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Background Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures, make cross-national comparisons of the cumulative mortality impacts of the COVID-19 pandemic challenging. Life expectancy is a widely used indicator that provides a clear and cross-nationally comparable picture of the population-level impacts of the pandemic on mortality. Methods Life tables by sex were calculated for 29 countries, including most European countries, Chile and the USA, for 2015–2020. Life expectancy at birth and at age 60 years for 2020 were contextualized against recent trends between 2015 and 2019. Using decomposition techniques, we examined which specific age groups contributed to reductions in life expectancy in 2020 and to what extent reductions were attributable to official COVID-19 deaths. Results Life expectancy at birth declined from 2019 to 2020 in 27 out of 29 countries. Males in the USA and Lithuania experienced the largest losses in life expectancy at birth during 2020 (2.2 and 1.7 years, respectively), but reductions of more than an entire year were documented in 11 countries for males and 8 among females. Reductions were mostly attributable to increased mortality above age 60 years and to official COVID-19 deaths. Conclusions The COVID-19 pandemic triggered significant mortality increases in 2020 of a magnitude not witnessed since World War II in Western Europe or the breakup of the Soviet Union in Eastern Europe. Females from 15 countries and males from 10 ended up with lower life expectancy at birth in 2020 than in 2015.

Although there are well-established relationships between women’s higher education, labour force participation (LFP), and occupation on the one hand and childlessness on the other hand in the US, the underlying reasons and the role that childlessness desires and expectations play remain unclear. We use the National Longitudinal Survey of Youth in the United States (N=4,198 women) and apply both logistic regression models to examine the role of childlessness desires early in life, and multilevel models for repeated measures to examine the role of childlessness expectations throughout the life course. We find that higher educational attainment and LFP are positively associated with childlessness. We do not find, however, that higher educated and working women more often desire or expect to remain childless. In contrast, we find that among women who ultimately remain childless, those women who work full-time and have higher status occupations have higher expectations to have children throughout their life course. These results suggest that education and occupation produce constraints, resulting in the postponement of childbearing which hinders women in realizing their desires and expectations. Since many working women remain childless despite the desire and expectation to become a mother, our findings stress the importance of work-life reconciliation. It furthermore highlights the importance of increasing public awareness regarding the decrease in fecundity with age.

SummaryBackgroundCOVID certification has been introduced, yet there are no empirical evaluations of its impact on vaccine uptake.MethodsMirroring an RCT, we designed a synthetic control model comparing six countries (Denmark, Israel, Italy, France, Germany, Switzerland) that introduced certification (May-August 2021), with 20 control countries. Our estimates provide a counterfactual trend estimating what would have happened in virtually identical circumstances if certificates were not introduced. The primary outcome was daily COVID-19 vaccine doses, with supplementary analyses of COVID-19 infections.FindingsCOVID-19 certification led to increased vaccinations 20 days prior to implementation, with a lasting effect up to 40 days after. Countries with lower than average pre-intervention uptake had a more pronounced increase. In France, doses exceeded 25,895 vaccines per million capita (pmc) or in absolute terms, 1,749,589 doses prior to certification and 11,434 pmc after (772,563 doses). There was no effect in countries with higher uptake (Germany) or when introduced during limited supply (Denmark). There was higher uptake for 1,000) were associated with higher uptake InterpretationWe provide the first empirical assessment of the relationship between COVID-19 certification and vaccine uptake. Interpretation should recognise additional factors, including age eligibility changes and pandemic trajectories. We provide evidence that certification could increase vaccine uptake.Funding and Competing Interest StatementMCM receives funding from the Leverhulme Trust (Large Centre Grant), European Research Council (835079) and participates in UK’s SAGE SPI-B (behavioural insights) committee. The funders had no role in study design, data collection, analysis, interpretation, or writing of the report.Research in ContextEvidence before this studyThe introduction of COVID-19 certification or vaccine passports has been linked to lower self-reported vaccine intentions, yet national media and health offices report increases in vaccinations. No empirical studies could be located that had examined the impact of the implementation of mandatory COVID-19 certification on vaccine uptake.Added value of this studyTo our knowledge, this is the first empirical analysis of the relationship of the introduction of COVID-19 certification on vaccine uptake.Implications of all the available evidenceOur study provides the first evidence that mandatory COVID-19 certification restricting access to certain settings can influence vaccine uptake for those groups affected by the intervention. Given higher vaccine complacency in certain groups, such as youth who perceive lower risks of infection, this intervention could be an additional policy lever to increase vaccine uptake and population level immunity. Future studies examining more countries and variation by eligibility criteria and factors beyond age are warranted.

We detail the implications of sociogenomics for social determinants research. We focus on education and race because of how early twentieth-century scientific eugenic thinking facilitated a range of racist and eugenic policies, most of which helped justify and pattern racial and educational morbidity and mortality disparities that remain today, and are central to sociological research. Consequently, we detail the implications of sociogenomics research by unpacking key controversies and opportunities in sociogenomics as they pertain to the understanding of racial and educational inequalities. We clarify why race is not a valid biological or genetic construct, the ways that environments powerfully shape genetic influence, and risks linked to this field of research. We argue that sociologists can usefully engage in genetics research, a domain dominated by psychologists and behaviorists who, given their focus on individuals, have mostly not examined the role of history and social structure in shaping genetic influence.

Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.

Understanding the rise to power is central to the study of politics. Yet, we still know little about the career paths of influential politicians like ministers. The literature assumes that dominant preparliamentary occupations (e.g., lawyer, local offices) predict promotion. We move beyond this potential ecological fallacy and suggest a perspective that emphasizes the role of gatekeepers and political human capital like national political experience and education. We leverage complete career data of all Dutch MPs (N = 1,263; 1945–2012) and study their (N = 4,966) opportunities to obtain a cabinet position. A sequence analysis with fuzzy clustering reveals eight career paths in both the professional and political domain. A logistic regression analysis that uses these career paths as predictors shows that prominent occupations and communicative experience do not constitute the pathway to ministerial power; a university education and preparliamentary national political experience do. Findings support the value of political human‐capital theory to understand political promotion.

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures make cross-national comparisons of the cumulative mortality impacts of the COVID-19 pandemic challenging. Life expectancy is a widely-used indicator that provides a clear and cross-nationally comparable picture of the population-level impacts of the pandemic on mortality. Life tables by sex were calculated for 29 countries, including most European countries, Chile, and the USA for 2015-2020. Life expectancy at birth and at age 60 for 2020 were contextualised against recent trends between 2015-19. Using decomposition techniques, we examined which specific age groups contributed to reductions in life expectancy in 2020 and to what extent reductions were attributable to official COVID-19 deaths. Life expectancy at birth declined from 2019 to 2020 in 27 out of 29 countries. Males in the USA and Lithuania experienced the largest losses in life expectancy at birth during 2020 (2.2 and 1.7 years respectively), but reductions of more than an entire year were documented in eleven countries for males, and eight among females. Reductions were mostly attributable to increased mortality above age 60 and to official COVID-19 deaths. The COVID-19 pandemic triggered significant mortality increases in 2020 of a magnitude not witnessed since WW-II in Western Europe or the breakup of the Soviet Union in Eastern Europe. Females from 15 countries and males from 10 ended up with lower life expectancy at birth in 2020 than in 2015.

The spread of false health information casts a shadow over required vaccine coverage. Melinda Mills says that we must, reluctantly, consider criminalising people who deliberately spread false information—but Jonas Sivela argues that the definitions are too murky and that criminalisation may do more harm than good

As COVID-19 vaccines are rolled out across the world, there are growing concerns about the role that trust, belief in conspiracy theories and spread of misinformation through social media impact vaccine hesitancy. We use a nationally representative survey of 1,476 adults in the UK between December 12 to 18, 2020 and five focus groups conducted in the same period. Trust is a core predictor, with distrust in vaccines in general and mistrust in government raising vaccine hesitancy. Trust in health institutions and experts and perceived personal threat are vital, with focus groups revealing that COVID-19 vaccine hesitancy is driven by a misunderstanding of herd immunity as providing protection, fear of rapid vaccine development and side effects, belief the virus is man- made and related to population control. Particularly those who obtain information from relatively unregulated social media sources such as YouTube that have recommendations tailored by watch history are less likely to be willing to become vaccinated. Those who hold general conspiratorial beliefs are less willing to be vaccinated. Since an increasing number of individuals use social media for gathering health information, interventions require action from governments, health officials and social media companies. More attention needs to help people understand their own risks, unpack complex concepts and fill knowledge voids.

As COVID-19 vaccines are rolled out across the world, there are growing concerns about the roles that trust, belief in conspiracy theories, and spread of misinformation through social media play in impacting vaccine hesitancy. We use a nationally representative survey of 1476 adults in the UK between 12 and 18 December 2020, along with 5 focus groups conducted during the same period. Trust is a core predictor, with distrust in vaccines in general and mistrust in government raising vaccine hesitancy. Trust in health institutions and experts and perceived personal threat are vital, with focus groups revealing that COVID-19 vaccine hesitancy is driven by a misunderstanding of herd immunity as providing protection, fear of rapid vaccine development and side effects, and beliefs that the virus is man-made and used for population control. In particular, those who obtain information from relatively unregulated social media sources—such as YouTube—that have recommendations tailored by watch history, and who hold general conspiratorial beliefs, are less willing to be vaccinated. Since an increasing number of individuals use social media for gathering health information, interventions require action from governments, health officials, and social media companies. More attention needs to be devoted to helping people understand their own risks, unpacking complex concepts, and filling knowledge voids.

Recent years have seen the birth of sociogenomics via the infusion of molecular genetic data. We chronicle the history of genetics, focusing particularly on post-2005 genome-wide association studies, the post-2015 big data era, and the emergence of polygenic scores. We argue that understanding polygenic scores, including their genetic correlations with each other, causation, and underlying biological architecture, is vital. We show how genetics can be introduced to understand a myriad of topics such as fertility, educational attainment, intergenerational social mobility, well-being, addiction, risky behavior, and longevity. Although models of gene-environment interaction and correlation mirror agency and structure models in sociology, genetics is yet to be fully discovered by this discipline. We conclude with a critical reflection on the lack of diversity, nonrepresentative samples, precision policy applications, ethics, and genetic determinism. We argue that sociogenomics can speak to long-standing sociological questions and that sociologists can offer innovative theoretical, measurement, and methodological innovations to genetic research.

