Index of Health & Well-Being Assets North West Development Agency November 2010
Index of Health & WellBeing Assets North West Development Agency November 2010 Contents ______________________________________________________________________ Introduction ...................................................................................................................1 1 1.1 1.2 1.3
Methodology........................................................................................................ 2 Selection of variables ............................................................................................ 2 Correlation analysis and weighting........................................................................ 3 Testing the Index................................................................................................... 4
2 2.1 2.2 2.3
Outputs ................................................................................................................ 6 An overview of well-being in the North West ......................................................... 6 An overview of Community well-being in the North West ...................................... 7 A detailed view of local areas – Allerdale and Bury............................................... 9
Appendix A: About us ______________________________________________________________________ This output is based on and comprises both your input and information sourced from third parties (which may include public data sources). Whilst we will use all reasonable care and skill in the collection and collation of this output we cannot warrant or guarantee the accuracy of the output. You acknowledge that outputs which use empirical data and/or statistical data and/or data modelling techniques cannot be taken as a guarantee of any particular outcome and are not intended to be the sole basis of your business decisions. Our standard terms of business apply.
Approved by: Sachin Dodhia Position: Research & Analytics Lead Date: 17th November 2010
Index of Health and Well-being Assets
Introduction There has been much understanding in recent years that the tools we use to measure the health and well-being of communities are not sufficient. Indeed as their main focus is on deficits, such as the Index of Multiple Deprivation (IMD), we risk putting out negative messages and reinforcing entrenched behaviours. This piece of work is intended to address this by providing a pathway to the creation of a positive index on the health and well-being of communities. For some time momentum has been building in the Department of Health Northwest, the Northwest Development Agency (NWDA), Government Office Northwest and HM Treasury into the possibility of creating an Index of Health and Well-being Assets. A desire has been articulated for an asset model for health and well-being which takes into account areas within which people have higher levels of well-being, have the capacity to recognise their illness better, access services easier, recover sooner, have resilient social networks, cohesive relationships and higher levels of mental well-being. It has been identified that what is required, in contrast to such tools as the IMD, is a complete asset model based on up-to-date and readily available indicators which can be used to inform why there are high levels of well-being only in certain areas, and which assets these areas have that contribute to well-being and vice versa. Developing such an index is a difficult task as benefit models are intrinsically harder to construct given that they tend to be focussed on softer measures which can only be modelled attitudinally, which can involve large scale market research and be costly. Consultation between Experian and the NWDA identified the need to scope out the viability of such an index. As well as achieving the aforementioned aims, it was noted as important that this index should contribute towards the ‘vision’ of the region – sustainable economic growth & reduced inequalities. The index would be more valuable if it could be aligned to specific policy interventions. In terms of specifics, it was agreed that the index should: be comparable with other areas in the UK cover the most detailed geographic levels possible be updateable on an annual basis
This document sets out the methodology used by Experian to develop this index. The following section outlines the methods applied, explaining the variables used as well as weightings and correlation with existing measures of well-being. Thereafter, headline rankings are detailed and Community resilience is explored by way of example.
© Experian Plc 2010
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Methodology
Well-being is an important element of local resilience. Experian’s wider resilience work focuses upon four key themes: Business, Community, People and Place. Considering resilience and well-being within this theoretical framework is particularly useful for understanding which factors in particular contribute to local prosperity and protect local areas from the impacts of economic shocks. This is because each theme can also be considered separately allowing for an additional level of well-being analysis. The business theme is particularly focussed on the economic resilience of local areas. For this reason, it is not considered as part of our analysis of well-being. Well-being is analysed within the framework of the three other broad themes – Community, People and Place. Throughout this research, we have applied this theoretical framework to our index. Figure 1.1: Experian’s theoretical approach to resilience (left) and well-being (right)
1.1
