A French classification to describe medical deserts: a multi-professional approach based on the first contact with the healthcare system.

BACKGROUND: Increasing inequalities in accessibility to primary care has generated medical deserts. Identifying them is key to target the geographic areas where action is needed. An extensive definition of primary care has been promoted by the World Health Organization: a first level of contact with the health system, which involves the co-presence of different categories of health professionals alongside the general practitioner for the diagnosis and treatment of patients. Previous analyses have focused mainly on a single type of provider while this study proposes an integrated approach including various ones to define medical deserts in primary care. METHOD: Our empirical approach focuses on the first point of contact with the health system: general practitioners, proximity primary care providers (nurses, physiotherapists, pharmacies, laboratories, and radiologists), and emergency services. A multiple analysis approach was performed, to classify French municipalities using the information on the evolution and needs of health care accessibility, combining a principal component analysis and a hierarchical ascending classification. RESULTS: Two clusters of medical deserts were identified with low accessibility to all healthcare professionals, socio-economic disadvantages, and a decrease in care supply. In other clusters, accessibility difficulties only concern a part of the health supply considered, which raises concern for the efficiency of primary care for optimal healthcare pathways. Even for clusters with better accessibility, issues were identified, such as a decrease and high needs of health care supply, revealing potential future difficulties. CONCLUSION: This work proposes a multi-professional and multi-dimensional approach to medical deserts based mainly on an extensive definition of primary care that shows the relevance of the co-presence of various healthcare professionals. The classification also makes it possible to identify areas with future problems of accessibility and its potential consequences. This framework could be easily applied to other countries according to their available data and their health systems' specificities.

Role of mammography accessibility, deprivation and spatial effect in breast cancer screening participation in France: an observational ecological study.

BACKGROUND: The detection of cancer in its early latent stages can improve patients' chances of recovery and thereby reduce the overall burden of the disease. Our objectives were to investigate factors (geographic accessibility and deprivation level) affecting mammography screening participation variation and to determine how much geographic variation in participation rates can be explained by spillover effects between adjacent areas, while controlling for covariates. METHODS: Mammography screening participation rates between 2015 and 2016 were calculated by census blocks (CB), for women aged 50-74 years, residing in Lyon metropolitan area. Global spatial autocorrelation tests were applied to identify the geographic variation of participation. Spatial regression models were used to incorporate spatial structure to estimate associations between mammography participation rate and the combined effect (geographic accessibility and deprivation level) adjusting for modes of travel and social cohesion. RESULTS: The mammography participation rate was found to have a statistically significant and positive spatial correlation. The participation rate of one CB was significantly and positively associated with the participation rates of neighbouring CB. The participation was 53.2% in residential and rural areas and 46.6% in urban areas, p < 0.001. Using Spatial Lag models, whereas the population living in most deprived CBs have statistically significantly lower mammography participation rates than lower deprived ones, significant interaction demonstrates that the relation differs according to the degree of urbanization. CONCLUSIONS: This study makes an important methodological contribution in measuring geographical access and understanding better the combined effect of deprivation and the degree of urbanization on mammography participation and other contextual factors that affect the decision of using mammography screening services -which is a critical component of healthcare planning and equity.

Geographical Ambulatory Endovascular Revascularisation Disparities in France From 2015 to 2019.

OBJECTIVE: Despite efficiency and safety evidence, ambulatory endovascular revascularisation for lower extremity arterial disease (LEAD) accounted for only 5% of interventions in France in 2016. Such a low rate suggests temporal and geographical space disparities. The aim of this study was to describe the space-time development of ambulatory endovascular revascularisation for LEAD in France and to investigate the contributions of healthcare services and population characteristics as potential determinants. METHODS: A retrospective study of discharge data from French hospitals that performed endovascular procedures for LEAD between 2015 and 2019 was conducted. Space-time analyses with Moran's Index, zero inflated Poisson regression, and clustering approaches were applied. Spatial clusters were compared on the basis of healthcare services and population characteristics (including poverty and single man household as proxies of social isolation). RESULTS: Between 2015 and 2019, the number of ambulatory interventions tripled (1 104 vs.3 130). Of the 86 French departments, the proportion with >5% of ambulatory interventions increased from 10.7% to 28.7% over the study period. In 2019, ambulatory activity in French departments ranged from 0% to 39%. This change was accompanied by a northwest to northeast spatial trend. The clusters of 27 departments with substantial ambulatory activity differed from the others notably by the mortality rate of lower limb arterial thromboembolic diseases in males (OR 3.15, 95% CI 1.2-8.1), the proportion of single man households of age ≥75 (OR 0.37, 95% CI 0.2-0.8), and the poverty rate of people aged 50-59 years (OR 0.69, 95% CI 0.5-0.9). CONCLUSIONS: The development of ambulatory interventions for LEAD in France is encouraging but heterogeneous. Some determinants of this evolution are clearly population based, with a positive impact of needs to take care of the burden of LEAD but negative effects of social isolation and poverty. Research should be conducted to overcome some patient constraints such as isolation.

