SesIndexCreatoR: An R Package for Socioeconomic Indices Computation and Visualization
Author(s)
Benoît Lalloué1,2,
Séverine Deguen2,3*,
Jean-Marie Monnez4,
Cindy Padilla2,3,
Wahida Kihal2,3,
Denis Zmirou-Navier2,3,5,
Nolwenn Le Meur2
Affiliation(s)
1 Institut Gustave Roussy, Paris, France. 2 EHESP Rennes, Sorbonne Paris Cité, Rennes, France. 3 Inserm, UMR IRSET, Institut de recherche sur la santé l’environnement et le travail - 1085, Rennes, France. 4 Lorraine University, CNRS, INRIA UMR 7502, Institut Elie Cartan, Lorraine, France. 5 Lorraine University, Medical School, Lorraine, France.
1 Institut Gustave Roussy, Paris, France. 2 EHESP Rennes, Sorbonne Paris Cité, Rennes, France. 3 Inserm, UMR IRSET, Institut de recherche sur la santé l’environnement et le travail - 1085, Rennes, France. 4 Lorraine University, CNRS, INRIA UMR 7502, Institut Elie Cartan, Lorraine, France. 5 Lorraine University, Medical School, Lorraine, France.
ABSTRACT
In order to study social inequalities, indices can be used to summarize the multiple dimensions of the socioeconomic status. As a part of the Equit’Area Project, a public health program focused on social and environmental health inequalities; a statistical procedure to create (neighborhood) socioeconomic indices was developed. This procedure uses successive principal components analyses to select variables and create the index. In order to simplify the application of the procedure for non-specialists, the R package SesIndexCreatoR was created. It allows the creation of the index with all the possible options of the procedure, the classification of the resulting index in categories using several classical methods, the visualization of the results, and the generation of automatic reports.
In order to study social inequalities, indices can be used to summarize the multiple dimensions of the socioeconomic status. As a part of the Equit’Area Project, a public health program focused on social and environmental health inequalities; a statistical procedure to create (neighborhood) socioeconomic indices was developed. This procedure uses successive principal components analyses to select variables and create the index. In order to simplify the application of the procedure for non-specialists, the R package SesIndexCreatoR was created. It allows the creation of the index with all the possible options of the procedure, the classification of the resulting index in categories using several classical methods, the visualization of the results, and the generation of automatic reports.
KEYWORDS
Socioeconomic Status, Multidimensional Index, Principal Component Analysis, Hierarchical Classification, R
Socioeconomic Status, Multidimensional Index, Principal Component Analysis, Hierarchical Classification, R
Cite this paper
Lalloué, B. , Deguen, S. , Monnez, J. , Padilla, C. , Kihal, W. , Zmirou-Navier, D. and Le Meur, N. (2015) SesIndexCreatoR: An R Package for Socioeconomic Indices Computation and Visualization. Open Journal of Statistics, 5, 291-302. doi: 10.4236/ojs.2015.54031.
Lalloué, B. , Deguen, S. , Monnez, J. , Padilla, C. , Kihal, W. , Zmirou-Navier, D. and Le Meur, N. (2015) SesIndexCreatoR: An R Package for Socioeconomic Indices Computation and Visualization. Open Journal of Statistics, 5, 291-302. doi: 10.4236/ojs.2015.54031.
References
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http://dx.doi.org/10.1111/j.1467-842X.1998.tb01505.x [5] Eibner, C. and Sturm, R. (2006) US-Based Indices of Area-Level Deprivation: Results from Health Care for Communities. Social Science & Medicine, 62, 348-359.
http://dx.doi.org/10.1016/j.socscimed.2005.06.017 [6] Messer, L.C., Laraia, B.A., Kaufman, J.S., et al. (2006) The Development of a Standardized Neighborhood Deprivation Index. Journal of Urban Health, 83, 1041-1062.
http://dx.doi.org/10.1007/s11524-006-9094-x [7] Bell, N., Schuurman, N. and Hayes, M.V. (2007) Using GIS-Based Methods of Multicriteria Analysis to Construct Socio-Economic Deprivation Indices. International Journal of Health Geographics, 6, 17.
http://dx.doi.org/10.1186/1476-072X-6-17 [8] Fukuda, Y., Nakamura, K. and Takano, T. (2007) Higher Mortality in Areas of Lower Socioeconomic Position Measured by a Single Index of Deprivation in Japan. Public Health, 121, 163-173.
http://dx.doi.org/10.1016/j.puhe.2006.10.015 [9] Pampalon, R., Hamel, D., Gamache, P., et al. (2009) A Deprivation Index for Health Planning in Canada. Chronic diseases in Canada, 29, 178-191. [10] Lalloué, B., Monnez, J.-M., Padilla, C., et al. (2013) A Statistical Procedure to Create a Neighborhood Socioeconomic Index for Health Inequalities Analysis. International Journal for Equity in Health, 12, 21.
