Kenneth Land
Duke University, Social Science Research Institute, Faculty Member
The analyses conducted in Part I did not exhaust all factors affecting age patterns of age-related changes in health and mortality. They actually provided a strong rationale for conducting more detailed analyses which require advanced... more
The analyses conducted in Part I did not exhaust all factors affecting age patterns of age-related changes in health and mortality. They actually provided a strong rationale for conducting more detailed analyses which require advanced methods of mathematical and statistical modeling. Development and implementation of such state-of-the-art methods is driven by two major factors. The first reflects systemic effects of various behavioral, physiological, and environmental processes on human aging and the related phenotypes. The second is that not all such processes can be readily measured and quantified in studies of human health, aging, and lifespan. In this regard, longitudinal data play a pivotal role in discovering different aspects of knowledge related to aging, health, and lifespan. A variety of statistical methods can be used to analyze longitudinal data.
Research Interests: Psychology and Longevity
Decades of studies of candidate genes show that they are not linked to aging-related traits in a straightforward manner. Recent genome-wide association studies (GWAS) have reached fundamentally the same conclusion by showing that traits... more
Decades of studies of candidate genes show that they are not linked to aging-related traits in a straightforward manner. Recent genome-wide association studies (GWAS) have reached fundamentally the same conclusion by showing that traits in late life are likely controlled by a relatively large number of common genetic variants. Further, GWAS often show that the associations are of tiny effect. The primary reason for complex actions of genes on age-related traits characteristic of modern societies is the elusive role of evolution in these traits. Therefore, the complexity of gene actions on traits in late life appears to be inherent. The complexity of gene actions on traits in late life can well explain why many genetic signals appear to be weak. In this chapter, we consider several examples of complex modes of gene actions, including genetic tradeoffs, antagonistic genetic effects on the same traits at different ages, and variable genetic effects on lifespan. The analyses focus on the APOE common polymorphism.
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The growth in interest in the biodemography of human aging, health, and longevity is motivated by the desire to better understand the factors and mechanisms responsible for age patterns and time trends in human mortality rates and... more
The growth in interest in the biodemography of human aging, health, and longevity is motivated by the desire to better understand the factors and mechanisms responsible for age patterns and time trends in human mortality rates and survival curves. The availability of human longitudinal and cross-sectional data on populations of study subjects made addressing these research questions possible and stimulated the development of methodological ideas on how these data could be efficiently analyzed. Biodemographic methods of studying human aging, health, and longevity allow for integration and efficient use of data and knowledge from relevant research fields including epidemiology, genetics, sociology, gerontology, environmental sciences, population genetics, etc. This chapter provides a selective account of important historical steps in the development of this research field in which members of the present research team have participated. It also illustrates how the integration of demographic and biological knowledge and data may contribute to progress in the field. Finally, it briefly describes the content and connections among the chapters of this monograph.
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Foreword List of Tables and Figures Notes on Contributors Introduction L.van der Maesen & A.Walker European and Global Challenges L.van der Maesen & A.Walker Theoretical Foundations W.Beck, L.van der Maesen & A.Walker... more
Foreword List of Tables and Figures Notes on Contributors Introduction L.van der Maesen & A.Walker European and Global Challenges L.van der Maesen & A.Walker Theoretical Foundations W.Beck, L.van der Maesen & A.Walker Conceptual Location of Social Quality P.Herrmann, L.van der Maesen & A.Walker Social Quality Indicators P.Herrmann, L.van der Maesen & A.Walker Socio-Economic Security D.Gordon Social Cohesion Y.Berman & D.Phillips Social Inclusion A.Walker & C.Walker Social Empowerment P.Herrmann The Functions of Social Quality Indicators L.van der Maesen Social Quality and Sustainability L.van der Maesen & A.Walker References Index
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AbstractThis paper is written to briefly summarize comments made on our paper “Fifty years after the social indicators movement: Has the promise been fulfilled? An assessment and an agenda for the future”, including additional ideas... more
AbstractThis paper is written to briefly summarize comments made on our paper “Fifty years after the social indicators movement: Has the promise been fulfilled? An assessment and an agenda for the future”, including additional ideas suggested by our reflections on the commentators’ remarks.
