Childhood adversity and the link between social inequality and early mortality
Notice bibliographique
Résumé
Exposure to childhood adversity is a global public health concern.1Gilbert R Widom CS Browne K Fergusson D Webb E Janson S Burden and consequences of child maltreatment in high-income countries.Lancet. 2009; 373: 68-81Summary Full Text Full Text PDF PubMed Scopus (2204) Google Scholar Meta-analyses have shown that exposure to adverse childhood experiences are directly2Hughes K Bellis MA Hardcastle KA et al.The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis.Lancet Public Health. 2017; 2: e356-66Summary Full Text Full Text PDF PubMed Scopus (1218) Google Scholar and intergenerationally3Cooke JE Racine N Pador P Madigan S Maternal adverse childhood experiences and child behavior problems: a systematic review.Pediatrics. 2021; 148e2020044131Crossref PubMed Scopus (1) Google Scholar associated with poor mental and physical health outcomes and result in considerable economic costs to society.4Hughes K Ford K Bellis MA Glendinning F Harrison E Passmore J Health and financial costs of adverse childhood experiences in 28 European countries: a systematic review and meta-analysis.Lancet Public Health. 2021; 6: e848-57Summary Full Text Full Text PDF PubMed Scopus (5) Google Scholar However, the potential role of adverse childhood exposures in associations between social inequalities and poor long-term health outcomes is largely uncharted.5Berthelot N Lemieux R Maziade M Shortfall of intervention research over correlational research in childhood maltreatment: an impasse to be overcome.JAMA Pediatr. 2019; 173: 1009-1010Crossref PubMed Scopus (14) Google Scholar In The Lancet Public Health, Leonie K Elsenburg and colleagues6Elsenburg LK Rieckmann A Nguyen T-L et al.Mediation of the parental education gradient in early adult mortality by childhood adversity: a population-based cohort study of more than 1 million children.Lancet Public Health. 2022; 7: e146-55Scopus (1) Google Scholar examined the extent to which childhood adversity (at age 0–16 years) explains the association between parental education levels and a child's mortality in later life (at age 16–39 years). They categorised parental education level according to years in education, as low (≤9 years), medium (10–12 years), and high (>12 years). Compared with children in the high parental education group, they found that exposure to childhood adversities mediated 41·5% (95% CI 8·0–67·5) of additional deaths among children in the medium parental education group, and 46·4% (32·9–58·8) among children in the low parental education group. Importantly, using a counterfactual framework, they found that this mediating effect was driven by differential exposure to childhood adversity. This finding contrasts the prevailing notion that children of parents with low education are more susceptible to childhood adversity (ie, parent education and exposure to childhood adversity do not interact to predict early mortality). The findings from this study provide a clear call for governments and policymakers to prevent exposure to, and mitigate poor outcomes associated with, childhood adversity. Elsenburg and colleagues6Elsenburg LK Rieckmann A Nguyen T-L et al.Mediation of the parental education gradient in early adult mortality by childhood adversity: a population-based cohort study of more than 1 million children.Lancet Public Health. 2022; 7: e146-55Scopus (1) Google Scholar make several novel methodological and empirical contributions to the literature. First, their study tests its hypotheses with use of objective, longitudinal, intergenerational, register-based data for a population of more than 1 million children in the nationwide Danish Life Course (DANLIFE) cohort. Unlike survey data, which is often not representative of the population from which it was sampled and has high attrition rates, register data provides routinely collected information on individuals regardless of their socioeconomic conditions. The DANLIFE cohort serves as an excellent model for countries internationally that seek to invest in data collection and infrastructure that can produce robust, evidence-based policy recommendations. Second, using data from birth to 16 years, the authors developed five trajectories of child adversity exposure that were based on annual exposure to 12 different adversities across three dimensions, including material deprivation, loss or threat of loss in the family, and family dynamics. By using trajectories, the authors were able to encapsulate data about the type, number, and timing of adversity exposures, moving beyond a simple and limited count measure of adversity. However, future research that can disentangle the specific adversity exposures that might be driving mediation effects is needed. Finally, and perhaps most importantly, findings from their study suggest that the influence of parental education, particularly low parental education, on mortality in offspring is partially explained by increased exposure to adversity in childhood, including poverty, parental loss, mental illness, or parent substance use difficulties. This finding identifies targets for governments seeking to improve mortality outcomes; specifically, targets that support family finances and mental health and reduce social disparities. Although the study by Elsenburg and colleagues has several strengths, child maltreatment (ie, physical, sexual, emotional abuse, and neglect) was not among the types of childhood adversity included as this information was not collected via register. Child maltreatment is foundational to most measures of childhood adversity7Afifi T Considerations for expanding the definition of ACEs.in: Asmundson GJG Afifi T Adverse childhood experiences: using evidence to advance research, practice, policy, and prevention. Academic Press, London2020: 35-44Crossref Scopus (4) Google Scholar and is one of the most robust predictors of poor health, poor mental health, and early mortality.1Gilbert R Widom CS Browne K Fergusson D Webb E Janson S Burden and consequences of child maltreatment in high-income countries.Lancet. 2009; 373: 68-81Summary Full Text Full Text PDF PubMed Scopus (2204) Google Scholar, 8Segal L Armfield JM Gnanamanickam ES et al.Child maltreatment and mortality in young adults.Pediatrics. 2021; 147e2020023416Crossref PubMed Google Scholar Although adversities included in the study (eg, foster care placement, material deprivation, and household dysfunction) do tend to co-occur with maltreatment, we anticipate that the inclusion of child maltreatment in the adversity trajectories would have further strengthened the findings and public health implications of the current study. Thus, future work seeking to build on the findings by Elsenburg and colleagues should include measures or metrics of child maltreatment in registry data. In addition, Elsenburg and colleagues focused primarily on proximal mechanisms within the family system, but research has shown that transmission of adversity from one generation to the next is multidetermined and includes biological factors (ie, health difficulties), community factors (eg, social supports, community violence), and broader systemic factors (ie, health-care access, discrimination, neighbourhood characteristics).9Racine N Hentges R McArthur B Madigan S The intergenerational transmission of risk and psychopathology.in: Elsevier Elsevier reference collection in neuroscience and biobehavioral psychology. Elsevier, Amsterdam2021: 1-15Crossref Google Scholar As such, future research would be of benefit by also considering biological, community, and system-level factors that might account for the association between low parental education and their offspring's potential for early adult mortality. In addition, further investigation is needed to identify how increased exposure to childhood adversity might be a key mechanism by which social inequality is transmitted across generations. Adversity in childhood can be prevented by going upstream and creating social policies that support optimal familial environments in early childhood. Such policies could focus on parenting, parent mental health and substance use, and poverty reduction, among other targets. The study of Elsenburg and colleagues should be used to prompt government and policy makers to address social inequalities and prevent exposure to adversity in early childhood, to optimise the health and wellbeing of individuals and families across generations. We declare no competing interests. Mediation of the parental education gradient in early adult mortality by childhood adversity: a population-based cohort study of more than 1 million childrenThe experience of childhood adversity seems to be an important mediator of the association between parental education and mortality in early adulthood. Interventions reducing the exposure to childhood adversity might thus reduce the parental education gradient in early adult mortality. Full-Text PDF Open Access
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».