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4.2  Region

Age structures vary across geographical areas, in line with variations in ethnicity, job prospects, desirability as a retirement destination, and so forth (Lepina 2000, Stephenson 2002). Figure 11 shows some illustrative data, based on the areas served by District Health Boards. Note that these areas differ not only in levels of population ageing but also in rates of change. Between 1991 and 2001, for instance, the proportion of the Wairarapa population aged 65 and over increased by 3.1 percentage points, while in Auckland it decreased by 2.4 percentage points (due, presumably, to migration). These data illustrate the importance of local priority-setting and of funding formulas that take into account differences in age structure.

Figure 11 – Percent of population aged 65 and over, by District Health Board, 1991 and 2001
Percent of population aged 65 and over, by District Health Board, 1991 and 2001
Source: 1991 and 2001 Census data, obtained from the Statistics New Zealand website in July 2003.

4.3  Narrow age groups

Broad changes to the overall shape of the age distribution such as population ageing, or the movement of the baby boom cohorts through the age distribution, are slow and systematic. These gradual transformations can, however, occur simultaneously with rapid, erratic changes within narrowly-defined age groups (Pool 2001). Figure 12, for example, shows historical and projected growth rates for the age groups 65-69 and 80-84. These growth rates vary enormously from one five-year period to the next: between the periods 1956-1961 and 1961-1966, for instance, the growth rate for the 80-84 age group fell from 4.8% per annum to 1.5%. These “disordered cohort flows” arise when sudden or mutually reinforcing changes in birth rates, death rates, or migration rates result in one cohort being substantially bigger or smaller than its predecessors (Pool 2001, Preston et al 2001: 180-4).

Figure 12 – Annual growth rates for the age groups 65-69 and 80-84
Annual growth rates for the age groups 65-69 and 80-84

The extent to which aggregate levels of a particular variable are affected by disordered cohort flows depends on the age profile of the variable. If age-specific rates for the variable are markedly different in the age groups experiencing the disordered cohort flows than they are in other age groups, then the effect of the disordered cohort flows is particularly large. The classic example is schooling. Enrolment rates for primary school, for instance, are high in the age group 5-9 and low elsewhere: a sharp increase in the size of the 5-9 age group therefore implies a sharp increase in the number of primary school students. Similarly, if admittance to rest homes becomes increasingly concentrated in the oldest age groups, then sudden changes in the size of these age groups could create large gaps between capacity and demand.

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