Tuesday, March 23, 2021

High income men are more likely to marry, less likely to divorce, if divorced are more likely to remarry, & are less likely to be childless; income is not linked with the probability of marriage for women

High income men have high value as long-term mates in the U.S.: personal income and the probability of marriage, divorce, and childbearing in the U.S. Rosemary L. Hopcroft. Evolution and Human Behavior, March 23 2021. https://doi.org/10.1016/j.evolhumbehav.2021.03.004

Abstract: Using data from the first Census data set that includes complete measures of male biological fertility for a large-scale probability sample of the U.S. population (the 2014 wave of the Study of Income and Program Participation-N = 55,281), this study shows that high income men are more likely to marry, are less likely to divorce, if divorced are more likely to remarry, and are less likely to be childless than low income men. Men who remarry marry relatively younger women than other men, on average, although this does not vary by personal income. For men who divorce who have children, high income is not associated with an increased probability of having children with new partners. Income is not associated with the probability of marriage for women and is positively associated with the probability of divorce. High income women are less likely to remarry after divorce and more likely to be childless than low income women. For women who divorce who have children, high income is associated with a lower chance of having children with new partners, although the relationship is curvilinear. These results are behavioral evidence that women are more likely than men to prioritize earning capabilities in a long-term mate and suggest that high income men have high value as long-term mates in the U.S.

Keywords: Evolutionary psychologyFertilityMarriageChildlesnessDivorceSex differences

Stronger negative feelings (i.e., more disturbed, upset, & frustrated) when encountered others who, in our view, hold false beliefs, compared to when we think that others’ beliefs are merely different from our own

Molnar, Andras and Loewenstein, George F., Thoughts and Players: An Introduction to Old and New Economic Perspectives on Beliefs (March 16, 2021). The Science of Beliefs: A multidisciplinary Approach (provisional title, to be published in October 2021). Cambridge University Press. Edited by Julien Musolino, Joseph Sommer, and Pernille Hemmer. SSRN: http://dx.doi.org/10.2139/ssrn.3806135

Abstract: In this chapter we summarize how economists conceptualize beliefs. Moving both backward and forward in time, we review the way that mainstream economics currently deals with beliefs, as well as, briefly, the history of economists’ thinking about beliefs. Most importantly, we introduce the reader to a recent, transformational movement in economics that focuses on belief-based utility. This approach challenges the standard economic assumption that beliefs are only an input to decision making and examines implications of the intuitive idea that people derive pleasure and pain directly from their beliefs. We also address the question of when and why people care about what other people believe. We close with a discussion of the implications of these insights for contemporary social issues such as political polarization and fake news.

Keywords: Anticipatory Emotions, Belief-based Utility, Cognitive Dissonance, False Beliefs, Homophily, Motivated Reasoning, Polarization, Self-esteem, Theory of Mind

JEL Classification: A11, B12, B21, D83, D91


In our own recent research, however (Molnar & Loewenstein, 2020), we have been advancing a subtly, but we believe crucially, different perspective. Our own view is that it is not awareness that other people have different beliefs than our own which causes discomfort. Rather, it is the belief that others hold, and act on, beliefs that we perceive to be wrong. This idea is also captured by “Cunningham’s Law”—named after Ward Cunningham, the developer of the first wiki—which states that “the best way to get the right answer on the internet is not to ask a question; it’s to post the wrong answer.”5 At the heart of this rather witty “law” lies the intuition that people have a strong desire to correct others’ beliefs when they deem those beliefs to be false. Aligned with the above anecdotal evidence, our own research demonstrates that participants express stronger negative feelings (i.e., are more disturbed, upset, and frustrated) when they encounter others who—from the participant’s point of view—hold false beliefs, compared to when participants think that others’ beliefs are merely different from their own (Molnar & Loewenstein, 2020). These strong negative emotions can then, based on the situation and the type of relationship, either trigger approach (e.g., confronting the other person, attempting to persuade them) or avoidance behaviors (e.g., blocking the other person online).

