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Assessment of the Ecological Bias of Seven Aggregate Social Deprivation

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Assessment of the Ecological Bias of Seven Aggregate Social Deprivation Bryere et al. BMC Public Health (2017) 17:86 DOI 10.1186/s12889-016-4007-8 RESEARCHARTICLE Open Access Assessment of the ecological bias of seven aggregate social deprivation indices Josephine Bryere1*, Carole Pornet1,2,3, Nane Copin4, Ludivine Launay1,5, Gaëlle Gusto4, Pascale Grosclaude6, Cyrille Delpierre6,7, Thierry Lang6,7, Olivier Lantieri4, Olivier Dejardin1,2 and Guy Launoy1,2,3 Abstract Background: In aggregate studies, ecological indices are used to study the influence of socioeconomic status on health. Their main limitation is ecological bias. This study assesses the misclassification of individual socioeconomic status in seven ecological indices. Methods: Individual socioeconomic data for a random sample of 10,000 persons came from periodic health examinations conducted in 2006 in 11 French departments. Geographical data came from the 2007 census at the lowest geographical level available in France. The Receiver Operating Characteristics (ROC) curves, the areas under the curves (AUC) for each individual variable, and the distribution of deprived and non-deprived persons in quintiles of each aggregate score were analyzed. Results: The aggregate indices studied are quite good “proxies” for individual deprivation (AUC close to 0.7), and they have similar performance. The indices are more efficient at measuring individual income than education or occupational category and are suitable for measuring of deprivation but not affluence. Conclusions: The study inventoried the aggregate indices available in France and evaluated their assessment of individual SES. Keywords: Ecological social deprivation indices, Social inequalities in health, Aggregate-level, Individual-level Background conditions independent of income, experienced by people Evidence-based policy-making for reducing social dispar- who are poor” [3]. Evaluate deprivation in its entire di- ities in health requires measuring disparities accurately mension suggests that the proper evaluation of the social and to follow trends over time. Various approaches are environment should not be limited to any particular indi- used to measure socioeconomic status (SES). At the indi- cator such as financial resources, education or profession. vidual level, SES is mainly explored in three domains: Geographical approaches are thus particularly relevant for income, education and occupational status [1]. At an studying social inequalities in health. Measuring only one aggregate level, publicly available measures of SES in resi- of the components of deprivation is insufficient to cor- dential areas are frequently used [2]. Several geographical rectly classify communities [4], while deprivation indices, composite indices have been created, these are known as by their composite nature, are less sensitive to measure- ecological deprivation indices. As described by Townsend, ment bias and provide a comprehensive approach to deprivation, a “state of observable and demonstrable deprivation [5, 6]. disadvantage relative to the local community or the wider Deprivation indices, which are mainly derived from society to which an individual, family or group belongs”,is population census data, were first developed in the a broad multidimensional concept that is closely linked to 1970s in the United Kingdom, the United States and poverty. “The concept of deprivation covers the various Canada [3, 4, 7–12]. They have been implemented more recently in Europe [13–20]. Their main limitation when used to approximate individual SES is ecological bias, * Correspondence: [email protected] 1“Cancers & Préventions” U1086 INSERM-UCN, Centre François Baclesse, leading to misclassification. Ecological bias is a particular Avenue Général Harris, 14076 Caen, France bias related to studies using aggregate data. It can lead Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Bryere et al. BMC Public Health (2017) 17:86 Page 2 of 7 to estimation error of the degree of association between Since the geocoding process was not fully automated exposure and effect. Individuals who have had an effect and was relatively intensive, a random sample of 10,000 are not necessary those who were exposed. One way to people was used. Among these, 402 could not be geo- minimize ecological bias is to use the lowest geograph- coded because they lived in a neighboring department. ical unit [21], although even at the lowest geographical level, ecological bias is expected to persist. Individual data The overall objective of this study was to assess the All subjects were interviewed about four characteristics: ecological bias induced by using seven deprivation indi- ces that evaluate deprivation at the lowest geographical – Their education level. unit level for which census data are available in France: – Their occupation and position. Townsend index [3], Carstairs index [8], Lasbeur index – The feeling of having financial difficulties, as [14], Havard index [15], European Deprivation index assessed by the following question “Are there times (EDI) [18], and the social (SCP) and material (MCP) of the month when you are having real financial components of Pampalon index [12, 22]. problems in meeting your needs (food, rent, electricity)?” – If they receive CMU. Methods A general population sample was constituted in north- Calculation of the seven aggregated deprivation indices west France using exact known addresses allowing Two British indices, Townsend and Carstairs, were geolocalization and geocoding for IRIS (Ilots Regroupés calculated based on the unweighted sum of four socio- pour l’Information Statistique). An IRIS comprises an economic standardized variables. average of 2000 inhabitants as defined by INSEE SCP, MCP (designed in Canada) were calculated using (National Institute of Statistics and Economic Studies). principal component analysis (PCA) [12–16, 19]. Unlike On 1st January 2009, Metropolitan France contained the components of other indices built by PCA, SCP and 16,076 IRIS based on divisions of urban municipalities of MCP components were selected a priori according to at least 10,000 inhabitants. Most municipalities had 5000 the literature [12, 16]. to 10,000 inhabitants. For the smallest undivided muni- The Havard and Lasbeur scores were designed in cipalities (34,115), an IRIS is considered equivalent to France and were defined as the first principal compo- the municipality [23]. nents of a PCA of nine (Havard) or 19 (Lasbeur) 2007 For each deprivation index, ecological bias was census variables [14, 16]. The SCP and MCP were calcu- assessed by comparing the deprivation level of the IRIS lated from the first two principal components of a six- with the individual level socioeconomic characteristics. variable PCA [12, 22]. The methodology of the French EDI [18] is based on Study population the weighted combination of geographical census vari- Approximately 85% of the French population affiliated ables correlated with an individual indicator of with the general health coverage system is invited to a deprivation, itself obtained from individual data from the periodic health examination in a health examination European Union Statistics on Income and Living Condi- center (HEC). The study sample of 10,000 subjects tions (EU-SILC) survey. consisted of individuals 16 years and older who The aggregate socioeconomic data in IRIS were ob- consulted in 2006 at one of the 11 HEC located in tained from the 2007 census for homogeneity with the northwest France—about 60,000 people. The study sam- individual data from 2006. A version in national quintiles ple average age was 44.34 years (median 45 years), older was available for each deprivation index. than the French general population average age of 37.9 years (median 37.9). Compared with the French Statistical analysis general population rates, the rate of Couverture Maladie Each individual-level socioeconomic variable was dichoto- Universelle (CMU), rate of unemployment among the mized as follows. “Education level”: having a diploma/not active population, and rate of people without diploma having a diploma. “Occupation and position”: employed/ were 10.3 vs 3.4%, 8.4 vs 8.8%, and 14.2 vs 19.4%, re- unemployed. “Financial difficulties”: having/not having spectively [24]. The CMU is a French public health financial difficulties. “CMU”: yes/no. People were synthet- welfare program. For people with low incomes (less than ically considered deprived at the individual level if they 720€ per month), the CMU offers complementary 100% were disadvantaged in at least two of the four variables health coverage, which is added to standard Social presented above. We set a threshold of at least two vari- Security payments; this avoids the necessity of additional ables both because we wanted to ensure that at least two private insurance. dimensions of deprivation were integrated and because Bryere et al. BMC Public Health (2017) 17:86 Page 3 of 7 with a threshold of at
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