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The cost of vision loss in Canada

Report by Access Economics Pty Limited for the

CNIB and the Canadian Ophthalmological Society

DisclaimerDisclaimer here

While every effort has been made to ensure the accuracy of this document, the uncertain nature of economic data, forecasting and analysis means that Access Economics Pty Limited is unable to make any warranties in relation to the information contained herein. Access Economics Pty Limited, its employees and agents disclaim liability for any loss or damage which may arise as a consequence of any person relying on the information contained in this document.


CONTENTS

Glossary of acronyms.............................................................................................................iExecutive summary................................................................................................................ii1. Background....................................................................................................................1

1.1 Definitions................................................................................................................11.1.1 Better eye, worse eye 21.1.2 Severity definitions used in this report 2

1.2 Main causes of impairment......................................................................................31.2.1 Age related macular degeneration (AMD) 31.2.2 Cataract 41.2.3 Diabetic retinopathy 61.2.4 Glaucoma 81.2.5 Refractive error (RE) and other causes of vision loss 10

2. Estimating prevalence.................................................................................................152.1 Population data......................................................................................................15

2.1.1 Age, gender and growth 152.1.2 Ethnicity 19

2.2 Data sources for prevalence of vision loss.............................................................232.2.1 Population-based eye studies 242.2.2 Canadian self-reported survey data 242.2.3 Data from Canadian journal articles and research studies 32

2.3 Prevalence rates for VL..........................................................................................362.3.1 White population VL 362.3.2 Aboriginals and Visible Minorities (AVM) VL 392.3.3 Cataract-induced VL in AVM 402.3.4 VL caused by AMD, Glaucoma and RE in AVM 442.3.5 Diabetes and DR in the AVM population 482.3.6 Summary of VL in AVM populations 50

2.4 Summary................................................................................................................51

3. Health system expenditure.........................................................................................623.1 Total expenditure on ‘vision care’...........................................................................623.2 Expenditure on particular eye disorders.................................................................633.3 Total health system expenditure.............................................................................66

3.3.1 Health system expenditure, top down 663.3.2 Health system expenditure, bottom up 67

4. Other financial costs...................................................................................................694.1 Productivity losses..................................................................................................69

4.1.1 Employment participation 69


4.1.2 Absenteeism from paid and unpaid work 704.1.3 Presenteeism 714.1.4 Premature mortality 724.1.5 Funeral costs 72

4.2 DWL from transfers................................................................................................724.2.1 Lost taxation revenue 724.2.2 Social security payments 744.2.3 Deadweight losses 75

4.3 Care and other assistance.....................................................................................764.4 Aids and devices....................................................................................................78

4.4.1 Canes and accessories 794.4.2 Writing aids/stationery 794.4.3 Variable speed tape recorders 814.4.4 Computer voice synthesizer software 814.4.5 Electronic Braille display systems 814.4.6 Talking time pieces 814.4.7 Sunglasses with non-corrective lenses 824.4.8 Hand held magnifiers 824.4.9 Video magnifiers/CCTVs 824.4.10 Screen magnification software 834.4.11 Other aids for the sight impaired 834.4.12 Summary of aids and devices 84

4.5 Summary of other financial costs...........................................................................86

5. Burden of disease........................................................................................................875.1 Willingness to pay and the value of a life year.......................................................87

5.1.1 Measuring burden: DALYs, YLLs and YLDs 875.1.2 Willingness to pay and the value of a statistical life year 87

5.2 Burden of disease from vision loss.........................................................................895.2.1 Disability weights 895.2.2 Deaths from VL 905.2.3 Years of life lost due to disability 905.2.4 Years of life due to premature death 90

5.3 Total DALYs due to VL...........................................................................................91

6. Summary......................................................................................................................93Appendix A: EDPRG prevalence tables..............................................................................96Appendix B: Prevalence projections by age, gender and disease................................100References...........................................................................................................................106


FIGURESFigure 1-1: Vision problems among Canadian seniors (% of age group) 1Figure 1-2: Prevalence of AMD by age and gender in whites (% population) 4Figure 1-3: Prevalence of cataract by age and gender in whites (% population) 5Figure 1-4: Rates of cataract surgery by age 6Figure 1-5: Prevalence of DR by age and gender in whites (% population) 8Figure 1-6: Prevalence of glaucoma by age and gender in whites(% population) 10Figure 1-7: Prevalence of myopia by age and gender in whites (% population) 11Figure 1-8: Prevalence of hyperopia by age and gender in whites (% population) 11Figure 1-9: Prevalence of hyperopia across countries by age, gender and source study

(% population) 13Figure 1-10: Prevalence of myopia across countries by age, gender and source study

(% population) 14Figure 2-1: Prevalence and incidence approaches to cost measurement 15Figure 2-2: Canadian population by age (’000 people), 2006 and 2031 16Figure 2-3: White and AVM populations, 2006-2032 (% total) 20Figure 2-4: Aboriginals and Visible Minorities, 1981-2017, selected years (%

population) 21Figure 2-5: Age distribution of non-white males (% population), 2001 22Figure 2-6: Age distribution of non-white females (% population), 2001 22Figure 2-7: Ethnic composition of Canadian population compared to Australia’s 23Figure 2-8: Prevalence of seeing disabilities by age and gender (2001) 25Figure 2-9: Uncorrected VL, by ethnicity, age and gender (% population) 26Figure 2-10: Under corrected VL from myopia, by ethnicity, age and gender (%

population) 27Figure 2-11: Under corrected VL from hyperopia, by ethnicity, age and gender (%

population) 27Figure 2-12: Canadians unable to see clearly at any distance or at all, by ethnicity, age

and gender (% population) 28Figure 2-13: Cataract prevalence, by ethnicity, age and gender (% population) 29Figure 2-14: Glaucoma, by ethnicity, age and gender (% population) 30Figure 2-15: Causes of VL in Prince George, Canada 33Figure 2-16: Myopia in Chinese children in Canada and Hong Kong 34Figure 2-17: Causes of blindness by ethnicity (US) 39Figure 2-18: Probability of developing VL after contracting selected diseases, by

ethnicity 46Figure 2-19: Prevalence rates of VL, by ethnicity and cause, 2007 52Figure 2-20: Prevalence of VL, by cause, 2007-2032 53


Figure 2-21: Prevalence of VL by gender, 2007 to 2032 54Figure 2-22: Projections of VL, by ethnicity, 2007 to 2032 54Figure 2-23: Relative share of total VL, by ethnicity, 2007 to 2032 55Figure 3-1: Canadian health system expenditure, 2007 (% of total) 62Figure 3-2: Expenditure on vision care, Canada, 1975-2007 63Figure 4-1: DWL of taxation 76Figure 4-2: Comparison of assistance with activities of daily living between study

groups 77Figure 5-1: Loss of wellbeing due to VL (DALYs), by age and gender, 2007 91Figure 6-1: Financial costs of VL, by type of cost (% total) 94Figure 6-2: Financial costs of VL, by bearer (% total) 94

TABLESTable 2–1: Canadian population projections, males (‘000), 2006-2031, selected years17Table 2–2: Canadian population projections, females (‘000), 2006-2031, selected years18Table 2–3: Ethnic composition of Canadian population (% total), 2001 19Table 2–4: Prevalence of diabetes, by age and gender, 2005 (%) 31Table 2–5: CCHS prevalence of eye diseases in AVM 32Table 2–6: Causes of blindness in CNIB clients (2007) 33Table 2–7: Prevalence of POAG among the Eskimo (%) 35Table 2–8: Prevalence of diabetes among Canadian Aboriginal peoples (1991) 35Table 2–9: Prevalence of blindness by cause, 2006 to 2031 (% population) 36Table 2–10: causes of VL, by disease, in white populations 36Table 2–11: Prevalence of VL due to AMD, by severity (% of age group) 37Table 2–12: Prevalence rates for VL from cataracts, by age and severity (%) 37Table 2–13: Prevalence rates for vision impairment (<6/12) from DR, and proportion by

stage of vision loss 37Table 2–14: Proportion of people with glaucoma by age and severity (%) 38Table 2–15: Prevalence rates for VL from RE, by age and severity (%) 38Table 2–16: Estimated VL prevalence in Canadian whites by disease and age 39Table 2–17: Prevalence of VL in US whites with cataracts (2000) 40Table 2–18: Prevalence of VL in US blacks with cataracts (2000) 41Table 2–19: Prevalence of VL in US Hispanics with cataracts (2000) 41Table 2–20: Prevalence of VL in US ‘Other’ with cataracts (2000) 41Table 2–21: Relative risk of developing VL from cataracts, by race 42Table 2–22: Prevalence of VL in whites with cataract, by age 42Table 2–23: Prevalence of VL in non- whites with cataract, by age 43


Table 2–24: Prevalence of cataract-induced VL in Canadian AVM, by age 44Table 2–25: Prevalence of eye diseases by ethnicity, US, 2000 44Table 2–26: Causes of VL by ethnicity 45Table 2–27: Prevalence of VL, by ethnicity and cause, US, 2000 45Table 2–28: Prevalence (%) of VL within specified diseases, by ethnicity 45Table 2–29: Relative risk of VL by eye disease, non-whites to whites 46Table 2–30: Prevalence of eye diseases in whites 46Table 2–31: Fraction of whites with each eye disease who have VL, by age and gender

(%) 47Table 2–32: prevalence of VL within disease groups, non-whites 47Table 2–33: Prevalence of VL in AVM 48Table 2–34: Under corrected VL in AVM 49Table 2–35: Prevalence of VL from DR within diabetic AVM groups 49Table 2–36: Prevalence of diabetes in AVM population, 2005 (%) 49Table 2–37: Estimated prevalence of DR-induced VL in AVM 50Table 2–38: Prevalence of VL in AVM by age, gender and disease 51Table 2–39: Prevalence of VL, by cause and ethnicity, 2007 52Table 2–40: All vision loss, by age, gender and ethnicity, 2007 56Table 2–41: Cataract vision loss, by age, gender and ethnicity, 2007 57Table 2–42: DR vision loss, by age, gender and ethnicity, 2007 58Table 2–43: Glaucoma vision loss, by age, gender and ethnicity, 2007 59Table 2–44: AMD vision loss, by age, gender and ethnicity, 2007 60Table 2–45: RE/Other vision loss, by age, gender and ethnicity, 2007 61Table 3–1: Total expenditure on certain eye procedures, 2004-05 64Table 3–2: Drug expenditure on nervous system and sense organ disorders, 1998 64Table 3–3: Expenditure on nervous system and sense organ disorders (1998) 64Table 3–4: Frequency of selected hospital procedures (2001) 65Table 3–5: Rebates for certain ophthalmological procedures in Ontario (2006) 65Table 3–6: Average treatment costs for neovascular AMD (2005) 66Table 3–7: Estimated VL health system expenditure (top down), 2007 67Table 4–1: Estimated AWE, by age and gender, 2007 70Table 4–2: percentage of population employed, by age and gender 70Table 4–3: Provincial sales taxes 73Table 4–4: Income sources (CNIB) 74Table 4–5: VL-related social security payments and beneficiaries 75Table 4–6: Excess usage of social security payments 75Table 4–7: Annual direct AMD non-medical related utilisation costs per person (2005$)77Table 4–8: Canes/accessories for the blind (2000-01$) 79


Table 4–9: Writing and stationery items (2000-01$) 81Table 4–10: Talking time pieces (2000-01$) 82Table 4–11: Sunglasses with non-corrective lenses (2000-01$) 82Table 4–12: Hand held magnifiers (2000-01$) 82Table 4–13: Other stationery (2000-01$) 83Table 4–14: Large button telephones (2000-01$) 84Table 4–15: Summary of aids and devices (2000-01$) 85Table 4–16: Estimates of additional aids and devices 86Table 4–17: Summary of other financial costs of VL, 2007 86Table 5–1: Value of a statistical life in Canadian studies ($ million) 89Table 5–2: Estimated years of healthy life lost due to disability (YLD), 2007 (DALYs) 90Table 5–3: Years of life lost due to premature death (YLL) due to VL, 2007 90Table 5–4: Net cost of lost wellbeing, $million, 2007 92Table 6–1: VL, total costs by type of cost and bearer, 2007 93


GLOSSARY OF ACRONYMSAMD age related macular degenerationAVM Aboriginal and Visible MinoritiesAWE Average Weekly EarningsBMES Blue Mountains Eye StudyCACS Comprehensive Ambulatory Classification SystemCCHS Canadian Community Health SurveyCCTV closed circuit televisionCERA Centre for Eye Research AustraliaCIHI Canadian Institute for Health InformationCNIB CNIBCOS Canadian Ophthalmological SocietyDALY Disability Adjusted Life YearDR diabetic retinopathyDWL deadweight lossEDPRG Eye Disease Prevalence Research GroupGST Goods and Services TaxHST Harmonized Sales TaxICES Institute for Clinical Evaluative SciencesMVIP Melbourne Visual Impairment ProjectNGS National Grouping SystemNHEX National Health Expenditure databaseNPHS National Population Health SurveyPALS Participation and Activity Limitation SurveyPOAG Primary Open Angle GlaucomaPST Provincial Sales TaxesRE refractive errorUK United KingdomUS United StatesUV ultravioletVL vision lossVSL(Y) Value of a Statistical Life (Year)

i


EXECUTIVE SUMMARYThis report estimates the cost of vision loss (VL) in Canada, utilising a prevalence-based approach. Direct health system expenditures on visually impairing eye conditions are included, as well as other financial costs (such as productivity losses) and the value of the loss of healthy life (measured in Disability Adjusted Life Years or DALYs).

Prevalence of vision loss

A variety of data sources were used to construct a model of Canadian VL by age, gender, ethnicity, severity and type. In 2007, there were an estimated 816,951 Canadians with VL.

Of this total, 780,534 (95.5%) were white and 36,416 (4.5%) were Aboriginals and Visible Minorities (AVM).

‘Refractive Error and Other’ is the main source of VL for the white population (68.1% of the total), and cataract is the main cause of VL in AVM (36.1% of the total)1.

For whites, the second largest source of VL is cataract (15.5%) and, for the AVM population, DR is the second largest source (24.4% of the total).

AVM have lower prevalence of VL for all diseases other than DR, largely due to lower prevalence of eye diseases at equivalent ages to whites, a younger age profile, and less likelihood of developing VL once they have contracted a given eye disease.

PREVALENCE OF VL, BY CAUSE AND ETHNICITY, 2007All ethnicities White AVM

Number % total Number % total Number % totalAMD 89,241 10.9% 84,641 10.8% 4,380 12.0%Cataract 133,836 16.4% 120,685 15.5% 13,151 36.1%DR 29,920 3.7% 20,992 2.7% 8,928 24.5%Glaucoma 24,937 3.1% 22,565 2.9% 2,373 6.5%RE/Other 539,236 66.0% 531,650 68.1% 7,586 20.8%

All VL 817,171 100.0% 780,534 100.0% 36,417 100.0%

1 ‘Other’ represents minor diseases – ie, not the ‘big five’ of cataract, diabetic retinopathy (DR), age-related macular degeneration (AMD), glaucoma, or refractive error (RE). ‘Other’ diseases have not been the subject of population eye health studies.

ii


PREVALENCE RATES OF VL, BY CAUSE AND ETHNICITY, 2007

0.3% 0.4%0.1% 0.1%

1.6%

2.5%

0.3%0.5%

0.1% 0.1%

2.0%

3.0%

0.1%0.2% 0.1% 0.0% 0.1%

0.6%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

AMD Cataract DR Glaucoma RE/Other All VI

Prev

alen

ce (%

)

All races White AVM

The prevalence of VL is projected to almost double in absolute numbers, and increase from 2.5% of the population in 2007 to 4.0% in 2032.

VL affects women more than men, reflecting greater longevity in females. In 2007, females accounted for 58.4% of VL; by 2032, this will have fallen slightly to 56.3%.

Despite the fact that the AVM share of the total population is rapidly increasing, the increase in this group’s share of VL at the end of the projection period is less than commensurate, partly due to AVM having a considerably younger age profile than the white population with no substantial aging over the forecast period.

iii


PREVALENCE OF VL, BY CAUSE, 2007-2032

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

2031

2032

Prev

alen

ce (%

)

All VI Cataracts DR

Glaucoma AMD RE/Other

Costs

In 2007, the financial cost of VL was $15.8 billion. Of this:

$8.6 billion (54.6%) was direct health system expenditure;

$4.4 billion (28.0%) was productivity lost due to lower employment, absenteeism and premature death of Canadians with VL;

$1.8 billion (11.1%) was the DWL from transfers including welfare payments and taxation forgone;

$0.7 billion (4.4%) was the value of the care for people with VL; and

$305 million (1.9%) was other indirect costs such as aids and home modifications and the bring-forward of funeral costs.

Additionally, the value of the lost wellbeing (disability and premature death) was a further $11.7 billion.

iv


VL, TOTAL COSTS BY TYPE OF COST AND BEARER, 2007

Individuals Family/Friends

Federal Government

Provincial Governments Employers Society/

Other Total

Burden of disease 11,710 0 0 0 0 0 11,710.4Health system costs 1,499 0 388 5,670 0 1,081 8,637.9Productivity costs 2,847 0 886 619 80 0 4,431.4Carer costs 0 413 218 0 0 62 692.8Other Indirect costs 61 62 0 61 61 61 304.9Deadweight losses 0 0 0 0 0 1,757 1,757.0Transfers -917 0 917 0 0 0 0Total financial costs 3,490 474 2,409 6,350 141 2,960 15,824Total costs including burden of disease 15,200 474 2,409 6,350 141 2,960 27,534

Burden of disease 14,334 0 0 0 0 0 14,334Health system costs 1,835 0 475 6,941 0 1,323 10,573Productivity costs 3,485 0 1,084 757 98 0 5,424Carer costs 0 505 267 0 0 76 848Other Indirect costs 74 76 0 74 74 74 373Deadweight losses 0 0 0 0 0 2,151 2,151Transfers -1,122 0 1,122 0 0 0 0Total financial costs 4,272 581 2,948 7,773 172 3,624 19,370Total costs including burden of disease 18,606 581 2,948 7,773 172 3,624 33,704

Total cost ($ million)

Cost per person with visual impairment ($)

In per capita terms, this amounts to a financial cost of $19,370 per person with VL per annum. Including the value of lost wellbeing, the cost is $33,704 per person per annum.

