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Statistical bulletin: Disability-Free Life Expectancy by Upper Tier Local Authority: England 2008-10

Released: 01 May 2014 Download PDF

Key Points

  • Richmond upon Thames had the highest DFLE at birth; for males it was 70.3 years and for females 71.8 years.
  • Liverpool had the lowest DFLE for males at 56.0 years and for females it was Derby at 57.5 years.
  • Men at age 65 in Kensington and Chelsea can expect an additional 7.3 years free from a disability when compared to their inner London neighbour Newham.
  • Males born in Liverpool are expected to live a quarter of their shorter lives with a disability, while Richmond upon Thames males can expect to live only a seventh of their longer lives with a disability.
  • Females live disability-free for more years; whereas males live a larger proportion of their shorter lives disability-free.

Summary

This bulletin presents estimates of Disability-Free Life Expectancy (DFLE) for Upper Tier Local Authorities (UTLAs) in England for the period 2008-10 for both genders at birth and age 65. Equivalent data for the periods 2006-08 and 2007-09 has been published in reference tables and interactive maps alongside this statistical bulletin.

Health expectancies add a quality of life dimension to estimates of longevity by dividing expected lifespan into time spent in given states of health. The Office for National Statistics (ONS) routinely publishes two types of health expectancies; Healthy Life Expectancy (HLE), which estimates lifetime spent in ‘Very good’ or ‘Good’ health based upon self-perceived general health and Disability-Free Life Expectancy (DFLE), which estimates lifetime free from a limiting persistent illness or disability based upon a self-rated functional assessment of health. Both summary measures of population health are key indicators of the well-being of society.

Such data provides information on the geographical distribution of functional health status which can provide evidence for government actions designed to address health inequalities and private sector service provision. This data can be used as evidence for funding health and social care and to inform policy about changes to the state pension age. It also has relevance for private sector pensions and provides the general public with information on how their local area’s health compares with neighbouring areas and with England as a whole.

Background

What are health expectancies?

Life Expectancy (LE) has increased markedly since the eighties, and is expected to increase further in the UK (ONS 2013c), but it is important that the number of years lived without a disabling health condition rises faster or at the same rate. If this is not the case, then these additional years of life are being spent in poor health and greater dependency and will put additional strain on health and social care resources.

It is for this reason health expectancies are being used to assess the proportion of life that is spent in a favourable health state. They are summary measures of population health, which estimate the average number of years a person would live in a given health state if he/she experienced the specified population’s particular age-specific mortality and health status for that time period throughout the rest of his/her life.

The DFLE figures presented represent a snapshot of the mortality and health status of the entire specified population in each time period. They are not, therefore, the number of years that a member of the specified population will actually live in a given health state, because both mortality and health rates are susceptible to change and part of a specified population are likely to migrate and live in other areas.

DFLE estimates are, in part, subjective and based upon the following survey question to determine whether the survey respondent has a limiting persistent illness or disability or not:

  • Do you have any health problems or disabilities that you expect will last for more than a year?

Yes/No

If ‘Yes’ the respondent is then asked

  • Do these health problems or disabilities, when taken singly or together, substantially limit your ability to carry out normal day to day activities? If you are receiving medication or treatment, please consider what the situation would be without the medication or treatment.

Yes/No

Only if a respondent answered ‘Yes’ to both of these questions were they classified as having a limiting persistent illness (disability). In terms of the questions, problems with mobility, dexterity, sight, speech and hearing, physical coordination, memory and the ability to concentrate may limit day to day activities.

The subjective nature of these questions means that responses are influenced by the way individuals perceive their health. Measures of self-rated health, including general health and the more functional assessment of limiting persistent illness, are influenced by an individual’s expectations with clear differences observed across socio-demographic factors such as age, sex, socio-economic position and area deprivation.

Self-reported general health and limiting persistent illness are linked (ONS, 2012, Manor et al., 2001) and have predictive value in health care need/usage and subsequent mortality. Research evidence indicates people with poor self-rated health (both general health and limiting illness) die sooner than those who report their health more favourably (Mossey and Shapiro, 1982; Idler and Benyamini, 1997; Miilunpalo et al., 1997; DeSalvo et al., 2006; Bopp et al., 2012; Ng et al., 2012).

In terms of morbidity the evidence is more limited; studies have shown that self-rated health, measured in terms of general health or limiting illness, has some predictive value in subsequent health and social care service use in the form of increased physician visits (Miilunpalo et al., 1997), hospital admission and nursing home placement (Weinberger et al., 1986). Studies have also shown that poor self-rated health correlates well with retirement due to disability/poor health (Pietilainen et al., 2011; Dwyer and Mitchell, 1999) and poor health outcomes (Lee, 2000).