Gender difference of geographic distribution of the stroke incidence affected by socioeconomic, clinical and urban-rural factors: an ecological study based on data from the Brest stroke registry in France.

BACKGROUND: Mapping the spatial distribution of disease occurrence is a strategy to identify contextual factors that could be useful for public health policies. The purpose of this ecological study was to examine to which extent the socioeconomic deprivation and the urbanization level can explain gender difference of geographic distribution in stroke incidence in Pays de Brest, France between 2008 and 2013. METHODS: Stroke cases aged 60 years or more were extracted from the Brest stroke registry and combined at the census block level. Contextual socioeconomic, demographic, and geographic variables at the census block level come from the 2013 national census. We used spatial and non-spatial regression models to study the geographic correlation between socioeconomic deprivation, degree or urbanization and stroke incidence. We generated maps using spatial geographically weighted models, after longitude and latitude smoothing and adjustment for covariates. RESULTS: Stroke incidence was comparable in women and men (6.26 ± 3.5 vs 6.91 ± 3.3 per 1000 inhabitants-year, respectively). Results showed different patterns of the distribution of stroke risk and its association with deprivation or urbanisation across gender. For women, stroke incidence was spatially homogeneous over the entire study area, but was associated with deprivation level in urban census blocks: age adjusted risk ratio of high versus low deprivation = 1.24, [95%CI 1.04-1.46]. For men, three geographic clusters were identified. One located in the northern rural and deprived census blocks with a 9-14% increase in the risk of stroke. Two others clusters located in the south-eastern (mostly urban part) and south-western (suburban and rural part) with low deprivation level and associated with higher risk of stroke incidence between (3 and 8%) and (8.5 and 19%) respectively. There were no differences in profile of cardiovascular risk factors, stroke type and stroke severity between clusters, or when comparing clusters cases to the rest of the study population. CONCLUSIONS: Understanding whether and how neighborhood and patient's characteristics influence stroke risk may be useful for both epidemiological research and healthcare service planning.

Stroke Incidence and Case Fatality According to Rural or Urban Residence: Results From the French Brest Stroke Registry.

Background and Purpose- Recent findings suggest that in the United States, stroke incidence is higher in rural than in urban areas. Similar analyses in other high-income countries are scarce with conflicting results. In 2008, the Brest Stroke Registry was started in western France, an area that includes about 366 000 individuals living in various urban and rural settings. Methods- All new patients with stroke included in the Brest Stroke Registry from 2008 to 2013 were classified as residing in town centers, suburbs, isolated towns, or rural areas. Poisson regression was used to analyze stroke incidence and 30-day case fatality variations in the 4 different residence categories. Models with case fatality as outcome were adjusted for age, stroke type, and stroke severity. Results- In total, 3854 incident stroke cases (n=2039 women, 53%) were identified during the study period. Demographic and socio-economic characteristics and primary healthcare access indicators were significantly different among the 4 residence categories. Patterns of risk factors, stroke type, and severity were comparable among residence categories in both sexes. Age-standardized stroke rates varied from 2.90 per thousand (95% CI, 2.59-3.21) in suburbs to 3.35 (95% CI, 2.98-3.73) in rural areas for men, and from 2.14 (95% CI, 2.00-2.28) in town centers to 2.34 (95% CI, 2.12-2.57) in suburbs for women. Regression models suggested that among men, stroke incidence was significantly lower in suburbs than in town centers (incidence rate ratio =0.87; 95% CI, 0.77-0.99). Case fatality risk was comparable across urban categories but lower in rural patients (relative risk versus town centers: 0.76; 95% CI, 0.60-0.96). Conclusions- Stroke incidence was comparable, and the 30-day case fatality only slightly varied in the 4 residence categories despite widely different socio-demographic features covered by the Brest Stroke Registry.