FINANCIAL COSTS OF VL, BY TYPE OF COST (% TOTAL)

Health System Costs54.6%

Productivity Costs28.0%

Carer Costs4.4%

Indirect Costs1.9%

DWL11.1%

Individuals with VL bear 22.1% of the financial costs, and their families and friends bear a further 3.0%. Federal government bears 15.2% of the financial costs (mainly through taxation revenues forgone and welfare payments). Provincial governments bear 40.1% of the costs, reflecting the nature of Canada’s Federal system, while employers bear 0.9% and the rest of society bears the remaining 18.7%.

v


If the burden of disease (lost wellbeing) is included, individuals bear 55.2% of the costs and Provincial governments bear 23.1% while the Federal government bears a lesser 8.7%, with family and friends 1.7%, employers 0.5% and others in society 10.8%.

FINANCIAL COSTS OF VL, BY BEARER (% TOTAL)

Individuals22.1%

Family/Friends3.0%

Federal Government15.2%

Provincial Governments

40.1%

Employers0.9%

Society/Other18.7%

Finally, an important finding from this analysis was the observation that, for an advanced Western nation, Canada has a serious deficiency in eye health data. CNIB’s Health Economic Statement (http://www.costofblindness.org/media/health-state.asp) observes that, with respect to blindness and vision loss, there is ‘strong argument for saying that Canada has the worst record of supporting research of all the G8 countries’. The importance of good eye health to Canadians is shown from survey data in the same document revealing that two-thirds of Canadians would cash in all their savings or sell everything they owned to save their eyesight. With a rapidly aging population, it is high time for a Canadian population eye health study to monitor incidence, prevalence and morbidity outcomes and economic impacts more robustly in the future.

Access Economics12 December 2008

vi

http://www.costofblindness.org/media/health-state.asp


1. BACKGROUNDThis report estimates the cost of vision loss (VL) in Canada, utilising a prevalence-based approach. Direct health system expenditures on visually impairing eye conditions are included, as well as other financial costs (such as productivity losses) and the value of the loss of healthy life (measured in Disability Adjusted Life Years or DALYs).

1.1 DEFINITIONS

Statistics Canada (2004a) reported that the majority (51%) of Canadians had some form of ‘vision problem’ in 2003, while Statistics Canada (2001) found that that 2.5% had a ‘visual disability’. A ‘vision problem’ is not considered a visual disability if it can be corrected (eg, with glasses or contact lenses for refractive error - RE). Figure 1-1 shows the differences between the two categories within age and gender cohorts for Canadian seniors (people aged 65 years or older), where prevalence is understandably higher (70%-90%).

FIGURE 1-1: VISION PROBLEMS AMONG CANADIAN SENIORS (% OF AGE GROUP)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

All S

enio

rs

65 to

69

70 to

74

75 to

79

80+

Years of age

Prev

alen

ce (%

)

Male, uncorrected

Male, corrected

Female, uncorrected

Female, corrected

Source: Statistics Canada (2004a).

In this report, the term ‘vision loss’ rather than ‘visual disability’ will be used.

Vision loss is broadly defined as a limitation in one or more functions of the eye or visual system, most commonly impairment of visual acuity (sharpness or clarity of vision), visual fields (the ability to detect objects to either side or above or below the direction in which the person is looking) and colour vision.

1


Normal vision is recorded as 20/20 in the Imperial system used in Canada (6/6 in metric), which means that a person can see at 20 feet (6 meters) what a person with normal vision can see at 20 feet. Degrees of VL are measured similarly, where the first number in the measure is the furthermost distance at which the person can clearly see an object and the second number is the distance at which a person with normal vision could see the same object. For example, 20/40 vision means that the person can clearly see at 20 feet (but not more) an object that a person with unimpaired vision could see at 40 feet (but not more).

The Blind Persons Regulations, Consolidated Regulations of Canada 1978 (Chapter 371A)2

states that ‘a person shall be considered legally blind whose central acuity does not exceed 20/200 in the better eye with correcting lenses’. This means that if a person with their glasses on can see the big 'E' on a Snellen eye chart, but none of the other optotypes, for legal purposes they are considered blind and are eligible for certain government tax credits as well as concessions from some retailers and other service providers. The Canadian definition of legal blindness also includes ‘or a visual field extent of less than 20 degrees in diameter horizontally’.

1.1.1 Better eye, worse eye

VL can differ from one eye to the other (asymmetrical vision loss). As a result of this, prevalence rates can be reported for either the better or the worse eye in terms of the extent of vision loss. Asymmetrical vision loss, however, has little impact on function or disability, and indeed, it is often only when vision loss becomes bilateral that it is identified and treated. When reporting prevalence rates, better eye measures would provide conservative estimates, while worse eye measures may tend to overstate costs and impairment.

In this study, the conservative approach has thus been to report VL prevalence for the better eye.

1.1.2 Severity definitions used in this report

Best corrected visual acuity (BCVA) is defined as the best possible vision a person can achieve with corrective lenses measured in terms of Snellen lines on an eye chart.

Common definitions for visual acuity used in Canada (Jutai et al, 2006), and in this report are as follows.

Blindness is defined as BCVA of 20/200 or worse (≤6/60) in the better-seeing eye.

Vision loss is defined as BCVA less than 20/40 (<6/12) in the better-seeing eye. It thus comprises blindness and low vision.

Low vision is defined as VL that is not blindness, and is categorized as: mild VL – BCVA worse than 20/40 (<6/12) but better than or equal to 20/60

(6/18) in the better-seeing eye; and moderate VL – BCVA worse than 20/60 (<6/18) but better than or equal to

20/200 (6/60) in the better-seeing eye.

2 http://www.amdcanada.com/template.php?section=4&lang=eng&subSec=3d&content=4_3 (accessed 28 March 2008)

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1.2 MAIN CAUSES OF IMPAIRMENT

1.2.1 Age related macular degeneration (AMD)

AMD is an incurable eye disease and a leading cause of blindness in elderly people. The macula is the part of the retina that enables central vision and the seeing of fine detail. Damage to the macula is characterized by a ‘black spot’ – losing the centre of the picture. In ‘early AMD,’ small yellow deposits called drusen form under the macula. Vision is usually lost with more advanced stages of AMD. There are two types of ‘late AMD’.

Dry (geographic/atrophic): In around one third of cases of late AMD, the macula thins. Vision loss is directly related to the location and amount of retinal thinning, but the progress of dry AMD is slower than that of the ‘wet’ type. There is no known treatment or cure for the ‘dry’ type of AMD.

Wet (exudative/neovascular): Two thirds of those with late AMD have this type. Abnormal blood vessels grow under the retina and macula; these vessels bleed and leak fluid, causing the macula to bulge or lift up. Vision loss may be rapid and severe. Thermal laser surgery may be used in the early stages and may prevent severe eye damage for some patients. Photodynamic laser therapy with verteporfin provides an improvement over thermal laser treatment, but does not preclude recurrence, so that at best it slows the rate of vision loss.

Causes of AMD are not well understood, but may include age and a genetic component, with family history increasing the risk of AMD three to four times. People who smoke are twice as likely to develop AMD. People who have a family history of AMD and smoke are up to 144 times more likely to develop the disease. In summary, in most cases there is no effective prevention of or treatment for AMD. Because AMD is painless, usually progresses slowly and generally occurs in one eye first, it may be difficult to self-detect AMD early (Access Economics, 2006).

Current treatments for AMD, such as photodynamic therapy, are limited both in terms of their ability to retard progression of disease and thus loss of vision, as well as only being effective for a proportion of people with neovascular AMD. However, emerging therapies have the potential to enhance the efficacy and coverage of treatment options for people with AMD.

Anti-angiogenesis is a treatment that aims to block the process of angiogenesis in neovascular AMD. Theoretically this will retard progression of neovascular AMD and reduce its recurrence. Anti-angiogenesis treatments include:

o Pegaptanib (Macugen). This requires six weekly injections in the affected eye over a period of at least two years. Pegaptanib has been shown to retard the progression of wet AMD.

o Ranibizumab (Lucentis) is new treatment, shown to be effective in both retarding the progression of wet AMD and restoring some vision to a significant number of patients.

o Bevacizumab (Avastin) has been fairly widely used ‘off label’ for AMD, although it is not indicated for this condition. As yet, no extensive head to head clinical trials have been conducted comparing bevacizumab and ranibizumab with respect to both safety and efficacy.

Figure 1-2 shows the prevalence of AMD by gender among whites, based on an international meta-analysis of these ethnicities by the Eye Disease Prevalence Research Group – EDPRG (Congdon et al, 2004a). Details of the source studies used by the EDPRG are provided in

3


Appendix A, and include studies from the United States (US), West Indies, Australia and the Netherlands.

FIGURE 1-2: PREVALENCE OF AMD BY AGE AND GENDER IN WHITES (% POPULATION)

0%

2%

4%

6%

8%

10%

12%

14%

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85+

Pre

vale

nce

(%)

Years of age

White Female

White Male

Note: See Appendix A for underlying data.Source: Congdon et al (2004a) and Access Economics (2006).

1.2.2 Cataract

A cataract is a cloudy area in the eye's lens that forms when proteins clump together. Over time, the cataract may grow larger and cloud more of the lens, making it hard to see. The most common symptoms are blurry vision, problems with light, ‘faded’ colours, double or multiple vision and the need for frequent changes in glasses or contact lenses.

The four main types of cataract are age related (most common), congenital, secondary (eg, due to diabetes or steroid use) and traumatic (eg, due to eye injury). Causes of cataract are still uncertain, although age, smoking, diabetes and ultraviolet (UV) exposure have been shown to increase risk. Detection is through an eye examination including a visual acuity test (eye chart test) and pupil dilation (where the pupil is widened with eye drops to allow the eye care professional to see more of the lens and look for other eye problems).

Cataract surgery may be indicated to improve vision, with the cloudy lens removed and replaced with a substitute lens. Surgery is safe and very effective, with almost all people having better vision and improved quality of life afterward, and only a small percentage experiencing complications such as infection, bleeding or inflammation. Cataract surgery is generally performed as same-day surgery without general aesthetic, with a six week total recovery period.

4


Figure 1-3 shows the prevalence of cataract by age, gender and ethnicity.

FIGURE 1-3: PREVALENCE OF CATARACT BY AGE AND GENDER IN WHITES (% POPULATION)

0%

10%

20%

30%

40%

50%

60%

70%

80%

40-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80+

Pre

vale

nce

(%)

Years of age

White Female

White Male


5


Taylor (2001) shows that, in Australia, rates of cataract surgery double with each decade of life. Figure 1-4 shows rate of cataract by age group. While younger people have lower rates of cataract surgery than older cohorts, because there are fewer people in the oldest cohorts3, the average age of cataract surgery in Canada is 74 years4. Conversely, while surgery rates increase in older cohorts, prevalence of cataract increases faster still, leading to higher rates of VL in the oldest of the old.

FIGURE 1-4: RATES OF CATARACT SURGERY BY AGE

Source: Taylor (2001).

1.2.3 Diabetic retinopathy

Diabetic retinopathy (DR) is a complication of diabetes mellitus, usually affecting both eyes, wherein microaneurysms develop on the tiny blood vessels inside the retina. As the disease progresses, some blood vessels that nourish the retina are blocked, causing vision loss through either proliferative retinopathy or macular edema.

Left: Normal vision. Right: The same scene as it might be viewed by a person with DR.

DR often has no early symptoms. Sometimes the person sees specks of blood, or spots, ‘floating’ in their vision. Diagnosis can be made via a visual acuity test (eye chart test), dilated eye examination, retinal photography and/or fluorescein angiogram. Macular edema is treated with focal laser surgery, which stabilizes vision and reduces the risk of vision loss by 50%.

3 There are over ten times as many Canadian septuagenarians as nonagenarians.

4 Canadian Ophthalmological Society, correspondence of 11 April 2008.

6


Proliferative retinopathy is treated with scatter laser surgery that, while it can worsen peripheral, colour and/or night vision, can save the rest of a person’s sight. If bleeding is severe and persistent, a vitrectomy may be necessary, where blood and gel are removed from the centre of the eye and replaced with a salt solution, under local or general anesthetic.

Although both laser treatment and vitrectomy can effectively reduce vision loss they do not cure DR, and the patient remains at risk for new bleeding. Multiple treatments may be necessary.

To prevent the onset and progression of DR (and the need for surgery), people with diabetes should control their levels of blood sugar, blood pressure and blood cholesterol. Early diagnosis and treatment can prevent almost all severe vision loss. The earlier treatment is received, the more likely it is to be effective. Prevalence is shown in Figure 1-5.

7


FIGURE 1-5: PREVALENCE OF DR BY AGE AND GENDER IN WHITES (% POPULATION)

0%

1%

2%

3%

4%

5%

6%

7%

8%18

-39

40-4

9

50-6

4

65-7

4

75+

Pre

vale

nce

(%)

Years of age

White Female

White Male


1.2.4 Glaucoma

Glaucoma is a group of diseases that, while initially asymptomatic, can damage the eye's optic nerve and result in blindness. The optic nerve comprises nerve fibers that connect the retina with the brain. In the front of the eye is a space called the anterior chamber – clear fluid flows in and out of this space, leaving the chamber at the angle where the cornea and iris meet. When the fluid reaches the angle, it flows through a spongy meshwork, like a drain, and leaves the eye.

Primary open-angle glaucoma (POAG), the most common type, occurs when, for unknown reasons, the fluid passes too slowly through the meshwork drain. As the fluid builds up, the pressure inside the eye rises. Unless the pressure at the front of the eye is controlled, it can damage the optic nerve and cause vision loss. Although people can see objects clearly in front of them, they miss things to the side and out of the corner of their eye. Peripheral vision may deteriorate without treatment, like looking through a tunnel, until there is no vision left.

Left: Normal vision. Right: The same scene as it might be viewed by a person with glaucoma.

8


Other less common types of glaucoma include:

Closed-angle glaucoma, in which the fluid at the front of the eye is blocked from reaching the angle, resulting in a sudden increase in pressure, pain, redness and blurred vision. Immediate (medical emergency) laser surgery is required to clear the blockage and protect sight.

Congenital glaucoma, occurring in children born with defects in the angle of the eye that slow fluid drainage, causing cloudy eyes, sensitivity to light and excessive tearing. Prompt surgery provides an excellent chance of saving vision.

Secondary glaucoma, which develops as a complication of other medical conditions, such as surgery, advanced cataract, eye injuries, certain eye tumours, uveitis (eye inflammation), diabetes or the use of corticosteroid drugs. Treatment includes medicines and laser or conventional surgery.

Increased risk for glaucoma occurs with age, family history and ethnicity. Glaucoma is detected through an eye examination including visual acuity, visual field, tonometry and optic nerve examination.

Although there is no cure for glaucoma, early diagnosis and treatment may help protect eyes against serious vision loss and blindness. Treatments include:

Eye drops (very common) – eye drops taken several times a day can lower pressure by helping fluid drain from the eye or causing the eye to make less fluid. Rare side effects include headaches or eye irritation.

Laser surgery (‘laser trabeculoplasty’) – helps fluid drain from the eye by burning holes in the meshwork with a high-energy light beam. The effects of laser surgery wear off so that, after two years, the pressure increases again in more than half of all patients. Repeating laser surgery is often not useful.

Conventional surgery – can make a new opening for the fluid to leave the eye. Such surgeries are often performed after eye drops and laser surgery have failed to control pressure. Surgery is around 80-90% effective at lowering pressure. However, if the new drainage opening closes, a second operation may be needed. Conventional surgery works best in the absence of other previous eye surgery.

Possible side effects of glaucoma surgery include cataract, inflammation or infection inside the eye, and swelling of blood vessels behind the eye – all of which are treatable. In some cases, vision may worsen after surgery.

9


FIGURE 1-6: PREVALENCE OF GLAUCOMA BY AGE AND GENDER IN WHITES(% POPULATION)

0%

1%

2%

3%

4%

5%

6%

7%

8%40

-49

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80+

Pre

vale

nce

(%)

Years of age

White Female

White Male


1.2.5 Refractive error (RE) and other causes of vision loss

A large part of remaining vision loss is caused by RE. Less common conditions such as neuro-ophthalmic disorders, retinitis pigmentosa and other retinal conditions account for the remaining prevalence of VL and blindness.

As noted above, RE is the most frequent yet most easily correctible source of eye problems in Canada, occurring when optical defects result in light not focusing properly on the retina. Myopia (near-sightedness with blurry distant vision) and hyperopia (farsightedness with close objects blurry) are the most well-known RE. Most infants have some degree of hyperopia, although vision usually normalizes by six years of age. Most myopia occurs later during adolescence. The extent of RE is measured in diopters. Other common forms of REs include astigmatism (uneven focus) and presbyopia (age related problem with near focus).

Myopia is a very common disorder. Prevalence is greater in women through age 60, after which rates become more comparable between genders. Myopia affects more whites than other races, and is generally less frequent with age, Hyperopia is less common, but prevalence generally increases with age. It is also most frequent in Whites. Prevent Blindness America (2002:12)

Almost all RE can be corrected by eyeglasses or contact lenses. Refractive surgery is another alternative treatment, but one not without risk.

Figure 1-7 and Figure 1-8 highlight that RE is less common in males than females. Myopia tends to decrease with age, whereas hyperopia increases. (Older black males have

10


significantly less of either condition than other groups – hyperopia is over 18 times more prevalent in older white females than equally aged black males.)

FIGURE 1-7: PREVALENCE OF MYOPIA BY AGE AND GENDER IN WHITES (% POPULATION)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

40-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80+

Pre

vale

nce

(%)

Years of age

White Female

White Male

Note: See Appendix A for underlying data.Source: Congdon et al (2004a) and Access Economics (2006). Note: Myopia = (-1.00 diopters or worse).

FIGURE 1-8: PREVALENCE OF HYPEROPIA BY AGE AND GENDER IN WHITES (% POPULATION)

0%

5%

10%

15%

20%

25%

30%

40-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80+

Pre

vale

nce

(%)

Years of age

White Female

White Male

Note: See Appendix A for underlying data.Source: Congdon et al (2004a) and Access Economics (2006). Note: Hyperopia = (+3.00 diopters or worse).

11


RE is the most common source of VL in Western countries; Figure 1-9 and Figure 1-10 show that population-based eyes studies demonstrate little variance in the prevalence of hyperopia and myopia in white populations across countries with similar cultures and income levels.

12


FIGURE 1-9: PREVALENCE OF HYPEROPIA ACROSS COUNTRIES BY AGE, GENDER AND SOURCE STUDY (% POPULATION)

Prevalence of hyperopia of +3 diopters or greater in white persons (A) and black and Hispanic persons (B). BES= Baltimore Eye Study; BDES=Beaver Dame Eye Study; BMES=Blue Mountains Eye Study; RS=Rotterdam Study; Melbourne VIP = Melbourne Visual Impairment Project; Proyecto VER=Vision Evaluation and Research.

Source: Congdon et al (2004b).

