The purpose of this domain is to measure lack of good health.

The indicators are:

• People with a GP-recorded diagnosis of a Chronic condition (indirectly age-sex standardised)
• People with a GP-recorded diagnosis of a Mental health condition (indirectly age-sex standardised)
• Cancer Incidence (indirectly age-sex standardised)
• Limiting Long-Term Illness (indirectly age-sex standardised)
• Premature Death Rate (death of those under the age of 75)

The indicators above are age-sex standardised to adjust for the expected prevalence of disease within the underlying population. This allows the index to identify areas where health deprivations exists beyond the effect of age and sex.

• Children aged 4-5 who are Obese
• Low Birth Weight, single births (live births less than 2.5kg)


To access all the individual spatial layers for the domains (types) of deprivation please click here.

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Please refer to the licence to understand the conditions of using this data.

OWS endpoints
Spatial data download

Metadata download

Maps using this data (2)

Groups using this data (1)

Attributes (9)

Attribute name Label Description
lsoa_code LSOA code Cod 9 nod unigryw ar gyfer yr Ardal Gynnyrch Ehangach Haen Is / A unique 9-character code for the LSOA
lsoa_name_en LSOA name Name of LSOA
lsoa_name_cy Enw’r Ardal Gynnyrch Ehangach Haen Is Enw’r Ardal Gynnyrch Ehangach Haen Is
rank Rank Mae MALlC yn rhoi safle rhwng 1 (y mwyaf difreintiedig) a 1909 (y lleiaf difreintiedig) i’r holl ardaloedd bach. / WIMD ranks all small areas from 1 (most deprived) to 1909 (least deprived).
decile Decile group
quintile Quintile group
map_group Deprivation group

Or display data on an existing map

Spatial data

Characteristics of society and cultures. Examples: settlements, anthropology, archaeology, education, traditional beliefs, manners and customs, demographic data, recreational areas and activities, social impact assessments, crime and justice, census information

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Creation date:
27 November 2019
Open Government Licence for Public Sector Information (OGL)

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features, wimd2019_health
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