Development and validation of a Spanish version of the Obstetric Quality of Recovery-10 item score (ObsQoR-10-Spanish)

Background

Spanish is the second most spoken language globally with around 475 million native speakers. We aimed to validate a Spanish version of the Obstetric Quality of Recovery-10 item (ObsQoR-10) patient-reported outcome measure.

Methods

ObsQoR-10-Spanish was developed using EuroQoL methodology. ObsQoR-10-Spanish was assessed in 100 Spanish-speaking patients undergoing elective Caesarean or vaginal delivery. Patients <38 weeks, undergoing an intrapartum Caesarean delivery, intrauterine death, or maternal admission to the intensive care unit (ICU) were excluded. Validity was assessed by evaluating (i) convergent validity-correlation with 24-h EuroQoL and global health visual analogue scale (GHVAS) scores (0-100); (ii) discriminant validity-difference in ObsQoR-10-Spanish score for patients with GHVAS scores >70 vs <70; (iii) hypothesis testing-correlation of ObsQoR score with maternal and neonatal factors; and (iv) cross-cultural validity assessed using differential item functioning analysis. Reliability was assessed by evaluating: (i) internal consistency; (ii) split-half reliability and (iii) test-retest reliability; and (iv) floor and ceiling effects.

Results

One hundred patients were approached, recruited, and completed surveys. Validity: (i) convergent validity: the ObsQoR 24-h score correlated moderately with the 24-h EuroQoL (r=-0.632) and GHVAS scores (r=0.590); (ii) discriminant validity: the ObsQoR-10-Spanish 24-h scores were higher in women who delivered vaginally compared to via Caesarean delivery, (mean [standard deviation] scores were 89 [9] vs 81 [12]; P<0.001). The 24-h ObsQoR-Spanish scores were lower in patients experiencing a poor vs a good recovery (mean [standard deviation] scores were 76 [12.3] vs 87.1 [10.6]; P=0.001); (iii) hypothesis testing: the ObsQoR-10 score correlated negatively with age (r=-0.207) and positively with 5-min (r=0.204) and 10-min (r=0.243) Apgar scores. Remaining correlations were not significant; and (iv) differential item functioning analysis suggested no potential bias among the 10 items. Reliability: (i) internal consistency was good (Cronbach alpha=0.763); (ii) split-half reliability was good (Spearman-Brown prophesy reliability estimate of 0.866); (iii) test-retest reliability was excellent with an intra-class correlation coefficient of 0.90; and (iv) floor and ceiling effects: six patients scored a maximum total ObsQoR-10 score.

Conclusions

The ObsQoR-10-Spanish patient-reported outcome measure is valid, reliable, and clinically feasible, and should be considered for use in Spanish-speaking women to assess quality of inpatient postpartum recovery.

A graph theory based similarity metric enables comparison of subpopulation psychometric networks

Network psychometrics leverages pairwise Markov random fields to depict conditional dependencies among a set of psychological variables as undirected edge-weighted graphs. Researchers often intend to compare such psychometric networks across subpopulations, and recent methodological advances provide invariance tests of differences in subpopulation networks. What remains missing, though, is an analogue to an effect size measure that quantifies differences in psychometric networks. We address this gap by complementing recent advances for investigating whether psychometric networks differ with an intuitive similarity measure quantifying the extent to which networks differ. To this end, we build on graph-theoretic approaches and propose a similarity measure based on the Frobenius norm of differences in psychometric networks' weighted adjacency matrices. To assess this measure's utility for quantifying differences between psychometric networks, we study how it captures differences in subpopulation network models implied by both latent variable models and Gaussian graphical models. We show that a wide array of network differences translates intuitively into the proposed measure, while the same does not hold true for customary correlation-based comparisons. In a simulation study on finite-sample behavior, we show that the proposed measure yields trustworthy results when population networks differ and sample sizes are sufficiently large, but fails to identify exact similarity when population networks are the same. From these results, we derive a strong recommendation to only use the measure as a complement to a significant test for network similarity. We illustrate potential insights from quantifying psychometric network similarities through cross-country comparisons of human values networks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Mode Effect of Web-Based Surveying on the 2018 U.S. Health and Retirement Study Measure of Cognitive Functioning

OBJECTIVES

Measuring cognition in an aging populabtion is a public health priority. A move towards survey measurement via the web (as opposed to phone or in-person) is cost-effective but challenging as it may induce bias in cognitive measures. We examine this possibility using an experiment embedded in the 2018 wave of data collection for the U.S. Health and Retirement Study (HRS).

METHODS

We utilize techniques from multiple group item response theory to assess the effect of survey mode on performance on the HRS cognitive measure. We also study the problem of attrition by attempting to predict dropout and via approaches meant to minimize bias in subsequent inferences due to attrition.

RESULTS

We find evidence of an increase in scores for HRS respondents who are randomly assigned to the web-based mode of data collection in 2018. Web-based respondents score higher in 2018 than experimentally matched phone-based respondents, and they show much larger gains relative to 2016 performance and subsequently larger declines in 2020. The differential in favor of web-based responding is observed across all items, but is most pronounced for the Serial 7 task and numeracy items. Due to the relative ease of the web-based mode, we suggest a cutscore of 12 being used to indicate CIND (cognitively impaired but not demented) status when using the web-based version rather than 11.

DISCUSSION

The difference in mode may be nonignorable for many uses of the HRS cognitive measure. In particular, it may require reconsideration of some cutscore-based approaches to identify impairment.

The distribution of child physicians and early academic achievement

OBJECTIVE

To describe the distribution of pediatricians and family physicians (child physicians) across school districts and examine the association between physician supply and third-grade test scores.

DATA SOURCES AND STUDY SETTING

Data come from the January 2020 American Medical Association Physician Masterfile, the 2009-2013 and 2014-2018 waves of American Community Survey 5-Year Data, and the Stanford Education Data Archive (SEDA), which uses test scores from all U.S. public schools. We use covariate data provided by SEDA to describe student populations.