13


FIGURE 1-10: PREVALENCE OF MYOPIA ACROSS COUNTRIES BY AGE, GENDER AND SOURCE STUDY (% POPULATION)

Prevalence of myopia of -1 diopter or less in white persons (A) and black and Hispanic persons (B). BES= Baltimore Eye Study; BDES=Beaver Dame Eye Study; BMES=Blue Mountains Eye Study; RS=Rotterdam Study; Melbourne VIP = Melbourne Visual Impairment Project; Proyecto VER=Vision Evaluation and Research.

Source: Congdon et al (2004b).

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2. ESTIMATING PREVALENCEPrevalence approaches to cost estimation, for a given health condition, measure the number of people with that given condition (in this case VL) in a base period (in this case calendar year 2007) and the costs associated with treating them, as well as other financial and non-financial costs (productivity losses, carer burden, loss of quality of life) in that year, due to the condition. This report adopts a prevalence approach to cost measurement rather than an incidence approach, as the data sources lend themselves to utilization of such an approach, and for consistency with other studies of the cost of VL (eg, in Australia, Japan and the US).

Figure 2-11 depicts the difference between a prevalence approach (areas A+B+C in Figure2-11) and an incidence approach, the latter estimating the present value of the lifetime costs of new cases of VL in 2005 (area C plus the present value of C* in Figure 2-11). Consider person A, who first experienced VL and its impacts in 1990 and continued to experience them until death in 2005. This person would be included in a prevalence approach (but not in an incidence approach), although only the costs incurred in 2005 would be included (ie, A but not A*, where A includes the present value of premature mortality costs if the death was premature). Person B developed VL during the late 1990s and experiences impairment and its impacts through to 2008 (with costs of B+B*+B**, shaded in blue); she also would be counted (but only costs of B) using a prevalence approach, but not using an incidence approach. Person C (shaded in red) is newly diagnosed with VL in 2005 and his costs in 2005 (C) would be included in a prevalence approach but not future costs (C*).

FIGURE 2-11: PREVALENCE AND INCIDENCE APPROACHES TO COST MEASUREMENT

1990 2006 2010

To estimate the number of cases of VL in the population, epidemiological data on prevalence rates are applied to population data. Ideally for projections, the number of cases of VL should be stratified by gender, age, ethnicity, severity (mild and moderate VL and blindness) and cause (AMD, cataract, DR, glaucoma, RE and ‘other’). A first step is thus to assimilate population data by gender, age and ethnicity, for 2007 and subsequent years (next section).

2.1 POPULATION DATA

2.1.1 Age, gender and growthStatistics Canada (2006) reports that Canada has the second youngest population in the G85. In 2006, around one in seven Canadians (13.7%)6 was aged 65 years or older and Statistics Canada (2006) projects that by 2031 these ‘senior citizens’ will account for around

5 The Group of Eight represents the world’s largest industrialised economies: US, UK, Russia, France, Germany, Italy, Japan and Canada.

6 Statistics Canada 2006 Census Online, www.statcan.ca (Cat, No, 97-551-XCB2006005).

15


one quarter of the population (Figure 2-12)7. Thus, as many eye diseases are age related, the overall prevalence of VL will increase over the medium term.

These projections were compiled using data from the 2001 Census. Although 2006 Census data have recently become available for that year, population projections by five year age-gender cohorts are not yet provided by Statistics Canada from the 2006 Census. Accordingly, this report uses Statistics Canada’s existing projections8.

FIGURE 2-12: CANADIAN POPULATION BY AGE (’000 PEOPLE), 2006 AND 2031

0

500

1,000

1,500

2,000

2,500

3,000

0–4

5–9

10–1

4

15–1

9

20–2

4

25–2

9

30–3

4

35–3

9

40–4

4

45–4

9

50–5

4

55–5

9

60–6

4

65–6

9

70–7

4

75–7

9

80–8

4

85–8

9

90–9

4

95–9

9

100+

Per

sons

('00

0)

Age group (years)

20062031

Source: Statistics Canada (2006).

7 Statistics Canada (2006) makes projections for the entire Canadian population out to 2031, with special data requests available out to 2056. Projections presented here are from the medium growth, medium immigration scenario (scenario 3).

8 This also enables consistency with the other vision health projections (Buhrmann, forthcoming).

16


TABLE 2–1: CANADIAN POPULATION PROJECTIONS, MALES (‘000), 2006-2031, SELECTED YEARS

Age group 2006 2007 2008 2009 2010 2011 2016 2021 2026 2031 0–4 868 872 875 876 879 884 914 931 929 913 5–9 943 927 917 914 911 911 928 960 979 980

10–14 1,068 1,054 1,037 1,020 1,002 982 952 971 1,004 1,026 15–19 1,109 1,121 1,130 1,131 1,123 1,113 1,029 1,001 1,022 1,057 20–24 1,153 1,154 1,152 1,153 1,161 1,171 1,176 1,095 1,069 1,092 25–29 1,125 1,138 1,152 1,165 1,173 1,178 1,199 1,206 1,129 1,105 30–34 1,122 1,128 1,139 1,154 1,169 1,183 1,238 1,263 1,275 1,203 35–39 1,183 1,181 1,179 1,175 1,173 1,172 1,236 1,294 1,322 1,338 40–44 1,357 1,322 1,279 1,241 1,217 1,210 1,202 1,268 1,329 1,360 45–49 1,335 1,353 1,372 1,386 1,384 1,362 1,220 1,216 1,284 1,346 50–54 1,170 1,206 1,241 1,268 1,294 1,321 1,350 1,215 1,214 1,282 55–59 1,029 1,038 1,054 1,081 1,114 1,144 1,295 1,327 1,198 1,199 60–64 778 833 879 919 958 991 1,107 1,256 1,291 1,171 65–69 591 613 641 670 699 732 936 1,050 1,197 1,235 70–74 490 490 495 504 515 531 662 852 964 1,105 75–79 387 396 402 405 407 409 449 567 736 841 80–84 249 255 263 270 278 286 307 344 440 579 85–89 115 123 131 138 143 148 175 192 220 288 90–94 38 39 40 41 44 48 64 77 87 103 95–99 7 8 8 8 9 9 12 17 21 24 100+ 1 1 1 1 1 1 1 2 2 3Total 16,116 16,251 16,386 16,520 16,654 16,787 17,451 18,102 18,711 19,249

Source: Statistics Canada (2006).

17


TABLE 2–2: CANADIAN POPULATION PROJECTIONS, FEMALES (‘000), 2006-2031, SELECTED YEARS

Age group 2006 2007 2008 2009 2010 2011 2016 2021 2026 20310–4 829 832 834 834 835 841 868 885 883 8685–9 900 885 876 873 871 870 883 912 931 931

10–14 1,017 1,001 986 970 954 934 907 921 953 97315–19 1,056 1,067 1,075 1,075 1,067 1,058 978 952 968 1,00120–24 1,100 1,103 1,102 1,105 1,115 1,124 1,128 1,051 1,028 1,04625–29 1,101 1,115 1,129 1,141 1,148 1,152 1,178 1,186 1,113 1,09430–34 1,101 1,110 1,121 1,138 1,154 1,172 1,225 1,255 1,268 1,20035–39 1,168 1,165 1,162 1,157 1,156 1,155 1,227 1,283 1,317 1,33340–44 1,342 1,309 1,268 1,232 1,207 1,199 1,188 1,263 1,321 1,35745–49 1,337 1,351 1,366 1,376 1,373 1,350 1,211 1,203 1,278 1,33850–54 1,194 1,229 1,260 1,284 1,306 1,330 1,345 1,211 1,204 1,28155–59 1,054 1,067 1,087 1,117 1,152 1,183 1,320 1,336 1,207 1,20260–64 806 863 912 956 1,000 1,037 1,165 1,302 1,321 1,19765–69 637 660 689 718 748 782 1,007 1,134 1,270 1,29270–74 554 555 560 571 583 600 739 955 1,080 1,21475–79 491 495 497 497 497 498 544 674 875 99680–84 389 392 395 397 402 406 417 460 576 75385–89 228 241 253 263 269 274 291 303 341 43290–94 99 102 104 108 114 121 148 160 170 19695–99 26 27 29 30 32 33 42 52 58 63100+ 4 4 4 4 4 5 6 8 10 11

Total 16,431 16,571 16,709 16,848 16,986 17,123 17,815 18,507 19,172 19,780Source: Statistics Canada (2006).

18


2.1.2 EthnicityCanada is a racially diverse country. While ‘white’ Europeans make up the great majority of the population (82%), the 2001 Census data showed that Aboriginals (North American Indians, Metis and Inuit) comprised 5% while ‘Visible Minorities’ comprised 13% (East Asians – mainly Chinese), South Asians – mainly Indians, and blacks and other migrant groups9 (Table 2–3).

TABLE 2–3: ETHNIC COMPOSITION OF CANADIAN POPULATION (% TOTAL), 2001Ethnicity % of populationAboriginal 4.6%Chinese and other East Asian 4.1%South Asian 3.1%Black 2.2%Other 4.1%White 81.7%

Source: Statistics Canada, topic-based tabulations 95F0363XCB2001004 and 97F0011XCB2001003.Note: Shares may not sum to 100% due to rounding.

While at present whites outnumber Aboriginal and Visible Minorities (AVM) by four to one, by the end of the projection period (2032) whites only outnumber AVM by two to one (Figure 2-13)10.

FIGURE 2-13: WHITE AND AVM POPULATIONS, 2006-2032 (% TOTAL)

0

10

20

30

40

50

60

70

80

90

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

2031

2032

Perc

enta

ge o

f Can

adia

n po

pula

tion

White Aboriginals and Visible Minorities

9 For consistency with Statistics Canada data, the term ‘Aboriginal’ is used in this report and ‘North American Indians’ is used rather than ‘First Nations’. For the same reason, ‘black’ is used instead of Caribbean Canadian or African Canadian, and ‘white’ is used instead of European or Caucasian.

10 Statistics Canada makes projections for the population as a whole to 2031, and by race to 2017. Access Economics has extended these trends to 2032, as that represents 25 years after the base year (2007)

19


Source: Statistics Canada (2005a, 2005b, 2006).

Statistics Canada (2005a and 2005b) makes projections for Aboriginal and, separately, Visible Minorities populations to 2017. However, both populations’ shares of the Canadian total have been growing in a fairly linear manner – due to high migration (Visible Minorities) and high birth rates (Aboriginal peoples). Out to 2017, official projections maintain these trends (Figure 2-14). Access Economics has extended the same trends from 2018 through to 2032.

FIGURE 2-14: ABORIGINALS AND VISIBLE MINORITIES, 1981-2017, SELECTED YEARS (% POPULATION)

0%

5%

10%

15%

20%

25%

1981 1986 1991 1996 2001 2006 2011 2017

Shar

e of

pop

ulati

on, b

y ra

ce

Visible Minorities (%) Aboriginal Peoples

Trend Trend

In Canada, demographic aging is less of an issue for non-white populations. Aboriginals in particular have a young age profile (over 60% are under 30 years old), although the East Asian population is fairly evenly spread across all age groups (Figure 2-15 and Figure 2-16).

Statistics Canada (2005b) publishes an age-gender profile for Aboriginal peoples at the beginning, middle and end (2017) of its projections. In the absence of further data, Access Economics has assumed that the 2017 profile is maintained through to 2032. This errs on the side of conservatism, as the Aboriginal population might age between 2017 and 2032, which would increase the prevalence of VL.

Statistics Canada (2005a) does not publish an age-gender profile for its Visible Minorities projections. However, given most of the growth in this population occurs through immigration, it could reasonably be expected to maintain a similar age-gender profile to that which it has at present.

The age-gender profile (as well as total numbers) for whites was estimated as a residual after subtracting Aboriginal and Visible Minorities (AVM) projections from Statistics Canada (2006) total population projections.

20


FIGURE 2-15: AGE DISTRIBUTION OF NON-WHITE MALES (% POPULATION), 2001

0%

1%

2%

3%

4%

5%

6%

7%

8%<

15

15-2

4

25-3

4

35-4

4

45-5

4

55-6

4

65 +

Per

cent

of p

opul

atio

n

Age group (years)

East AsianSouth AsianBlackOther Visible MinorityAboriginal

Source: Statistics Canada, topic-based tabulations 95F0363XCB2001004 and 97F0011XCB2001003.

FIGURE 2-16: AGE DISTRIBUTION OF NON-WHITE FEMALES (% POPULATION), 2001

0%

1%

2%

3%

4%

5%

6%

7%

8%

<15

15-2

4

25-3

4

35-4

4

45-5

4

55-6

4

65 +

Per

cent

of p

opul

atio

n

Age group (years)

East AsianSouth AsianBlackOther Visible MinorityAboriginal

Source: Statistics Canada, topic-based tabulations 95F0363XCB2001004 and 97F0011XCB2001003.

21


It is noteworthy that there is a strong concordance between the ethnic compositions of Canada and Australia (Figure 2-17). Australia is also similar to Canada in culture and standard of living 11, and has similar principles and values underlying its health system.

FIGURE 2-17: ETHNIC COMPOSITION OF CANADIAN POPULATION COMPARED TO AUSTRALIA’S

0

10

20

30

40

50

60

70

80

90

100

European Asian Aboriginal Black / Islander

Other / Mixed

Per

cent

of P

opul

atio

n

Canada

Australia

Note: ‘Black / Islander’ for Canada refers to blacks (72% of whom have Caribbean island heritage) and to Pacific islanders for Australia. Australian data are 2006, Canadian data are 2001.

Source: Statistics Canada (2004b) and Statistics Canada Online Topic Based Tabulations, www.statcan.ca (Cat No 97F0010XCB2001004) and, Australian Bureau of Statistics, Australia Year Book 2007 (Cat No 1301.0).

2.2 DATA SOURCES FOR PREVALENCE OF VISION LOSS

A variety of data sources were reviewed to estimate prevalence of VL stratified by age, gender, ethnicity, severity (mild and moderate VL and blindness) and cause (AMD, cataract, DR, glaucoma, RE and ‘other’). Since this level of granularity is not available from any single Canadian epidemiological data source, various data sources were combined in order to ensure that Canadian aggregates were used wherever possible, with credible alternative sources used where there were found to be data gaps.

Three types of data sources were used.

Population-based eye studies. These are the gold standard, where the degree, type and cause of VL are assessed by experts over a large sample of people. However, because such

11 In 2006, according to World Bank statistics Australia’s per capita income was $US 36,000, where Canada’s was $US 36,200 (see http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS).

22

http://www.statcan.ca/


studies require large amounts of time, money and equipment, they are very rare, and none have been conducted in Canada, although data from the EDPRG eye studies (Appendix A) were utilised where appropriate.

Canadian surveys. These large scale collections assemble data from, typically, tens of thousands of respondents, across all ages, genders, ethnicities and geographic areas. The down side is that they are self-diagnosed and self-reported, and thus may suffer a substantial degree of error. Another issue is that publicly available data are usually highly aggregated. Relevant studies in Canada include the Canadian Community Health Survey (CCHS), the National Population Health Survey (NPHS) – a longitudinal study, and the Participation and Activity Limitation Survey (PALS)12.

Canadian journal articles and research studies. These often provide a great deal of detail, but only in relation to a small subject area – eg, myopia among children of Chinese immigrants, or use of visual support services by the poor in a particular city, for example. Extensive literature searching has only uncovered a handful of such studies conducted in Canada. Examples include: Cheng et al (2007) on the prevalence of myopia in Chinese-Canadian children; Hanley et al (2005) on complications of diabetes (including DR) among Aboriginal

Canadians; Meddings et al (1998) on the relationship between the development of cataract at a

young age and socioeconomic status in British Columbia; Chang et al (1999) on AMD in Chinese-Canadians; and Iskedjian et al (2003) on the costs of treating patients with glaucoma in Canada.

2.2.1 Population-based eye studies

Population-based eye studies in the US, Australia and the Netherlands show that the prevalence of VL and its underlying eye diseases do not vary greatly between white populations in these countries. Accordingly, data from these studies form the basis of estimates for the white Canadian population. However, these population studies also show significant differences in VL prevalence between given racial groups (eg, East Asian and black) living in wealthy countries (such as Canada) and those living in poorer countries (eg, China, Barbados). Accordingly, wherever possible, data for non-white groups are sourced from Canadian surveys and journal articles (see the following sections).

2.2.2 Canadian self-reported survey data

While data from national health surveys are self diagnosed and self reported, they may still be a reasonably good indicator of overall VL, and some major eye diseases.

People generally know they have vision problems. The Canadian Ophthalmological Society’s (2006) eye examination guidelines note that less than 1% of the population are unaware of having decreased vision. The exception is glaucoma, where only half of those with the condition are aware of it.

Surveys may be a reasonably accurate diagnostic tool. Djafair et al (2003) conducted an interesting evaluation of survey questionnaires as a diagnostic tool. Administering typical survey questions to over 500 patients in a Canadian hospital (whose VL was also able to be clinically assessed) resulted in a sensitivity of 82.6% and a specificity of 88.9% for best corrected VL.

12 Neither the PALS or the CCHS are published in hard copy, but selected data can be tabulated from these surveys at the Statistics Canada website (www.statcan.ca)

23


Conversely, while rates between races are reasonably similar within the CCHS and within the EDPRG data (Congdon et al, 2004a), they do tend to be quite different to each other. (As noted above, the approach adopted herein is to use EDPRG data for Canadian whites, and Statistics Canada data for the AVM population.) The only disease for which AVM prevalence is similar to US whites is glaucoma, which is the disease least likely to be self-diagnosed as most people don’t know they have it. Cataract rates in US whites are some three times higher than in Canadian AVM. Refractive error rates for US whites are around ten times or more higher than Canadian AVM rates – when both are assessed on a best-corrected basis. Moreover the age patterns (for both races) are reversed in CCHS data (increasing with age, where EDPRG data shows decreases with age). As eye health questions are optional for CCHS participants, the data also has a number of gaps due to responses being too small to be statistically valid &/or not contravene privacy regulations.

2.2.2.1 PARTICIPATION AND ACTIVITY LIMITATION SURVEY (PALS, 2001)

The PALS asks respondents the following questions.

With your glasses or contact lenses, do you have any difficulty seeing ordinary newsprint?

Have you been diagnosed by an eye specialist as being legally blind?

Besides glasses or contact lenses, do you use any other aids or specialized equipment for persons who are blind or visually impaired eg, magnifiers or Braille reading materials?

Figure 2-18 shows the prevalence of seeing disabilities according to this source’s definition, differing somewhat from Statistics Canada (2004a) (recall Figure 1-1).

