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About the data

The data presented in Longer Lives is drawn from data published for the Public Health Outcomes Framework (PHOF).

Where the data comes from

The PHOF sets out the vision for public health and has been developed in a way that supports local communities to identify opportunities to improve health.

The indicators in Longer Lives use records of deaths provided for each year by the Office of National Statistics. The disease considered to be the underlying cause of each death is recorded using the International Classification of Diseases. For more information about each indicator you can download the data and metadata here.

How the rates are calculated

Premature mortality data throughout Longer Lives is based on directly standardised rates. This special measure of mortality makes allowances for the fact that death rates are higher in older populations and adjusts for differences in the age make up of different areas, enabling an accurate comparison.

In the calculation of these directly standardised rates, the European Standard Population is used. This standard population has recently been revised from the version published in 1976 to a new 2013 version. The data presented in Longer Lives uses the 2013 European Standard Population. Further information about the 2013 European Standard Population is available from the Office of National Statistics. The 2013 European Standard Population aims to reflect the current population structure more accurately, including a growing proportion of older adults.

The two local authorities not included in Longer Lives – Isles of Scilly and City of London – have less than 25 observed deaths, which is too few to calculate directly standardised rates reliably. Lung disease and liver disease data for the local authority of Rutland is not included for the same reason. The result is that, for these diseases, the premature mortality rankings are out of 149 and not 150 local authorities.

What the colour key indicates

The maps and local authority data pages use a red, orange, yellow and green colour key to indicate how the individual premature mortality rates in local authorities compare. Comparisons are by disease, with the national average, or with local authorities of similar socioeconomic status. Green denotes rates that are statistically significantly better than the average and red denotes rates that are statistically significantly worse. Yellow denotes rates that are within expected limits but better than average, and orange denotes rates within expected limits but worse than average.

In the key, descriptive labels are attached to the colours as follows:

Similar areas comparison

On the map, selecting ‘socioeconomic deprivation’ will divide local authorities into five groups according to their index of multiple deprivation – an estimate of local affluence or poverty. This is illustrated using five different shades of purple. Local authorities can be ordered by socioeconomic group if required.

On the mortality rank tables, these five socioeconomic groups are described as: ‘least deprived’, ‘less deprived’, ‘average’, ‘more deprived’ or ‘most deprived’. This is the basis of the similar group comparison, by which local authorities are allocated to ten groups (rather than five) according to their index of multiple deprivation, allowing their premature mortality rates to be compared with 14 others that have similar socioeconomic status.

It is important to note that, generally, more deprived areas have worse premature mortality. However, it may be possible to identify local authorities that have better premature mortality than might be expected from their socioeconomic status and investigate whether there is any local learning that could be shared. On the homepage, we have compared local authorities with others in the same socioeconomic group and highlighted those that have the worst premature mortality in each of the five most affluent groups of authorities. We have also highlighted the local authorities that have the best premature mortality in each of the five most deprived groups.