STUDY DESIGN

This descriptive analysis constructs a physician-to-child-population ratio for every school district in the country and describes the child population served by the current distribution of physicians. We fit a set of multivariable regression models to estimate the associations between district test score outcomes and district physician supply. Our model includes state fixed effects to control for unobservable state-level factors, as well as a covariate vector of sociodemographic characteristics.

DATA COLLECTION

Public data from three sources were matched by district ID.

PRINCIPAL FINDINGS

Physicians are highly unequally distributed across districts: nearly 3640 (29.6%) of 12,297 districts have no child physician, which includes 49% of rural districts. Rural children of color in particular have very little access to pediatric care, and this inequality is more extreme when looking exclusively at pediatricians. Districts that have higher child physician supplies tend to have higher academic test scores in early education, independent of community socioeconomic status and racial/ethnic composition. While the national data show this positive relationship (0.012 SD, 95% CI, 0.0103-0.0127), it is most pronounced for districts in the bottom tertile of physician supply (0.163 SD, 95% CI, 0.108-0.219).

CONCLUSIONS

Our study demonstrates a highly unequal distribution of child physicians in the U.S., and that children with less access to physicians have lower academic performance in early education.

Ubiquitous bias and false discovery due to model misspecification in analysis of statistical interactions: The role of the outcome's distribution and metric properties

Studies of interaction effects are of great interest because they identify crucial interplay between predictors in explaining outcomes. Previous work has considered several potential sources of statistical bias and substantive misinterpretation in the study of interactions, but less attention has been devoted to the role of the outcome variable in such research. Here, we consider bias and false discovery associated with estimates of interaction parameters as a function of the distributional and metric properties of the outcome variable. We begin by illustrating that, for a variety of noncontinuously distributed outcomes (i.e., binary and count outcomes), attempts to use the linear model for recovery leads to catastrophic levels of bias and false discovery. Next, focusing on transformations of normally distributed variables (i.e., censoring and noninterval scaling), we show that linear models again produce spurious interaction effects. We provide explanations offering geometric and algebraic intuition as to why interactions are a challenge for these incorrectly specified models. In light of these findings, we make two specific recommendations. First, a careful consideration of the outcome's distributional properties should be a standard component of interaction studies. Second, researchers should approach research focusing on interactions with heightened levels of scrutiny. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Social mobility and biological aging among older adults in the United States

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm "clocks" and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.

Predictive Fit Metrics for Item Response Models

The fit of an item response model is typically conceptualized as whether a given model could have generated the data. In this study, for an alternative view of fit, "predictive fit," based on the model's ability to predict new data is advocated. The authors define two prediction tasks: "missing responses prediction"-where the goal is to predict an in-sample person's response to an in-sample item-and "missing persons prediction"-where the goal is to predict an out-of-sample person's string of responses. Based on these prediction tasks, two predictive fit metrics are derived for item response models that assess how well an estimated item response model fits the data-generating model. These metrics are based on long-run out-of-sample predictive performance (i.e., if the data-generating model produced infinite amounts of data, what is the quality of a "model's predictions on average?"). Simulation studies are conducted to identify the prediction-maximizing model across a variety of conditions. For example, defining prediction in terms of missing responses, greater average person ability, and greater item discrimination are all associated with the 3PL model producing relatively worse predictions, and thus lead to greater minimum sample sizes for the 3PL model. In each simulation, the prediction-maximizing model to the model selected by Akaike's information criterion, Bayesian information criterion (BIC), and likelihood ratio tests are compared. It is found that performance of these methods depends on the prediction task of interest. In general, likelihood ratio tests often select overly flexible models, while BIC selects overly parsimonious models. The authors use Programme for International Student Assessment data to demonstrate how to use cross-validation to directly estimate the predictive fit metrics in practice. The implications for item response model selection in operational settings are discussed.

The Physiologic and Emotional Effects of 360-Degree Video Simulation on Head-Mounted Display Versus In-Person Simulation: A Noninferiority, Randomized Controlled Trial

INTRODUCTION

A key simulation component is its capability to elicit physiological changes, improving recall. The primary aim was to determine whether parasympathetic responses to head-mounted display simulations (HMDs) were noninferior to in-person simulations. The secondary aims explored sympathetic and affective responses and learning effectiveness.

METHODS

The authors conducted a noninferiority trial. Hospital providers who did not use chronotropic medications, have motion sickness, or have seizures were included. The authors randomized participants to in-person or HMD simulation. Biometric sensors collected respiratory sinus arrhythmia and skin conductance levels to measure parasympathetic and sympathetic states at baseline, during, and after the simulation. Affect was measured using a schedule. The authors measured 3-month recall of learning points and used split-plot analysis of variance and Mann-Whitney U tests to analyze.

RESULTS

One hundred fifteen participants qualified, and the authors analyzed 56 in each group. Both groups experienced a significant change in mean respiratory sinus arrhythmia from baseline to during and from during to afterward. The difference of change between the groups from baseline to during was 0.134 (95% confidence interval = 0.142 to 0.410, P = 0.339). The difference of change from during the simulation to after was -0.060 (95% confidence interval = -0.337 to 0.217, P = 0.670). Noninferiority was not established for either period. Sympathetic arousal did not occur in either group. Noninferiority was not established for the changes in affect that were demonstrated. The mean scores of teaching effectiveness and achievement scores were not different.

CONCLUSIONS

Although a parasympathetic and affective response to the video simulation on an HMD did occur, it was not discernibly noninferior to in-person in this study.

Estimating heritability in heights without zygosity information for under-five children in low- and middle-income countries: An application of normal finite mixture distribution model

Twin studies are widely used to estimate heritability of traits and typically rely on knowing the zygosity of twin pairs in order to determine variation attributable to genetics. Most twin studies are conducted in high resource settings. Large scale household survey data, such as the Demographic and Health Surveys, collect various biomarkers for children under five years old in low- and middle-income countries. These data include twins but no information on zygosity. We applied mixture models to obtain heritability estimates without knowing zygosity of twins, using 249 Demographic and Health Surveys from 79 low- and middle-income countries (14,524 twin pairs). We focused on height of children, adjusted for age and sex, but also provided estimates for other biomarkers available in the data. We estimated that the heritability of height in our sample was 46%.