FIGURE 2-18: PREVALENCE OF SEEING DISABILITIES BY AGE AND GENDER (2001)

0.12% 0.42% 0.4% 0.7%

2.5%3.4%

11.5%

0.9%

3.3%

6.0%

14.9%

0.44% 0.4%0.24% 0.38%0.13%0%

2%

4%

6%

8%

10%

12%

14%

16%

0-4 5-9 10-14 15-24 25-44 45-64 65-74 75+

Age group (years)

Prev

alen

ce (%

)

MaleFemale

Source: Statistics Canada Online PALS (2001) www.statcan.ca.

24


2.2.2.2 CANADIAN COMMUNITY HEALTH SURVEY (2005) AND NATIONAL POPULATION HEALTH SURVEY (NPHS)

A major limitation for our purposes is that PALS does not provide any information about ethnicity. The CCHS in contrast collects detailed data about ethno-cultural identities and background. Unfortunately, in its publicly available form, the CCHS amalgamates this into only two categories ‘White’ and ‘Other’.

The CCHS classified respondents as (under corrected) hyperopic if they could not see well enough to read ordinary newsprint (with glasses); and (under corrected) myopic if they could not recognise a friend across the street (with glasses). The CCHS also asked respondents if they could see at all (ie, blindness), but this was amalgamated in the category ‘myopic and hyperopic and/or blind’.

Figure 2-19 shows that in Canada, non-whites have a higher degree than whites of uncorrected VL in younger years, but generally lower rates in older age. This pattern is also apparent for VL from best corrected myopia (Figure 2-20) and for Canadians unable to see clearly at any distance or at all (Figure 2-22). There is a generally higher prevalence of VL from under corrected hyperopia among non-whites (Figure 2-21).

FIGURE 2-19: UNCORRECTED VL, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

12-1

4

15-1

7

18-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

Years of age

Prev

alen

ce (%

)

White FemaleWhite MaleNon-white FemaleNon-white Male

Source: Statistics Canada CCHS public use microdata files.

25


FIGURE 2-20: UNDER CORRECTED VL FROM MYOPIA, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

1%

2%

3%

4%

5%

6%

7%

8%12

-14

15-1

7

18-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

Years of age

Prev

alen

ce (%

)


Source: Statistics Canada CCHS public use microdata files.Note: Data for non-white males over 65 not supplied.

FIGURE 2-21: UNDER CORRECTED VL FROM HYPEROPIA, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

1%

2%

3%

4%

5%

6%

12-1

4

15-1

7

18-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

ALL

AG

ES

Years of age

Prev

alen

ce (%

)



26


FIGURE 2-22: CANADIANS UNABLE TO SEE CLEARLY AT ANY DISTANCE OR AT ALL, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

1%

2%

3%

4%

5%

6%

7%

8%

12-1

4

15-1

7

18-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

Years of age

Prev

alen

ce (%

)



While elderly male non-whites continue to fit the pattern by having lower cataract prevalence13 than their white contemporaries, there is a divergence for older non-white women, who have the highest cataract prevalence (Figure 2-23).

13 The CCHS only reports cataract prevalence, not VL from cataract.

27


FIGURE 2-23: CATARACT PREVALENCE, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

18-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

Years of age

Prev

alen

ce (%

)



Over most age ranges, it is non-white males who have the highest rates of glaucoma14 (Figure 2-24). Another important fact to note with glaucoma is that its prevalence appears to be increasing in Canada. Data from various CCHSs and NPHSs compiled by Peruccio et al (2007) show that the prevalence of glaucoma in Canadians over the age of 20 years increased by 64% between 1994 and 2003. Moreover, this is not just due to population aging, as the same trend can be seen within each age group – and in fact the increase is highest in those under 50 years. Some of this increase can be ascribed to improved diagnosis over this period. A similar trend is evident in diabetes, and thus presumably DR (see discussion around Table 2–4).

14 The CCHS only reports prevalence of glaucoma, not of VL from glaucoma

28


FIGURE 2-24: GLAUCOMA, BY ETHNICITY, AGE AND GENDER (% POPULATION)

0%

2%

4%

6%

8%

10%

12%

14%18

-19

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80 +

Years of age

Prev

alen

ce (%

)



Diabetic Retinopathy causes around 600 new cases of blindness in Canada each year15. Despite acknowledging that DR is ‘the leading cause of adult blindness in Canada’16 Statistics Canada does not collect any information on this disease. (The CCHS asks people with diabetes if they have had an eye examination where their pupils were dilated but does not provide the results of these tests.)

However, it is possible to derive the prevalence of VL from DR from the CCHS in conjunction with another Statistics Canada publication: Wilkins and Park (1996) calculated from the 1994-95 NPHS that people with diabetes were almost twice as likely as those without (odds ratio of 1.72) to have a vision limitation. Most of this is likely to refer to DR, although Canadians with diabetes also have higher rates of cataract and glaucoma than those without (James et al, 1997). Thus an upper limit for prevalence of VL from DR could be calculated by taking each age-gender cohort in the diabetic population (from Table 2–4) and assigning it 1.72 times the VL prevalence experienced by that cohort in the general population. (This is discussed in more detail in section 2.3.5)

15 Public Health Agency of Canada, National Diabetes Fact Sheet 2007, http://www.phac-aspc.gc.ca/ccdpc-cpcmc/diabetes-diabete/english/pubs/ndfs-fnrd07-eng.html

16 http://www.statcan.ca/english/research/82-619-MIE/2005002/sequelae.htm (accessed 3 Feb 2008)

29

http://www.statcan.ca/english/research/82-619-MIE/2005002/sequelae.htm


TABLE 2–4: PREVALENCE OF DIABETES, BY AGE AND GENDER, 2005 (%)Age Male Female All12-14 0.315-19 0.3 0.3 0.320-24 0.9 0.7 0.825-34 0.9 1.2 1.135-44 2.1 1.9 2.045-54 5.0 4.0 4.555-64 11.8 8.5 10.165-74 17.3 12.3 14.675+ 16.8 13.1 14.6

Total 5.3 4.4 4.9Source: Statistics Canada http://www40.statcan.ca/l01/cst01/health53b.htm

One important fact to note with diabetes is that it is growing faster than population growth. Moreover, this growth is not just due to population aging either, as the prevalence of diabetes has increased significantly within every age-gender cohort (by an average of over 50% in the decade to 2005, potentially due to increasing rates of obesity and other risk factors). Again, as with glaucoma, the highest increases in prevalence are in the younger ages. This could have significant implications for the prevalence of blindness in Canada over the next 25 years. However, in the interests of conservatism, age-gender prevalence rates were modelled to remain constant in the future.

A summary of eye disease prevalence in AVM groups from the 2005 CCHS is contained in Table 2–5. As noted above, for the white Canadian population, studies in the EDRPG dataset are used.

The CCHS does not report the prevalence of either AMD or DR. DR, however, can be estimated indirectly (and is done so in Section 2.3.5, covering VL caused by DR in AVM groups). The prevalence of AMD in Canadian AVMs is assumed to be the same as the average prevalence in non-white Americans (from Congdon et al, 2004a).

30

http://www40.statcan.ca/l01/cst01/health53b.htm


TABLE 2–5: CCHS PREVALENCE OF EYE DISEASES IN AVMMales Cataract Glaucoma Hyperopia Myopia AMD15-19 0.0% 0.00% 0.47% 0.00%20-24 0.4% 0.05% 1.31% 0.00%25-29 0.0% 0.00% 0.00% 0.80%30-34 0.2% 0.15% 0.00% 0.00%35-39 0.3% 0.82% 0.00% 0.00%40-44 0.1% 0.56% 0.83% 0.32%45-49 1.9% 0.64% 0.40% 0.00%50-54 2.0% 1.18% 1.46% 0.10% 0.24%55-59 4.4% 4.45% 2.52% 0.92% 0.39%60-64 11.7% 1.85% 1.48% 0.62% 0.64%65-69 13.2% 6.26% 2.24% 3.40% 1.06%70-74 22.9% 9.53% 2.53% 2.16% 1.75%75-79 16.0% 5.70% 2.82% 2.26% 2.88%80-84 21.0% 5.99% 2.45% 2.64% 4.69%85-89 20.99% 5.99% 2.45% 2.64% 7.55%90+ 20.99% 5.99% 2.45% 2.64% 7.55%

Females15-19 0.00% 0.18% 0.00% 0.00%20-24 0.05% 0.00% 0.18% 0.00%25-29 0.09% 0.00% 2.19% 0.00%30-34 0.43% 0.25% 1.42% 0.98%

35-39 0.28% 0.18% 1.53% 0.00%40-44 0.56% 0.50% 1.63% 0.00%45-49 0.19% 0.21% 1.25% 0.39%50-54 1.41% 0.99% 3.20% 0.00% 0.50%55-59 3.46% 0.65% 5.15% 1.00% 0.70%60-64 10.05% 2.34% 3.02% 0.87% 0.97%65-69 21.14% 2.08% 0.88% 0.95% 1.34%70-74 34.68% 3.07% 0.31% 3.17% 1.85%75-79 36.80% 11.50% 3.20% 3.24% 2.57%80-84 41.99% 2.95% 3.19% 2.55% 3.59%85-89 41.99% 2.95% 3.19% 2.55% 5.02%90+ 41.99% 2.95% 3.19% 2.55% 5.02%

Note: Figures in italics contain no data in original, and are interpolated from relative changes between cohorts in the same ethnicity or gender.

Source: Source: Statistics Canada CCHS public use microdata files, Congdon et al (2004a).

2.2.3 Data from Canadian journal articles and research studies

2.2.3.1 CANADIAN POPULATION STUDIES

Maberley et al (2006) conducted an analysis of all ophthalmological records (around 2,500, of which 962 were suitable) in Prince George, a medium-sized Canadian city, over a five year period. They concluded that ‘The overall prevalence of low vision and blindness in Canada are in keeping with data from large population-based studies from other developed nations’. As Figure 2-25 shows, cataract, visual pathway disorders17 and AMD were the leading causes of VL in this study.

17 Visual pathway disorders (ICD10 H446-H48) are conditions which impede the visual pathway. Occasionally acute vision loss is caused by homonymous hemianopia and, more rarely, cortical blindness.

31


FIGURE 2-25: CAUSES OF VL IN PRINCE GEORGE, CANADA

Cataract29%

AMD13%

Other retinal causes12%

Visual pathway12%

Cornea / conjunctiva11%

Refractive8%

DR7%

Other (iris, trauma, lid)5%

Glaucoma3%

Source: Maberley et al (2006).

CNIB has a database of its clients that can also be used to derive an estimate of the causes of blindness in Canada (Table 2–6), assuming that registering with CNIB is equally likely for all causes of blindness. The fact that the elderly blind may have difficulty registering may represent a source of bias, however.

TABLE 2–6: CAUSES OF BLINDNESS IN CNIB CLIENTS (2007)

Cause Persons (‘000)AMD 50.2DR 7.5Glaucoma 7.6Other 49.2Total 114.5

Source: CNIB

2.2.3.2 CHINESE CANADIANS

Chang et al (1999) reports in a study of 20,000 patients presenting for fluorescein angiography that the rate of AMD in Chinese Canadians (30.4%) was over twice as high as in white Canadians (14.6%). From this, it may be plausible to assume that AMD in Chinese-Canadians is twice as high as the overall population estimate provided by Maberley et al (2006).

Cheng et al (2007) report that Chinese Canadian children aged six years have a prevalence rate of myopia of 22.4%, which is several times the prevalence reported by Robinson (1999) for Canadian six year olds in general of 6.4%. Cheng et al (2007) also report that the prevalence of myopia among Chinese children in Canada is broadly similar to earlier findings from Chinese children in China (Hong Kong) – Figure 2-26. The assumption is made that Chinese-Canadian teenagers have

32


the same rates of myopia as do their counterparts in China in Figure 2-26. However, this appears to decline in later years; Wong (2006) records that Chinese in China over the age of 40 and 60 years have myopia prevalence of 22.9% and 19.4% respectively.

FIGURE 2-26: MYOPIA IN CHINESE CHILDREN IN CANADA AND HONG KONG

0

10

20

30

40

50

60

70

80

90

100

5 6 7 8 9 10 11 12 13 14 15

Age (years)

Prev

alen

ce o

f myo

pia

(%)

Canada 2003

Hong Kong 1996

Hong Kong 2000

Hong Kong 2001

Source: Cheng et al (2007).

If nature dominates nurture for the Canadian Chinese population, as well as having twice the rate of AMD, it is also possible that Chinese Canadians may have twice the rate of DR. The 2001 PALS found that 17.4% of Canadians who have diabetes report a seeing disability. Wong et al (2006) found that 35% of the Chinese population in Taiwan with diabetes have a seeing disability. The Institute for Clinical Evaluative Sciences - ICES (Glazier et al, 2007) note that in the US, African and Hispanic populations have twice the rate of diabetes as do whites; diabetes among Asian Americans is higher than in whites and rising faster than in other ethnic groups; and that in the United Kingdom (UK), South Asians have at least three times the rate of diabetes as the white population.

2.2.3.3 ABORIGINALS

Data availability for VL in North American Indians, Metis and Inuit is also scarce. Hanley et al (2005) found 23.3% of North American Indian diabetics in remote communities had DR, with similar figures also being reported by Maberley et al (2002). This is around a third higher than for the general population (albeit lower than the Chinese figures). ICES (Glazier et al, 2007) note that the prevalence of diabetes in Aboriginal communities in Ontario (13%) was three times higher than for the non-indigenous population.

Van Rens et al (1988) reported remarkably high levels of POAG in Eskimo women in Alaska (Table2–7). Similarly, Adams and Adams (1974) reported that the prevalence of POAG in Canadian Inuit women was up to 40 times that in non-Inuit women.

33


TABLE 2–7: PREVALENCE OF POAG AMONG THE ESKIMO (%)Age (years) Males Females

<49 3.1 3.650-59 2.6 11.860-69 3.7 11.870+ 0.5 1.2

Source: Van Rens et al (1988).

Young et al (2000) state that Canada’s North American Indians have a ‘high prevalence of serious and untreated diabetic retinopathy’.18 Health Canada (2002b) reports that 25% of Mohawks who have had diabetes for ten years also have DR.

TABLE 2–8: PREVALENCE OF DIABETES AMONG CANADIAN ABORIGINAL PEOPLES (1991)

0

1

2

3

4

5

6

7

8

9

Total Aboriginal

On-Reserve North

American Indians

Off-Reserve North

American Indians

Total North American

Indians

Metis Inuit

Prev

alen

ce (%

)

Source: Health Canada (2002b).

2.2.3.4 BLINDNESS

Buhrmann et al (forthcoming) estimate the prevalence of blindness by cause in Canada out to 2031, by applying the breakdown from Congdon et al (2004a) to Statistics Canada’s (total) population projections for selected years.

18 They cite Ross and Flick (1991) as their source, but this article does not appear to be electronically available.

34


TABLE 2–9: PREVALENCE OF BLINDNESS BY CAUSE, 2006 TO 2031 (% POPULATION)

Cause 2006 2011 2016 2021 2026 2031

AMD 0.4 0.4 0.5 0.5 0.5 0.6DR 0.0 0.0 0.0 0.1 0.1 0.1Glaucoma 0.1 0.1 0.1 0.1 0.1 0.1Other 0.2 0.2 0.2 0.2 0.2 0.2Total 0.7 0.7 0.7 0.8 0.9 1.0

Source: Buhrmann et al (forthcoming).

2.3 PREVALENCE RATES FOR VL

2.3.1 White population VL

As noted above, there have not yet been any major population eye health studies conducted in Canada. Thus, for Canadian whites, the choice falls to using self-diagnosed and self-reported data from the CCHS, or using data from American or Australian eye health studies. Australian data (Centre for Eye Research Australia, 2005)19 is preferred for two reasons. First, Australian VL data for each disease is available by age cohort, which is essential for working with population projections. Second – and potentially reflecting similar ethnic mix and health systems – the Australian proportion of total VL caused by each of the major diseases is significantly closer to Canada’s than the US data (Table 2–10). As the table shows, the proportion of VL caused by cataract in the US is more than three times higher than in Canada, whereas the ratio between Canada and Australia is around 1.30 to 1.00 At the other end of the scale, the proportion of VL due to RE and other is more than five times smaller in the US than it is Canada, whereas the ratio between Australia and Canada is around 1.39 to 1.00.

TABLE 2–10: CAUSES OF VL, BY DISEASE, IN WHITE POPULATIONS

Disease US Canada Australia

Cataract 59.2% 18.6% 14.3%Glaucoma 3.3% 7.0% 2.9%DR 4.9% 7.0% 1.6%AMD 22.9% 16.3% 10.1%RE/Other 9.7% 51.3% 71.2%

Sources: US (Congdon et al, 2004a), Canada (Maberley et al, 2006), Australia (CERA, 2005)

Australian VL

Access Economics (2007) used data from the MVIP to determine the prevalence of VL caused by AMD (Table 2–11). Severity was measured according to the better seeing eye (noting that with AMD it can become the worse one over time). For Canada, the distribution between mild, moderate and severe VL from AMD and by age are based on these data, as it was considered likely that AMD incidence and progression follows a similar pathway in Canada.

19 These data have been published in a number of journal articles, including Taylor, Pezzullo and Keeffe (2006)

35


TABLE 2–11: PREVALENCE OF VL DUE TO AMD, BY SEVERITY (% OF AGE GROUP)

Age Mild Moderate Severe0-69 0.00 0.00 0.00

70-74 0.17 0.00 0.1775-79 0.00 0.87 0.0080-84 1.00 1.00 1.0085-89 2.13 4.26 3.1990+ 3.15 6.29 4.7240+ 0.10 0.33 0.13

Source: Access Economics (2007).

The Centre for Eye Research Australia (CERA, 2005) estimated the prevalence of VL caused by cataract in Australia, also from the MVIP (Table 2–12). For Canada, as with AMD, the distribution between mild, moderate and severe VL from cataract and by age are based on these data.

TABLE 2–12: PREVALENCE RATES FOR VL FROM CATARACTS, BY AGE AND SEVERITY (%)Age Total VL (<20/40) VL by severity Total40-49 0.0% Mild (6/12 to 6/18) 60.2%50-59 0.0% Moderate (<6/18 to 6/60) 26.7%60-69 0.1% Severe (>6/60) 13.0%70-79 1.4%80-89 6.6%90+ 15.2%

Source: CERA (2005).

Access Economics (2008c, forthcoming) provides estimates of the prevalence of VL caused by DR (Table 2–13), based on combined data from the MVIP and Blue Mountains Eye Study (BMES). For Canada, the distribution between mild, moderate and severe VL from DR and by age are again based on these data.

