ArticleBMC public health2019
Using ecological socioeconomic position (SEP) measures to deal with sample bias introduced by incomplete individual-level measures: inequalities in breast cancer stage at diagnosis as an example.
Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Socioeconomic deprivation, disease complications and access to preventive care in sickle cell disease in mainland France.Annals of hematology · 2026Article
- Dynamics of social inequalities in severe COVID-19 outcomes in metropolitan France from 2020 to 2022.Communications medicine · 2025Article
- Mapping the costs and socioeconomic characteristics involved in traumatic brain injuries: a scoping review.Journal of rehabilitation medicine · 2024Article
- Educational level and characteristics of invasive breast cancer: findings from a French prospective cohort.Cancer causes & control : CCC · 2024Article
- Article
- Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias.medRxiv : the preprint server for health sciences · 2024Article
- Socioeconomic and geographic disparities of breast cancer incidence according to stage at diagnosis in France.Cancer causes & control : CCC · 2024Article
- Assessing How Social Exposures Are Integrated in Exposome Research: A Scoping Review.Environmental health perspectives · 2022Article
- The effect of social deprivation on the dynamic of SARS-CoV-2 infection in France: a population-based analysis.The Lancet. Public health · 2022Article
- Importance of collecting data on socioeconomic determinants from the early stage of the COVID-19 outbreak onwards.Journal of epidemiology and community health · 2020Review
- Spatiotemporal ecological study of COVID-19 mortality in the city of São Paulo, Brazil: Shifting of the high mortality risk from areas with the best to those with the worst socio-economic conditions.Travel medicine and infectious diseaseArticle
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Abstract
backgroundWhen studying the influence of socioeconomic position (SEP) on health from data where individual-level SEP measures may be missing, ecological measures of SEP may prove helpful. In this paper, we illustrate the best use of ecological-level measures of SEP to deal with incomplete individual level data. To do this we have taken the example of a study examining the relationship between SEP and breast cancer (BC) stage at diagnosis.
methodsUsing population based-registry data, all women over 18 years newly diagnosed with a primary BC in 2007 were included. We compared the association between advanced stage at diagnosis and individual SEP containing missing data with an ecological level SEP measure without missing data. We used three modelling strategies, 1/ based on patients with complete data for individual-SEP (n = 1218), or 2/ on all patients (n = 1644) using an ecological-level SEP as proxy for individual SEP and 3/ individual-SEP after imputation of missing data using an ecological-level SEP.
resultsThe results obtained from these models demonstrate that selection bias was introduced in the sample where only patients with complete individual SEP were included. This bias is redressed by using ecological-level SEP to impute missing data for individual SEP on all patients. Such a strategy helps to avoid an ecological bias due to the use of aggregated data to infer to individual level.
conclusionWhen individual data are incomplete, we demonstrate the usefulness of an ecological index to assess and redress potential selection bias by using it to impute missing individual SEP.
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