The Prevalence of Cognitive Impairment Is Not Increasing in the United States: A Critique of Hale et al. (2020)

Abstract

Previous research based on the longitudinal Health and Retirement Study (HRS) has argued that the prevalence of cognitive impairment has declined in recent years in the United States. A recent article published in Epidemiology by Hale et al., however, suggests this finding is biased by unmeasured panel conditioning (improvement in cognitive scores resulting from repeat assessment). After adjusting for test number, Hale and colleagues found that the prevalence of cognitive impairment had actually increased between 1996 and 2014. In this commentary, we argue that simply adjusting for test number is not an appropriate way to handle panel conditioning in this instance because it fails to account for selective attrition (the tendency for cognitively high-functioning respondents to remain in the sample for a longer time). We reanalyze HRS data using models that simultaneously adjust for panel conditioning and selective attrition. Contrary to Hale et al., we find that the prevalence of cognitive impairment has indeed declined in the United States in recent decades.

Figure 1.

Causal diagrams depicting the relationship between survey year, T, survey experience, E, measured cognitive health, Y*, and actual cognitive health, Y. In the graph on the left, cognitive health and experience are a function of year (T→Y and T→E), actual cognitive health predicts measured health scores (Y→Y*), and prior experience predicts health scores (E→Y*) but not actual cognitive health, as would be the case if there is panel conditioning. In the graph on the right, cognitive health predicts survey experience (E←Y*←Y), as would be the case if healthier individuals remain in the panel longer (because they have fewer comorbidities and/or find the survey taking experience less demanding). In the second scenario, experience is a collider (T→E←Y*←Y), because it is a common effect of year and cognitive health. Conditioning on a collider (as indicated by the box around E) induces a non-causal relationship between the variables that predict it. We illustrate this relationship with a bi-directional dashed line. See the text for more details.

Figure 2.

Revised causal diagram depicting the relationship between survey year, T, survey experience, E, measured cognitive health, Y*, actual cognitive health, Y, and a respondent’s propensity to remain in the panel, P. Our concern is that healthier respondents accumulate more survey experience because they tend to stay in the sample longer than respondents with poorer cognitive functioning. We can close this path (through P) by entering a control for total survey experience, where total experience is defined as the number of surveys a respondent completes across all waves in which they appear in the sample (including future waves). This returns us to a situation where we can estimate the time trend in dementia prevalence that is free of collider bias. See the text for more details.