Importance: Family history is a prominent indicator of psychiatric disorder risk and used in clinical assessment. Pearson-Aitken Family-Genetic Risk Scores (PA-FGRSs) aim to quantify genetic risk based on diagnostic history of family members and genetic relatedness. However, there is limited knowledge about how PA-FGRSs characterize psychiatric and neurodevelopmental diagnoses, clinical indicators (age of onset, recurrence), and their assumptions. Objective: Provide an overview of how PA-FGRS characterize psychiatric and neurodevelopmental diagnoses, relationships with clinical indices, partner similarity, and use a within-family design to examine assumptions of the PA-FGRS. Design, Setting, and Participants: This cohort study included 6 242 506 Norwegian residents born between 1934 and 2023. We observed participants from January 1st 2006 through December 31st 2023 using Norwegian primary and specialist healthcare registry data (including inpatient and outpatient clinics). We also incorporated a genotyped parent-offspring subsample from the Norwegian Mother, Father and Child Cohort Study. Exposures: PA-FGRSs for 10 major psychiatric (alcohol use, drug use, schizophrenia, bipolar, depression, anxiety and stress-related, obsessive-compulsive, and eating disorders) and neurodevelopmental diagnoses (ADHD and autism). We incorporated polygenic indices (PGIs) for drug use, schizophrenia, bipolar disorder, depression, autism, and ADHD. Main Outcomes and Measures We calculated individual-level PA-FGRSs for diagnoses, estimated associations with clinical indicators, and examined partner similarity. We compared empirical and theoretically expected PA-FGRS and PGI correlations to evaluate the PA-FGRS as a between-family index of risk. Results: Diagnosis-specific PA-FGRSs were most strongly elevated when comparing affected and unaffected individuals for most diagnoses, while PA-FGRSs for depressive and anxiety disorders were elevated across all. Higher PA-FGRS was associated with earlier age of onset and higher recurrence and partners were correlated for PA-FGRSs. The within-family design generally supported assumptions of the PA-FGRS but also suggested it does not solely capture direct genetic effects for alcohol use disorder. Conclusions and relevance: PA-FGRSs exhibit varying patterns across psychiatric and neurodevelopmental diagnoses and are associated with recurrence and age of onset. While we found support for key assumptions of PA-FGRS, potential impact of assortative mating should be explored further. The PA-FGRS offers a scalable approach to identify familial liability in population registry data and its application can provide insights into the etiology of psychiatric and neurodevelopmental conditions.

Background From a functionalist perspective, parenting behaviors have adaptive functions and are partly expressions of genetic variation. Maternal genes that have effects on children are often referred to as indirect maternal genetic effects. Indirect genetic effects provide a means for measuring the role of parenting without the need for specifying the relevant parental behaviors. We studied indirect maternal genetic effects to address both the importance and commonality of parenting across the internalizing-externalizing spectrum of behavior problems in childhood. We further addressed how indirect genetic effects impact our understanding of direct genetic effects if not accounted for.Methods Utilizing data from the Norwegian Mother, Father, and Child Cohort Study (MoBa), our analyses involved 42,423 children and their mothers. Both pedigree and genotype data were used to infer genetic relationships. We applied multivariate latent variable models to distinguish indirect maternal genetic effects and direct offspring genetic effects on seven measures of internalizing-externalizing behaviors.Results Our findings indicate significant maternal genetic influences, explaining 7%-18% of the variance across internalizing-externalizing behaviors. A general maternal effect common across behaviors could adequately account for most of the variability. The analyses further indicate that direct child genetic effects appear smaller and more complex when indirect maternal genetic effects are modeled simultaneously.Conclusions By summarizing the effects of parenting with indirect maternal genetic effects, we show a substantial contribution of parents with respect to internalizing-externalizing behaviors in childhood. Although parenting is multifaceted, the effects of parenting are general and can succinctly be described as a single common dimension. Further, our study demonstrates that direct genetic effects appear smaller and more complex when maternal genetic effects are accounted for, highlighting the confounding potential of parental effects in understanding the role of genetic differences in child psychopathology.