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Mixture model was used to obtain heritability estimates for biomarkers for children under five without zygosity information.

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46% of height was determined by heritability.

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Heritability estimate was 0.54 for weight-for-age z-score and 0.51 for residualized weight.

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An implausible heritability estimate of 0.93 was found for weight-for-height z-score.

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Birthweight had a heritability estimate of 0.71 and hemoglobin level had a heritability estimate of 0.61.

Innovative methods to analyse the impact of gender norms on adolescent health using global health survey data

Background

Understanding how gender norms affect health is an important entry point into designing programs and policies to change norms and improve gender equality and health. However, it is rare for global health datasets to include questions on gender norms, especially questions that go beyond measuring gender-related attitudes, thus limiting gender analysis.

Methods

We developed five case studies using health survey data from six countries to demonstrate approaches to defining and operationalising proxy measures and analytic approaches to investigating how gender norms can affect health. Key findings, strengths and limitations of our norms proxies and methodological choices are summarised.

Findings

Case studies revealed links between gender norms and multiple adolescent health outcomes. Proxys for norms were derived from data on attitudes, beliefs, and behaviours, as well as differences between attitudes and behaviours. Data were cross-sectional, longitudinal, census- and social network-based. Analytic methods were diverse. We found that gender norms affect: 1) Intimate partner violence in Nigeria; 2) Unhealthy weight control behaviours in Brazil and South Africa; 3) HIV status in Zambia; 4) Health and social mobility in the US; and 5) Childbirth in Honduras.

Interpretation

Researchers can use existing global health survey data to examine pathways through which gender norms affect health by generating proxies for gender norms. While direct measures of gender norms can greatly improve the understanding of how gender affects health, proxy measures for norms can be designed for the specific health-related outcome and normative context, for instance by either aggregating behaviours or attitudes or quantifying the difference (dissonance) between them. These norm proxies enable evaluations of the influence of gender norms on health and insights into possible reference groups and sanctions for non-compliers, thus informing programmes and policies to shape norms and improve health.

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This article presents effective methods to study gender norms in existing global health survey data.

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We devised conceptual pathways linking gender norms to gender-based health disparities.

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We identified gender norms proxies and reference groups enforcing the norm.

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We tested hypotheses linking gender norms to health.

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These methods can aid policy and programme design to advance gender equality and health.

Modeling Interaction and Dispersion Effects in the Analysis of Gene-by-Environment Interaction

Genotype-by-environment interaction (GxE) studies probe heterogeneity in response to risk factors or interventions. Popular methods for estimation of GxE examine multiplicative interactions between individual genetic and environmental measures. However, risk factors and interventions may modulate the total variance of an epidemiological outcome that itself represents the aggregation of many other etiological components. We expand the traditional GxE model to directly model genetic and environmental moderation of the dispersion of the outcome. We derive a test statistic, [Formula: see text], for inferring whether an interaction identified between individual genetic and environmental measures represents a more general pattern of moderation of the total variance in the phenotype by either the genetic or the environmental measure. We validate our method via extensive simulation, and apply it to investigate genotype-by-birth year interactions for Body Mass Index (BMI) with polygenic scores in the Health and Retirement Study (N = 11,586) and individual genetic variants in the UK Biobank (N = 380,605). We find that changes in the penetrance of a genome-wide polygenic score for BMI across birth year are partly representative of a more general pattern of expanding BMI variation across generations. Three individual variants found to be more strongly associated with BMI among later born individuals, were also associated with the magnitude of variability in BMI itself within any given birth year, suggesting that they may confer general sensitivity of BMI to a range of unmeasured factors beyond those captured by birth year. We introduce an expanded GxE regression model that explicitly models genetic and environmental moderation of the dispersion of the outcome under study. This approach can determine whether GxE interactions identified are specific to the measured predictors or represent a more general pattern of moderation of the total variance in the outcome by the genetic and environmental measures.

Essay content and style are strongly related to household income and SAT scores: Evidence from 60,000 undergraduate applications

There is substantial evidence of the relationship between household income and achievement on the standardized tests often required for college admissions, yet little comparable inquiry considers the essays typically required of applicants to selective U.S. colleges and universities. We used a corpus of 240,000 admission essays submitted by 60,000 applicants to the University of California in November 2016 to measure relationships between the content of admission essays, self-reported household income, and SAT scores. We quantified essay content using correlated topic modeling and essay style using Linguistic Inquiry and Word Count. We found that essay content and style had stronger correlations to self-reported household income than did SAT scores and that essays explained much of the variance in SAT scores. This analysis shows that essays encode similar information as the SAT and suggests that college admission protocols should attend to how social class is encoded in non-numerical components of applications.

Customizing CAT Administration of the PROMIS Misuse of Prescription Pain Medication Item Bank for Patients with Chronic Pain

OBJECTIVE

The 22-item PROMIS®-Rx Pain Medication Misuse item bank (Bank-22) imposes a high response burden. This study aimed to characterize the performance of the Bank-22 in a computer adaptive testing (CAT) setting based on varied stopping rules.

METHODS

The 22 items were administered to 288 patients. We performed a CAT simulation using default stopping rules (CATPROMIS). In 5 other simulations, a "best health" response rule was added to decrease response burden. This rule stopped CAT administration when a participant selected "never" to a specified number of initial Bank-22 items (2-6 in this study, designated CATAlt2-Alt6). The Bank-22 and 7-item short form (SF-7) scores were compared to scores based on CATPROMIS, and the 5 CAT variations.

