Most users of population projections seem to be primarily interested in the total size of the population. From a substantive point of view, however, it is difficult to think of specific policy or research questions, where only changes in absolute size matter and where it is supposedly irrelevant whether one refers to newborn babies, young adults or frail elderly people. Presumably, the great interest in data on the sheer number of people has two main reasons. First, total population size can be seen as a first-order approximation of the scale of the population-related issues in particular, if it is assumed that the age patterns of the two populations to be compared do not differ greatly. Second, total population size is an important denominator of many frequently used indicators ranging from gross domestic product (GDP) per capita to food consumption per person to greenhouse gas emissions per person. In all those cases a separately derived total quantity is divided by total population size in order to produce an indicator that can be compared across populations.

Particularly in the context of population ageing, the explicit interest in the population's changing age structure has recently increased significantly. While there has always been an interest by planners in the likely future number of school-age children or young adults trying to enter the labour market, the currently dominating questions relate to the sustainability of pension systems under conditions of rapid increase in the number of elderly. Closely related questions deal with the likely impact of ageing on healthcare cost or care for the elderly in general. There is significant concern that an increase in the mean age of the labour force may be associated with decreasing productivity in the future (Skirbekk 2008). These are all questions for which a projection of the population by age is essential. Much of this discussion, however, is based on fixed age categories and does not consider the fact that healthy life-expectancy tends to increase in parallel with total life-expectancy. Hence, a 65-year-old person today is typically quite different from one of the same age who lived several decades ago and who had a much shorter remaining life-expectancy.

Place of residence has always been an important dimension since the very origin of demography when statistical information on households was collected for taxation purposes and conscriptions for the army. Associating people with a specific locality, however, requires that people have a more or less permanent residence and are not permanently on the move. This is one problem facing statisticians when trying to distinguish between urban and rural populations in countries (such as China), where millions of people (the so-called floating population) are constantly on the move between their home villages and the urban centres where they work but have no legal right of residence. Another problem with comparing reported proportions urban across countries and over time is that there is a multitude of changing national sets of definitions based partly on the size of the agglomeration, its statutory status, its population density or the proportion of the labour force that is working in agriculture. Since urbanization will be discussed elsewhere, it will not be covered here.

Like the other dimensions discussed above, education is also an important source of population heterogeneity and bears a significant weight of its own. Almost universally more educated people have lower mortality and there is sufficient evidence that this is a real effect and not just owing to selectivity. Also for all populations that are still in the process of demographic transition, more educated women have lower fertility. These educational differentials can be very significant. 

There are several other dimensions of population that are considered relevant either in their own right or as further important sources of heterogeneity. The parity distribution of the female population, i.e. the distribution of women by the number of children they have already given birth to, is an important determinant of fertility in the near-term future. Highly important for economic and labour force consideration is the distribution of the population by age, sex and labour force participation rates. While there are several national projections of future labour force participation, consistent global projections do not yet exist. Another very relevant dimension in the context of global population ageing and the associated needs for care for the elderly is the projection of the population by health status.