TABLE 2–13: PREVALENCE RATES FOR VISION IMPAIRMENT (<6/12) FROM DR, AND PROPORTION BY STAGE OF VISION LOSS

Age Total VL (<20/40) VL by severity Total40-49 0.0% Mild (6/12 to 6/18) 30.6%50-59 0.0% Moderate (<6/18 to 6/60) 47.8%60-69 0.2% Severe (>6/60) 21.6%70-79 0.1%80-89 0.5%90+ 0.6%

(a) Prevalence based on combined data from the MVIP and BMES. (b) Stages of vision loss based on MVIP.Source: Access Economics (2008c).

Access Economics (2008b) estimated the prevalence of VL caused by POAG, by degrees of severity, from the MVIP and the BMES (Table 2–14). For Canada, the distribution between mild, moderate and severe VL from glaucoma and by age are once again based on these data.

36


TABLE 2–14: PROPORTION OF PEOPLE WITH GLAUCOMA BY AGE AND SEVERITY (%)

Age Group Mild Moderate Severe0-59 0.0 0.0 0.060-64 0.2 1.7 2.965-69 0.4 2.8 2.670-74 0.5 3.7 3.375-79 1.2 8.4 1.880-84 1.7 11.5 2.585-89 2.2 15.1 4.890+ 1.1 7.7 20.6

Source: Based on combined data from the MVIP and BMES.

Most people with glaucoma in developed countries are unaware they have the disease (Canadian Ophthalmological Society, 2007). Even among those regularly visiting eye professionals, the probability of diagnosis depends on the severity of the condition. Hence, the more severe forms have the highest (diagnosed) prevalence.

Wong et al (2004) examined the presence of undiagnosed glaucoma in people who had visited an eye care provider in the previous year using MVIP data. They found that 81% of possible cases, 72% of probable cases and 59% of definite cases of glaucoma were previously undiagnosed by the eye care provider.

CERA (2005) estimated the prevalence of VL caused by RE in Australia from the MVIP (Table 2–15). For Canada, the relativities between mild, moderate and severe VL from RE and by age are based on these data, as it is likely that RE incidence and progression follows a similar pathway in Canada.

TABLE 2–15: PREVALENCE RATES FOR VL FROM RE, BY AGE AND SEVERITY (%)Age Total VL (<20/40) VL by severity Total

40-49 0.5% Mild (6/12 to 6/18) 83.4%50-59 1.8% Moderate (<6/18 to 6/60) 14.6%60-69 3.9% Severe (>6/60) 2.0%70-79 7.8%80-89 13.0%90+ 7.9%

Source: CERA (2005).

In addition to the above breakdowns by severity, CERA (2005) also gives an overall prevalence of VL caused by each major eye disease, which is used as the basis for the prevalence of VL by cause for Canadian whites (Table 2–16).

37


TABLE 2–16: ESTIMATED VL PREVALENCE IN CANADIAN WHITES BY DISEASE AND AGE

Cataract DR Glaucoma AMD RE Other

40-44 0.71% 0.18%45-49 0.00% 0.00% 0.29% 0.14%50-54 0.00% 0.09% 0.00% 1.05% 0.52%55-59 0.08% 0.12% 0.00% 2.62% 0.17%60-64 0.01% 0.16% 0.00% 0.00% 2.51% 0.25%65-69 0.16% 0.16% 0.16% 0.08% 5.38% 0.43%70-74 0.73% 0.10% 0.20% 0.22% 6.30% 0.64%75-79 2.37% 0.44% 0.34% 1.70% 9.87% 0.78%80-84 5.49% 0.78% 1.52% 2.31% 13.13% 0.92%85-89 8.71% 0.68% 1.32% 8.77% 12.80% 3.75%90+ 15.17% 0.58% 1.23% 12.97% 7.86% 2.44%

Source CERA (2005).

2.3.2 Aboriginals and Visible Minorities (AVM) VL

There are severe data problems in estimating the prevalence of VL among Canada’s AVM populations. While the CCHS collects the prevalence of eye diseases, by age, for the AVM population, it does not collect data on the causes of VL. Moreover, the prevalence data are not disaggregated by race, despite known differences between races (Figure 2-27). There have been some international population eye health studies covering the causes of VL in non-whites, but the races (blacks and Hispanics) covered were not representative of Canada’s AVM population (blacks are 2% of the Canadian population, and Hispanic does not rate a category in the Canadian census). Moreover the data is not available by age-cohort which, given how greatly the incidence of VL varies by age, makes it very difficult to map to Canada’s AVM population.

FIGURE 2-27: CAUSES OF BLINDNESS BY ETHNICITY (US)

Source: Congdon et al (2004a).

Access Economics’ approach has been to estimate from international sources the likelihood that a non-white person who has an eye disease will develop VL, and apply that ratio to the CCHS prevalence of that disease in Canada’s AVM population. The next few paragraphs illustrate the concepts involved using illustrative round numbers.

38


Suppose, for example, that 25% of the US non-white population who have cataract will also have VL from that disease. Suppose further, that 10,000 Canadian AVM have cataract. Then - if making the assumption that the share of non-whites with cataract who have VL is similar on both sides of the border - there are an estimated 2,500 (=10,000 * 25%) AVM who suffer VL because of their cataracts.

Prevalence rates of cataract by age group among Canadian AVM are known and Congdon et al (2004a) reports that, in America, if a white and a non-white both have cataract, the white is more likely to suffer VL from the disease (for illustrative purposes, suppose twice as likely). Assuming that American, Australian and Canadian whites are similar in this relative risk, then if 80% of 80 year old (Australian) whites with cataract have VL, it follows that half as many (40%) of Canadian non-whites (Canadian) with cataract will have VL. So if the CCHS reports that there are 1,000 80 year old Canadian AVM with cataract, 400 of them (=1,000 * 40%) are estimated to have VL.

2.3.3 Cataract-induced VL in AVM

Because there are multiple races and multiple diseases, this section works through one disease in detail – cataract – using actual data, and other disease prevalence rates are similarly calculated.

Using the NEI disease prevalence (http://www.nei.nih.gov/eyedata/tables.asp) and 2000 US Census data (http://factfinder.census.gov/), an estimated 7.47% of the white population had cataract (Row A, Table 2–17). Access Economics (2006) shows that 2.79% of white Americans had VL (Row B). Congdon et al (2004a) show that 59.2% of this total VL was caused by cataract (Row C). Thus, the prevalence of cataract-induced VL was 1.65% (59.2% times 2.79%) of the white population (Row D). Thus, it can be deduced that 22.1% (1.65/7.47) of whites who have cataract will also have VL from those cataracts (Row E).

TABLE 2–17: PREVALENCE OF VL IN US WHITES WITH CATARACTS (2000)

Factor %A. Prevalence of cataract 7.47%B. Prevalence of VL 2.79%C. Proportion of VL caused by cataract 59.2%D. Prevalence of cataract-induced VL (C*B) 1.65%E. Percent of cataract population who have VL (D/A) 22.1%

Sources: Access Economics (2006), Congdon et al (2004a).

For blacks, the same data show that 6.42% of the black population had cataract (Row A, Table 2–18). Access Economics (2006) shows that 2.28% of black Americans had VL (Row B). Congdon et al (2004a) show that 50.9% of this total VL was caused by cataract (Row C). Thus, the prevalence of cataract-induced VL was 1.16% (50.9% times 2.79%) of the black population (Row D) and it can be deduced that 18.1% (1.16/6.42) of blacks who have cataract will also have VL from those cataracts (Row E).

TABLE 2–18: PREVALENCE OF VL IN US BLACKS WITH CATARACTS (2000)

Factor %

A. Prevalence of cataract 6.42%B. Prevalence of VL 2.28%C. Proportion of VL caused by cataract 50.9%D. Prevalence of cataract-induced VL (C*B) 1.16%E. Percent of cataract population who have VL (D/A) 18.1%

39

http://www.nei.nih.gov/eyedata/tables.asp



For Hispanics, the data record that 6.96% of the Hispanic population had cataract (Row A, Table 2–19). Access Economics (2006) shows that 1.96% of Hispanic Americans had VL (Row B). Congdon et al (2004a) show that 46.7% of this total VL was caused by cataract (Row C). Thus, the prevalence of cataract-induced VL was 0.91% (46.7% times 1.96%) of the Hispanic population (Row D) and it can be deduced that 13.1% (0.91/6.96) of Hispanics who have cataract will also have VL from those cataracts (Row E).

TABLE 2–19: PREVALENCE OF VL IN US HISPANICS WITH CATARACTS (2000)

Factor %



Finally, for other races, according to the data, 6.96% of the remaining population of other races had cataract (Row A, Table 2–20). Access Economics (2006) shows that 2.15% of ‘other’ Americans had VL (Row B). Congdon et al (2004a) show that 52.3% of this total VL was caused by cataract (Row C). Thus, the prevalence of cataract-induced VL was 1.12% (52.3% times 2.15%) of the remainder of the population (Row D) and it can be deduced that 16.2% (1.12/6.96) of other races who have cataract will also have VL from those cataracts (Row E).

TABLE 2–20: PREVALENCE OF VL IN US ‘OTHER’ WITH CATARACTS (2000)

Factor %



Drawing this together, it is possible to estimate how much less likely the average non-white is to develop VL after contracting cataracts than is the average white (Table 2–21). Weighting the three non-white races (black, Hispanic and ‘other’) by their respective shares of the Canadian AVM population (blacks 12%, Latin Americans20 4%, ‘other’ 84%) yields the result that 16.3% of Canadian AVM with cataract will have VL from their cataracts (Row E). This in turn indicates that an AVM person with cataract is only 74% as likely to develop VL as is a white person with cataract (Row F).

TABLE 2–21: RELATIVE RISK OF DEVELOPING VL FROM CATARACTS, BY RACE

Race/Ethnic group Prevalence of VL in those with cataract

Share of Canadian AVM population

A. Whites (Table 2–17) 22.1%B. Blacks (Table 2–18) 18.1% 12%C. Hispanic (Table 2–19) 13.1% 4%

20 As noted above, the Canadian census does not include the category ‘Hispanic’; ‘Latin American’ is used as a proxy.

40


D. Other (Table 2–20) 16.2% 84%E. Non-white weighted average 16.3%

F. Ratio average non-white to white (E/A) 0.74

Source: Derived from previous tables.

Having derived above that, over the whole population, an AVM person with cataract is around three-quarters as likely to have VL as a white person, this is then applied to the fraction of whites with cataracts who have VL (Column C in Table 2–22). The latter, in turn, is derived from the prevalence of cataract-induced VL (from Table 2–16, reproduced as Column A in Table 2–22) and from the prevalence of cataract as a disease in whites (from the Australian Bureau of Statistics, 2006, Column B below).

TABLE 2–22: PREVALENCE OF VL IN WHITES WITH CATARACT, BY AGE

Age A. Prevalence of cataract

B. Prevalence of cataract induced VL

C. Fraction of those with cataracts who have

VL (B/A)35-39 0.2% 0.0% 0.0%40-44 0.2% 0.0% 0.0%45-49 0.5% 0.0% 0.0%

50-54 0.5% 0.0% 0.0%55-59 1.5% 0.1% 5.5%60-64 1.5% 0.0% 0.7%65-69 5.1% 0.2% 3.2%70-74 5.1% 0.7% 14.2%75-79 13.2% 2.4% 17.9%80-84 13.2% 5.5% 41.5%85-89 19.9% 8.7% 43.8%90+ 19.9% 15.2% 76.2%

Sources: CERA (2005), Australian Bureau of Statistics (2006).

The likelihood that a non-white with cataract will develop VL (Column C in Table 2–23) can then be derived from the fraction of whites with cataracts who have VL (from Table 2–22, reproduced as Column A in Table 2–23) and the relative risk between whites and non-whites (from Table 2–21, reproduced as Column B).

41


TABLE 2–23: PREVALENCE OF VL IN NON- WHITES WITH CATARACT, BY AGE

Age A. Fraction of whites with cataracts who have

VL

B. Relative risk of developing VL from

cataract (non-white/white)

C. Fraction of non-whites with cataracts who have

VL (A*B)

35-39 0.0% 0.74 0.0%40-44 0.0% 0.74 0.0%45-49 0.0% 0.74 0.0%

50-54 0.0% 0.74 0.0%55-59 5.5% 0.74 4.1%60-64 0.7% 0.74 0.5%65-69 3.2% 0.74 2.3%70-74 14.2% 0.74 10.5%75-79 17.9% 0.74 13.2%80-84 41.5% 0.74 30.5%85-89 43.8% 0.74 32.2%90+ 76.2% 0.74 56.1%

Source: derived from Tables 2-21 and 2-22.

Finally, having derived how likely a non-white with cataract is to develop VL (Table 2–23), it remains to ascertain how many non-whites have cataract. This information is provided by the CCHS (Table2–5) and reproduced as Column A in Table 2–24. Multiplying the number of AVM with cataract (Column A) by their chance of having VL (Column B) gives the prevalence of VL from cataract in the AVM population by age group. For example, if 22.9% of AVM aged between 70 and 74 have cataract, and 10.5% of these develop VL, then around 2.4% of AVM in this age group will have VL caused by cataract.

42


TABLE 2–24: PREVALENCE OF CATARACT-INDUCED VL IN CANADIAN AVM, BY AGE

A Prevalence of cataract in non-

whites

B Fraction of non-whites with

cataracts who have VL

C Prevalence of cataract-induced VL in non-whites

(A*B)Males35-39 0.3% 0.0% 0.0%40-44 0.1% 0.0% 0.0%

45-49 1.9% 0.0% 0.0%50-54 2.0% 0.0% 0.0%55-59 4.4% 4.1% 0.2%60-64 11.7% 0.5% 0.1%65-69 13.2% 2.3% 0.3%70-74 22.9% 10.5% 2.4%75-79 16.0% 13.2% 2.1%80-84 21.0% 30.5% 6.4%85-89 21.0% 32.2% 6.8%90+ 21.0% 56.1% 11.8%Females35-39 0.3% 0.0% 0.0%40-44 0.6% 0.0% 0.0%45-49 0.2% 0.0% 0.0%50-54 1.4% 0.0% 0.0%55-59 3.5% 4.1% 0.1%60-64 10.0% 0.5% 0.1%65-69 21.1% 2.3% 0.5%70-74 34.7% 10.5% 3.6%75-79 36.8% 13.2% 4.9%80-84 42.0% 30.5% 12.8%85-89 42.0% 32.2% 13.5%90+ 42.0% 56.1% 23.5%

Source: Derived from above tables and data from the CCHS.

2.3.4 VL caused by AMD, Glaucoma and RE in AVM

The exercise in the previous section can be repeated for VL in AVM caused by the other major eye diseases, except DR, which is dealt with by a different method, using solely Canadian data, in Section 2.3.5. Table 2–25 reports the prevalence of each eye disease in each non-white group from the NEI dataset (weighted by 2000 Census age cohorts, as above).

TABLE 2–25: PREVALENCE OF EYE DISEASES BY ETHNICITY, US, 2000White Black Hispanic Other

A. AMD 0.8% 0.4% 0.4% 0.4%B. Cataract 7.5% 6.4% 7.0% 7.0%C. Glaucoma 0.7% 1.6% 0.9% 1.0%D. RE/Other 16.7% 8.6% 10.7% 10.9%

Source: US Census 2000 (http://factfinder.census.gov/servlet/STTable?_bm=y&-geo_id=01000US&-qr_name=ACS_2006_EST_G00_S0101&-ds_name=ACS_2006_EST_G00_)

EDPRG (http://www.nei.nih.gov/eyedata/tables.asp)

43

http://www.nei.nih.gov/eyedata/tables.asp

http://factfinder.census.gov/servlet/STTable?_bm=y&-


The prevalence of VL caused by each eye disease is derived from Congdon et al (2004a), which reports both the total prevalence of VL for each race in the US (Row E in Table 2–27) and the percentage of this VL which is caused by each major disease (Table 2–26). The prevalence of VL by disease is then derived as per cataract in the previous section, presented in Table 2–28.

TABLE 2–26: CAUSES OF VL BY ETHNICITY21

White Black Hispanic OtherA. AMD 22.9% 3.2% 14.3% 13.5%B. Cataract 59.2% 50.9% 46.7% 52.3%C. Glaucoma 3.3% 14.3% 7.6% 8.4%D. RE/Other 9.7% 17.0% 18.5% 15.1%

Source: Congdon et al (2004a).

TABLE 2–27: PREVALENCE OF VL, BY ETHNICITY AND CAUSE, US, 2000White Black Hispanic Other

A. AMD 0.64% 0.07% 0.28% 0.29%B. Cataract 1.65% 1.16% 0.91% 1.12%C. Glaucoma 0.09% 0.33% 0.15% 0.18%D. RE/Other 0.27% 0.39% 0.36% 0.32%E. Sum 2.79% 2.28% 1.96% 2.15%

Source: Access Economics (2006), Table 2–26.

TABLE 2–28: PREVALENCE (%) OF VL WITHIN SPECIFIED DISEASES, BY ETHNICITY

White Black Hispanic OtherA. AMD 95.2 17.4 63.2 69.5B. Cataract 22.1 18.1 13.1 16.2C. Glaucoma 14.0 20.1 16.7 17.9D. RE/Other 1.6 4.5 3.4 3.0

Source: Derived from Table 2–25 and Table 2–27.

Extending the above analysis across ethnicities and diseases, Figure 2-28 shows the variance in the probability of VL across diseases and ethnic groups. For example, AMD appears to have a significantly greater likelihood of causing VL in whites than in blacks, while RE is more likely to cause VL in blacks than whites. This may possibly be due to genetic factors or to socioeconomic factors governing access to medical care (and thus detection and treatment).

21 DR is not included as it is calculated separately in Section 2.3.5. Rates are white 5%, black 15%, Hispanic 13%, other 11%.

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FIGURE 2-28: PROBABILITY OF DEVELOPING VL AFTER CONTRACTING SELECTED DISEASES, BY ETHNICITY

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Cataract Glaucoma DR RE/Other AMD

Prob

abili

ty o

f vis

ual i

mpa

irmen

t afte

r co

ntra

ctin

g sp

ecifi

ed d

isea

se (%

)

WhiteBlackHispanicOther

Source: Derived from EDPRG (Congdon et al, 2004a) and US Census data.

As with the methodology for cataract, the relative risk of VL from a particular disease is compared between whites and each other group and a weighted average is developed using the population weights for each group among the Canadian AVM total (Table 2–29).

TABLE 2–29: RELATIVE RISK OF VL BY EYE DISEASE, NON-WHITES TO WHITES

Disease Relative RiskA. AMD 1.52B. Cataract 0.74C. Glaucoma 1.29D. RE/Other 1.96

Source: Derived from previous tables and Canadian Census data.

To derive an age breakdown for the relative risks for the non-white population, data on prevalence of each disease were used from the Australian Bureau of Statistics (2006) and the Australian Institute of Health and Welfare (2005) (Table 2–30).

