A Deprivation Index for Health and Welfare Planning in Quebec

Robert Pampalon and Guy Raymond

Abstract

Given that one of the goals of public health policy in Quebec and Canada is to reduce social inequalities in health and well-being, it is surprising, to say the least, that most information systems in this field make no mention of people's socio-economic characteristics. The present article proposes an index to reflect the material and social dimensions of deprivation as this concept has been developed by Peter Townsend and other authors. The article describes the method used to create the index, which uses census data and tools developed by Statistics Canada to match postal codes with enumeration areas. Examples are provided of the use of the index in information systems covering three aspects of health and well-being in Quebec: deaths, hospitalizations and births. The value of the information provided by this index in planning health and social services is demonstrated.

Key words: births; deprivation; geography; hospitalization; mortality; Quebec; social inequalities

Introduction

The association between social inequalities and differences in people's health and well-being is now well known, and the struggle against inequalities has become a major public health policy issue throughout the world,^1,2 in Canada^3,4 and in Quebec.^5,6 The strategies put forward in the Quebec policy for health and welfare⁵ include improving living conditions, such as level of education and income; providing support in people's environments (home, school and workplace); and working with groups that are considered vulnerable from the standpoint of their health and well-being.

Except for the general surveys on health and social issues that have been conducted recently,⁷ measuring social inequalities in health and welfare has always posed some problems in Quebec. These problems are due to the lack of socio-economic data in the main information systems used to determine the health and well-being of the population and to assess its consumption of health and social services, such as long-term care, home support and youth and children's services. Such information is lacking in the databases used to track deaths, hospitalizations and tumours in Quebec, and it is also absent from the database of the Quebec health insurance plan.

To get around these difficulties, researchers have turned to an ecological approach: to compensate for the lack of data on individuals, they substitute data on geographic areas such as neighbourhoods or CLSC (local community service centre) districts and analyze these data to determine the presence of socially based inequalities in health.^8-12 This approach undeniably provides some valuable information, but it does have limitations. The populations of the areas analyzed are often not very homogeneous. This kind of analysis is used only for large urban centres, and it has no explicit conceptual reference, or at least no unique one.

We therefore intend to propose a deprivation index that has explicit conceptual foundations, that can be incorporated into databases in the health and social services sector, and that can be used to track those inequalities in health and well-being that are associated with deprivation. In particular, we intend to describe the way the index is constructed and, by way of examples, to illustrate the possibilities that it offers for analyzing inequalities and for planning health and social service interventions. We begin with a short description of the concept of deprivation and how it has been measured around the world. We then show how we have adapted this concept to the Quebec context and provide a few examples of its use. Last, we suggest how the index could contribute to health and social service policies and programs.

The Concept of Deprivation

The term "deprivation" emerged in Britain in the 1980s from a long tradition of analyzing social inequalities in health. Peter Townsend¹³ saw deprivation as "a state of observable and demonstrable disadvantage relative to the local community or the wider society or nation to which the individual, family or group belongs." This disadvantage may occur at various levels, for example, with regard to food, clothing, housing, education or work. In fact, a person is considered deprived to the extent that he or she falls below the level attained by the majority of the population or below what is considered socially acceptable.

Peter Townsend distinguishes two forms of deprivation: material and social. The first involves deprivation of the goods and conveniences that are part of modern life-for example, a car, a television or a neighbourhood with green space. Social deprivation refers to relationships among individuals in the family, the workplace and the community. According to Townsend, material deprivation should be distinguished from "poverty," which is more related to lack of the resources-especially the financial resources-needed to acquire modern goods and commodities. Social deprivation, on the other hand, is more closely related to the concept of "social capital,"¹⁴ reflecting certain characteristics of social organization, such as isolation or cohesion, individualism or co-operation, mutual assistance and trust.

Both of these forms of deprivation are closely linked with public health and welfare. They are related to mortality in the general population^15,16 and to premature mortality (either general or due to ischemic heart disease or other causes related to tobacco use).¹⁷ They vary with all forms of morbidity, from cancer¹⁸ to restriction of activities,¹⁹ and from respiratory diseases and diabetes²⁰ to tooth decay.²¹ Material and social deprivation are also associated with mental health, such as short-term and long-term use of psychiatric services^22-25 and criminal behaviour.²⁶ Finally these forms of deprivation may be used as a guide in managing public health services, especially in the area of medical resources.^27,28

Measuring Deprivation

Many studies of deprivation (chiefly material deprivation) rely on two particular deprivation indices, one developed by Townsend¹³ and the other by Carstairs and Morris.²⁹ Both indices involve four variables, three of which are the same in both cases: unemployment, lack of a car and overcrowded housing. The fourth variable in the Townsend index is home ownership; in the Carstairs index, it is lower social class. In the construction of these indices, the four variables are standardized and normalized, each variable being given an equal weight.

