“Anti-social” individuals can be identified at age 3

A new paper in Nature: Human Behaviour.

A. Caspi et al, Childhood forecasting of a small segment of the population with large economic burdenNature Human Behaviour 1, Article number: 0005 (2016), doi:10.1038/s41562-016-0005

The study following 1000 children in New Zealand found that by age 38,

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.

But, the study goes on, the high social cost segment could be identified by age 3:

Moreover, variation in cohort members’ brain health at three years of age predicted with considerable accuracy which individuals would be members of the multiple-high cost segment 35 years later.

They define “brain health”:

At 3 years of age, each child in the cohort participated in a 45 minute examination that included assessments of neurological soft signs, intelligence, receptive language and motor skills. The examiners (having no previous knowledge of the child) then rated each child’s frustration tolerance, resistance, restlessness, impulsivity and lack of persistence in reaching goals. This examination yielded a summary index that we have termed brain health, a global index of the neurocognitive status of three-year-old children. Variation in brain health at three years of age significantly predicted economically burdensome outcomes in each sector, except injury claims.

They conclude

This research yielded two results. First, the study uncovered a population segment that featured as high cost across multiple health and social sectors. ……… Second, by linking administrative data with individual-level longitudinal data, the study provides the strongest effect sizes yet, measuring the connection between an at-risk childhood and costly adult outcomes in the population.

Suppose this study does indeed apply to developed societies generally. The question then becomes what should be done if a predictive test at age 3 reveals those likely to pose a high societal burden. Ideally one should identify the genetics or the development (or lack of development) upto age 3 which gives rise to the result and attack those. An obvious problem arises if genetics – which cannot be remedied – has a large influence. Since even the non-genetic causes are mainly unknown, it then becomes a case of finding remedial methods that can be applied after age 3 to reduce the social burden they could potentially pose.

A fascinating study but it again poses the challenge we will increasingly face as we learn to predict the potential behaviour of humans at an early age. If a potential sociopath can clearly be identified at a very early age, what then becomes the strategy for management of risk? Lock him up before he kills someone? Send him to behaviour correctional institution based on a prediction? If there is a large genetic component do we ban the parents from having further offspring?


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.

Around the world, the population is ageing and total fertility rates are declining. As a result, nations increasingly view children and young people as valuable resources for the economic and social well-being of whole societies. This view is accompanied by public-policy interest in early interventions to help as many children as possible achieve their full potential. A key question concerns the potential size of the impact that might be brought about by interventions in the early years of children’s lives1,2 . Research teams that have followed up on small samples of children who were enrolled in intervention experiments carried out decades ago point to reductions in school leaving, unemployment, crime, obesity and even blood pressure3,4,5,6 . Some argue that today’s better-designed interventions might achieve greater reductions in adult problems than previous efforts7 (see also www.nuffieldfoundation.org, www.blueprintsprograms.com, http://ies.ed.gov/ncee/wwc and http://incredibleyears.com). Others assert that interventions for the youngest children will bring an even greater return on investment compared with interventions that begin when children are older8 . However, a skeptic could point out that return on investment for society will depend not only on an intervention’s capacity to ameliorate childhood risks, but also on how relevant those risks are for downstream adult functioning in the general population. Thus, to a large extent, the question of how much early-years intervention can lift health and social well-being and reduce costs depends on how strongly early-years risk factors are tied to adult outcomes in the population. Our own research and that of others suggests that while childhood risk factors do predict adult outcomes with statistical significance, the effect sizes are typically modest9,10,11 . The interpretation of these modest child-to-adult effect sizes is polarizing, and has sown confusion among scientists, policy makers and the public12,13,14 . On the one hand, claims are made that the ‘child is father of the man’, because continuity from childhood risks to adult outcomes is stronger than expected, given the long duration of follow-up. On the other hand, on the basis of the same data, warnings are issued about the myth of early-childhood determinism and about unwarranted overemphasis on childhood.

Here, we tackled the prediction question anew in the context of the Dunedin Longitudinal Study, a population-representative 1972–1973 birth cohort of 1,037 New Zealanders assessed at ages 3, 5, 7, 9, 11, 13, 15, 18, 21, 26, 32 and 38 years and followed from birth to midlife with 95% retention (Supplementary Information). We first integrated our longitudinal survey data and clinical data with multiple nationwide government administrative databases and electronic medical records. Then, using a novel segmentation approach, we tested the hypothesis that a small segment of the adult population accounts for a large cumulative economic burden and that this segment can be predicted with good accuracy from early childhood.


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