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Percentage of Households with more than one person per room in 2001 for
These figures record, for most years, how many households had less than one room
per person (not counting bathrooms and corridors). How good a measure of
living conditions is this?
The figures for 1931 are for 'families', not households, and the total number of families excludes those with more than five rooms. The figures seem to show a very clear geographical pattern, with the worst conditions concentrated into both urban and rural parts of the north-east of England. However, this pattern may be a result of the way the census measured crowding, by counting numbers of rooms rather than floorspace. To some extent housing in the north-east resembled that in Scotland, with fewer but larger rooms, while in the north-west of England people lived in terraced houses with lots of small rooms. There was also serious over-crowding in inner London: the twenty worst districts include Tower Hamlets, Islington and Southwark.
In 1931, three districts had over half their households living at over one person per room, but by 1951 only one had over a third. The worst districts were still concentrated in the north-east, but slum clearance schemes in some urban areas meant that the rural west midlands now appear as a problem area. In the 1950s and 1960s very active slum clearance programmes, planned construction of 'overspill' estates and new towns, and home-owning middle class families being able to afford better homes all led to great improvements: by 1971, only 6% of households in England and Wales had less than one room per person, compared to 21% in 1931 and 16% in 1951. The concentration of bad conditions in the north-east and London remained, although the north-east then saw remarkable improvement in its relative position during the 1970s.
By 1991, only 2% of households had less than one room per person, and the 2001 census used a new measure of over-crowding. This 'occupancy rating' relates the actual number of rooms to the number of rooms 'required' by the members of the household, based on their relationships and ages. There is some comparability: a household consisting of a husband and wife, a son and a daughter would require five rooms, and we concentrate on households with an 'occupancy rating' of -1 or less. These households were clearly concentrated into the main cities, but the four 'worst' districts were affluent parts of London: the City, Camden, Westminster, and Kensington and Chelsea. As a single person in a bedsit with separate bathroom and kitchen counts as over-crowded, the new standard may simply be too demanding.
The "Statistical atlas" lets you view our British statistical data rates by theme in their entirety as maps for both modern local authorities and historical units.
Please note that although there are some statistics within the system relating to places outside Great Britain, particularly Ireland, the majority of our statistics are British and this is reflected in the presentation of data within the Statistical atlas.
The Statistical atlas presents national views of rates. This differs from the specific numeric data for individual administrative units presented in the "Units & Statistics" part of the place pages accessed via typing in a place-name on the homepage.
Select a theme by clicking on a theme title. You must then decide whether you wish to view data for modern local authorities or historical units. At the top of the theme page are the links to rate maps for modern units. Select one to enter the atlas. Alternatively, at the bottom of the theme page are links to maps of rates only available in their historical units.
After selecting a rate we are presented with the map page showing the selected rate. On the left hand side is the map legend and some generic subject information about the theme. Below the text is a link to the "Rate definition" which takes you out of the statistical atlas and into the description of the nCube for that theme within the data documentation system.
Beneath this are various "Options" for altering the mapped rate. With the exception of the "Political Life" theme, drop down menus exist to change the mapped rate or to select an alternative unit type. All themes have the option to select alternative dates. Selecting a different date will change the map to display re-districted data i.e. statistics which are estimates for the same (modern) geographical area going back over time. More information on how this was achieved is available here.
The map window on the right can be zoomed and panned. Using the drop down menu at the top left of the map window you can select and add a "base layer" map image beneath the transparent statistical map to help you understand the geography of the rates. The window itself can be expanded to see a bigger map using the "Bigger map" option at the top right of the map window. If this function is enabled, the information given on the left will automatically move to below the map.
The statistics come from national overviews, including Censuses, Surveys and other collated tables. You should be aware that the same information was not always collected, the questions change over time to suit contemporary conditions. For example, in the 2011 Census English households were asked about their car ownership, but this would have been of little relevance in 1921 when very few people owned their own vehicle. Conversely, the 1951 question about whether your household had shared access or no access to piped water has disappeared because it is now assumed that all, or virtually all, households will have exclusive use of a piped hot water supply. This is why not all themes have data in all years, the dates available vary according to the questions asked.
We should also point out that we have not digitised all possible historical statistics. Although we have gone a significant way to capturing and integrating suitable tables useful for our themes, this is a labour intensive and time-consuming process. We have tried to focus on particular tables to produce runs of data and in this sense the "Population" theme is the fullest. We continue to work on improving the data, both in its consistency and its accuracy as well as its extent.