• Introduction: 1: Introduction: The Biodemography of Complex Relationships among Aging, Health, and Longevity.- Part I: Informational on Aging, Health, and Longevity from Available Data.: 2: Age Trajectories of Physiological Indices: Which Factors Influence Them?.- 3: Health Effects and Medicare Trajectories: Population-Based Analysis of Morbidity and Mortality Patterns.- 4: Evidence for Dependence among Diseases.- 5: Factors that May Increase Vulnerability to Cancer and Longevity in Modern Human Populations.- 6: Medical Cost Trajectories and Onsets of Age-Associated Diseases.- 7: Indices of Cumulative Deficits.- 8: Dynamic Characteristics of Aging-related Changes as Predictors of Longevity and Healthy Lifespan.- 9: The Complex Role of Genes in Diseases and Traits in Late Life: An Example of the Apolipoprotein E Polymorphism.- 10: Conclusions Regarding Empirical Patterns of Aging, Health, and Longevity.- Part II: Statistical Modeling of Aging, Health, and Longevity.- 11: Approaches to Statistical Analysis of longitudinal Data on Aging, Health, and Longevity: Biodemographic Perspectives.- 12: Stochastic Process Models of Mortality and Aging.- 13: The Latent Class Stochastic Process Model for Evaluation of Hidden Heterogeneity in Longitudinal Data.- 14: How Biodemographic Approaches Can Improve Statistical Power in Genetic Analyses of Longitudinal Data on Aging, Health, and Longevity.- 15: Integrative Mortality Models with Parameters that Have Biological Interpretations.- 16: Integrative Mortality Models for the Study of Aging, Health, and Longevity: Benefits of Combining Data.- 17: Analysis of the Natural History of Dementia Using Longitudinal Grade of Membership Models.- 18: Linear Latent Structure Analysis: Modeling High-Dimensional Survey Data.- 19: Conclusions Regarding Statistical Modeling of Aging, Health, and Longevity.- Part III: Conclusions: Continuing the Search for Determinants of Healthy Life Span and Longevity.

“A key strength of the book is the serious endeavor to go beyond traditional demographic approaches and incorporate more sophisticated mathematical analyses in the quest to integrate models for health, biology, and lifespan. A reasonable job is done of highlighting useful stochastic models for longitudinal data. Another positive is the variety and quality of the data used.” (Anthony Medford, Canadian Studies in Population, Vol. 46, 2019)“The book is an effort to conciliate the empirical evidence that indicates that aging is a multidimensional process that involves changesin many variables, such as biomarkers. Thus, the book contributes at integrating biological knowledge and methods with traditional demographic analyses. Population scientists interested in population and biological mechanisms of aging will find this book valuable since it provides an overview of the most recent developments in the field.” (Vladimir Canudas-Romo and José Manuel Aburto, European Journal of Population, Vol. 33, 2017)