Selection of variables
In consultation with the NWDA a number of potential variables were identified for use in this study. As such the first stage thereafter was to consolidate these discussions and form two distinct variable sets. The first (option 1) uses only publically available datasets. The second (option 2) includes all of those variables used in option 1 as well as unique Experian pH Group, Experian Mosaic Economics and Experian UKCCD variables. The variables identified for use are detailed in the lists below. Each variable has been allocated to at least one of three key themes of well-being. Some variables have been included under more than one theme. This is to allow these three themes to be considered separately, and reflects the importance of the variable to each theme. For example, worklessness is an important factor when examining the wellbeing of both the ‘community’ and ‘people’. Appropriate weights have later been applied to avoid over representing these variables. The weighting process is detailed later on in this report. The variables included in option 1 have been chosen to reflect key factors of well-being identified through consultation with the NWDA and as part of Experian’s ongoing resilience and well-being research. These factors included such things as: coping financially, employability, worklessness, crime levels etc. For each of these factors a small number of variables are assigned. In total there are nineteen variables included in the index. © Experian Plc 2010
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Figure 1.2: Nineteen variables used for the well-being index (option 1): Community
People
Place
Well being factor Coping financially Employability Employability Employability Worklessness Worklessness Physical Space Place and Community Place and Community Place and Community Physical Space Crime Housing need/condition Environment Local Ownership Population Churn Population Churn Physical Exercise Healthy Eating
Variables Mean FT earnings – workplace based Number and % working age residents NVQ4+ Economic activity of all persons in working age % elementary occupations % working age residents with no quals Total claimants rateable value by class per sqm (£) business spaces % wards amongst 10% most deprived (IMD) Life expectancy at birth M Life expectancy at birth F % green space Crime rates Average property price Carbon emissions per capita VAT registrations per 10,000 adults % workforce self employed Working Age Population Meeting physical activity recommendations Consumption of 5 fruit and veg a day
Source Annual Survey of Hours and Earnings Annual Population Survey Annual Population Survey Annual Population Survey Annual Population Survey Department of Work and Pensions Communities and Local Government Index of Multiple Deprivation 2007 ONS ONS Communities and Local Government Police Land Registry DECC ONS Annual Population Survey Annual Population Survey Active People's Survey Health Survey for England
In addition to the variables outlined above, Experian have identified a number of additional factors and variables that are worthy of consideration. These additional variables would bring the total number to twenty-nine. The inclusion of these variables would allow for a number of other factors important to well-being to be quantified. These factors include cost of living, health services, commuting, marital status, length of residency and social cohesion. The inclusion of these variables (below) would also mean that the index would be enhanced by building upon publically available local authority level data with a significant amount of household and person level data. Experian are able to tie the index and the underlying variables to individual households, using our bespoke segmentation system, Mosaic Public Sector. This will ensure that the index can be used operationally as well as strategically. Figure 1.3: Additional propriety datasets suggested (option 2): Community
People
Place
1.2
Well being factor Cost of living Cost of living Cost of living Worklessness Health Services Local Ownership Commuting Marital Status Length of Residency Social Cohesion
Variables Estimated disposable income Council tax band % vulnerable to declines in disposable income % vulnerable to long term unemployment Number of primary care organisations Foreign Owned businesses Travel to work time Marital Status Length of residency Social Cohesion - do neighbours look out for each other?
Source UKCCD UKCCD Experian Mosaic Economics Experian Mosaic Economics UKCCD Experian pH data Build suggestions/ Experian UKCCD UKCCD Experian Mosaic
Correlation analysis and weighting
An essential part of developing an index is ensuring that appropriate weightings are assigned to all of the constituent variables. Some variables, whilst seemingly distinct from others, are closely correlated. For example, the level of deprivation in any given area is highly correlated with the number of people claiming benefits. As such these variables need to be weighted to reflect this correlation. Failure to do this would mean that the index favours certain variables over others. Seven variables were found to have strong correlations with other variables included in the index. These have been weighted down accordingly to ensure accuracy. 1 The final weightings applied to each of the variable are shown below.
1
If correlation was found between one variable and four others, it was weighted down by 2%. If correlation was found between one variable and between three and four others, it was weighted down by 1%. If correlation was found between one variable two or fewer others, it was weighted down by 0.5%.