Survey measurements of general health and limiting persistent illness are used globally to identify health inequality between administrative areas, inform health and social care service needs, indicate unmet care needs, and target and monitor health care resource allocation amongst population groups (Marmot, 2010). International organisations and networks such as the World Health Organisation, Eurostat and the Reves network on health expectancy use this information to compare morbidity across countries and to monitor trends over time.

Quality information about ONS health expectancies is available on the ONS website (185.7 Kb Pdf) .

Regional

For the period 2008-2010 in England, Disability-Free Life Expectancy (DFLE) at birth was 63.6 years for males and 64.8 years for females. To put this into context, a male born in this period could expect to live on average 63.6 years of their expected 78.5 years (or 81.0% of their life) free from disability or a long term illness that limits their day to day activities.

Calculating DFLE at regional level allows differences within England to be assessed. The South East had the longest DFLE for both genders at 66.2 years for males and 67.3 for females. The North East had the shortest DFLE for both sexes at 60.5 years for males and 60.6 years for females. The regional inequality for males was 5.7 years and 6.7 years for females.

For both males and females a clear North-South divide was observed with the Southern regions having higher DFLE’s than the England average and the Northern regions having lower DFLE’s than the England average (Figures 1 and 2).

In all cases, at the regional level and in England, females had longer DFLE than males. Interestingly however, men had a greater proportion of life disability-free in each region. The reason for this is males tend to assess their health more positively than females and therefore have lower rates of self- assessed disability at a given age (ONS 2013d). Females however, have significantly longer LE and are therefore expected to live more years with a disability- but also more years than males free from a disability.

Table 1: DFLE, expected years with a disability, proportion of life with a disability and LE by region for males at birth

Years
Region /Country Name  DFLE  Expected years with a disability  LE  Proportion of life with a disability %
North East 60.5 16.6 77.1 21.5
North West 61.2 15.8 77.0 20.5
Yorkshire and The Humber 61.5 16.2 77.7 20.8
West Midlands 62.2 15.7 77.9 20.1
East Midlands 62.9 15.5 78.3 19.8
London 64.2 14.7 78.8 18.6
East of England 65.2 14.3 79.5 18.0
South West 65.5 13.9 79.4 17.5
South East 66.2 13.5 79.7 16.9
England 63.6 14.9 78.5 19.0

Table source: Office for National Statistics

Table notes:

  1. Regions have been ordered by DFLE.
  2. Figures may not sum due to rounding.

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Table 2: DFLE, expected years with a disability, proportion of life with a disability and LE by region for females at birth

Years
Region /Country Name  DFLE  Expected years with a disability  LE  Proportion of life with a disability %
North East 60.6 20.5 81.1 25.3
North West 62.6 18.5 81.1 22.9
Yorkshire and The Humber 62.9 18.9 81.7 23.1
East Midlands 63.5 18.8 82.3 22.9
West Midlands 63.9 18.3 82.2 22.2
London 65.3 17.9 83.2 20.5
East of England 66.1 17.0 83.2 21.5
South West 67.1 16.3 83.4 19.6
South East 67.3 16.2 83.4 19.4
England 64.8 17.7 82.5 21.5

Table source: Office for National Statistics

Table notes:

  1. Regions have been ordered by DFLE.
  2. Figures may not sum due to rounding.

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Figure 1: Difference in DFLE estimates from the England average by region for males at birth

Figure 1: Difference in DFLE estimates from the England average by region for males at birth
Source: Annual Population Survey (APS) - Office for National Statistics

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Figure 2: Difference in DFLE estimates from the England average by region for females at birth

Figure 2: Difference in DFLE estimates from the England average by region for females at birth
Source: Annual Population Survey (APS) - Office for National Statistics

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The picture at age 65 is similar to that at birth with the Northern and Midland regions having a lower DFLE than the England average of 10.2 years for males and 11.0 years for females. However at age 65 London is also below the England average and it is only the Southern regions that have a higher DFLE. For both men and women the North East had the lowest DFLE at 8.6 and 8.8 years respectively. The region with the highest DFLE for men was the South East at 11.6 years and for women the South West at 12.5 years.