A third index, called the Under-privileged Areas (UPA) score, was developed by Jarman et al.³⁰ and is extensively used in deprivation studies. (Incidentally, it is also used in determining remuneration for physicians in Britain.) The UPA score comprises eight variables, including the four already mentioned and four more: the proportion of single-parent families, children under age 5, retired persons living alone and recent immigrants. The weight given to each of these variables in constructing the index differs according to the perception that physicians have of that variable's impact on their workload. A comparative analysis of the three indices³¹ has shown that the first two correlate more closely with a set of health indicators than does the third.

Lastly, studies of deprivation sometimes use other kinds of indices or numerous individual variables, including income, education level, marital status and residential mobility as well as those already mentioned.^13,22,31

These measures have been derived essentially from national census data on small geographic areas such as wards and enumeration districts in Britain,^16-18,20,29 "small area market statistics" in Sweden²⁸ and meshblocks in New Zealand.³² The measures can then be transposed into individual records in population surveys²⁶ and surveys of specific client groups,^20,22,23 or they can be used in ecological analyses.^16-18,27,29 In such analyses, these small areas are usually grouped into larger, arbitrary statistical aggregates (such as quintiles or deciles) according to their level of deprivation, from lowest to highest.

What is important when creating such measures is to choose a basic geographic unit that is as small as possible and as homogeneous as possible in its socio-economic characteristics. The size of the social inequalities in health and well-being that will be observed and the accuracy of the observations will depend greatly on the basic geographic unit chosen. In Britain, for instance, it has been shown that basing analyses on enumeration districts (average population of about 500), rather than on wards (average population of over 5,000), reduces errors in classifying individuals, leads to higher correlations between social inequalities and health, and results in more stable funding of medical services from one census to the next.^27,33,34

Data and Methods

Basic Geographic Unit

Our basic geographic unit, the enumeration area (EA), was chosen for two reasons. First, this is the smallest geographic unit for which census data are available in Canada. The average EA has a population of 750. Second, the postal code conversion file can be used to establish a link between information on EAs and the geographically based information, classified by 6-character postal codes, available in the health and welfare databases maintained in Quebec.³⁵

Not all of the EAs in Quebec were used in the analysis. The EAs in Nunavik and the Cree territories of James Bay were excluded because of the poor quality of their census data. All EAs with fewer than 250 inhabitants (fewer than 68 households) were eliminated, because this is the minimum size of EA for which Statistics Canada produces income figures. Many of the EAs thus eliminated have no inhabitants and are classified as unorganized areas. Also, most of those EAs that consist of health and social service institutions, such as hospitals, psychiatric facilities, homes for the aged and rehabilitation centres, were eliminated since any group institution with 75 beds or more constitutes an EA, according to the census rules.³⁶ The 9,058 EAs that remained and were included in the present analysis represent about 96% of the total population and of all households in Quebec.

The equivalence that the postal code conversion file establishes between the 6-character postal code areas and the EAs is not perfect. Slightly less than 6% of the postal code areas cover more than one EA. For these areas, the EA was randomly and proportionally assigned, according to the population of each EA living in the same postal code area. This population figure comes from the Statistics Canada file for weighting the population by postal codes.³⁷

Indicators

The deprivation index combines six indicators chosen for the following reasons: their relation to a large number of health and welfare issues; their association with one of the two forms of deprivation (material or social); and their availability by EA in the Canadian census data. The six indicators and the mnemonics that we have used for them are as follows: the proportion of persons who have no high-school diploma (SCOLAR); the ratio of employment to population (EMPLOI); average income (REVMOY); the proportion of persons who are separated, divorced or widowed (S_D_V); the proportion of single-parent families (F_MONO); and the proportion of people living alone (SEULES). All of these indicators except for the proportion of single-parent families have been adjusted according to the age and sex of the population so as to highlight the economic and social conditions of the persons concerned.³² In order to normalize the distribution, it was necessary to convert some of the indicators (REVMOY, S_D_V and SEULES) to their logarithms and one (F_MONO) to its square root.

