Dataset Information

Increasing incidence and spatial hotspots of hospitalized endometriosis in France from 2011 to 2017.

ABSTRACT: Endometriosis is a female hormone-dependent disease, possibly related to endocrine disruptor exposure. We aimed to monitor this disease nationwide in France and analyze spatial trends at a fine scale to explore possible environmental contributing risk factors. We conducted a retrospective national descriptive study from 2011 to 2017 in females aged 10 years old and over, using comprehensive hospital discharge data. Cases were identified using ICD-10 N80 codes and were localized at their municipality of residence. We defined incident cases as the first hospital stay of patients, without a stay in at least the previous 5 years. We performed statistical analyses according to age and type of endometriosis, and we modeled the temporal, spatial and spatiotemporal trends. We identified 207,462 incident cases of all-type hospitalized endometriosis (83,112 for non-adenomyosis cases). The crude incidence rate for the study period was 9.85/10,000 person-years (3.95/10,000 for non-adenomyosis cases). From 2011 to 2017, the risk of all-type endometriosis increased by 8.5% (95% CI: 3.9; 13.4) (by 3.6% (95% CI: 0.6; 6.8) for non-adenomyosis cases). The risk was geographically heterogeneous, with 20 high-risk hotspots, showing similar results for non-adenomyosis cases. Shifting practice patterns, improved awareness and healthcare disparities interlinked with environmental risk factors could explain these trends.

SUBMITTER: Le Moal J

PROVIDER: S-EPMC9050825 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Increasing incidence and spatial hotspots of hospitalized endometriosis in France from 2011 to 2017.

Le Moal Joëlle J Goria Sarah S Chesneau Julie J Fauconnier Arnaud A Kvaskoff Marina M De Crouy-Chanel Perrine P Kahn Vanessa V Daraï Emile E Canis Michel M

Scientific reports 20220428 1

Endometriosis is a female hormone-dependent disease, possibly related to endocrine disruptor exposure. We aimed to monitor this disease nationwide in France and analyze spatial trends at a fine scale to explore possible environmental contributing risk factors. We conducted a retrospective national descriptive study from 2011 to 2017 in females aged 10 years old and over, using comprehensive hospital discharge data. Cases were identified using ICD-10 N80 codes and were localized at their municipa ...[more]

PMID: 35484205

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Project description:BackgroundHuman migration facilitate the spread of tuberculosis (TB). Migrants face an increased risk of TB infection. In this study, we aim to explore the spatial inequity of sputum smear-positive pulmonary TB (SS + PTB) in China; and the spatial heterogeneity between SS + PTB and internal migration.MethodsNotified SS + PTB cases in 31 provinces in mainland China were obtained from the national web-based PTB surveillance system database. Internal migrant data were extracted from the report on China's migrant population development. Spatial autocorrelations were explored using the global Moran's statistic and local indicators of spatial association. The spatial variation in temporal trends was performed using Kulldorff's scan statistic. Fixed effect and spatial autoregressive models were used to explore the spatial inequity between SS + PTB and internal migration.ResultsA total of 2 380 233 SS + PTB cases were reported in China between 2011 and 2017, of which, 1 716 382 (72.11%) were male and 663 851 (27.89%) were female. Over 70% of internal migrants were from rural households and had lower income and less education. The spatial variation in temporal trend results showed that there was an 9.9% average annual decrease in the notification rate of SS + PTB from 2011 to 2017; and spatial clustering of SS + PTB cases was mainly located in western and southern China. The spatial autocorrelation results revealed spatial clustering of internal migration each year (2011-2017), and the clusters were stable within most provinces. Internal emigration, urban-to-rural migration and GDP per capita were significantly associated with SS + PTB, further, internal emigration could explain more variation in SS + PTB in the eastern region in mainland. However, internal immigration and rural-to-urban migration were not significantly associated with SS + PTB across China.ConclusionsOur study found the spatial inequity between SS + PTB and internal migration. Internal emigration, urban-to-rural migration and GDP per capita were statistically associated with SS + PTB; the negative association was identified between internal emigration, urban-to-rural migration and SS + PTB. Further, we found those migrants with lower income and less education, and most of them were from rural households. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migration.

Project description:BackgroundSuicide mortality is high in Japan and early interventional strategies to solve that problem are needed. An accurate evaluation of the regional status of current suicide mortality would be useful for community interventions. A few studies in Kanagawa prefecture, located next to Tokyo and with the second largest population in Japan, have identified spatial clusters of suicide mortality at regional levels. This study examined spatial clustering and clustering over time of such events using spatial data from regional statistics on suicide deaths.MethodsData were obtained from regional statistics (58 regions in Kanagawa prefecture) of the National Vital Statistics of Japan from 2011 to 2017. The standardized mortality ratio (SMR) and Empirical Bayes estimator for the SMR (EBSMR) were used as measures. Spatial clusters were examined by Kulldorff's circular spatial scan statistic, Tango-Takahashi's flexible spatial scan statistic and Tango's test. Linear regression and conditional autoregressive (CAR) models were used not only to adjust for covariates but also to estimate regional effects. The analyses were conducted for each year, inclusive.ResultsAmong male suicide deaths, being unemployed (50%) was most frequently related to suicide while among female health problem (50%) were frequent. Spatial clusters with significance detected by FlexScan, SatScan and Tango's test were few and varied somewhat according to the method used. Spatial clusters were detected in some regions including Kawasaki ward after adjustment by covariates. By the linear regression models, selected variables with significance were different between the sexes. For males, unemployment, family size, and proportion of higher education were detected for several of the years studied while for females, family size and divorce rate were detected over this period. These variables were also observed by the CAR model with 5 covariates. Regional effects were much clearer by considering the spatial parameter for both males and females and especially, Kawasaki ward was detected as a high risk region in many years.ConclusionThe present results detected some spatial clustering of suicide deaths within certain regions. Factors related to suicide deaths were also indicated. These results would provide important information in policy making for suicide prevention.

Dataset Information

Increasing incidence and spatial hotspots of hospitalized endometriosis in France from 2011 to 2017.

Publications

Increasing incidence and spatial hotspots of hospitalized endometriosis in France from 2011 to 2017.

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