TABLE 2–30: PREVALENCE OF EYE DISEASES IN WHITES

Age AMD Cataract Glaucoma RE/Other40-44 0.1% 0.2% 0.2% 43.9%45-49 0.3% 0.5% 0.8% 77.4%50-54 0.3% 0.5% 0.8% 77.4%55-59 0.8% 1.5% 1.3% 70.9%60-64 0.8% 1.5% 1.3% 70.9%65-69 1.1% 5.1% 2.4% 52.8%70-74 1.1% 5.1% 2.4% 52.8%75-79 3.7% 13.2% 6.3% 54.1%80-84 3.7% 13.2% 6.3% 54.1%85-89 6.3% 19.9% 7.2% 51.2%90+ 6.3% 19.9% 7.2% 51.2%

Source: Australian Bureau of Statistics (2006), Australian Institute of Health and Welfare (2005).

45


Recall that the prevalence of VL in whites by cause was shown in Table 2–16. Using that prevalence and the prevalence of each disease (Table 2–30) gives the fraction of VL caused by that disease (Table 2–31) for each five-year age cohort in the white population.

TABLE 2–31: FRACTION OF WHITES WITH EACH EYE DISEASE WHO HAVE VL, BY AGE AND GENDER (%)

Age AMD Cataract Glaucoma RE/Other40-44 0.0% 0.0% 2.0%45-49 0.0% 0.0% 0.6%50-54 0.0% 0.0% 0.0% 2.0%55-59 0.0% 5.5% 0.0% 3.9%60-64 0.0% 0.7% 0.0% 3.9%65-69 7.4% 3.2% 6.7% 11.0%70-74 20.2% 14.2% 8.2% 13.1%75-79 45.4% 17.9% 5.4% 19.7%80-84 61.5% 41.5% 24.3% 26.0%85-89 100.0% 43.8% 18.3% 32.3%90+ 100.0% 76.2% 17.0% 20.1%

Note: AMD prevalences in 85 years and older capped at 100%Source: Congdon et al (2004a), Access Economics (2007).

Combining the fractions in Table 2–31 with the relative risks (non-white to white) from Table 2–29 leads to the prevalence of VL within disease groups in non-whites as per Table 2–32.

TABLE 2–32: PREVALENCE OF VL WITHIN DISEASE GROUPS, NON-WHITES

Age AMD Cataract Glaucoma RE/Other40-44 0.0% 0.0% 4.0%45-49 0.0% 0.0% 1.1%50-54 0.0% 0.0% 0.0% 4.0%55-59 0.0% 4.1% 0.0% 7.7%60-64 0.0% 0.5% 0.0% 7.6%65-69 10.5% 2.3% 8.7% 21.5%70-74 28.6% 10.5% 10.6% 25.7%75-79 64.4% 13.2% 7.0% 38.6%80-84 87.3% 30.5% 31.2% 50.8%85-89 100.0% 32.2% 23.5% 63.3%90+ 100.0% 56.1% 21.8% 39.4%

Source: Derived from previous tables.

Using this with the prevalence of eye disease in AVM from CCHS data (Table 2–5) results in the prevalence of VL from that disease (Table 2–33).

46


TABLE 2–33: PREVALENCE OF VL IN AVM

Males AMD Cataract Glaucoma RE/Other40-44 0.00% 0.00% 0.05%45-49 0.00% 0.00% 0.00%50-54 0.00% 0.00% 0.00% 0.06%55-59 0.00% 0.18% 0.00% 0.27%60-64 0.00% 0.06% 0.00% 0.16%65-69 0.11% 0.31% 0.54% 1.22%70-74 0.50% 2.40% 1.01% 1.21%

75-79 1.85% 2.11% 0.40% 1.96%80-84 4.09% 6.41% 1.87% 2.59%85-89 7.55% 6.76% 1.41% 3.22%90+ 7.55% 11.77% 1.31% 2.01%

Females AMD Cataract Glaucoma RE/Other40-44 0.00% 0.00% 0.06%45-49 0.00% 0.00% 0.02%50-54 0.00% 0.00% 0.00% 0.13%55-59 0.00% 0.14% 0.00% 0.47%60-64 0.00% 0.05% 0.00% 0.30%65-69 0.14% 0.49% 0.18% 0.39%70-74 0.53% 3.63% 0.33% 0.89%75-79 1.66% 4.85% 0.80% 2.48%80-84 3.13% 12.82% 0.92% 2.92%

85-89 5.02% 13.52% 0.69% 3.63%90+ 5.02% 23.54% 0.64% 2.26%

2.3.5 Diabetes and DR in the AVM population

The above methods cannot be fully used for DR in the Canadian AVM population, because the CCHS does not report on the prevalence of DR in AVM. However, there are sufficient Canadian data from other sources to estimate age-gender prevalence of DR using an alternate methodology discussed in this section.

Data from various Canadian publications enable an estimate of VL from DR in the AVM population to be calculated directly (rather than having to rely on non-Canadian EDPRG data.) Statistics Canada’s Health Report (Wilkins and Park, 1996) shows that the prevalence of VL among Canadian diabetics is 72% higher than in the general population. However, as Access Economics (2008c) notes, diabetics also have higher rates of cataract, glaucoma and macular edema, with the result that the prevalence of DR in diabetics is roughly equivalent to the combined prevalence of these three other diseases in diabetics. Thus, it was assumed that half of the increased rate of VL (36%) is due to DR (rather than the other three associated eye diseases). Increasing the 2005 CCHS figures for the prevalence of under corrected VL in the AVM population (Table 2–34) by 36% enabled an estimate of the prevalence of DR-induced VL among diabetics in this population (Table2–35).

47


TABLE 2–34: UNDER CORRECTED VL IN AVMAge Male Female20-24 1.3% 1.0%25-34 0.4% 3.9%35-44 0.6% 1.4%45-54 0.2% 1.0%55-64 1.7% 3.1%65-74 1.7% 2.0%75+ 3.7% 4.7%

Source: Statistics Canada, CCHS public use microdata files.

TABLE 2–35: PREVALENCE OF VL FROM DR WITHIN DIABETIC AVM GROUPS

Age Male Female20-24 1.8% 1.4%25-34 0.5% 5.3%35-44 0.8% 1.9%45-54 0.3% 1.3%55-64 2.3% 4.2%65-74 2.3% 2.8%75+ 5.0% 6.4%

Source: Derived from Table 2–34.

Although the CCHS does not provide an estimate of diabetic prevalence in the AVM population, ICES (Glazier et al, 2007) reports that rates of diabetes among First Nation groups in Ontario are among the highest in the world, and are some three times higher than for the rest of the population. ICES also reports that diabetes in Ontario’s South Asian population is three times the general population. They also note the prevalence of diabetes in black Americans is twice as high as the general population, which might reasonably be assumed to apply also to black Canadians. Finally, ICES reports that the prevalence of diabetes in Toronto neighbourhoods is strongly correlated with the percentage of the population from Visible Minorities. Taken together, Access Economics has conservatively assumed that the rate of diabetes in the AVM population is twice that of the white population. Statistics Canada publishes rates of diabetes for the general population (Table 2–4). Doubling these rates thus yields an estimate of the prevalence of diabetes in the AVM population (Table 2–36).

TABLE 2–36: PREVALENCE OF DIABETES IN AVM POPULATION, 2005 (%)Age Male Female All12-14 0.0% 0.0% 0.6%15-19 0.6% 0.6% 0.6%20-24 1.8% 1.4% 1.6%25-34 1.8% 2.4% 2.2%35-44 4.2% 3.8% 4.0%45-54 10.0% 8.0% 9.0%55-64 23.6% 17.0% 20.2%65-74 34.6% 24.6% 29.2%75+ 33.6% 26.2% 29.2%Total 10.6% 8.8% 9.8%

Source: As per Table 2–4, and ICES (Glazier et al, 2007).

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Multiplying the prevalence of diabetes in the AVM population (Table 2–36) by the prevalence of VL in the AVM diabetic population (Table 2–35) provides the prevalence of AVM diabetics who have DR-induced VL (Table 2–37).

TABLE 2–37: ESTIMATED PREVALENCE OF DR-INDUCED VL IN AVMMale Female

20 to 24 0.03% 0.02%25 to 34 0.01% 0.13%35 to 44 0.03% 0.07%45 to 54 0.03% 0.11%55 to 64 0.55% 0.71%65 to 74 0.80% 0.68%75 and older 1.69% 1.67%

Source: Derived from earlier tables.

2.3.6 Summary of VL in AVM populations

Combining the prevalence of VL from DR (Table 2–37) with the prevalence estimates for the other eye diseases (Table 2–33) enables a completion of the estimates of VL by disease for the whole AVM population (Table 2–38). As noted above, the CCHS does not report VL by disease, only the prevalence of the diseases. However, it does report the total number of AVM who have under-corrected VL (Table 2–34). Self-reported VL for AVM was 0.8% for males and 2.0% for females. The estimates here, derived from ratios of diagnosed VL between races, are 0.5% for AVM males, and 0.7% for AVM females (Table 2–40).

49


TABLE 2–38: PREVALENCE OF VL IN AVM BY AGE, GENDER AND DISEASE

Males AMD Cataract DR Glaucoma RE/Other40-44 0.00% 0.03% 0.00% 0.05%45-49 0.00% 0.03% 0.00% 0.00%50-54 0.00% 0.00% 0.03% 0.00% 0.06%55-59 0.00% 0.18% 0.55% 0.00% 0.27%60-64 0.00% 0.06% 0.55% 0.00% 0.16%65-69 0.11% 0.31% 0.80% 0.54% 1.22%70-74 0.50% 2.40% 0.80% 1.01% 1.21%75-79 1.85% 2.11% 1.69% 0.40% 1.96%80-84 4.09% 6.41% 1.69% 1.87% 2.59%85-89 7.55% 6.76% 1.69% 1.41% 3.22%90+ 7.55% 11.77% 1.69% 1.31% 2.01%

Female AMD Cataract DR Glaucoma RE/Other40-44 0.00% 0.07% 0.00% 0.06%45-49 0.00% 0.11% 0.00% 0.02%50-54 0.00% 0.00% 0.11% 0.00% 0.13%55-59 0.00% 0.14% 0.71% 0.00% 0.47%60-64 0.00% 0.05% 0.71% 0.00% 0.30%65-69 0.14% 0.49% 0.68% 0.18% 0.39%70-74 0.53% 3.63% 0.68% 0.33% 0.89%75-79 1.66% 4.85% 1.67% 0.80% 2.48%80-84 3.13% 12.82% 1.67% 0.92% 2.92%85-89 5.02% 13.52% 1.67% 0.69% 3.63%90+ 5.02% 23.54% 1.67% 0.64% 2.26%

2.4 SUMMARY

A variety of data sources were used to construct a model of Canadian VL by age, gender, ethnicity, severity and type. There was found to be little difference in the prevalence of visually impairing eye conditions among white populations in US, Australian and European population eye health studies, so these studies (Congdon et al, 2004a and CERA, 2005) were used to estimate the prevalence of VL for white Canadians.

For AVM, self-reported data from the CCHS were used to estimate the prevalence of cataract, glaucoma and RE, with supplementation from Canadian academic studies and journal articles for DR and AMD, since these conditions are not covered in the CCHS. DR was estimated from other Canadian sources and AMD was estimated from the average prevalence rates for non-whites in the US. The risk of VL within each disease for AVM was derived from the risk for non-whites in the US. These data show that differences in the rates of VL from ‘disease x’ are related to differences in prevalence of that disease across ethnicities as well as differences in access to treatment and genetic factors that may affect progression of VL. Since the self-reported data do not distinguish between mild and medium levels of VL, the severity distribution is assumed to be the same for AVM as for whites (by disease).

In total, there were an estimated 816,951 Canadians with VL in 2007 (Table 2–39).

Of this total, 780,534 (95.5%) were white and 36,417 (4.5%) were AVM.

RE / Other is the main source of VL for the white population (68% of the total), and cataract is the main cause of VL in AVM (36% of the total).

50


For whites the second largest source of VL is cataract (15.5%) and, for the AVM population, DR is the second largest source (24.5% of the total).22

AVM have lower prevalence of VL for all diseases other than DR (Figure 2-29), largely due to lower prevalence of eye diseases at equivalent ages to whites, a younger age profile, and less likelihood of developing VL once they have contracted a given eye disease.

TABLE 2–39: PREVALENCE OF VL, BY CAUSE AND ETHNICITY, 2007All ethnicities White AVM

Number % total Number % total Number % totalAMD 89,241 10.9% 84,641 10.8% 4,380 12.0%Cataract 133,836 16.4% 120,685 15.5% 13,151 36.1%DR 29,920 3.7% 20,992 2.7% 8,928 24.5%Glaucoma 24,937 3.1% 22,565 2.9% 2,373 6.5%RE/Other 539,236 66.0% 531,650 68.1% 7,586 20.8%

All VL 817,171 100.0% 780,534 100.0% 36,417 100.0%Note: For corresponding prevalence rates, see Table 2–40 to Table 2–45.

FIGURE 2-29: PREVALENCE RATES OF VL, BY ETHNICITY AND CAUSE, 2007

0.3% 0.4%0.1% 0.1%

1.6%

2.5%

0.3%0.5%

0.1% 0.1%

2.0%

3.0%

0.1%0.2% 0.1% 0.0% 0.1%

0.6%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

AMD Cataract DR Glaucoma RE/Other All VI

Prev

alen

ce (%

)

All races White AVM

Note: Estimates are raw prevalence rates, not age-standardised, so low AVM figures reflect low average age.

The prevalence of VL is projected to increase from 2.5% of the population in 2007 to 4.0% in 2032 (Figure 2-30). In terms of numbers of people, there are projected to be almost twice as many Canadians with VL in 25 years than in 2007, with VL from cataract, AMD and glaucoma all projected to increase by more than 100% over the next 25 years (114%, 113% and 117% respectively).

22 As noted earlier, Canadian Aboriginals have some of the highest rates of diabetes in the world, and Asians have some three to six times the diabetes prevalence of whites.

51


Detailed tables underlying the projections in this section may be found in Appendix B. Summaries for 2007 are provided in Table 2–40 through to Table 2–45 at the end of this section.

FIGURE 2-30: PREVALENCE OF VL, BY CAUSE, 2007-2032

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

2031

2032

Prev

alen

ce (%

)

All VI Cataracts DR

Glaucoma AMD RE/Other

VL affects women more than men (Figure 2-31), reflecting greater longevity in females now and in the future. In 2007, females accounted for 58.4% of VL, by 2032, this will have fallen slightly to 56.3%.

FIGURE 2-31: PREVALENCE OF VL BY GENDER, 2007 TO 2032

0

100

200

300

400

500

600

700

800

900

1,000

2007 2010 2015 2020 2025 2032

Per

sons

with

vis

ual Im

pairm

ent

(000

)

Males Females

52


While the AVM share of the total population is rapidly increasing (recall Figure 2-13), the rise in this group’s share of VL at the end of the projection period is smaller than their increase in population share (Figure 2-33). This is partly due to AVM having a considerably younger age profile than the white population. It is also due to the assumption that the Visible Minorities population – which is mostly growing through migration – is not aging over the forecast period23.

FIGURE 2-32: PROJECTIONS OF VL, BY ETHNICITY, 2007 TO 2032

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

0

200

400

600

800

1,000

1,200

1,400

1,600

2007 2010 2015 2020 2025 2032

AVM

per

sons

with

visu

al im

pairm

ent

Whi

te p

erso

ns w

ith v

isual

impa

irmen

t ('0

00)

WhiteAVM

FIGURE 2-33: RELATIVE SHARE OF TOTAL VL, BY ETHNICITY, 2007 TO 2032

4.2%

4.3%

4.4%

4.5%

4.6%

4.7%

4.8%

4.9%

5.0%

5.1%

95%

95%

95%

95%

95%

95%

95%

95%

96%

96%

2007 2010 2015 2020 2025 2032

Whi

te p

erso

ns w

ith v

isual

im

pairm

ent (

'000

)

AVM

per

sons

with

visu

al

impa

irmen

t

White

AVM

23 This assumption is necessary as Statistics Canada does not disaggregate its growth forecasts for Visible Minorities by age cohorts. However, it is plausible.

