Éditeur(s) : HAL CCSD Nature Publishing Group
Résumé : International audience
Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise, etc.or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare. We propose to use statistical factor and cluster analyses to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach in a large French metropolitan area. The study was carried out in the Great Lyon area (France, 1.2 M inhabitants) at the census Block Group (BG) scale. We used as environmental indicators ambient air NO2 annual concentrations, noise levels and proximity to green spaces, to industrial plants, to polluted sites and to road traffic. They were synthesized using Multiple Factor Analysis (MFA), a data-driven technique without a priori modeling, followed by a Hierarchical Clustering to create BG classes. The first components of the MFA explained, respectively, 30, 14, 11 and 9% of the total variance. Clustering in five classes group: (1) a particular type of large BGs without population; (2) BGs of green residential areas, with less negative exposures than average; (3) BGs of residential areas near midtown; (4) BGs close to industries; and (5) midtown urban BGs, with higher negative exposures than average and less green spaces. Other numbers of classes were tested in order to assess a variety of clustering. We present an approach using statistical factor and cluster analyses techniques, which seem overlooked to assess cumulative exposure in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.Journal of Exposure Science and Environmental Epidemiology advance online publication, 24 September 2014; doi:10.1038/jes.2014.66.
ISSN: 1559-0631

hal-01069587
https://hal.archives-ouvertes.fr/hal-01069587
https://hal.archives-ouvertes.fr/hal-01069587/document
https://hal.archives-ouvertes.fr/hal-01069587/file/Article_multiexpo_20140708_c.pdf
DOI : 10.1038/jes.2014.66

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
Background: The evaluation of geographical healthcare accessibility in residential areas provides crucial information to public policy. Traditional methods - such as Physician Population Ratios (PPR) or shortest travel time - offer only a one-dimensional view of accessibility. This paper developed an improved indicator: the Index of Spatial Accessibility (ISA) to measure geographical healthcare accessibility at the smallest available infra-urban level, that is, the Ilot Regroupe pour des Indicateurs Statistiques. Methods: This study was carried out in the department of Nord, France. Healthcare professionals are geolocalized using postal addresses available on the French state health insurance website. ISA is derived from an Enhanced Two-Step Floating Catchment Area (E2FCA). We have constructed a catchment for each healthcare provider, by taking into account residential building centroids, car travel time as calculated by Google Maps and the edge effect. Principal Component Analyses (PCA) were used to build a composite ISA to describe the global accessibility of different kinds of health professionals. Results: We applied our method to studying geographical healthcare accessibility for pregnant women, by selecting three types of healthcare provider: general practitioners, gynecologists and midwives. A total of 3587 healthcare providers are potentially able to provide care for inhabitants of the department of Nord. On average there are 92 general practitioners, 22 midwives and 21 gynecologists per 100,000 residents. The composite ISA for the three types of healthcare provider is 39 per 100,000 residents. A comparative analysis between ISA and physician-population ratios indicates that ISA represents a more even distribution whereas the physician-population ratios show an 'all-or-nothing' approach. Conclusion: ISA is a multidimensional and improved measure, which combines the volume of services relative to population size with the proximity of services relative to the population's location, available at the smallest feasible geographical scale. It could guide policy makers towards highlighting critical areas in need of more healthcare providers, and these areas should be earmarked for further knowledge-based policy making.
ISSN: 1475-9276

hal-01359567
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01359567
DOI : 10.1186/s12939-016-0411-z
PUBMED : 27485740

Éditeur(s) : HAL CCSD Scientific Research Publishing
Résumé : International audience
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.
ISSN: 2161-718X

hal-01161775
https://hal.archives-ouvertes.fr/hal-01161775
https://hal.archives-ouvertes.fr/hal-01161775/document
https://hal.archives-ouvertes.fr/hal-01161775/file/OJS_2015060814030742.pdf
DOI : 10.4236/ojs.2015.54031

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
Background - Pregnant women are a vulnerable population. Although regular follow-ups are recommended during pregnancy, not all pregnant women seek care. This pilot study wanted to assess whether the integration of data from administrative health information systems and socio-economic features allows identifying disparities in prenatal care trajectories.Methods - Prenatal care trajectories were extracted from the permanent sample of the French health insurance information system linked to the hospital discharge information system. The records of 2518 women who gave birth without complications in France in 2009 were analyzed. State sequence data analysis was performed to identify homogeneous groups of prenatal care trajectories. Socio-economic data were used to characterize their living environment.Results -We identified three groups of homogeneous prenatal care trajectories: (i) women with relatively high prenatal care consumption (~11 %), (ii) women with no prenatal care (~21 %), and (iii) women with an intermediate level of prenatal care (~66 %). Analysis of the socio-economic data demonstrated the association between disparities in prenatal care trajectories and the women’s living environment. Women with relatively high care consumption generally lived in socio-economically privileged areas (better education levels, employment status and housing conditions) compared with women with few or no prenatal care.Conclusions -Although ecological, our approach demonstrates that data from health administrative information systems could be used to describe prenatal care. However, more individual variables and an improvement of the data quality are needed to efficiently monitor the content and timing of prenatal care. Moreover, state sequence analysis, which was used in this context for the first time, proves to be an interesting approach to explore care trajectories. Finally, the integration of heterogeneous sources of data, including contextual information, might help identifying areas that require health promotion actions toward vulnerable populations, such as pregnant women.
ISSN: 1472-6963

hal-01169792
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01169792
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01169792/document
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01169792/file/Mining%20care%20trajectories%20using%20health%20administrative.pdf
DOI : 10.1186/s12913-015-0857-5