An Alternative Mathematical Modeling Approach to Estimating a Reference Life Expectancy

Misalignment of Reward Response With Healthful Behavior: An Underappreciated Driver of Population Health Deficits and Health Disparities?

Socioeconomic status-related (SES-related) health disparities are worsening across resource-rich environments, despite increased knowledge about health determinants and inducements for healthful behavior change. We ask whether insights from addiction science and evolutionary biology may assist understanding and counteracting SES-related health disparities. It is known that a mismatch between evolved traits and behaviors that conserve energy drives many health deficits. We posit that this energy mismatch is one manifestation of a more expansive mismatch in levels of reward activation, between environments more versus less manipulated by human activity. This larger mismatch explains why SES-related health disparities arise not only from overeating and excessive sedentism, but also from alcohol, nicotine, other substances, and mood disorders. Lower SES persons are more likely to have lower baseline reward activation, which leads to higher prioritization of reward elevating activities, and at the same time are less likely to act on knowledge about unhealthfulness of behaviors.

Measuring Population Health in a Large Integrated Health System to Guide Goal Setting and Resource Allocation: A Proof of Concept

In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.