In the Q&A portion of the webinar, an attendee asked the following question:

• "Ratios of probability tell one story, but underlying probabilities may tell another. For example, the report shows that 1.3% of those with 4 or more ACEs experience heart disease compared to only 0.9% of those with no ACEs. The bolded interpretation emphasizes that those with 4 or more ACEs are 1.5 times as likely to have heart disease despite the very low likelihood for all BRFSS respondents. Predicting an individual adult would have heart disease by their high ACE score would be an error almost 99% of the time. How should one manage this disparity in interpretation?"

Partners from the University of California, Davis Violence Prevention Research Program (VPRP) and the University of California Firearm Violence Research Center (UCFC), who completed the analysis for this report, shared the following response to this question:

• BRFSS is a population-based surveillance system for tracking public health issues at the population level. The data are prepared to provide state representative estimates for the California adult population. It is not appropriate to apply these population level contrasts to clinical efforts to “predict an individual adult’s” outcome. Public health surveillance data generally are useful to identify and track systemic and population level problems. These data can generate hypotheses for further exploration on the underlying mechanisms and systemic forces at play, as well as insights for clinical prevention and intervention approaches, not for individual patient predictions.
• Given that ACEs are common (two-thirds of CA adults experienced at least one ACE, and one in eight had experienced four or more) but modifiable, even associations with health conditions that are of relatively low population prevalence have the potential to greatly impact the personal and societal burdens of these conditions. The cost of addressing the personal and collateral costs of heart disease, for example, are substantial. One compelling question then becomes a “cost-benefit” calculation – what is the cost of reducing ACEs versus the benefit of reducing the number of heart disease patients needing treatment (see e.g., T. Miller et al, Adult Health Burden article).

Miller, T.R., Waehrer, G.M., Oh, D.L., Boparai, S.P., Walker, S.O., Marques, S.S., & Harris, N.B. (2020). Adult health burden and costs in California during 2013 associated with prior adverse childhood experiences. PLOS One. doi: https://doi.org/10.1371/journal.pone.0228019

Waehrer, G.M., Miller, T.R., Silverio Marques, S.C., Oh, D.L., Harris, N.B. (2020). Disease Burden of Adverse Childhood Experiences Across 14 States. PLOS One. doi: https://doi.org/10.1371/journal.pone.0226134