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Figure 1.4: Applied weightings Variables
Weightings 6.1% 4.6% 6.1% 6.1% 5.1% 6.1% 6.1% 5.1% 2.3% 2.3% 6.1% 6.1% 3.6% 6.1% 6.1% 6.1% 6.1% 3.6% 6.1%
Mean FT earnings – workplace based Number and % working age residents NVQ4+ Economic activity of all persons in working age % elementary occupations % working age residents with no quals Total claimants rateable value by class per sqm (£) business spaces % wards amongst 10% most deprived (IMD) Life expectancy at birth M Life expectancy at birth F % green space Crime rates Average property price Carbon emissions per capita VAT registrations per 10,000 adults % workforce self employed Working Age Population Meeting physical activity recommendations Consumption of 5 fruit and veg a day
1.3
Testing the Index
In order to confirm the consistency of approach with that of existing well-being indices, we compared the results of our index with those of the Local Index of Child Well-Being (CWB), compiled by CLG. A precise correlation could not be expected, given that the CWB measures well-being in children and due to the fact that our index is based on a wider number of variables. 2 Between the two indices there was a high correlation with an overall R² value of 0.76. There were a few outliers, which result mainly from the differing variables used by the two indices. This correlation confirms that our approach is consistent with existing methodologies. Figure 1.4: Correlation with the Local Index of Child Well-Being 2009 40
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Child Welfare Index ranking
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25 y = 0.8753x + 2.4939 R² = 0.7662 20
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Experian Index of Well being ranking
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It should be noted that our methodology also uses up-to-date local authority district boundaries whereas the CWI was based on pre-2009 boundaries.
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We also tested the index against the Warwick Edinburgh Mental Wellbeing Scale. 3 Between the two indices there was a small correlation with an overall R² value of 0.127. However, due to the distributions not being normal, it is not possible to perform statistical tests on this data to infer which areas had significantly higher or lower scores than others. 4 Figure 1.5: Correlation with the Warwick Edinburgh Mental Wellbeing Scale 34% y = 0.0423x + 0.2533 R² = 0.127 32%
WEMWBS Mean
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Experian Index of Wellbeing
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It should be noted that due to differing boundaries this analysis was based on only 21 geographies. For more information please refer to the North West Mental Well Being Survey, 2009
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Outputs
2.1
An overview of well-being in the North West
Our index considers the thirty-nine local authority districts in the North West. 5 By weighting the nineteen variables as detailed in the previous section, headline well-being rankings have been produced. These are detailed in Figure 2.1 (below). Ribble Valley has the highest well-being ranking. This position is underpinned by high scores across a number of variables. Notably the local authority has a highly qualified working age population and the lowest concentration of working age residents with no qualifications in the North West. It also has no pockets of deprivation, a very low claimant count rate and the lowest crime rate in the North West and a Blackpool has the lowest well-being ranking. This is due to the area having low average earnings and high crime rates. In addition, Blackpool suffers from a high proportion of workers with no qualifications and a high claimant count rate compared to the regional average. Figure 2.1: Headline well-being rankings
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Headline Rankings Rank Ribble Valley Eden South Lakeland Trafford Cheshire East Lancaster Warrington Cheshire West & Chester Stockport Copeland South Ribble Fylde Chorley Wyre West Lancashire Allerdale Bury Preston Barrow-in-Furness Sefton
21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
Wigan Rossendale Wirral Tameside Carlisle St. Helens Bolton Hyndburn Halton Salford Oldham Rochdale Manchester Blackburn with Darwen Pendle Liverpool Burnley Knowsley Blackpool
5
LADs have been used for this analysis due to the ready availability of comparable indicators at this geographic level. However, these geographies often do not reflect functional economic geographies. This is particularly evident around major cities. The City of Manchester, for example, spans across a number of LADs not only Manchester LAD. As such, this research can be conducted at other geographic levels to better reflect functional geographies – for example Primary Urban Areas (PUAs) which better reflect cities and are compiled from a number of LADs.. This research could be undertaken at any geographic level where the data is readily available and comparable.