The application of polygenic scores has transformed our ability to investigate whether and how genetic and environmental factors jointly contribute to the variation of complex traits. Modelling the complex interplay between genes and environment, however, raises serious methodological challenges. Here we illustrate the largely unrecognised impact of gene-environment dependencies on the identification of the effects of genes and their variation across environments. We show that controlling for heritable covariates in regression models that include polygenic scores as independent variables introduces endogenous selection bias when one or more of these covariates depends on unmeasured factors that also affect the outcome. This results in the problem of conditioning on a collider, which in turn leads to spurious associations and effect sizes. Using graphical and simulation methods we demonstrate that the degree of bias depends on the strength of the gene-covariate correlation and of hidden heterogeneity linking covariates with outcomes, regardless of whether the main analytic focus is mediation, confounding, or gene × covariate (commonly gene × environment) interactions. We offer potential solutions, highlighting the importance of causal inference. We also urge further caution when fitting and interpreting models with polygenic scores and non-exogenous environments or phenotypes and demonstrate how spurious associations are likely to arise, advancing our understanding of such results.

ObjectiveTo determine the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in the first half of 2020 (from week 1 to week 26 starting June 22) in England and Wales.DesignDemographic analysis of all-cause mortality from week 1 through week 26 of 2020 using publicly available death registration data from the Office for National Statistics.Setting and populationEngland and Wales population by age and sex in 2020.Main outcome measureAge and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality in the first half of 2020. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the standard deviation in age at death.ResultsWe estimate that there have been 53,937 (95% Prediction Interval: 53,092, 54,746) excess deaths in the first half of 2020, 54% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 1.7 and 1.9 years for females and males relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period.ConclusionsQuantifying excess deaths and their impact on life expectancy at birth provides a more comprehensive picture of the full COVID-19 burden on mortality. Whether mortality will return to - or even fall below - the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.Summary boxesWhat is already known on this topicCOVID-19 related deaths may be misclassified as other causes of death thereby underestimating the full impact of the pandemic on mortality. Excess mortality, the difference between observed deaths and what would have been expected in the absence of the pandemic, is a useful metric to quantify the overall impact of the pandemic on mortality and population health. Life expectancy at birth and lifespan inequality assess the cumulative impact of the pandemic on population health.What this study addsWe examine death registration data from the Office for National Statistics from 2015 to week 26 (mid-year) in 2020 to quantify the impact of the COVID-19 pandemic on mortality in England and Wales thus far. We estimate excess mortality risk by age and sex, and quantify the impact of excess mortality risk on excess deaths, life expectancy and lifespan inequality. During weeks 10 through 26 of 2020, elevated mortality rates resulted in 53,937 additional deaths compared with baseline mortality. Life expectancy at birth for males and females in the first half of 2020 was 78 and 81.8 years, which represent a decline of 1.9 and 1.7 years of life lost relative to the year 2019. Lifespan inequality, a measure of the spread or variation in ages at death, declined due to the increase of mortality at older ages.

Background COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in Europe, second in the world only to the USA. Hospitalization and death from COVID-19 have been linked to demographic and socioeconomic variation. Since this varies strongly by location, there is an urgent need to analyse the mismatch between health care demand and supply at the local level. As lockdown measures ease, reinfection may vary by area, necessitating a real-time tool for local and regional authorities to anticipate demand. Methods Combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial County (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales, we calculate the number of individuals at risk of COVID-19 hospitalization. Combining multiple sources, we produce geospatial risk maps on an online dashboard that dynamically illustrate how the pre-crisis health system capacity matches local variations in hospitalization risk related to age, social deprivation, population density and ethnicity, also adjusting for the overall infection rate and hospital capacity. Results By providing fine-grained estimates of expected hospitalization, we identify areas that face higher disproportionate health care burdens due to COVID-19, with respect to pre-crisis levels of hospital bed capacity. Including additional risks beyond age-composition of the area such as social deprivation, race/ethnic composition and population density offers a further nuanced identification of areas with disproportionate health care demands. Conclusions Areas face disproportionate risks for COVID-19 hospitalization pressures due to their socioeconomic differences and the demographic composition of their populations. Our flexible online dashboard allows policy-makers and health officials to monitor and evaluate potential health care demand at a granular level as the infection rate and hospital capacity changes throughout the course of this pandemic. This agile knowledge is invaluable to tackle the enormous logistical challenges to re-allocate resources and target susceptible areas for aggressive testing and tracing to mitigate transmission.