http://dx.doi.org/10.1186/1475-9276-12-21 [11] Padilla, C., Lalloué, B., Pies, C., et al. (2013) An Ecological Study to Identify Census Blocks Supporting a Higher Burden of Disease: Infant Mortality in the Lille Metropolitan Area, France. Maternal and Child Health Journal, 17, 1-9. http://dx.doi.org/10.1007/s10995-013-1251-8 [12] Padilla, C.M., Deguen, S., Lalloue, B., et al. (2013) Cluster Analysis of Social and Environment Inequalities of Infant Mortality. A Spatial Study in Small Areas Revealed by Local Disease Mapping in France. Science of The Total Environment, 454-455, 433-441.
http://dx.doi.org/10.1016/j.scitotenv.2013.03.027 [13] R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna Austria Published Online First: http://www.R-project.org [14] Husson, F., Josse, J., Le, S. and Mazet, J. (2013) FactoMineR: Multivariate Exploratory Data Analysis and Data Mining with R. R Package Version 1.25. http://CRAN.R-project.org/package=FactoMineR. [15] Lê, S., Josse, J. and Husson, F. (2008) FactoMineR: An R Package For multivariate Analysis. Journal of Statistical Software, 25, 1-18. [16] Venables, W.N. and Ripley, B.D. (2002) Modern Applied Statistics with S. 4th Edition. Springer, NY. http://www.stats.ox.ac.uk/pub/MASS4 http://dx.doi.org/10.1007/978-0-387-21706-2
[1] Jarman, B. (1983) Identification of Underprivileged Areas. British Medical Journal (Clinical Research Ed.), 286, 1705-1709. http://dx.doi.org/10.1136/bmj.286.6379.1705 [2] Morris, R. and Carstairs, V. (1991) Which Deprivation? A Comparison of Selected Deprivation Indexes. Journal of Public Health, 13, 318-326. [3] Carstairs, V. (1995) Deprivation Indices: Their Interpretation and Use in Relation to Health. Journal of Epidemiology & Community Health, 49, S3-S8. http://dx.doi.org/10.1136/jech.49.Suppl_2.S3 [4] Salmond, C., Crampton, P. and Sutton, F. (1998) NZDep91: A New Zealand Index of Deprivation. Australian and New Zealand Journal of Public Health, 22, 835-837.
http://dx.doi.org/10.1111/j.1467-842X.1998.tb01505.x [5] Eibner, C. and Sturm, R. (2006) US-Based Indices of Area-Level Deprivation: Results from Health Care for Communities. Social Science & Medicine, 62, 348-359.
http://dx.doi.org/10.1016/j.socscimed.2005.06.017 [6] Messer, L.C., Laraia, B.A., Kaufman, J.S., et al. (2006) The Development of a Standardized Neighborhood Deprivation Index. Journal of Urban Health, 83, 1041-1062.
http://dx.doi.org/10.1007/s11524-006-9094-x [7] Bell, N., Schuurman, N. and Hayes, M.V. (2007) Using GIS-Based Methods of Multicriteria Analysis to Construct Socio-Economic Deprivation Indices. International Journal of Health Geographics, 6, 17.
http://dx.doi.org/10.1186/1476-072X-6-17 [8] Fukuda, Y., Nakamura, K. and Takano, T. (2007) Higher Mortality in Areas of Lower Socioeconomic Position Measured by a Single Index of Deprivation in Japan. Public Health, 121, 163-173.
http://dx.doi.org/10.1016/j.puhe.2006.10.015 [9] Pampalon, R., Hamel, D., Gamache, P., et al. (2009) A Deprivation Index for Health Planning in Canada. Chronic diseases in Canada, 29, 178-191. [10] Lalloué, B., Monnez, J.-M., Padilla, C., et al. (2013) A Statistical Procedure to Create a Neighborhood Socioeconomic Index for Health Inequalities Analysis. International Journal for Equity in Health, 12, 21.
http://dx.doi.org/10.1186/1475-9276-12-21 [11] Padilla, C., Lalloué, B., Pies, C., et al. (2013) An Ecological Study to Identify Census Blocks Supporting a Higher Burden of Disease: Infant Mortality in the Lille Metropolitan Area, France. Maternal and Child Health Journal, 17, 1-9. http://dx.doi.org/10.1007/s10995-013-1251-8 [12] Padilla, C.M., Deguen, S., Lalloue, B., et al. (2013) Cluster Analysis of Social and Environment Inequalities of Infant Mortality. A Spatial Study in Small Areas Revealed by Local Disease Mapping in France. Science of The Total Environment, 454-455, 433-441.
http://dx.doi.org/10.1016/j.scitotenv.2013.03.027 [13] R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna Austria Published Online First: http://www.R-project.org [14] Husson, F., Josse, J., Le, S. and Mazet, J. (2013) FactoMineR: Multivariate Exploratory Data Analysis and Data Mining with R. R Package Version 1.25. http://CRAN.R-project.org/package=FactoMineR. [15] Lê, S., Josse, J. and Husson, F. (2008) FactoMineR: An R Package For multivariate Analysis. Journal of Statistical Software, 25, 1-18. [16] Venables, W.N. and Ripley, B.D. (2002) Modern Applied Statistics with S. 4th Edition. Springer, NY. http://www.stats.ox.ac.uk/pub/MASS4 http://dx.doi.org/10.1007/978-0-387-21706-2