The Impact of Socioeconomic Status and Comorbid Medical Conditions on Ionizing Radiation Exposure From Diagnostic Medical Imaging in Adults

Strauchler, Daniel; Freeman, Katherine; Miller, Todd S.

doi:10.1016/j.jacr.2011.07.009

Cited by 16 publications

(7 citation statements)

References 18 publications

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“…Exposure to ionizing radiation has been shown to increase risk, 31,32 whereas atopic disease may have protective effects. Exposure to ionizing radiation has been shown to increase risk, 31,32 whereas atopic disease may have protective effects.…”

Section: Incidence Of Glioma By Sesmentioning

confidence: 99%

“…To the best of our knowledge, there currently is little evidence for factors that modify the risk of glioma. Exposure to ionizing radiation has been shown to increase risk, 31,32 whereas atopic disease may have protective effects. 6 Although both of these may be correlated with SES, this confounding is unlikely to explain the relatively large differences in incidence reported herein.…”

Section: Incidence Of Glioma By Sesmentioning

confidence: 99%

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Glioma incidence and survival variations by county‐level socioeconomic measures

Coté

Ostrom

Gittleman

et al. 2019

Cancer

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BACKGROUND: Multiple studies have reported higher rates of glioma in areas with higher socioeconomic status (SES) but to the authors' knowledge have not stratified by other factors, including race/ethnicity or urban versus rural location. METHODS: The authors identified the average annual age-adjusted incidence rates and calculated hazard ratios for death for gliomas of various subtypes, stratified by a county-level index for SES, race/ethnicity, US region, and rural versus urban status. RESULTS: Rates of glioma were highest in counties with higher SES (rate ratio, 1.18; 95% CI, 1.15-1.22 comparing the highest with the lowest quintiles [P < .001]). Stratified by race/ethnicity, higher rates in high SES counties persisted for white non-Hispanic individuals. Stratified by rural versus urban status, differences in incidence by SES were more pronounced among urban counties. Survival was higher for residents of high SES counties after adjustment for age and extent of surgical resection (hazard ratio, 0.82; 95% CI, 0.76-0.87 comparing the highest with the lowest quintile of SES [P < .001]). Survival was higher among white Hispanic, black, and Asian/Pacific Islander individuals compared with white non-Hispanic individuals, after adjustment for age, SES, and extent of surgical resection, and when restricted to those individuals with glioblastoma who received radiation and chemotherapy. CONCLUSIONS: The incidence of glioma was higher in US counties of high compared with low SES. These differences were most pronounced among white non-Hispanic individuals and white Hispanic individuals residing in urban areas. Better survival was observed in high SES counties, even when adjusting for extent of surgical resection, and when restricted to those who received radiation and chemotherapy for glioblastoma. Differences in incidence and survival were associated with SES and race, rather than rural versus urban status. Cancer 2019;125:3390-3400.

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Section: Incidence Of Glioma By Sesmentioning

confidence: 99%

Section: Incidence Of Glioma By Sesmentioning

confidence: 99%

Glioma incidence and survival variations by county‐level socioeconomic measures

Coté

Ostrom

Gittleman

et al. 2019

Cancer

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“…Neither of these studies reported cumulative radiation exposure estimates. In a study paralleling our cohort of children but with adult patients, we similarly report that radiation exposure is directly related to comorbidities rather than SES [31]. …”

Section: Discussionmentioning

confidence: 86%

Impact of Socioeconomic Status on Ionizing Radiation Exposure From Medical Imaging in Children

Freeman¹,

Strauchler²,

Miller³

2012

Journal of the American College of Radiology

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Purpose To characterize cumulative exposure to ionizing radiation from diagnostic imaging (CEDI) in pediatric patients, and investigate its relationship to patients’ socioeconomic status (SES) and comorbid medical conditions (CMC). Methods An IRB approved HIPAA compliant 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, that estimated the CEDI from all procedures performed within three years of the index visit (until January 2009). SES was estimated from census tract geocoding. CMC were identified from the electronic medical record. Results 19063 patients had an imaging test within the index month. Mean age was 8.9 years (SD=6.3). Most had private insurance (56%), with 36% receiving Medicaid and 8% private payors. 27% (SD=16) reside in poverty areas, with 62% living in areas of which more than 20% of residents were living below the poverty level. There were differences in CEDI (p<.0001) by age, insurance type, and percent poverty in 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 (RA). Conclusion Patients living in areas of greater poverty were exposed over time to more radiation from diagnostic testing than those living in areas with a lower percentage of residents living in poverty. This association was explained almost entirely by the presence of disease burden. We found no direct association between SES and CEDI.

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“…While patients of underinsured/uninsured status required sternotomy at a higher rate, this relationship was not statistically significant; our study may not have had enough power to detect a difference in rates. 3,35,36 Finally, those of low SES have been shown to have less health consciousness (thinking about things to do to keep healthy) and hold stronger beliefs in the influence of chance on improving health, rather than seeking medical attention; these types of health attitudes may additionally contribute to advanced presentation in our underinsured/uninsured population. While we demonstrated an association between low SES and larger thyroid volume, causality may be more complex.…”

Section: Discussionmentioning

confidence: 99%

“…13,34 While no differences in medical comorbidities or history of radiation exposure existed based on health insurance type in our study population, competing priorities (ie, concerns over daily food and housing) among patients of underinsured/uninsured status may contribute significantly to late presentation. 3,35,36 Finally, those of low SES have been shown to have less health consciousness (thinking about things to do to keep healthy) and hold stronger beliefs in the influence of chance on improving health, rather than seeking medical attention; these types of health attitudes may additionally contribute to advanced presentation in our underinsured/uninsured population. 37 A notable limitation of our study is that SES is a multifactorial variable which encompasses a number of components, including insurance, income, neighborhood, education level, and occupation.…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic disparities in a population of patients undergoing total thyroidectomy for benign disease

El‐Sayed

et al. 2018

Head & Neck

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Background This study examines the effect of insurance status (as a measure of socioeconomic status) on patient with benign thyroid disease. Methods A retrospective review was performed among 60 patients undergoing total thyroidectomy for benign thyroid disease. Univariate and multivariable analyses examined the relationship between insurance status and thyroid volume (sum of the left and right lobe volumes). Results Twenty‐eight (47%) patients were considered of underinsured/uninsured status, and 32 (53%) patients were considered of private/government/military insurance status. Median pathologic whole thyroid volume was 66 mL (range, 2‐855). After multivariable linear regression, underinsured/uninsured status was the only significant predictor of larger volume (correlation coefficient [r] = 118; 95% CI, 42 to 194; P = .003), after adjusting for age, sex, body mass index, and presence of concomitant thyroid disease and compressive symptoms. Conclusion Patients of underinsured/uninsured status suffered more severe disease presentations at time of thyroidectomy, as measured by larger thyroid volumes.

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The Impact of Socioeconomic Status and Comorbid Medical Conditions on Ionizing Radiation Exposure From Diagnostic Medical Imaging in Adults

Cited by 16 publications

References 18 publications

Glioma incidence and survival variations by county‐level socioeconomic measures

Glioma incidence and survival variations by county‐level socioeconomic measures

Impact of Socioeconomic Status on Ionizing Radiation Exposure From Medical Imaging in Children

Socioeconomic disparities in a population of patients undergoing total thyroidectomy for benign disease

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