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.It is not surprising to see the Pareto hypothesis validated. It is a common phenomenon. But it is absolutely worthwhile empirically confirming what might otherwise be simply assumed.
Throughout the cohort’s childhood, during the first decade of life, we measured risk factors that are thought to augur poor adult outcomes: growing up in a socioeconomically deprived family, exposure to maltreatment, low IQ and poor self-control. We report these four risk factors here because they are proven predictors of adult health and social outcomes and are high-priority targets in many early-years intervention programmes. A strength of this analysis is that all childhood risk predictors were measured prospectively, unbiased by participants’ knowledge of their adult outcomes.
Adult outcomes were concentrated as anticipated from the Pareto principle (that is, the 80–20 rule). Cumulative distribution functions showed that in each of the eight social and health sectors where we collected data, 20% of the individuals consistently accounted for a disproportionate share (close to 80%) of the outcome (Fig. 1). These distributions led us to operationally define a high-cost group in each sector as the 20% of the cohort members who accounted for a disproportionate share in that sector.
We observed that members of the high-cost group in every sector could be differentiated from their peers by the same four childhood disadvantages: they tended to have grown up in more socioeconomically deprived environments; to have experienced child maltreatment; to have scored poorly on childhood IQ tests; and to have exhibited low childhood self-control (Table 1). The predictions were fairly uniform across each of the eight different social and health sectors with the exception of injury claims. In addition to being less concentrated within a high-cost group, injury claims were less strongly associated with childhood risk factors.
The scary thing, to me, is what do you do with this knowledge. While the research is couched in terms of positive social investment to avert future costs, that is not the only outcome possible.
The Liverpool Care Pathway for the Dying Patient was similarly introduced for humanitarian reasons. The fact that it was well intentioned did not stop it from becoming a mechanism to generate revenue and control costs by designating people as terminal and expediting their demise. In other words, the NHS was using LCP as a mechanistic data driven means of killing patients for the greater good of the budget.
We see similar dynamics in the Netherlands where a concern to make it easier for people in chronic and intense pain to take their own lives (assisted by doctors) has led to a regimen where many are concerned that it has become too easy for the state and hospitals to euthanize those who are inconvenient.
Looking at the New Zealand study and all the alarm bells go off. 20% of the population causes 80% of the state costs. These 20% are identified (with 80% accuracy by four attributes: low IQ, low self-control, being poor, and being abused.
Translate that into a diverse culture and you can immediately see the implications. What, beyond sheer humanity, stops a totalitarian state from using this knowledge, not to invest in people, but to contain future costs? Eugenics is a tool always ready to hand among socialists and progressives. The Kiwis have proven that you can, with some accuracy, identify who the future cost drivers are going to be. They have not proven that childhood interventions will actually yield the assumed benefits. One would wish that the claims of childhood investments yielding reduced costs in the future were true but the supporting research is hotly contested. What if there are no benefits to the investment? It doesn't bear thinking about.
And yet, think about it we must. John Ralston Saul's critique in Voltaire's Bastards is that we in the West have become too reliant and place too great a faith in simple reason to lead us to the right answers.
I am inclined to agree that we distort out thinking by an over-reliance on reason and logic. There has to be a role for intuition and for humanitarian guidance. Human life is not simply Scrooge's balance sheet of costs and benefits.
It is admirable of the New Zealand team to be so well intended and what they have produced (subject to independent validation) is likely useful knowledge. But it still makes me nervous. There are too many men of the system, rationalists in service of the aggregating state who never look at the humans and instead examine only the costs and the benefits.