ArticleJournal of the American College of Radiology : JACR2012
Impact of socioeconomic status on ionizing radiation exposure from medical imaging in children.
Article in Journal of the American College of Radiology : JACR, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 14 citations in OpenAlex.
- Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review.JMIR public health and surveillance · 2019Review
- Article
- CT scan exposure in Spanish children and young adults by socioeconomic status: Cross-sectional analysis of cohort data.PloS one · 2018Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo characterize cumulative radiation exposure from diagnostic imaging (CEDI) in pediatric patients and to investigate its relationship to patients' socioeconomic status and comorbid medical conditions.
methodsA retrospective cohort study of >19,000 pediatric patients seen within the outpatient clinic system of an academic tertiary care urban medical center during the month of January 2006 was conducted to estimate CEDI from all procedures performed within 3 years of the index visit (until January 2009). Socioeconomic status was estimated from census tract geocoding. Comorbid medical conditions were identified from the electronic medical record.
resultsA total of 19,063 patients underwent imaging tests within the index month. The mean age was 8.9 ± 6.3 years. Most had private insurance (56%), with 36% receiving Medicaid and 8% private payers. Our population lived in census tracts in which 27 ± 16% of the population were below the federal poverty level with 62% living in areas in which 20% of residents were living below the poverty level. There were differences in CEDI (P < .0001) by age, insurance type, and percentage poverty in the census tract of residence but not among racial groups (P = .6508). The association between poverty and CEDI was generally explained by the 26 Elixhauser diagnoses, with the exception of rheumatoid arthritis.
conclusionPatients living in areas of greater poverty were exposed over time to more radiation from diagnostic testing than those living in areas with lower percentages of residents living in poverty. This association was explained almost entirely by the presence of disease burden. No direct association was found between socioeconomic status and CEDI.
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