RESULTS

Bank-22 scores correlated highly with the SF-7 and CATPROMIS, Alt5, Alt6 scores (r=0.87-0.95) and moderately with CATAlt2- Alt4 scores (r=0.63-0.74). In all CAT conditions, the greatest differences with Bank-22 scores were at the lower end of misuse T-scores. The smallest differences with Bank-22 and CATPROMIS scores were observed with CATAlt5 and CATAlt6. Compared to the SF-7, CATAlt5 and CATAlt6 reduced overall response burden by about 42%. Finally, the correlations between PROMIS-Rx Misuse and Anxiety T-scores remained relatively unchanged across the conditions (r=0.31-0.43, Ps < .001).

CONCLUSIONS

Applying a stopping rule based on number of initial "best health" responses reduced response burden for respondents with lower levels of misuse. The tradeoff was less measurement precision for those individuals, which could be an acceptable tradeoff when the chief concern is in discriminating higher levels of misuse.

Genes Related to Education Predict Frailty Among Older Adults in the United States

OBJECTIVE

This article expands on research that links education and frailty among older adults by considering the role of genes associated with education.

METHOD

Data come from a sample of 7,064 non-Hispanic, white adults participating in the 2004-2012 waves of the Health and Retirement Study. Frailty was measured with two indices: (a) The Frailty Index which corresponds to a deficit accumulation model; and (b) The Paulson-Lichtenberg Frailty Index which corresponds to the biological syndrome/phenotype model. Genes associated with education were quantified using an additive polygenic score. Associations between the polygenic score and frailty indices were tested using a series of multilevel models, controlling for multiple observations for participants across waves.

RESULTS

Results showed a strong and negative association between genes for education and frailty symptoms in later life. This association exists above and beyond years of completed education and we demonstrate that this association becomes weaker as older adults approach their 80s.

DISCUSSION

The results contribute to the education-health literature by highlighting new and important pathways through which education might be linked to successful aging.

Associations of Loneliness and Social Isolation with Healthspan and Lifespan in the US Health and Retirement Study

BACKGROUND

Loneliness and social isolation are emerging public health challenges for aging populations.

METHODS

We followed N=11,302 US Health and Retirement Study (HRS) participants aged 50-95 from 2006-2014 to measure persistence of experiences of loneliness and exposure to social isolation. We tested associations of longitudinal loneliness and social isolation phenotypes with disability, morbidity, mortality, and biological aging through 2018.

RESULTS

During follow-up, 18% of older adults met criteria for loneliness, with 6% meeting criteria at two or more follow-up assessments. For social isolation, these fractions were 21% and 8%. HRS participants who experienced loneliness and were exposed to social isolation were at increased risk for disease, disability, and mortality. Those experiencing persistent loneliness were at a 57% increased hazard of mortality compared to those who never experienced loneliness. For social isolation, the increase was 28%. Effect-sizes were somewhat larger for counts of prevalent activity limitations and somewhat smaller for counts of prevalent chronic diseases. Covariate adjustment for socioeconomic and psychological risks attenuated but did not fully explain associations. Older adults who experienced loneliness and were exposed to social isolation also exhibited physiological indications of advanced biological aging (Cohen's-d for persistent loneliness and social isolation=0.26 and 0.21, respectively). For loneliness, but not social isolation, persistence was associated with increased risk.

CONCLUSION

Deficits in social connectedness prevalent in a national sample of US older adults were associated with morbidity, disability, and mortality and with more advanced biological aging. Bolstering social connectedness to interrupt experiences of loneliness may promote healthy aging.

Rapid online assessment of reading ability

An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2-3 min) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.

Young Children's Prosocial Behavior Protects Against Academic Risk in Neighborhoods With Low Socioeconomic Status

Children raised in neighborhoods with low socioeconomic status (SES) are at risk for low academic achievement. Identifying factors that help children from disadvantaged neighborhoods thrive is critical for reducing inequalities. We investigated whether children's prosocial behavior buffers concurrent and subsequent academic risk in disadvantaged neighborhoods in Bradford, UK. Diverse children (N = 1,175) were followed until age seven, with measurements taken at four times. We used governmental indices of neighborhood-level SES, teacher observations of prosocial behaviors, and direct assessments of academic achievement. Neighborhood SES was positively associated with academic achievement among children with low levels of prosocial behavior, but not among children with high levels of prosocial behavior. Prosocial behavior may mitigate academic risk across early childhood.

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.

A large-scale genome-wide association study meta-analysis of cannabis use disorder

BACKGROUND

Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

METHODS

To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.

FINDINGS

We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.

INTERPRETATION

These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.

FUNDING

National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated life course mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n = 7193) and educational outcomes for adopted (n = 855) and biological (n = 20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted children's schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated life course mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n = 7193) and educational outcomes for adopted (n = 855) and biological (n = 20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on "genetic nurture" by showing associations of parental polygenic scores with adopted children's schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.

Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges

Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene-environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene-environment interaction studies.

A mutation associated with stress resistance in mice is associated with human grip strength and mortality

Hand grip strength (GS) is a valid and reliable predictor of future morbidity and mortality and is considered a useful indicator of aging. In this paper, we use results from the genetic analysis in animal studies to evaluate associations for GS, frailty, and subsequent mortality among humans. Specifically, we use data from the Health and Retirement Survey (HRS) to investigate the association between three polymorphisms in a candidate frailty gene (Tiam1) and GS. Results suggest that the A allele in rs724561 significantly reduces GS among older adults in the US (b = -0.340; p < .006) and is significantly associated with self-reported weakness (b = 0.221; p = .036). This same polymorphism was weakly associated (one-tailed) with an increased risk of mortality (b = 1.091; p < .093) and adjustments for GS rendered this association statistically non-significant (b = 1.048; p < .361). Overall, our results provide tentative evidence that the Tiam1 gene may be associated with frailty development, but we encourage further studies.

