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1000
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Abstract/Summary
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Purpose!#!Differences in the risk of childhood central nervous system (CNS) tumors by socioeconomic status (SES) may enhance etiologic insights. We conducted a nationwide register-based case-control study to evaluate socioeconomic differences in the risk of childhood CNS tumors in Denmark and examined whether associations varied by different SES measures, time points of assessment, specific tumor types, and age at diagnosis.!##!Methods!#!We identified all children born between 1981 and 2013 and diagnosed with a CNS tumor at ages 0-19 years (n = 1,273) from the Danish Cancer Registry and sampled four individually matched controls per case (n = 5,086). We used conditional logistic regression models to estimate associations with individual-level and neighborhood-level socioeconomic measures.!##!Results!#!We observed elevated risks of ependymoma and embryonal CNS tumors in association with higher parental education (odds ratios (ORs) of 1.6-2.1 for maternal or paternal high education and ependymoma) and higher risk of all tumor types in association with higher maternal income, e.g., OR 1.93; 95% CI 1.05-3.52 for high versus low income for astrocytoma and other gliomas. Associations were often stronger in children diagnosed at ages 5-19 years. We found little evidence for an association with neighborhood SES.!##!Conclusion!#!This large nationwide register study with minimal risk of bias showed that having parents with higher educational level and a mother with higher income was associated with a higher risk of childhood CNS tumors. Bias or under-ascertainment of cases among families with low income or basic education is unlikely to explain our findings.
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1000
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Hinweis
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DeepGreen-ID: cde62907ca5d4910a5b8869944700d47 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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