Two paradoxical hypotheses – (i) that countries with low population growth rates or a decline in population growth rate will have high elderly dependency ratios leading to high elderly suicide rates, and (ii) that countries with high population growth rates will have high elderly suicide rates because of Durkheim's hypothesis that the overall cohort size may influence suicide rates due to competition for scarce resources – were supported by a recent study (Shah, Reference Shah2008). The relationship between average annual population growth rates and elderly suicide rates was shown to be curvilinear (U-shaped curve) fitting the quadratic equation y = a + bx + cx 2 (where y is the elderly suicide rate, x is the average annual population growth rate and a, b and c are constants) using an ecological study design.
Population growth rate is a function of life expectancy and birth rate. Thus, in countries with low average annual population growth rates or decline in average annual population growth rates, elderly dependency ratios may be high because of increased life expectancy and low birth rate. This, in turn, may result in increased elderly suicide rates. The average annual growth rate may begin to increase in some countries due to an increase in birth rates. This, in turn, may lead to a decline in the elderly dependency ratios. Moreover, in turn, this may result in a decline in elderly suicide rates. As the average annual population growth rate continues to increase, at a critical point the composite influence of increased life expectancy, increased elderly population size and the increase in the proportion of elderly in the general population on elderly suicide rates may become more prominent. This may, in part, reflect Durkheim's hypothesis that the overall cohort size may influence suicide rates due to competition for scarce resources (Shah and De, Reference Shah and De1998).
The same curvilinear (U-shaped curve) relationship between elderly suicide rates and the average annual predicted future population growth rate was examined. Data on elderly suicide rates for males and females in the age-bands 65–74 years and 75+ years for each listed country were ascertained from the World Health Organization (WHO) website (www.who.int/whosis/mort/table1.cfm). The median (range) of the latest available year for data on elderly suicide rates was 2000 (1985–2003). Data on the average annual predicted future population growth rate until 2015 for each listed country were ascertained from the United Nations Development Programme (UNDP) website (www.hdr.undp.org/reports/global/2005/pdf/hdr05_HDI.pdf). Curve estimation regression models were used to examine the curvilnear relationship between elderly suicide rates and the average annual predicted population population growth fitting the quadratic equation y = a + bx + cx 2.
Full data sets for elderly suicide rates and the average annual predicted future population growth were available for 80 countries. Table S1 (available online at www.journals.cambridge.org/jid_IPG as supplementary material to the electronic version of this letter) illustrates the curve estimation regression models, whereby the relationships between suicide rates in both sexes in both elderly age-bands and the average annual predicted future population growth rates were curvilinear (U-shaped curve) and fitted the quadratic equation y = a + bx + cx 2; the significance level was at least at the 0.05 level.
How can the average annual predicted future population growth rates predict current suicide rates given that this population growth has not yet occurred? It is possible that this observed relationship was purely due to chance. Also, the average annual predicted future population growth rate may be a proxy measure for other correlates of elderly suicides or other variables may predict both elderly suicide rates and the average annual predicted future population growth rates (epiphenomena). The findings of this brief study illustrate that considerable caution and care are required in interpreting findings from cross-sectional ecological studies exploring potential etiological relationships.
