changes on short-term and longer-t c i - qut · 2018. 1. 31. · sekar ulaganathan (mphil...
TRANSCRIPT
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THE INFLUENCE OF LIGHT EXPOSURE AND SEASONAL
CHANGES ON SHORT-TERM AND LONGER-TERM CHANGES IN
AXIAL LENGTH OF THE HUMAN EYE
Sekar Ulaganathan
(MPhil Optometry)
Submitted in fulfilment of the requirements for the award of the
degree of Doctor of Philosophy
Contact Lens and Visual Optics Laboratory
School of Optometry and Vision Science
Institute of Health and Biomedical Innovation
Queensland University of Technology
Brisbane, Australia
2018
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The influence of light exposure and seasons upon the axial length changes in humans iii
KEYWORDS
Eye
Axial length
Myopia
Diurnal variations
Light exposure
Outdoor activity
Environmental factors
Sampling
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The influence of light exposure and seasons upon the axial length changes in humans v
ABSTRACT
It is widely accepted that environmental factors play a significant role in regulating eye
growth and myopia development. There is also considerable evidence that ambient light
exposure is an important environmental risk factor associated with eye growth in
children, however, the underlying mechanism remains unclear. Furthermore, animal
studies have shown that diurnal variations in ocular components appear to be involved
in the mechanisms controlling eye growth. Animal studies also suggest that altering
light exposure disrupts normal diurnal variations and can lead to the development of
refractive errors. Despite this evidence, the exact role of light exposure and ocular
diurnal rhythms in the regulation of human eye growth, and the interaction between
these factors is not well understood. Myopia development and progression have been
widely documented in young adults and typically occurs due to axial elongation, but
there has been limited research examining the potential impact of ambient light
exposure upon eye growth and myopia development and progression in young adults.
Therefore, this research examined the habitual light exposure patterns in a population of
young adult emmetropes and progressing myopes using objective techniques, and
assessed the influence of light exposure upon daily axial length variations and
longitudinal axial eye growth in this population. The potential association between daily
axial length fluctuations and longer-term changes in axial length was also explored.
Since there is no consensus on the optimal sampling strategy required for capturing
personal objective light exposure measurements, in the first study, we systematically
examined the impact of different measurement durations and measurement frequencies
upon objective light exposure measures, in order to determine the optimal sampling
strategy to reliably capture habitual light exposure patterns of both children (Age: 11 to
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vi The influence of light exposure and seasons upon the axial length changes in humans
15 years) and young adults (Age: 18 to 30 years). Ambient light exposure data were
obtained using a wrist-worn light sensor (Actiwatch 2), which was configured to
measure instantaneous light levels every 30 seconds, 24 hours a day for a period of 14
consecutive days in children (n = 30) and young adults (n = 31). Daily time exposed to
bright outdoor (>1000 lux) light levels was derived from the raw 14 days of data with
30 second sampling, and was subsequently derived from data re-sampled from 12, 10, 8,
6, 4 and 2 randomly selected measurement days using 1, 2, 3, 4, 5 and 10 minute
sampling rates. Calculating daily outdoor light exposure time using a lower number of
days and coarser sampling frequencies did not significantly alter the mean time spent in
bright (outdoor) light. However, a significant increase in measurement variability
occurred for outdoor light exposure derived from less than 8 days and from 3 minutes or
coarser measurement frequencies in adults, and from less than 8 days and from 4
minutes or coarser frequencies in children. Our analyses also indicated that
measurement duration has a substantially greater impact upon light exposure measures
than sampling frequency. These findings suggest that a measurement duration of at least
one week and a measurement frequency of 2 minutes or finer is required to provide the
most reliable estimates of the habitual daily light exposure patterns of children and
young adults.
In the main study of this program of research, we conducted a prospective longitudinal
study of objective ambient light exposure measures along with ocular measures
assessing the daily, seasonal and annual variations occurring in axial length of young
adult emmetropes and progressing myopes. In this study, the objective light exposure
patterns in young adult emmetropes (n = 21) and progressing myopes (n = 22) were
assessed, in order to examine the association between light exposure and refractive
error. Measures of personal light exposure were acquired over winter and summer for
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The influence of light exposure and seasons upon the axial length changes in humans vii
each subject to explore the influence of seasons upon the association between refractive
error and personal light exposure. Ambient light measurements were captured every 30
seconds, 24 hours a day for 14 days in each season. For each participant, the mean daily
time exposed to bright (outdoor) light levels (>1000 lux) was derived from 14 days of
data. The mean daily bright light exposure was found to be higher in summer (58
minutes) compared to winter (36 minutes). Although light exposure averaged across
both seasons was not significantly different between emmetropes (49 minutes) and
progressing myopes (43 minutes), a significant interaction between seasons and
refractive group was observed. Emmetropes exhibited significantly greater daily bright
light exposure in summer (67 minutes) compared to winter (35 minutes), while
progressing myopes did not exhibit any seasonal light exposure variations (summer: 50
minutes and winter: 37 minutes). In summer, the daily outdoor light exposure was
significantly greater in emmetropes compared to progressing myopes. Therefore, this
study established that there are seasonal variations in daily time exposed to bright light
in young adults, and differences in these seasonal variations were found to be associated
with refractive error.
We also examined the longitudinal (annual) and seasonal changes occurring in axial
length and the influence of personal light exposure upon these longitudinal axial length
changes. Axial length measurements were obtained every six months over a 12-month
period using the Lenstar optical biometer. The 6-monthly measurements were scheduled
to coincide with the seasonal measures of ambient light exposure (i.e. in winter and
summer) in order to provide the first assessment of seasonal variations of axial length in
young adults. There was a significant change in axial length observed over time, with
significantly larger magnitude changes in axial length seen in progressing myopes
(0.066 mm/year) compared to emmetropes (0.008 mm/year). A significant interaction
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between the longitudinal changes in axial length and the daily time spent in bright light
was also observed, with greater daily bright (outdoor) light exposure being associated
with smaller magnitude changes in axial length over the 12-month study period. The
axial elongation was slower by 0.002 mm/year for every minute per day spent in bright
outdoor light intensities. There was also a significant effect of season upon the
longitudinal axial length changes. Emmetropes were found to have an increase in axial
length during winter (mean change of 0.015 mm) and a small magnitude reduction
during summer (-0.007 mm), whereas progressing myopes showed axial elongation
during both seasons (0.027 mm in winter and 0.041 mm in summer). A significant
inverse relationship between seasonal differences in axial length and time spent in
bright (outdoor) light was also observed. Therefore, this study provides the first
objective evidence of a role of ambient light exposure in the regulation of eye growth in
young adult subjects, and indicates that ambient light exposure also plays a role in
seasonal variations in eye growth.
To explore the mechanism underlying this association between light exposure and
longitudinal axial length changes, in this study, we also assessed the daily axial length
variations occurring in these young adult emmetropes and progressing myopes. We
further examined the association between ambient light exposure, daily axial length
variations and longitudinal axial length changes to explore the potential role of ambient
light exposure and daily axial length variations upon the longer-term axial length
changes. A series of axial length measurements were collected ~every 3 hours from 9
am to 9 pm (i.e. 5 measurement sessions per day) using the Lenstar optical biometer on
a weekday and a weekend in winter and then six months later on a weekday and a
weekend in summer. Significant diurnal variations in axial length were observed in both
refractive groups with the typical peak in axial length occurring at the second (12:09)
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measurement session and the trough in axial length occurring at the final (20:51)
measurement session of the day. There were no significant differences in the diurnal
axial length changes between weekdays and weekends or between winter and summer.
Significant differences in the diurnal variations of axial length were observed between
refractive groups, with the mean change in axial length between the second and the final
measurement of the day being significantly greater in progressing myopes (0.019 mm)
compared to emmetropes (0.009 mm). There was a significant inverse association
between the habitual daily time spent in bright light and the amplitude of daily axial
length variations, with more time exposed to bright light being associated with a smaller
amplitude of diurnal axial length change. Higher amplitudes of daily axial length
fluctuations were also associated with greater longitudinal axial length changes,
demonstrating a positive association between the amplitude of diurnal axial length
variations and longitudinal axial elongation. From this study, we have shown that
ambient light exposure is significantly associated with diurnal ocular variations and
there was evidence to suggest that these short-term diurnal variations may play a role in
longer-term eye growth in young adults.
