On July 22, 2011, a deranged man killed eight persons in a bomb attack in Oslo and, 2 hours later, began shooting children and staff at a youth camp on an island near the city. Over the ensuing 90 minutes he killed 69 staff and young people. After the initial killings on the island, the perpetrator reportedly waited for survivors to attempt escape so that he could target them as they swam. Police could not reach the island when the shooting began due to the lack of helicopters and vessels. Hundreds of other people were injured in the attacks, scores of them seriously.

The Oslo Massacre elicited strong emotional responses, including fear, heightened threat perception, and grief in the general population (Nordanger et al., Reference Nordanger, Hysing, Posserud, Lundervold, Jakobsen, Olff and Stormark2013; Thoresen et al., Reference Thoresen, Aakvaag, Wentzel-Larsen, Dyb and Hjemdal2012). Indeed, one in four Norwegians reportedly knew someone bereaved by the attacks (Thoresen et al., Reference Thoresen, Aakvaag, Wentzel-Larsen, Dyb and Hjemdal2012). Whether grief arose solely among those closely tied to the deceased or in the larger population, which included witnesses to the pain of those with close ties, the fraction of Norwegians grieving the death of their young surely reached very high levels in late summer of 2011.

Dating at least to the work of Bruce (Reference Bruce1959), researchers have noted that in several non-human species, environmental threats to the survival of young, proximate conspecifics appear to induce spontaneous abortion in gravid females, both under laboratory conditions and in the wild (Becker & Hurst, Reference Becker, Hurst, Hurst, Beynon, Roberts and Wyatt2008; Cheney & Seyfarth, Reference Cheney and Seyfarth2009; Labov, Reference Labov1981; Roberts et al., Reference Roberts, Lu, Bergman and Beehner2012; Rulicke et al., Reference Rulicke, Guncz and Wedekind2006). Labov (Reference Labov1981) infers that this ‘Bruce Effect’ functions as an adaptive strategy to limit female investment in offspring likely to die in environments prevailing at birth. In non-human animals, the Bruce Effect may provide a female counterstrategy to infanticide, or may be an adaptive strategy to limit investment in gestations that face a high risk of death (Labov, Reference Labov1981). Mechanisms associated with the Bruce Effect likely include the endocrine stress response (Beehner et al., Reference Beehner, Bergman, Cheney, Seyfarth and Whitten2005; Cheney & Seyfarth, Reference Cheney and Seyfarth2009), suggesting that the Bruce Effect may be part of a generalized female reproductive response to environments that threaten offspring.

Theory (Haig, Reference Haig and Stearns1999; Schooling, Reference Schooling2014; Stearns, Reference Stearns and Stearns1987; Trivers & Willard, Reference Trivers and Willard1973; Wells, Reference Wells2000) and empirical work in human populations (Bruckner et al., Reference Bruckner, Helle, Bolund and Lummaa2015; Karasek et al., Reference Karasek, Goodman, Gemmill, Falconi, Hartig, Magganas and Catalano2015; Orzack et al., Reference Orzack, Stubblefield, Akmaev, Colls, Munné, Scholl and Zuckerman2015) suggest that natural selection has conserved endemic selection in utero that allows women to spontaneously abort gestations least likely to yield grandchildren. Acute stressors on a population appear, moreover, to induce epidemic selection in utero via the maternal stress response that reportedly raises the level of fetal fitness required for a gestation to continue (Catalano & Bruckner, Reference Catalano and Bruckner2006; Catalano et al., Reference Catalano, Bruckner and Smith2008; Reference Catalano, Saxton, Bruckner, Goldman and Anderson2009; Reference Catalano, Currier and Steinsaltz2015; Navara, Reference Navara2014).

In both humans (Nesse, Reference Nesse, Carr, Nesse and Wortman2005; Segerstrom & Miller, Reference Segerstrom and Miller2004; Winegard et al., Reference Winegard, Reynolds, Baumeister, Winegard and Maner2014) and other species (Bercovitch, Reference Bercovitch2013; Bosch et al., Reference Bosch, Nair, Ahern, Neumann and Young2008; Bradshaw et al., Reference Bradshaw, Schore, Brown, Poole and Moss2005; Cheney & Seyfarth, Reference Cheney and Seyfarth2009; Douglas-Hamilton et al., Reference Douglas-Hamilton, Bhalla, Wittemyer and Vollrath2006; Fashing & Nguyen, Reference Fashing and Nguyen2011), the death of proximate conspecifics appears to trigger the stress response. Indeed, bereavement among pregnant women increases the risk of spontaneous abortion (László et al., Reference László, Svensson, Li, Obel, Vestergaard, Olsen and Cnattingius2013).

