The Human Secondary Sex Odds in the Vicinity of the Nuclear Power Plant Leibstadt in Switzerland, 2002 to 2019 View PDF

The health effects of ionizing radiation, especially radiation induced genetic effects are still little understood [1-4]. There is obvious everyday environmental radiological contamination by nuclear power plants (NPPs), which impacts local environments and produce [5]. Since nutrition is a key driver in women’s health [6], detrimental reproductive effects may be induced by radiologically contaminated food, e.g., by tritium in ground and tap water. Childhood cancer was associated with natural background radiation in Switzerland [7] and was increased within 5 km from nuclear power plants in Germany [8]. The human sex odds at birth was elevated in affected European countries after Chernobyl [9] and associated with distance from nuclear facilities in Austria, Germany, France, and Switzerland [10- 12]. At the Swiss nuclear power plant Leibstadt (NPPL) on August 31, 2010, a radiological incident occurred, which was classified as INES-2 [13,14]. This study aims to investigate the possible impact of this event or of its surrounding circumstances in 2010 [15] on the birth sex odds trend in the vicinity of NPPL from 2011 onward.

The annual counts of male and female births by municipality were provided by the Swiss Bundesamt für Statistik. The centers of 5 Swiss municipalities are located within 5 km distance form NPPL: Leibstadt (1.5 km), Full-Reuenthal (2.0), Schwaderloch (3.3), Leuggern (3.6), and Koblenz (3.8). Table 1 lists the birth counts by year, gender, and municipality. A parsimonious logistic regression model assuming an interrupted or piece-wise constant birth sex odds trend allowing for a level shift from 2011 onward was employed [16]. The Wald- Chi2 statistic was used to test whether a potential level shift in 2011 was different from zero. A p-value < 0.05 was taken to represent a statistically significant result. Data was processed with MS-Excel-365 (2016) and SAS/STAT software 9.4, namely SAS-PROCs LOGISTIC and SGPLOT, SAS Institute Inc.: SAS/STAT User’s Guide, Cary NC: SAS Institute Inc., 2014.

Table 1: Birth counts in the 5 km vicinity of NPPL by municipality in Switzerland, year, and sex; the three bottom rows contain the municipality-specific 2. 2-tables of sex by period and the corresponding sex odds ratios for those 2 tables.

*sex odds ratio (SOR) from 2011 versus before 2011

The gray dots in Figure 1 show the annual sex odds from 2002 to 2019 in the combined municipalities Full-Reuenthal, Koblenz, Leibstadt, Leuggern, and Schwaderloch. These municipalities are the only ones in Switzerland situated within 5 km from NPPL. The thick gray line in Figure 1 depicts the sex odds trend in whole Switzerland, for comparison.

Note, the sex odds near Leibstadt from 2011 onward may be compared to several negative controls, so to speak. The first control is the vicinity of Leibstadt in the period before 2011. The further controls are all of Switzerland in the three periods 2002 to 2010, 2011 to 2019, and 2002 to 2019. In none of those possible negative controls, unnatural sex odds of approximately 1.5 can be observed, as is the case in the 5 km vicinity of Leibstadt from 2011 onward. The solid black line in Figure 1 represents the segmented logistic regression allowing for a jump in 2011 [16]. The jump sex odds ratio (SOR) is 1.484, 95% CI [1.155, 1.907], p-value 0.0020. This level-shift model has a deviance of 17.3 with 16 degrees of freedom. This is equivalent to 8.1% overdispersion, which means good compliance of the data with the binomial assumption of logistic regression. As an alternative to the before/after comparison in the 5 km vicinity of Leibstadt one can compare the sex odds near Leibstadt with the remainder of Switzerland from 2011 onward. The SOR for this contrast is 1.385, 95% CI [1.165, 1.648], p-value 0.0002. If the sex odds jump in Figure 1 is interpreted as a loss of girls from 2011 onward compared to before, this level-shift represents 104, 95%-CI (33, 195), lost girls in the 9-year-period from 2011 to 2019, in which period actually 530 children were born (315 boys, 215 girls, SO 1.465). If we restrict the comparison of the sex odds near Leibstadt with the rest of Switzerland to the period after 2010, the number of theoretically lost girls is smaller but more precisely estimated: 83, 95%-CI (35,139). For detailed discussions and examples of overall lost children under the perspective of lost boys see [10,11].

The analysis of the ratio of male to female offspring at birth (male/ female, secondary sex ratio, sex odds) may be a simple and noninvasive way to monitor the reproductive health of a population [17- 19]. Generally, 104 to 106 boys are born for every 100 girls. However, subpopulations or specific medical conditions may involve deviating sex odds [20]. Radiation is one of few stressors known to elevate the sex odds while dropping total births [10-12,21, and 22]. From these observations it may be concluded that the sex odds are useful, however neglected sentinel indicators for possibly detrimental changes in the environment inducing sub-clinical or yet unnoticed clinical effects. An officially acknowledged INES-2 level incident at a nuclear power plant in Europe is a relatively rare event. Careful consideration of the spatiotemporal vicinity of NPPL revealed a long-term nearly 50% increase of the sex odds after the radiological incident in 2010. This means that within 5 km from NPPL in Switzerland after 2010 approximately every 3rd girl expected to be conceived got lost, under the simplifying assumption that boys were not affected [10]. This distinct finding near a Swiss nuclear power plant immediately after a serious radiological event strengthens previous evidence that elevated environmental or occupational ionizing radiation may increase secondary sex odds at the population level.

95%-CI or 95%-confidence interval
INES-2: International Nuclear and Radiological Event Scale, level 2
NPPL: Nuclear Power Plant Leibstadt, Switzerland
SAS: Statistical Analysis System, software produced by SAS Institute Inc.
SO: Sex Odds
SOR: Sex Odds Ratio

Ethical Approval and Consent to Participate

Not applicable. Ethics approval and consent to participate are not required and not necessary, since only publicly available data and previously published information is being used.

Consent for Publication

Not applicable. Only anonymous data is being used.

Availability of Supporting Data

The employed data has exclusively been published previously and/ or it is contained in the Tables and in the Figures included in this paper.

Competing Interests

The author declares that he has no conflicts of interest.

Funding

The author declares that he has no funding for this study.

Authors’ Contributions

Not applicable.

Competing Financial Interests Declaration

The author declares he has no actual or potential competing financial interests.

I am most grateful to the reviewers for detailed suggestions improving the initial draft.

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