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1.
Health Phys ; 126(6): 386-396, 2024 Jun 01.
Article in English | MEDLINE | ID: mdl-38568156

ABSTRACT

ABSTRACT: The linear no-threshold (LNT) model has been the regulatory "law of the land" for decades. Despite the long-standing use of LNT, there is significant ongoing scientific disagreement on the applicability of LNT to low-dose radiation risk. A review of the low-dose risk literature of the last 10 y does not provide a clear answer, but rather the body of literature seems to be split between LNT, non-linear risk functions (e.g., supra- or sub-linear), and hormetic models. Furthermore, recent studies have started to explore whether radiation can play a role in the development of several non-cancer effects, such as heart disease, Parkinson's disease, and diabetes, the mechanisms of which are still being explored. Based on this review, there is insufficient evidence to replace LNT as the regulatory model despite the fact that it contributes to public radiophobia, unpreparedness in radiation emergency response, and extreme cleanup costs both following radiological or nuclear incidents and for routine decommissioning of nuclear power plants. Rather, additional research is needed to further understand the implications of low doses of radiation. The authors present an approach to meaningfully contribute to the science of low-dose research that incorporates machine learning and Edisonian approaches to data analysis.


Subject(s)
Radiation Dosage , Humans , Risk Assessment , Radiation Protection/standards , Dose-Response Relationship, Radiation , Radiation Injuries/prevention & control
2.
Disaster Med Public Health Prep ; 17: e538, 2023 Nov 23.
Article in English | MEDLINE | ID: mdl-37994037

ABSTRACT

OBJECTIVE: Evacuation and relocation are key actions used to protect the public in response to natural or technological disasters, but there are inherent risks to both. Unfortunately, these risks have not been fully quantified, which limits the ability of emergency managers and the public to effectively balance the risks and benefits of evacuation or relocation. This work provides quantitative data on the risks of health effects from displacement following evacuation or relocation. METHODS: Researchers performed a literature review and meta-analysis of published studies and quantified risks of 14 different health effects, including both physical and socio-behavioral outcomes, from studies of 9 different disaster types. RESULTS: The findings show statistically significant increases in 9 of the 14 health effects in displaced populations, indicating an increased likelihood of experiencing detrimental health effects compared with nondisplaced populations. A pooled analysis of all negative health effects found an odds ratio of 1.49 (95% confidence interval: 1.24-1.79), which shows a significant relationship between displacement and negative health outcomes. CONCLUSIONS: These findings demonstrate that evacuated or relocated populations have an increased risk of experiencing negative health effects associated with displacement. The broad number of disaster types included mean that findings are applicable to any emergency evacuation or relocation.


Subject(s)
Disasters , Health Status , Survivors , Humans
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