The Earliest Origins of Genetic Nurture: The Prenatal Environment Mediates the Association Between Maternal Genetics and Child Development

Observed genetic associations with educational attainment may be due to direct or indirect genetic influences. Recent work highlights genetic nurture, the potential effect of parents' genetics on their child's educational outcomes via rearing environments. To date, few mediating childhood environments have been tested. We used a large sample of genotyped mother-child dyads (N = 2,077) to investigate whether genetic nurture occurs via the prenatal environment. We found that mothers with more education-related genes are generally healthier and more financially stable during pregnancy. Further, measured prenatal conditions explain up to one third of the associations between maternal genetics and children's academic and developmental outcomes at the ages of 4 to 7 years. By providing the first evidence of prenatal genetic nurture and showing that genetic nurture is detectable in early childhood, this study broadens our understanding of how parental genetics may influence children and illustrates the challenges of within-person interpretation of existing genetic associations.

Not a family matter: The effects of religiosity on academic outcomes based on evidence from siblings

Religiosity has been positively linked with multiple measures of academic success, but it is unclear whether the "effect" of religiosity on academic outcomes is causal or spurious. One source of heterogeneity that may contribute to a child's level of religiosity and his/her academic success is family background. This paper is the first to use sibling differences to estimate the associations between religiosity on short and long-term academic success. Our analysis yields two main results. First, more religious adolescents earned higher GPAs in high school, even after including family fixed effects. Second, because they earned higher GPAs in high school, more religious adolescents completed more years of education 14 years after their religiosity was measured. Our findings suggest that adolescents' religious commitments influence their schooling in both the short and long term and should be more actively included and theorized as important drivers of educational and economic stratification.

Short-Term Mental Health Sequelae of Bereavement Predict Long-Term Physical Health Decline in Older Adults: U.S. Health and Retirement Study Analysis

OBJECTIVES

Spousal death is a common late-life event with health-related sequelae. Evidence linking poor mental health to disease suggests the hypothesis that poor mental health following death of a spouse could be a harbinger of physical health decline. Thus, identification of bereavement-related mental health symptoms could provide an opportunity for prevention.

METHODS

We analyzed data from N = 39,162 individuals followed from 1994 to 2016 in the U.S. Health and Retirement Study; N = 5,061 were widowed during follow-up. We tested change in mental and physical health from prebereavement through the 5 years following spousal death.

RESULTS

Bereaved spouses experienced an increase in depressive symptoms following their spouses' deaths but the depressive shock attenuated within 1 year. Bereaved spouses experienced increases in disability, chronic-disease morbidity, and hospitalization, which grew in magnitude over time, especially among older respondents. Bereaved spouses were at increased risk of death compared to nonbereaved respondents. The magnitude of depressive symptoms in the immediate aftermath of spousal death predicted physical-health decline and mortality risk over 5 years of follow-up.

DISCUSSION

Bereavement-related depressive symptoms indicate a risk for physical health decline and death in older adults. Screening for depressive symptoms in bereaved older adults may represent an opportunity for intervention to preserve healthy life span.

From Socrates to Virtual Reality: A Historical Review of Learning Theories and Their Influence on the Training of Anesthesiologists

Over the past couple of centuries, the training of American physicians, and anesthesiologists in particular, has undergone a radical transformation. The revolution of medical training has been and continues to be fueled by insights from learning theorists. In this historical review, we discuss the origins of American medical education in the 1700s and continue through the centuries illustrating the impact of learning theories on the education and training of anesthesiologists. In particular, we explore the impact of learning theories of the 1800s and the adult-centered teaching strategies of the 1900s. We also discuss the role of learning theories in molding medical education in the modern technological age.

Genetic associations with mathematics tracking and persistence in secondary school

Maximizing the flow of students through the science, technology, engineering, and math (STEM) pipeline is important to promoting human capital development and reducing economic inequality. A critical juncture in the STEM pipeline is the highly cumulative sequence of secondary school math courses. Students from disadvantaged schools are less likely to complete advanced math courses. Here, we conduct an analysis of how the math pipeline differs across schools using student polygenic scores, which are DNA-based indicators of propensity to succeed in education. We integrated genetic and official school transcript data from over 3000 European-ancestry students from U.S. high schools. We used polygenic scores as a molecular tracer to understand how the flow of students through the high school math pipeline differs in socioeconomically advantaged versus disadvantaged schools. Students with higher education polygenic scores were tracked to more advanced math already at the beginning of high school and persisted in math for more years. Analyses using genetics as a molecular tracer revealed that the dynamics of the math pipeline differed by school advantage. Compared to disadvantaged schools, advantaged schools buffered students with low polygenic scores from dropping out of math. Across all schools, even students with exceptional polygenic scores (top 2%) were unlikely to take the most advanced math classes, suggesting substantial room for improvement in the development of potential STEM talent. These results link new molecular genetic discoveries to a common target of educational-policy reforms.

Gender Norms and Weight Control Behaviors in U.S. Adolescents: A Prospective Cohort Study (1994-2002)

PURPOSE

The aim of this article was to determine the relationship between gender norms and weight control behaviors in U.S. adolescents.

METHODS

We analyzed prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (N = 9,861), at baseline in 1994-1995 (ages 11-18 years, Wave I), 1-year follow-up (ages 12-19 years, Wave II), and 7-year follow-up (ages 18-26 years, Wave III). The primary exposure variable was a measure of one's gender normativity based on the degree to which males and females behave in ways that are similar to the behaviors of their same-gender peers. The outcome variable was an individual's weight control attempts (trying to lose or gain weight) and behaviors (dieting, fasting/skipping meals, vomiting, or weight-loss pills/laxatives/diuretics to lose weight or ate different/more foods than usual or taking supplements to gain weight).

RESULTS

In logistic regression analyses controlling for potential confounders, a higher baseline individual gender normativity score (higher femininity in females and higher masculinity in males) was associated with weight loss attempts (β = .10; p = .01) and weight loss behaviors (β = .18; p < .001) in girls but was associated with weight gain attempts (β = .18; p < .001) and behaviors (β = .16; p < .001) in boys at 1-year follow-up. Higher individual gender normativity score was protective of weight loss attempts (β = -.15; p < .001) and weight loss behaviors (β = -.17; p < .001) in males but not females at 7-year follow-up. Loess plots provided visualizations of significant relationships.