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Aging-related deterioration in health impacts an important economic component: the medical costs associated with disease diagnosis and treatment. Because almost all U.S. residents aged 65+ years old are covered by the Medicare system,... more
Aging-related deterioration in health impacts an important economic component: the medical costs associated with disease diagnosis and treatment. Because almost all U.S. residents aged 65+ years old are covered by the Medicare system, prediction of future Medicare costs is crucial for health care planning. These costs represent the sum of the medical costs associated with every person enrolled in the system. Individual costs deal with expenditures associated with disease onsets, their treatment, and subsequent causes of acute and chronic conditions. In this Chapter, we analyze time trajectories of medical costs associated with the onset of 12 aging-related conditions: acute coronary heart disease, stroke, ulcer, breast cancer, prostate cancer, melanoma, lung cancer, colon cancer, diabetes, asthma, Parkinson’s disease, and Alzheimer’s disease. These trajectories were reconstructed using the NLTCS data linked to the Medicare Files of Service Use (NLTCS-M). We developed a special procedure for selecting individuals with onset of each geriatric disease and used it for identification of the date of the disease onset. We found that the time patterns of medical cost trajectories are similar for all studied diseases. These patterns can be described in terms of four components representing: (i) the cost associated with initial comorbidity (reflected in medical expenditures); (ii) the cost of the onset of each disease; (iii) the rate of decline in medical costs due to recovery, reflecting a reduction of medical expenditures after disease onset; and (iv) an acquired comorbidity characterizing the steady-state of medical costs after disease onset. The description of the trajectories was formalized by a model that explicitly involves four parameters reflecting these four components of the medical cost trajectories. The four components were evaluated for the entire U.S. population as well as for the subpopulation conditional on age, disability, and comorbidity states, and survival for 2.5 years after the date of the disease onset. The approach developed results in a family of new forecasting models with covariates. The properties of Medicare expenditures for older U.S. adults revealed in these analyses contribute to an understanding of the impacts of screening effectiveness and therapeutic innovations on the dynamics of disease incidence with advancing age as well as for projecting future Medicare costs.
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Demography of aging is a subfield of demography that focuses on the older members of a population as well as the processes and consequences of population aging. Research in the demography of aging examines a number of topics, including... more
Demography of aging is a subfield of demography that focuses on the older members of a population as well as the processes and consequences of population aging. Research in the demography of aging examines a number of topics, including the state and status of the older population, changes in the numbers, proportionate size, and composition of the older population, demographic forces of fertility, mortality, and migration that bring about these changes, and the effects of these changes on the social, economic, health, and personal well-being of the elderly. Major factors associated with population aging are reviewed.
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Our projection study demonstrated that, while the population in China will be aging at a rapid speed and to a huge scale, particularly the oldest-old aged 80+, Chinese family households will continue to contract to a substantially smaller... more
Our projection study demonstrated that, while the population in China will be aging at a rapid speed and to a huge scale, particularly the oldest-old aged 80+, Chinese family households will continue to contract to a substantially smaller average size in the next a few decades. The proportion of elderly households with at least one person aged 65+ will increase dramatically in China in the next few decades. By the years 2030 and 2050, the proportion of the elderly aged 65+ living in empty-nest households without children among the total population will be 2.5 and 3.7 times that in 2000. The increase in percentages of the oldest-old living in empty-nest households will be even more dramatic: 4 and 11.5 times as high as in 2000 for the years 2030 and 2050. These aging population structure problems – with respect to proportion of elderly and elderly households as well as proportion of elderly living in empty-nest households – will be much more serious in rural areas than in urban areas. This strongly suggests that, to avoid serious social problems in the future China needs to change its household registration policy which restricts free movement from rural to urban areas and to adopt policies encouraging rural-to-urban family migration or family reunion after young migrants settle down in urban areas.
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In this chapter presents projections of households and living arrangements for the five decades from 2000 to 2050 with medium, small, and large family scenarios, for each of the 50 states, DC, six counties of Southern California, and the... more
In this chapter presents projections of households and living arrangements for the five decades from 2000 to 2050 with medium, small, and large family scenarios, for each of the 50 states, DC, six counties of Southern California, and the Minneapolis-St. Paul Metropolitan Area. Among many interesting numerical outcomes of household and living arrangements projections with medium, low, and high bounds, the aging of American households over the next few decades across all states/areas is particularly striking.
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This chapter presents a tutorial with detailed explanations to help users set up the projection model. You may simply use the example input data files that accompany the software to quickly go through the main steps.
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Research Interests: Sociology and Trajectory
Research Interests: Psychology and Routledge
Various approaches to statistical model building and data analysis that incorporate unobserved heterogeneity are ubiquitous in different scientific disciplines. Frailty models introduce the concept of unobserved or hidden heterogeneity in... more
Various approaches to statistical model building and data analysis that incorporate unobserved heterogeneity are ubiquitous in different scientific disciplines. Frailty models introduce the concept of unobserved or hidden heterogeneity in survival analysis for time-to-event data. Longitudinal data provide an additional source of heterogeneity that can contribute to differences in risks of time-to-event outcomes. Individual age trajectories of biomarkers can differ due to various observed as well as unobserved factors and such individual differences propagate to differences in risks of related time-to-event outcomes such as the onset of a disease or death. In this chapter, we briefly review recent biostatistical approaches to deal with heterogeneity, focusing on approaches that model both time-to-event and longitudinal data such as joint models (see Chap. 11). One of the approaches to deal with hidden heterogeneity assumes that a population under study may consist of “latent” subpopu...