Background: Genetic variants in family members may exert environmentally mediated indirect genetic effects on children’s attention-deficit hyperactivity disorder (ADHD) traits. We set out to quantify the indirect genetic effects of parents’ genotypes on children’s ADHD traits as measured in early and mid-childhood. Methods: We analyzed data from genotyped trios of children, mothers, and fathers of European ancestry from the Norwegian Mother, Father and Child Cohort Study (MoBa) birth cohort. Child ADHD data were available for analytic subsamples of 12,374 trios at age 5 (children 50.5% male), and 12,714 trios at age 8 (children 50.9% male). We quantified direct genetic effects of children’s genotype and indirect effects of mothers’ and fathers’ genotypes on children’s ADHD traits at each age. Results: At age 5, maternal indirect genetic effects explained roughly twice as much variance in children’s ADHD traits as did child direct genetic effects. At age 8, maternal indirect genetic effects and child direct genetic effects explained roughly equal portions of variance in child ADHD traits. However, issues with power were evident throughout analyses and precluded confident interpretation of indirect genetic effects. Conclusions: We find tentative evidence for heritable parental traits exerting environmental effects on child ADHD traits in early and mid-childhood, suggesting that maternal genotypes exert indirect effects on children’s traits after accounting for the direct effects of children’s own genotype. However, future studies with larger samples are needed to enable clear inferences on the importance of indirect genetic effects for children’s ADHD traits.

Lockdowns and social restrictions imposed in response to the Covid-19 pandemic intensified the proximity and reciprocal exposure among members of nuclear families. It is unclear how variation in mental distress during this period is attributed to potential influences of family members. This study used genetic data from adolescents (n = 4 388), mothers (n = 27 852) and fathers (n = 25 953), to disentangle the contributions of parent-driven, child-driven, and partner-driven components to mental distress during the first two months of the Covid-19 lockdown. Separate models also included adolescents’ non-pandemic mental distress as outcomes (n = 13 484). Trio genome-wide complex trait analyses separated two types of genetic components; direct–how an individual’s genotype is associated with their own mental distress, and indirect–how an individual’s genotype is associated with the mental distress of family members. A trio polygenic score (PGS) design was used to investigate associations of specific genetic liability factors with mental distress, and whether these changed over time (PGS×time). Results suggest that family-level genetic factors contribute to mental distress; variance components capturing indirect genetic effects accounted for 10% of adolescent mental distress (mother-driven), 2–3% of maternal (partner-driven), and 5% of paternal mental distress (child-driven). Mothers’ depression and ADHD PGS were positively associated with fathers’ mental distress. No PGS×time interactions were found. Direct genetic effects accounted for 9–10% variance in mental distress across family members, partly explained by genetic variants associated with anxiety, depression, ADHD and neuroticism. These findings highlight the importance of family dynamics and emphasize the potential value of including family members in mental health interventions.