We thank Nepomuceno et al. (1) for their thoughtful comments and welcome this extension. We strongly agree that in addition to age and sex, additional demographic factors such as the prevalence of comorbidities and broader social determinants are crucial for understanding the impact of coronavirus disease 2019 (COVID-19) on mortality within and across countries. Reiterating our conclusion, we note that the benefit of younger age structures in lower-income countries may be partially offset by weak health systems and a higher prevalence of HIV, tuberculosis, and other chronic conditions (2). In the midst of shockingly high mortality in Italy, our aim was to highlight the potential impact of … [↵][1]1To whom correspondence may be addressed. Email: jennifer.dowd{at}sociology.ox.ac.uk or melinda.mills{at}nuffield.ox.ac.uk. [1]: #xref-corresp-1-1

Many predicted a heavy toll of the COVID-19 pandemic on Africa. Its weakened health systems were harbingers of a terrible outcome. However, local expertise gathered from previous outbreaks and centralized public-health infrastructure with a clear action plan, in addition to a favorable demographic structure and climate, have put many countries in the continent in good standing to face this epidemic head on.

Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and also identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identify 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology across the life course, including puberty timing, age at first birth, sex hormone regulation and age at menopause. Missense alleles in ARHGAP27 were associated with increased NEB but reduced reproductive lifespan, suggesting a trade-off between reproductive ageing and intensity. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Accordingly, we find that NEB-increasing alleles have increased in frequency over the past two generations. Furthermore, integration with data from ancient selection scans identifies a unique example of an allele—FADS1/2 gene locus—that has been under selection for thousands of years and remains under selection today. Collectively, our findings demonstrate that diverse biological mechanisms contribute to reproductive success, implicating both neuro-endocrine and behavioural influences.

Age at first sexual intercourse (AFS) and age at first birth (AFB) have implications for health and evolutionary fitness. In the largest genome-wide association study to date (AFS, N=387,338; AFB, N=542,901), we identify 370 independent signals, 11 sex-specific, with a 5-6% polygenic score (PGS) prediction. Heritability of AFB shifted from 9% [CI=4-14] for women born in 1940 to 22% [CI=19-25] in 1965. Signals are driven by the genetics of reproductive biology and externalising behaviour, with key genes related to follicle stimulating hormone (FSHB), implantation (ESR1), infertility, and spermatid differentiation. Polycystic Ovarian Syndrome leads to later AFB, linking with infertility. Late AFB is protective against later-life disease and associated with parental longevity. Higher childhood socioeconomic circumstances and those in the highest PGS decile (90%+) experience markedly later reproductive onset. Results are relevant for improving teenage and late-life health, for understanding longevity, and guiding experimentation into mechanisms of infertility.

BACKGROUNDThe age at parenthood has risen by about five years in the last decades in the Netherlands. Previous studies typically focused on the age at which people have their first child, but little is known about desired timing of parenthood and how this desire changes.OBJECTIVEIn this study, we examined three facets of postponement: (1) desired age to have a first child, (2) changes in this desired age, and (3) whether the desires are met.METHODSWe use data from the Longitudinal Internet Studies for the Social Sciences (N = 2,296), which is a representative sample of men and women in the Netherlands who have been followed for up to ten years.RESULTSMen and women desire to have children at relatively high ages, i.e., around age 30. About half of the respondents update these desires by increasing the desired age as they get older. Half of respondents do not become a parent at their desired time.CONCLUSIONSThe high ages at first birth observed are due to a combination of the three facets of postponement.CONTRIBUTIONThis study contributes to the literature by showing that the high observed age at which people have children nowadays is due to high desired ages, updating these desires upwards, and not achieving their desired timing.

The use of ART varies considerably across countries in Europe (Calhaz-Jorge et al., 2016, Prag and Mills, 2017). The most recent release of the registers of the European IVF-Monitoring Consortium (EIM) for the European Society of Human Reproduction and Embryology (ESHRE) (Calhaz-Jorge et al., 2016) reveals that the number of ART treatment cycles in 2012 ranged between 1457 per million women between the ages of 15 and 44 in Moldova compared to 14 431 per million women in the same age range in Denmark. The reasons for these differences, however, are not yet fully understood. The economic development of countries has been previously considered as a main driving factor, but cannot explain the vast differences between countries. While richer countries have a somewhat higher prevalence of ART use, the relationship is far from perfect, with many poorer countries in Europe having high levels of ART usage. For instance, the Czech Republic reported 10 473 cycles per million women of reproductive age in 2012 but ranks low (51st) in national wealth as measured by purchasing power parity GDP. The Czech Republic has an ART treatment level that is close to the comparatively wealthier Denmark (ranked 37th), whereas high-income nations such as Italy (ranked eighth) and the United Kingdom (ranked fifth) reported only 5480 and 4918 cycles per million women of reproductive age, respectively (World Bank, 2011). Existing research points to other economic, regulatory and demographic factors underlying country differences in ART uptake. Chambers et al. (2014) argued that it is not only country wealth, but rather the consumer affordability of treatment that drives the country differences in ART usage. Countries where ART treatments are more affordable due to insurance mandates or public subsidies have higher ART usage, suggesting that a cost cut of 10 percentage points of the average disposable income in a country predicts a 32% increase in ART utilization. With respect to ART regulation, Berg Brigham et al. (2013) showed that European countries with more liberal social eligibility regulations registered higher levels of ART usage. Kocourkova et al. (2014) illustrate that country differences in ART usage are related to fertility postponement. The greater the extent of postponement of first birth in a country, the higher demand for ART treatments. These studies have identified important societal drivers of cross-country differences in ART utilization. Large-scale cross-national empirical research on cultural and normative factors shaping ART usage are rare, with some studies showing that cultural factors such as social norms and religion may be important predictors of ART usage (Benagiano, 2008; Adamson, 2009). Billari et al. (2011) reported that country differences in social age deadlines for childbearing, such as beliefs about having a child too early or too late, were predictive of differences in ART availability in European countries. This study examines ART utilization data from 35 European countries and examines the extent to which financial, demographic, and cultural determinants explain the vast cross-national differences in ART usage and treatments in Europe. We replicate the well-known correlation of country wealth and ART treatments. In addition, we show how demographic factors such as fertility postponement are related to ART usage. There is a well-established link between women's higher educational attainment and postponement (Mills et al., 2011, Balbo et al., 2013), with the proportion of higher educated women also varying across nations. We therefore focus on the group of women most likely to postpone childbearing, namely mid-aged, highly educated women. We then take regulatory aspects of ART in the countries under study into account (Prag and Mills, 2015) and make use of survey data to understand country differences in the moral and normative cultural acceptance towards ART and how religious composition of countries is related to ART usage.

