Year: 2025
Type: article
Abstract: PURPOSE OF REVIEW: Prevention research has largely concentrated on mid- and late-life modifiable risk factors, whereas early-life adversities have received less attention. Growing evidence shows that early adversities can influence brain health across biological systems and social environments, yet findings are fragmented and rarely address broader structural conditions. This review synthesizes recent evidence and introduces an exposome-informed conceptual model to guide future research and prevention. RECENT FINDINGS: Childhood adversities are linked to faster aging-related changes, including biological alterations, poorer cognition, subjective decline, functional impairment, and neuropsychiatric and mental health symptoms, as well as increased risk of mild cognitive impairment and dementia. Abuse, neglect, and socioeconomic deprivation show the most consistent associations. However, variation in how adversities are measured and the underrepresentation of global settings limit comparability. Few studies examine combined social and physical exposures, incorporate structural determinants such as segregation or conflict, or assess protective factors. SUMMARY: Findings highlight the need to move beyond single exposures, address structural and environmental influences, and broaden diversity in research populations. Identifying individuals exposed to early adversities may help tailor prevention efforts. An exposome-informed conceptual model links social and physical exposures with both vulnerability and resilience and can inform precision-prevention strategies to promote equitable brain health.
Source: Current Opinion in Psychiatry
Authors: Sandra Baez, Yehia Nabil, Agustin Ibanez
Language: English
Topic: Child Abuse and Trauma
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: National Institutes of Health
Awards: US-South American Initiative for Genetic-Neural-Behavioral Interactions in Human Neurodegenerative Research, An automated machine learning approach to language changes in Alzheimer’s disease and frontotemporal dementia across Latino and English-speaking populations, Circadian Disturbance and Dementia in Latin America
OpenAlex ID: W7124489302