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This article discusses the growing interest in the effects of social class on health and education outcomes. It explores the use of deprivation indices to measure these effects and highlights the advantages of using a composite deprivation index. The article also explains the conceptual basis of the Pobal HP Deprivation Index and its application in resource allocation models.
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Dublin, August 2017 The 2016 Pobal HP Deprivation Index for Small Areas (SA)Conceptual Basis
A New Interest in Health and Education inequalities There is a growing interest in the effects of social class on key outcomes in relation to health and education Social gradients in these arenas are important from an equality perspective and must be taken into account when planning services Measuring the effects of social class on health and education permits the development of evidence-based resource allocation models and facilitates the monitoring of social gradients The precise measurement of social gradients plays an important part in the design of performance measurement frameworks and in the evaluation of interventions to improve social equality
Health Outcomes With normally Distributed Measure of Relative Affluence / Deprivation Deprived Affluent Above Average Risks Health Risks Below Average Risks (Average Health Risks) SD -3 -2 -1 0 1 2 3 0.1% 2.1% 13.6% 34.1% 34.1% 13.6% 2.1% 0.1% High Moderate Low Source: Haase, Pratschke (2017)
Some Considerations when thinking about Health inequalities Health Outcomes: Mortality, Life Expectancy, Self-rated Health, Long-term Limiting Conditions, Cancer, Respiratory Diseases, Coronary Heart and Cardio-vascular Diseases Socio-economic Contrasts: Education, Social Class, Deprivation Indices Geographic Scale: specific spatial contrasts - e.g. individual towns, counties or regions, Electoral Divisions (ED), Small Areas (SA) Display: Emphasis on Relative Risks, usingBar and Line Charts, Boxplots, and Maps Category Scales: Quintiles, Deciles, Standard Deviations Y-Scale: raw percentages, percentage deviation (Mean = 0), standardised mean deviation (e.g. Mean = 0, STD = 10)
Why do we use deprivation Indices? The Census and many sample surveys (TILDA, GUI, Healthy Ireland and the Irish Health Survey) include variables which relate to social class. Social class is often measured by educational attainments, occupation, employment status or income. Whilst each of these indicators allow us to identify social gradients, it is arguably more effective to measure social class using a multivariate measurement model based on clearly-defined and theoretically-supported dimensions. The resulting composite index is likely to perform better than any individual indicator when predicting health-related and educational outcomes. It also has the advantage that it may be used even where individual-level measures of social class are not available (e.g. in administrative datasets such as POD, P-POD, HIPE, NDTRS, NDRDI, CTL, etc.).
Advantages of Composite Deprivation Indices It is difficult to simultaneously comprehend the spatial distribution of multiple socio-economic indicators at a high level of spatial disaggregation at multiple points in time. For practical purposes, therefore, it is helpful to have a composite measure of social class which draws together a variety of related observations. This is a more reliable predictor of health and educational outcomes than any individual indicator. Deprivation indices such as the Pobal HP Deprivation Index provide a reliable means of assessing the effect of social class on health and education, facilitating monitoring and evaluation. The Pobal HP Deprivation Index also provides a means to support the targeting of disadvantaged areas and communities through the application of evidence-based Resource Allocation Models.