The few historic data we have describing gestational fitness (i.e., the number of grandchildren eventually produced by a gestation) come from Northern Europe (Gabler & Voland, Reference Gabler and Voland1994) and Nordic countries (Lummaa et al., Reference Lummaa, Jokela and Haukioja2001) and show that gestations of male–male twins yielded the fewest grandchildren per gestation. Gestations of female–female twins, obversely, yielded the most grandchildren per gestation. The fitness difference between these gestations appeared due, in large part, to the likelihood of surviving to reproductive age. Male twins more likely died before reproductive age than all other infants. Male singletons had the next highest likelihood of death and the next lowest fitness. Although female twins more likely died than female singletons, the difference did not approach that between male twins and singletons, and enough female twins historically survived to ensure that gestations of female twins produced the most grandchildren per pregnancy.

Much observational literature has invoked stress-induced selection in utero to explain lower secondary sex ratios (i.e., ratio of male to female live births) following natural (Torche & Kleinhaus, Reference Torche and Kleinhaus2012) and manmade (Catalano et al., Reference Catalano, Bruckner, Gould, Eskenazi and Anderson2005) calamities, as well as societal disruption (Catalano, Reference Catalano2003). The secondary sex ratio presumably falls after such acute population stressors because selection in utero would abort male fetuses at lower levels of maternal stress than it would female fetuses, given the former's relatively low fitness if born and their relatively high need for maternal investment (Gaulin & Robbins, Reference Gaulin and Robbins1991; Powe et al., Reference Powe, Knott and Conklin-Brittain2010).

Taken as a whole, the literature summarized above suggests that natural selection may have conserved a Bruce Effect in humans that averts maternal investment in less fit offspring when infants and children in the population die at unexpectedly high rates. Because male twin gestations disproportionately populate the low end of the distribution of gestational fitness, they should suffer spontaneous abortion more frequently than would male singleton gestations when a population experiences the Bruce Effect. Female singleton gestations, however, rank below female twin gestations in fitness and, in such a population, should suffer spontaneous abortion more frequently than female twins.

Given the historic ranking of Nordic gestations on fitness, we hypothesize that if natural selection has conserved a Bruce Effect in humans, the monthly odds of a twin among Norwegian newborns exposed in gestation to the events of July 2011 will be lower than statistically expected among males and higher than expected among females. The timing of these associations should show that the decline of twins among male births occurs before the increase among female births because selection against less fit female fetuses occurs earlier in gestation than that against less fit males (Boklage, Reference Boklage2005; Orzack et al., Reference Orzack, Stubblefield, Akmaev, Colls, Munné, Scholl and Zuckerman2015).

Results

The monthly sex-specific ratio of twins to singletons had a mean of 0.0344 (SD=0.0055) for males and a mean of 0.0343 (SD=0.0053) for females. Step 1 produced the following models, in which all estimated coefficients were at least twice their standard errors. The fitted values of these models include the counterfactuals for male and female twin ratios following the Oslo Massacre.

$$\begin{equation*} {\left( {{\raise0.7ex\hbox{${m{t_t}}$} \! / \!\lower0.7ex\hbox{${{m_t} - m{t_t}}$}}} \right)^e} = - 3.3787 + \left( {1 + 0.3540{B^{13}}} \right){a_t}, \end{equation*}$$

$$\begin{equation*} {\left( {{\raise0.7ex\hbox{${f{t_t}}$} \! / \!\lower0.7ex\hbox{${{f_t} - f{t_t}}$}}} \right)^e} = - 3.3859 + {\raise0.7ex\hbox{$1$} \! / \!\lower0.7ex\hbox{${\left( {1 + 0.3584{B^3}} \right)}$}}{a_t}, \end{equation*}$$