Background:The extent to which children's psychological traits influence their educational performance is thought to depend on the fit between the individual and their developmental context. However, this assumption has yet to be empirically tested on a population scale. This study examines how neurodevelopmental, mental health, and personality traits interact with latent environmental contexts to enhance, maintain, or mitigate their educational performance. Methods:Using the Norwegian Mother, Father and Child Cohort Study (MoBa), we estimated the association between 16 developmental traits and grade point average (GPA) in 26,875 children across environmental contexts in 2131 primary schools, 1075 middle schools, ~14,000 neighborhoods, 1471 districts, and 347 municipalities. Results:Across the developmental traits, the effect on GPA ranged from -0.286 to 0.220. However, these effects varied substantially across environmental contexts (SD 0.022 to 0.090). Trait-by-context interactions were detected in primary schools (2 traits), middle schools (6 traits), neigbourhoods (0 traits), districts (3 traits), and municipalities (1 trait), respectively. Moderation magnitudes were largest for neurodevelopmental traits in primary schools. On average, the effects of ADHD and communication difficulties were -0.252 and -0.193. However, these effects differed substantially across primary schools with SD 0.090 and 0.070, implying b < -0.370 and b < -0.282 in 10% of schools. For average children, primary schools explained 0.504% of middle school GPA. Similarly, the effect of depression and extraversion was dependent on middle-school environments (b = -0.128; SD = 0.058 and b = 0.024; SD = 0.022). Moreover, schools and districts with high GPAs tended to express lower detrimental effects on children's developmental traits. Conclusion:Schools and residential areas function as educational catalysts, enhancing or mitigating the influence of developmental traits. High-performing environments compensate for psychological challenges, whereas lower-performing contexts exacerbate difficulties. Because the study integrated multiple traits and contextual levels, the analyses were exploratory and data-driven, and the findings should be interpreted as hypothesis-generating. These results suggest a need for both context-sensitive and individually tailored educational interventions.

While it is well-established that educational attainment and Right-Wing Authoritarianism (RWA) are negatively correlated, it remains unclear why, as causal effects are hard to distinguish from the effects of confounders. Here, we use an adaptation of the discordant twin design in a structural equation framework (ACE-β models) with 1264 Norwegian monozygotic and dizygotic twins, to investigate whether education and RWA remain associated after controlling for confounders from genes and environmental influences shared by twins. Our model estimates that 25% of the covariance between education and RWA reflects genetic confounders, 47% reflects shared-environmental confounders, and 28% of the covariance remains unaccounted for. This remaining covariance then reflects causal effects and/or environmental confounders not shared by twins. Perceived socioeconomic status (SES) in childhood accounted for about one-third of the shared-environmental confounding. We did not find evidence that effects of education on RWA are mediated by perceived SES in adulthood.

BACKGROUND:The intergenerational transmission of obesity-related traits could propagate an accelerating cycle of obesity, if parental adiposity causally influences offspring adiposity. The extent to which intergenerational obesity associations are due to such causal effects, as opposed to genetic confounding (inheritance), is unclear. We aimed to establish whether associations between parental peri-pregnancy body mass index (BMI) and offspring birth weight (BW), BMI until 8 years of age, and 8-year-old eating behaviour are due to genetic confounding. METHODS AND FINDINGS:Data were from the Norwegian Mother, Father and Child Cohort Study, a prospective population-based birth cohort born between 1999 and 2009 at 50 out of 52 hospital maternity units in Norway. We compared the strength of the associations of maternal pre-pregnancy BMI versus paternal BMI during pregnancy, with offspring outcomes including birth weight and BMI assessed between age 6 months and 8 years of age, and appetite-related eating behaviour traits assessed at age 8 years via the Child Eating Behaviour Questionnaire (CEBQ), adjusting for potential confounders including parity, parental/grandparental language group and parental age, smoking, education and income). We then used an extended children of twins structural equation model (SEM) to quantify the extent to which associations were due to genetic confounding. Up to 85,866 children (51.3% male) were included in linear regression models, whereas SEM models included up to 50,999 children. Maternal BMI was more strongly associated than paternal BMI with offspring BW, but the maternal-paternal difference decreased for offspring BMI after birth. Greater parental BMI was associated with obesity-related offspring eating behaviours. SEM results indicated that genetic confounding did not explain the association between parental BMI and offspring BW, but explained the majority of the association with offspring BMI from 6 months onwards. For 8-year BMI, genetic confounding explained 79% (95% CI [62, 95]; p = 1.9 × 10-12) of the covariance with maternal BMI and 94% (95% CI [72, 113]; p = 2.7 × 10-14) of the covariance with paternal BMI. Limitations of this study include selective recruitment and attrition, potential bias due to parental assortative mating, and that findings may not generalise beyond high-income country settings with high obesity prevalence. CONCLUSIONS:We found strong evidence that parent-child BMI associations may primarily be due to genetic confounding. When considered alongside prior evidence, this finding may argue against a strong causal effect of maternal or paternal adiposity on childhood adiposity via intrauterine or periconceptional mechanisms.