Overall, this research provides the first objective evidence that there are seasonal
variations in objective ambient light exposure associated with refractive errors in young
adults. This study also provides evidence of an inverse relationship between light
exposure and longitudinal axial length changes, and between seasonal changes in axial
length and light exposure in young adults. A significant relationship between ambient
light exposure, daily axial length variations and longitudinal axial length changes was
also established for the first time in human eyes. These findings suggest that less time
spent in bright (outdoor) light is associated with greater daily axial length variations,
and these short-term ocular variations are in turn, associated with longer-term axial eye
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growth. This research provides new knowledge regarding environmental factors
involved in the regulation of eye growth of young adults, and suggests that, similar to
findings in children and animal models, greater daily light exposure is associated with
slower eye growth in young adults. Although additional research is required to
understand the mechanisms underlying the observed associations, these findings support
the potential for greater outdoor light exposure in young adults to protect against the
development and progression of myopia.
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TABLE OF CONTENTS
Keywords ................................................................................................................. iii
Abstract ..................................................................................................................... v
List of Figures ........................................................................................................ xvi
List of Tables ....................................................................................................... xxiv
List of Abbreviations ............................................................................................ xxvi
Statement of Original Authorship ....................................................................... xxviii
Acknowledgements ............................................................................................... xxx
Chapter 1: Literature review…………………………………………………………..1
1.1 Emmetropization and eye growth: ................................................................... 1
Control of eye growth by visual signals: .................................................. 1 1.1.1
Defocus induced by spectacle lenses: ....................................................... 2 1.1.2
Form-deprivation: .................................................................................... 3 1.1.3
Local control of eye growth: .................................................................... 4 1.1.4
Possible central nervous system involvement in the control of eye growth:1.1.5
………………………………………………………………………..…...5
Defocus induced axial length and choroidal thickness changes in humans:1.1.6
………………………………………………………………………….....6
1.2 Human myopia: .............................................................................................. 8
Epidemiology: ......................................................................................... 8 1.2.1
Aetiology of myopia: ............................................................................. 10 1.2.2
1.3 Light exposure and refractive development in animals: ................................. 28
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xii The influence of light exposure and seasons upon the axial length changes in humans
1.4 Diurnal ocular variations: .............................................................................. 30
Eye growth, refractive error and diurnal variations: ................................ 33 1.4.1
Light/dark cycle and refractive development in animals: ........................ 36 1.4.2
1.5 Rationale, aims and hypotheses: .................................................................... 40
Chapter 2: Measurement duration and frequency impact objective light exposure
measures………………………………………………………………………………..45
2.1 Introduction: ................................................................................................. 45
2.2 Methods: ....................................................................................................... 49
2.3 Data analysis:................................................................................................ 51
2.4 Results: ......................................................................................................... 55
Average hourly light exposure and daily time spent in bright (outdoor) 2.4.1
light in adults and children: .................................................................................. 55
The influence of measurement duration upon estimates of daily exposure 2.4.2
to bright (outdoor) light levels: ............................................................................. 56
The influence of sampling rate upon estimates of daily exposure to bright 2.4.3
(outdoor) light levels: ........................................................................................... 60
Interaction between different measurement durations and frequencies:... 62 2.4.4
2.5 Discussion: ................................................................................................... 64
Chapter 3: Seasonal personal ambient light exposure variations in young adult
emmetropes and progressing myopes……………………………………………….. ... 71
3.1 Introduction: ................................................................................................. 71
3.2 Methods: ....................................................................................................... 74
Study participants: ................................................................................. 74 3.2.1
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Light exposure measurements: ............................................................... 75 3.2.2
3.3 Data analysis:................................................................................................ 76
3.4 Results: ......................................................................................................... 79
Climate conditions: ................................................................................ 79 3.4.1
Objective light exposure measurements: ................................................ 82 3.4.2
3.5 Discussion: ................................................................................................... 94
Chapter 4: Light exposure and longitudinal axial length changes in young adults .. 101
4.1 Introduction: ............................................................................................... 101
4.2 Methods: ..................................................................................................... 104
4.3 Data analysis:.............................................................................................. 107
4.4 Results: ....................................................................................................... 109
Longitudinal changes in axial length: ................................................... 110 4.4.1
Light exposure and longitudinal changes in axial length:...................... 111 4.4.2
Seasonal variation in longitudinal axial length changes and light exposure:4.4.3
………………………………………………………………………….114
4.5 Discussion: ................................................................................................. 119
Chapter 5: The short-term daily variations in axial length of emmetropes and
progressing myopes: Associations with light exposure and longitudinal axial length
change………...……………………………………………………………………….129
5.1 Introduction: ............................................................................................... 129
5.2 Methods: ..................................................................................................... 132
Study participants: ............................................................................... 132 5.2.1
Daily ocular variation measurements: .................................................. 133 5.2.2
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xiv The influence of light exposure and seasons upon the axial length changes in humans
5.3 Data analysis:.............................................................................................. 136
5.4 Results: ....................................................................................................... 137
Within-session repeatability: ................................................................ 137 5.4.1
Daily variations in axial length: ........................................................... 138 5.4.2
Light exposure and daily variations in axial length: .............................. 142 5.4.3
Wake-up time, light exposure and daily axial length variations: ........... 145 5.4.4
Daily variations in axial length, light exposure and longitudinal axial 5.4.5
length changes: .................................................................................................. 147
5.5 Discussion: ................................................................................................. 150
Chapter 6: Conclusions.……………………………………………………………159
6.1 Summary and main findings: ...................................................................... 160
Impact of sampling on objective light exposure measurements: ........... 160 6.1.1
Seasonal light exposure variations: ...................................................... 162 6.1.2
Longitudinal changes in eye growth: .................................................... 165 6.1.3
Association between light exposure and eye growth: ............................ 165 6.1.4
Seasonal light exposure and eye growth variations: .............................. 166 6.1.5
Physical activity and eye growth: ......................................................... 168 6.1.6
Indoor activities and eye growth: ......................................................... 168 6.1.7
Daily axial length variations in emmetropes and progressing myopes: . 169 6.1.8
Light exposure and daily axial length variations: .................................. 171 6.1.9
Light exposure and daily axial length variations during weekdays and 6.1.10
weekends and different seasons:......................................................................... 172
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Sleep patterns and daily axial length variations: ................................... 173 6.1.11
Daily axial length variations and longitudinal eye growth: ................... 174 6.1.12
Light exposure, daily axial length variations and longitudinal eye growth 6.1.13
changes:….. ....................................................................................................... 175
6.2 Limitations and future research directions: .................................................. 179
Bibliography…………………………………………………………………………..184
Appendix……………………………………………………………………………...211
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xvi The influence of light exposure and seasons upon the axial length changes in humans
LIST OF FIGURES
Figure 1.1: Sine curve modelling of the mean changes in axial length (AL), choroidal
thickness (CT) and intraocular pressure (IOP). The mean change of each
parameter at each measurement time is shown. The diurnal variations of
axial length and choroidal thickness exhibit an antiphase relationship, and
the diurnal variation in axial length and intraocular pressure shows an in-
phase relationship (Chakraborty et al., 2011)........................................... 33
Figure 2.1: Example of the raw light exposure (yellow line) and physical activity data
(black bars) obtained from Actiwatch 2 from a representative subject for a
period of 24 hours. .................................................................................. 51
Figure 2.2: Mean hourly light exposure for children (blue line) and adults (red line)
averaged over 14 days (A). * indicates a significant difference (p
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adults (B) and children (D). The 95% limits of agreement (LOA) are plotted
for each cumulative day. The error bars indicate the exact 95% confidence
intervals of the LOA. * indicates significant increase in LOA from 12 days.
