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

Avshalom Caspi, Renate M. Houts, Daniel W. Belsky, Honalee Harrington, Sean Hogan, Sandhya Ramrakha, Richie Poulton and Terrie E. Moffitt
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Avshalom Caspi: Duke University
Renate M. Houts: Duke University
Daniel W. Belsky: Duke University School of Medicine
Honalee Harrington: Duke University
Sean Hogan: University of Otago
Sandhya Ramrakha: University of Otago
Richie Poulton: University of Otago
Terrie E. Moffitt: Duke University

Nature Human Behaviour, 2017, vol. 1, issue 1, 1-10

Abstract: Abstract Policymakers are interested in early-years interventions to ameliorate childhood risks. They hope for improved adult outcomes in the long run that bring a return on investment. The size of the return that can be expected partly depends 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-long Dunedin birth cohort study to test child-to-adult prediction in a different way, using a population-segmentation approach. A segment comprising 22% 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 child-rearing; 78% of prescription fills; and 81% of criminal convictions. Childhood risks, including poor brain health at three years of age, predicted this segment with large effect sizes. Early-years interventions that are effective for this population segment could yield very large returns on investment.

Date: 2017
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DOI: 10.1038/s41562-016-0005

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