Psychosocial functioning and intelligence both partly explain socioeconomic inequalities in premature death. A population-based male cohort study

The possible contributions of psychosocial functioning and intelligence differences to socioeconomic status (SES)-related inequalities in premature death were investigated. None of the previous studies focusing on inequalities in mortality has included measures of both psychosocial functioning and intelligence.The study was based on a cohort of 49 321 men born 1949-1951 from the general community in Sweden. Data on psychosocial functioning and intelligence from military conscription at ∼18 years of age were linked with register data on education, occupational class, and income at 35-39 years of age. Psychosocial functioning was rated by psychologists as a summary measure of differences in level of activity, power of initiative, independence, and emotional stability. Intelligence was measured through a multidimensional test. Causes of death between 40 and 57 years of age were followed in registers.The estimated inequalities in all-cause mortality by education and occupational class were attenuated with 32% (95% confidence interval: 20-45%) and 41% (29-52%) after adjustments for individual psychological differences; both psychosocial functioning and intelligence contributed to account for the inequalities. The inequalities in cardiovascular and injury mortality were attenuated by as much as 51% (24-76%) and 52% (35-68%) after the same adjustments, and the inequalities in alcohol-related mortality were attenuated by up to 33% (8-59%). Less of the inequalities were accounted for when those were measured by level of income, with which intelligence had a weaker correlation. The small SES-related inequalities in cancer mortality were not attenuated by adjustment for intelligence.Differences in psychosocial functioning and intelligence might both contribute to the explanation of observed SES-related inequalities in premature death, but the magnitude of their contributions likely varies with measure of socioeconomic status and cause of death. Both psychosocial functioning and intelligence should be considered in future studies

Initial evidence that non-clinical autistic traits are associated with lower income

Among non-clinical samples, autistic traits correlate with a range of educational and social outcomes. However, previous work has not investigated the relationship between autistic traits and income, a key determinant of socio-economic status and wellbeing. In 5 studies (total N = 2491), we recruited participants without a diagnosis of autism from the general US population via an on-line platform, and administered the short-form Autism Spectrum Quotient (AQ) as well as asking a range of demographic questions. We found a negative association between AQ and household income, which remained robust after controlling for age, gender, education, employment status, ethnicity, and socially-desirable responding. The effect was primarily driven by the participant’s own income, and was mainly due to the social subscale of the AQ. These results provide initial evidence that income is negatively related to autistic traits among the general population, with potential implications for a range of social, psychological, and health outcomes.WJS was supported by Wellcome Trust grant RG76641 and Isaac Newton Trust grant RG70368. SBC was supported by the Autism Research Trust

Implications of Advancing Paternal Age: Does It Affect Offspring School Performance?

Average paternal age is increasing in many high income countries, but the implications of this demographic shift for child health and welfare are poorly understood. There is equivocal evidence that children of older fathers are at increased risk of neurodevelopmental disorders and reduced IQ. We therefore report here on the relationship between paternal age and a composite indicator of scholastic achievement during adolescence, i.e. compulsory school leaving grades, among recent birth cohorts in Stockholm County where delayed paternity is notably common. We performed a record-linkage study comprising all individuals in Stockholm County who finished 9 years of compulsory school from 2000 through 2007 (n = 155,875). Data on school leaving grades and parental characteristics were retrieved from administrative and health service registers and analyzed using multiple linear regression. Advancing paternal age at birth was not associated with a decrease in school leaving grades in adolescent offspring. After adjustment for year of graduation, maternal age and parental education, country of birth and parental mental health service use, offspring of fathers aged 50 years or older had on average 0.3 (95% CI −3.8, 4.4) points higher grades than those of fathers aged 30–34 years. In conclusion, advancing paternal age is not associated with poorer school performance in adolescence. Adverse effects of delayed paternity on offspring cognitive function, if any, may be counterbalanced by other potential advantages for children born to older fathers

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (<i>N</i>=112 151) and 24 GWAS consortia

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular–metabolic, neuropsychiatric, physiological–anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer’s disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples

Non-verbal IQ Gains from Relational Operant Training Explain Variance in Educational Attainment: An Active-Controlled Feasibility Study

Research suggests that training relational operant patterns of behavior can lead to increases in general cognitive ability and educational outcomes. Most studies to date have been under-powered and included proxy measures of educational attainment. We attempted to extend previous findings with increased experimental control in younger children (aged 6.9–10.1 years). Participants (N = 49) were assigned to either a relational training or chess control group. Over 5 months, teachers assigned class time to complete either relational training or play chess. Those who were assigned relational training gained 8.9 non-verbal IQ (NVIQ) points, while those in the control condition recorded no gains (dppc2 = .99). Regression analyses revealed that post-training NVIQ predicted reading test scores (conducted approximately 1 month later) over and above baseline NVIQ in the experimental condition only, consistent with what we might expect in a full test of far transfer towards educational outcomes

Attribution-based motivation treatment efficacy in an online learning environment for students who differ in cognitive elaboration

Attribution-based motivation treatments can boost performance in competitive achievement settings (Perry and Hamm 2017), yet their efficacy relative to mediating processes and affect-based treatments remains largely unexamined. In a two-semester, pre-post, randomized treatment study (n = 806), attributional retraining (AR) and stress-reduction (SR) treatments were administered in an online learning environment to first-year college students who differed in cognitive elaboration (low, high). Low elaborators who received AR outperformed their SR peers by nearly a letter grade on a class test assessed 5 months post-treatment. Path analysis revealed this AR-performance linkage was mediated by causal attributions, perceived control, and positive and negative achievement emotions in a hypothesized causal sequence. Results advance the literature by showing AR (vs. SR) improved performance indirectly via cognitive and affective process variables specified by Weiner’s (1985a, 2012) attribution theory of motivation and emotion

Differences in exam performance between pupils attending selective and non-selective schools mirror the genetic differences between them

On average, students attending selective schools outperform their non-selective counterparts in national exams. These differences are often attributed to value added by the school, as well as factors schools use to select pupils, including ability, achievement and, in cases where schools charge tuition fees or are located in affluent areas, socioeconomic status. However, the possible role of DNA differences between students of different schools types has not yet been considered. We used a UK-representative sample of 4814 genotyped students to investigate exam performance at age 16 and genetic differences between students in three school types: state-funded, non-selective schools (‘non-selective’), state-funded, selective schools (‘grammar’) and private schools, which are selective (‘private’). We created a genome-wide polygenic score (GPS) derived from a genome-wide association study of years of education (EduYears). We found substantial mean genetic differences between students of different school types: students in non-selective schools had lower EduYears GPS compared to those in grammar (d = 0.41) and private schools (d = 0.37). Three times as many students in the top EduYears GPS decile went to a selective school compared to the bottom decile. These results were mirrored in the exam differences between school types. However, once we controlled for factors involved in pupil selection, there were no significant genetic differences between school types, and the variance in exam scores at age 16 explained by school type dropped from 7% to <1%. These results show that genetic and exam differences between school types are primarily due to the heritable characteristics involved in pupil admission