In a time of limited resources and growing needs, policy makers need to understand the causes of our deepest social issues and invest resources appropriately. Understanding the role of childhood trauma and the social costs that trauma creates in health care, drug and alcohol abuse, poverty, lost productivity, incarceration, and special education will drive informed social policy. Supporting programs that build resilience will reduce costs in treatment, education, criminal justice, and create a stronger society.
In the Adverse Childhood Experiences Study, the Kaiser-Permanente (KP) Health Maintenance Organization (HMO) and the US Centers for Disease Control and Prevention (CDCP) collaborated in surveying over 17,000 HMO members about their experience of a variety of adversities as 0-18 year olds and their subsequent health histories. They found a strong relationship between the number of ten categories of adversities experienced ((physical abuse, emotional abuse, sexual abuse, physical and emotional neglect and experience of parental domestic violence, substance abuse, incarceration, mental illness, and separation/ bereavement) and risk of a variety of negative behavior and health outcomes, including “the leading causes of morbidity, mortality and disability in the USA: cardiovascular disease, chronic lung disease, chronic liver disease, depression and other forms of mental illness, obesity, smoking and alcohol and drug abuse.”
Initially eight and then ten categories of adversity were included in the study because of their high prevalence in the KP weight reduction program: five directed toward children (physical abuse, emotional abuse, sexual abuse, and, later, physical neglect, emotional neglect) and five household issues (domestic violence to mother, separation, substance abuse, incarceration, significant psychiatric illness). Although other risk factors such as poverty, political and cultural trauma, etc. also affect illness and wellness, they were not analyzed in the ACE Study of KP members.The number of adversity categories experienced in childhood significantly predicted negative health and behavior outcomes, but it did not appear to matter much which categories were involved. The number of experiences within categories was not counted.
The Adverse Childhood Experiences (ACE) Study can brings cohesion and synergy to policy work with its findings that illustrate how the cumulative stress of ACEs can be a powerful determinate of the public’s health and a strongest common driver of mental, physical and behavioral health costs. Through the prevention and promotion of awareness of ACEs policy makers can help create informed policy that gets to the heart of the issues that create many health problems and in doing so be more effective with public dollars.
The following table introduces ways to answer these questions. This table is a starting point for further analyses, as it is based on a number of statistical assumptions (e.g. independence or confounding of risk factors), multiple inferences about population characteristics (generalizing from ACE Study to Maine), and a variety of outcome data sources—all of which could be more precise.
Within the table the Odds Ratio (OR) focuses on the individual and involves the increased statistical odds of a person with 4 or more ACEs having the outcome (it doesn’t predict that any specific individual will have the outcome). The Population Attributable Fraction (PAF) focuses on the group of people who experience the outcome and estimates the degree to which the outcome is attributable to having 4 or more ACEs.
According to the data above, Maine spends over 3.5 billion dollars a year on outcomes relevant to ACEs, not counting lost work productivity (absent, not fully productive, etc.). It is estimated that over $500 million in expenses is attributable to those having 4 or more ACEs and that if even ¼ of those experiencing the above outcomes could resolve their impairment (to ‘not bothered’), the state could save $124 million annually.
14 P=Prevalence in ACE Studies of 4 or more ACEs = 12.5 (overall, individual studies may differ insignificantly)
(For simplicity doesn’t include outcome attributable to 1-3 ACEs). http://www.cdc.gov/ace/prevalence.htm
15 RR=Relative Risk or Odds Ratio of someone with 4 or more ACEs having the outcome versus someone with no ACEs
(i.e. the baseline)having the outcome.
16 PAF%=The percentage of the population experiencing the outcome that can be attributed to having 4 or more ACEs
(i.e. there may be a variety of other factors that could also contribute to the outcome).