ArticleBMC women's health2021
Using geographically weighted Poisson regression to examine the association between socioeconomic factors and hysterectomy incidence in Wallonia, Belgium.
Article in BMC women's health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 8 citations in OpenAlex.
- Spatiotemporal distribution of sustained dengue hotspots associated with climate and urbanisation in Singapore.Scientific reports · 2025Article
- Analysis of the Relationship between Socioeconomic Status and Incidence of Hysterectomy Using Data of the Korean Genome and Epidemiology Study (KoGES).Healthcare (Basel, Switzerland) · 2022Article
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6 authors at 2 institutions in 2 countries.
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Abstract
backgroundVarious studies have investigated geographical variations in the incidence of hysterectomy in Western countries and analyzed socioeconomic factors to explain those variations. However, few studies have used spatial analysis to characterize them. Geographically weighted Poisson regression (GWPR) explores the spatially varying impacts of covariates across a study area and focuses attention on local variations. Given the potential of GWPR to guide decision-making, this study aimed to describe the geographical distribution of hysterectomy incidence for benign indications in women older than 15 years old (15+) at the municipal level in Wallonia (southern region of Belgium) and to analyze potential associations with socioeconomic factors ('Education/training', 'Income and purchasing power' and 'Health and care') influencing the use of this surgery.
methodsWe carried out an ecological study on data for women aged 15+ living in one of the 262 Walloon municipalities who underwent hysterectomies for benign indications between 2012 and 2014. We linked standardized hysterectomy rates to three municipal-level socioeconomic factors ('Education/training', 'Income and purchasing power' and 'Health and care'). Then, a Poisson regression model and a GWPR were applied to study the relationships between hysterectomy incidence and socioeconomic covariates in Wallonia.
resultsThe hysterectomy rate varied across the region. The Poisson regression revealed a positive and significant association between the hysterectomy rate and 'Income and purchasing power', and a negative and significant association between hysterectomies and 'Health and care'. The same associations were seen in the GWPR model. The latter demonstrated that the association between hysterectomies and 'Education and training' ranged from negative to positive over the study area.
conclusionsHysterectomy incidence was shown to have nonstationary relationships with socioeconomic factors. These results support the development of targeted interventions for a more appropriate use of this surgery.
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