Complex traits emerge from reciprocal interactions among genotype, environment, and developmental processes. Yet, standard genetic models assume purely additive effects, potentially obscuring non-additive effects. Here, we introduce a longitudinal log-linear variance and genotype-by-time model to detect associations from within-individual variation departing from additivity, i.e., putative non-additive effects. Applied to early growth (infant length and BMI) and cognitive traits (math and reading) of 45,000 to 65,000 individuals, we report 76 lead putative non-additive loci that are enriched 16-fold for cis-regulatory interactions. Of the 76, 6 overlap prior interaction studies (anthropometric) and only 3 loci overlap prior genome-wide association study (GWAS) (cognitive). Accounting for scale effects and linkage disequilibrium (LD), we observe that additive effects are correlated with putative non-additive effects, i.e., "effect pleiotropy." These results are consistent with non-additive genetic contribution to trait development, which may partly be absorbed by effects estimated under standard GWAS parameterization that assumes strict additivity.

BACKGROUND:Within-family designs are increasingly used to decompose genotype-trait associations into direct and indirect genetic effects. Many such designs, including trio designs or within-sibship designs, assume an absence of sibling indirect genetic effects. METHODS:We expand two well-known molecular genetic within-family designs, one variance component (genome-based restricted maximum likelihood) and one trait-based (structural equation modeling with polygenic indices), to estimate sibling indirect genetic effects, along with direct genetic effects. We link the Norwegian Mother, Father, and Child Cohort Study (MoBa) to Norway's national education database to model genetic effects on national standardized testing results at ages 10, 13, and 14, and on parent-rated attention-deficit hyperactivity disorder (ADHD) symptoms at ages 3 and 8 in up to 15,971 genotyped and phenotyped siblings. RESULTS:Estimates of direct and indirect genetic effects from the genome-based restricted maximum likelihood and the structural equation modeling with polygenic indices approaches converge, albeit with the variance component estimates typically an order of magnitude greater than the trait-based estimates. We observe no indirect genetic effects of siblings on educational performance at any age, and only slightly negative indirect genetic effects of siblings on ADHD symptoms at age 3. We argue that the latter effect might reflect parental contrasting ratings. CONCLUSIONS:The results suggest that within-family models of educational performance are unlikely to be drastically biased by an assumption of absent sibling indirect genetic effects. Combining trait-based analyses with variance component analyses can benefit understanding of indirect genetic effects, especially when the effects are not specific to a particular mechanism.

Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease1. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother-father-child trios2,3. However, samples of genotyped families are rare4-11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. 3), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children's height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

Research on mental health has traditionally separated the study of ill-being, including clinically defined mental and behavioural disorders and subthreshold problems, from the study of well-being, which encompasses factors such as life satisfaction and positive affect. Although previous reviews of studies primarily using self-report scales indicate that ill-being and well-being are distinct yet interconnected constructs, a deeper examination of their relationship is lacking. In this Perspective, we synthesize genetic, biological, developmental, psychosocial, societal, cultural and clinical research on ill-being and well-being. Our review reveals substantial genetic overlap and similar biological underpinnings for ill-being and well-being. By contrast, environmental factors and societal changes often exert divergent influences. We propose a differentiated multidisciplinary framework in which the shared and unique determinants, predictors, mechanisms and consequences of mental ill-being and well-being vary across levels of analysis, offering a more nuanced understanding of the interconnections.

