Harmonization of self-reported and performance-based measures of vision using inverse probability weighting: an example using vision and depression in NHATS, CLSA, and LASI.

Visual impairment is a potential risk factor for depression and other outcomes in older adults. In population-based studies, vision can be measured using self-report or performance-based visual acuity, but epidemiologic associations often depend on which measure is used.In this Research Practice article, we illustrate the use of propensity scores to harmonize analyses of self-reported and performance-based vision in older adults. Using 2021 data from the National Health and Aging Trends Study (NHATS; n = 2447), we measured associations between self-reported visual difficulty, distance visual impairment (logMAR >0.3), and depression. To harmonize self-reported and performance-based measures of vision, we modeled distance visual impairment as a function of self-reported vision and covariates and calculated exposure misclassification overlap weights. External validation was conducted using the Canadian Longitudinal Study on Aging (CLSA) and the Longitudinal Aging Study in India (LASI).Self-reported visual difficulty was associated with depression in NHATS (adjusted OR 2.32, 95% CI: 1.46-3.69), but distance visual impairment was not (OR 1.41, 95% CI: 0.99-2.01). After exposure misclassification overlap weighting, self-reported vision was no longer associated with depression, and results mirrored the association between distance visual impairment and depression (OR 1.49, 95% CI: 0.93-2.36). Similar findings were observed in CLSA and LASI.Associations between vision and depression in older adults differ according to how vision is measured. In studies that measure self-reported vision but not visual acuity, propensity score methods that leverage known relationships between the two can be used to approximate associations between reduced visual acuity and health outcomes.

Duke Scholars

Author Dylan Thibault