There is a long history of research into the effect of socioeconomic factors and deprivation on health. The spatial dimension where people live – is a major determinant of health inequalities, for example in terms of marked variations in life expectancy
( Mitchell et al 2005). One socioeconomic variable, the type of housing that people can afford to live in, is obviously related to income. Hence housing is thought to be one of the determinants of a person’s overall health and wellbeing in terms of both physical and psychological.
Fuel poverty can be defined as an individual being not capable of affording those resources to keep them in warm condition. Boardman (1991) defined fuel poverty as the inability of a household to acquire energy sources such as heating by using 1o percent of their household income. While the department of energy and climate change approach the same description of fuel poverty as a household to be in fuel poverty in case it needs to spend more than 10 percent of its income on fuel or on heating for sufficient warm ( 21 degrees for the main living area, and 18 degrees for other in use rooms). The living standard and people’s health can be damage while living in cold and damp houses. There is the possibility that elderly, children and people with a long term illness and disability are more susceptible to fuel poverty. The department of energy and climate change classifies fuel poverty into three main categories. (Department of energy and climate change, Addressing Fuel Poverty).
Poor condition of the energy efficiency in home
High energy prices and its affordability.
Low income status of the people
Dr. Noel DL Olsen (2001) described that “few people choose to live in cold damp homes that they cannot afford to heat well enough to protect their health. Yet for millions of British households this is the reality of poor quality housing, inefficient heating systems and inadequate building standards stretching back over generations.”
The aim of the study is to understand and mapping of housing and heath determinants and their relationship in fueling poverty in Salford area of Greater Manchester.
To understand basic factors of housing and health inequalities
To understand how various housing and health inequalities fueling poverty
To understand the relationship of various factors using statistical analysis
The literature review will described the basic description of health and housing inequalities. The condition of housing includes a collection of characters that are integral to the status and well being of a family. Housing on the other hand must be in a state of safe and well-mannered conditions to represent a family life.
One of the most famous and influential sources here is John Snow’s study of clusters of cholera which were found to be caused by contaminated public water facilities in London (Hempel, 2007). This study will be important both in terms of its part in the then emerging field of public health, but also more recently as an illustration of the potential for GIS and spatial analysis techniques in that field. Other early works on the state of the emerging discipline of public health focused on the newly-industrializing slum communities of nineteenth century England. Manchester, the first industrial city, was a good example of this and accounts of the conditions there at that time have acquired totemic status. For example, Engels’ ‘Conditions of the working class in England’, (1987, originally published in 1844) formed part of the primary research which he and his colleague Marx used in their globally-influential economic and political analyses. One hundred and thirty years later, Roberts’ ‘Classic slum’ (1971) provided a first-hand account of someone growing up in Salford, the deprived area immediately to the North West of inner city Manchester, particularly the social and related health problems of its housing stock. However, although the relation between poor health and poor housing seems obvious because of the basic human need for shelter, Thomson et al (2001) comment in a systematic review of published literature of “despite, or perhaps because of this intuitive relation, good research evidence is lacking on the health gains that result from investment in housing”. Furthermore, Thomson et al (2001) described that “there is also a lack of comparative information on the costs and effects of specific housing improvements, such as central heating or major refurbishment. It is this type of evidence that is likely to be most valuable to policy makers and housing providers. Large scale studies that investigate the wider social context of housing improvements and their comparative effectiveness and cost effectiveness are now required.”
Palmer et al. (2008) explained that “single-person households in England are much more likely to be in fuel poverty than couples or larger families, their risk being twice as high as the next highest household type, lone parents (in 2005, 15% compared with 7%). This applies to working-age singles as well pensioner singles. Because of their relatively high risk, two-thirds of the households in fuel poverty in 2005 in England were single-person households even though only a quarter of all households were single-person households.”
Housing, Health and Adequate heating
Boardman (1991) first described that fuel poverty are due to the causes of inability of adequate energy usage for adequate heating but on the same time Shortt and Rugkasa (2005) in their research explained that there is the complex relationship between other factors associated with the household such as income, adequate heating and how to use efficient use of the energy, in which case the failure occur when defining the fuel poverty. There has been an effect on person mental health due to poor and inadequate heating system. Poor housing and inadequate heating system lead to damp which causes most of the common health issues. The personal well being, mental health and physical health has been affected by damp conditions of a place. Such type of mental health effect on a person life has been suggested by Lowry (1991) describing that “the psychological consequences of having scrape mould off your walls everyday are obvious”.
A relationship between ill health and poor housing
It has been described by (Byrne et al., 1986) that impressive developments in housing sector were accompanied by the developments in health such as at younger age measured of the mortality or children growth and development and also by the declination in the occurrence of diseases associated with overcrowded houses and insanitary conditions. While Burridge and Ormandy (1993) described that there has been the revision of such relationship with in recent years. There is the declaration that due to the construction of as specific type of housing accommodation especially flatted, with no consideration to health criteria, without the needs of the prospective residents has had effects on health. Beside this ill health has been described as a physical manifesto which includes social and psychological effects. One of the local housing authority motivations and a aspiration for the improvement of working class health with the help of providing them with better housing, has resulted in recent decades new slums and health risks associated with it.