............................................................................................................... 59
Figure 2.4: (Left) Bland-Altman Graph: Daily time spent in bright light (>1000 lux)
difference between the 30 second sampling rate and other sampling rates
plotted against its average for each subject for adults (A) and children (C).
(Right) The mean difference (Mean Diff) in daily time spent in bright light
for each sampling rate from the 30 second sampling rate is plotted along the
x-axis for adults (B) and children (D). The 95% limits of agreement (LOA)
are plotted for each sampling rate. The error bars indicate the exact 95%
confidence intervals for the LOA. * indicates significant increase in LOA
from 1 minute sampling rate. .................................................................. 61
Figure 2.5: Average absolute difference in the daily time exposed to bright light (>1000
lux) levels for adults (A) and children (B) across different measurement
durations and sampling frequencies. The absolute difference from 14 days is
plotted for each of the measurement durations along the z-axis and sampling
frequencies along the x-axis. ................................................................... 63
Figure 3.1: Mean hourly light exposure in winter (green line) and summer (orange line)
averaged over 14 days for all subjects (A). Mean hourly light exposure
during weekdays (turquoise line) and weekends (black line) for all subjects
(B). Mean hourly light exposure during weekdays and weekends in winter
(C) and in summer (D) for all subjects. The vertical error bars denote the
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xviii The influence of light exposure and seasons upon the axial length changes in humans
standard error of the mean. * indicates a significant difference (p
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Figure 3.4: Relationship between day length and objectively measured mean daily time
spent in bright light (>1000 lux) (A) and mean daily (6 am – 6 pm) light
exposure (B) for emmetropes (blue circles) and progressing myopes (red
circles). Solid lines indicate best fit regression line for emmetropes (blue
line) and progressing myopes (red line). .................................................. 90
Figure 3.5: Average hourly physical activity in winter (solid black line) and summer
(dashed black line) averaged over 14 days for all subjects (A). Average
hourly physical activity in winter (solid blue line) and summer (dashed blue
line) for emmetropes (B). Average hourly physical activity in winter (solid
red line) and summer (dashed red line) for progressing myopes (C). Mean
hourly physical activity in emmetropes (blue line) and progressing myopes
(red line) during winter (D) and summer (E) seasons. The vertical error bars
denote the standard error of mean. The shaded zone in each plot represents
sundown and the vertical lines at the boundaries of the shaded zone indicate
the mean sun rise and sun set times for winter (green) and summer (orange).
............................................................................................................... 93
Figure 4.1: Schematic overview of the study procedures. Each subject had axial length
(AL) measured every 6 months over the one year study and wore an
Actiwatch 2 light sensor/actigraphy device for 14 days during winter and
summer. Examining the change in axial length between baseline and the
second visit provides an assessment of the axial progression in winter, and
between the second and third visit provides an assessment of the axial
progression in summer. ......................................................................... 105
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xx The influence of light exposure and seasons upon the axial length changes in humans
Figure 4.2: Mean change in axial length over the 12 months of the study for the
progressing myopes (red line), emmetropes (green line) and all subjects
(blue line). Vertical error bars indicate the standard error of the mean
change in axial length. Horizontal error bars indicate the standard error of
the study visit time. ............................................................................... 111
Figure 4.3: Relationship between 6-monthly change in axial length (winter - blue
circles and summer - red circles) and objectively measured mean daily time
exposed to light levels >1000 lux for all subjects. r values indicate the
correlation coefficient. Solid lines indicate the best fit regression line for
winter (blue line) and summer (red line). .............................................. 113
Figure 4.4: Mean seasonal changes in axial length of emmetropes and progressing
myopes in winter (red bar) and summer (blue bar) season (A). Objectively
measured mean daily time exposed to bright light (>1000 lux) intensities (B)
and mean daily (6 am to 6 pm) light exposure (C) of emmetropes and
progressing myopes in winter (red bar) and summer (blue bar) are also
illustrated. * indicates significant seasonal differences. ** indicates
significant difference between refractive groups. Vertical error bars indicate
the standard error of the mean. .............................................................. 117
Figure 4.5: Relationship between the seasonal differences in axial length change and
the seasonal differences in objectively measured daily time exposed to
bright light intensities (>1000 lux) (top), and seasonal axial length variation
and objectively measured daytime (6 am – 6 pm) light exposure (bottom). r
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values indicate the correlation after adjusting for baseline axial length. Solid
lines indicate the best fit regression line. ............................................... 118
Figure 5.1: Schematic overview of the study procedures. The mean ± standard
deviation timings for each of the daily variation measurement sessions on
different measurement days of the experiment are presented. Each subject
wore an Actiwatch 2 light sensor/actigraphy device for 14 days during
winter and summer and the daily ocular variations were measured on a
weekday and a weekend during the 14 days of Actiwatch wear. Ocular
biometrics were measured during each of the measurement sessions. AL –
Axial length. ......................................................................................... 134
Figure 5.2: The mean daily variations in axial length (9 am to 9 pm) during weekdays
(turquoise line) and weekends (black line) (averaged across the two seasons)
for all subjects (A), during winter (green line) and summer (orange line)
(averaged across weekdays and weekends for all subjects) (B) and in
emmetropes (blue line) and progressing myopes (red line) (averaged across
weekdays and weekends and summer and winter) (C). To highlight the daily
variations in axial length, all values are expressed as the difference from the
mean of all sessions each day (i.e. all values are normalised to the mean).
Vertical error bars represent the standard error of the mean. Horizontal error
bars indicate standard error in the mean measurement time at each session
(in minutes). * indicates significant difference in the change in axial length
between the refractive groups (p
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xxii The influence of light exposure and seasons upon the axial length changes in humans
Figure 5.3: Association between the amplitude of daily variations in axial length and
daily time exposed to light levels >1000 lux (averaged across all days and
seasons) for all subjects. r value indicates the correlation coefficient after
adjusting for baseline axial length. Solid line indicates the best fit regression
line. p value indicates significance value. .............................................. 142
Figure 5.4: Relationship between the amplitude of daily variations in axial length and
daily time exposed to light levels >1000 lux (averaged across all days and
seasons) in emmetropes (top) and progressing myopes (bottom). r values
indicate the correlation value after adjusting for baseline axial length. Solid
lines indicate the best fit regression line for emmetropes (blue line) and
progressing myopes (red line). p value indicates significance value. ...... 144
Figure 5.5: Association between the time of peak axial length measurement and the
habitual wake-up time (averaged across all days and seasons) for all subjects
(top) and in the emmetropes (blue dots) and progressing myopes (red dots)
(bottom). r values indicate the correlation coefficient. Solid lines indicate
the best fit regression line (black – all subjects, blue – emmetropes and red –
progressing myopes). p value indicates significance value. ................... 146
Figure 5.6: Relationship between 12-monthly changes in axial length and amplitude of
daily axial length variations (averaged across winter and summer) for all
subjects, after adjusting for baseline axial length (top), and after adjusting
for baseline axial length and objectively measured daily time exposed to
light levels >1000 lux (bottom). r values indicate the correlation coefficient.
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Solid lines indicate the best fit regression line for all subjects. p value
indicates significance value. .................................................................. 149
Figure 6.1: Illustration of the interaction between habitual daily light exposure (time
spent in bright outdoor [>1000 lux] light), amplitude (difference from peak
to trough) of daily axial length variations and longitudinal axial eye growth.
