title: Regional Deprivation and Non-Cancer Related Computed Tomography Use in Pediatric Patients in Germany: Cross-Sectional Analysis of Cohort Data.
abstract: BACKGROUND
  Conflicting findings were observed in recent studies assessing the association between patients' area-level socio-economic status and the received number of computed tomography (CT) examinations in children. The aim was to investigate the association between area-level socio-economic status and variation in CT examination practice for pediatric patients in Germany.
  
  
  METHODS
  Data from Radiology Information Systems for children aged 0 to < 15 years without cancer who had at least one CT examination between 2001 and 2010 were extracted in 20 hospitals across Germany. The small-area German Index of Multiple Deprivation (GIMD) was used to assess regional deprivation. The GIMD scores were classified into least, medium and most deprived areas and linked with the patient's last known postal code. A multinomial logistic regression model was used to assess the association between patients' CT numbers and regional deprivation adjusting for age, sex, and location of residence (urban/rural).
  
  
  RESULTS
  A total of 37,810 pediatric patients received 59,571 CT scans during the study period. 27,287 (72%) children received only one CT, while n = 885 (2.3%) received six or more. Increasing numbers of CT examinations in non-cancer patients were significantly associated with higher regional deprivation, which increased, although CI overlap, for higher CT categories: '2-3 CT' odds ratio (OR) = 1.45, 95%CI: 1.40-1.50; '4-5 CT' OR = 1.48, 95%CI: 1.38-1.59; '6+CT' OR = 1.54, 95%CI: 1.41-1.69. In addition, male sex, higher age categories, and specific body regions were positively associated with increased numbers of CT examinations.
  
  
  CONCLUSIONS
  We observed a positive association between regional deprivation and CT numbers in non-cancer pediatric patients. Limitations of the ecological approach and the lack of differentiation of CT details have to be acknowledged. More information on CT indications is necessary for a full assessment of this finding. In addition, further work on ways to assess socio-economic status more accurately may be required.
authors.affiliation: Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
authors.forename: Steffen
authors.initials: S
authors.lastname: Dreger
authors.affiliation: Institute for Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany.|International Agency for Research on Cancer, Lyon, France.
authors.forename: Lucian
authors.initials: L
authors.lastname: Krille
authors.affiliation: Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Neuherberg, Germany.
authors.forename: Werner
authors.initials: W
authors.lastname: Maier
authors.affiliation: Institute for Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany.
authors.forename: Roman
authors.initials: R
authors.lastname: Pokora
authors.affiliation: Institute for Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany.
authors.forename: Maria
authors.initials: M
authors.lastname: Blettner
authors.affiliation: Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.|Health Sciences Bremen, University of Bremen, Bremen, Germany.
authors.forename: Hajo
authors.initials: H
authors.lastname: Zeeb
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D005858:Germany / Q000453:epidemiology; D054625:Healthcare Disparities; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D009369:Neoplasms / Q000453:epidemiology / Q000473:pathology*; D012189:Retrospective Studies; D012923:Social Class; D012959:Socioeconomic Factors; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*