Combining the Indicators

In general, there are two ways to combine indicators: the additive approach, with weighting, which has been used to create deprivation indices in Britain,^13,29,30 and the factorial approach, which has been used to develop various socio-economic indices^38-40 and, more recently, a deprivation index in New Zealand.³² We opted for the factorial approach because the weight assigned to each indicator is not determined arbitrarily on the basis of the perceptions of the researcher or of a group of professionals (for example, general practitioners),³⁰ but is determined from the statistical relationships that exist among the indicators within the geographic area in question. More specifically, we used principal component analysis (a form of factor analysis), applying a Varimax rotation and retaining only those components whose eigenvalues exceeded 1.00. Two of the components that we analyzed satisfied this criterion, and it was from these two components and their cross-tabulations that we developed the deprivation index (Table 1).

Each of the two components accounts for slightly more than one third of the variations in the six indicators considered, for a total of 73%, and the two are sharply differentiated in their meaning. The first component reflects variations in education, employment and income in Quebec and thus tends to emphasize the material aspect of deprivation. The second component reflects variations in the indicators associated with the social aspect of deprivation-the proportions of widowed, separated and divorced persons, of single-parent families and of persons living alone.

To test the validity of this model for Quebec as a whole, we repeated the same principal component analysis for four distinct areas in Quebec: the Montreal Census Metropolitan Area (CMA), the other CMAs in Quebec (Quebec City, Sherbrooke, Hull, Chicoutimi-Jonquière and Trois-Rivières), the Census Agglomerations (CAs) of Quebec (cities with 10,000 to 100,000 inhabitants) and, finally, Quebec's small towns and rural areas. In every case, we found the same factorial structure, with the two principal components accounting for 72-75% of the variation in the indicators for the CMAs and CAs and 62% of the variation in the indicators for small towns and rural areas.

Grouping the Enumeration Areas

To ensure a certain statistical accuracy in the analysis of inequalities in health and welfare, we had to combine the EAs into sufficiently large groups while ensuring that these groups were homogeneous in terms of material and social deprivation. The EAs were therefore grouped according to their factor scores, which represent the importance of each component in each EA, and a conventional method^16,18,27,29 was followed. For each component, the factor scores were ranked from least to most deprived EA, and then the resulting distribution was divided into quintiles, according to the size of the population of each EA. Thus, quintile 1 represents the least deprived segment of the population of Quebec, and quintile 5 represents the segment that is most deprived.

Lastly, the two sets of quintiles (for material and social deprivation) were cross-tabulated, for a total of 25 cells. We could then see which population segments were not deprived according to either of these measures, which ones were deprived according to one but not the other and which ones were deprived according to both. For example, the cell in which quintile 1 for component 1 intersects quintile 1 for component 2 represents the population segment that is most privileged both materially and socially; the cell for quintile 5 for both components represents the segment that is the most deprived.

Health and Welfare Indicators

The deprivation values were entered into three information systems, covering deaths, hospitalizations and births. Various measures were then produced by quintiles and cross-tabulated deprivation quintiles. Some of the measures were general, such as life expectancy at birth, the standardized mortality ratio (SMR) for the years 1995-1997 and the hospitalization rate adjusted for population age and sex and for the level of resource use (APR-DRG: classification and weighting system for short-term patients) for the year 1997/98. In the case of the SMR, chi-squared tests were used to determine the significance of any differences between the values by quintiles and cross-tabulated quintiles and the values for Quebec as a whole.⁴¹

The other measures were more specific and were designed to test the sensitivity of the index by associating it with problems known to be largely determined by material and social living conditions.^{7,17,24,25,42,43} These measures were as follows: standardized mortality ratio for premature deaths (at ages 35-74) due to tobacco use, adjusted rate of hospitalization for mental illness and two measures regarding births-the fertility rate for teenage girls (< 20 years old) and the birth rate of infants with low birth weight (< 2500 g) among all women in Quebec for the years 1995-1997.

For most of the deaths, hospitalizations and births analyzed (89-96%), a corresponding deprivation value was obtained (Table 2). For the remaining events no deprivation value was obtained, either because the associated EA had been excluded for being too small or because the postal code in the database was invalid (less than 3% of the events had invalid postal codes).