............................................................................................................. 176
Figure 6.2: Illustration of a potential model for the role of light exposure and diurnal
axial length variations in normal eye growth (top) and the development of
myopia (bottom). R – Retina, C – Choroid and S – Sclera. .................... 178
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xxiv The influence of light exposure and seasons upon the axial length changes in humans
LIST OF TABLES
Table 1.1: Summary of studies that assessed time outdoors and myopia in children. . 16
Table 1.2: Summary of selected studies that used objective techniques to assess light
exposure (time outdoors) in children and adults. ..................................... 26
Table 2.1: Coefficient of determination (R2) values for daily minutes of exposure to
bright light (>1000 lux) between different sampling durations and sampling
rates and the assumed gold standard (i.e. 14 days and 30 seconds). ......... 58
Table 3.1: The average climate conditions and day length over the period of Actiwatch
wear for each season and refractive group. .............................................. 81
Table 3.2: The mean ± SD light exposure measured over a 2 week period for
emmetropes and progressing myopes in different seasons. ...................... 86
Table 3.3: The mean ± SD sleep time, wake time and sleep efficiency for different
refractive error groups in different seasons. ............................................. 89
Table 4.1: Fixed effects from the linear mixed model (LMM) examining the
longitudinal changes in axial length over the 12 month study period. .... 110
Table 4.2: Mean ± SD axial length variation between seasons, and the time spent in
bright (outdoor) light (>1000 lux), mean daytime (6 am – 6 pm) light
exposure, and mean daytime (6 am – 6 pm) physical activity measures in
different seasons for emmetropes and progressing myopes. ................... 114
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Table 5.1: The mean ± SD amplitude (mm) of daily axial length variations on weekdays
and weekends in the emmetropes and progressing myopes over winter and
summer. ................................................................................................ 139
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xxvi The influence of light exposure and seasons upon the axial length changes in humans
LIST OF ABBREVIATIONS
AL Axial length
C Choroid
CPM Counts per minutes
CI Confidence Interval
CT Choroidal thickness
DS Dioptre sphere
DOPAC Dihydroxyphenylacetic acid
ICC Intraclass correlation coefficient
IOP Intraocular pressure
ipRGCs Intrinsically photosensitive retinal ganglion cells
IQ Intelligent quotient
LMM Linear mixed model
LOA Limits of agreement
nm Nanometre
OR Odds ratio
R Retina
RPE Retinal pigment epithelium
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S Sclera
SCN Suprachiasmatic nucleus
SD Standard deviation
SER Spherical equivalent refraction
UV Ultraviolet
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xxviii The influence of light exposure and seasons upon the axial length changes in humans
STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the best
of my knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signature: _
Date: __________________________
QUT Verified Signature
n9029630Date
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ACKNOWLEDGEMENTS
First and foremost, I would like to express my sincere and wholehearted gratitude
to my principal supervisor Associate Professor Scott Read for his patience, constant
guidance and support throughout this research. This thesis wouldn’t have been possible
without his time and expertise.
Thank you, my associate supervisors, Professor Michael Collins and Dr Stephen
Vincent, for your timely guidance and motivation during the most important times in
this research. Thank you, Dr David Alonso-Caneiro, for your help in data analysis in the
research.
I would like to acknowledge that I was supported by a “Myopia Endowment”
scholarship for this PhD, which enabled the successful completion of my PhD without
any financial hardship.
Special thanks to all my participants, for their time and willingness to help me in
this research. Sincere and heartfelt thanks, Catherine Foster and Madhavan Mani for
your support and assistance with recruiting participants for this research.
It was a pleasure to be associated with the Contact Lens and Visual Optics
Laboratory. The time I spent in the lab will be remembered as an amazing part of my
life. Thank you everyone for making this happen. Catherine, you have been friendly,
supportive and motivating. Thank you for all your help throughout these 3 years.
Thank you, Professor Peter Swann, for your help in proofreading the thesis.
Thank you, Pryntha, families back home, for your love and unconditional support
and for bearing with me for the past 3 years.
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The influence of light exposure and seasons upon the axial length changes in humans xxxi
Lastly, I would like to thank everyone who has directly or indirectly helped me
during these 3 years.
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Chapter 1: Literature review 1
Chapter 1: Literature review
1.1 Emmetropization and eye growth:
The condition where the geometric length of the eye (axial length) and the focal length
of its optics are matched to allow distance objects to form a clear image on the retina
without accommodation is called emmetropia. At birth, a mismatch between the axial
length and focal length of the eye is common. In most cases, axial length is shorter than
the focal length of the eye (resulting in images of distance objects focussing posterior to
the retina), leading to hyperopia or long-sightedness. In some instances, the axial length
is longer than the eye’s focal length (where images of distance objects focus anterior to
the retina), resulting in myopia or short/near-sightedness. During the post-natal period,
the eye undergoes rapid, coordinated growth in order to match the axial length with the
eye’s focal length. This eliminates the typically hyperopic neo-natal refractive error and
produces a clear image of distance objects on the retina. This active process of eye
growth in childhood is referred to as emmetropization (Wildsoet, 1997). It is believed
that visual signals guide the active emmetropization process, and interrupting these
visual signals in early life (e.g. by imposing retinal image blur/defocus, or through
deprivation of normal vision) leads to a breakdown of the normal emmetropization
process, resulting in the development of refractive errors such as myopia or hyperopia
(Wallman & Winawer, 2004).
Control of eye growth by visual signals: 1.1.1
There is substantial evidence showing that altering retinal image quality can alter
normal eye growth and result in refractive error development. Several animal and
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2 Chapter 1: Literature review
human studies have shown that the eye appears capable of detecting changes in the
quality of the retinal image and subsequently producing compensatory changes in eye
growth, when the retinal image is shifted in front or behind the retina (Schaeffel et al.,
1988; Irving et al., 1992; Hung et al., 1995; Kroger & Wagner, 1996; Whatham &
Judge, 2001; McFadden et al., 2004; Read et al., 2010; Irving et al., 2015), indicating
that the eye relies on vision to guide normal growth (Wildsoet, 1997; Wallman &
Winawer, 2004).
Defocus induced by spectacle lenses: 1.1.2
When a negative lens is placed in front of an emmetropic eye, the image plane is moved
behind the retina, inducing hyperopic defocus. Animal studies have shown that
exposure to hyperopic defocus results in an initial thinning of the choroid (the vascular
tissue posterior to the retina) (Wallman et al., 1995) and a subsequent increase in the
rate of eye growth (Nickla et al., 1997), moving the retina backwards towards the
defocussed image plane (resulting in myopic refractive errors when the negative lens is
removed). Once the retina attains a clear image, the rate of ocular elongation and
choroidal thickness returns to normal (Wallman & Winawer, 2004). Alternatively, when
a positive lens is placed in front of the eye, inducing myopic defocus, the eye
compensates by initially thickening the choroid, followed by a slowing of ocular
elongation, thereby moving the retina forwards towards the defocussed image plane
(resulting in a hyperopic refractive error when the defocus lens is removed) (Wallman et
al., 1995; Wildsoet & Wallman, 1995). It has been shown that myopic defocus induces
choroidal thickness changes of greater magnitude than hyperopic defocus in chicks,
since it appears that the choroid has a greater capacity to increase its thickness in
response to myopic defocus compared to thinning with hyperopic defocus (Wallman et
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Chapter 1: Literature review 3
al., 1995). However, the documented bi-directional responses to defocus, that are
proportional to the magnitude of induced myopic and hyperopic blur, suggests that
animal eyes have the ability to interpret the sign and magnitude of the blur and move the
retina in the corresponding direction in order to provide a clear image on the retina
(Schaeffel & Diether, 1999).
Form-deprivation: 1.1.3
If the retinal image is degraded by diffusers or through lid suture in animals such that it
disrupts form vision (resulting in blur both in front and behind the retina), the eye
responds with rapid axial elongation, resulting in large myopic refractive errors,
proportional to the magnitude of image degradation (Sherman et al., 1977; Wiesel &
Raviola, 1977; Wallman & Adams, 1987; Smith & Hung, 2000; Schaeffel et al., 2004).
Form-deprivation is also accompanied by substantial thinning of the choroid (Wallman
et al., 1995; Nickla & Wallman, 2010). The axial elongation leading to the development
of myopia in form-deprived eyes is hypothesized to be due to uncontrolled growth in the
absence of visual feedback (Wiesel & Raviola, 1977). However, when form-deprivation
is removed, the resultant myopic defocus (due to excessive elongation), leads to
choroidal thickening, followed by a slowing of eye growth, and the refraction returns to
emmetropia (Wallman & Winawer, 2004). This rapid recovery from form-deprivation
myopia emphasises the strong involvement of image quality on the control of eye
growth.