Mapping Variation in Breast Cancer Screening: Where to Intervene?

Small geographic areas with lower mammography screening participation rates may reflect gaps in screening efforts. Our objective was to use spatial analyses to understand disparities in mammography screening use and to identify factors to increase its uptake in areas that need it in Lyon metropolitan area, France. Data for screened women between the ages of 50 and 74 were analyzed. Census blocks of screened and non screened women were extracted from the mammography screening programme 2015-2016 dataset. We used spatial regression models, within a generalized additive framework to determine clusters of census blocks with significantly higher prevalence of non-participation of mammography screening. Smoothed risk maps were crude and adjusted on the following covariates: deprivation index and opportunistic screening. Among 178,002 women aged 50 to 74, 49.9% received mammography screening. As hypothesized, women living in highly deprived census blocks had lower participation rates compared to less deprived blocks, 45.2% vs. 51.4% p < 0.001. Spatial analyses identified four clusters, one located in an urban area and three in suburban areas. Moreover, depending on the location of the cluster, the influence came from different variables. Knowing the impact of site-specific risk factors seems to be important for implementing an appropriate prevention intervention.

Geographic Variations in the Risk of Emergency First Dialysis for Patients with End Stage Renal Disease in the Bretagne Region, France.

Emergency first dialysis start considerably increases the risk of morbidity and mortality. Our objective was to identify the geographic variations of emergency first dialysis risk in patients with end-stage renal disease in the Bretagne region, France. The spatial scan statistic approach was used to determine the clusters of municipalities with significantly higher or lower risk of emergency first dialysis. Patient data extracted from the REIN registry (sociodemographic, clinical, and biological characteristics) and indicators constructed at the municipality level, were compared between clusters. This analysis identified a cluster of municipalities in western Bretagne with a significantly higher risk (RR = 1.80, p = 0.044) and one cluster in the eastern part of the region with a significantly lower risk (RR = 0.59, p < 0.01) of emergency first dialysis. The degree of urbanization (the proportion of rural municipalities: 76% versus 66%, p < 0.001) and socio-demographic characteristics (the unemployment rate: 11% versus 8%, p < 0.001, the percentage of managers in the labor force was lower: 9% versus 13% p < 0.001) of the municipalities located in the higher-risk cluster compared with the lower-risk cluster. Our analysis indicates that the patients' clinical status cannot explain the geographic variations of emergency first dialysis incidence in Bretagne. Conversely, where patients live seems to play an important role.

Revisiting human T-cell lymphotropic virus types 1 and 2 infections among rural population in Gabon, central Africa thirty years after the first analysis.

HTLV-1 infection is considered as highly endemic in central Africa. Thirty years ago, a first epidemiological study was performed in Gabon, central Africa, and revealed that the prevalence varied from 5.0 to 10.5%. To evaluate current distribution of HTLVs in Gabon, 4.381 samples were collected from rural population living in 220 villages distributed within the 9 provinces of country. HTLVs prevalence was determined using two ELISA tests and positive results were confirmed by Western Blot. The overall HTLV-1 seroprevalence was of 7.3% among the rural Gabonese population; with 5.4% for men and 9.0% for women. Prevalence of HTLV-1 differed by province, ranging from 2.3% to 12.5% into the rain forest. Being a woman older than 51 years represented a high risk for HTLV-1 acquisition. Hospitalization, operation/surgery, transfusion and medical abortion or fever, arthritis and abdominal pain are also significant risk factors. In addition, 0.1% of samples were found as HTLV-2 positive, while 12.0% had an indeterminate HTLV serological pattern. HTLV-3 and HTLV-4 were not found. Phylogenetic analysis was performed on 87 samples and demonstrated that HTLV-1 present in Gabon belongs mostly to subtype B, however the rare subtype D was also found. Altogether, our results demonstrate that almost thirty years after the first epidemiological study prevention of HTLVs infection is still an issue in Gabon.

Do Individual and Neighborhood Characteristics Influence Perceived Air Quality?