Table 3: DFLE, expected years with a disability, proportion of remaining life with a disability and LE by region for males at age 65

Years
Region /Country Name  DFLE  Expected years with a disability  LE  Proportion of remaining life with a disability %
North East 8.6 8.5 17.1 49.9
Yorkshire and The Humber 9.0 8.6 17.6 49.1
North West 9.2 8.0 17.2 46.4
West Midlands 9.7 8.1 17.9 45.6
East Midlands 10.0 7.9 17.9 44.0
London 10.2 8.2 18.4 44.6
East of England 11.0 7.7 18.6 41.1
South West 11.3 7.4 18.7 39.4
South East 11.6 7.2 18.8 38.5
England 10.2 7.9 18.1 43.4

Table source: Office for National Statistics

Table notes:

  1. Regions have been ordered by DFLE.
  2. Figures may not sum due to rounding.

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Table 4: DFLE, expected years with a disability, proportion of remaining life with a disability and LE by region for females at age 65

Years
Region /Country Name  DFLE  Expected years with a disability  LE  Proportion of remaining life with a disability %
North East 8.8 10.8 19.6 55.2
North West 10.0 9.8 19.8 49.4
Yorkshire and The Humber 10.1 10.2 20.2 50.2
East Midlands 10.6 10.0 20.6 48.7
West Midlands 10.6 10.0 20.6 48.7
East of England 11.6 9.6 21.1 45.2
London 10.8 10.5 21.3 49.4
South East 12.4 9.0 21.4 42.0
South West 12.5 8.9 21.4 41.7
England 11.0 9.7 20.7 46.8

Table source: Office for National Statistics

Table notes:

  1. Regions have been ordered by DFLE.
  2. Figures may not sum due to rounding.

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Local Authority at Birth

At birth

Calculating Disability-Free Life Expectancy (DFLE) at Upper Tier Local Authority (UTLA) level allows a more detailed picture of geographical inequality in health within regions and within England to be examined. For example for males, the UTLA with the longest DFLE was Richmond upon Thames with 70.3 years while the shortest DFLE was found in Liverpool at 56.0 years. Consequently at birth, males living in Richmond upon Thames could expect to live for 14.3 years longer without a disability than males in Liverpool. The inequality can be demonstrated further as males in Richmond upon Thames could expect to live one seventh of their lives (13.5%) with a disability, while males in Liverpool could expect to live a quarter of their lives (25.6%) with a disability.

Table 5: DFLE with rank, proportion of life disability-free with rank and LE by upper tier local authorities for males at birth

Years
UTLA Name DFLE   DFLE Rank Proportion of life disability-free % Rank proportion of life disability-free LE
Top 10             
Richmond upon Thames 70.3 * 1 86.5 6 81.2
Kingston upon Thames 70.2 * 2 86.8 4 80.9
West Berkshire 69.9 * 3 86.8 2 80.5
Kensington and Chelsea 69.9 * 4 85.6 9 81.6
Surrey 69.8 * 5 86.3 7 80.9
Bromley 69.4 * 6 86.6 5 80.2
Oxfordshire 69.4 * 7 86.8 3 79.9
Buckinghamshire 69.4 * 8 86.2 8 80.5
Herefordshire, County of 69.2 * 9 87.5 1 79.1
Wokingham 69.0 * 10 84.9 13 81.3
Bottom 10            
Blackpool 57.6 ** 141 78.1 117 73.8
Blackburn with Darwen 57.4 ** 142 76.2 133 75.4
Knowsley 57.2 ** 143 75.1 141 76.2
Barnsley 57.1 ** 144 74.2 147 77.0
Hartlepool 57.1 ** 145 75.1 142 76.1
Tameside 56.8 ** 146 75.0 143 75.6
Wakefield 56.6 ** 147 73.6 149 76.9
Newham 56.5 ** 148 73.9 148 76.5
Manchester 56.0 ** 149 76.0 135 73.7
Liverpool 56.0 ** 150 74.4 146 75.2

Table source: Office for National Statistics

Table notes:

  1. * Denotes significantly higher than England estimate.
  2. ** Denotes significantly lower than England estimate.
  3. Significance was assigned by a Z-test as detailed in (Jagger 2007 et al).
  4. Figures may not sum due to rounding.