mt_t and ft_t are counts of male and female twins born in month t. m_t an f_t are total male and female births in month t. -3.3787 and -3.3859 are constants. 0.3540B ¹³ is a moving average parameter implying that the natural log of the odds of a male twin in month t predicted, in part, values at month t+13. 0.3584B ³ is an autoregressive parameter implying that the natural logs of the odds of a female twin in month t predicted, in part, values at month t + 3. a is the error term of the model at month 1. The error terms exhibit no autocorrelation and have an expected value of 0. These models imply that twin ratios of neither sex exhibited secular trends over the test period but that both showed ‘echoes’ of high or low values. The echo for males appeared 13 months later, suggesting a weak seasonal pattern in which a high or low value at month t predicted a similarly deviant, but diminished in absolute size, value about a year later. The diminished echo for the female twin ratio appeared much sooner — 3 months later. We have no post hoc explanation for the detected autocorrelation in these two series but must, for reasons noted above, use it to arrive at the counterfactuals for our test.

Tables 1 and 2 show the results of step 2 or the estimation of transfer functions formed by adding a binary bereavement variable scored 1 for July 2011 and 0 otherwise to the two models shown above. As noted above, we included eight ‘lags’ of the binary variable to estimate responses among all nine monthly birth cohorts exposed in utero to the massacre (i.e., infants born from July 2011 through March 2012). Tables 1 and 2 also show the results of step 3 in which we estimated pared equations formed by deleting any non-significant lags of the binary variable from the results of step 2. Consistent with our theory and hypothesis, the odds of a twin among males born in the early months after the massacre fell significantly below the expected value while the odds of a twin among female births rose significantly in later months.

TABLE 1 Estimated Transfer Functions of the Natural Logs of the Monthly Odds of a Twin Among Males Born in Norway From May 2007 Through March 2012

*p<.05; single-tailed test; **p<.01; single-tailed test.

TABLE 2 Estimated Transfer Functions of the Natural Logs of the Monthly Odds of a Twin Among Females Born in Norway From May 2007 Through March 2012

*p<.05; single-tailed test; **p<.01; single-tailed test.

Figure 1 shows the proportion of the monthly counterfactual values represented by observed values. The values for males born in September (0.896) and October (0.902) 2011 represented the two lowest values in the entire test period. Among females, only three values in the test period exceed that for February 2012 (1.071).

FIGURE 1 Proportion of the monthly counterfactual values represented by observed values for the log odds of male and female twin births in Norway, May 2007–March 2012.

We identified and adjusted for outliers in our dependent variable outside the nine test cohorts. Such outliers could have expanded the confidence intervals of the full models shown in Tables 1 and 2 and led us to falsely accept the null hypothesis for test cohorts with non-significant coefficients in the tables (Chang et al., Reference Chang, Tiao and Chen1988). We detected no outliers for males and one (i.e., high value in February 2009) for females. Adjusting our test for the single outlier among females did not change the results shown in Table 2.

We offer two ways to understand the strength of our results. First, taking the antilog of the pared model coefficients in Table 1 suggests that the odds of a twin among male births fell 33% below expected levels in September 2011 and 31% below expected levels in October. Doing the same for females born in February 2012 implies that the odds rose 29% above the expected value.

We calculated another familiar metric for strength of association, change in explained variance (i.e., ‘R ²’). Autocorrelation in the dependent variable for males, as expressed by model 1 above, accounted for 8.5% of the series’ variance. The pared model shown in Table 1 accounted for 23.2% of the variance. For females, we calculated these values as 9.6% and 23.5%.

To connect our work with that on the secondary sex ratio in stressed populations, we also determined whether the secondary sex ratio among singletons fell in Norway after the Oslo Massacre. The Bruce Effect and the historical fitness rankings of Nordic gestations would suggest an effect of the massacre on the sex ratio of singletons, in addition to its effect on twins. Applying the three steps in our main test described above to the natural logarithm of the odds of a male among live singleton births yielded the results shown in Table 3. We found, consistent with the Bruce Effect and with timing reported in other literature (Karasek et al., Reference Karasek, Goodman, Gemmill, Falconi, Hartig, Magganas and Catalano2015), that the secondary sex ratio dropped significantly 5 months after the Oslo Massacre.

TABLE 3 Estimated Transfer Functions of the Natural Logs of the Male–Female secondary Sex Ratio Among Singleton Births in Norway From May 2007 Through March 2012

*p<.05; single-tailed test; **p<.01; single-tailed test.