Robert D. Hoppa - Böcker

Studies of dental and skeletal growth and development have often been treated as independent disciplines within the literature. Human Growth in the Past, first published in 1999, brings together these two related fields of enquiry in a single volume whose purpose is to place methodological issues of growth and development in past populations within a strong theoretical framework. Contributions examine a variety of aspects of human growth in the past, drawing from both palaeoanthropological and bioarchaeological data. The book covers a wide spectrum of topics, from patterns of growth in humans and their close relatives, innovative methods and applications of techniques and models for the study of growth, to estimation of age-at-death in subadults and infant mortality in archaeological samples. Human Growth in the Past will be of interest to biological anthropologists, and those in the related fields of dental anatomy, evolutionary biology and developmental biology.

Paleodemography is the field of enquiry that attempts to identify demographic parameters from past populations (usually skeletal samples) derived from archaeological contexts, and then to make interpretations regarding the health and well-being of those populations. However, paleodemographic theory relies on several assumptions that cannot easily be validated by the researcher, and if incorrect, can lead to large errors or biases. In this book, physical anthropologists, mathematical demographers and statisticians tackle these methodological issues for reconstructing demographic structure for skeletal samples. Topics discussed include how skeletal morphology is linked to chronological age, assessment of age from the skeleton, demographic models of mortality and their interpretation, and biostatistical approaches to age structure estimation from archaeological samples. This work will be of immense importance to anyone interested in paleodemography, including biological and physical anthropologists, demographers, geographers, evolutionary biologists and statisticians.