The subject of these false beliefs can be anything: beliefs about the individual (e.g., misunderstanding one’s intentions), about relationships (incorrectly believing that someone’s partner had been cheating on them), economic outcomes (tax cuts on the rich ultimately “trickle down” to help the poor), or even global phenomena (climate change is unrelated to human activity). What matters more is not the domain of belief, rather, the conviction that someone else holds an incorrect view of the individual, relationships, outcomes, or the world. The more convinced people are that others hold false beliefs, the more upset they will be (Molnar & Loewenstein, 2020), and the more likely they will take some action (either confront these others, or making extra effort to avoid them).

We find that men remain active in the dating and sexual marketplace longer than women

Dating and sexualities across the life course: The interactive effects of aging and gender. Lisa R. Miller, Justin R. Garcia, Amanda N. Gesselman. Journal of Aging Studies, Volume 57, June 2021, 100921. https://doi.org/10.1016/j.jaging.2021.100921


• The authors investigate whether aging differentially impacts single women's and men's dating and sexual attitudes and behaviors

• The authors find that aging has greater effects on women's than men's dating and sexual attitudes and behaviors

• Gender differences in dating and sexuality are only found in specific stages of the life course

• Age is central to understandings of gendered heterosexuality

Abstract: Research on aging and sexuality has proliferated in recent years. However, little is known about the gender-specific effects of aging on dating and sexuality. Using survey data from the 2014 wave of Singles in America (SIA), a comprehensive survey on adult singles' experiences with dating and sexuality, we examine whether age differentially affects heterosexual women's and men's dating and sexual attitudes and behaviors and whether gender differences persist across the life course. We find that men remain active in the dating and sexual marketplace longer than women. Although main effects of gender differences are documented in dating and sexual attitudes and behaviors, the results show that gender does not operate the same across the life course. Notably, gender differences shrink or are eliminated in attitudes and behaviors surrounding partnering in midlife and late adulthood, suggesting that age is integral to understanding gendered heterosexuality.

Keywords: GenderSexualitiesAgingIntimate relationshipsLife course

Over and above other Big Five personality domains, both conscientiousness & agreeableness were negatively correlated with alcohol consumption, risky/hazardous drinking, & negative drinking-related consequences

Lui, P. P., Michael Chmielewski, Mayson Trujillo, Joseph Morris, and Terri Pigott. 2021. “Linking Big Five Personality Domains and Facets to Alcohol (mis)use: A Systematic Review and Meta-analysis.” PsyArXiv. March 17. doi:10.31234/osf.io/x2yta


Aims: The goal of this investigation was to synthesize (un)published studies linking Big Five personality domains and facets to a range of alcohol use outcomes. Meta-analyses were conducted to quantify the unique associations between alcohol use outcomes and each Big Five personality domains over and above other domains. Within each domain, meta-analyses also were conducted to examine the unique contribution of each personality facet in alcohol use outcomes.

Methods: Systematic literature reviews were performed in PsycINFO and PubMed using keywords related to alcohol use and personality. Peer-reviewed and unpublished studies were screened and coded for the meta-analyses. Eighty independent samples were subjected to correlated effects meta-regressions.

Results: Over and above other Big Five personality domains, both conscientiousness and agreeableness were negatively correlated with alcohol consumption, risky/hazardous drinking, and negative drinking-related consequences. Facet-level analyses indicated that deliberation and dutifulness were uniquely associated with alcohol (mis)use over and above other conscientiousness facets, and compliance and straightforwardness were uniquely associated with alcohol (mis)use over and above other agreeableness facets. Extraversion—namely excitement seeking—was correlated with alcohol consumption, whereas neuroticism—namely impulsiveness and angry hostility—was correlated with negative drinking-related consequences.

Conclusions: Personality characteristics are robust correlates of alcohol (mis)use. Examining relevant narrowband traits can inform mechanisms by which personality affects drinking behaviors and related problems, and ways to enhance clinical interventions for alcohol use disorder. Gaps in this literature and future research directions are discussed.

