Compared with firefighters and soldiers, inmates had more biological- and stepsiblings, experienced their sexual onset earlier, had offspring with more women, and reported lower life expectancy

Do Criminals Live Faster Than Soldiers and Firefighters? A Comparison of Biodemographic and Psychosocial Dimensions of Life History Theory. Monika Kwiek & Przemysław Piotrowski
Human Nature, Aug 22 2020. https://rd.springer.com/article/10.1007/s12110-020-09374-5

Abstract: A high risk of morbidity-mortality caused by a harsh and unpredictable environment is considered to be associated with a fast life history (LH) strategy, commonly linked with criminal behavior. However, offenders are not the only group with a high exposure to extrinsic morbidity-mortality. In the present study, we investigated the LH strategies employed by two groups of Polish men: incarcerated offenders (N = 84) as well as soldiers and firefighters (N = 117), whose professions involve an elevated risk of injury and premature death. The subjects were asked to complete the Mini-K (used as a psychosocial LH indicator) and a questionnaire which included a number of biodemographic LH variables. Although biodemographic and psychosocial LH indicators should be closely linked with each other, the actual connection between them is unclear. Thus, this study was driven by two aims: comparing LH strategies in two groups of men with a high risk of premature morbidity-mortality and investigating the relationship between the biodemographic and psychosocial LH dimensions. The study showed that incarcerated men employed faster LH strategies than soldiers and firefighters, but only in relation to biodemographic variables (e.g., number of siblings, age of sexual initiation, life expectancy). No intergroup differences emerged regarding psychosocial LH indicators. Moreover, the correlation analysis showed a weak association between biodemographic and psychosocial LH indicators. The results strengthen the legitimacy of incorporating biodemographic LH traits into research models and indicate the need for further research on the accuracy of the Mini-K. The possible explanations for the intergroup differences in LH strategies are discussed.

Discussion

Intergroup Differences in LH Strategies

One of the aims of the current study was to examine differences in LH strategies adopted by incarcerated offenders and men working as firefighters and soldiers. As predicted, the inmates turned out to develop faster LH strategies than men in dangerous professions. However, this dependency occurred only in relation to biodemographic variables. The inmates’ mothers gave birth to their firstborn at a younger age and had shorter intervals between subsequent pregnancies than the soldiers and firefighters’ mothers. Moreover, compared with firefighters and soldiers, inmates had more biological- and stepsiblings, experienced their sexual onset earlier, had offspring with more women, and reported lower life expectancy.

All the differences reported above consistently indicate that incarcerated men employ faster LH strategies both in relation to biodemographic factors of mating/parenting trade-offs and regarding life expectancy. Although we expected such differences in the context of LH strategy pace, it is interesting that soldiers and firefighters, whose exposure to physical threats is often a part of their daily work routine, expected to live longer than inmates who are incarcerated, constantly monitored, and therefore protected from many external morbidity-mortality cues. Such findings suggest that the perceived risk of premature mortality might not be a simple reflection of prevailing conditions but may tell us something more about the person. To shed more light on this matter, it is worth referring to the previously described predictive adaptive response (PAR) hypotheses, according to which an individual makes predictions about future environmental conditions (external PAR) or their own life expectancy (internal PAR) based on the level of adversity experienced early in life (Nettle et al. 2013). Thereby, when it comes to an individual’s expected survival, early-life adversity might be even more important than objective current morbidity-mortality risk.

Admittedly, we did not ask the participants about their backgrounds. However, our results showed that compared with soldiers and firefighters, inmates had more biological siblings and stepsiblings and their parents started their families at an earlier age. Considering that larger family size and becoming a parent at a younger age are commonly associated with a family’s lower socioeconomic status (Mace 2014), lower parental investments (Stulp and Barrett 2016), as well as a higher occurrence of harsh parenting (Lee and Guterman 2010) and child maltreatment (Scannapieco and Connell-Carrick 2016), we assume that the inmates from our study may have grown up in more adverse households than men working as soldiers and firefighters. That could make them more perceptive of mortality cues in their current environment. Since the correlation analyses used in this study prevent us from using causal language, the possibility presented above is a mere speculation that requires further investigation.

The possibility of higher early-life adversity among the inmates could also serve as an explanation for commonly known differences in prosociality between our two study groups. In fact, as a recent study has shown, growing up in a disadvantaged environment tends to be negatively associated with further prosociality by leading to lower levels of Honesty-Humility and dispositional trust in others (Wu et al. 2020).

It also seems to be plausible that intergroup differences in prosociality are not only the result of a more adverse childhood and explain the different LH strategies adopted by the subjects, but might also affect these LH strategies. As soldiers and firefighters engage in risky behaviors in the service of society, their professions are respected in their communities and are a source of recognition, status, and prestige (King and Karabell 2003; Martens 2005). Therefore, their everyday life must be far less hostile than prison reality, which is typically characterized by a high prevalence of male aggressive competition and dominance (Kupers 2005) and inflicts considerable harm on inmates (Irwin and Owen 2005). Living under such hostile conditions might consolidate inmates’ fast LH strategies and partly explain their relatively pessimistic outlook on the future.

Furthermore, starting a family at younger age and having more offspring turned out to be characteristic of the inmates as well as the inmates’ parents. These similarities in biodemographic indicators of LH strategies between participants and their parents might have occurred partly due to genetic influence. In fact, LH traits are considered to be to some extent heritable (Briley et al. 2017; Figueredo et al. 2004; Tielbeek et al. 2018), which makes genetic confounding another hypothetical explanation of our results.

