Cognitive ability in early life and risk of depression in adulthood: A systematic review and meta-analysis.

BACKGROUND: There is an established association between cognitive ability and risk of depression, though the direction of this association is unclear. Measuring cognitive ability in childhood, prior to the diagnosis of depression, could help to understand whether childhood cognitive ability is associated with a later diagnosis of depression. This systematic review and meta-analysis explored the association between childhood cognitive ability and risk of depression in adulthood. METHODS: We searched five databases to January 2024. We included studies that assessed cognitive ability in childhood (<18 years) and depression in adulthood. We excluded studies with very specific populations. We pooled each study's most-adjusted correlation coefficient in a random-effects meta-analysis. When studies reported a dichotomous outcome (depression/no depression), we converted the effect size to a correlation coefficient. Subgroup analyses were performed to explore sources of heterogeneity. RESULTS: 18 articles (19 cohorts) were included. There was no association between childhood cognitive ability and depression in adulthood (20 sample populations, N = 45,786, r = -0.04, 95 % CI = -0.09 to 0.01, p = 0.09). Neither age at cognitive assessment, length of follow-up, using a continuous/categorical measure of depression, or sex, significantly influenced the association. We rated most studies as having moderate risk of bias. LIMITATIONS: We limited the literature search to studies written in English. Existing studies were also heterogeneous, often adjusting for a variety of covariates. CONCLUSIONS: Our meta-analysis found no association between childhood cognitive ability and depression in adulthood. Future, longitudinal population-level studies should endeavour to control for potential mediators across the life-course (e.g., demographic and environmental factors).

Childhood intelligence and risk of depression in later-life: A longitudinal data-linkage study.

Background: Lower childhood intelligence test scores are reported in some studies to be associated with higher risk of depression in adulthood. The reasons for the association are unclear. This longitudinal data-linkage study explored the relationship between childhood intelligence (at age ∼11) and risk of depression in later-life (up to age ∼85), and whether childhood family structure and adulthood socio-economic and geographical factors accounted for some of this association. Methods: Intelligence test scores collected in the Scottish Mental Survey 1947 were linked to electronic health records (hospital admissions and prescribing data) between 1980 and 2020 (n = 53,037), to identify diagnoses of depression. Mixed-effect Cox regression models were used to explore the relationship between childhood intelligence test scores and risk of depression in later-life. Analyses were also adjusted for childhood family structure (size of family) and adulthood socio-economic and geographical factors (Carstairs index, urban/rural). Results: Twenty-seven percent of participants were diagnosed with depression during follow-up (n = 14,063/53,037). Greater childhood intelligence test scores were associated with a reduced risk of depression in an unadjusted analysis (HR = 0.95, 95% CI = 0.93 to 0.97, P < 0.001), and after adjustment for factors experienced in childhood and adulthood (HR = 0.95, 95% CI = 0.91 to 1.00, P = 0.032). When identifying depression using only hospital admissions data, greater childhood intelligence test scores were associated with a reduced risk of depression following unadjusted analysis (HR = 0.86, 95% CI = 0.82 to 0.90, P < 0.001), and after adjusting for risk factors in childhood and adulthood (HR = 0.94, 95% CI = 0.89 to 0.99, P = 0.026). There was no association between childhood cognitive test scores and depression when identifying cases of depression using only prescribed drugs data. Conclusions: This study provides additional evidence suggesting that higher childhood intelligence predicts reduced risk of later-life depression only when depression is assessed based on hospital admission records. Childhood family structure and adulthood socio-economic and geographical factors did not seem to be substantial confounders.

Childhood cognitive ability and self-harm and suicide in later life.

Background: Self-harm and suicide remain prevalent in later life. For younger adults, higher early-life cognitive ability appears to predict lower self-harm and suicide risk. Comparatively little is known about these associations among middle-aged and older adults. Methods: This study examined the association between childhood (age 11) cognitive ability and self-harm and suicide risk among a Scotland-wide cohort (N = 53037), using hospital admission and mortality records to follow individuals from age 34 to 85. Multistate models examined the association between childhood cognitive ability and transitions between unaffected, self-harm, and then suicide or non-suicide death. Results: After adjusting for childhood and adulthood socioeconomic conditions, higher childhood cognitive ability was significantly associated with reduced risk of self-harm among both males (451 events; HR = 0.90, 95% CI [0.82, 0.99]) and females (516 events; HR = 0.89, 95% CI [0.81, 0.98]). Childhood cognitive ability was not significantly associated with suicide risk among those with (Male: 16 events, HR = 1.05, 95% CI [0.61, 1.80]; Female: 13 events, HR = 1.08, 95% CI [0.55, 2.15]) or without self-harm events (Male: 118 events, HR = 1.17, 95% CI [0.84, 1.63]; Female: 31 events, HR = 1.30, 95% CI [0.70, 2.41]). Limitations: The study only includes self-harm events that result in a hospital admission and does not account for self-harm prior to follow-up. Conclusions: This extends work on cognitive ability and mental health, demonstrating that these associations can span the life course and into middle and older age.

Cohort profile: The Scottish SHARE Mental Health (SHARE-MH) cohort - linkable survey, genetic and routinely collected data for mental health research.

PURPOSE: The SHARE Mental Health (SHARE-MH) cohort was established to address the paucity of clinical and genetic data available for mental health research. The cohort brings together detailed mental health questionnaire responses, routinely collected electronic health data and genetic data to provide researchers with an unprecedented linkable dataset. This combination of data sources allows researchers to track mental health longitudinally, across multiple settings. It will be of interest to researchers investigating the genetic and environmental determinants of mental health, the experiences of those interacting with healthcare services, and the overlap between self-reported and clinically derived mental health outcomes. PARTICIPANTS: The cohort consists of individuals sampled from the Scottish Health Research Register (SHARE). To register for SHARE, individuals had to be over the age of 16 years and living in Scotland. Cohort participants were recruited by email and invited to take part in an online mental health survey. When signing up for SHARE, participants also provided written consent to the use of their electronic health records and genetic data-derived from spare blood samples-for research purposes. FINDINGS TO DATE: From 5 February 2021 to 27 November 2021, 9829 individuals completed a survey of various mental health topics, capturing information on symptoms, diagnoses, impact and treatment. Survey responses have been made linkable to electronic health records and genetic data using a single patient identifier. Linked data have been used to describe the cohort in terms of their demographics, self-reported mental health, inpatient and outpatient hospitalisations and dispensed prescriptions. FUTURE PLANS: The cohort will be improved through linkage to a broader variety of routinely collected data and to increasing amounts of genetic data obtained through blood sample diversion. We see the SHARE-MH cohort being used to drive forward novel areas of mental health research and to contribute to global efforts in psychiatric genetics.