From 2019... Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants

From 2019... Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants. Daniel B. Rosoff, Toni-Kim Clarke, Mark J. Adams, Andrew M. McIntosh, George Davey Smith, Jeesun Jung & Falk W. Lohoff. Molecular Psychiatry volume 26, pages1119–1132. Oct 2019. https://www.nature.com/articles/s41380-019-0535-9

Rolf Degen's take: The genetic instruments associated with higher educational attainment are linked to reduced binge drinking, reduced amount of alcohol consumed per occasion, but to increased frequency of alcohol intake, especially of wine

Abstract: Observational studies suggest that lower educational attainment (EA) may be associated with risky alcohol use behaviors; however, these findings may be biased by confounding and reverse causality. We performed two-sample Mendelian randomization (MR) using summary statistics from recent genome-wide association studies (GWAS) with >780,000 participants to assess the causal effects of EA on alcohol use behaviors and alcohol dependence (AD). Fifty-three independent genome-wide significant SNPs previously associated with EA were tested for association with alcohol use behaviors. We show that while genetic instruments associated with increased EA are not associated with total amount of weekly drinks, they are associated with reduced frequency of binge drinking ≥6 drinks (ßIVW = −0.198, 95% CI, −0.297 to –0.099, PIVW = 9.14 × 10−5), reduced total drinks consumed per drinking day (ßIVW = −0.207, 95% CI, −0.293 to –0.120, PIVW = 2.87 × 10−6), as well as lower weekly distilled spirits intake (ßIVW = −0.148, 95% CI, −0.188 to –0.107, PIVW = 6.24 × 10−13). Conversely, genetic instruments for increased EA were associated with increased alcohol intake frequency (ßIVW = 0.331, 95% CI, 0.267–0.396, PIVW = 4.62 × 10−24), and increased weekly white wine (ßIVW = 0.199, 95% CI, 0.159–0.238, PIVW = 7.96 × 10−23) and red wine intake (ßIVW = 0.204, 95% CI, 0.161–0.248, PIVW = 6.67 × 10−20). Genetic instruments associated with increased EA reduced AD risk: an additional 3.61 years schooling reduced the risk by ~50% (ORIVW = 0.508, 95% CI, 0.315–0.819, PIVW = 5.52 × 10−3). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our findings suggest EA may have important effects on alcohol consumption patterns and may provide potential mechanisms explaining reported associations between EA and adverse health outcomes.


Using large summary-level GWAS data and complementary two-sample MR methods, we show that EA has a likely causal relationship with alcohol consumption behaviors and alcohol dependence risk in individuals of European Ancestry. More specifically, higher EA reduced binge drinking (six or more units of alcohol), the amount of alcohol consumed per occasion, frequency of memory loss due to drinking, distilled spirits intake, and AD risk. EA increased the frequency of alcohol intake, whether alcohol is consumed with meals, and wine consumption. We found evidence that our results may be driven by genetic pleiotropy in only two of the eight alcohol consumption behaviors (average weekly beer plus cider intake and alcohol usually taken with meals) and significance remained after additional analysis using EA instruments with SNPs nominally associated with either cognition or income suggest that EA may be an important factor responsible for variation in alcohol use behaviors. Consistency of our results across MR methods also strengthens our inference of causality.

Educated persons generally have healthier lifestyle habits, fewer comorbidities, and live longer than their less educated counterparts [52], and our results suggest EA is causally associated with different likelihoods of belonging to variegated alcohol consumer typologies. We found that an additional 3.61 years of education reduced the risk of alcohol dependence by ~50%, which is consistent with results from small community samples [53], and the two most recent alcohol dependence GWASs findings strong inverse genetic correlations with educational attainment [2754]. Notably, binge drinking significantly increases the alcohol dependence risk [55], and distilled spirits and beer consumption account for the majority of hazardous alcohol use [56]. Furthermore, compared to wine drinkers, beer and spirits drinkers are at increased risk of becoming heavy or excessive drinkers [57], for alcohol-related problems and illicit drug use [5859], and AD [57]. Our findings related to alcoholic drink preferences, when combined with our results showing increased binge drinking, memory loss due to alcohol, and a suggestive relationship with remorse after drinking, imply a pattern of alcohol consumption motivated to reduce negative emotions or becoming intoxicated [14].