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Count responses with grouping and right censoring have long been used in surveys to study a variety of behaviors, status, and attitudes. Yet grouping or right-censoring decisions of count responses still rely on arbitrary choices made by... more
Count responses with grouping and right censoring have long been used in surveys to study a variety of behaviors, status, and attitudes. Yet grouping or right-censoring decisions of count responses still rely on arbitrary choices made by researchers. We develop a new method for evaluating grouping and right-censoring decisions of count responses from a (semisupervised) machine-learning perspective. This article uses Poisson multinomial mixture models to conceptualize the data-generating process of count responses with grouping and right censoring and demonstrates the link between grouping-scheme choices and asymptotic distributions of the Poisson mixture. To search for the optimal grouping scheme maximizing objective functions of the Fisher information (matrix), an innovative three-step M algorithm is then proposed to process infinitely many grouping schemes based on Bayesian A-, D-, and E-optimalities. A new R package is developed to implement this algorithm and evaluate grouping s...
Research Interests: Sociology, Computer Science, Statistics, Machine Learning, Survey Methodology, and 11 moreExperimental Design, Medicine, Fisher information, Optimality, Search Algorithm, Count data, Public health systems and services research, Sociological Methods, Bayesian Probability, Poisson Distribution, and Right-censoring
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Despite broad interest in the mechanisms responsible for human aging and numerous efforts to identify factors contributing to morbidity, biological senescence, and longevity, these processes still remain elusive. This makes the systemic... more
Despite broad interest in the mechanisms responsible for human aging and numerous efforts to identify factors contributing to morbidity, biological senescence, and longevity, these processes still remain elusive. This makes the systemic description of aging-related changes embedded in data from different studies a difficult task. Indeed, observational studies typically measure not only major changes in health and well-being captured by well-defined risk factors (e.g., physiological measurements), but also various aging-related changes spread throughout hundreds of distinct variables. The connection between such variables as well as between each of these variables and health or survival outcomes is unclear and often cannot be evaluated statistically with acceptable accuracy. This is due to the fact that the number of these variables is typically large, while the effect of each on health and survival is small, so most estimates of effect parameters in corresponding statistical models are statistically non-significant. This chapter describes a line of analysis that is based on the premise that, by taking such “mild-effect” variables into account, the description of aging-related deterioration in health and well-being in humans can be substantially improved without costly investments in collecting new data. To realize this potential, new statistical methods are required.
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In this chapter, we apply the ProFamy extended cohort-component model to project U.S. households by race from 2000 to 2050. We address important questions such as: How may demographic changes alter the number and proportion of different... more
In this chapter, we apply the ProFamy extended cohort-component model to project U.S. households by race from 2000 to 2050. We address important questions such as: How may demographic changes alter the number and proportion of different types and sizes of households in future years? How may demographic changes affect the living arrangements of elderly persons? We also provide evidence of “family household momentum,” which is similar to the well-known phenomenon of population momentum.
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In this chapter presented a simple method associated with the ProFamy projection model and software to project the annual pension deficit rate based on (1) The elderly dependency ratio determined by demographic factors of fertility,... more
In this chapter presented a simple method associated with the ProFamy projection model and software to project the annual pension deficit rate based on (1) The elderly dependency ratio determined by demographic factors of fertility, mortality and migration; (2) The retirement age; and (3) Four (or three) pension program parameters, which can be predicted by trend extrapolation or expert opinions. These input parameters can be derived from commonly available data. The illustrative application to China demonstrates that if the average age at retirement gradually increases from the current very low level to age 65 for both men and women in 2050, the annual pension deficit rate would be largely reduced or eliminated under various possible demographic regimes up to the middle of this century. With everything else being equal, the annual pension deficit rate in the scenario of medium fertility (associated with a two-child policy) would be much lower than that under low fertility (associated with the current fertility policy unchanged) after 2030. The impact of potentially faster mortality decline is likely sizable but relatively moderate; it starts earlier than the effects of fertility change. Note that one may also use the simple method presented in this chapter to explore the magnitude and timing of impacts on future pension deficits due to alternative international migration and/or pension policies by predicting or assuming the size and age/gender structure of international migration and/or the pension program parameters.
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A better understanding of processes and mechanisms linking human aging with changes in health status and survival requires methods capable of analyzing new data that take into account knowledge about these processes accumulated in the... more
A better understanding of processes and mechanisms linking human aging with changes in health status and survival requires methods capable of analyzing new data that take into account knowledge about these processes accumulated in the field. In this paper, we describe an approach to analyses of longitudinal data based on the use of stochastic process models of human aging, health, and longevity which allows for incorporating state of the art advances in aging research into the model structure. In particular, the model incorporates the notions of resistance to stresses, adaptive capacity, and "optimal" (normal) physiological states. To capture the effects of exposure to persistent external disturbances, the notions of allostatic adaptation and allostatic load are introduced. These notions facilitate the description and explanation of deviations of individuals' physiological indices from their normal states, which increase the chances of disease development and death. Th...