by Giulia Melis
SiTI, Politecnico di Torino, Italy
Since ancient times, we have known that the place where we live can impact our health. Cities have always been shaped and restructured according to the needs and priorities of the time. The Roman Empire, for instance, created a model for the planned city: with its rigid morphologic and geometric rules, the typical Roman settlement provided basic facilities and infrastructure for its inhabitants, ranging from thermal baths, to aqueducts and sewers. During the Industrial Revolution, cities had to face a new challenge: overcrowding, industrial dumps, and bad hygiene conditions were helping the spread of infectious diseases, and working class suburbs were growing too fast, without any concern about the quality of life in those areas.
That’s how laws about urban décor, cleanliness and sanitation started to be discussed: the Public Health Act (UK, 1948) is one of the first examples. This Act linked the urban design of a city with the spreading of epidemic diseases, and tried to prevent it by moving industrial production out of the city core. This model lasted until recent decades, when deindustrialization and various crises meant the need for new paradigms.
Nowadays, modern cities are starting to wonder not only how to create a healthy environment to protect the spread of epidemics, diseases, violence etc., but also how to enhance the quality of life of their citizens and their wellbeing. The waves of New Urbanism are questioning our lifestyles, and starting to re-consider the social component of city life as fundamental for granting us happiness and fulfilment.
That’s why, as a group of researchers coming from the architectural and medical domain, we became interested in mental health in our cities. As urban planners, we were interested in understanding which urban features most significantly affect our daily life, in order to identify the most urgent and promising intervention opportunities towards less-stressful urban living. And as public health experts, we wanted to know if the effects are equally distributed among the population, or whether some groups are experiencing a higher burden?
We chose an Italian city, Torino, where a huge dataset on population health is available, and looked to see if the numbers confirmed our initial theory. While a lot of researchers have already presented evidence of the importance of urban trees and parks, which can have a profoundly beneficial impact on psychological wellbeing and general mental health, not many studies have analysed the urban built environment in its complex functioning. We therefore gathered data both on the structure of the city (how dense it is, where are the parks for recreational activities, which is the mix of functions in one area) and its services (is the nearest library placed within an accessible distance? is the area well-served by public transport? Are there public sport facilities? Cinemas, theatres? etc) and we looked for connections between this data and the consumption of antidepressant drugs in the city.
This scheme illustrates the variables considered in the study as plausibly connected to mental health in urban areas.
Our research suggests that good accessibility to public transport, as well as a dense urban structure (versus sprawl), could contribute to a reduced risk of depression, especially for women and elderly, by increasing opportunities to move around and enjoy an active social life.
Women (of all ages) and older people (age 50 to 64) were found to be prescribed fewer antidepressant drugs when they lived in places reached more quickly by bus or train, and in places with taller average building heights, compared with counterparts in more remote or sparse areas. That connection held up even when social factors were taken into account. This means that if everybody had the same level of education, same citizenship, and were all in employment, all living in a neighbourhood that had equivalent levels of crimes and social and physical disorder, there would still be differences in antidepressant consumption according to how well the area is served by public transport and to the density and liveliness of the neighbourhood.
Challenges and decisions with the method
Antidepressant consumption is quite a strong indicator in mental health. Taking antidepressants implies that you have recognised you have a problem, actively sought help from a doctor, received a diagnosis and a prescription for antidepressant medication, and started treatment. This is a long way from starting to feel that you may be stressed or depressed. We used this indicator in our research as we were looking for solid evidence, but by doing so, it is likely that our results underestimate the phenomenon of stress and depression in the city, thus setting the stage for further and more accurate investigations and reflections.
Of course the range of density that we were able to test was limited to that of a typical European city; this range does not include the extremes of US cities sprawl and high density (which are both known to have negative effects on health).
Also, this type of large-scale data analysis can’t pinpoint causal mechanisms. But it’s not hard to speculate why transit and density might reduce stress: the former relieves the need to drive everywhere (and to own a car); the latter enhances the potential for social connectivity. For older populations, in particular, both aspects help guard against feelings of isolation or loneliness. They also stand in contrast to remote suburban living that “can have a serious impact on mental health, particularly when it results in forgone trips”.
Transit provides key connectivity, linked to urban mental health.
Photo from Inquisitr
There’s still a lot to understand about the key stressors of city life, but sound advice to urban planners could already be launched: in order to address health inequalities, urban policies should invest in the delivery of services that enhance resilience factors, above all a good public transport network, in a careful and equal manner, throughout the city.
Sanity and Urbanity: