Thursday, August 12, 2021

Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used

Socioeconomic Background and Gene–Environment Interplay in Social Stratification across the Early Life Course. Jani Erola, Hannu Lehti, Tina Baier, Aleksi Karhula. European Sociological Review, jcab026, August 4 2021.

Abstract: To what extent are differences in education, occupational standing, and income attributable to genes, and do genetic influences differ by parents’ socioeconomic standing? When in a children’s life course does parents’ socioeconomic standing matter for genetic influences, and for which of the outcomes, fixed at the different stages of the attainment process, do they matter most? We studied these research questions using Finnish register-based data on 6,529 pairs of twins born between 1975 and 1986. We applied genetically sensitive variance decompositions and took gene–environment interactions into account. Since zygosity was unknown, we compared same-sex and opposite-sex twins to estimate the proportion of genetic variation. Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used. We found that the shared environment influences were negligible for all outcomes. Parental social background measured early during childhood was associated with weaker interactions with genetic influences. Genetic influences on children’s occupation were largely mediated through their education, whereas for genetic influences on income, mediation through education and occupational standing made little difference. Interestingly, we found that non-shared environment influences were greater among the advantaged families and that this pattern was consistent across outcomes. Stratification scholars should therefore emphasize the importance of the non-shared environment as one of the drivers of the intergenerational transmission of social inequalities.

Discussion and Conclusions

In this article, we have presented our findings on the gene–environment interplay over the early life course in education, occupational standing, and income. In summary, our study highlights five findings. First, our baseline findings for education, occupational status, and income show that the relative importance of shared environmental influences was negligible. This challenges previous findings on the substantial influence of the shared environment on education (Branigan, McCallum and Freese, 2013). The results differ from those of earlier studies in Finland studying older cohorts but are similar to those in Norway involving more recent cohorts with similar institutional settings (Silventoinen et al., 2004Nisén et al., 2013Ørstavik et al., 2014Lyngstad, Ystrøm and Zambrana, 2017). For income, the result is in line with a previous Finnish study (Hyytinen et al., 2019). There have been no previous studies on genetic influences in ISEI in Finland, and, to our knowledge, very few elsewhere.

Second, we find that genetic influences are strongest among the most advantaged families. This partly confirms our first hypothesis: There is no linear relationship between the strength of genetic influences and the quality of the family environment, and the differences between the other groups of families are small. Thus, the enhancement mechanism seems to work principally at the top end of the social spectrum. A similar pattern has been found in previous studies studying the social stratification of genetic influences using twin data (Baier and Lang, 2019).

Third, the social stratification of genetic influences is to some extent depending on the age at which parental SES is observed. In contrast to our expectations, parental social background measured early during childhood led to weaker interactions with genetic influences. This finding is an important addition to previous research on the role of socioeconomic rearing environment at different stages of the early life course. It suggests that the average contribution SES would be more or less constant across childhood and youth (Erola, Jalonen and Lehti, 2016). If gene-environment interactions were not taken into account, we would miss the life-course-specific pattern. It may be that parents have not reached their final level of socioeconomic attainment during children’s early childhood, and once parents have achieved that, their status reflects more accurately their genetic potential. If this is the case, the differences we observe in the association between family background and genetic influences according to children’s age can follow from gene–environment correlation related to parent’s socioeconomic attainment. For future research, the results suggest that in order to fully account for stratification according to parental educational and socioeconomic characteristics in genetic influences, one should prefer indicators of parental SES that are observed later than during early childhood.

Fourth, in line with our third hypothesis, we found that the contribution of socioeconomic parental characteristics to genetic influences is stronger the earlier the maturity of an outcome is reached. More specifically, parental characteristics matter mostly for the genetic influences in education, and for occupational standing mostly because it is mediated by their children’s education. Notably, in the case of income, stratification by parental characteristics was weak even before their children’s own education was considered. This is striking: It suggests that nearly all of the factors behind parents’ success or failure in terms of their observed socioeconomic outcomes cannot on average explain that much of how their children succeed economically by age 32–36.

Finally, the results showed the stronger importance of the non-shared environment among the children of parents of high SES. This result was consistent across the three outcomes as well as the indicators of parental SES, and aligned with previous studies showing that socioeconomic outcomes within families differ more strongly among advantaged children (Goldstein and Warren, 2000Heflin and Pattillo, 2006). A possible explanation can be borrowed from research on stratified parenting (Lareau, 2011Kalil, Ryan and Corey, 2012) showing that parents of higher social status make more child-specific investments based on their children’s individual talents or particular weaknesses that can accentuate differences among their children (Baier, 2019). However, similar findings could also result from the multiplicative processes if advantaged parents or the children themselves prefer differential treatment. For example, the same innate talent in math could lead to different educational and career pathways and could encourage careers in either business or academia.

Our results also contribute to the broader discussion on equality of opportunity. As comparative research has shown that social background matters relatively little in Finland, this could lead one to expect that the genetic influences in attainment should also be particularly strong. To some extent, the results are in line with this: The shared environment alone matters very little compared to the results on older birth cohorts in Finland (Silventoinen et al., 2004Branigan, McCallum and Freese, 2013Nisén et al., 2013). However, there is an addition: the comparison of outcomes shows that a negligible impact of shared environmental influences does not mean that only the impact of genes would automatically become stronger; it can also change the differences due to the non-shared environment. To date, the role of non-shared environmental influences has barely been discussed in the literature on genetic influences in socioeconomic attainment (as a notable exception, see Beam and Turkheimer, 2013). These channels nonetheless appear to be relevant for intergenerational socioeconomic transmission processes.

A caveat regarding the data is that we could not follow income as long as would have been preferable (until over age 40); we only covered log mean income from at age 32–36. It may be that the stronger role of genes in the incomes of the highly educated parents we observe now reflects their children’s improved chances to fulfil their own genetic potential, rather than the parents’ investments for their children. If this is the case, the genetic influences on income would become even stronger later. Furthermore, the immediate family context is not the only environment that we are exposed to during childhood and youth. Extended families, schools, or neighbourhoods could have also contributed to the gene–environment interplay. Also a detailed analysis of gender differences was beyond the scope of our study.

Moreover, it may be that our method of estimating genetic influences by comparing same and different sex twins led to a bias in the results; for instance, previous twin studies on education in Finland have found a substantive effect of shared influences that we did not observe. Testing our hypotheses with increasingly available molecular genomic data could shed light on the mechanisms involved; for instance, in the context of the third hypothesis on mediation, direct measures for genetic influences relevant for education, occupation, and income would allow us to test directly to what extent the same genetic influences contribute to each outcome.

In sum, the results underline the value of studying the gene–environment interplay for a better understanding of intergenerational socioeconomic inequalities. Clearly, genetic inheritance plays a key role in this and should be more strongly integrated into stratification research. Importantly, the results show that our theoretical assumptions about the relationship between social inequalities, genes, and shared and non-shared environments are still relatively underdeveloped, especially regarding the importance and role of the non-shared environment. In the future, one of the key tasks of research on intergenerational social mobility and attainment should be the development of better theories on the relationship between gene–environment interplay and its implications for equality of opportunity. The latter goal calls for comparisons of results by applying similar research designs across multiple nations.

A new study challenges assumptions about energy expenditure by people, including the idea that metabolism slows at middle age

Daily energy expenditure through the human life course. Herman Pontzer et al. Science  Aug 13 2021:Vol. 373, Issue 6556, pp. 808-812. DOI: 10.1126/science.abe5017

A lifetime of change

Measurements of total and basal energy in a large cohort of subjects at ages spanning from before birth to old age document distinct changes that occur during a human lifetime. Pontzer et al. report that energy expenditure (adjusted for weight) in neonates was like that of adults but increased substantially in the first year of life (see the Perspective by Rhoads and Anderson). It then gradually declined until young individuals reached adult characteristics, which were maintained from age 20 to 60 years. Older individuals showed reduced energy expenditure. Tissue metabolism thus appears not to be constant but rather to undergo transitions at critical junctures.

Abstract: Total daily energy expenditure (“total expenditure”) reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass–adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Popular version: What We Think We Know About Metabolism May Be Wrong.

At around age 5, children become gradually capable of strategically using prosocial acts to achieve ulterior goals such as to improve their reputation, to be chosen as social partners, to elicit reciprocity, & to navigate interpersonal obligations

The development of prosocial behavior – from sympathy to strategy. Sebastian Grueneisen, Felix Warneken. Current Opinion in Psychology, August 12 2021.

Abstract: Children act prosocially already in their first years of life. Research has shown that this early prosociality is mostly motivated by sympathy for others, but that, over the course of development, children’s prosocial behaviors become more varied, more selective, and more motivationally and cognitively complex. Here, we review recent evidence showing that, starting at around age 5, children become gradually capable of strategically using prosocial acts as instrumental means to achieve ulterior goals such as to improve their reputation, to be chosen as social partners, to elicit reciprocity, and to navigate interpersonal obligations. Children’s sympathy-based prosociality is thus being extended and reshaped into a behavioral repertoire that enables individuals to pursue and balance altruistic, mutualistic, and selfish motives.

Keywords: Prosocial behaviorchildrencooperationstrategicaltruism

From 2020... People living with close others (children or romantic partners) experienced better well-being before and during the pandemic’s first 6 months

From 2020... The Benefits of Living with Close Others: A Longitudinal Examination of Mental Health Before and During a Global Stressor. Sisson NM, Willroth EC, Le BM, Ford BQ. PsyArXiv, Dec 1 2020. DOI: 10.31234/

Abstract: For better or worse, the people we live with may exert a powerful influence on our mental health, perhaps especially during times of stress. The COVID-19 pandemic—a large-scale stressor that prompted health recommendations to stay home to reduce disease spread—provided a unique context for examining how the people we share our homes with may shape our mental health. A seven-wave longitudinal study assessed mental health month-to-month before and during the pandemic (February through September, 2020) in two diverse samples of U.S. adults (N = 656; N = 544). Pre-registered analyses demonstrated that people living with close others (children and/or romantic partners) experienced better well-being before and during the pandemic’s first six months. These groups also experienced unique increases in ill-being during the pandemic’s onset, but parents’ ill-being also recovered more quickly. These findings highlight the crucial protective function of close relationships for mental health both generally and amidst a pandemic.

The full supply chain of blue hydrogen makes the hydrogen greenhouse footprint more than 20% greater than burning natural gas or coal for heat & some 60% greater than burning diesel oil for heat

How green is blue hydrogen? Robert W. Howarth, Mark Z. Jacobson. Energy Science & Engineering, August 12 2021.

Abstract: Hydrogen is often viewed as an important energy carrier in a future decarbonized world. Currently, most hydrogen is produced by steam reforming of methane in natural gas (“gray hydrogen”), with high carbon dioxide emissions. Increasingly, many propose using carbon capture and storage to reduce these emissions, producing so-called “blue hydrogen,” frequently promoted as low emissions. We undertake the first effort in a peer-reviewed paper to examine the lifecycle greenhouse gas emissions of blue hydrogen accounting for emissions of both carbon dioxide and unburned fugitive methane. Far from being low carbon, greenhouse gas emissions from the production of blue hydrogen are quite high, particularly due to the release of fugitive methane. For our default assumptions (3.5% emission rate of methane from natural gas and a 20-year global warming potential), total carbon dioxide equivalent emissions for blue hydrogen are only 9%-12% less than for gray hydrogen. While carbon dioxide emissions are lower, fugitive methane emissions for blue hydrogen are higher than for gray hydrogen because of an increased use of natural gas to power the carbon capture. Perhaps surprisingly, the greenhouse gas footprint of blue hydrogen is more than 20% greater than burning natural gas or coal for heat and some 60% greater than burning diesel oil for heat, again with our default assumptions. In a sensitivity analysis in which the methane emission rate from natural gas is reduced to a low value of 1.54%, greenhouse gas emissions from blue hydrogen are still greater than from simply burning natural gas, and are only 18%-25% less than for gray hydrogen. Our analysis assumes that captured carbon dioxide can be stored indefinitely, an optimistic and unproven assumption. Even if true though, the use of blue hydrogen appears difficult to justify on climate grounds.

Popular version: For Many, Hydrogen Is the Fuel of the Future. New Research Raises Doubts. TNYT, Aug 2021.


Some of the CO2eq emissions from blue hydrogen are inherent in the extraction, processing, and use of natural gas as the feedstock source of methane for the SMR process: fugitive methane emissions and upstream emissions of carbon dioxide from the energy needed to produce, process, and transport the natural gas that is reformed into hydrogen are inescapable. On the other hand, the emissions of methane and carbon dioxide from using natural gas to produce the heat and high pressure needed for SMR and to capture carbon dioxide could be reduced if these processes were instead driven by renewable electricity from wind, solar, or hydro. If we assume essentially zero emissions from the renewable electricity, then carbon dioxide emissions from blue hydrogen could be reduced to the 5.8 g CO2 per MJ that is not captured from the SMR process (Equation 11) plus the indirect emissions from extracting and processing the natural gas used as feedstock for the SMR process, estimated as 2.9 g CO2 per M (7.5% of 38.5 g CO2 per MJ; see section on “total carbon dioxide and methane emissions for gray hydrogen”), for a total of 8.7 g CO2 per MJ. This is a substantial reduction compared with using natural gas to power the production of blue hydrogen. However, the fugitive methane emissions associated with the natural gas that is reformed to hydrogen would remain if the process is powered by 100% renewable energy. These emissions are substantial: 3.5% of 14 g CH4 per MJ (Equation 3). Using the 20-year GWP value of 86, these methane emissions equal 43 g CO2eq per MJ of hydrogen produced. The total greenhouse gas emissions, then, for this scenario of blue hydrogen produced with renewable electricity are 52 g (8.7 g plus 43 g) CO2eq per MJ. This is not a low-emissions strategy, and emissions would still be 47% of the 111 g CO2eq per MJ for burning natural gas as a fuel, using the same methane emission estimates and GWP value (Table 1). Seemingly, the renewable electricity would be better used to produce green hydrogen through electrolysis.

This best-case scenario for producing blue hydrogen, using renewable electricity instead of natural gas to power the processes, suggests to us that there really is no role for blue hydrogen in a carbon-free future. Greenhouse gas emissions remain high, and there would also be a substantial consumption of renewable electricity, which represents an opportunity cost. We believe the renewable electricity could be better used by society in other ways, replacing the use of fossil fuels.

Similarly, we see no advantage in using blue hydrogen powered by natural gas compared with simply using the natural gas directly for heat. As we have demonstrated, far from being low emissions, blue hydrogen has emissions as large as or larger than those of natural gas used for heat (Figure 1; Table 1; Table 2). The small reduction in carbon dioxide emissions for blue hydrogen compared with natural gas are more than made up for by the larger emissions of fugitive methane. Society needs to move away from all fossil fuels as quickly as possible, and the truly green hydrogen produced by electrolysis driven by renewable electricity can play a role. Blue hydrogen, though, provides no benefit. We suggest that blue hydrogen is best viewed as a distraction, something than may delay needed action to truly decarbonize the global energy economy, in the same way that has been described for shale gas as a bridge fuel and for carbon capture and storage in general.43 We further note that much of the push for using hydrogen for energy since 2017 has come from the Hydrogen Council, a group established by the oil and gas industry specifically to promote hydrogen, with a major emphasis on blue hydrogen.5 From the industry perspective, switching from natural gas to blue hydrogen may be viewed as economically beneficial since even more natural gas is needed to generate the same amount of heat.

We emphasize that our analysis in this paper is a best-case scenario for blue hydrogen. It assumes that the carbon dioxide that is captured can indeed be stored indefinitely for decades and centuries into the future. In fact, there is no experience at commercial scale with storing carbon dioxide from carbon capture, and most carbon dioxide that is currently captured is used for enhanced oil recovery and is released back to the atmosphere.44 Further, our analysis does not consider the energy cost and associated greenhouse gas emissions from transporting and storing the captured carbon dioxide. Even without these considerations, though, blue hydrogen has large climatic consequences. We see no way that blue hydrogen can be considered “green.”

People higher in verbal ability had more polarized responses to COVID-19; skill with numbers predicted lower risk perceptions, but not polarization; people higher in verbal ability interpreted information to support beliefs

Ability-related political polarization in the COVID-19 pandemic. Brittany Shoots-Reinhard et al. Intelligence, August 12 2021, 101580.


• People higher in verbal ability had more polarized responses to COVID-19.

• Skill with numbers predicted lower risk perceptions, but not polarization.

• People higher in verbal ability interpreted information to support beliefs.

• People higher in verbal ability were more polarized in media consumption.

Abstract: In two large-scale longitudinal datasets (combined N = 5761), we investigated ability-related political polarization in responses to the COVID-19 pandemic. We observed more polarization with greater ability in emotional responses, risk perceptions, and product-purchase intentions across five waves of data collection with a diverse, convenience sample from February 2020 through July 2020 (Study 1, N = 1267). Specifically, more liberal participants had more negative emotional responses and greater risk perceptions of COVID-19 than conservative participants. Compared to conservatives, liberal participants also interpreted quantitative information as indicating higher COVID-19 risk and sought COVID-related news more from liberal than conservative news media. Of key importance, we also compared verbal and numeric cognitive abilities for their independent capacity to predict greater polarization. Although measures of numeric ability, such as objective numeracy, are often used to index ability-related polarization, ideological differences were more pronounced among those higher in verbal ability specifically. Similar results emerged in secondary analysis of risk perceptions in a nationally representative longitudinal dataset (Study 2, N = 4494; emotions and purchase intentions were not included in this dataset). We further confirmed verbal-ability-related polarization findings on non-COVID policy attitudes (i.e., weapons bans and Medicare-for-all) measured cross-sectionally. The present Study 2 documented ability-related polarization emerging over time for the first time (rather than simply measuring polarization in existing beliefs). Both studies demonstrated verbal ability measures as the most robust predictors of ability-related polarization. Together, these results suggest that polarization may be a function of the amount and/or application of verbal knowledge rather than selective application of quantitative reasoning skills.

Keywords: COVID-19 pandemicPolarizationPolitical ideologyCognitive abilityIntelligenceMotivated reasoningNumeracy

Our findings contribute to the literature by suggesting that testosterone and competition lead to greater unethical behaviour in men, and that anger plays a role in promoting unethical behaviour

The association between testosterone and unethical behaviours, and the moderating role of intrasexual competition. Marcelo Vinhal Nepomuceno, Eric Stenstrom. British Journal of Psychology, August 7 2021.

Abstract: Researchers have called for a greater use of neuroscientific methods to advance theories in ethical behaviour. Our research takes a neuroscientific approach to investigating unethical behaviour by examining the roles of testosterone and intrasexual competition. We propose that unethical behavioural intentions will be greater for high-testosterone individuals in response to highly intrasexually competitive situations as a means of enhancing status. In an experiment, we measure baseline testosterone and assign participants to an intrasexually competitive or control condition. We demonstrate that in men, but not in women, testosterone is positively associated with unethical behavioural intentions in response to an intrasexual competition prime. Furthermore, using textual analysis, we find that testosterone is positively associated with the usage of anger-related words in response to an intrasexual competition prime among men. In turn, anger-related words are positively associated with unethical behaviour, suggesting that anger may play a role in motivating high-testosterone men to behave unethically. Overall, our findings contribute to the literature by suggesting that testosterone and competition lead to greater unethical behaviour in men, and that anger plays a role in promoting unethical behaviour.

Check also No strong evidence for a causal role of testosterone in promoting human aggression, positive but weakly correlations:

Is testosterone linked to human aggression? A meta-analytic examination of the relationship between baseline, dynamic, and manipulated testosterone on human aggression. S. N. Geniole et al. Hormones and Behavior, December 28 2019, 104644.