Discussion

The size of the inequalities that our deprivation index revealed-especially as regards premature death due to tobacco usage, hospitalization for mental illness, fertility in teenage girls and births of infants with low birth weight-shows that this deprivation index is especially sensitive to the material and social conditions in which people live.

The approach used to develop the index is not totally new. Six-digit postal codes have been used previously in Canada to introduce an income measure into death records,^46-48 and some differences in life expectancy and mortality due to several causes have been identified thereby. However, our approach does differ from past efforts in several respects.

First of all, it is based on a clearly established concept of deprivation that comprises two dimensions confirmed by our principal component analysis: material deprivation (including an income measure) and social deprivation. Our results show that within Quebec the two dimensions do not necessarily co-exist: an area can very well be deprived materially but not socially, and vice versa. Our results also show that each of these forms of deprivation can have its own distinct impact on health and that this impact is increased when the two forms are found together. The impact can also vary with sex and with the health and welfare indicator considered. Thus it is useful to distinguish between these two forms of deprivation.

Another difference in our index is that it uses data for enumeration areas rather than census tracts to estimate people's degree of deprivation. Studies done in Quebec⁴⁹ and elsewhere^27,33,34 show that the smaller the reference area, the more likely the population will be homogeneous, the more classification errors will be avoided and the more major discrepancies in health will be revealed. A recent Manitoba study⁵⁰ shows that average household income for EAs is just as good a predictor of mortality, hospitalization and other health problems as the household income reported in the census. Thus there appears to be an advantage in using EAs as the reference area in this kind of study.

However, some studies^51,52 have shown that geographic measures, no matter how small, are not individual measures and that it could be somewhat risky to substitute one for the other. A geographic measure is an aggregate of individual and environmental features, which, separately and jointly, have an impact on the health of a population.^53,54 Geographic measures, therefore, provide a general estimate of such an impact without having to disentangle the specific contribution of these individual and environmental features.

A final difference in our approach is that it offers a model of deprivation that covers the vast majority of the territory and population of Quebec rather than just a sample or a part of it and is thus valid everywhere, regardless of area of residence. The model can therefore help to provide a more complete knowledge of inequalities in health and welfare within the population. It can also help to plan programs in a manner consistent with the resources available to the individual communities throughout the jurisdiction concerned. This is a definite advantage for a health and social services system like Quebec's, in which many programs have large regional and local intervention components.

Indeed, the deprivation index presented in this paper offers many possibilities for planning and implementing health and social service programs. Here are a few of them.

First of all, we consider it important to conduct an extensive analysis of inequalities in all aspects of the public's health and well-being. Our deprivation index can be used for this purpose, and we have begun a detailed analysis not only of mortality and hospitalization rates but also of malignant tumours, consumption of medical services, consumption of services for young victims of abuse and neglect and for old people living in their own homes. This analysis will allow a preliminary assessment of inequalities in health and well-being associated with deprivation, monitoring of these inequalities and consideration of them when public policies and programs are being developed.

The deprivation index can also be used to support regional and local interventions. Since this index is a geographic measure, based on census data, it can be used to derive a profile of deprived communities at the regional and local levels and determine exactly where such communities are located in Quebec. Because the index can also be entered into client files that record use of services, it can be used to establish deprivation profiles for different target client groups at the regional and local levels. Through comparison of the deprivation profile for the population as a whole with profiles of specific groups of clients, the rate of penetration of health and social services within the deprived population of Quebec can be estimated. We have already started such a project concerning the services provided by CLSCs in the province.

Lastly, our index can simplify the task of measuring population needs in order to allocate resources among regions and local communities. Currently, needs for health and social services are measured in Quebec,^55,56 elsewhere in Canada^57-59 and elsewhere in the world^60,61 according to two parameters: the population's age and its social and health-related characteristics. Two distinct methods are used for this purpose, one for each parameter. Our deprivation index will allow analysts to apply the same method to measure both types of needs, taking a provincial consumption profile and projecting it onto the regional or local level.

In short, the index offers considerable opportunities both for acquiring new information about health and social service needs and for planning policies and programs to meet them. This is true not only in Quebec but also elsewhere in Canada because the tools required to construct the index are available.

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