Abstract
Over the past two decades, mathematical models of the human reproductive process have been devised to meet a broad range of needs. First, because of the difficulty of performing meaningful experiments in real populations, investigators have turned to models to understand which components of the reproductive process are most important in determining fertility, how these components interact, and what the magnitude of the potential effect of changes in these components might be. Second, in many cases, accurate data on one or a few components are not available, although an investigator might be able to make an informed guess as to the maximum and minimum values feasible. A model, if sufficiently realistic, could then estimate whether, within the range or ranges given, differences in the component could imply substantial differences in fertility. In this way, models have served as aids in deciding the kinds of studies needed and which measurements were crucial to an understanding of fertility in an actual population. Finally, once a model has been devised and validated, it can also provide a means of indirectly estimating either a specified fertility indicator from the components of reproduction, or a component from knowledge of the other variables and fertility itself.
Keywords
- Infant Mortality
- Spontaneous Abortion
- Total Fertility Rate
- Birth Interval
- Spontaneous Abortion Rate
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Menken, J., Bongaarts, J. (1978). Reproductive Models in the Study of Nutrition-Fertility Interrelationships. In: Mosley, W.H. (eds) Nutrition and Human Reproduction. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-0790-7_15
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DOI: https://doi.org/10.1007/978-1-4684-0790-7_15
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