Poverty Health warning for Wales
ViewsApril 18th, 2024
ViewsAugust 15th, 2013
We know that child poverty is associated with low educational achievement and that educational attainment is the best indicator of future income and health. The Welsh Government has two flagship schemes for working towards reducing and eliminating poverty namely community first and flying start.
Communities First
Since becoming the Assembly Member for Swansea East in 2011, I’ve witnessed first-hand practical examples of Communities First programmes that have made a significant difference to the lives of many people; this has ranged from helping people find employment, helping reduce their financial outgoings, to helping people improve their health and wellbeing.Community first supports the most disadvantaged people in our most deprived communities with the aim of contributing to alleviating persistent poverty especially inter generational poverty.
The Welsh Government funded Communities First Delivery Teams work with residents, community organisations, business and other key agencies in the newly formed Clusters and focus on actions leading to the long term sustainability and wellbeing of communities. It is based upon involving local people in all aspects of this work as an essential feature of the programme .Communities First aims to contribute to reducing the education/skills, economic and health gaps between the most deprived and more affluent areas in Wales. The Programme has three strategic objectives helping to achieve these outcomes which are prosperous Communities, learning Communities and healthier communities.
The weakness is that each area is identified from its census data which can only be accessed at lower super output area level. These are a set of geographical areas developed following the census, initially to facilitate the calculation of the Indices of Deprivation. The problem is that where the area is not homogenous pockets of deprivation can be missed. Is there a better way of identifying areas of deprivation such as housing tenure and council tax band because such relatively large areas as these can include both relative affluence and pockets of poverty?
Flying Start
Flying start is a programme to create positive outcomes for children. When some children start nursery school at three can be two years behind others in terms of development then something needs to be done. It is incredibly difficult to reduce this gap over the eight years children are in primary education, this needs addressing before they start nursery school. The core elements of flying start are drawn from a range of actions that have been shown to create positive outcomes for children and their families. These include free quality part-time childcare for 2-3 year olds, an enhanced Health Visiting service, access to Parenting Programmes and early Language Development. The key is providing an opportunity for children to develop between 2 and 3 in such a way that they start school with development consistent with their chronological age. Within Swansea, despite a change in the targeting approach from school catchment in phase 1 to LSOAs in phase 2 the model for the childcare continues to be locates in Primary Schools, where this is possible, in order to achieve effective transition into the Foundation Phase. This should make it easy for the benefits and impact to be identified. The criteria for identifying the Flying Start target areas are not the same as Communities First, Flying Start is based on the Income Benefit Household Data for 0-3 year olds in order to ensure that the programme is targeted effectively at young children.
To be eligible for Flying Start, the family or individual must meet certain criteria, such as being pregnant or have at least one child aged 0-3 years, and live within the catchment areas. First time parents or those who need particular help with parenting are identified through a health assessment, and appropriate support given for their needs. Again this area based approach misses many children who live in areas outside the designated area who have the same or greater needs. It is imperative that action is taken to ensure that these children do not miss out.
Concerns
Whilst the census area data catches most areas of poverty and children who need support the problem occurs where there are either pockets of deprivation or more often where the boundary used is not a community boundary and so consequently an area alongside a flying start or community first area of equal or even greater need is missed.
I believe that either a greater flexibility is needed or that a better method of identifying those in need, especially for flying start must be found. We owe it to our children to ensure that they all have an equal opportunity and that it does not become a post code lottery.
Mike Hedges is Assembly Member for Swansea East. Please let us know what you think.
This post is one of a series supported by Joseph Rowntree Foundation about Poverty and Social Exclusion in Wales in the run up to the launch of their report in September.
I’m not sure using units smaller than LSOAs necessarily leads to more accurate identification. LSOAs are already small and have been used in the most recent editions of the WIMD precisely because they allow for a more nuanced sub-ward analysis of deprivation at community level. They are constrained by the arrangement of electoral wards above them, which would presumably be costly to rearrange. With such rapid growth in housing in some wards (Butetown springs to mind) the LSOAs need to evolve to reflect the new communities that spring up; this is not necessarily about the size of LSOAs, but the cohesion and sensitivity with which a ward is carved up into them. At a macro level it is less about the size of the LSOAs and, rightly as Mike Hedges points out, about how flexibly they are interpreted by the programmes that use such data and whether other data is eligible to complement WIMD and census data. The experience of Communities First (CF) is salient here.
CF, through its use of Results Based Accountability, requires a story behind the baseline. In essence ‘what else does one know about a community beyond what the statistics suggest’. This is welcome. I recall CF staff in the Dulais Valley citing broadband connectivity data that suggested it was among the most 2-3% ‘dis-connected’ communities in the whole UK. Data related to digital connectivity, whether it is use or availability thereof, is not an indicator that WIMD draws upon; though arguably with the increased shift towards online access to job searches and availability of financial products and transactions it is a key indicator that shapes deprivation. CF allowed for additional data and research to shape the argument for resources towards particular tackling poverty activities.
The emphasis on the size of LSOAs potentially draws attention away from the underlying indicators that the WIMD draw on. Mike Hedges focuses on two housing related indicators: tenure and council tax band. This is particularly interesting for two reasons. Firstly, that the last WIMD in 2011 deliberately reduced the weighting in the calculation of the overall WIMD of the housing domain from 10% to 5% because it drew on census data from 2001 and this was felt to be less robust than it might have been. Thus, irrespective of which indicators are used, the key issue is that the weighting of the different domains reflects the proportionality to which different indicators cause, aggregate or reflect poverty. Secondly, tenure and council tax seem reasonable indicators to accompany the current housing domain indicators of overcrowding and presence of central heating. One might argue however that data related to affordability of housing might be more pertinent again; or even availability of housing. In respect of tenure, is the status of tenure or security of tenure that is a more pertinent indicator to levels of deprivation within a community? This reveals how politically-laden the identification of indicators actually is. Why is there no business start-up related indicator? Or self-employment related indicator? Whatever the indicator, the data has to be available consistently at whatever unit level is employed because the more gaps there are the harder it is to be flexible in the interpretation of data for which Mike Hedges calls. Again CF’s experience is helpful.
The gaps in ‘NEET’ data at LSOA level made for a very patchy understanding of even the statistical extent of the problem and provided for a muddled picture among CF clusters. If the extent of a problem is not accurately known, how can tackling it be accurately resourced? Or progress be measured? Perhaps this is why WIMD does not use ‘NEETs’ as an underlying indicator?
The opportunity to participate in the construction and design of WIMD is one which should be more prominent than it traditionally has been in order to pluralise the debate about *what* is relevant in defining ‘in need’ and not just *where* people in a pre-determined and possibly remotely-determined need are.