Could differential underreporting of loneliness between men and women bias the gender-specific association between loneliness duration and rate of memory decline? A probabilistic bias analysis of effect modification

Abstract

Gender is an observed effect modifier of the association between loneliness and memory aging. However, this effect modification may be a result of information bias due to differential loneliness underreporting by gender. We applied probabilistic bias analyses to examine whether effect modification of the loneliness-memory decline relationship by gender is retained under three simulation scenarios with various magnitudes of differential loneliness underreporting between men and women. Data were from biennial interviews with adults aged ≥ 50 years in the US Health and Retirement Study from 1996-2016 (5646 women and 3386 men). Loneliness status (yes vs no) was measured from 1996-2004 using the Center for Epidemiologic Studies Depression (CES-D) Scale loneliness item, and memory was measured from 2004-2016. Simulated sensitivity and specificity of the loneliness measure were informed by a validation study using the UCLA Loneliness Scale as a gold standard. The likelihood of observing effect modification by gender was higher than 90% in all simulations, although the likelihood reduced with an increasing difference in magnitude of the loneliness underreporting between men and women. The gender difference in loneliness underreporting did not meaningfully affect the observed effect modification by gender in our simulations. Our simulation approach may be promising to quantify potential information bias in effect modification analyses.

Keywords: effect modification; gender difference; loneliness exposure misclassification; memory aging; probabilistic bias analysis.

Figure 1

Gender-specific simulation estimates and 95% simulation intervals (SIs) for the interaction between loneliness exposure duration (continuous) and years of follow-up, the US Health and Retirement Study (n = 9032), 1996-2016. These estimates were from gender-stratified subgroup analyses: A) men; B) women. We conducted additional pooled analyses to derive gender-specific simulation estimates (Figure S2). Results were consistent with those shown in Figure 1.

Figure 2

Simulation estimates and 95% simulation intervals (SIs) for the 3-way interaction between loneliness exposure duration (continuous), years of follow-up, and gender in each of the three simulation scenarios, the US Health and Retirement Study (n = 9032), 1996-2016. A) First scenario; B) second scenario; C) third scenario. The % below the null represents the proportion of the simulation estimates below the null in the 10 000 replications for each situation.

Figure 3

Gender-specific simulation estimates for the interaction between loneliness exposure duration (categorical) and years of follow-up, the US Health and Retirement Study (n = 9032), 1996-2016. These estimates were from gender-stratified subgroup analyses: A) men; B) women. We conducted additional pooled analyses to derive gender-specific simulation estimates (Figure S3). Results were consistent with those shown in Figure 3.

Figure 4

Simulation estimates and 95% simulation intervals (SIs) for the 3-way interaction between loneliness exposure duration (categorical), years of follow-up (1, 2, and ≥ 3time points in the respective columns), and gender in each of the three simulation scenarios (first, second, and third scenarios in the respective rows), the US Health and Retirement Study, 1996-2016 (n = 9032). The % below the null represents the proportion of the simulation estimates below the null in the 10, 000 replications for each situation.