Elsevier

Social Science & Medicine

Volume 67, Issue 12, December 2008, Pages 2007-2016
Social Science & Medicine

A small-area index of socioeconomic deprivation to capture health inequalities in France

https://doi.org/10.1016/j.socscimed.2008.09.031Get rights and content

Abstract

In the absence of individual data, ecological or contextual measures of socioeconomic level are frequently used to describe social inequalities in health. This work focuses on the methodological aspects of the development and validation of a French small-area index of socioeconomic deprivation and its application to the evaluation of the socioeconomic differentials in health outcomes. This index was derived from a principal component analysis of 1999 national census data from the Strasbourg metropolitan area in eastern France, at the census block level. Composed of 19 variables that reflect the multiple aspects of socioeconomic status (income, employment, housing, family and household, and educational level), it can discriminate disadvantaged urban centres from more privileged rural and suburban areas. Several statistical tests (Cronbach's alpha coefficient, convergent validity tests with other deprivation indices from the literature) provided internal and external validation. Its successful application to another French metropolitan area (Lille, in northern France) confirmed its transposability. Finally, its capacity to capture the social inequalities in health when applied to myocardial infarction data shows its potential value.

This study thus provides a new tool in French public health research for characterising neighbourhood deprivation and detecting socioeconomic disparities in the distribution of health outcomes at the small-area level.

Introduction

The existence of inverse gradients between the socioeconomic status (SES) of populations and the incidence or mortality rates of numerous health outcomes, such as low birth weight (Krieger et al., 2003, Pattenden et al., 1999), cardiovascular diseases (Avendano et al., 2006, Kaplan and Keil, 1993, Mackenbach et al., 2000), mental health (Curtis et al., 2006, Tello et al., 2005), respiratory diseases (Ellison-Loschmann et al., 2007, Prescott et al., 2003), and some types of cancers (Steenland et al., 2002, Ward et al., 2004), is solidly established today. These social inequalities in health are not limited to the extreme ends of the social scale (Marmot, 2005), and they present an important health policy challenge (Adler and Newman, 2002, Wilkinson and Marmot, 2003).

In the absence of individual data, which are not generally routinely available, ecological (or contextual) measures of SES are frequently used to describe health inequalities. Although some epidemiological studies are based on only one socioeconomic indicator (income, educational level, or occupation) (Finkelstein et al., 2003, Kunst et al., 1998, Winkleby et al., 1992), SES is usually recognized as complex and multidimensional, integrating different components that may be either material (e.g., housing conditions, income, or occupation), social (e.g., social position or isolation, or family support) or both (Braveman et al., 2005, Folwell, 1995).

Area-based deprivation indices for the measurement of the economic or social disadvantages of urban areas were proposed in the 1980s (Townsend, 1987). Initially designed for health care planning and resource allocation, they have been recently used to evaluate and analyse health inequalities (Carstairs, 1995, Eibner and Sturm, 2006, Niggebrugge et al., 2005). These measures, including Townsend's, Carstairs', and Jarman's indices, as well as the more recent Index of Multiple Deprivation, combine contextual indicators such as unemployment rate or proportions of overcrowded or of non-owner-occupied households (Carstairs and Morris, 1991, DETR, 2000, Jarman, 1983, Townsend et al., 1988). Since the end of the 1990s, numerous other area-based deprivation indices have emerged – in the United States (Eibner and Sturm, 2006, Messer et al., 2006, Singh, 2003), Canada (Pampalon & Raymond, 2000), New Zealand (Salmond, Crampton, & Sutton, 1998), Japan (Fukuda, Nakamura, & Takano, 2007), Italy (Cadum et al., 1999, Cesaroni et al., 2006, Tello et al., 2005), Spain (Benach & Yasui, 1999), and Belgium (Lorant, 2000).

In France, on the other hand, this field has been the object of relatively little research (Challier and Viel, 2001, Lasbeur et al., 2006, Lucas-Gabrielli et al., 1998). Challier and Viel (2001) proposed a deprivation index at the resolution of the municipality and the canton in the district of Doubs, while Lucas-Gabrielli et al. (1998) focused on developing a classification of the social-health landscape of France at the scale of “employment zones” (which normally are not supposed to include fewer than 25,000 members of the labour force).

The 1999 French census made available a substantial quantity of demographic and economic information at a new and finer scale. The French census block (called IRIS in French for Ilots Regroupés pour l'Information Statistique, that is, housing blocks regrouped for statistical information) corresponds to a neighbourhood of residence of 2000 inhabitants on average and is comparable to the US census block group (National Institute of the Statistic and the Economic Studies, 2008). The multitude of information routinely available at this resolution offered us the opportunity to construct a new socioeconomic deprivation index at a finer geographical resolution than previously in France. This type of work at this small-area scale has developed slowly in France because very little relevant health or environmental data was available at this scale, for comparison with the socioeconomic deprivation index.

This article describes methodological aspects of the development of this new deprivation index and demonstrates its application to the evaluation of socioeconomic differentials in health outcomes at the census block level. This work took place in three consecutive stages. First, we conducted a multidimensional analysis of a relevant selection of available data to create at the census block level a small-area index of socioeconomic deprivation intended to characterise the contextual deprivation in French metropolitan areas. Then, we verified its validity by testing its content and construct validities. We simultaneously verified its reliability by reproducing the same multidimensional approach on another French metropolitan area at the same scale. Finally, we further demonstrated its validity by illustrating its capacity to capture health inequalities in an example using myocardial infarction data.

Section snippets

Study area

The study area is the Strasbourg metropolitan area (SMA) located in eastern France in the Bas-Rhin district (or department, an administrative subdivision of France). This area is composed of 28 municipalities (of which 21 are rural and 7 are urban) (316 km2) subdivided into 190 census blocks (for a total of around 450,000 inhabitants). In our study, a rural municipality is defined by a low population density (mean: 565 inhabitants/km2) and is composed of one or two census blocks, while an urban

Index

Our deprivation index was defined by the PCA as the first principal component, which explained 66% of the total variance of the model, while the second explained only 17%. The impossibility of drawing any residual structure from the second component justifies the conclusion that all of the discriminating information useful for characterising socioeconomic deprivation was in fact captured by the first component. Our index is composed of 19 socioeconomic variables that describe different

Discussion

From available census variables, we developed and validated a new French socioeconomic deprivation index at the census block level. Such work has never before been performed in France at so fine a geographic resolution. Working at this resolution ensures a better homogeneity of the residents' characteristics so that we can better identify and measure with greater precision their relation with the health events observed. Our index is a measure of overall SES, which combines material and, to a

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    The authors sincerely thank the directors of the Bas-Rhin Coronary Heart Disease registry for the production and loan of the myocardial infarction data. The authors also express their gratitude to the French Research Agency (grant ANR 06SEST27) and the French Agency for Environmental and Occupational Safety (grant AFSSET EST-2006/1/2), which jointly funded this project.

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