Abstract

Patterns of human mortality share common traits in different populations. They include higher mortality in early childhood, lower mortality during the reproductive period, an accelerated increase of mortality near the end of the reproductive period, and deceleration in the mortality increase at oldest old ages. The deceleration of mortality rate is one of the most intriguing recent findings in longevity research. The role of differential selection in this phenomenon has been well studied. Possible contribution of individual aging in the shape of mortality curve is also recognized. However, this contribution has not been studied in details. In this paper, we specify most common patterns of age-associated changes in an individual organism and discuss their possible influence on morbidity and mortality in population. We subdivide individual age-associated changes into three components, having different influence on morbidity and mortality: (1) basal, (2) ontogenetic, and (3) time-dependent. Basal changes are connected with the universal decrease in the rate of living during an individual life. As a result, some phenotypic effects of aging may accumulate in an organism at a slower rate with age. Basal changes are likely to contribute to a plateau of morbidity often observed at old ages, and may partially be responsible for mortality deceleration at oldest old ages. Ontogenetic component is connected with change of the stages of ontogenesis (e.g., the growth, the reproductive period and the climacteric) during an individual life. The ontogenesis-related changes contribute to wave-like patterns of morbidity in population and may partially be responsible for mortality increase at middle ages and its deceleration at old ages. Time-dependent changes are connected with long-time exposure of an organism to different harmful factors. They are most likely to contribute to morbidity and mortality acceleration. We discuss how all three components of individual age-associated changes may interact in human organism and influence patterns of morbidity and mortality in population.

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