “deep structure learning,” an approach naturally accommodates other features associated with the case studies method—the development of critical thinking skills, the use of real world problems, the emphasis of concepts over mechanics, writing and presentation skills, active cooperative learning and the “worthwhileness” of a course. As noted by others, we understand the limitations of the case study method. However, given its strengths, we believe it has a place in the instructional toolbox for courses in business demography. The fact that courses we teach is a testament to our perceived efficacy of this tool.     

New Directions in the Development of Population Estimates in the United States?

The advent of a continuously updated Master Area File (MAF) following the 2000 census represents an information resource that can be tapped for purposes of developing timely, cost-effective, and precise population estimates for even the smallest of geographical units (e.g., census blocks). We argue that the MAF can be enhanced (EMAF) for these purposes. In support of our argument we describe a set of activities needed to develop EMAF, each of which is well within the current capabilities of the U.S. Census Bureau and discuss various costs and benefits of each. We also describe how EMAF would provide population estimates containing a wide range of demographic (e.g., age, race, and sex) and socio-economic characteristics (e.g., educational attainment, income, and employment). As such, it could largely negate and eliminate the need for many of the traditional demographic methods of population estimation and possibly reduce the number of sample surveys. We identify important challenges that must be surmounted in order to realize EMAF and make suggestions for doing so. We conclude by noting that the idea of the EMAF could be of interest to other countries with MAF files and strong administrative records systems that, like the United States, are facing the challenge of producing good population information in the face of increasing census costs.