Academic journal article Population

The Effect of Mortality Shocks on the Age-Pattern of Adult Mortality

Academic journal article Population

The Effect of Mortality Shocks on the Age-Pattern of Adult Mortality

Article excerpt

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Environmental conditions affect mortality of populations. Life expectancy can be extended or contracted either by lowering or raising the mortality curve proportionally at all ages, or by changing the slope of the mortality curve, i.e. the rate at which mortality increases with age. Both phenomena may also operate simultaneously. The debate is open as to which of the three mechanisms actually occurs.

To answer this question, a setting typical of natural experiments is needed in order to compare a control group with a case group that is subject to random assignment of the treatment, or, as in case-crossover studies, to analyse the effect of exposure to the treatment for a certain period of time, after which the treatment is withdrawn.

Such experimental conditions are not achievable in studies on human mortality, but abundant research has been performed on laboratory organisms. Several experiments have been conducted to investigate whether the slope of the age trajectory of mortality is affected by abrupt changes in external conditions, such as sudden dietary restriction or exposure to desiccating air flows in the case of Drosophila, but the results are contradictory (Johnson, 1990; Aziz, 1995; Flurkey et al., 2001; Mair et al., 2003; Magwere et al., 2004; De Magalhães et al., 2005). Transposition to human mortality could be operated by focusing on population groups that undergo external shocks and by studying the mortality risk of the survivors after the shock.

The aim of this article is to shed light on how a brusque worsening of the environmental conditions might act on human mortality. To analyse this question, the investigator has to look for documented cases of sudden change in environmental conditions - mortality shocks - that resemble a natural experiment as much as possible. A famous example, though representing a positive shock, is the reunification of Germany in 1990-1991, when the death rates of the East quickly converged with the lower death rates of the West (Vaupel et al., 2003). Other historical events like famines, deportations and internments represent negative mortality shocks. These events are an appropriate analysis tool because the shock is applied to the study population in a nonselective way, thereby reducing the risk of bias due to confounding factors in the evaluation of the shock's effects. Other shocking events, like flu epidemics for example, depending on the specific disease or virus, might affect some specific age groups more than others. The 1918-1919 influenza epidemic, for instance, killed mainly at young ages (Simonsen et al., 1998).

However, even in cases when, at least in principle, the shock is supposed to act on the population unselectively, such events never completely satisfy the conditions required by a natural experiment. Systems of values and social interactions, such as solidarity or competition, could distort the purely biological effect of the shock, modifying the final outcome of mortality increase by age. Unfortunately, the available data can seldom be used to investigate these factors.

Famines are a good example of mortality shock and the literature about them is wide. Depending on the availability of data, they have been more or less extensively analysed. Examples of sadly famous famines are the great Finnish Famine in 1866-1868 (Pitkänen, 1992; Pitkänen and Mielke, 1993), the Dutch Famine in 1944-1945 (Lumey and Van Poppel, 1994), the 1941-1944 Greek Famine (Hionidou, 1995), the Ukrainian Famine in 1932-1933 (Meslé and Vallin, 2003; Meslé and Vallin, 2012), the Irish Potato Famine in 1840 (Guinnane, 2002) and the devastating famine that accompanied the Chinese Great Leap Forward in 1958-1961 which caused around 30 million excess deaths (Ashton, Hill et al., 1984; Peng, 1987; Song, 2009). There are also numerous studies on imprisonment in war camps (Dent et al., 1989; Williams et al., 1993; Costa, 2011) or in cities under siege (Stanner et al. …

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