Background: Despite improvements, air pollution still remains a major public health issue. Numerous epidemiological studies have demonstrated the adverse health effects of air pollution exposure based on modeled measures, but only a few have considered the health impact of perceived air quality. Improving our knowledge of individual perceptions is crucial to defining targeted actions and promoting appropriate intervention measures. Our objective is to investigate the relationship between subjective and objective measures of air pollution and to focus on how individual characteristics combined with the neighborhood socioeconomic deprivation index, measured at a fine spatial scale, may or may not alter this relationship. Materials and Methods: The subjective measures of air quality reported by a sample of Lyon residents were collected via an individual questionnaire. The objective measures of air pollution were modeled by the local air quality monitoring network of the Rhône-Alpes region at census block level. We used a socioeconomic deprivation index to capture the different socioeconomic dimensions at census block level. The statistical analysis was structured in two steps: (1) identification of individual determinants of the subjective measures of air quality using multiple correspondence analysis followed by hierarchical clustering; (2) identification of individual and contextual characteristics that may alter the relationship between the objective and subjective measures of air pollution. Results: Among the youngest and the middle aged population (ages 30 to 59), consistent results between level of satisfaction, perceived air quality and objective measures of air pollution were found whatever the individual characteristics of the population. It is less clear among the oldest population: globally no significant difference between the NO2 concentrations and the level of satisfaction was observed. Conclusions: We found a significant relationship between the subjective and objective measures of air pollution in many population sub-groups with different combinations of individual characteristics. The relationship is less clear among the oldest population, which confirms previous findings. Our finding highlights that age combined with low level of education and unemployment, or women or health problems as well as the neighborhood deprivation index influence the level of air quality satisfaction.

Systematic literature review of reproductive outcome associated with residential proximity to polluted sites.

This study aims to assess the evidence on adverse pregnancy outcome associated with living close to polluted industrial sites, and identify the strengths and weaknesses of published epidemiological studies. A systematic literature search has been performed on all epidemiological studies published in developed countries since 1990, on the association between residential proximity to industrial sites (hazardous waste sites, industrial facilities and landfill sites) and adverse pregnancy outcome (low birth weight, preterm birth, small for gestational age, intrauterine growth retardation, infant mortality, congenital malformation). Based on 41 papers, our review reveals an excess risk of reproductive morbidity. However, no studies show significant excess risk of mortality including fetal death, neonatal or infant mortality and stillbirth. All published studies tend to show an increased risk of congenital abnormalities, yet not all are statistically significant. All but two of these studies revealed an excess risk of low birth weight. Results for preterm birth, small for gestational age and intrauterine growth retardation show the same pattern. There is suggestive evidence from the post-1990 literature that residential proximity to polluted sites (including landfills, hazardous waste sites and industrial facilities) might contribute to adverse reproductive outcomes, especially congenital malformations and low birth weight-though not mortality. This body of evidence has limitations that impede the formulation of firm conclusions, and new, well-focused studies are called for. The review findings suggest that continued strengthening of rules governing industrial emissions as well as industrial waste management and improved land use planning are needed.

The need for, and value of, a spatial scan statistical tool for tackling social health inequalities.

Today, one important challenge in developed countries is health inequalities. Research conducted in public health policy issues supply little evidence for effective interventions aiming to improve population health and to reduce health inequalities. There is a need for a powerful tool to support priority setting and guide policy makers in their choice of health interventions, and that maximizes social welfare. This paper proposes to divert a spatial tool based on Kulldorff's scan method to investigate social inequalities in health. This commentary argues that this spatial approach can be a useful tool to tackle social inequalities in health by guiding policy makers at three levels: (i) supporting priority setting and planning a targeted intervention; (ii) choosing actions or interventions which will be performed for the whole population, but with a scale and intensity proportionate to need; and (iii) assessing health equity of public interventions.

Neighborhood Deprivation and Risk of Congenital Heart Defects, Neural Tube Defects and Orofacial Clefts: A Systematic Review and Meta-Analysis.