We investigate the hypothesis that family resemblance on school performance can be fully explained by additive genetic effects and assortative mating. Our sample consists of all schoolchildren who took Norwegian national standardized tests between 2007 and 2019 (N = 936,708). These tests measure aptitude in math and reading comprehension, and are taken the years children turn 10, 13, and 14 y old. We identify millions of pairs of relatives within our sample (82 different kinds, in total), including not only conventional biological relatives such as siblings and cousins, but also relatives-in-law, relatives through adoption, twins, and relatives connected through twins. When fitting models which assume that family resemblance arises solely from additive genetic effects and assortative mating, we find that they describe much of our data well, but that they systematically underestimate the similarity of close relatives (particularly monozygotic twins), maternal relatives, relatives-in-law, and relatives through adoption. We discuss potential explanations for these deviations, including shared-environmental effects, nonadditive genetic effects, and gene–environment interplay.

Educational field choices shape careers, wellbeing and the societal skill distribution, yet genetic influences on what people study remain poorly understood. Here we show that genetic factors are associated with educational field specializations using genome-wide association studies (GWASs) across 463,134 individuals from Finland, Norway and the Netherlands (effective n between 40,072 and 317,209). We identified 17 independent genome-wide significant variants linked to 7 of 10 educational fields, with average heritability of 7%. The genetic signal is specific to field choice rather than educational level, persisting after controlling for years of schooling and confounding factors. By examining genetic clustering across specializations, we uncovered two key dimensions: technical versus social and practical versus abstract. We performed GWASs of these components and demonstrated distinct genetic correlations with personality, behavior and socioeconomic status. Our findings demonstrate that genomic research can illuminate 'horizontal' stratification, revealing insights into vocational interests and social sorting beyond traditional attainment measures.

BACKGROUND:Lower parental income is associated with more psychiatric disorders among offspring, but it is unclear if this association reflects effects of parental income (social causation) or shared risk factors (social selection). Prior research finds contradictory results, which may be due to age differences between the studied offspring. METHODS:Here, we studied psychiatric disorders in the entire Norwegian population aged 10 to 40 years between 2006 and 2018 (N = 2,468,503). By linking tax registries to administrative health registries, we described prevalence rates by age, sex, and parental income rank. Next, we grouped observations into age groups (adolescence, ages 10-20 years; early adulthood, 21-30 years; adulthood, 30-40 years) and applied kinship-based models with extended families of twins and siblings to decompose the parent-offspring correlation into phenotypic transmission, passive genetic transmission, and passive environmental transmission. RESULTS:We found that lower parental income rank was associated with higher prevalence of nearly all psychiatric disorders, except for eating disorders, for both men and women at all ages from 10 to 40 years. Comparing the top with the bottom paternal income quartile, the prevalence ratio of any psychiatric disorder was 0.47 among 10-year-olds and decreased to 0.72 among 40-year-olds. The parent-offspring correlation was -.15 in adolescence, -.10 in early adulthood, and -.06 in adulthood. The kinship-based models indicated that phenotypic transmission could account for 39% of the parent-offspring correlation among adolescents (p < .001), but with no significant contribution in early adulthood (p = .181) or adulthood (p = .737). Passive genetic and environmental transmission contributed to the parent-offspring correlation in all age groups (all p's < .001). CONCLUSIONS:Our findings are consistent with a significant role of social causation during adolescence, while social selection could fully explain the parent-offspring correlation in adulthood.

Estimating the contributions of genetic and environmental factors is key to understanding differences in socioeconomic status (SES). However, the heritability of SES varies by measure, method, and context. Here, we estimate genetic and environmental sources of variance and commonality in the 'big four' SES indicators. We use high-quality administrative data on educational attainment, occupational prestige, income, and wealth, and employ four family-based and unrelated genotype-based heritability methods, all drawn from the same population-wide cohort of >170,000 Norwegians aged 35-45. By drawing subsamples from a consistent sample and using registry-based data, we reduce differences in estimates due to population characteristics and measurement error. Our results show that genetic variation consistently explains more for educational attainment and occupational prestige. Family-shared environmental contributions explained more for educational attainment and wealth. Our results highlight considerable common influences on the four SES indicators among genetic and shared environmental factors, but not among non-shared environmental factors. Overall, we show how the relative importance of genetic and environmental factors to SES differences in Norway varies by method and type of socioeconomic attainment. This study is a reliable source for comparing heritability methods, and for comparing SES indicators and their genetic and environmental commonality in a social-democratic welfare state.