CONCLUSIONS

Gender norms may reinforce a thinner body ideal for girls but a larger ideal for boys.

Cohort Trends in the Gender Distribution of Household Tasks in the United States and the Implications for Understanding Disability

Objectives: Measures of disability depend on health and social roles in a given environment. Yet, social roles can change over time as they have by gender. We document how engagement in Instrumental Activities of Daily Living (IADLs) is shifting by gender and birth cohort among older adults, and the challenges these shifts can create for population-level estimates of disability. Method: We used the Health and Retirement Study (N = 25,047) and multinomial logistic regression models with an interaction term between gender and birth cohort to predict limitation and nonperformance relative to no difficulty conducting IADLs. Results: Nonperformance of IADLs have significantly decreased among younger cohorts. Women in younger cohorts were more likely to use a map, whereas men in younger cohorts were more likely to prepare meals and shop. Discussion: Failing to account for gender and cohort changes in IADL, performance may lead to systematic bias in estimates of population-level disability.

Implications of gendered behaviour and contexts for social mobility in the USA: a nationally representative observational study

BACKGROUND

We constructed measures of an individual's gendered behaviour and their gendered environment to investigate the salience of gender norms during adolescence for social mobility during the next decade of life.

METHODS

In this nationally representative observational study, we collected individual-level data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), which enrolled a cohort of nationally representative school students aged 11-19 years from across the USA and followed them up for 14 years (ie, to age 25-33 years). We characterised gendered behaviour for adolescents in a performative sense via self-reports of behaviours and beliefs. We aggregated this individual-level measure to create a proxy measure of an individual's social context by taking averages for an individual's peers of the same sex and school year.

FINDINGS

Between Jan 5, 1994, and Dec 26, 1995, Add Health collected data on a cohort of 20 745 students. 14 540 respondents were followed-up 14 years later between April 3, 2007, and Feb 1, 2009, of whom 7722 (53·1%) were female. More masculine male respondents were downwardly mobile; they were enrolled in school for fewer years and were more likely to have lower status jobs than their less masculine same-sex school peers. More masculine male respondents were also more likely to have jobs in occupational categories with larger proportions of males than their same-sex school peers. Gendered behaviour was not predictive of future educational and occupational attainment for female respondents. Male adolescents in school years with more masculine same-sex peers than male adolescents in other school years also tended to have lower educational and occupational attainment than their male peers. Educational and occupational attainment in early midlife for female respondents was not affected by their gendered environment.

INTERPRETATION

Gender, when measured as a set of gender-distinct behaviours in adolescence, was associated with differential patterns of social mobility from adolescence to young adulthood. Moreover, variation in an individual's local gender norms has implications for subsequent socioeconomic attainment, especially for male adolescents. These findings have potential implications for observed health disparities.

FUNDING

Bill & Melinda Gates Foundation.

Genetic risk, body mass index, and weight control behaviors: Unlocking the triad

BACKGROUND

The relationship between genetic risk for body mass index (BMI) and weight control behaviors remains unknown. The objectives of this study were to determine the association between genetic risk for BMI and weight control behaviors in young adults, and to examine actual measured BMI as a potential mediator variable.

METHOD

We analyzed data from three data collection waves of the National Longitudinal Study of Adolescent to Adult Health. The BMI polygenic score (PGS) was based on published genome-wide association studies for BMI. BMI was collected at 11-18 years and 18-26 years. Weight control behaviors included self-reported: (a) weight loss behaviors (dieting, vomiting, fasting/skipping meals, diet pills, laxatives, or diuretic use to lose weight) and (b) weight gain behaviors (eating more or different foods than normal, taking supplements to gain weight).

RESULTS

Among 4,397 participants, the BMI PGS was associated with higher odds of weight loss behaviors in females (OR 1.24, 95% CI 1.14-1.35) and males (OR 1.43, 95% CI 1.26-1.62), and this association was mediated by BMI (indirect effect 0.04, 95% CI 0.03-0.05 in females and 0.03, 95% CI 0.03-0.04 in males). The BMI PGS was associated with lower odds of weight gain behaviors in females and males, which was also mediated by actual BMI.

CONCLUSIONS

The BMI PGS was associated with weight loss behaviors in both males and females, and this association was mediated by actual measured BMI. Clinical interventions to prevent high BMI, particularly for individuals with genetic risk, may also prevent subsequent development of potentially unhealthy weight loss behaviors.

Gender norms and health: insights from global survey data

Despite global commitments to achieving gender equality and improving health and wellbeing for all, quantitative data and methods to precisely estimate the effect of gender norms on health inequities are underdeveloped. Nonetheless, existing global, national, and subnational data provide some key opportunities for testing associations between gender norms and health. Using innovative approaches to analysing proxies for gender norms, we generated evidence that gender norms impact the health of women and men across life stages, health sectors, and world regions. Six case studies showed that: (1) gender norms are complex and can intersect with other social factors to impact health over the life course; (2) early gender-normative influences by parents and peers can have multiple and differing health consequences for girls and boys; (3) non-conformity with, and transgression of, gender norms can be harmful to health, particularly when they trigger negative sanctions; and (4) the impact of gender norms on health can be context-specific, demanding care when designing effective gender-transformative health policies and programmes. Limitations of survey-based data are described that resulted in missed opportunities for investigating certain populations and domains. Recommendations for optimising and advancing research on the health impacts of gender norms are made.

Author Correction: Testing the key assumption of heritability estimates based on genome-wide genetic relatedness

In the original paper, we used the variable "URBRUR08," from the 2008 survey wave as a measure of childhood urbanicity. Upon further investigation we realized that this variable actually measured Beale urban-rural code during the respondent's adulthood.  Thus, we reran our analysis of the pseudo-heritability of childhood urbanicity using the variable. The original results hold such that even with the first 20 principal components held constant, childhood urban-rural status appears to be ~20% "heritable" in GREML models-a figure that is actually higher than the original estimate reported in the paper (14% controlling for 25 PCs, 15% controlling for 10 PCs, and 29% controlling for two PCs). Meanwhile, the heritabilities of the other phenotypes-height, BMI and education-still do not change when they are residualized on childhood urbanicity. In other words, the original results of the paper do not change.