In contrast to the often-reported positive association between EA and total amount of alcohol consumption reported from observational studies [1860], we found little evidence of a causal relationship. This null finding may be reconciled by the opposing influences on alcohol intake frequency and total alcohol consumed per occasion, which, while not leading to an overall change in total consumption, nonetheless significantly affect the pattern. Our null finding regarding total consumption does support similar results from Davies et al. [52], who used the 1972 mandated increase in school-leaving age in the UK as a natural experiment instrumental variable design to investigate the causal effects of staying in school on total alcohol consumption (from individuals in the UKB sample who turned 15 in the first year before and after the schooling age increased). Davies et al. may have found a significant effect of staying in school had they included the disaggregated behavioral dimensions of alcohol consumption behaviors. Nevertheless, even if no EA-total alcohol consumption relationship exists, studies have reported that both the specific alcoholic beverage and the pattern with which it is consumed, controlling for total consumption, independently contribute to risky health behaviors [6162].

Natural experiments [5263], and twin studies have found that differences in EA, even after controlling for shared environmental factors, still significantly impact mortality risk [64,65,66], and recent large Mendelian randomization studies have demonstrated inverse relationships between EA on smoking behaviors [35] and coronary heart disease (CHD) risk [34] add to the growing body of literature, suggesting a causal effect of increased EA on health and mortality. Other observational studies have linked alcohol consumption patterns to health, disease, and mortality risk [67,68,69]. In particular, binge drinking may have dramatic short-term consequences, including motor vehicle accidents, alcoholic coma, cerebral dysfunction, and violent behavior [70], as well as long-term effects such as hypertension, stroke, and other cardiovascular outcomes [71]. A recent MR study showed that smoking mediates, in part, the effect of education on cardiovascular disease [72], and our results suggest that differences in alcohol consumption patterns may also be another mediator. Health consequences incur significant costs with binge drinking accounting for ~77% of the $249 billion alcohol-related costs (lost workplace productivity, health care expenses, law enforcement, and criminal justice expenses, etc.) in the United States in 2010 [55].

While we do not fully understand the underlying biological mechanisms through which the instrument SNPs influence EA, they are primarily found in genomic regions regulating brain development and expressed in neural tissue. These SNPs demonstrate significant expression throughout the life course, but exhibit the highest expression during development [36]. For example, rs4500960, which was associated with reduced EA, is an intronic variant in the transcription factor protein, T-box, Brain 1 (TBR1), that is important for differentiation and migration of neurons during development [36], while rs10061788 is associated with cerebral cortex and hippocampal mossy fiber morphology [36]. It is, however, important to note that interpreting these SNPs as representing “genes for education” may be “overly simplistic” since EA is strongly affected by environmental factors [36]. Our results remained when using an EA instrument with SNPs nominally associated with income removed, suggesting that an individual’s genetics may impact behavior development, which then increases EA [73]. Conversely, genetic estimates of EA and its correlations with other complex social phenotypes using population-based samples may be susceptible to biases, such as assortative mating and dynastic effects that provide pathways alternate to direct biological effects [40]. For example, EA-associated genetic influence on parental behavior could causally affect the child’s environment [73]. Using polygenic scores for EA, Belsky et al. [73] recently found the mothers’ EA-linked genetics actually predicted their children’s social attainment better than the child’s own EA-linked genetics, suggesting an effect mediated by environmental effects. While policies are not able to change children’s genes, or their inherited social status, they can provide resources [73], and our results suggest that interventions to increase education may help improve health outcomes through changing alcohol consumption patterns.