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Table 6: DFLE with rank, proportion of life disability-free with rank and LE by upper tier local authorities for females at birth

Years
UTLA Name DFLE   DFLE Rank Proportion of life disability-free % Rank proportion of life disability-free LE
Top 10             
Richmond upon Thames 71.8 * 1 83.8 3 85.6
Herefordshire, County of 71.1 * 2 85.4 1 83.3
Surrey 70.7 * 3 84.0 2 84.2
West Berkshire 70.5 * 4 83.7 4 84.1
Wokingham 70.3 * 5 83.5 5 84.2
Kingston upon Thames 70.3 * 6 83.5 6 84.2
Bromley 70.2 * 7 83.4 8 84.2
Buckinghamshire 69.8 * 8 83.1 9 84.0
Somerset 69.7 * 9 83.5 7 83.5
Devon 69.6 * 10 83.1 10 83.8
Bottom 10             
Liverpool 58.6 ** 141 73.6 132 79.6
Sunderland 58.5 ** 142 72.6 141 80.6
Newham 58.5 ** 143 71.9 146 81.4
Salford 58.4 ** 144 73.1 137 79.9
Kingston upon Hull, City of 57.8 ** 145 72.1 144 80.2
Barnsley 57.8 ** 146 71.8 147 80.5
Knowsley 57.7 ** 147 72.3 143 79.9
County Durham 57.6 ** 148 71.2 149 81.0
Tameside 57.5 ** 149 71.7 148 80.2
Derby 57.5 ** 150 70.3 150 81.7

Table source: Office for National Statistics

Table notes:

  1. * Denotes significantly higher than England estimate.
  2. ** Denotes significantly lower than England estimate.
  3. Significance was assigned by a Z-test as detailed in (Jagger 2007 et al).
  4. Figures may not sum due to rounding.

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For females the UTLA with the longest DFLE was again Richmond upon Thames at 71.8 years while Derby had the shortest at 57.5 years. Life Expectancy (LE) is also higher in Richmond upon Thames at 85.6 years compared to Derby at 81.7 years. A female born in Derby can expect to live 24.2 years (29.7% of life) with a disability, while a female born in Richmond upon Thames would expect to live 13.9 years (16.2% of life) with a disability or illness that limits their day to day activity.

Maps such as map 1 and 2 provide a clear visual summary of the pattern of DFLE both in England and at regional levels. The concentration of the darker blue colours (representing higher DFLE) in Southern parts of England clearly displays the North-South divide. The maps also show the considerable variation in DFLE between the London boroughs in a relatively small geographical area with all five quintiles of DFLE present.

Map 1: Disability-free life expectancy (DFLE) for males at birth by county and unitary authority in England, 2008-10

The distribution of DFLE estimates for males at birth in 2008-10, showing a north-south divide and large within London variation
Source: Annual Population Survey (APS) - Office for National Statistics

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Map 2: Disability-free life expectancy (DFLE) for females at birth by county and unitary authority in England, 2008-10

The distribution of DFLE estimates for females at birth in 2008-10, showing a north-south divide and large within London variation in rates of DFLE
Source: Annual Population Survey (APS) - Office for National Statistics

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Examining the DFLE for a local authority is useful but more value is added when DFLE is compared with the figure for England, the region to which it belongs and with other local authorities. In tables 5-6 each local authority was given a rank based on their DFLE. Rank 1 was the highest DFLE and rank 150 the lowest. Tables 5 and 6 show the top ten and bottom ten ranked upper tier local authorities, for males and females at birth respectively. Richmond upon Thames, Kingston upon Thames, West Berkshire, Surrey, Bromley and Buckinghamshire all feature in the top ten for both males and females. On the other end of the scale Liverpool, Newham, Barnsley, Tameside and Knowsley all feature in the bottom ten for males and females. Those in the top ten are found in the South of England while those in the bottom ten are found in the North or in deprived, ethnically diverse parts of London.

When comparing each local authority with the England estimate, 40 UTLAs were found to be significantly higher1 than England for males and 41 for females. This means there is more reassurance that they are higher than England as a whole. Conversely, 55 UTLAs were found to have significantly lower DFLE than England for males and 59 UTLAs for females showing they are lower than England as a whole.

Using the DFLE and LE estimates we can draw a line representing the average DFLE we would expect a UTLA to have knowing the life expectancy2,  shown in Figure 3 for males and Figure 4 for females. If a local authority is above the diagonal line then they are doing well in terms of DFLE given their life expectancy. If a local authority is below the line then they are not doing as well as expected.

Figure 3: DFLE vs. LE for upper tier local authorities males at birth

Figure 3: DFLE vs. LE for upper tier local authorities males at birth
Source: Annual Population Survey (APS) - Office for National Statistics

Notes:

  1. The line was derived from a linear least squares regression of DFLE vs. Life Expectancy for all UTLAs. The line serves as a guide to how large we would expect DFLE to be given the size of life expectancy. The further from the line the UTLA is found the more extreme the value.