Using a large-scale sample of online daters in eight European countries ( N = 196,777), we examine willingness to stepparent among divorcees in relation to both gender and number of children, as well as a set of contextual determinants. We find evidence that having one’s own resident children increases the readiness to partner someone with children. Contrary to previous findings, women are generally less willing to stepparent than men, but when resident children are present, gender dissimilarities fade. Notable national differences are also found. Divorced mothers living in Sweden, the Netherlands, Austria, or France are more open to having a partner with children, whereas Polish and Spanish divorced mothers would be less willing to stepparent. These results are interpreted in light of each country’s institutional background.

Studies of the association between wealth and fertility in industrial populations have a rich history in the evolutionary literature, and they have been used to argue both for and against a behavioral ecological approach to explaining human variability. We consider that there are strong arguments in favor of measuring fertility (and proxies thereof) in industrial populations, not least because of the wide availability of large-scale secondary databases. Such data sources bring challenges as well as advantages, however. The purpose of this article is to illustrate these by examining the association between wealth and reproductive success in the United States, using the National Longitudinal Study of Youth 1979. We conduct a broad-based exploratory analysis of the relationship between wealth and fertility, employing both cross-sectional and longitudinal approaches, and multiple measures of both wealth (income and net worth) and fertility (lifetime reproductive success and transitions to first, second and third births). We highlight the kinds of decisions that have to be made regarding sample selection, along with the selection and construction of explanatory variables and control measures. Based on our analyses, we find a positive effect of both income and net worth on fertility for men, which is more pronounced for white men and for transitions to first and second births. Income tends to have a negative effect on fertility for women, while net worth is more likely to positively predict fertility. Different reproductive strategies among different groups within the same population highlight the complexity of the reproductive ecology of industrial societies. These results differ in a number of respects from other analyses using the same database. We suggest this reflects the impossibility of producing a definitive analysis, rather than a failure to identify the "correct" analytical strategy. Finally, we discuss how these findings inform us about (mal)adaptive decision-making.

A wide body of research over the past 30 years links non-standard work schedules to increased work–family conflict (WFC), but often only within single country contexts. A relatively under-explored question is the extent to which the effects of non-standard schedules on family life might vary by country or be buffered by institutional context. Building on past research, this study uses multilevel modelling techniques on 2004 and 2010 European Social Survey data to explore whether the effects of non-standard schedules on WFC vary across 32 countries in Europe, and if so, whether this contextual variation can be explained by labour regulations and industrial relations characteristics measured at the country level. Findings show that while non-standard work hours and days are associated with increased WFC across the majority of sampled countries, the strength of this association varies significantly between countries. The strongest factor shaping the social consequences of non-standard schedules is the degree to which workers are covered under collective bargaining agreements in a country, which explains as much as 17% of the observed between-country variation in the effects of non-standard schedules on WFC. These findings highlight collective agreements as one of the central mechanisms through which family-friendly regulations on working times and conditions are generated for non-standard schedule workers across Europe. More broadly, findings suggest that when studying the social consequences of non-standard schedules, these arrangements must be contextualized in the broader institutional frameworks within which they are organized and regulated.

