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The multiple LAYERS of childhood adversity

Project description

Understanding childhood adversity and health inequality

Childhood adversity is a significant cause of health inequality. Disadvantaged children are exposed to multiple forms of adversity, but most research has only focused on social adversity, limiting our understanding. We need empirical data that follows individuals across various layers of adversity, from biology to environment. With this in mind, the ERC-funded LAYERS project will analyse life course data of 2 million people over three generations to address the impact of multiple types of childhood adversity. The project will build a large-scale unified data infrastructure and combine various methods, such as data science, epidemiology, econometrics and systems science. Building on insights on health inequality and childhood adversity, LAYERS will establish a real-world policy data lab that may help to identify children and families in need of targeted support.

Objective

Health inequality is a major societal challenge, and evidence suggests that health inequality is established in childhood and may even transcend generations. Childhood is a sensitive period with rapid growth and development, and adversity during this period may have long-lasting health effects. More importantly, multiple forms of adversity intersect with each other, and disadvantaged children are often exposed to adversity across multiple biological, health, social, neighbourhood and environmental layers, but the childhood adversity literature has almost exclusively focused on social adversity. This is a major gap in our understanding, and empirical data which transcends multitude layers of adversity and follows individuals over entire life courses or across generations is lacking.

With LAYERS, I am in a unique position to meet this challenge by creating a unified data infrastructure for life course analyses of multiple layers of childhood adversity in 2M people over three generations combined with an interdisciplinary fusion of methods from data science, epidemiology, econometrics, and systems science within a newly developed complex systems framework. This innovative combination of data and methods will allow for a systematic generation of knowledge on the patterns of health inequality that emerge in early life and transcend generations, the mechanisms which generate these patterns, and the dynamics that make them change over time. To translate these insights into actionable public health, LAYERS will establish a real-world policy data lab which integrates evidence from nationwide policies and simulations.

Combined, these interconnected elements will redirect the next frontier in health inequality research towards the multiple layers of adversity which generate inequality over the life course and across generations. Ultimately, this will help us break vicious circles of adversity by identifying children and families who would benefit from targeted support.

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Programme(s)

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Topic(s)

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-COG

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Host institution

KOBENHAVNS UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 000 000,00
Address
NORREGADE 10
1165 KOBENHAVN
Denmark

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Region
Danmark Hovedstaden Byen København
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 000 000,00

Beneficiaries (1)

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