Optimizing the Potential Utility of Blue-Blocking Glasses for Sleep and Circadian Health

Abstract

Purpose: Wearable filters that reduce light in the short wavelength region of the visible spectrum, or "blue-blocking glasses," are increasingly available and offer an individualized, low-cost tool for enhancing sleep and circadian health. However, their effectiveness depends on filtering properties, application, timing, and implementation. If these factors are disregarded, blue-blocking glasses may be ineffective or lead to counterproductive outcomes.

Methods: We introduce a new metric, melanopic daylight filtering density (mDFD), to quantify a filter's capacity to decrease melanopic input, providing an alternative to ad-hoc measures. We applied mDFD to 26 commercially available glasses, estimating their potential to reduce circadian and related physiological effects of light across common applications in the context of consensus-based metrics and recommendations. We also reviewed intervention studies that used blue-blocking glasses.

Results: Products varied considerably in mDFD, with only those rated at mDFD ≥1 providing sufficient reductions in melanopic input to justify the "blue-blocking" label and associated claims. At least one relevant sleep or circadian-related outcome improved with blue-blocking interventions in the studies reviewed. In addition to filtering strength, appropriate timing and usage are critical to effectiveness.

Conclusions: The efficacy of blue-blocking glasses depends on both spectral filtering and proper usage. The mDFD metric offers a consistent, evidence-based approach for evaluating, selecting, and designing products that reduce photic input for non-visual physiological effects of light.

Translational relevance: Standardized characterization of blue-blocking glasses using mDFD facilitates reliable product comparisons, evidence-based selection, and rational design of lenses that are optimized for circadian health across a range of applications.

Figure 1.

Illustration of the effects of filter coatings with differing mDFD values. Shaded regions show the shift in melanopic EDI at the corneal plane under a lighting environment with an unfiltered melanopic EDI of 125 lux, superimposed on the consensus dose response curve for non-visual responses from Brown et al. 2022.

Figure 2.

Spectral power distributions for various light sources to which people are commonly exposed. Residential applications include (A) incandescent, (B) iPhone X screen, and (C) a desktop computer monitor. Commercial examples include (D) 5000 K light emitting diode and (E) fluorescent (F11) light sources. Finally, our natural light scenario is (F) outdoor light on a foggy morning in Los Angeles.

Figure 3.

The mDFD provides a reliable basis to judge the relevant benefits of blue-blocking filters across common use cases. (A) Relationship between mDFD and actual melanopic filtering density for a range of 26 filters across six scenes representing common indoor and outdoor use cases (relationship for each scene analyzed by Spearman correlation). (B) Relationship between mDFD and predicted non-visual response for the filters and common lighting conditions in A, as determined from corneal melanopic EDI after filtering and the consensus irradiance response function from Brown et al.

Figure 4.

Decision tree for use of blue-blocking glasses. Assuming you want to wear blue-blocking glasses for some reason (blue box), black diamonds include relevant questions that must be considered. Depending on the answer to those questions, results include times to not wear blue-blocking glasses (red circles); when to exercise caution (yellow circles); and how to best move forward with using them (green circles)

Figure 5.

Implementation data from three different shift worker intervention studies using blue-blocking glasses (N = 59), including (A) perceptions of the ease of use of the blue-blocking glasses and (B) the perceived likelihood of future use after the study.^,