Genetic and environmental factors both make substantial contributions to the heterogeneity in individuals’ levels of cognitive ability. Many studies have examined the relationship between educational attainment and cognitive performance and its rate of change. Yet there remains a gap in knowledge regarding whether the effect of genetic predictors on individual differences in cognition becomes more or less prominent over the life course. In this analysis of over 5000 older adults from the Health and Retirement Study (HRS) in the U.S., we measured the change in performance on global cognition, episodic memory, attention & concentration, and mental status over 14 years. Growth curve models are used to evaluate the association between a polygenic risk score for education (education PGS) and cognitive change. Using the most recent education PGS, we find that individuals with higher scores perform better across all measures of cognition in later life. Education PGS is associated with a faster decline in episodic memory in old age. The relationships are robust even after controlling for phenotypic educational attainment, and are unlikely to be driven by mortality bias. Future research should consider genetic effects when examining non-genetic factors in cognitive decline. Our findings represent a need to understand the mechanisms between genetic endowment of educational attainment and cognitive decline from a biological angle., Highlights • Older adults with higher scores perform better across all measures of cognition. • The relationship is robust after controlling for phenotypic educational attainment. • The genetic effect on episodic memory diminishes with age. • Future research should consider genetic effects when examining cognitive decline.

Education is strongly correlated with health outcomes in older adulthood. Whether the impact of education expansion improves health remains unclear due to a lack of clarity over the causal relationship. Previous health research within the social sciences has tended to use specific activities of daily living or self-reported health status. This study uses a broader and objective health measure – allostatic load (AL) – to take into consideration the exposures that accumulate throughout the life course. This paper applies a Mendelian Randomization (MR) approach to identify causality in relation to education on health as measured by AL. Using the Health and Retirement Study 2008 (N=3935), we adopt a polygenic score built from genetic variants associated with years of education. To test whether our analyses violate the exclusion assumption, we further run MR Egger regressions to test for bias from pleiotropy. We also explore the potential pathways between education and AL, including smoking, drinking, marital length, health insurance, etc. Using this genetic instrument, we find a 0.3 unit (19% of a standard deviation) reduction in AL per year of schooling. The effect is mainly driven by BMI and Hba1c. Smoking and marital stability are two potential pathways that also causally influenced by education. If our main and sensitivity analyses are valid, the results find support that a higher level of education is causally related to better health in older adulthood., Highlights • This study measures health with allostatic load (AL) which captures the exposures that accumulate throughout the life course. • Educational attainment has a protective effect on allostatic load in later life. • Genetic variants are used as an instrument for years of education to establish a causal pathway. • The IV estimates suggest a negative causal effect of education on allostatic load, BMI and Hba1c.

This scientometric review of genome-wide association studies (GWAS) from 2005 to 2018 (3639 studies; 3508 traits) reveals extraordinary increases in sample sizes, rates of discovery and traits studied. A longitudinal examination shows fluctuating ancestral diversity, still predominantly European Ancestry (88% in 2017) with 72% of discoveries from participants recruited from three countries (US, UK, Iceland). US agencies, primarily NIH, fund 85% and women are less often senior authors. We generate a unique GWAS H-Index and reveal a tight social network of prominent authors and frequently used data sets. We conclude with 10 evidence-based policy recommendations for scientists, research bodies, funders, and editors., Melinda Mills and Charles Rahal discuss genome-wide association studies published in the last 13 years, finding increases in sample sizes, rates of discovery, and traits studied over time. They discuss limitations, including sample diversity, and make recommendations for scientists and funding bodies.

In modern societies, individual differences in completed fertility are linked with genotypic differences between individuals. Explaining the heritability of completed fertility has been inconclusive, with alternative explanations centering on family formation timing, pursuit of education, or other psychological traits. We use the twin subsample from the Midlife Development in the United States study (MIDUS) and the TwinsUK study to examine these issues. In total, 2,606 adult twin pairs reported on their completed fertility, age at first birth and marriage, level of education, Big Five personality traits, and cognitive ability. Quantitative genetic Cholesky models were used to partition the variance in completed fertility into genetic and environmental variance that is shared with other phenotypes and residual variance. Genetic influences on completed fertility are strongly related to family formation timing and less strongly, but significantly, with psychological traits. Multivariate models indicate that family formation, demographic, and psychological phenotypes leave no residual genetic variance in completed fertility in either dataset. Results are largely consistent across U.S. and U.K. sociocultural contexts.

IMPORTANCE: A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age. OBJECTIVE: To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets. DESIGN, SETTING, AND PARTICIPANTS: This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18?957 SCZ cases and 22?673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12?247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study. MAIN OUTCOMES AND MEASURES: We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age. RESULTS: We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2?=?1.1E-03, P?=?4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014. CONCLUSIONS AND RELEVANCE: This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers. This research is supported by grants 613602, 1047956, 1078901, 1080157, 1087889, and 1067795 from the Australian National Health and Medical Research Council and by grants DE130100614 and DP160102126 from the Australian Research Council. Primary analyses of the SchizophreniaWorking Group of the Psychiatric Genomics Consortium data were conducted on the Genetic Cluster Computer (http://www .geneticcluster.org) hosted by SURFsara and supported by grant NOW480-05-003 from the Netherlands Scientific Organization, along with a supplement from the Dutch Brain Foundation and the Vrije Universitiet Amsterdam. TwinsUK was funded by theWellcome Trust, by grant FP7/2007-2013 from the European Community’s Seventh Framework Programme, and by support from the National Institute for Health Research–funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ National Health Service Foundation Trust in partnership with King’s College London, and single-nucleotide polymorphism genotyping was performed by theWellcome Trust Sanger Institute and National Eye Institute via the National Institute for Health/Center for Inherited Disease Research. Estonian Genome Center Biobank, University of Tartu, received targeted financing by grant IUT20-60 from the Estonian Research Council, Center of Excellence in Genomics, and University of Tartu, and data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. The Swedish Twin Registry is supported by Karolinska Institutet. Mr Tropf received funding from sciencestarter.de for a research visit to The University of Queensland. The research leading to these results received funding from the European Research Council via an ERC Consolidator Grant SOCIOGENOME (grant 615603 awarded to Dr Mills [http://www.sociogenome.com]).