Š Experian Plc 2010
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Index of Health and Well-being Assets
2.2
An overview of Community well-being in the North West
Drawing upon our theoretical approach to well-being, in addition to headline ranking we are able to investigate well-being by the three themes outlined in the previous section. By way of an example, this sub-section outlines community well-being. Figure 2.2: Experian’s theoretical approach to well-being
Using shares reflective of the weightings applied to the nineteen variables, as detailed in the previous section, the eight constituent variables of community well-being have been assigned weightings. 6 Figure 2.3: Experian’s theoretical approach to well-being Variables Mean FT earnings – workplace based Number and % working age residents NVQ4+ Economic activity of all persons in working age % elementary occupations % working age residents with no quals Total claimants rateable value by class per sqm (£) business spaces % wards amongst 10% most deprived (IMD) Life expectancy at birth M Life expectancy at birth F % green space Crime rates Average property price Carbon emissions per capita VAT registrations per 10,000 adults % workforce self employed Working Age Population Meeting physical activity recommendations Consumption of 5 fruit and veg a day
Community
Weightings 0.0% 0.0% 0.0% 15.7% 12.9% 15.7% 0.0% 12.9% 5.8% 5.8% 0.0% 0.0% 0.0% 0.0% 15.7% 15.7% 0.0% 0.0% 0.0%
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Please note that these weightings have been assigned for the purposes of demonstration. The construction of the full model would see the application of a different weighting process which reflected the fact that some variables span a number of themes. © Experian Plc 2010
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Analysing community rankings it is clear that a number of local areas, which perform well over all, have comparatively lower community resilience ranks. A number of LADs in the top ten according to the overall well-being index, namely Cheshire East, Lancaster, Warrington, Cheshire West and Chester and Stockport, perform worse for community well-being. Figure 2.4: Community Well-being rankings
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Community Rankings Rank Ribble Valley Eden Wyre South Lakeland South Ribble Fylde Allerdale Copeland Trafford Chorley Lancaster West Lancashire Cheshire East Stockport Barrow-in-Furness Carlisle Cheshire West & Chester Preston Warrington Rossendale
21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
Bury Wigan Hyndburn Wirral Tameside Sefton St. Helens Bolton Pendle Blackburn with Darwen Salford Halton Oldham Burnley Liverpool Rochdale Knowsley Blackpool Manchester
Identifying these differences outline the advantages of the theoretical approach taken. By using this approach, it is possible to gain a more detailed understanding of the strengths and weaknesses of local areas with regard to well-being. This is important as, different LADs within the North West will have different strengths and weaknesses and therefore require different policy actions. The use of the theoretical framework helps to quickly identify which key variables are most important to analyse for particular localities
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2.3
A detailed view of local areas – Allerdale and Bury
Detailed analysis of two local authorities further supports the need to use the index as a framework to explore well-being in greater detail. Allerdale and Bury have a similar well-being ranking, coming 16th and 17th respectively in terms of overall well-being. However, with regard to Community well-being, the two areas differ greatly. Whilst Allerdale performs relatively strongly by this measure (7/39), Bury performs significantly worse (21/39). Looking further into the data it is obvious that such differences are a result of the fact that despite the well-being rankings of the two areas being very similar, there are a number of fundamental differences between these two areas. Some significant differences are:
Qualification levels are notably much higher in Bury than in Allerdale. 26.5% of the population in Bury are qualified to NVQ level 4 and above compared to 16.9% in Allerdale.
The claimant count rate is much higher in Bury (3.6%) than in Allerdale (2.9%).
The occupational profile of the two places is also different with a far higher proportion of people in Bury working in elementary occupation roles (10.4% compared to 5.0%).
Office space is much more valuable in Bury (£80 per m²) that in Allerdale (£44 per m²).
Property prices are much higher in Allerdale than in Bury (£162,613 compared to £136,664).
Ultimately, policy intervention to improve well-being in these areas would need to be specific to the needs of these different areas. Whilst Bury enjoys a highly qualified workforce by regional standards, perhaps intervention would focus upon further up skilling - to tackle the high concentration of workers in elementary occupations and the high claimant rate. This type of intervention would not be appropriate for Allerdale.
© Experian Plc 2010
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Appendix A About us
Experian Experian is a global leader in providing information, analytical and marketing services to organisations and consumers to help manage the risk and reward of commercial and financial decisions. Combining its unique information tools and deep understanding of individuals, markets and economies, Experian partners with organisations around the world to establish and strengthen customer relationships and provide their businesses with competitive advantage. For consumers, Experian delivers critical information that enables them to make financial and purchasing decisions with greater control and confidence. Clients include organisations from financial services, retail and catalogue, telecommunications, utilities, media, insurance, automotive, leisure, e-commerce, manufacturing, property and government sectors. Experian Group Limited is listed on the London Stock Exchange (EXPN) and is a constituent of the FTSE 100 index. It has corporate headquarters in Dublin, Ireland, and operational headquarters in Costa Mesa, California and Nottingham, UK. Experian employs around 15,500 people in 36 countries worldwide, supporting clients in more than 65 countries. Annual sales are in excess of $3.8 billion (ÂŁ1.9 billion/â‚Ź2.8 billion). For more information, visit the Group's website on www.experiangroup.com The word 'Experian' is a registered trademark in the EU and other countries and is owned by Experian Ltd and/or its associated companies.
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