Another issue is the lack of intergroup differences in terms of number of offspring. In addition, there was no association between the number of children reported by the subjects and the other biodemographic variables. Among the inmates, however, the more children they had, the slower the psychometric LH strategy they employed. Similar results were reported by Richardson et al. (2017b), who argued that one of the reasons for the existence of such associations that are inconsistent with LH theory might be the prevalence of contraception use, which makes it easier to prevent unwanted pregnancies among more promiscuous individuals who are not interested in starting a family. As a result, slower LH strategists who intend to be parents can have more offspring than people with faster LH strategies, who usually prefer not to have children (Richardson et al. 2017b). Our findings seem to confirm the above line of reasoning because, although the number of children was not a reliable indicator of the subject’s LH strategy, the intergroup differences in the number of both biological siblings and stepsiblings were consistent with LH theory predictions. Considering the upward trend in using birth control methods over the several past decades (Blanc et al. 2009; Sonenstein et al. 1998), it becomes apparent that around thirty years ago, when the subjects were born, contraception use was not as ubiquitous as it is at present, and greater mating effort was certainly more strongly associated with a higher number of children. In fact, as the recent study has shown, modern industrialized populations adopting a slower LH strategy tend to enjoy increased fertility (Woodley of Menie et al. 2017), which as stated above is most likely a result of the fact that slower LH strategists are more interested in parenting in general (Clutterbuck et al. 2014). Basically, all these findings lead us to the supposition that number of offspring was a more accurate reflection of LH pace in the past than it is currently. In our modern societies, employing a slow LH strategy seems to be related to higher parental investment, which does not always require having fewer offspring. Perhaps when optimized to its fullest potential, a slow LH strategy may actually favor both the quality and the quantity of children. After all, although parental investments influence children’s fitness, the more an individual has invested in their offspring, the more they can lose by employing a fast LH strategy. Thus, at least to some extent, a slow LH strategy might become more and more beneficial with each subsequent child. The association between a slower LH strategy and having more offspring may also be explained by the fact that people with slow LH strategies are typically perceived as higher-quality mates (Dillon et al. 2013), so they are more likely to attract partners interested in long-lasting relationship and starting families.

The Connection between Biodemographic and Psychosocial Indicators of LH Strategy

Compelled by the dispute over the existence and importance of the relations between biodemographic and psychosocial aspects of LH dimension as well as the shortage of research done on this subject, we aimed to examine the associations between the group of traditional biodemographic LH indicators and the psychosocial assessment of LH strategy obtained by using the Mini-K.

In general, higher scores on the Mini-K indicating a slower LH strategy were associated with having parents who had their first child at a greater age, being older when becoming a parent oneself and, counterintuitively, having more offspring (discussed in the previous section). This already weak association between biodemographic and psychosocial LH variables turned out to be even less significant within the groups. Among the inmates, the slower LH strategy measured by the Mini-K was connected with becoming a father at a later age and having slightly more offspring. Among soldiers and firefighters there was no connection between biodemographic and psychosocial LH variables at all. These results seem to suggest a weak and incoherent connection between biodemographic LH variables and psychosocial aspects of LH dimension assessed using the Mini-K. On the other hand, more correlations occurred in the general sample than among the subgroups, which might suggest that some connections may be more likely to occur if the sample sizes were larger.

Limitations and Future Directions

The current study has several limitations. The first is the exclusive use of correlation analyses, which prevents us from making conclusions about any causal dependencies. Admittedly, the use of correlation analyses was justified by the aims of the study, which included investigating intergroup differences and verifying connections between the two groups of LH indicators. In future studies, analyses concerning causal relationships would have to include indicators of the perceived harshness and unpredictability of early and current environments. Incorporating such variables into research projects would provide us with a more holistic perspective on the LH strategies currently being employed. Thus, future studies on the psychosocial LH dimension should include traditional biodemographic variables, on which LH theory is based, as well as indicators of perceived harshness and unpredictability experienced at different stages of life. This could be achieved by carrying out longitudinal studies with repetitive usage of questionnaires regarding personal convictions about other people and their immediate surroundings (e.g., The World Assumptions Scale; Janoff-Bulman 1989).

The use of a nonrandom selection process might be perceived as another limitation in the context of intergroup differences in the Mini-K scores. The study groups were similar in terms of experiencing higher morbidity-mortality rates on average than the general population. Intergroup differences occurred but only in relation to biodemographic LH indicators. However, comparing the study groups to individuals with a lower morbidity-mortality risk (a control group) might provide us with intergroup differences in the Mini-K as well. In fact, when comparing our subjests’ scores on the Mini-K with the results of the study investigated on a sample of university students (Figueredo et al. 2014), we found that the Mini-K average obtained in our research (M = 1.21, SD = .71) was significantly lower than the average result for the students (1.41; t200 = −4.07, p < .001). Same results were obtained separately for inmates (M = 1.15, SD = .73; t83 = −3.25, p = .002) and for soldiers and firefighters group (M = 1.25, SD = .70; t116 = −2.56, p = .012).

Another point, mentioned previously, is that the lack of connection between biodemographic indicators and the Mini-K in the firefighters and soldiers as well as the very weak connections between these variables in the inmates might be partly affected by the relatively small sample sizes.

Also, because inmates are characterized by a high prevalence of ADHD and comorbid conditions (Ginsberg et al. 2010; Rasmussen et al. 2001), we did not want to include too many questionnaires in the study since this could have lowered the inmates’ motivation to participate. As a result, we chose to restrict the psychosocial LH assessment to the Mini-K, which, as mentioned above, is the most popular psychosocial LH measure considered to be an alternative for the ALHB and K-SF-42 and correlated with the HKSS (Dunkel and Decker 2010). Nevertheless, more comprehensive analyses including all psychometric LH measures in relation to traditional LH variables would offer a valuable verification of the results obtained in the current study.

Finally, our study was limited to the LH strategies of male participants only because of our greater access to men in both study groups. Certainly, future studies including female subjects would be welcome.