Two of the most prominent phenomena in the study of social determinants of health, the socio-economic gradient in health and the income inequality–health association, have both been suggested to be explainable by the mechanism of status comparisons. This, however, has rarely ever been tested in a direct fashion. In this article, we explicate and test this mechanism by assessing the role of social comparison orientation. Research has shown that individuals vary in their propensity to engage in social comparisons, and those with a higher propensity are also more likely to be affected by the outcomes of such comparisons. In our analysis, we check whether the tendency to compare one’s income to that of others can contribute to explaining socio-economic disparities in health. Using individual-level data (N = 18,356) from 23 European countries on self-rated overall health and psychological well-being, we show that a high-income comparison orientation neither moderates the negative effect of income inequality on health nor the health differences by relative income. Our findings cast doubt on the crucial role that researchers such as Wilkinson and Pickett (2010) have attributed to the mechanism of status differentiation as the link between social stratification and health outcomes.

Human reproductive behavior until relatively recently has been explained exclusively via individual and social characteristics. This article applies results from a recent Genome-Wide Association Study that combined sixty-two data sources to isolate twelve genetic loci associated with reproductive behavior. We create polygenic scores that allow us to include a summary variable of genetic factors into our statistical models. We use four datasets: the U.S. Health and Retirement Study, Dutch LifeLines, TwinsUK and the Swedish Twin register. First, we provide a brief overview of the dominant explanations of reproductive behavior. Second, we test the predictive power of polygenic scores. Third, we interrogate the robustness of our models using a series of sensitivity analyses to take into account possible confounders due to population stratification and selection.

Genetic loci linked with same-sex sexual behavior cannot predict orientation of individuals

The social sciences have been reticent to integrate a biodemographic approach to the study of fertility choice and behaviour, resulting in theories and findings that are largely socially-deterministic. The aim of this paper is to first reflect on reasons for this lack of integration, provide a review of previous examinations, take stock of what we have learned until now and propose future research frontiers. We review the early foundations of proximate determinants followed by behavioural genetic (family and twin) studies that isolated the extent of genetic influence on fertility traits. We then discuss research that considers gene and environment interaction and the importance of cohort and country-specific estimates, followed by multivariate models that explore motivational precursors to fertility and education. The next section on molecular genetics reviews fertility-related candidate gene studies and their shortcomings and on-going work on genome wide association studies. Work in evolutionary anthropology and biology is then briefly examined, focusing on evidence for natural selection. Biological and genetic factors are relevant in explaining and predicting fertility traits, with socio-environmental factors and their interaction still key in understanding outcomes. Studying the interplay between genes and the environment, new data sources and integration of new methods will be central to understanding and predicting future fertility trends.In sozialwissenschaftlichen Untersuchungen von Fertilitätsentscheidungen und –verhalten sind biodemographische Ansätze bislang kaum integriert worden, was zu überwiegend sozial-deterministischen Theorien und Befunden geführt hat. Der vorliegende Beitrag diskutiert zunächst die Gründe für diese weitgehend fehlende Integration, gibt dann einen Überblick über frühere Untersuchungen, fasst die bisher vorliegenden Erkenntnisse zusammen und zeigt schließlich Perspektiven zukünftiger Forschung auf. Ausgehend von grundlegenden Arbeiten zu den proximalen Determinanten der Fertilität werden verhaltensgenetische (Familien- und Zwillings-)Studien besprochen, die das Ausmaß genetischer Einflüsse auf Fertilitätsmerkmale isolieren konnten. Anschließend wird die Forschung zur Gen-Umwelt-Interaktion, zur Bedeutung von kohorten- und länderspezifischen Analysen sowie von Modellen, die Bildung und Fertilitätsentscheidungen vorausgehende Motivlagen berücksichtigen, betrachtet. Darüber hinaus werden Möglichkeiten und Grenzen molekulargenetischer Studien besprochen, bevor schließlich ein kurzer Überblick über Arbeiten aus der evolutionären Anthropologie und Biologie mit einem Fokus auf den Aspekt der natürlichen Auslese gegeben wird. Es zeigt sich, dass biologische und genetische Faktoren für das Verständnis und die Vorhersage von Fertilitätsmerkmalen relevant sind und dass ihre Interaktion mit sozialen Umweltfaktoren zentral für das Verständnis von Fertilitätsoutcomes ist. Für die Vorhersage zukünftiger Fertilitätstrends wird die Untersuchung des Zusammenspiels von Gen-Umwelt-Faktoren sowie die Nutzbarmachung neuer Datenquellen und die Integration neuer Methoden eine wesentliche Rolle spielen.

