Litter and crime the most important aspects in making the local area a beautiful place to live
A poll conducted by Ipsos on behalf of ResPublica has found that the public believe less litter and rubbish (36%) and less crime, vandalism and graffiti (35%) are the most important aspects that make their area a beautiful place to live.
They are also the factors the public think most need improving when thinking about making the local area more beautiful, highlighting the important role Local Authorities can play in helping to improve perceptions of the local area.
Three in five (61%) of the public rate their local area as a beautiful place to live although there are some marked variations geographically. Of those living in the South West, 81% rate their local area as a beautiful place to live compared to 52% of those living in the Midlands.
Other key findings include:
- The public overwhelmingly believe that their local area is good in terms of having green and open spaces, with more than four in five rating their local area as good or very good in this regard (81%).
- Three-quarters of the public are satisfied with their family life (75%), and they are more likely to think their local area is a beautiful place to live (67%) than those who are dissatisfied (41%).
- Those who rate their local area as poor in terms of low levels of pollution are considerably less likely to think it is a beautiful place to live (30% vs. 80%).
- Diversity of the population is considered somewhat less important in making the local area more beautiful: close to two in five rate this as one of the least important things (38%).
- Over half (54%) of the public agree that they can access beautiful buildings, places and spaces whenever they want in their local area. Owner-occupiers are more likely than social renters to say they have such access (57% vs. 45%).
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Technical Note
Ipsos interviewed a representative sample of 2,164 adults aged between 16 and 75 across Great Britain (online). Fieldwork was conducted between 19-25 June 2015. Data has been weighted to the known population profile.