Similar to animal studies showing myopia development in response to form-deprivation,
ocular conditions that disrupt form-vision in humans such as congenital cataract, ptosis,
corneal opacity and vitreous haemorrhage have also been shown to lead to excessive
axial elongation and myopia development (O'Leary & Millodot, 1979; Hoyt et al., 1981;
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4 Chapter 1: Literature review
Rabin et al., 1981; Nathan et al., 1985; von Noorden & Lewis, 1987; Gee & Tabbara,
1988; Miller-Meeks et al., 1990; Meyer et al., 1999).
Local control of eye growth: 1.1.4
The mechanism controlling both form-deprivation and lens-induced refractive errors is
thought to be locally controlled within the eye given that severing the optic nerve does
not substantially affect the development of form-deprivation myopia, or the
compensation to spectacle lens-induced defocus (Troilo et al., 1987; Wildsoet &
Pettigrew, 1988; Norton et al., 1994; Wildsoet & Wallman, 1995; Wildsoet, 2003).
Imposing defocus to a localised retinal region also results in an ocular response
confined to the region of the retina exposed to defocus. For example, if a hemi-field
positive defocus lens is placed in front of the eye, ocular growth inhibition occurs only
in that corresponding hemi-field and the other half of the choroid and axial length show
normal growth (Hodos & Kuenzel, 1984; Wallman et al., 1987; Diether & Schaeffel,
1997; Smith et al., 2010).
Although it is acknowledged that local, visually guided eye growth involves the
detection of image blur (presumably by the retina), followed by a signal cascade
resulting in choroidal thickness changes and alterations in eye growth, the exact
mechanism and pathways underlying this process are not fully understood.
Accommodation was initially thought to mediate the association between visual signals
and eye growth, since accommodation can alter the optical focus of the eye. However,
several animal studies that blocked accommodation in eyes exhibiting active growth
(Schaeffel et al., 1990; Schwahn & Schaeffel, 1994; Schmid & Wildsoet, 1996),
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Chapter 1: Literature review 5
concluded that accommodation is not essential for either natural emmetropization or
emmetropization in response to imposed defocus to occur.
Form-deprivation and negative lens-induced axial elongation and myopia may have
different underlying mechanisms. Studies examining dopaminergic pathways in chicks
demonstrated that the administration of 6-hydroxy dopamine (a neurotoxin known to
damage retinal dopaminergic pathways) suppressed the development of form-
deprivation myopia, but not lens-induced myopia (Li et al., 1992; Schaeffel et al.,
1994). Studies in guinea pigs also demonstrate that the administration of dopamine
agonists inhibited the development of form-deprivation myopia, but did not completely
arrest the development of lens-induced myopia (Dong et al., 2011). This evidence
suggests that two different feedback mechanisms may be involved in the development
of form-deprivation myopia and lens-induced refractive errors (Schaeffel et al., 1994;
Ashby & Schaeffel, 2010).
Possible central nervous system involvement in the control of eye growth: 1.1.5
Although the majority of previous studies suggest that emmetropization mechanisms are
locally controlled within the eye, there is some evidence supporting a contribution from
the central nervous system to the control of eye growth. Wildsoet (2003) explored the
role of the central nervous system in normal emmetropization and experimentally
induced refractive errors in chicks by altering the inputs from the optic nerve and/or
ciliary nerve. The study showed that although an intact central nervous system was not
required for emmetropization or compensation to experimental refractive errors to
occur, the absence of input from both the optic nerve and ciliary nerve led to alterations
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6 Chapter 1: Literature review
in the emmetropization end-point, suggesting an interaction between brain centres and
the eye in the fine-tuning of emmetropization (Wildsoet, 2003).
Animal studies have also suggested that circadian rhythms of ocular structures may play
a significant role in the regulation of eye growth, since these natural circadian rhythms
are altered during the development of experimental refractive errors (Nickla, 2013;
Stone et al., 2013). Although the control of circadian rhythms is complex and not fully
understood, it is known that the circadian rhythms are controlled by a “clock gene”
which controls the timing of these rhythms (Roenneberg & Foster, 1997). It is also
known that intrinsically photosensitive retinal ganglion cells (ipRGCs) present in the
retina provide information about the ambient environmental lighting to the
suprachiasmatic nucleus (SCN) in the brain, thereby helping to synchronize the internal
circadian rhythms to the external light/dark cycle (Berson et al., 2002). Studies have
also shown that environmental light information from the retina are not necessary to
control the circadian rhythms, since rhythms can run even in the absence of a light/dark
cycle, but the inputs are essential to entrain the internal rhythms to the external
light/dark cycle (Inouye & Kawamura, 1979). These findings suggest that eye growth is
a coordinated process controlled primarily by local mechanisms with some contribution
from brain centres (Flitcroft, 2012).
Defocus induced axial length and choroidal thickness changes in humans: 1.1.6
The animal studies described above provide strong evidence that defocus can lead to
predictable changes in axial length and choroidal thickness across a range of different
species. Recently, a number of human studies have also investigated the impact of
retinal image blur upon choroidal thickness and eye length. In a sample of young adults,
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Chapter 1: Literature review 7
Read et al. (2010) demonstrated that short-term (60 minutes) imposition of lens-induced
hyperopic (-3 D) and myopic (+3) blur resulted in small magnitude, bi-directional
changes in axial length (+8 µm and -13 µm in response to hyperopic and myopic
defocus respectively). Choroidal thickness changes in response to blur were also
observed in this experiment, of opposite direction but lesser magnitude than axial length
changes (Read et al., 2010). Chiang et al. (2015) investigated the time-course and
amplitude of choroidal thickness changes in response to imposed myopic and hyperopic
defocus for a period of 60 minutes in young adults and also found a bi-directional
response to defocus, of slightly higher magnitude to the previous study (+20 µm and -20
µm change in choroidal thickness in response to -2 D hyperopic and +2 D myopic
defocus respectively). The response to myopic defocus was also more rapid (significant
thickening after 10 minutes of defocus) compared to hyperopic defocus (significant
thinning after 20 – 35 minutes of defocus) (Chiang et al., 2015). Chakraborty et al.
(2012, 2013) reported that the natural diurnal rhythms occurring in axial length and
choroidal thickness of young adults were altered after imposing hyperopic and myopic
defocus, and bi-directional axial length and corresponding choroidal thickness changes
were documented after 3 hours of hyperopic and myopic defocus. In a population of
children, Wang et al. (2016) documented similar bi-directional axial length and
choroidal thickness changes after imposing myopic and hyperopic defocus. Recovery
from these changes was also observed in the two hours following removal of the
defocus in these children, suggesting that the ocular responses to short-term defocus in
the human eye are rapid and reversible upon removal (Wang et al., 2016).
There is consistent evidence therefore that exposure of the human eye to defocus can
result in changes in axial length and choroidal thickness, consistent with previous
findings in animal research. While these findings suggest a potential role of defocus in
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8 Chapter 1: Literature review
the development of human refractive errors and are consistent with a visually guided
emmetropization process in human eyes, the short-term nature of the majority of the
human studies in this field mean the impact of defocus on longer-term eye growth and
myopia development in humans is not clearly understood.
1.2 Human myopia:
Myopia is a common refractive error, currently affecting approximately 30% of the
world’s population (Holden et al., 2016), that occurs when the eye grows too long for its
refractive power, causing distant light rays to be focussed in front of the retina. Myopia
most commonly develops due to excessive axial elongation of the eye (i.e. axial
myopia), however myopia can also develop in some cases due to excessive refractive
power of the eye (i.e. refractive myopia). Myopia typically develops in early to mid-
childhood and progresses into adulthood (Cumberland et al., 2007). However, there is
also evidence that myopia can develop and progress in adults, particularly in certain
populations (e.g. university students and microscopists) (McBrien & Adams, 1997;
Kinge et al., 2000). Myopia is considered to be a major public health concern, due to its
increasing prevalence in recent decades and the documented association between
myopia and sight-threatening ocular complications such as cataract, retinal detachment,
retinal degeneration, and glaucoma (Flitcroft, 2012; Morgan et al., 2012).