There is currently little knowledge about what gay men and lesbians seek in a romantic relationship. This study extends the literature on gay men and lesbians' partnership preferences by engaging in the first large-scale empirical study of the long-term dating intentions and monogamy beliefs of gay and lesbian online daters across 53 regions in 8 European countries (N=24,598). Looking at profile and preference information, the authors examined both individual and contextual determinants in a series of multilevel logistic regression analyses. They show that lesbians give more importance to monogamy but show less interest in starting a long-term relationship. The data also reveal the importance of life course aspects such as relationship history and presence of children. Finally, the authors empirically demonstrate that social tolerance and legal recognition of same-sex unions are associated with higher long-term dating intentions and stronger monogamy beliefs.

In humans, for the first time, we are now able to observe ongoing natural selection at the molecular level. Natural selection operates when particular genetic variants render the individuals who bear them more likely to reproduce. As a consequence, those genetic variants increase in frequency in the next generation. In PNAS, Beauchamp (1) presents evidence of negative natural selection on genes implicated in higher educational attainment in a contemporary population in the United States. To understand his conclusion and avoid misinterpretation, we unpack the central concepts. The empirical study of natural selection in humans started with the examination of phenotypes: that is, individual traits, such as height or schizophrenia, measured without reference to genetics (Fig. 1). The simplest design establishes heritability of a phenotype by showing how much variation is attributed to genetic differences between relatives (using twins or other family members) (2). To claim evidence of natural selection, studies measure how much the number of children varies with the phenotype to produce a measure of the “magnitude” of natural selection. If the trait has some heritability and is associated with the number of children, researchers conclude that the traits are evolving as a result of natural selection (3). Height is highly heritable (4), so if taller individuals have more children, genes important for tall stature may become more frequent in future generations (5, 6). Fig. 1. The evolution of study designs used to document ongoing natural selection in contemporary human populations. The figure shows measurement and modeling approaches used to investigate ongoing natural selection. It differentiates between phenotypic and genotypic level and whether the level has been directly observed (gray box) or is inferred (red circles). The blue arrows mark the associations being used as evidence for natural selection. In classic study designs, the observed association between phenotype X … [↵][1]2To whom correspondence may be addressed. Email: courtiol{at}izw-berlin.de or melinda.mills{at}nuffield.ox.ac.uk. [1]: #xref-corresp-1-1

Research suggests that doctor–patient relations have evolved from a doctor-centered, paternalistic approach towards a more patient-centered, egalitarian model of interactions between physicians and their patients. Given the long-running debate on the positive relationship between education and health, the question arises how this development in doctor–patient relations affects social inequalities in health. First, we test to what extent egalitarian (e.g. discussing treatment decisions with patients) doctor–patient relations are underlying the education–self-reported health association. Second, we test whether egalitarian and paternalistic (e.g. withholding some information from patients) doctor–patient relations show differential effects on self-reported health across educational groups. Analyses of the European Social Survey (ESS) 2004/2005 for 24 countries demonstrate that a more egalitarian doctor–patient relationship does not substantially reduce educational inequalities in self-reported health. However, some direct positive effects of egalitarian and direct negative effects of paternalistic doctor–patient relations on health ratings can be found. Finally, results show how the health status of the lower educated can improve with a more egalitarian and less paternalistic doctor–patient relationship.

Knowledge about how race governs partner selection has been predominantly studied in the United States, yet it is unclear whether these results can be generalized to nations with different racial and immigration patterns. Using a large-scale sample of online daters in nine European countries, we engage in the first cross-national analysis of race-related partner preferences and examine the link between contextual factors and ethnic selectivity. We provide a unique test of contact, conflict, and in-group identification theories. We show that individuals uniformly prefer to date same-race partners and that there is a hierarchy of preferences both among natives and minority groups. Notable country differences are also found. Europeans living in countries with a large foreign-born population have an increased preference for minority groups. The ethnically heterogeneous Swiss population displays the strongest preference for minorities, with the more homogenous Poland, Spain, and Italy, the least. Anti-immigrant attitudes are related to stronger in-group preferences among natives. Unexpectedly, non-Arabic minority daters belonging to large-size communities have strong preferences for Europeans. The results have implications for immigrant integration policies and demonstrate that Internet dating allows efficient selection by racial divisions, perpetuating country-specific racial inequalities.

The use of assisted reproductive technology (ART) is widespread, with an estimated five million ART-conceived children born now worldwide. Despite this marked increase in the use of ART, little is known about the demographic consequences. We explore several dimensions of demographic consequences of ART. The proportion of ART-conceived babies varies greatly across countries, and our analyses suggest that ART costs, policies and regulations, and national norms and values are core determinants of these differences. Based on a review of the literature, we conclude that ART has a negligible impact on national fertility rates, thereby suggesting that it is not an effective policy instrument to counter low fertility. Furthermore, we show that the recent increase in twin births in Europe can be attributed to ART usage. A case study of Italy reveals that ART mothers were more likely to deliver prematurely, even when controlling for maternal age.