We develop a framework for understanding indirect assortative mating and provide updated definitions of key terms. We then develop family models that use partners of twins and siblings to freely estimate the degree of genetic and social homogamy, and account for it when investigating sources of parent-offspring similarity. We applied the models to educational attainment using 1,545,444 individuals in 212,070 extended families in the Norwegian population and Norwegian Twin Registry. Partner similarity in education was better explained by indirect assortment than direct assortment on observed educational attainment, with social homogamy being particularly important. The implied genotypic partner correlation ( r = 0.34) was comparable to earlier studies, and higher than expected under direct assortment. About 38% of the parent-offspring correlation ( r = 0.34) was attributable to various forms of environmental transmission. Alternative models that assumed direct assortment estimated environmental transmission to be lower, but these did not fit the data well.

Traditional perspectives emphasize a unidirectional link between parental economic outcomes and child traits, but effects could be bidirectional; child behavioral or health-related traits might elicit caregiving and practical demands that affect parents’ economic outcomes heterogenously. Advances in genomics enable testing this reverse causal pathway by leveraging the random allocation of alleles from parents to offspring. First, we linked ~28,000 genotyped parent-offspring trios from the Norwegian Mother, Father and Child Cohort to yearly registry data on parental labor income, net wealth, and government transfers from three years before to fifteen years after birth. Second, we estimated the overall impact of the first child in the genotyped sample using event studies. Third, we estimated the impact of common genetic variation in children on parental economic outcomes. We used relatedness disequilibrium regression to estimate the total effect of children’s genetic differences and within-family polygenic index models to test particular child genetic dispositions. Event studies show a larger impact associated with child birth for maternal outcomes compared to paternal outcomes. The genetically informed methods yielded inconclusive statistical evidence of child-driven genetic effects on parental economic outcomes. Translating effect sizes into practical terms, a child one standard deviation above the mean on a relevant genetic trait would be expected to reduce the parental “child penalty” by near zero at the confidence interval lower bound and roughly 40% at the upper confidence interval bound. Although mitigation of effects by the Norwegian welfare state is likely, both null and moderate effects remain plausible, warranting further investigation. In this exploratory study, we provide a novel foundation for future research on child-driven economic effects and how institutions limit their impact.

Background Neurodevelopmental conditions are highly heritable. Recent studies have shown that genomic heritability estimates can be confounded by genetic effects mediated via the environment (indirect genetic effects). However, the relative importance of direct versus indirect genetic effects on early variability in traits related to neurodevelopmental conditions is unknown. Methods The sample included up to 24,692 parent‐offspring trios from the Norwegian MoBa cohort. We use Trio‐GCTA to estimate latent direct and indirect genetic effects on mother‐reported neurodevelopmental traits at age of 3 years (restricted and repetitive behaviors and interests, inattention, hyperactivity, language, social, and motor development). Further, we investigate to what extent direct and indirect effects are attributable to common genetic variants associated with autism, ADHD, developmental dyslexia, educational attainment, and cognitive ability using polygenic scores (PGS) in regression modeling. Results We find evidence for contributions of direct and indirect latent common genetic effects to inattention (direct: explaining 4.8% of variance, indirect: 6.7%) hyperactivity (direct: 1.3%, indirect: 9.6%), and restricted and repetitive behaviors (direct: 0.8%, indirect: 7.3%). Direct effects best explained variation in social and communication, language, and motor development (5.1%–5.7%). Direct genetic effects on inattention were captured by PGS for ADHD, educational attainment, and cognitive ability, whereas direct genetic effects on language development were captured by cognitive ability, educational attainment, and autism PGS. Indirect genetic effects on neurodevelopmental traits were primarily captured by educational attainment and/or cognitive ability PGS. Conclusions Results were consistent with differential contributions to neurodevelopmental traits in early childhood from direct and indirect genetic effects. Indirect effects were particularly important for hyperactivity and restricted and repetitive behaviors and interests and may be linked to genetic variation associated with cognition and educational attainment. Our findings illustrate the importance of within‐family methods for disentangling genetic processes that influence early neurodevelopmental traits, even when identifiable associations are small.