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Examining Figure 3 showed that Harrow, Westminster, Newham and Wakefield are among the UTLAs which have a shorter DFLE than expected given their LE for males. Whereas Reading, Salford, Richmond upon Thames and the county of Herefordshire were among the UTLAs with the highest DFLEs given their respective life expectancies.

Figure 4: DFLE vs. LE for upper tier local authorities females at birth

Figure 4: DFLE vs. LE for upper tier local authorities females at birth
Source: Annual Population Survey (APS) - Office for National Statistics

Notes:

  1. The line was derived from a linear least squares regression of DFLE vs. Life Expectancy for all UTLAs. The line serves as a guide to how large we would expect DFLE to be given the size of life expectancy. The further from the line the UTLA is found the more extreme the value.

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For females Figure 4 shows that Westminster, Harrow, Brent and Derby were lower in terms of DFLE than anticipated given their life expectancy. Manchester, Wirral, Lewisham and the county of Herefordshire were among the UTLAs with higher DFLEs than expected.

For the majority of local authorities (121 out of 150) DFLE is higher for females than males. The local authority with the largest gender gap favouring females was Havering with women expecting to live for 5.4 more years free from a disability. The local authority where males have the greatest advantage over females in terms of DFLE is Brent with males expected to live 3.7 years longer.

By comparing the expected years with a disability between males and females a more prominent inequality is revealed. In 146 out of the 150 UTLAs females are expected to live longer with a disability. The largest inequality was found in Brent with females expecting to live 8.2 more years with a disability than males. Of the 4 UTLAs where males are expected to live longer with a disability, Havering has the greatest difference at 0.7 years.

Females were also expected to live a greater proportion of life with a disability than males in 145 of 150 local authorities. Females in Brent could expect to live a further 8.8 percentage points of their life with a disability than males. However, in Havering the situation was reversed with males expecting to live a further 1.9 percentage points of their life with a disability than females.

What is driving the difference in DFLE between local authorities? Among other factors area deprivation is likely to play a part (ONS 2010). Area deprivation can be measured using a ranking system known as the Index of Multiple Deprivation (IMD 2010) that takes into account many aspects of deprivation. Using the average summary scores of the authority, the most deprived UTLAs are ranked 1 and least deprived ranked 150. A scatter plot (Figure 5) of the DFLE against the IMD rank, for males, shows a broad pattern of increasing DFLE with decreasing deprivation. The trend is mirrored in the female data and is consistent with what has been found in other analyses (ONS 2013b, ONS 2014) suggesting that area deprivation is an important determinant of health and, if tackled, would have an impact on reducing the inequality in health experienced between areas.

Figure 5: DFLE vs. IMD rank for upper tier local authority at birth for males

Figure 5: DFLE vs. IMD rank for upper tier local authority at birth for males
Source: Annual Population Survey (APS) - Office for National Statistics

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Notes for Local Authority at Birth

  1. See methods section for how statistical significance is assigned.
  2. The line was derived from a linear least squares regression of DFLE vs. Life Expectancy for all UTLAs. The line serves as a guide to how large we would expect DFLE to be given the size of life expectancy. The further from the line the UTLA is found the more extreme the value.

Local Authority at Age 65

The top Upper Tier Local Authority (UTLA) at age 65 for males was Kensington and Chelsea with 14.5 years disability-free while Newham was the lowest at 5.5 years. At age 65 males in Kensington and Chelsea are expected to live for a further 20.6 years; however, only 29.9%, amounting to 6.2 years of those years, will be with a disability. In Newham, Life Expectancy (LE) at age 65 is 16.7 years but males are expected to live 66.9% (11.2 years) of their remaining life with a disability. This inequality between London boroughs means that males in Newham can expect to live 5.0 more years with a disability than males in Kensington and Chelsea despite being expected to live for 4.0 fewer years.

For females West Berkshire had the highest Disability-Free Life Expectancy (DFLE) at 15.1 years while Knowsley had the lowest at 6.6 years. Again, despite Knowsley having a shorter LE than West Berkshire at 18.9 and 21.8 years respectively, females in Knowsley could expect to live 12.2 years (64.8% of life) with a disability, 5.5 years more than West Berkshire where females at age 65 could expect to live with a disability for 6.7 years.

At age 65 three London boroughs (Merton, Kingston upon Thames and Bromley) as well as Surrey and the County of Herefordshire feature in the top ten local authorities for males and females. Sunderland, Kingston upon Hull, Newham and Knowsley all feature in the bottom ten.

