*3.4. Self-Perceived Health*

Having analyzed the indicators related to life opportunities, employment and poverty, we can go on to examine the issue of spatial inequalities via another variable directly related to living conditions: the state of health. Experts in public health have reliably explained how personal inequalities in health are systematic and produced—and reproduced—socially and spatially [74–77]. Once again, the present circumstances associated with the COVID-19 pandemic seem to clearly confirm the relationship between the health status of the population and social cleavages [12,78]. Accordingly, health is not a vector that only affects individuals through particular genetic factors but is in fact closely linked to their living conditions—and these, in their turn, largely depend on social and spatial factors such as working conditions, mobility, housing and environment.

What needs to be unpicked here is whether or not these factors are more decisive when they are analyzed in terms of geographical areas, population size, intensity of urbanization, or residential segregation. Territorial differences in health are usually discussed on the basis of mortality rates and life expectancy, with a view to establishing these factors' relationships with socio-economic and work-related circumstances, as well as material deprivations. We follow a less well-trod path herein by examining the self-perceived health of individuals aged 16 years and over—an indicator that covers subjective experience of not only illness but also sensations like exhaustion [79]. In particular, as mentioned above, we have used the ECVHP data on self-perceived health to establish two categories: one of people who declare their state of health to be very good or good and the rest of the population (i.e., people who, according to their own subjective perception, have a state of health that is middling, bad or very bad).

In this case, the data in Figure 5 show biases that can be partly attributed not so much to spatial factors but more to the age structure of the population resident in each area. Thus, territories that have, on average, a more elderly population than that of Catalonia as a whole—as in the case of Ponent and Alt Pirineu-Aran and Terres de l'Ebre, as well as towns with under 5000 inhabitants and sparsely populated areas—present a poorer state of self-perceived health than the rest. Beyond these extremes, however, the differences between settings—whether classified by geographical area, population size or intensity of urbanization—are not very significant. Neither are the differences between the vulnerable and the well-off settings particularly marked, although the latter, as expected, present a notably better state of self-perceived health.

**Figure 5.** Self-perceived health. Population aged 16 years and over. Catalonia. Source: In-house construction based on the ECVHP, 2011.

It would surely be possible to obtain more conclusive results with other indicators (such as life expectancy and specific diseases) and adjustments to the scales of analysis to avoid biases such as age structure [80,81] but these steps would take us beyond the remit of this study.
