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.

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.

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.

Air quality and social deprivation in four French metropolitan areas--a localized spatio-temporal environmental inequality analysis.

Several studies have documented that more deprived populations tend to live in areas characterized by higher levels of environmental pollution. Yet, time trends and geographic patterns of this disproportionate distribution of environmental burden remain poorly assessed, especially in Europe. We investigated the spatial and temporal relationship between ambient air nitrogen dioxide (NO2) concentrations and socioeconomic and demographic data in four French metropolitan areas (Lille in the North, Lyon in the center, Marseille in the South, and Paris) during two different time periods. The geographical unit used was the census block. The dependent variable was the NO2 annual average concentration (µg/m(3)) per census block, and the explanatory variables were a neighborhood deprivation index and socioeconomic and demographic data derived from the national census. Generalized additive models were used to account for spatial autocorrelation. We found that the strength and direction of the association between deprivation and NO2 estimates varied between cities. In Paris, census blocks with the higher social categories are exposed to higher mean concentrations of NO2. However, in Lille and Marseille, the most deprived census blocks are the most exposed to NO2. In Lyon, the census blocks in the middle social categories were more likely to have higher concentrations than in the lower social categories. Despite a general reduction in NO2 concentrations over the study period in the four metropolitan areas, we found contrasting results in the temporal trend of environmental inequalities. There is clear evidence of city-specific spatial and temporal environmental inequalities that relate to the historical socioeconomic make-up of the cities and its evolution. Hence, general statements about environmental and social inequalities can be made.

An exploratory spatial analysis to assess the relationship between deprivation, noise and infant mortality: an ecological study.

BACKGROUND: Few studies have explored how noise might contribute to social health inequalities, and even fewer have considered infant mortality or its risk factors as the health event of interest.In this paper, we investigate the impact of neighbourhood characteristics - both socio-economic status and ambient noise levels - on the spatial distribution of infant mortality in the Lyon metropolitan area, in France. METHODS: All infant deaths (n = 715) occurring between 2000 and 2009 were geocoded at census block level. Each census block was assigned multi-component socio-economic characteristics and Lden levels, which measure exposure to noise. Using a spatial-scan statistic, we examined whether there were significant clusters of high risk of infant mortality according to neighbourhood characteristics. RESULTS: Our results highlight the fact that infant mortality is non-randomly distributed spatially, with clusters of high risk in the south-east of the Lyon metropolitan area (RR = 1.44; p = 0.09). After adjustments for socio-economic characteristics and noise levels, this cluster disappears or shifts according to in line with different scenarios, suggesting that noise and socio-economic characteristics can partially explain the spatial distribution of infant mortality. CONCLUSION: Our findings show that noise does have an impact on the spatial distribution of mortality after adjustments for socio-economic characteristics. A link between noise and infant mortality seems plausible in view of the three hypothetical, non-exclusive, pathways we propose in our conceptual framework: (i) a psychological pathway, (ii) a physiological disruption process and (iii) an unhealthy behaviours pathway. The lack of studies makes it is difficult to compare our findings with others. They require further research for confirmation and interpretation.

Green space, social inequalities and neonatal mortality in France.

BACKGROUND: Few studies have considered using environmental amenities to explain social health inequalities.Nevertheless, Green spaces that promote good health may have an effect on socioeconomic health inequalities. In developed countries, there is considerable evidence that green spaces have a beneficial effect on the health of urban populations and recent studies suggest they can have a positive effect on pregnancy outcomes. To investigate the relationship between green spaces and the spatial distribution of infant mortality taking account neighborhood deprivation levels. METHODS: The study took place in Lyon metropolitan area, France. All infant deaths that occurred between 2000 and 2009 were geocoded at census block level. Each census block was assigned greenness and socioeconomic deprivation levels. The spatial-scan statistic was used to identify high risk cluster of infant mortality according to these neighborhood characteristics. RESULTS: The spatial distribution of infant mortality was not random with a high risk cluster in the south east of the Lyon metropolitan area (p<0.003). This cluster disappeared (p=0.12) after adjustment for greenness level and socioeconomic deprivation, suggesting that these factors explain part of the spatial distribution of infant mortality. These results are discussed using a conceptual framework with 3 hypothetical pathways by which green spaces may have a beneficial effect on adverse pregnancy outcomes: (i) a psychological pathway, (ii) a physiological disruption process and (iii) an environmental pathway. CONCLUSIONS: These results add some evidence to the hypothesis that there is a relationship between access to green spaces and pregnancy outcomes but further research is required to confirm this.

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.

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.

Cluster analysis of social and environment inequalities of infant mortality. A spatial study in small areas revealed by local disease mapping in France.

Mapping spatial distributions of disease occurrence can serve as a useful tool for identifying exposures of public health concern. Infant mortality is an important indicator of the health status of a population. Recent literature suggests that neighborhood deprivation status can modify the effect of air pollution on preterm delivery, a known risk factor for infant mortality. We investigated the effect of neighborhood social deprivation on the association between exposure to ambient air NO2 and infant mortality in the Lille and Lyon metropolitan areas, north and center of France, respectively, between 2002 and 2009. We conducted an ecological study using a neighborhood deprivation index estimated at the French census block from the 2006 census data. Infant mortality data were collected from local councils and geocoded using the address of residence. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. The average death rate was 4.2‰ and 4.6‰ live births for the Lille and Lyon metropolitan areas during the period. We found evidence of statistically significant precise clusters of elevated infant mortality for Lille and an east-west gradient of infant mortality risk for Lyon. Exposure to NO2 did not explain the spatial relationship. The Lille MA, socioeconomic deprivation index explained the spatial variation observed. These techniques provide evidence of clusters of significantly elevated infant mortality risk in relation with the neighborhood socioeconomic status. This method could be used for public policy management to determine priority areas for interventions. Moreover, taking into account the relationship between social and environmental exposure may help identify areas with cumulative inequalities.