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Caspi A, Houts RM, Belsky DW, et al. Childhood forecasting of a small segment of the population with large economic burden. Nat Hum Behav. 2016;1doi: 10.1038/s41562-016-0005.
Caspi, A., Houts, R. M., Belsky, D. W., Harrington, H., Hogan, S., Ramrakha, S., Poulton, R., & Moffitt, T. E. (2016). Childhood forecasting of a small segment of the population with large economic burden. Nature human behaviour, 1. https://doi.org/10.1038/s41562-016-0005
Caspi, Avshalom, et al. "Childhood forecasting of a small segment of the population with large economic burden." Nature human behaviour vol. 1 (2016). doi: https://doi.org/10.1038/s41562-016-0005
Caspi A, Houts RM, Belsky DW, Harrington H, Hogan S, Ramrakha S, Poulton R, Moffitt TE. Childhood forecasting of a small segment of the population with large economic burden. Nat Hum Behav. 2016;1. doi: 10.1038/s41562-016-0005. Epub 2016 Dec 12. PMID: 28706997; PMCID: PMC5505663.
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Nat Hum Behav. 2016;1. doi: 10.1038/s41562-016-0005. Epub 2016 Dec 12.

Childhood forecasting of a small segment of the population with large economic burden.

Nature human behaviour

Avshalom Caspi, Renate M Houts, Daniel W Belsky, Honalee Harrington, Sean Hogan, Sandhya Ramrakha, Richie Poulton, Terrie E Moffitt

Affiliations

  1. Department of Psychology & Neuroscience, Duke University, Durham, NC, USA.
  2. Department of Psychiatry & Behavioural Sciences, Duke University School of Medicine, Durham, NC, USA.
  3. Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
  4. Social, Genetic, & Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, England.
  5. Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
  6. Social Science Research Institute, Duke University, Durham, NC, USA.
  7. Department of Psychology, University of Otago, Dunedin, New Zealand.

PMID: 28706997 PMCID: PMC5505663 DOI: 10.1038/s41562-016-0005

Abstract

Policy-makers are interested in early-years interventions to ameliorate childhood risks. They hope for improved adult outcomes in the long run, bringing return on investment. How much return can be expected depends, partly, on how strongly childhood risks forecast adult outcomes. But there is disagreement about whether childhood determines adulthood. We integrated multiple nationwide administrative databases and electronic medical records with the four-decade Dunedin birth-cohort study to test child-to-adult prediction in a different way, by using a population-segmentation approach. A segment comprising one-fifth of the cohort accounted for 36% of the cohort's injury insurance-claims; 40% of excess obese-kilograms; 54% of cigarettes smoked; 57% of hospital nights; 66% of welfare benefits; 77% of fatherless childrearing; 78% of prescription fills; and 81% of criminal convictions. Childhood risks, including poor age-three brain health, predicted this segment with large effect sizes. Early-years interventions effective with this population segment could yield very large returns on investment.

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