Epidemiology: 1.2.1
There is evidence suggesting that a significant increase in the prevalence of myopia has
occurred in recent decades. The greatest increase in prevalence has been observed in
developed East-Asian and South-East Asian countries like Singapore, Hong Kong,
Japan and China, where recent reports indicate myopia (greater than -0.25 D)
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Chapter 1: Literature review 9
prevalence of up to 80 – 90% in young populations (school-leavers) in these countries,
with approximately 10 – 20% of these myopes exhibiting high myopia (greater than -
6.00 D) (Lin et al., 2004). Other countries outside of East Asia (e.g. Europe (prevalence
levels in different age groups range from 9.4 – 29.4%), America (2 – 41%), Australia
(11.9%), Africa (1.6 – 9.6%) and South-Asia (4.1 – 7.4%)) also show evidence of
increasing myopia prevalence, but the rate of increase in myopia is lower compared to
East and South-East Asian countries (Morgan & Rose, 2005; Vitale et al., 2009; Pan et
al., 2012). Interestingly, there appears to be a difference in myopia prevalence among
children of Chinese ancestry living in different geographic locations, with Chinese
children living in Sydney, Australia noted to have a substantially lower myopia
prevalence compared to Chinese children living in Singapore (Rose et al., 2008b).
These findings suggest that genetics alone are unlikely to account for the rapid rise in
prevalence, but, the association of myopia with increased educational pressures and
geographic location support a role of environmental influences on myopia development
(Morgan & Rose, 2005; Morgan et al., 2012).
Invariably, studies typically show that the prevalence of myopia increases with age,
throughout childhood and in young adults. Across different countries, the estimate of
myopia prevalence among 5 year old children ranges from 1.6% to 11.3%, and the
prevalence among 15 year old children ranges from 13.0% to 69%, showing a clear
trend of increasing prevalence with age (Rudnicka et al., 2016). Although myopia most
commonly develops in childhood, there is considerable evidence that myopia can also
develop and progress in adulthood. The incidence and progression of myopia have been
documented in a number of populations of young adults (mean ages ranging from 18 to
26 years), in a range of geographic locations (e.g. Taiwan, Denmark, Norway, UK,
USA) particularly in populations of adults with high near-work demands (e.g. university
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10 Chapter 1: Literature review
students, microscopists). Studies of myopia in adults have reported incidence levels of
myopia ranging from 6% to 22.5% per year and progression rates from -0.13 D/year to -
0.24 D/year (Shulkin & Bari, 1986; Zadnik & Mutti, 1987; Lin et al., 1996; Kinge &
Midelfart, 1999; Kinge et al., 2000; Onal et al., 2007; Jacobsen et al., 2008). Adult-
onset myopia also typically occurs due to axial elongation of the eye, with reported rates
of axial elongation in young adults ranging from 0.010 to 0.083 mm per year.
Aetiology of myopia: 1.2.2
Myopia is aetiologically heterogeneous. Its risk factors include genetics as well as
environmental influences such as near-work, level of education, time spent outdoors,
ethnicity, urban environment and dietary factors (Morgan & Rose, 2005).
1.2.2.1 Genetics:
A variety of different genes have been reported to be associated with myopia (Kiefer et
al., 2013; Li et al., 2015a). Sibling risk ratio is high in myopia with the risk increasing
with the severity of myopia (Guggenheim et al., 2000). However, it should also be noted
that while families and siblings do share genes, they typically share similar
environments as well. An established finding is that children with myopic parents have
a higher prevalence of myopia compared to children without myopic parents (Ip et al.,
2008), but the relative risk varies with location especially in high prevalence locations
like East-Asia (Morgan et al., 2012). In a study of Singaporean Chinese pre-school
children (aged from 6 to 72 months of age), a family history of myopia was found to be
the strongest factor associated with myopia, and environmental factors such as near-
work and outdoor activity were not associated with early myopia. These findings
suggest that genetics play a substantial role, particularly in early-onset myopia (Low et
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Chapter 1: Literature review 11
al., 2010). Wojciechowski (2011) recently reported that complex interactions between
genes and/or environmental factors are also likely to be important in determining
individual risk of myopia development.
1.2.2.2 Environmental factors:
Although genetics is considered a major risk factor, the rapidly increasing prevalence of
myopia in recent decades and results from human and animal experimental studies
suggest important additional environmental factors influence myopia development and
progression. Results from these studies have shown that the eye’s growth rate appears to
be increased or decreased by a variety of environmental modifications such as induced
retinal defocus, varying light levels and altering other aspects of visual input (Wallman
& Winawer, 2004; Nickla, 2013; Norton & Siegwart, 2013; Stone et al., 2013).
1.2.2.2.1 Near-work:
Since myopia typically develops during the school years (so called “school myopia”)
(Sorsby, 1932) and near-work demands are also higher during schooling, near-work has
long been considered as an important risk factor in myopia development and
progression. Higher levels of education and near-work related activities have been
found to be associated with increased myopia prevalence in a number of studies (Saw et
al., 2002a; Saw et al., 2007; Ip et al., 2008). Myopia prevalence is also higher among
children attending selective schools with higher academic demands (Quek et al., 2004).
In a cross sectional study of 7 to 9 year old school children, near-work was associated
with high myopia and early-onset myopia independent of other risk factors (Saw et al.,
2002a). However, it is important to note that a significant association between myopia
and near-work is not a universal finding in all studies. A longitudinal study of 7 to 9
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12 Chapter 1: Literature review
year old children in Singapore assessed near-work in detail with a questionnaire
regarding books read per week, hours per day reading, computer use, playing video
games and watching television (Saw et al., 2006). They found that parental myopia and
a higher Intelligent Quotient (IQ) increased the risk of onset of myopia more than near-
work activity (number of books read per week) (Saw et al., 2006). Another longitudinal
study of 514 children, that investigated factors predictive of juvenile myopia onset,
found parental myopia was a significant predictor of myopia onset, but near-work (i.e.
various tasks related to near-work) was not a significant factor that could predict
myopia development (Jones et al., 2007).
Since imposed hyperopic defocus results in myopia development in animals, a larger lag
of accommodation due to under accommodation during near-work (which results in
hyperopic defocus during reading) has been postulated to be one potential factor
underlying the association between myopia and near-work in humans (Gwiazda et al.,
1993). Although myopic children have been reported to have higher accommodative
lags than emmetropic children (Gwiazda et al., 1993), a longitudinal study found no
increase in the lag of accommodation in children prior to the onset of myopia (Mutti et
al., 2006). Moreover, studies have shown that there is no correlation between
accommodative inaccuracy and the rate of emmetropization (Gabriel & Mutti, 2009) or
myopic eye growth (Mutti & Zadnik, 2009). Although there is some support for a
potential role for near-work in myopia development and progression, the conflicting
findings from a number of studies regarding a role for near-work in myopia suggest
there are likely additional environmental factors involved.
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Chapter 1: Literature review 13
1.2.2.2.2 Outdoor activity:
The amount of time spent on outdoor activities has emerged in recent years as an
additional environmental influence on myopia. Several studies have shown that children
who spend more time outdoors are less likely to become myopic (Parssinen & Lyyra,
1993; Mutti et al., 2002; Jones et al., 2007; Rose et al., 2008a; Rose et al., 2008b; Dirani
et al., 2009; Jones-Jordan et al., 2011; Guggenheim et al., 2012; French et al., 2013a;
French et al., 2013c; Guo et al., 2013a; Wu et al., 2013; Read et al., 2014; He et al.,
2015; Li et al., 2015b; Guo et al., 2017) (Table 1.1). Low levels of outdoor activity have
been reported in children living in urban Beijing (1 hour/day) (Guo et al., 2013a),
Taiwan (0.5 hours/day) (Wu et al., 2010) and Singapore (0.5 hours/day) (Rose et al.,
2008b), and all of these locations are documented to have a high prevalence of myopia
in young populations. A study of school students of Chinese ancestry in Singapore and
Sydney showed that myopia prevalence was higher in Chinese children living in
Singapore, and the time spent outdoors was the major distinguishing factor between the
two groups (Rose et al., 2008b).
