Part of understanding people is learning more about their respective habitats, especially as M J Mapp is to successfully impact buildings in and out of London.

As we will understand in the next section perception is not linear, in other words how someone experiences a building in terms of needs and support is not just in terms of their relationship with the building. It is also necessary to understand what their home environment looks like as that can have an affect on how they interact with the building or what they need from a building.


The Built Environment as a Spectrum


Historically research has separated environments into urban and rural, however, Taylor and colleagues (2018) argue that the typical urban-rural dichotomy, based on population numbers and geography, is too simplistic. Instead one should view the environment as a spectrum.

They suggest to categorise environments into five classes:

  • Urban large-city, which includes areas that are characterised by grid-like road networks, high population density, and high land use mix within settlements greater than 100,000 people;

  • Suburban large-city, which include areas that are characterised by irregular, looping and cul-de-sac road networks, lower population density, and low land use mix within settlements greater than 100,000 people;

  • Urban small-town, which include settlement areas with a population between 10,000 and 100,000 people;

  • Rural small-town, which include settlements with a population between 1000 and 10,000; and

  • Rural areas, which are all other areas of our study area, with a population less than 1000, low population density and mostly characterised by agricultural land and natural areas.”

Human behaviour is affected by multiple levels of environmental influences. By combining geographic with intrapersonal (psychological and demographic factors, personal preferences and choices) and interpersonal (social networks, norms, supports, standards, household arrangement, employment status, income, health) information, we are able to gain a much clearer picture and ultimately provide better services. Some key geographical / urban-rural differences observed include:


The Social Market Foundation has found geographical inequalities in education, with damaging effects on life chances. For example, children in the north and Midlands are much less likely to attend a good or outstanding secondary school than their peers in the south. Whilst some of the effects can be mitigated by parental income, research showed that where one lives, plays an equally big role in determining educational achievement. Unsurprisingly geographical differences are also observed in higher education. The 2017 report by the Department for Education acknowledged that there are large differences in the participation rates of young people living in different parts of the country.


The location of a building could play a role in the educational level found within the workforce hosted by the building. This could mean that certain buildings will host people with a lower income bracket, which influence the type of tasks they conduct.


Although employment urban and rural areas have become more similar over time, the 2013 report by the UK Commission for Employment and Skills, has found that several important differences remain. In particular, they found the following for rural areas:

  • The primary sector is more important (whilst in urban area sectors include: financial series, public administration, professional, associate professional and administrative/clerical staff account)

  • More small sized establishments

  • Higher incidence of hard-to-fill vacancies (yet this is linked to types and size of businesses rather than region)

  • Peripheral rural areas face particular challenges in terms of accessibility and transport, which affects the labour pool.

  • More likely to outsource work or withdraw from markets

  • More likely to cite delays in developing new products and services

  • More likely to redefine existing jobs or increase training in response to hard-to-fill vacancies (yet less likely to have a dedicated budget for training).


This information can be used to inform clients at the very start of the built cycle, who are seeking to put buildings outside of London. Especially, in the context of science parks to avoid a narrative of inequality. Currently, Amazon is being judged heavily because of the potential gentrification effects it will potentially have on that area of Queens. Specifically as some people in the population pool of the area may not be qualified for the jobs at offer. In this case advising clients to create training programmes for the local community to mitigate against inequality is advisable to adhere to holistic sustainability practices.


  • In 2001, Griffiths and colleagues published a report to provide a broader view of geographical differences in health. Their work indicated highlighted that there is an increased risk of mortality from heart disease, lung cancer, stroke, infant mortality and stillbirths in areas of deprivation.

  • Figures released by the NHS display key variations in the diagnosis of severe mental illness in England, and Metzler and colleagues (2000) have found that many mental health disorders are strongly associated with deprivation. Additionally, some data revealed that Londoners suffer most from mental illnesses, followed by those in the north west. Some areas in the south of England have much lower rates of mental illness. Yet, interestingly and maybe counterintuitively, research by Weich and colleagues (2005) has shown that place does not affect individuals’ mental health, when examining anxiety and depression. Instead, it is individual-level differences which dominate patterns of variance across these disorders in Britain.

  • Whilst no major geographical variations in healthcare have been observed, there are socio-economic inequalities in healthcare. Cookson and colleagues (2016), found that in England poorer and more socially disadvantaged people are sicker and consume more healthcare (by volume and in terms of cost). In reverse, wealthier and advantaged people instead present themselves to healthcare earlier and consumer more preventative healthcare.  


This type of data can be used a strong indicator and proxy for likely triggers for sick days. In this case the role of M J Mapp could be to advice the occupier of the health vulnerabilities of their workforce in order to promote healthy building practices. In other words, it could be a point to advocate for better ventilation or more natural light etc.

Josh Artus