Background:Young people from families with low socioeconomic position have higher rates of mental disorders. However, wealth is underexamined despite large wealth inequity worldwide. Here, we aim to investigate the relationship between early life parental wealth and mental disorders in young Norwegians. Methods:We conducted a population study of associations between early-life parental wealth and 17 diagnostic categories of mental disorders in 1.4 M children (7-12), adolescents (13-18), and young adults (19-24) observed 2006-2023. Ranked parental socioeconomic indicators at age 0-6 (wealth, income, occupation, and education) and mental disorder diagnoses (ICD-10 and ICPC-2) were obtained from Norwegian Tax, Employment, Education, and Control and Payment of Health Reimbursements registries. Estimates were derived from mean prevalences, generalised estimating equations, and sibling comparison designs. Findings:Parental wealth represents a gradient in young people's mental disorders across age, sex, diagnostic categories, and cohorts. The lowest wealth quintile demonstrated 87% [95% CI = 78-96%] higher 1-year prevalence than the highest quintile. In multivariable analyses, parental wealth was the strongest predictor of mental disorders relative risk in adolescents (1.83 [1.76-1.9]) and young adults (1.92 [1.8-2.04]), while wealth (1.53 [1.46-1.6]) and education (1.52 [1.45-1.6]) were the strongest predictors in children. Parental wealth has a significant within-family association with mental disorders (relative risks: children 1.57 [1.44-1.71], adolescents 1.34 [1.26-1.42], young adults 1.42 [1.31-1.54]). Interpretation:Our study serves as a point of reference for understanding the relationship between parental wealth and mental health. Our findings establish early life parental wealth as a fundamental social gradient in young people's mental disorders. Funding:European Research Council consolidator grant (#101045526).

Underwater vehicles and other mobile platforms are seeing increased use as tools within fish farming, particularly due to current trends towards Precision Farming practices, and more exposed farming sites. Although many of the applications of such tools (e.g., net cleaning and inspection) have become well established industrial practices, it is largely unknown how much such operations disturb the fish and the consequence of this disturbance. In this study, we explored this by exposing Atlantic salmon in commercial net cages to intrusive objects and monitoring the distribution of fish around these using on-board 360-degree sonars. Six different object designs were tested covering variations in size, shape, and colour, which are important static characteristics of underwater vehicles/platforms. The sonar data was first aggregated into images containing the Cumulative Fish Presence over 1-, 5- and 10-min periods to provide a more robust foundation for further analyses. By training a deep learning based method using UNet++ architecture to automatically segment the fish distribution patterns, the mean distance between the inner perimeter of the fish distribution and the object was assessed. Results from the study implied that fish keep greater distances to larger objects. There was, however, no clear impact of the shape. Regarding the effect of colour, fish kept greater distances to yellow than to white objects. When comparing results from tests on fish of different size, data indicate a positive linear relationship between fish weight (age) and distance to an object, that can be expressed as an avoidance distance of an average 3.8 body-lengths. Our findings provide new fundamental knowledge on the dynamics between the fish and objects such as vehicles or other mobile platforms in fish farms, and thus provides valuable insights that can be useful when designing such tools specifically for aquaculture.