Kingston upon Thames, Surrey and Bromley were also in the top ten for both sexes at birth indicating that males and females enjoy relative advantage in terms of disability-free living throughout their lifetime. Knowsley and Newham feature in the bottom ten at birth and age 65 for both the sexes indicating that these areas are more vulnerable to disabling illnesses across all ages. 

Of the 150 UTLAs, 30 were found to be statistically higher than the England DFLE estimate at age 65 for males while 52 were found to be lower. For females 26 were higher while 50 were significantly lower. Similar to the picture at birth the majority of those that are higher than the England average are in the South of the country, while those that have significantly lower DFLE are found in the North of England or deprived and ethnically diverse parts of London.

Table 7: DFLE with rank, proportion of remaining life disability-free with rank and LE by upper tier local authorities for males at age 65

Years
UTLA Name DFLE   DFLE Rank Proportion of remaining life disability-free % Rank proportion of  remaining life disability-free LE
Top 10             
Kensington and Chelsea 14.5 * 1 70.1 4 20.6
Oxfordshire 14.0 * 2 73.9 1 19.0
Merton 13.4 * 3 71.0 3 18.9
Surrey 13.4 * 4 68.7 6 19.5
Herefordshire, County of 13.2 * 5 71.2 2 18.6
Wokingham 13.1 * 6 66.8 13 19.6
Rutland 13.1 * 7 63.9 23 20.5
Kingston upon Thames 13.0 * 8 67.2 12 19.3
Buckinghamshire 13.0 * 9 67.4 11 19.2
Bromley 12.9 * 10 67.9 9 19.0
Bottom 10            
Halton 7.2 ** 141 44.7 128 16.2
Leicester 7.2 ** 142 43.4 137 16.6
Sunderland 7.2 ** 143 43.2 138 16.6
Kingston upon Hull, City of 7.0 ** 144 42.5 140 16.4
Liverpool 6.5 ** 145 40.8 145 15.9
Manchester 6.3 ** 146 41.0 144 15.4
Wakefield 6.3 ** 147 36.7 148 17.1
Hartlepool 6.2 ** 148 38.1 147 16.4
Knowsley 5.7 ** 149 34.9 149 16.4
Newham 5.5 ** 150 33.1 150 16.7

Table source: Office for National Statistics

Table notes:

  1. * Denotes significantly higher than England estimate.
  2. ** Denotes significantly lower than England estimate.
  3. Significance was assigned by a Z-test as detailed in (Jagger 2007 et al).
  4. Figures may not sum due to rounding.

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Table 8: DFLE with rank, proportion of remaining life disability-free with rank and LE by upper tier local authorities for females at age 65

Years
UTLA Name DFLE   DFLE Rank Proportion of remaining life disability-free % Rank proportion of  remaining life disability-free LE
Top 10             
West Berkshire 15.1 * 1 69.3 1 21.8
Bracknell Forest 14.7 * 2 66.3 5 22.2
Surrey 14.7 * 3 67.6 2 21.7
Richmond upon Thames 14.5 * 4 62.6 10 23.2
Devon 14.5 * 5 66.7 3 21.7
Herefordshire, County of 14.3 * 6 66.5 4 21.5
Kingston upon Thames 14.2 * 7 65.5 7 21.7
West Sussex 14.1 * 8 66.2 6 21.3
Bromley 14.1 * 9 64.7 8 21.7
Merton 13.4 * 10 62.6 11 21.5
Bottom 10            
Hounslow 8.1 ** 141 38.2 145 21.1
Sunderland 8.0 ** 142 42.2 133 19.0
Brent 7.8 ** 143 35.4 147 22.0
Slough 7.7 ** 144 37.4 146 20.6
Kingston upon Hull, City of 7.7 ** 145 39.9 141 19.2
Salford 7.5 ** 146 40.4 138 18.6
Tameside 7.4 ** 147 39.2 143 18.8
Newham 7.0 ** 148 35.0 149 20.0
County Durham 6.8 ** 149 35.0 150 19.5
Knowsley 6.6 ** 150 35.2 148 18.9

Table source: Office for National Statistics

Table notes:

  1. * Denotes significantly higher than England estimate.
  2. ** Denotes significantly lower than England estimate.
  3. Significance was assigned by a Z-test as detailed in (Jagger 2007 et al).
  4. Figures may not sum due to rounding.

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Conclusion

In 2008-10 large differences in DFLE existed between local authorities in England at birth and at age 65. At birth there was a large difference between the top and bottom UTLAs for both males and females at 14.3 years. At 65 the difference was 8.5 years for males and 9.0 years for females.