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Boardman (1991) said that “people give priority to adequate heating, if they have sufficient income and therefore fuel poverty is a clear indicator of poverty. Whilst the concern is not necessarily true, it is reasonable to assume that most of those in poverty are restricted to the amount of fuel that they can purchase and thus are suffering from fuel poverty”. Health and well being of older people is crucial in terms of adequate warmth in their homes, mainly to avoid winter deaths among them (Wilkinson, et al, 2001). Where as Bates et al, (2001) illustrated that for inadequate heating the central heating is not only the just the suggestion but it is in association with the deprivation. From the above reports there is the indication that there is a significant relationship between poor health and other poor housing factors such as dampness, moulds and poor heating or no heating provisions.
There are many research methods from which to choose for a typical research methodology. In the research methodology there is the following general discussion on the conducting of the research and some understanding of type basic concept of the qualitative and quantitative methods. There are many research methods from which to choose from. Research methods are the technique of investigation used to conduct a study. They include the use of questionnaires, interviews, participant observation or field work with the community being studied together with the interpretation of official statistics and historical documents and other techniques not so widely used. Generally there are three main methodologies.
Van Maanen (1983) defines qualitative methods as “an array of interpretative technique which seek to describe, decode, and translate and other wise come to term with the meaning, not the frequency, of certain more or less naturally occurring phenomena in the natural world.”
Easterby-smith et al (1995) described four main ways of gathering of quantitative data:
While they stress that the differences between quantitative and qualitative techniques is not always clear. Quantitative methodologies have an emphasis on the importance of basing research upon protocol and technique.
In this piece of research the author will rely on quantitative methodology in the form of secondary data through various sources of database. These databases will include census data to perform the analysis and find out the results.
The case study area: Salford, Greater Manchester
Manchester’s ‘twin city’, Salford, adjoins it across the River Irwell and shares much of its history. The wider Greater Manchester region is made up of ten metropolitan local authorities:
Manchester (City of)
Salford (City of)
The metropolitan authority known as the ‘City of Salford’ comprises 20 wards and has a population of 216,000. In this study GIS application will be used along with spatial analysis and statistical techniques to investigate the reality of fuel poverty in this area. This issue is important in policy terms because it seems likely to be a major problem for public health – and hence for the economy – because of the increasing proportion of elderly people in the population. Fuel poverty is worst among the oldest members of society, particularly those in deprived areas such as Salford. Areas like some parts of Salford also have a higher than average concentration of elderly people because younger people tend to leave the area to seek employment and training opportunities elsewhere.
Data and methods
The data on socio-economic conditions in Salford will be gathered along with the maps of the area using a variety of resources. Specifically, data on health, housing, family configuration and other conditions in Salford’s wards were obtained from the 2001 Census via NOMIS. Maps were obtained from Ordnance Survey and other sources.
In the census, ‘health’ will be chiefly covered by two questions. Firstly, responses confirm whether a person considers themselves to be in (a) ‘good health’, (b) ‘fairly good’ health or (c) not in good health. Secondly, data will be the available on whether respondents suffer from ‘limiting long-term conditions’. Some other variables will be envisaged may affect people’s health in this region. These were: whether housing accommodation provided, or did not provide, central heating; whether people lived as part of a couple or lived alone; and whether people were economically active or inactive (i.e were/were not in work, education or training).
Data on local pollution will be downloaded from the UK Air Quality website (UK NATIONAL AIR QUALITY ARCHIVE,). This will demonstrate the relationship between health and pollution. Pollutants included Nox, No2 and PM10.
These will be obtained from EDINA Ordnance Survey for both the Greater Manchester area as a whole and Salford’s constituent wards.
Statistical analysis of the results
The data will be analyzed using SPSS software, then using regression statistics to determine whether there is significance. The data will be modeled the extent to which health is affected by variables such as central heating, being economically active, living in a couple and so on. Map reports can be used to address the out come from the analysis of the geographical data.
In the following section there will be an analysis of results through regression analysis by using multiple variables. In SPSS a simple method “Analyze…. Regression…. Linearâ€¦..” in each case will be followed. There will be the selection of different criterion (dependent) and the predictor (independent) variables and will used the multiple regression model four times. Multiple regression analysis (MRA) is a useful method for generating mathematical models where there are several (more than two) variables involved.
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Multiple Regression analysis: the multivariate regression will be used for at least four times to analyze the relationship between various variable of housing and health inequalities. People in good health and unstanderised predicted variables. The multiple regressions will use run of people in good health as a dependent variable and various other in dependent factors as in a variable entered table.
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