Genetics and the geography of health, behaviour and attainment

Young people's life chances can be predicted by characteristics of their neighbourhood¹. Children growing up in disadvantaged neighbourhoods exhibit worse physical and mental health and suffer poorer educational and economic outcomes than children growing up in advantaged neighbourhoods. Increasing recognition that aspects of social inequalities tend, in fact, to be geographical inequalities^2-5 is stimulating research and focusing policy interest on the role of place in shaping health, behaviour and social outcomes. Where neighbourhood effects are causal, neighbourhood-level interventions can be effective. Where neighbourhood effects reflect selection of families with different characteristics into different neighbourhoods, interventions should instead target families or individuals directly. To test how selection may affect different neighbourhood-linked problems, we linked neighbourhood data with genetic, health and social outcome data for >7,000 European-descent UK and US young people in the E-Risk and Add Health studies. We tested selection/concentration of genetic risks for obesity, schizophrenia, teen pregnancy and poor educational outcomes in high-risk neighbourhoods, including genetic analysis of neighbourhood mobility. Findings argue against genetic selection/concentration as an explanation for neighbourhood gradients in obesity and mental health problems. By contrast, modest genetic selection/concentration was evident for teen pregnancy and poor educational outcomes, suggesting that neighbourhood effects for these outcomes should be interpreted with care.

Genetic Risks for Chronic Conditions: Implications for Long-term Wellbeing

Background

Relationships between genetic risks for chronic diseases and long-run wellbeing are largely unexplored. We examined the associations between genetic predispositions to several chronic conditions and long-term functional health and socioeconomic status (SES).

Methods

We used data on a nationally representative sample of 9,317 adults aged 65 years or older from the 1992 to 2012 Health and Retirement Survey (HRS) in the US. Survey data were linked to genetic data on nearly 2 million single-nucleotide polymorphisms (SNPs). We measured individual-level genetic predispositions for coronary-artery disease, type 2 diabetes (T2D), obesity, rheumatoid arthritis (RA), Alzheimer's disease, and major depressive disorder (MDD) by polygenic risk scores (PRS) derived from genome-wide association studies (GWAS). The outcomes were self-rated health, depressive symptoms, cognitive ability, activities of everyday life, educational attainment, and wealth. We employed regression analyses for the outcomes including all polygenic scores and adjusting for gender, birth period, and genetic ancestry.

Results

The polygenic scores had important associations with functional health and SES. An increase in genetic risk for all conditions except T2D was significantly (p < .01) associated with reduced functional health and socioeconomic outcomes. The magnitudes of functional health declines were meaningful and in many cases equivalent in magnitude to several years of aging. These associations were robust to several sensitivity checks for ancestry and adjustment for parental educational attainment and age at death or the last interview if alive.

Conclusion

Stronger genetic predispositions for leading chronic conditions are related to worse long-run health and SES outcomes, likely reflecting the adverse effects of the onset of these conditions on one's wellbeing.

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Conceptualizing School Belongingness in Native Youth: Factor Analysis of the Psychological Sense of School Membership Scale

The Psychological Sense of School Membership (PSSM) scale is widely used to measure school belongingness among adolescents. However, previous studies identify inconsistencies in factor structures across different populations. The factor structure of the PSSM has yet to be examined with American Indian/Alaska Native (AI/AN) youth, a population of keen interest given reports of their educational and health disparities, and the potential of belongingness as a protective factor against risk behaviors. Thus, this study examined the factor structure of the PSSM in two samples of AI adolescents (N = 349). The two main aims of this study were to 1) determine if a comparable factor structure exists between the two AI groups and 2) examine the factor structure of the PSSM for use in AI/AN populations. Randomization analysis was used to test research aim one, and exploratory factor analysis was used to test research aim two. Analyses revealed that comparable factor structures existed based on responses from the two AI groups. Analyses also identified two factors: school identification/peer support and connection with teachers. Moreover, negatively worded statements were found to be unreliable and were removed from the final scale, reducing the PSSM to 13 items. Findings from this study will assist researchers and clinicians with assessing sense of school belongingness in AI/AN adolescents and with appropriately interpreting aspects of belongingness for this population.

Wide educational disparities in young adult cardiovascular health

Widening educational differences in overall health and recent stagnation in cardiovascular disease mortality rates highlight the critical need to describe and understand educational disparities in cardiovascular health (CVH) among U.S. young adults. We use two data sets representative of the U.S. population to examine educational disparities in CVH among young adults (24-34) coming of age in the 21st century: the National Health and Nutrition Examination Survey (2005-2010; N= 689) and the National Longitudinal Study of Adolescent to Adult Health (2007-2008; N=11,200). We employ descriptive statistics and regression analysis. The results show that fewer than one in four young adults had good CVH (at least 5 out of 7 ideal cardiovascular indicators). Young adults who had not attained a college degree demonstrate particularly disadvantaged CVH compared with their college-educated peers. Such educational disparities persist after accounting for a range of confounders, including individuals' genetic propensity to develop coronary artery disease. The results indicate that the CVH of today's young adults is troubling and especially compromised for individuals with lower levels of educational attainment. These results generate substantial concern about the future CVH of the US population, particularly for young adults with a low level of education.