Notably, there was evidence for some causal effects of alcohol consumption patterns on EA, and the divergent effects again demonstrate the importance of separating drinking variables. However, we failed to find evidence that total alcohol consumed, binge drinking, or AD impacts EA, which is in line with observational studies finding no, or small effects [21], and suggests that other studies findings a negative effect [21] may be due to confounding. Alternatively, EA may not be sensitive enough to detect changes in schooling, e.g., grade point average [21], falling behind in homework and other academic difficulties that also reported association  with heavy drinking [74]. Further, there are currently no adolescent drinking behavior GWAS, so the temporal sequence of these analyses should be considered during their interpretation. Our findings, therefore, need replication when GWAS on adolescent alcohol consumption patterns becomes available.

Exploratory sex-specific analyses revealed differences in certain aspects of the relationship between EA and alcohol consumption. For men, the relationship between their consumption of red wine, beer, and whether they drink with meals was more sensitive to changes in EA than for women. Conversely, the reduction in binge drinking with increased EA may be driven by its effect for women since its effect on men was not significant. In addition, in women the negative effect of EA on spirit consumption was more than double its effect on men. We found no differences among the AUDIT question.

There are noted gender gaps in alcohol use and associated outcomes due to a combination of physiological and social factors [39]. Notably, Huerta et al. [75] found sex-specific effects of EA and academic performance on the odds of belonging to different alcohol consumption typologies (ranging from “Abstainer” to “Regular Heavy Drinker with Problems”). The absence of any association in males may be due to their inability to model binge drinking [75]; however, our results suggest otherwise. Additionally, the recent Clarke et al. [28] total weekly alcohol GWAS found sex-specific genetic correlation differences with an rg = 0.1 in men and 0.33 in women. Taken together, our findings suggest EA may partially account for some of these observed gender gaps in alcohol consumption, but not others. We should note that the only available sex-specific EA GWAS had significant overlap ( ≥18.9%) with the outcome datasets, so our exploratory sex-specific analysis used the same EA GWAS combining men and women. The lack of available sex-specific AD GWAS also meant we were unable to examine differences in AD risk. Notably, the sex-specific EA GWAS demonstrated nearly identical effect sizes between men and women, which support the validity of the estimates derived from the combined-sex EA GWAS, but future studies using sex-specific instruments are required.

Strengths and limitations

We note several strengths. We have analyzed multiple alcohol-related behavioral phenotypes, which support the consistency of our results. We have implemented multiple complementary MR methods (IVW, Egger, weighted median, and weighted mode MR) and diagnostics. Consistency of results across MR methods (accommodating different assumptions about genetic pleiotropy) strengthens our causal interpretation of the estimates [76]. We also used the largest publicly available GWASs for both exposure and outcome samples; large summary datasets are important for MR and other genetic analysis investigating small effect sizes [77]. We also note limitations and future directions. There is minimal sample overlap between the exposure SSGAC GWAS and the outcome PGC GWAS (AD), but there may still be individuals participating in multiple surveys, which event we cannot ascertain with available summary-level GWAS statistics. Further, the GWASs cohorts are from Anglophone countries, where beer is the preferred drink [78]; therefore, applicability to other countries with different alcohol preferences may be limited. Further still, it has been reported the UKB sample is more educated, with healthier lifestyles, and fewer health problems than the UK population [79], which may limit the generalizability to other populations. Replication of these findings using alcohol use information from different ethnicities is necessary. EA only measured years of completed schooling; determining how various aspects of education differentially impact alcohol consumption was not possible but should be a topic of future work. Finally, alcohol consumption is not stable over time [15]; however, the alcohol consumption outcomes correspond to current drinking behavior, which may have led to the misclassification of some individuals. The current drinking also impacts the temporal relationship of our bidirectional analyses, since the current alcohol intake likely occurred after maximum educational attainment for most of the participants. Future GWAS that evaluate drinking behavior during adolescence, or other longitudinal studies are necessary to confirm these findings and better elucidate the impact of alcohol intake on EA.