BACKGROUND: We conducted this systematic review and meta-analysis to address the open question of a possible association between the socioeconomic level of the neighborhoods in which pregnant women live and the risk of Congenital Heart Defects (CHDs), Neural Tube Defects (NTDs) and OroFacial Clefts (OFCs). METHODS: We searched MEDLINE from its inception to December 20th, 2015 for case-control, cohort and ecological studies assessing the association between neighborhood socioeconomic level and the risk of CHDs, NTDs and the specific phenotypes Cleft Lip with or without Cleft Palate (CLP) and Cleft Palate (CP). Study-specific risk estimates were pooled according to random-effect and fixed-effect models. RESULTS: Out of 245 references, a total of seven case-control studies, two cohort studies and two ecological studies were assessed in the systematic review; all studies were enrolled in the meta-analysis with the exception of the two cohort studies. No significant association has been revealed between CHDs or NTDs and neighborhood deprivation index. For CLP phenotype subgroups, we found a significantly higher rate in deprived neighborhoods (Odds Ratios (OR) = 1.22, 95% CI: 1.10, 1.36) whereas this was not significant for CP phenotype subgroups (OR = 1.20, 95%CI: 0.89, 1.61). CONCLUSION: In spite of the small number of epidemiological studies included in the present literature review, our findings suggest that neighborhood socioeconomic level where mothers live is associated only with an increased risk of CLP phenotype subgroups. This finding has methodological limitations that impede the formulation of firm conclusions, and further investigations should confirm this association.

Use of geographic indicators of healthcare, environment and socioeconomic factors to characterize environmental health disparities.

BACKGROUND: An environmental health inequality is a major public health concern in Europe. However just few studies take into account a large set of characteristics to analyze this problematic. The aim of this study was to identify and describe how socioeconomic, health accessibility and exposure factors accumulate and interact in small areas in a French urban context, to assess environmental health inequalities related to infant and neonatal mortality. METHODS: Environmental indicators on deprivation index, proximity to high-traffic roads, green space, and healthcare accessibility were created using the Geographical Information System. Cases were collected from death certificates in the city hall of each municipality in the Nice metropolitan area. Using the parental addresses, cases were geocoded to their census block of residence. A classification using a Multiple Component Analysis following by a Hierarchical Clustering allow us to characterize the census blocks in terms of level of socioeconomic, environmental and accessibility to healthcare, which are very diverse definition by nature. Relation between infant and neonatal mortality rate and the three environmental patterns which categorize the census blocks after the classification was performed using a standard Poisson regression model for count data after checking the assumption of dispersion. RESULTS: Based on geographic indicators, three environmental patterns were identified. We found environmental inequalities and social health inequalities in Nice metropolitan area. Moreover these inequalities are counterbalance by the close proximity of deprived census blocks to healthcare facilities related to mother and newborn. So therefore we demonstrate no environmental health inequalities related to infant and neonatal mortality. CONCLUSION: Examination of patterns of social, environmental and in relation with healthcare access is useful to identify census blocks with needs and their effects on health. Similar analyzes could be implemented and considered in other cities or related to other birth outcomes.

City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France.

Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease-a leading cause of infant mortality.

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale.

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects' residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO2 following two steps: (i) retrospective reconstitution of NO2 concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs.

Evolution of research in health geographics through the International Journal of Health Geographics (2002-2015).

Health geographics is a fast-developing research area. Subjects broached in scientific literature are most varied, ranging from vectorial diseases to access to healthcare, with a recent revival of themes such as the implication of health in the Smart City, or a predominantly individual-centered approach. Far beyond standard meta-analyses, the present study deliberately adopts the standpoint of questioning space in its foundations, through various authors of the International Journal of Health Geographics, a highly influential journal in that field. The idea is to find space as the common denominator in this specialized literature, as well as its relation to spatial analysis, without for all that trying to tend towards exhaustive approaches. 660 articles have being published in the journal since launch, but 359 articles were selected based on the presence of the word "Space" in either the title, or the abstract or the text over 13 years of the journal's existence. From that database, a lexical analysis (tag cloud) reveals the perception of space in literature, and shows how approaches are evolving, thus underlining that the scope of health geographics is far from narrowing.

Neighbourhood Characteristics and Long-Term Air Pollution Levels Modify the Association between the Short-Term Nitrogen Dioxide Concentrations and All-Cause Mortality in Paris.

BACKGROUND: While a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France). METHODS: A time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866). RESULTS: The mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p<0.001). Among these deprived census blocks, excess risk was even higher where long-term average NO2 concentrations were above 55.8 µg/m3 (the top tercile of distribution): ER=4.84% (95%CI=[1.56;8.24], p for interaction=0.02). CONCLUSION: Our results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO2 levels.

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

BACKGROUND: Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. METHODS: All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. RESULTS: The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. CONCLUSIONS: Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Data analysis techniques: a tool for cumulative exposure assessment.

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.