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. 2020 Sep 1;61(11):42.
doi: 10.1167/iovs.61.11.42.

The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development

Daniel Ian Flitcroft  1   2 , Elise N Harb  3 , Christine Frances Wildsoet  3
Affiliations

The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development

Daniel Ian Flitcroft et al. Invest Ophthalmol Vis Sci. .

Abstract

Purpose: To examine the hypothesis that the spatial frequency spectra of urban and indoor environments differ from the natural environment in ways that may promote the development of myopia.

Methods: A total of 814 images were analyzed from three datasets; University of California Berkeley (UCB), University of Texas (UT), and Botswana (UPenn). Images were processed in Matlab (Mathworks Inc) to map the camera color characteristics to human cone sensitivities. From the photopic luminance images generated, two-dimensional spatial frequency (SF) spectra were calculated and converted to one-dimensional spectra by rotational averaging. The spatial filtering profile of a 0.4 Bangerter foil, which has been shown to induce myopia experimentally, was also determined.

Results: The SF slope for natural scenes followed the recognized 1/fα relationship with mean slopes of -1.08, -0.90, and -1.04 for the UCB, UT and UPenn image sets, respectively. Indoor scenes had a significantly steeper slope (-1.48, UCB; -1.52, UT; P < 0.0001). Urban environments showed an intermediate slope (-1.29, UCB; -1.22, UT) that was significantly different from the slopes derived from the natural scenes (P < 0.0001). The change in SF content between natural outdoor scenes and indoors was comparable to that induced by a 0.4 Bangerter foil, which reduced the SF slope of a natural scene from -0.88 to -1.47.

Conclusions: Compared to natural outdoor images, man-made outdoor and indoor environments have spatial frequency characteristics similar to those known to induce form-deprivation myopia in animal models. The spatial properties of the man-made environment may be one of the missing drivers of the human myopia epidemic.

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Conflict of interest statement

Disclosure: D.I. Flitcroft, None; E.N. Harb, None; C.F. Wildsoet, None

Figures

Figure 1.
Figure 1.
Spatial analysis of images showing the source image (left), the two-dimensional FFT (center), and the amplitude versus spatial frequency spectrum (right). For a natural scene image (a) the slope (α) of the log (amplitude) to log (spatial frequency) relationship is −0.98. For an indoor image (b) the slope of the log (amplitude) to log (spatial frequency) relationship is −1.42.
Figure 2.
Figure 2.
Violin plots of the calculated amplitude spectrum slopes (α) for the different types of images from the Berkeley image set. Significance markers (*) indicate comparison with the natural image set.
Figure 3.
Figure 3.
Violin plots of the calculated amplitude spectrum slopes (α) for the different types of images from the Botswana and Texas image sets. Significance markers (*) indicate comparison with the Texas natural image set.
Figure 4.
Figure 4.
Photos taken (a) with and (b) without a 0.4 Bangerter foil and derived amplitude versus spatial frequency spectra.
Figure 5.
Figure 5.
Comparison of amplitude vs. spatial frequency spectra corresponding to unfiltered image and image taken through a 0.4 Bangerter foil and the derived empirical MTF.
Figure 6.
Figure 6.
Estimated log Illuminance (lux) by category for the Berkeley image set. Significance markers (*) indicate comparison with the natural image set.
Figure 7.
Figure 7.
Estimated log Illuminance (lux) by category for the Botswana and Texas image sets. Significance markers (*) indicate comparison with the Texas natural image set.
See this image and copyright information in PMC

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