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2014 - 2015

Adapting the Future Elderly Model to Japan

Karen Eggleston, PhD

This project adapts the Future Elderly Model (FEM), a demographic and economic Markov microsimulation model that projects the health conditions and functional status of an elderly population, to the Japanese population. The model starts with a “snap-shot” of the middle-aged and elderly Japanese population in 2010 and then projects risk of developing 19 chronic conditions, health care utilization, annual medical expenditures, and mortality. The researchers have received and analyzed the basic Japanese Study of Aging and Retirement (JSTAR) data; developed appropriate estimates of conditional mortality for the relevant diseases for the Japanese elderly; constructed a micro-simulation model; and used the 2007-2013 claims data for over 84,000 Japanese aged 40 to 70 to predict the medical spending associated with different constellations of medical conditions. The researchers will now look at how spending conditional on given co-morbidities differs by age group, and develop projections appropriate for the above-70 population. They have completed a preliminary integration of medical spending projections by age and health status into the FEM built from multiple waves of the JSTAR to estimate the health status transition matrix.




U.S. Mortality Variation by County, Age, Sex, and Race: Data and Preliminary Analyses

The researchers are developing prior work on the temporal, spatial and socioeconomic variation in US mortality for males and females. To achieve these goals they will assemble a data set of time series of mortality rates by age, cause and sex, and assemble a data set of relevant socio-economic and environmental variables for all US counties starting in 1970. Data set assembly now nearly complete, code for county-level comparisons of variance written and tested, and a new focus on male-female comparisons, so far mainly done with international data. International analyses are the first to causally demonstrate that changes in causes of death that are strongly influenced by tobacco use are responsible for the change in the female-male difference in life expectancy.  These results are one of the few that demonstrate, at whole-country population level, the impact of a single public health change.  Further, the study makes novel use of high-quality demographic data, cause-of-death data curated by WHO, and decompositions of mortality rates that have rarely been used in epidemiologic or public health literature.


Migration, Poverty Alleviation and Wellbeing of the Elderly: Population Modeling for Rural Western China

Jian Quanbao, PhD

The researchers developed models for the time course of the economic demography of remote Chinese villages that takes into account the migration, and sometimes return, of the villagers, the predicted remittances, the costs for maintenance of those remaining in the villages (mainly parents and children of the migrants), and the marriage squeeze on males, which is very pronounced in remote rural China. They constructed formal mathematical models that include the above-mentioned features, as well as the rate of migration (which is available from our data). These models are necessarily mathematical simplifications of the actual social and aging processes, but they allow predictions as to the needs of these communities over the next few decades. It is natural to assume that China’s economic growth will continue at a rate within a few percent of its present value, and hence that rural-to-urban migration will continue.

The data previously collected provides a snapshot of the needs of the communities in remote rural China. The researchers’ models allowed prediction of the future needs, in terms of facilities for education, health care, management of the elderly, as well as transportation infrastructure, which they have shown is a major impediment to economic progress in remote rural China. Modeling then explored how rural-urban migration and poverty alleviation policies affect the wellbeing of the elderly and their very young family members in rural Western China. Application of these models to the data provided important suggestions for formulation of policies regarding the ever-increasing migration of farmers to urban areas.

At paper entitled "Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options" was published in Population Research and Policy Review in 2011. A second paper entitled Marriage squeeze in China’s future was published in Asian Population Studies in 2011.  And a third paper entitled Estimates of missing women in twentieth century China was published in Continuity and Change in 2012. A paper entitled "The Life Cycle of Bare Branch Families in China---A Simulation Study" " has been accepted by Canadian Studies in Population and another paper entitled “Marriage squeeze, never-married proportion and mean age at first marriage in China” is now under review.


Demographic Impact of HIV on Africa's Elderly

Eran Bendavid, MD, MS

The overall goal of this project was to estimate the relationship between the HIV epidemic in Africa and mortality patterns of Africa's elderly.  The lead investigator audited Professor Shripad Tuljapurkar's demography class to have a more nuanced understanding of the methods involved in mortality estimations.  He identified the data sources to be used in this project, and employed the services of a programmer at Stanford's Quantitative Sciences Unit, Jessica Kubo, to help with the data analysis.  They revised the proposed approach after they discovered a new source of data that provides both a census of household populations and recent household deaths in nationally representative surveys in 10 African countries between 2005 and 2009.  They used this data to estimate age- and gender-specific mortality directly and compare those estimates to the official estimates published by the UN Population Division (UNPD) and the World Health Organization (WHO).  To the best of their knowledge, they were the first ones to use this information for demographic purposes.  The researchers found very close concordance between their direct estimates of mortality up to age 60.  From age 60 upwards, however, they found a consistent and widening (with age) gap in the estimates that suggest old-age mortality in these countries is over-estimated by the UNPD and WHO.  They tested the determinants of these discrepancies, but think the HIV epidemic's burden on prime-age adults is skewing modeled estimates of older-age mortality, and that in fact older Africans are in better health than what demographic estimates suggest.  They presented the work in a local (Stanford) demography conference, and Dr. Bendavid travelled to Washington DC to discuss the work with colleagues at the Population Association of America conference. A manuscript entitled, “Comparative analysis of old-age mortality estimations in Africa” was published in PLoS One in 2011, and another manuscript “United States aid policy and induced abortion in sub-Saharan Africa” was published in Bull World Health Organization”.


The Quantitative Genetic Architecture of Sex Differences in Longevity

Jamie Jones, PhD

The aim of this project was to investigate the heritability of longevity and the relative contributions of selection on mean lifespan and sex-specific lifespan to human longevity. The researchers pursued two different computational approaches to the problem: (1) period samples and their associated offspring, and (2) backward genealogical pruning of samples.  From this research, they answered whether these two approaches yield different estimates of heritabilities or G-matrices?  And if different period samples yield stable estimates of G? They developed a way through which distinct estimates can reduce uncertainty in the overall parameter estimates. This research has resulted in 2 manuscripts entitled “The Marginal Valuation of Fertility and Risk-Sensitive Reproductive Decision-Making during Economic Crises” and “Quantitative Genetic Analysis Reveals Trade-Offs between Age at First Reproduction and Fertility”.

How and Why US Counties and UK Registration Areas Differ in the Distribution of Age at Death

Shripad Tuljapurkar, PhD

This project aimed to assemble a US mortality data series with county-level identifiers and assembled data on covariates at the county level (education, income, health care). The researcher analyzed changes in variance at adult death and the age distribution of deaths within counties as well as among them. In addition he assembled a UK mortality data set at the local area level and analyzed change in the age distribution of deaths within and among local areas. This pilot helped illuminate the nature of inequalities in mortality within and between the US and UK, especially the puzzling differences that have been reported in the literature. This pilot also helped prepare for future international comparisons of the nature and source of mortality inequality within and between countries. The researcher completed a systematic analysis of mortality change in the US and its age-patterns, using alternative measures of disparity (entropy and variance). He developed an analytical formulation of the dynamics of change in life expectancy using versions of the Lee-Carter model, and obtained new insights into the processes of mortality change. He applied these to spatially distributed data. This project led to the publication of three manuscripts: “The Final Inequality”, “Variance in death and its implications for modeling and forecasting mortality” and “Linking the population growth rate and the age-at-death distribution”. The researchers submitted an R01 grant entitled, “Individual variation, environments and evolution in biodemography” in March 2012.