Author links open overlay panelAnton V.Korsakov, Emilia V.Geger, Dmitry G.Lagerev, Leonid I.Pugach, Timothy A.Mousseau
Abstract
Background
Ionizing radiation and chemical pollution can disrupt normal embryonic development and lead to congenital malformations and fetal death. We used official government statistical data for 2000–2017 to test the hypothesis that radioactive and chemical pollutants influenced the frequency of de novo congenital malformations in newborns of the Bryansk region of southwest Russia.
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Conclusion
These findings suggest additive and potentially synergistic effects of radioactive and chemical pollutants on the frequencies of multiple congenital malformations in the Bryansk region of southwestern Russia.
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The main factors associated with development abnormalities are genetic and environmental factors including the influence of pollution, background radiation, diet, disease and parasites. Genetic mutations and other forms of genetic damage are also influenced by the chemical and physical environment and radiation and chemical pollutants are well known teratogens (Gilbert-Barness, 2010). Therefore, CM rates can be considered as indicators of adverse factors in the environment (Bochkov and Chebotaryov, 1989).
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4. Discussion
The WHO and IAEA have suggested that levels of radioactive pollution caused by the Chernobyl accident are too low to cause a statistically significant increase in the frequency of congenital malformations (CM) (Chernobyl Joint News Release, 2005; IAEA, 2006). However, a review of the literature suggests a different story. For example, many studies have suggested a link between exposure to Chernobyl-derived fallout and the incidence of CM including Down syndrome, anencephaly, polydactyly, limb reduction defects, CM of the central nervous system, and multiple CM(e.g. Lazyuk et al., 1999; Zhilenko and Fedorova, 1999; Ivanov, 2002; Busby et al., 2009; TORCH, 2006, 2016; Dancause et al., 2010; Wertelecki, 2010; Wertelecki et al., 2014; Timchenko et al., 2014; Korsakov et al., 2014, 2016; Yablokov et al., 2016; Schmitz-Feuerhake, 2020).
WHO and IAEA experts have suggested that radiation doses due to Chernobyl are insufficient to induce CM, and have stated that “Small, but steady increase in messages on congenital defects … belongs to the better statistics, not radiation” (IAEA, 2006). However, others have suggested that the real cumulative doses are significantly higher than calculated (e.g. Datesman, 2020) and that even low levels of chronic radiation can generate significantly higher effects than the official radiation risk models employed by UNSCEAR and ICRP (Fairlie, 2005; TORCH, 2006; 2016; Busby et al., 2009; Yablokov et al., 2016; Korsakov et al., 2016; Schmitz-Feuerhake, 2020).
Perhaps the main reason for the lack of acknowledgement by WHO, IAEA, and UNSCEAR experts (Dolk and Nichols, 1999; ICRP, 2003; 2007; NCRP, 2013) of a relationship between the frequency of CM and radiation exposure from the Chernobyl accident is the perceived lack of correlation between the CM frequencies and dose. However, the dose reconstruction methods that were employed were inconsistent and inaccurate with enormous errors that failed to capture the relevant variation for the affected populations (Yablokov et al., 2016; Korsakov et al., 2016). The IAEA and WHO (Chernobyl Forum, 2005) estimate the collective dose for Belarus, Ukraine and European Russia at 55000 person-Sv. According to other estimates (CERRIE, 2004; Fairlie, 2005; TORCH, 2006, 2016), this collective dose reaches 326000 person-Sv. According to the National Report of Belarus (2016), only for Belarus this dose is 514000 person-Sv. Collective doses for Western Europe were also high and estimated (CERRIE, 2004; Fairlie, 2005) to be over 500000 personSv. For the whole world, the collective dose from the Chernobyl disaster can reach 930 000 person-Sv (TORCH, 2006, 2016). Therefore in practice, it is far more reasonable to use the actual measured levels of environmental contamination where people live, drink, eat and breath. When such direct approaches are used, relationships between contamination levels and biological effects are often observed (Yablokov et al., 2016).
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