Parssinen and Lyrra (1993) investigated the factors associated with myopia progression
in Finnish myopic school children and established the association between time
outdoors and myopia for the first time, although significant effects were only observed
in boys. They found that greater time spent outdoors and in sports activities was
associated with less myopic refraction and slightly slower myopia progression.
Subsequently, in a cohort of American school children, Mutti et al. (2002) established
that children with myopia were involved in less sports and outdoor activities compared
to emmetropic children of similar age. A study of Australian school children found that
higher levels of outdoor activities were associated with more hyperopic refraction and
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14 Chapter 1: Literature review
less myopia prevalence, suggesting a protective effect of outdoor activity against
myopia (Rose et al., 2008a).
In a prospective longitudinal study of childhood myopia, French et al. (2013c) reported
that more time spent outdoors at a young age (around 6 years) had a protective effect
against future myopia development irrespective of the amount of near-work performed.
Guggenheim et al. (2012) also suggested that time outdoors at the age of 8 – 9 years
significantly predicted the future development of myopia. A recent longitudinal study
(4-years follow-up) that investigated the factors associated with myopia development
and progression in primary school children in China also revealed that less time spent
outdoors and longer time spent indoors was significantly associated with greater ocular
axial elongation and myopia progression (Guo et al., 2017). Recent studies have also
shown that interventions to increase outdoor time during school hours result in a
significant decrease in myopia incidence (Wu et al., 2013; He et al., 2015), suggesting
that time spent outdoors protects against the development of myopia. Although most
studies have reported significant associations between more outdoor activity and less
prevalence and incidence of myopia, a study of rural Chinese school children (mean age
14.6 years) found no association between outdoor activity and myopia progression (Lu
et al., 2009). A longitudinal study of American school children also found that myopia
progression was not associated with sports and outdoor activities (Jones-Jordan et al.,
2012).
The consistent finding across the majority of studies of an association between less
myopia and more time outdoors, supports a potential role of light exposure in the
regulation of human eye growth, since ambient light levels outdoors are substantially
higher than typical indoor light levels. A number of possible mechanisms have been
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Chapter 1: Literature review 15
postulated for this association, including: bright light exposure causing increased retinal
dopamine (which has been shown to inhibit axial elongation in animal studies) (Iuvone
et al., 1989; McCarthy et al., 2007), increased light intensity leading to pupil
constriction, increased depth of focus, decreasing blur and slowing eye growth (Rose et
al., 2008a), less accommodative demand when outdoors (Deng et al., 2010), the spectral
composition of outdoor light (Mehdizadeh & Nowroozzadeh, 2009), or the influence of
vitamin D due to sun exposure (Mutti & Marks, 2011).
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16 Chapter 1: Literature review
Table 1.1: Summary of studies that assessed time outdoors and myopia in children.
Author, year Sample Participants Location, Design Key findings
Parssinen & Lyyra,
1993 238
Myopic school children
Age: 11 years
Finland,
Longitudinal (3 years
follow-up)
Time spent on sports and outdoor activities significantly
associated with myopia progression in boys.
Mutti et al., 2002
336
School children
Age: 14 years
USA,
Cross-sectional
Myopic children spent significantly less time in outdoor sports
per week than emmetropic children (7.4 hours/week in
myopes vs 9.7 hours/week in emmetropes). Less time in
sports activity was associated with higher odds of juvenile
myopia (OR=0.92).
Saw et al., 2002b
957
School children (Chinese)
Age: 7-9 years
Singapore and China,
Cross-sectional
Children in China had lower myopia prevalence than
Singapore (19% vs 37%) and spent more time outdoors per
week (8.7 vs 3.3 hrs/week).
Saw et al., 2006
994
Non-myopic school
children
Age: 7-9 years
Singapore,
Longitudinal (3 years
follow-up)
Time spent outdoors was not related to incident myopia.
Khader et al., 2006
1777
School children, Age: 12-
17 years
Jordan,
Cross-sectional
Non-myopic children spent more time outdoors than myopes
(4 vs 1.9 hrs/day). Playing sports was inversely associated
with myopia (OR=0.89).
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Chapter 1: Literature review 17
Jones et al., 2007
514
Population,
Age: 9 years
USA, Longitudinal (11
years follow-up)
Children who developed myopia spent less time in sports and
outdoor activities (8 vs 11.7 hrs/week). Lower amounts of
sports and outdoor activities increased the odds of becoming
myopic (OR=0.91).
Rose et al., 2008a
4088
Population,
Age: 6 years and 12 years
Australia,
Cross-sectional
Less time outdoors and more near-work had greater odds of
myopia in older children (OR=2.6). More time on near-work
combined with more time outdoors did not appear to increase
myopia risk. Indoor sports had no association with myopia.
Rose et al., 2008b
4088
Chinese school children
Age: 6 years
Australia and Singapore,
Cross-sectional
Higher myopia prevalence in Singaporean children than
Sydney children (29 vs 3%). The difference in prevalence was
associated with differences in time spent outdoors (Singapore
vs Sydney children: 3 vs 14 hrs/week).
Dirani et al., 2009
1249
School children,
Age: 14 years
Singapore,
Cross-sectional
Myopic children spent less time outdoors than non-myopic
children (3.1 vs 3.6 hrs/day). Children who spent more time
outdoors were less likely to be myopic (OR=0.90).
Lu et al., 2009
998
School children,
Age: 15 years
China,
Cross-sectional
Time spent outdoors was not significantly different between
myopic and non-myopic children (6 vs 6.2 hrs/week). Time
spent outdoors was low for the whole population and the
prevalence of myopia was 83%.
Low et al., 2010 2639
Preschool children,
Age: 6-72 months
Singapore,
Cross-sectional
Outdoor activity was not different between myopic and
emmetropic preschool children (0.7 vs 0.86 hrs/day).
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18 Chapter 1: Literature review
Wu et al., 2010
145
School children,
Age: 7-12 years
Taiwan (Rural),
Cross-sectional
Rural children who spent more time outdoors were protected
against myopia development. Outdoor activity was inversely
associated with myopia (OR=0.3).
Jones-Jordan et al.,
2011 1329
Population,
Age: 6-14 years at
baseline
USA, (CLEERE,
multicentre) Longitudinal
(10 years follow-up)
Compared to emmetropes, children who developed myopia
spent fewer hours in sports/outdoor activities from 3 years
before onset to 4 years after onset.
Jones-Jordan et al.,
2012 835
Population,
Age: 6-14 years at
baseline
USA, (CLEERE,
multicentre) Longitudinal
(1 year follow-up)
Time engaged in outdoor/sports activity was not associated
with myopia progression.
Guggenheim et al.,
2012
3061
Population,
Age: 7 years at baseline
England, Longitudinal (8
years follow-up)
Children who spent more time outdoors at the age of 8 – 9
years were at less risk of developing myopia after 11 years of
age, compared to children who spent less time outdoors. Time
spent outdoors predicted myopia independent of physical
activity.
Sherwin et al., 2012
636
Population,
Age: >15 years
Norfolk Island,
(NIES)
Cross-sectional
Prevalence of myopia decreased with increasing time
outdoors, but time outdoors was not statistically associated
with myopia.
Guo et al., 2013a
681
School children,
Age: 5 – 8 years and 8 –
13 years
China (urban and rural),
Cross-sectional
Longer axial length and myopia was associated with less time
spent outdoors. Less time outdoors was associated with higher
odds of myopia (OR=0.32). Children living in urban regions
had higher odd of developing myopia than children in rural
regions (OR=0.17).
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Chapter 1: Literature review 19
Guo et al., 2013b
643
School children,
Age: 5 – 8 years and 8 –
13 years at baseline
China (urban and rural),
Longitudinal (1 year
follow-up)
Axial elongation was significantly associated with less time
spent outdoors (OR=0.53). Urban habitation was not
associated with axial elongation.
