The multiple LAYERS of childhood adversity

Introduction

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.

Intersection of Adversities

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. However, the childhood adversity literature has almost exclusively focused on social adversity. This is a major gap in our understanding, and empirical data which transcends multiple layers of adversity and follows individuals over entire life courses or across generations is lacking.

The LAYERS Initiative

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 2 million people over three generations. This will be combined with an interdisciplinary fusion of methods from:

1. Data science
2. Epidemiology
3. Econometrics
4. Systems science

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.

Translating Insights into Action

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.

Conclusion

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.