The Starting Point for designing a deprivation iNdex: A Comprehensive Definition of Poverty • Relative Poverty “People are living in poverty if their income and resources (material, cultural and social) are so inadequate as to preclude them from having a standard of living which is regarded as acceptable by Irish society generally.” (Government of Ireland, NAPS, 1997) • Relative Deprivation “The fundamental implication of the term deprivation is of an absence – of essential or desirable attributes, possessions and opportunities which are considered no more than the minimum by that society.” (Coombes et al., DoE – UK, 1995)
Traditional Approach to combining multiple Indicators: Exploratory Factor Analysis (EFA) • Exploratory Factor Analysis (EFA) reduces variables to a smaller number of underlying Dimensions or Factors V1 F1 V2 V3 V4 V5 F2 V6 • EFA is an exploratory technique; .i.e. essentially data-driven • all variables load on all factors • the structure matrix is the (accidental) outcome of the variables available • EFA cannot be used to compare outcomes over time
Approach underlying the HP Deprivation Indices: Confirmatory Factor Analysis (CFA) • Confirmatory Factor Analysis also reduces observations to the underlying Factors, however d V1 1 L1 d V2 2 d V3 3 d V4 4 d V5 L2 5 d V6 6 • CFA requires a strong theoretical justification before the model is specified • Researchers determine which observed variables are associated with which latent construct • variables are treated as imperfect manifestations of the latent concepts • CFA models can allow the comparison of outcomes over time • CFA facilitates the objective evaluation of the quality of the model through fit statistics
Overview of Successive Deprivation Indices, Haase & Pratschke 1996 - 2012 Haase et al., 1996 Haase, 1999 Pratschke & Haase, 2001 Pratschke & Haase, 2004 Haase & Pratschke, 2005 Haase & Pratschke, 2008 Haase & Pratschke, 2010 Haase & Pratschke, 2012 Haase & Pratschke, 2011
HP Deprivation Indices 2011-2016 2011 Pobal HP Deprivation Index 2016 Pobal HP Deprivation Index All-Island HP Deprivation Index Longitudinal HP Deprivation Index Longitudinal HP Deprivation Index Haase & Pratschke, August 2017 Haase & Pratschke, 2012 Pratschke & Haase, 2014 Haase & Pratschke, October 2017 Haase, Pratschke & Gleeson, 2014
The Underlying Dimensions of Social Disadvantage • Demographic Decline(predominantly rural) • population loss and the social and demographic effects of emigration (age dependency, low education of adult population) • Social Class Deprivation(applying in rural and urban areas) • social class composition, education, housing quality • Labour Market Deprivation(predominantly urban) • unemployment, lone parents, low skills base
The Measurement Model of the Pobal HP Deprivation Index d Age Dependency Rate 1 Demographic d Population Change Growth 2 d Primary Education only 3 d Third Level Education 4 d Persons per Room Social Class 5 Composition d Professional Classes 6 d Semi- and Unskilled Classes 7 d Lone Parents 8 Labour Market d Male Unemployment Rate Situation 9 d Female Unemployment Rate 10 • The Pobal HP Deprivation Index is estimated using a multiple group means and covariance structure model • This makes it possible to measure the change that occurred in the mean of the latent variables between 2006, 2011 and 2016
Strengths of the HP Deprivation Indices • true multidimensionality, based on theoretical considerations • provides for an appropriate treatment of both urban and rural deprivation • no double-counting • rational approach to indicator selection • uses variety of alternative fit indices to test model adequacy • identical structure matrix across multiple waves • identical measurement scale across multiple waves • true distances to means are maintained (i.e. measurement, not ranking) • distinguishes between measurement of absolute and relative deprivation • allows for true inter-temporal comparisons
Mapping Deprivation most disadvantaged most affluent
Distribution of Absolute and Relative HP Index Scores, 2006, 2011 and 2016
Distribution of AbsoluteHP Index Scores, 2006, 2011 and 2016 most disadvantaged most affluent The Figure shows the decline by 7.0 points in the mean of the Absolute HP Index Scores between 2006 and 2011 (or 0.7 of a standard deviation) and the subsequent recovery by 2.8 Index Scores (or 0.28 of a standard deviation) between 2011 and 2016.
Comparison of Relative Deprivation Scores between 2006 and 2016 • The most basic pattern of affluence and disadvantage has remained broadly intact over this 15-year period: affluence is highest in the urban peripheries and gradually declines as one moves towards more rural locations. • There is some indication that the reach of affluent commuter belts has diminished, particularly in the years following the recession. • Within the Greater Dublin Area, there has been a shift in the location of the most affluent areas. Whereas in 2006 the Western part of this area scored highly, in 2011 and 2016 affluence is once again concentrated in its traditional heartlands (e.g. Dun Laoghaire/Rathdown.