Education, Smoking, and Cohort Change: Forwarding a Multidimensional Theory of the Environmental Moderation of Genetic Effects

We introduce a genetic correlation by environment interaction model [(rG)xE] which allows for social environmental moderation of the genetic relationship between two traits. To empirically demonstrate the significance of the (rG)xE perspective, we use genome wide information from respondents of the Health and Retirement Study (HRS; n = 8,181; birth years 1920-1959) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,347; birth years 1974-1983) to examine whether the genetic correlation (rG) between education and smoking has increased over historical time. Genetic correlation estimates (rG_HRS = -0.357; rG_{Add Health} = -0.729) support this hypothesis. Using polygenic scores for educational attainment, we show that this is not due to latent indicators of intellectual capacity, and we highlight the importance of education itself as an explanation of the increasing genetic correlation. Analyses based on contextual variation the milieus of the Add Health respondents corroborate key elements of the birth cohort analyses. We argue that the increasing overlap with respect to genes associated with educational attainment and smoking is a fundamentally social process involving complex process of selection based on observable behaviors that may be linked to genotype.

Schools as Moderators of Genetic Associations with Life Course Attainments: Evidence from the WLS and Add Health

Genetic variants identified in genome-wide association studies of educational attainment have been linked with a range of positive life course development outcomes. However, it remains unclear whether school environments may moderate these genetic associations. We analyze data from two biosocial surveys that contain both genetic data and follow students from secondary school through mid- to late life. We test if the magnitudes of the associations with educational and occupational attainments varied across the secondary schools that participants attended or with characteristics of those schools. Although we find little evidence that genetic associations with educational and occupational attainment varied across schools or with school characteristics, genetic associations with any postsecondary education and college completion were moderated by school-level socioeconomic status. Along similar lines, we observe substantial between-school variation in the average level of educational attainment students achieved for a fixed genotype. These findings emphasize the importance of social context in the interpretation of genetic associations. Specifically, our results suggest that though existing measures of individual genetic endowment have a linear relationship with years of schooling that is relatively consistent across school environments, school context is crucial in connecting an individual's genotype to his or her likelihood of crossing meaningful educational thresholds.

Genetic analysis of social-class mobility in five longitudinal studies

A summary genetic measure, called a "polygenic score," derived from a genome-wide association study (GWAS) of education can modestly predict a person's educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents' position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother's polygenic score predicted her child's attainment over and above the child's own polygenic score, suggesting parents' genetics can also affect their children's attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals' family-of-origin environments and their social mobility.

Genetic nature or genetic nurture? Introducing social genetic parameters to quantify bias in polygenic score analyses

Results from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS), an individual-level measure summarizing identified genetic influence on a trait dispersed across the genome. For complex, behavioral traits, the association between an individual's PGS and their phenotype may contain bias (from geographic, ancestral, and/or socioeconomic confounding) alongside the causal effect of the individual's genes. We formalize the introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes, known as genetic nurture. GWAS do not discriminate between the various pathways through which genes become associated with outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a theoretical model for genetic effects and show that the presence of genetic nurture biases PGS coefficients from both naïve OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naïve OLS estimates are biased away from zero, family fixed effects estimates are biased toward zero. We quantify this bias using two novel parameters: (1) the genetic correlation between the direct and nurture effects and (2) the ratio of the SNP heritabilities for the direct and nurture effects.

Geographic Clustering of Polygenic Scores at Different Stages of the Life Course

We interrogate state-level clustering of polygenic scores at different points in the life course and variation in the association of mean polygenic scores in a respondent's state of birth with corresponding phenotypes. The polygenic scores for height and smoking show the most state-level clustering (2 to 4 percent) with relatively little clustering observed for the other scores. However, even the small amounts of observed clustering are potentially meaningful. The state-mean polygenic score for educational attainment is strongly associated with an individual's educational attainment net of that person's polygenic score. The ecological clustering of polygenic scores may denote a new environmental factor in gene-environment research. We conclude by discussing possible mechanisms that underlie this association and the implications of our findings for social and genetic research.

The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health

Humans tend to form social relationships with others who resemble them. Whether this sorting of like with like arises from historical patterns of migration, meso-level social structures in modern society, or individual-level selection of similar peers remains unsettled. Recent research has evaluated the possibility that unobserved genotypes may play an important role in the creation of homophilous relationships. We extend this work by using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic similarities among pairs of friends. Although there is some evidence that friends have correlated genotypes, both at the whole-genome level as well as at trait-associated loci (via polygenic scores), further analysis suggests that meso-level forces, such as school assignment, are a principal source of genetic similarity between friends. We also observe apparent social-genetic effects in which polygenic scores of an individual's friends and schoolmates predict the individual's own educational attainment. In contrast, an individual's height is unassociated with the height genetics of peers.

Genetic Predisposition to Obesity and Medicare Expenditures

Background

The relationship between obesity and health expenditures is not well understood. We examined the relationship between genetic predisposition to obesity measured by a polygenic risk score for body mass index (BMI) and Medicare expenditures.

Methods

Biennial interview data from the Health and Retirement Survey for a nationally representative sample of older adults enrolled in fee-for-service Medicare were obtained from 1991 through 2010 and linked to Medicare claims for the same period and to Genome-Wide Association Study (GWAS) data. The study included 6,628 Medicare beneficiaries who provided 68,627 complete person-year observations during the study period. Outcomes were total and service-specific Medicare expenditures and indicators for expenditures exceeding the 75th and 90th percentiles. The BMI polygenic risk score was derived from GWAS data. Regression models were used to examine how the BMI polygenic risk score was related to health expenditures adjusting for demographic factors and GWAS-derived ancestry.

Results

Greater genetic predisposition to obesity was associated with higher Medicare expenditures. Specifically, a 1 SD increase in the BMI polygenic risk score was associated with a $805 (p < .001) increase in annual Medicare expenditures per person in 2010 dollars (~15% increase), a $370 (p < .001) increase in inpatient expenses, and a $246 (p < .001) increase in outpatient services. A 1 SD increase in the polygenic risk score was also related to increased likelihood of expenditures exceeding the 75th percentile by 18% (95% CI: 10%-28%) and the 90th percentile by 27% (95% CI: 15%-40%).

Conclusion

Greater genetic predisposition to obesity is associated with higher Medicare expenditures.