French et al., 2013b
2103
Population,
Age: 6 and 12 years at
baseline
Australia, (SMS and
SAVES),
Longitudinal (5-6 year
follow-up)
Children of East-Asian ethnicity spent less time outdoors
compared to Caucasian children (one hour difference). Less
time outdoors was associated with higher odds of myopia in
both age groups (OR=2.84 in 6 year old children and
OR=2.15 in 12 year old children).
Guo et al., 2017
382
School children,
Age: 6.3 years
China (urban and rural),
Longitudinal (4 year
follow-up)
Greater axial elongation was associated with less time spent
outdoors. Children who spent less time outdoors over 4 years
had higher odds of developing myopia (OR=0.63).
OR, odds ratio
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20 Chapter 1: Literature review
1.2.2.2.3 Seasonal variations in myopia progression:
Further evidence for a potential role of light exposure in the regulation of human eye
growth is provided by the finding that the rate of eye growth appears to vary in different
seasons (potentially due to the days being longer in summer than winter, allowing the
opportunity for more light exposure in summer months). Studies have shown that
myopia progression/axial elongation slows down in summer compared to winter (Fulk
& Cyert, 1996). A recent longitudinal study of Danish children reported that both the
rate of myopia progression and axial growth was associated with day length (i.e. with
increasing day length, the myopia progression and axial growth rate decreased) (Cui et
al., 2013). This study also revealed that the cornea steepens and the axial growth rate
reduces during summer compared to winter and vice versa. Estimated cumulative
daylight exposure (derived from meteorological records, rather than direct measures of
individual exposure) was also found to have a significant correlation with the rate of
myopia progression and axial growth (Cui et al., 2013).
Another longitudinal study of children in the United States measured refraction
periodically across a 3 year period and reported that myopia progression was
significantly higher during the winter months than summer. The mean myopia
progression in winter was -0.35 D per 6 months, whereas in summer it was -0.14 D
(Gwiazda et al., 2014). In Chinese children, Donovan et al. (2012) reported a
progression of -0.31 D in summer and -0.53 D for winter. It has been suggested that the
combination of low levels of near activities and longer outdoor hours may modulate the
reduction in progression typically observed during summer (Rose et al., 2008a; Deng et
al., 2010; French et al., 2013c). Although significant associations have been consistently
found between seasons and eye growth, none of the above mentioned studies
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Chapter 1: Literature review 21
objectively quantified the light exposure across the different seasons. Hence, future
work is needed to quantify the relationship between seasonal variations in eye growth
and light exposure which could improve the understanding of the mechanisms
regulating human eye growth.
1.2.2.2.4 Physical activity and myopia:
Although increased light exposure outdoors is commonly postulated as being involved
in the association between myopia and outdoor activities, the fact that people are often
more physically active when they spend time outdoors leaves open a potential role for
physical activity in this association. Studies examining physical activity and myopia
have shown that myopes are less physically active (Deere et al., 2009) and spend less
time in sports activities (Mutti et al., 2002) compared to non-myopes. A recent study
showed that children who became myopic spent significantly less time outdoors and
less time involved in sporting activities before and after the development of myopia
when compared to emmetropes (Jones-Jordan et al., 2011). Studies of young adults have
also reported that myopes were engaged in less physical activity than non-myopes and
physical activity was also a significant predictor of myopia progression in university
students (Jacobsen et al., 2008; Deere et al., 2009).
Interestingly, a recent population based study in Sydney, found that indoor sport was
not associated with myopia, and concluded that the total time spent outdoors is more
important than time involved in sporting activities (Rose et al., 2008a). Guggenheim et
al. (2012) also assessed time spent outdoors (using questionnaires) and objective
physical activity in childhood myopia, and suggested that the association between
physical activity and myopia incidence is primarily due to physical activity measures
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22 Chapter 1: Literature review
providing information about time outdoors, rather than an independent effect of
physical activity. Read et al. (2014) objectively assessed physical activity in a cohort of
Australian school children and found no significant difference in the physical activity
levels between myopic and emmetropic children. In a longitudinal study following these
same children, objective physical activity measures were not significantly associated
with longitudinal eye growth (Read et al., 2015). A recent study that objectively
assessed the physical activity of Danish school children has also shown that physical
activity was not associated with axial length or spherical equivalent refraction
(Lundberg et al., 2017). These findings suggest that the time involved in physical/sports
activities does not appear to be the major factor underlying the association between
myopia and outdoor time.
1.2.2.2.5 Light exposure and human myopia:
The association between less myopia and more outdoor activities, and the seasonal
variations in eye growth all support a role for light exposure in the regulation of eye
growth and the development of myopia. It is worth noting though that the majority of
studies reporting upon the association between time spent outdoors and myopia have
used questionnaires to estimate outdoor time and/or time engaged in physical activity
(Jones et al., 2007; Rose et al., 2008b; Dirani et al., 2009). Questionnaire based activity
estimates are subjective and may vary due to memory bias (Alvarez & Wildsoet, 2013).
These potential drawbacks associated with questionnaires have been the catalyst for a
number of recent studies that have quantified the light exposure (Backhouse & Phillips,
2011; Dharani et al., 2012; Alvarez & Wildsoet, 2013; Schmid et al., 2013; Read et al.,
2014, 2015; Ostrin, 2017) and/or physical activity (Deere et al., 2009; Guggenheim et
al., 2012; Read et al., 2014, 2015) using objective techniques such as wearable sensors
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Chapter 1: Literature review 23
in order to quantify individual environmental exposures (Table 1.2). Studies comparing
questionnaires of outdoor exposure and objective light exposure measures have
generally found relatively poor agreement between subjective questionnaire responses
and objective light exposure measures (Dharani et al., 2012; Alvarez & Wildsoet,
2013).
Recent studies using objective ambient light exposure measurements in both children
(Dharani et al., 2012; Read et al., 2014, 2015) and young adults (Alvarez & Wildsoet,
2013; Schmid et al., 2013; Ostrin, 2017) have consistently reported that subjects
typically spend only relatively small amounts of time per day (between 1-2 hours on
average) exposed to outdoor light levels (typically defined as ambient light exposures
>1000 lux (Guillemette et al., 1998; Goulet et al., 2007; Backhouse & Phillips, 2011;
Dharani et al., 2012; Alvarez & Wildsoet, 2013; Read et al., 2014, 2015)). Dharani et al.
(2012) reported that Singaporean children experienced greater light exposure on
weekends compared to weekdays, but did not find any significant difference in average
light exposure between myopic and emmetropic children. Of note, the light exposure
levels reported in both the myopic and emmetropic children were relatively low in this
study (~60 minutes per day exposed to light >1000 lux). Using objective light exposure
measurements, Read et al. (2014) also reported that Australian children experienced
greater light exposure on weekends, but in contrast to the findings of Dharani et al.
(2012), a significant difference in light exposure was found between myopic children
(mean of 91 minutes per day exposed to light >1000 lux) and emmetropic children
(mean of 127 minutes per day), consistent with previous questionnaire based studies
reporting less time outdoors in myopic children (Read et al., 2014). In a subsequent
longitudinal study, Read et al. (2015) established that greater daily light exposure was
associated with slower axial eye growth irrespective of the existing refractive error in
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24 Chapter 1: Literature review
school children. They found that children who were exposed to low daily light exposure
(on average, mean daily light exposure of 1000 lux) had significantly faster axial eye growth over a period of 18
months compared to children habitually exposed to moderate and high light levels.
In a small sample of 35 young adults, Schmid et al. (2013) found no significant
difference in ambient visible light exposure associated with myopia, but did find
significantly greater UV light exposure in stable myopes compared to progressing
myopes. Alvarez and Wildsoet (2013) examined objective light exposure in 27 young
adults (4 emmetropes and 23 myopes) and found no evidence of differences associated
with refractive errors or seasons in light exposure. Using a wrist-worn light sensor,
Ostrin (2017) reported that personal light exposure in adults (aged 21-65 years) with
(self-reported) myopic and emmetropic refractive errors was significantly higher in
summer when compared to winter, but there was no difference in light exposure
between refractive groups. However, neither of these studies captured the light exposure
on the same group of pa