CHANGES ON SHORT-TERM AND LONGER-T C I - QUT · 2018. 1. 31. · Sekar Ulaganathan (MPhil Optometry) Submitted in fulfilment of the requirements for the award of the degree of Doctor

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

ii The influence of light exposure and seasons upon the axial length changes in humans

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

iv The influence of light exposure and seasons upon the axial length changes in humans

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

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

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

viii The influence of light exposure and seasons upon the axial length changes in humans

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)

The influence of light exposure and seasons upon the axial length changes in humans ix

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

x The influence of light exposure and seasons upon the axial length changes in humans

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.

The influence of light exposure and seasons upon the axial length changes in humans xi

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

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

The influence of light exposure and seasons upon the axial length changes in humans xiii

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

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

The influence of light exposure and seasons upon the axial length changes in humans xv

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

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

The influence of light exposure and seasons upon the axial length changes in humans xvii

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

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

The influence of light exposure and seasons upon the axial length changes in humans xix

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

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

The influence of light exposure and seasons upon the axial length changes in humans xxi

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

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.

The influence of light exposure and seasons upon the axial length changes in humans xxiii

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

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

The influence of light exposure and seasons upon the axial length changes in humans xxv

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

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

The influence of light exposure and seasons upon the axial length changes in humans xxvii

S Sclera

SCN Suprachiasmatic nucleus

SD Standard deviation

SER Spherical equivalent refraction

UV Ultraviolet

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

The influence of light exposure and seasons upon the axial length changes in humans xxix

xxx The influence of light exposure and seasons upon the axial length changes in humans

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.

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.

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

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


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;


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),


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


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,


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


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)


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


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


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


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.


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


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


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).


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).


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).


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).


Guo et al., 2013b

643

School children,

Age: 5 – 8 years and 8 –

13 years at baseline


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


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


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


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


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


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


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

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CHANGES ON SHORT-TERM AND LONGER-T C I - QUT · 2018. 1. 31. · Sekar Ulaganathan (MPhil Optometry) Submitted in fulfilment of the requirements for the award of the degree of Doctor