53


TABLE 2–40: ALL VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total

0-4 0 0 0 0-4 0.00% 0.00% 0.00%5-9 0 0 0 5-9 0.00% 0.00% 0.00%10-14 0 0 0 10-14 0.00% 0.00% 0.00%15-19 0 0 0 15-19 0.00% 0.00% 0.00%20-24 0 86 86 20-24 0.00% 0.03% 0.01%25-29 0 24 24 25-29 0.00% 0.01% 0.00%30-34 0 24 24 30-34 0.00% 0.01% 0.00%35-39 0 87 87 35-39 0.00% 0.03% 0.01%40-44 9,369 207 9,577 40-44 0.89% 0.08% 0.72%45-49 4,964 64 5,028 45-49 0.43% 0.03% 0.37%50-54 16,752 173 16,924 50-54 1.66% 0.09% 1.40%55-59 27,740 1,102 28,842 55-59 2.99% 0.99% 2.78%60-64 21,291 805 22,096 60-64 2.92% 0.77% 2.65%65-69 34,347 2,207 36,555 65-69 6.38% 2.98% 5.97%70-74 35,808 3,112 38,920 70-74 8.19% 5.92% 7.94%75-79 56,857 2,380 59,237 75-79 15.51% 8.00% 14.95%

80-84 57,986 2,540 60,526 80-84 24.15% 16.65% 23.70%85-89 41,730 1,146 42,877 85-89 36.04% 19.11% 34.75%90+ 18,606 690 19,296 90+ 40.26% 28.81% 41.06%

All Males 325,451 14,646 340,097 All Males 2.5% 0.5% 2.1%

Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 49 49 20-24 0.0% 0.0% 0.0%25-29 0 347 347 25-29 0.0% 0.1% 0.0%30-34 0 345 345 30-34 0.0% 0.1% 0.0%35-39 0 205 205 35-39 0.0% 0.1% 0.0%40-44 9,080 389 9,469 40-44 0.9% 0.1% 0.7%45-49 4,895 271 5,166 45-49 0.4% 0.1% 0.4%50-54 16,903 487 17,390 50-54 1.7% 0.2% 1.4%55-59 28,374 1,568 29,942 55-59 3.0% 1.3% 2.8%60-64 21,967 1,182 23,148 60-64 2.9% 1.1% 2.7%65-69 36,264 1,715 37,979 65-69 6.4% 1.9% 5.8%70-74 40,146 3,895 44,041 70-74 8.2% 6.1% 7.9%75-79 71,038 4,232 75,270 75-79 15.5% 11.5% 15.2%

80-84 89,952 4,114 94,066 80-84 24.1% 21.5% 24.0%85-89 83,576 1,760 85,336 85-89 36.0% 25.4% 35.4%90+ 52,888 1,213 54,101 90+ 40.3% 31.0% 40.6%All Females 455,083 21,771 476,854

All Females 3.4% 0.7% 2.9%

All Persons 780,534 36,417 816,951

All Persons 3.0% 0.6% 2.5%

54


TABLE 2–41: CATARACT VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 783 198 980 55-59 0.1% 0.2% 0.1%60-64 78 63 141 60-64 0.0% 0.1% 0.0%65-69 873 229 1,102 65-69 0.2% 0.3% 0.2%70-74 3,173 1,261 4,434 70-74 0.7% 2.4% 0.9%75-79 8,692 626 9,319 75-79 2.4% 2.1% 2.4%80-84 13,186 978 14,164 80-84 5.5% 6.4% 5.5%85-89 10,086 375 10,462 85-89 8.7% 6.3% 8.5%90+ 7,010 334 7,344 90+ 15.2% 13.9% 15.6%


Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 801 166 967 55-59 0.1% 0.1% 0.1%60-64 80 58 138 60-64 0.0% 0.1% 0.0%65-69 921 450 1,371 65-69 0.2% 0.5% 0.2%70-74 3,557 2,334 5,892 70-74 0.7% 3.6% 1.1%75-79 10,860 1,791 12,651 75-79 2.4% 4.9% 2.6%80-84 20,455 2,458 22,914 80-84 5.5% 12.8% 5.8%85-89 20,201 969 21,170 85-89 8.7% 14.0% 8.8%90+ 19,927 861 20,788 90+ 15.2% 22.0% 15.6%All Females 76,803 9,088 85,891

All Females 0.6% 0.3% 0.5%

All Persons 120,685 13,151 133,836

All Persons 0.5% 0.2% 0.4%

55


TABLE 2–42: DR VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 86 86 20-24 0.0% 0.0% 0.0%25-29 0 24 24 25-29 0.0% 0.0% 0.0%30-34 0 24 24 30-34 0.0% 0.0% 0.0%35-39 0 87 87 35-39 0.0% 0.0% 0.0%40-44 0 87 87 40-44 0.0% 0.0% 0.0%45-49 0 55 55 45-49 0.0% 0.0% 0.0%50-54 881 53 933 50-54 0.1% 0.0% 0.1%55-59 1,130 610 1,740 55-59 0.1% 0.6% 0.2%60-64 1,141 575 1,717 60-64 0.2% 0.6% 0.2%65-69 879 593 1,472 65-69 0.2% 0.8% 0.2%70-74 447 421 869 70-74 0.1% 0.8% 0.2%75-79 1,623 503 2,125 75-79 0.4% 1.7% 0.5%80-84 1,881 258 2,138 80-84 0.8% 1.7% 0.8%85-89 792 94 886 85-89 0.7% 1.6% 0.7%90+ 270 48 318 90+ 0.6% 2.0% 0.7%


Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 49 49 20-24 0.0% 0.0% 0.0%25-29 0 347 347 25-29 0.0% 0.1% 0.0%30-34 0 345 345 30-34 0.0% 0.1% 0.0%35-39 0 205 205 35-39 0.0% 0.1% 0.0%40-44 0 206 206 40-44 0.0% 0.1% 0.0%45-49 0 232 232 45-49 0.0% 0.1% 0.0%50-54 889 224 1,112 50-54 0.1% 0.1% 0.1%55-59 1,155 842 1,997 55-59 0.1% 0.7% 0.2%60-64 1,177 794 1,971 60-64 0.2% 0.7% 0.2%65-69 928 616 1,544 65-69 0.2% 0.7% 0.2%70-74 502 435 937 70-74 0.1% 0.7% 0.2%75-79 2,028 616 2,643 75-79 0.4% 1.7% 0.5%80-84 2,917 320 3,237 80-84 0.8% 1.7% 0.8%85-89 1,586 120 1,706 85-89 0.7% 1.7% 0.7%90+ 768 61 829 90+ 0.6% 1.6% 0.6%All Females 11,950 5,411 17,360

All Females 0.1% 0.2% 0.1%

All Persons 20,992 8,928 29,920

All Persons 0.1% 0.1% 0.1%

56


TABLE 2–43: GLAUCOMA VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 0 0 0 55-59 0.0% 0.0% 0.0%60-64 0 0 0 60-64 0.0% 0.0% 0.0%65-69 885 402 1,288 65-69 0.2% 0.5% 0.2%70-74 879 532 1,410 70-74 0.2% 1.0% 0.3%75-79 1,246 118 1,364 75-79 0.3% 0.4% 0.3%80-84 3,643 285 3,928 80-84 1.5% 1.9% 1.5%85-89 1,533 78 1,611 85-89 1.3% 1.3% 1.3%90+ 568 37 605 90+ 1.2% 1.5% 1.3%


Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 0 0 0 55-59 0.0% 0.0% 0.0%60-64 0 0 0 60-64 0.0% 0.0% 0.0%65-69 935 164 1,099 65-69 0.2% 0.2% 0.2%70-74 985 209 1,194 70-74 0.2% 0.3% 0.2%75-79 1,556 297 1,853 75-79 0.3% 0.8% 0.4%80-84 5,651 177 5,828 80-84 1.5% 0.9% 1.5%85-89 3,069 50 3,119 85-89 1.3% 0.7% 1.3%90+ 1,615 24 1,639 90+ 1.2% 0.6% 1.2%All Females 13,812 920 14,731

All Females 0.1% 0.0% 0.1%

All Persons 22,565 2,373 24,937

All Persons 0.1% 0.0% 0.1%

57


TABLE 2–44: AMD VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 0 0 0 55-59 0.0% 0.0% 0.0%60-64 0 0 0 60-64 0.0% 0.0% 0.0%65-69 436 83 519 65-69 0.1% 0.1% 0.1%70-74 968 264 1,232 70-74 0.2% 0.5% 0.3%75-79 6,236 551 6,787 75-79 1.7% 1.9% 1.7%80-84 5,537 624 6,161 80-84 2.3% 4.1% 2.4%85-89 10,157 420 10,577 85-89 8.8% 7.0% 8.6%90+ 5,996 214 6,210 90+ 13.0% 8.9% 13.2%


Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 0 0 0 40-44 0.0% 0.0% 0.0%45-49 0 0 0 45-49 0.0% 0.0% 0.0%50-54 0 0 0 50-54 0.0% 0.0% 0.0%55-59 0 0 0 55-59 0.0% 0.0% 0.0%60-64 0 0 0 60-64 0.0% 0.0% 0.0%65-69 461 128 589 65-69 0.1% 0.1% 0.1%70-74 1,085 341 1,427 70-74 0.2% 0.5% 0.3%75-79 7,791 611 8,402 75-79 1.7% 1.7% 1.7%80-84 8,590 600 9,190 80-84 2.3% 3.1% 2.3%85-89 20,342 360 20,702 85-89 8.8% 5.2% 8.6%90+ 17,043 184 17,227 90+ 13.0% 4.7% 12.9%All Females 55,311 2,225 57,536

All Females 0.4% 0.1% 0.3%

All Persons 84,641 4,380 89,022

All Persons 0.3% 0.1% 0.3%

58


TABLE 2–45: RE/OTHER VISION LOSS, BY AGE, GENDER AND ETHNICITY, 2007Prevalent cases Prevalence rateMales White AVM Total Males White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 9,369 120 9,490 40-44 0.9% 0.0% 0.7%45-49 4,964 9 4,973 45-49 0.4% 0.0% 0.4%50-54 15,871 120 15,991 50-54 1.6% 0.1% 1.3%55-59 25,828 294 26,122 55-59 2.8% 0.3% 2.5%60-64 20,072 167 20,239 60-64 2.8% 0.2% 2.4%65-69 31,274 900 32,174 65-69 5.8% 1.2% 5.3%70-74 30,341 634 30,975 70-74 6.9% 1.2% 6.3%75-79 39,060 582 39,642 75-79 10.7% 2.0% 10.0%80-84 33,739 395 34,134 80-84 14.0% 2.6% 13.4%85-89 19,163 179 19,342 85-89 16.5% 3.0% 15.7%90+ 4,762 57 4,819 90+ 10.3% 2.4% 10.3%


Female White AVM Total Female White AVM Total0-4 0 0 0 0-4 0.0% 0.0% 0.0%5-9 0 0 0 5-9 0.0% 0.0% 0.0%10-14 0 0 0 10-14 0.0% 0.0% 0.0%15-19 0 0 0 15-19 0.0% 0.0% 0.0%20-24 0 0 0 20-24 0.0% 0.0% 0.0%25-29 0 0 0 25-29 0.0% 0.0% 0.0%30-34 0 0 0 30-34 0.0% 0.0% 0.0%35-39 0 0 0 35-39 0.0% 0.0% 0.0%40-44 9,080 184 9,264 40-44 0.9% 0.1% 0.7%45-49 4,895 39 4,934 45-49 0.4% 0.0% 0.4%50-54 16,015 263 16,278 50-54 1.6% 0.1% 1.3%55-59 26,418 560 26,978 55-59 2.8% 0.5% 2.5%60-64 20,709 330 21,039 60-64 2.8% 0.3% 2.4%65-69 33,020 358 33,378 65-69 5.8% 0.4% 5.1%70-74 34,017 575 34,592 70-74 6.9% 0.9% 6.2%75-79 48,803 917 49,720 75-79 10.7% 2.5% 10.0%80-84 52,338 559 52,897 80-84 14.0% 2.9% 13.5%85-89 38,378 260 38,638 85-89 16.5% 3.8% 16.0%90+ 13,535 83 13,617 90+ 10.3% 2.1% 10.2%All Females 297,207 4,129 301,336

All Females 2.2% 0.1% 1.8%

All Persons 531,650 7,586 539,236

All Persons 2.0% 0.1% 1.6%

59


3. HEALTH SYSTEM EXPENDITUREAfter ascertaining the prevalence of VL from the various eye disorders, costs to the Canadian economy can be calculated. Financial costs included direct health system expenditure (medicines, surgery, lenses, and so on) and indirect costs (for example, lower levels of employment for visually impaired people and time spent by caregivers for people with VL).

While available data from Canada are not sufficient to uniformly adopt a ‘top-down’ approach (that is, national expenditure on all forms of treatment for visually impairing eye conditions) or ‘bottom-up’ estimates (known costs and quantities of specific eye care procedures), using a combination approach enables a reasonable estimate of total health system expenditure.

3.1 TOTAL EXPENDITURE ON ‘VISION CARE’

The Canadian Institute for Health Information (CIHI) tracks health expenditure on its National Health Expenditure (NHEX) database, including expenditure on ‘vision care’. The vision care category includes expenditures for the professional services of optometrists and dispensing opticians, as well as expenditures for eyeglasses and contact lenses. Expenditure on vision care was nearly $3.5 billion in 200724, representing 2.2% (Figure 3-34) of all health system expenditure ($160.1 billion in 2007).

FIGURE 3-34: CANADIAN HEALTH SYSTEM EXPENDITURE, 2007 (% OF TOTAL)

Hospitals28.4%

Other Institutions10.4%

Physicians13.4%

Vision Care 2.2%

Other Professional Services8.6%

Drugs16.8%

Capital4.6%

Public Health5.8%

Administration3.6%

Other Health Spending6.1%

Source: CIHI NHEX.

Apart from differentiating the services of particular types of health professionals (eg, optometrists), the NHEX does not divide expenditure by disease category.

Expenditure on health care in Canada has been growing rapidly – considerably faster than Gross Domestic Product. After adjusting for inflation, health care spending grew at an average annual real rate of 3.8% between 1975 and 1991, by 0.8% per annum from 1991 to 1996 and by 5.1% from

24 Expenditure for 2007 ($3,483m) was still a provisional forecast at time of drafting.

60


1996 to 2003. However, expenditure on vision care has risen even faster, rising from 1.8% of the total in 1975 to 2.2% in 2007 (Figure 3-35).

FIGURE 3-35: EXPENDITURE ON VISION CARE, CANADA, 1975-2007

1,000

10,000

100,000

1,000,000

100

1,000

10,00019

75

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

Tota

l hea

lth e

xpen

ditu

re ($

m)

Visi

on c

are

expe

nditu

re ($

m)

Vision Care ServicesTotal

Source: CIHI NHEX.

NHEX data from earlier years (before 2007) provides more detail than are currently available for 2007. Total health system expenditure reported by the NHEX for Canada was $141.2 billion in 2005. The majority of this, $99.1 billion (or 70.1%) was publicly funded, with the remaining $42.2 billion (29.9%) privately funded.

The NHEX reports that in 2005, nearly all Canadian public expenditure (93.6%) came from Provincial and Territory governments. Only 4.3% came from the Federal Government, with municipal governments and worker’s compensation funds comprising the remaining 2.1%.

Households accounted for the majority (58.1%) of total private expenditure on health care in Canada in 2005. Private health insurance entities constituted 29.2%, and ‘other’ (including hospital non-patient revenue, capital expenditures for privately owned facilities and health research) made up the remaining 12.7%.

Expenditure on vision care totalled $3.19 billion in 2005. In 2003 when the total was $2.64 billion, the NHEX showed that private spending on vision care in Canada was $2.44 billion, whereas public spending only amounted to $200 million. Of private expenditure, households contributed $1.91 billion and private health insurance $0.53 million.

3.2 EXPENDITURE ON PARTICULAR EYE DISORDERS

While ‘vision care’ is only a small component of overall health system expenditure on visually impairing conditions, it can be supplemented from other sources. In a number of cases, detailed information about the costs of certain eye procedures are available. Less frequently, numbers of eye procedures performed are also available. Where both are available, ‘bottom up’ calculations of expenditure can be estimated.

61


CIHI’s National Grouping System (NGS) attempts to provide reasonably comparable and consistent statistics on the utilization, cost and distribution of physicians’ services for which payment was made on a fee-for-service basis by provincial and territorial medical care insurance plans. CIHI (2007) data on eye examinations and cataract surgery summed to around $144 million in 2004-05 (Table3–46). Assuming expenditure on these procedures has risen by the same amount as total health system expenditure, this figure would have risen to $153 million by 2007.

TABLE 3–46: TOTAL EXPENDITURE ON CERTAIN EYE PROCEDURES, 2004-05Procedure Number Average $/case Expenditure $m

Eye Examinations 373,148 $41.44 $15.5Cataract Surgery 284,523 $452.30 $128.7

Total 657,671 $219.15 $144.2Source: CIHI (2007). Note $/case is derived from the other two columns.

Additionally, some partial information is available on drug expenditure from Health Canada (2002a) The Economic Burden of Illness in Canada 1998. Drug expenditure on two categories of eye disorders – glaucoma and conjunctiva disorders – totalled $143.2 million in 1998 (Table 3–47). Given the NHEX shows expenditure on drugs has increased by 214% since then, proportionally, this figure in 2007 would be $307 million (Table 3–48).

TABLE 3–47: DRUG EXPENDITURE ON NERVOUS SYSTEM AND SENSE ORGAN DISORDERS, 1998

Disorder $m

Glaucoma 54.7Conjunctiva disorders 88.5Ear infections 92.7Parkinson’s disease 24.1Other nervous system and sense organ disorders 276.4

Sub-total for nervous system and sense organ disorders 536.4Total for all diseases 12,385.2

Source: Health Canada (2002a).

Health Canada (2002a) gives a breakdown of the ICD-10 block ‘Nervous System and Sense Organ Disorders’, of which vision conditions are a major component. Unfortunately Health Canada were unable to supply more detailed data than as provided in Table 3–48, to isolate the vision component.

TABLE 3–48: EXPENDITURE ON NERVOUS SYSTEM AND SENSE ORGAN DISORDERS (1998)$m % of total health system expenditure

Hospital Care 1,425.6 5.20%Drugs 536.4* 4.30%Physician Care 824.8 7.10%Research 35.7 0.20%

Total 2,822.5 3.36%Source: Health Canada (2002a). * Matches the Table 3-2 sub-total.

CIHI (2005) Exploring the 70/30 Split: How Canada’s Health System is Financed, provides quite detailed information on the costs of a selected range of hospital procedures. The only procedure listed there relevant to VL – ‘Retinal procedures’ – averaged $2,538 in 2003 (around half the cost of most procedures). Charts in the same document show that these costs can be broken down to

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provincial level. The CIHI website shows a casemix spreadsheet with the following reporting (Table3–49) of eye operations by volume in 2000-01. This, together with the above data on cost of retinal procedures, allows an estimate of the cost and quantity of retinal procedures (4,126 cases in 2000/01). A more detailed breakdown of hospital expenditures is not possible.

TABLE 3–49: FREQUENCY OF SELECTED HOSPITAL PROCEDURES (2001)25

Case Mix Description Volume FY00/01

Retinal procedures 4,126Orbital procedures 2,889Lens insertion 1,284Other ophthalmic dx 1,134Major eye infections 847Other intraocular procedures 715Other ophthalmic proc 492Extraocular procedures 289Iris and lens procedures 110Hyphema 95

Source: CIHI secure.cihi.ca/cihiweb/en/downloads/Casemix_ICDimpact_AppA_CMG_02_03.xls

For specialist consultations, data on Medicare rebates are available for some provinces. Rebates for ophthalmological procedures from the Ontario Ministry of Health and Long-Term Care’s Schedule of Benefits for Physician Services 2006 are shown in Table 3–50. However, for these data to be useful there is also a need to know the numbers of each procedure performed.

TABLE 3–50: REBATES FOR CERTAIN OPHTHALMOLOGICAL PROCEDURES IN ONTARIO (2006)Ophthalmological Listing Cost ($)A235 Consultation 71.30A935 Special surgical consultation (see General Preamble GP17) 132.50A236 Repeat consultation 45.85A233 Specific assessment 42.15A234 Partial assessment 22.45A237 Periodic Oculo-visual Assessment 42.15A115 Major eye examination 42.15A230 Orthoptic assessment 25.00A250 Retinopathy of prematurity assessment 120.00A252 Initial vision rehabilitation assessment 240.00A251 Special ophthalmologic assessment 120.00

Source: Ontario Ministry of Health and Long-Term Care’s Schedule of Benefits for Physician Services 2006.

Cruess et al (2007) provide a comprehensive coverage of the average costs involved in treating AMD in Canada (Table 3–51), which can be used with prevalence data to estimate the total cost of AMD.

TABLE 3–51: AVERAGE TREATMENT COSTS FOR NEOVASCULAR AMD (2005)Treatment Cost ($)

25 COS advise that it is ‘totally unbelievable’ that there are four times as many retinal procedures as lens insertions (and in Australia it is more like the other way round). Accordingly, information from this table is regarded as unreliable and not utilized for final costings. It is still included, however, as part of the census of information available from official sources in Canada.