At birth, males living in the top UTLAs could expect to have a disability that affects their day to day activities for a seventh of their lives, but those in the bottom could expect to live a quarter of their lives with a disability. The inequality is highlighted by the fact that males in the UTLA with the lowest DFLE could expect to die 6.0 years before males in the UTLA with the highest DFLE. A similar pattern is seen for females at birth and for both sexes at age 65. Those living in UTLAs with high DFLE are having a better quality of life in terms of functional health as well as having a longer life.

The difference between UTLAs can be linked to the average level of deprivation each area experiences and the analysis shows a strong correlation between health and deprivation. Other more detailed analysis has also highlighted area deprivation as an important determinant of health (ONS 2013b, ONS 2014).

A clear North-South divide was observed at regional and local authority level with those in the South having higher DFLE and living greater proportions of their already longer lives without a disability. Area deprivation is likely to contribute to the North-South divide as there is a higher concentration of deprived areas in the Northern regions (DCLG 2011).

Females tend to have longer DFLE and this is mainly due to the fact that they are expected to live longer but males tend to have a greater proportion of their life disability-free. In the UK males have been closing the gap in terms of LE (ONS 2013c) in recent decades and therefore it will be interesting to see whether they will continue to enjoy the same proportion of life disability-free in future updates, as their life expectancy approaches that of women.

Methods

Calculating Disability-free Life Expectancy

This is the first release of sub-national DFLE using revised mid year population estimates based on the 2011 Census. Reference tables for the aggregate data 2006-08, 2007-09 as well as 2008-10, using revised mid year population estimates, have been published alongside this report.

The data used in calculating the prevalence of disability was obtained from the Annual Population Survey (APS) and aggregated over a three year period to achieve sufficiently large sample sizes to enable meaningful statistical comparison.

The prevalence of disability among males and females resident in private households in England was compared across regions and UTLAs, which include unitary authorities, London boroughs and metropolitan districts in England, but excludes the City of London and Isles of Scilly. DFLE was then calculated using the Sullivan method which combines prevalence data with mortality and mid-year population estimates (MYPE) over the same period and geographical coverage to calculate estimates of LE and DFLE at birth by sex (ONS Life Table Template, Jagger et al, 2007). The MYPEs used to estimate DFLE for this bulletin are the revised backdated estimates based on the 2011 Census.

The APS provides prevalence information for those over the age of 16. We are able to estimate DFLE at birth by directly imputing disability prevalence at age 16 -19 for those under 16 (ONS, 2013a). The age band structure used for calculating DFLE is not that outlined in the update to the methodology to calculate health expectancies (ONS, 2013a) but is the age band structure of <1, 1-4, 5-9, 10-14, 15-19……85+.

Results are presented with 95% confidence intervals in reference tables to aid interpretation. Confidence intervals in this bulletin indicate the uncertainty surrounding DFLE estimates and enable more meaningful comparisons between areas. When comparing the estimates of two areas, non-overlapping confidence intervals are indicative of statistical significance but to confirm this, a test of significance should be carried out. When the statistical significance is noted in the text this is based on a statistical test of the differences (Jagger et al, 2007). All differences noted in the text have been calculated to more than 1 decimal place.

Interpretation of DFLE

DFLE at a given age for a specific period and population, such as at birth among those residing in private households in UTLAs in 2008-10, is an estimate of the average number of years a person would live without a limiting illness (i.e. disability) if he/she experienced the specified population’s age-specific mortality and disability rates for that time period throughout the rest of his/her life.

The figures reflect the mortality and health status of a population in a given time period residing in that area, rather than those born in an area. It is not therefore the number of years that a person will actually expect to live free from disability, because both the death rates and health status of the specified population will change in the future, through changing attitudes to health, provision of treatments, healthcare and migration in and out of the area.

Results are comparable by age, sex and between specified populations as health expectancies take into account differences in the age structures of populations.

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References

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DCLG (2011) The English Indices of Deprivation 2010. Department of Communities and Local Government

DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P (2006) ‘Mortality prediction with a single general self-rated health question. A meta-analysis’ Journal of General Internal Medicine, 21, pp 267–275

Dwyer D S and Mitchell O S (1999) Health problems as determinants of retirement: Are self-rated measures endogenous? Journal of Health Economics. 18. Page 173-193

Eurostat (2013) Healthy Life Years and Life Expectancy at birth, by sex http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/dataset?p_product_code=TSDPH100

Idler EL and Benyamini Y (1997) ‘Self-rated health and mortality: a review of twenty-seven Community studies’ Journal of Health and Social Behaviour, 38, pp 21–37

Jagger C, Cox B, Le Roy S, EHEMU (2007) Health Expectancy Calculation by the Sullivan Method. Third Edition. EHEMU Technical Report

Lee, Y (2000) ‘The predictive value of self assessed general, physical, and mental health on functional decline and mortality in older adults’ Journal of Epidemiology and Community Health, 54, pp 123-129

Manor O, Matthews S and Power C (2001) Self-rated health and limiting longstanding illness: inter-relationships with morbidity in early adulthood. International Journal of Epidemiology. 30 page 600-607

Marmot M (2010) ‘Fair Society, Healthy Lives; The Marmot Review. Strategic review of Health Inequalities in England post–2010’. The Marmot Review

Miilunpalo S, Vuori I, Oja P, Pasanen M and Urponen H (1997) Self-Rated Health Status as a Health Measure: The Predictive Value of Self-Reported Health Status on the Use of Physician Services and on Mortality in the Working-Age Population. Journal of Clinical Epidemiology. Vol. 50 No. 5 pp.517-528.

Mossey J M and Shapiro E (1982) Self-Rates Health: A Predictor of Mortality Among the Elderly. American Journal of Public Health. Vol. 72, No.8, page 800-808

Ng N, Hakimi M, Santosa A, Byass P, Wilopo SA and Wall S (2012) Is self-rated health an independent index for mortality among older people in Indonesia?. PLoS ONE 7(4): e35308. doi:10.1371/journal.pone.0035308

ONS (2010) Inequalities in healthy life expectancy by social class and area type: England 2001-03. Office for National Statistics

ONS (2012) Health Expectancies at Birth and at Age 65 in the United Kingdom, 2008–2010. Office for National Statistics

ONS (2013a) Update to the Methodology used to Calculate Health Expectancies. Health Statistics Quarterly Spring 56:1

ONS (2013b) Inequality in Disability-Free Life Expectancy by Area Deprivation: England, 2003–06 and 2007–10. Office for National Statistics

ONS (2013c) Historic and Projected Mortality Data from the Period and Cohort Life Tables, 2012-based, UK, 1981-2062. Office for National Statistics

ONS (2013d) 2011 Census Analysis, Local Authority Variations in Self-assessed Activity Limitations (Disability) for Males and Females, England and Wales, 2011. Office of National Statistics

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Pietilainen O, Laaksonen M, Rahkonen O and Lahelma E (2011) ‘Self-Rated health as a predictor of Disability Retirement – The contribution of ill-Health and Working Conditions’ PLoS ONE, 6 (9): e25004. doi:  10.1371/journal.pone.0025004

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Weinberger M, Darnell JC, Tierney WM, Martz BL, Hiner SL, Barker J and Neill PJ (1986) ‘Self-rated health as a predictor of hospital admissions and nursing home placement in elderly public housing tenants’ American Journal of Public Health, 76, pp 457–459.

WHO (2011) World Report on Disability. http://www.who.int/disabilities/world_report/2011/report/en/index.html

Background notes

  1. Figures in the text may not sum due to rounding.

  2. The significance test refers to a one tailed Z- test of the difference of the estimates as detailed in (Jagger et al 2007).

  3. In Q1 2010 of the APS the disability module included a new introduction which increased the rates of disability reported by economically active people (216 Kb Excel sheet) . The results from 2010 are robust and can be considered a more complete measure of disability than earlier estimates. The pre 2010 estimates are still considered as the best estimates for those periods. The data in this article is for the aggregate period 2008-2010. The increase in the disability rates from Q1 2010 is likely to reduce the size of DFLE compared with estimates of DFLE produced from the years previous to 2010.

  4. Enquiries relating to these statistics should be made to:

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  5. National Statistics are produced to high professional standards set out in the Code of Practice for Official Statistics. They undergo regular quality assurance reviews to ensure that they meet customer needs. They are produced free from any political interference.

  6. The UK Statistics Authority has designated these statistics as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and signifying compliance with the Code of Practice for Official Statistics.
    Designation can be broadly interpreted to mean that the statistics:

    1. meet identified user needs;

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    Once statistics have been designated as National Statistics it is a statutory requirement that the Code of Practice shall continue to be observed.

  7. Details of the policy governing the release of new data are available by visiting www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html or from the Media Relations Office email: media.relations@ons.gsi.gov.uk

Statistical contacts

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Tim Gibbs +44 (0)1633 456921 Health Analysis, Office for National Statistics hle@ons.gsi.gov.uk
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