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Verteporfin, one eye only $2,112Simultaneous verteporfin treatment, both eyes $2,266Intravitreal coriscosteroids, per eye $183Photodynamic therapy with intravitreal steroid injection $308

Source: Cruess et al (2007).

Ray et al (2005) provide costs for both cataract surgery and retinal laser treatment for DR in Canada of $1,323 and $709 in 2003. Interestingly, these procedures were substantially less expensive in Canada than the same operations in Australia - $2,061 and $2,237 respectively.26

Iskedjian et al (2003) conducted an Ontario-based costing analysis of glaucoma in Canada and estimated the total cost of procedures associated with the treatment of glaucoma to be $344 for mild, $420 for moderate, and $511 for severe forms of glaucoma in 2001. These estimates included the cost of the procedure itself, physician’s fee, assistant’s fee, and the anaesthetist’s fee. Costs associated with hospital resources and medications were not included.

3.3 TOTAL HEALTH SYSTEM EXPENDITURE

3.3.1 Health system expenditure, top down

This top down estimate relies primarily on two sources: Health Canada’s 2002 publication The Economic Burden of Illness in Canada 1998 and CIHI’s National Health Expenditure Database (NHEX), and is calculated as outlined below.

Total health system expenditure in 2007 was $160.1 billion dollars. Expenditure on ‘nervous system and sense disorders’ in 1998 was 3.36% (from Table 3–48) of health system expenditure (Health Canada, 2002a). However, health system expenditure as defined in this source only covers hospitals, physicians, drugs and research. Assuming nervous system and sense disorders are also responsible for the same ratio (3.36%) of the total health system expenditure reported for 2007 by the NHEX ($160.1 billion) then total health system expenditure on nervous system and sense disorders in 2007 would be $5.38 billion. This provides an upper limit on expenditure on VL (for the above categories).

Health Canada (2002a) does not provide any further breakdowns, except for drugs (Table 3–47). Within drugs there are a number of subcategories that can be attributable to VL (noting that the category ‘other’ accounts for the majority of expenditure). Specifically, expenditure on glaucoma and conjunctiva disorders can be attributed to VL, ear infections to other sense organ disorders, and Parkinson’s to nervous system disorders. Thus represented, VL accounts for 55.1% of such drug expenditure as it is able to be attributed to separately identified categories; other sense organ disorders (ear infections) account for 35.7% and nervous system disorders (Parkinson’s) account for 9.3%. It is assumed that expenditure in ‘other’ would have the same distribution between these identifiable categories.

Assuming that, if VL accounts for 55.1% of all drug expenditure on ‘nervous system and sense disorders’ then VL would also account for the same proportion of health system expenditure on nervous system and sense disorders, and 55.1% of $5.38 billion equals $2.97 billion. This provides an upper limit for VL expenditure under the hospital, research, physicians and drug categories.

The NHEX also provides explicit expenditure for the professional services category under ‘Vision Care’,27 which includes optometrists, ophthalmologists, glasses and contact lenses, of

26 In the original article, all costs were in Euros, converted to Canadian dollars at then prevailing exchange rates.

27 For total health system expenditure, the NHEX divides Professional Services is divided into two subcategories ‘Vision Care’ and ‘Other’.

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$3.48 billion. Adding vision care to the $5.38 billion estimate of expenditure on hospitals, physicians, drugs and research yields a total of $6.45 billion in 2007.

The NHEX further shows that expenditure on ‘Other institutions’ is composed of nursing homes (90%) and mental institutions (10%). Access Economics (2006) calculated that 3.0% of US nursing home patients had been institutionalized due to VL. Thus, 2.7% (=3.0% * 90%) of the total ‘other institutions’ of $16.7 billion (NHEX) is estimated to be due to VL, or $448.8 million.

This still leaves an amount to be calculated for public health, administration, capital, and other expenditure ‘not elsewhere classified’. These categories collectively account for 20% of total health system expenditure (Figure 3-34). Thus, given the categories already calculated account for 80% of health system expenditure, these remaining categories are equivalent to a quarter of those already calculated (=20% / 80%), or $1.7 billion

Thus, a top down estimate of health system expenditure on VL in Canada for 2007 is $8.64 billion.

TABLE 3–52: ESTIMATED VL HEALTH SYSTEM EXPENDITURE (TOP DOWN), 2007Type of cost Total ($m)Hospital 1,497.7Physicians 866.5Pharmaceuticals 563.5Vision Care (optometry, ophthalmology and lenses) 3,483.7Research 37.5Other Institutions 444.8Other (capital, public health, administration, other institutions and professional services)

1,740.3

Total $8,637.9

3.3.2 Health system expenditure, bottom up

For a bottom up approach, estimates were undertaken for each of the five major eye diseases, either for total expenditure, or by the categories covered under the top-down approach, but for each individual disease.

For AMD, Cruess et al (2008) estimated the total to society of AMD in Canada was $1.12 billion in 2005. For the average patient, medical costs accounted for over three quarters of this figure (76.7%) and non-medical costs (primarily aids, equipment and carers) the remainder (23.3%). Subtracting non-medical costs proportionally leaves health system expenditure of $858.7 million. As these estimates apply to 2005, allowing for cumulative inflationary increases of 4.7% yields a total for 2007 health system expenditure of $898.9 million.

For RE, given this is the only form of VL correctable by lenses, the assumption was made most of the NHEX category ‘vision care’ would be attributable to RE. Conversely, it was also assumed that RE required little in the way of hospital care, physicians, drugs or the other categories in Table 3–52. Thus, expenditure on RE would be around $3.48 billion.

For glaucoma, following the methodology adopted in the top-down approach, the ratio of glaucoma drug expenditure to total nervous drug expenditure (10.2%) was assumed to hold for glaucoma’s share of total ‘nervous system and sense organ disorders’ health system expenditure. Nervous system and sense disorders in turn were (3.36%) of total health system expenditure. This yields a total of $549 million for glaucoma.

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Total expenditure on cataract surgery is estimated at $136.6 million, taking the $128.7 million in 2004-05 from Table 3–46 and allowing for inflation to 2007. Assuming that most such surgery takes place in hospitals, then given hospitals account for 28.4% of total health system expenditure, if the same ratio holds for cataract, total health system expenditure for cataract would be $481 million.

For diabetic retinopathy (DR), given there is only one frequency of procedure number, which COS advise is not plausible, costs are assumed to be the same as the average for the other diseases ($6,875 per person per year), which for the total of 29,920 people with VL from DR, gives a total of $205.71 million.

Thus, estimating from the bottom up, total health system expenditure on VL was $5.62 billion in Canada in 2007. As with the top-down estimate, this figure needs to be scaled up to account for factors such as capital expenditure, research, public health and other unallocated health expenditure. For consistency, the same mark-up (25.2%) is used, giving a total bottom-up estimate of $7.04 billion.

3.3.2.1 SUMMARY

The bottom-up estimate above is around 18.5% lower than the top-down estimate derived earlier. Most of this difference would be due to the fact that the bottom-up estimate only includes the ‘big five’ eye diseases (cataract, DR, glaucoma, AMD, RE). For example, Maberley et al (2006) in their study of VL in one Canadian city found that 12% of VL was caused by visual pathway disease (which is not included in the bottom up estimates).

Accordingly, while Access Economics has a preference to err on the side of caution, in this case the top-down estimate is considered more reliable. Thus the total cost of VL-related health expenditure in Canada is estimated as $8,637.9 million in 2007. This equates to $10,570 per person with VL per annum.

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4. OTHER FINANCIAL COSTSIn addition to health system costs, VL also imposes a number of other important financial costs on society and the economy, including the following.

Productivity losses of people with VL comprise those from lower employment participation, absenteeism and/or premature mortality.

Carer costs comprise the value of care services provided in the community primarily by informal carers and not captured in health system costs.

Other costs comprise the cost of aids, home modifications and other pertinent financial costs not captured elsewhere.

Transfer costs comprise the deadweight loss (DWL) associated with government transfers such as taxation revenue forgone, welfare and disability payments.

It is important to make the economic distinction between real and transfer costs.

Real costs use up real resources, such as capital or labour, or reduce the economy’s overall capacity to produce goods and services.

Transfer payments involve payments from one economic agent to another that do not use up real resources eg, a disability support pension or taxation revenue.

Data on other financial costs are drawn from a variety of sources eg, the literature (focusing on Canadian literature but sometimes supplemented by other international material).

4.1 PRODUCTIVITY LOSSES

Productivity losses are the cost of production that is lost when people with VL are unable to work because of the condition. They may work less than they otherwise would (either being employed less, being absent more often or being less productive while at work) or they may die prematurely. This represents a real cost to the Canadian economy. Access Economics adopts a human capital approach to measurement of productivity losses in developed countries.

4.1.1 Employment participation

Some insight into the employment impact of VL is provided by CNIB (2005). A survey of people living with vision loss found that the employment rate among those of working age was only 24.7% compared to 67.6% for the general population of the same age (Table 4–54). The chances of being employed are thus almost two-thirds (64%) lower for someone who is visually impaired. In addition to 24.7% who were employed, 49.2% listed themselves as unemployed, while the remaining 26.1% were ‘retired’ or ‘other’ and are assumed to be not participating in the labour force. Thus, of those actively participating in the labour force, 67% of people with VL describe themselves as unemployed. Of those who were employed, 63% were working full time, but only 29% had a permanent position. Alternate data from the 2001 PALS indicates that the employment rate among those with VL was 32%. Given the PALS survey has a larger sample size than the CNIB survey, the former is preferred. On PALS data, people with VL are around half as likely to be employed as those with full sight (53% lower).

This reduced employment result was then combined with employment rates for each respective age-gender group (Table 4–54) to calculate, from the number of people with VL in that age group, how many would be unemployed. The lost productivity for those unemployed due to VL was then

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measured by the average weekly earnings (AWE) of $855.06 that they would have otherwise been earning (Table 4–53).28

TABLE 4–53: ESTIMATED AWE, BY AGE AND GENDER, 2007Age Male Female Persons15-19 $264.49 $192.03 $227.3520-24 $576.08 $493.65 $537.1325-34 $926.61 $686.58 $817.9235-44 $926.61 $686.58 $817.9245-54 $1,096.00 $670.28 $897.6355-59 $1,096.00 $670.28 $897.6360-64 $1,095.09 $681.15 $890.3865+ $1,095.09 $681.15 $890.38Total $1,036.21 $645.82 $855.06

Source: Derived from Statistics Canada Employment, Earnings and Hours, Cat No 72-002-XIB.

TABLE 4–54: PERCENTAGE OF POPULATION EMPLOYED, BY AGE AND GENDER

Age Male Female15-19 years 45% 49%20-24 years 73% 70%25-34 years 86% 78%35-44 years 88% 79%45-54 years 85% 78%55-64 years 64% 51%

Source: Statistics Canada, Labor force characteristics by age and sex http://www40.statcan.ca/l01/cst01/labor20a.htm

The annual cost of lost earnings due to reduced employment is thus estimated as $4.06 billion in 2007.

4.1.2 Absenteeism from paid and unpaid work

In addition to workforce separation, people with VL may be absent from work more often as a result of their impairment. Our literature search was unable to locate published works on such absenteeism rates for people with VL in Canada.

However, Access Economics (2006) calculated (from the National Health Interview Survey-Disability data set) that in the US, VL was shown to result in an additional 4.1 days off work per annum. This estimate could also be applied to Canada, noting it is small ($155 per person with VL) relative to the productivity cost associated with lower workforce participation.

In cases of absenteeism, employers often choose to make up lost production through overtime employment of another employee that attracts a premium on the ordinary wage. The overtime premium represents lost employer profits. On the other hand, the overtime premium also indicates how much an employer is willing to pay to maintain the same level of production. Thus, if overtime employment is not used, the overtime premium also represents lost employer profits due to lost production. While productivity remains at the same level, the distribution of income between wages and profits changes29. For this study it is assumed that the overtime rate is 40%30.

28 As Statistics Canada does not break down AWE for each age-gender group, these were estimated from the distribution in Australia, due to the similarities (see footnote Error: Reference source not found).

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According to traditional microeconomic theory (in particular the work of Gary Becker in the 1960s), people will work until they are indifferent between the marginal value of the income earned relative to the personal value of the time sacrificed that could be used for unpaid domestic work or leisure. However no-one else tends to value the individual's leisure similarly. The typical approach to overcome this problem is to value leisure time at a discounted proportion of earnings which takes into account taxes that reduce the effective income from work and restrictions on the amount of time that can be used for work (for both biological and governmental regulation reasons). Access Economics assumes that visually impaired people incur the same loss of time from unpaid work (‘leisure’) as from paid work, but that the value of this time is 30% of paid work.

Based on these parameters and the AWE for each age-gender group, Access Economics estimates that in 2007, the total cost of absenteeism due to VL is $231.7 million. Of this, $22.8 million is the workplace absenteeism cost borne by the employee, $122.5 million is the workplace absenteeism cost borne by the employer, and $86.5 million is the value of absenteeism from unpaid work.

4.1.3 Presenteeism

VL can also affect a person’s ability to work effectively while at work. Presenteeism can be estimated by multiplying the number of days worked with VL by the percentage reduction in effectiveness on days worked with VL. Workers with VL must have productivity reasonably close to their sighted counterparts; otherwise they would not continue to be employed. With the right equipment, they should be just as productive as anyone else. However, the CNIB survey found that around three-quarters (73.8%) of workers with VL indicated that their workplace was taking some measures to accommodate them; mostly in the form of adapted equipment, flexible scheduling and modified responsibilities. Around a quarter (23.5%) indicated that they did not receive job accommodation measures that they needed, with the greatest unmet need being for adaptive computers. Daum et al (2004) in a study of productivity and visual status in the US found that vision loss reduced productivity in the workforce by between 2.5% and 28.9%. Taking a simple average of an 15.7% reduction in productivity, and applying this to the 23.5% of VL workers without proper equipment, yields an estimated overall lower productivity for VL workers of 3.7%.

Such a low level of productivity highlights the significant impact of VL on employment outcomes.

Given these results, Access Economics estimates that in 2007, the total cost of ‘presenteeism’ (lower productivity while at work) due to VL is $133.9 million.

4.1.4 Premature mortality

The production loss arising from premature mortality associated with VL through falls and depression is calculated as the expected remaining lifetime earnings multiplied by the number of people who died prematurely who would otherwise have been employed. As discussed in Section 5.2.2, the estimated number of deaths due to VL is 313. Since most (98%) of these deaths are in the 75+ age group where employment rates are low, lifetime earnings lost are not large.

29 While the opportunity cost of any overtime employment of another employee is implicitly taken into account through the overtime premium, this methodology does not allow for the choice to use salaried or part-time employees to make up the production at ordinary or no additional wage costs. However given that workers are assumed to value their leisure time at 30% of their earnings, the difference in estimated economic costs if this choice is taken into account would be small – the only difference would be that ‘society’ would incur these costs rather than the ‘employer’.

30 Based on the lower bound of workplace injuries literature - NOHSC assumed an overtime rate of 40% (Access Economics 2004b).

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The estimated annual cost due to lost productivity from premature death due to VL is $3.4 million in 2007.

Premature death also leads to additional search and hiring costs for replacement workers. These are estimated as the number of people with VL who die prematurely (by age and gender) multiplied by their chance of being employed multiplied by the search and hiring cost brought forward three years (the search and hiring cost is estimated as 26 weeks at AWE and the three year bring forward reflects average staff turnover rates). Since premature mortality costs are very low, these costs are tiny.

In 2007, additional search and hiring costs are estimated at only $9,040 for people with VL, based on the present value of bringing forward three years of average cost of staff turnover (26 weeks at AWE).

4.1.5 Funeral costs

The ‘additional’ cost of funerals borne by family and friends of people with VL is based on the additional likelihood of death associated with VL in the period that the person experiences it. However, some people (particularly older people) would have died during this time anyway. Eventually everyone must die and thus incur funeral expenses – so the true cost is the cost brought forward (adjusted for the likelihood of dying anyway in a given year). The most recent official data on funeral costs from are from 1991 (Statistics Canada, 1998), at which point an average funeral cost around $3,510. Updating this to allow for inflation to 2007 yields a current cost of $4,301. (This roughly accords with the figure from the Australian Bureau of Transport and Road Economics (2000), which after allowing for inflation and conversion to Canadian dollars, equates to $3,541.)

The bring forward of funeral costs associated with premature death for people with VL is estimated at around $1.1 million in 2007.

4.2 DWL FROM TRANSFERS

Lost taxation revenue is considered a transfer payment, rather than an economic cost. However, raising additional taxation revenue does impose real efficiency costs on the Canadian economy, known as DWLs. Besides the cost of administering the taxation system costs, DWLs arise from the distortionary impact of taxes on workers’ work and consumption choices.

4.2.1 Lost taxation revenue

Reduced earnings due to reduced workforce participation, absenteeism and premature death will also have an effect on taxation revenue collected by Canadian Governments. As well as forgone income (personal) taxation, there will also be a fall in indirect (consumption) tax, as those with lower incomes spend less on the consumption of goods and services.

Personal income tax forgone is a product of the average personal income tax rate and the forgone income. With VL and lower income, there will be less consumption of goods and services, estimated up to the level of the disability pension. Without VL, it is assumed that consumption would comprise (on average) virtually all household income - based on Statistics Canada reports that Canadians only save 3% of their income (Chawla and Wannell, 2005). The indirect tax forgone is estimated as a product of the forgone consumption and the average indirect tax rate.

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The (Federal) Canadian Goods and Services Tax (GST) rate is 5%, however most Provinces also levy separate sales taxes. In fact in Canada there are three types of sales taxes: provincial sales taxes or PST, the federal Goods and Services Tax or GST, and the Harmonized Sales Tax or HST.

Every province except Alberta implements a Provincial Sales Tax or HST. The Yukon Territory, Northwest Territories and Nunavut do not have any type of regional sales tax.

The HST is used in certain provinces to combine the federal GST and the PST into a single, blended, sales tax. Currently, there is a 13% HST in the provinces of New Brunswick, Newfoundland, and Nova Scotia. The HST is collected by the Canada Revenue Agency, which then remits the appropriate amounts to the participating provinces.

Separate PST are collected in the provinces of British Columbia, Saskatchewan, Manitoba, Ontario, Quebec, and Prince Edward Island. Goods to which the tax is applied vary by province, as do the rates. Moreover, for those provinces whose provincial sales tax is applied to the combined cost and GST, provincial revenues decline or increase with respective changes in the GST.

TABLE 4–55: PROVINCIAL SALES TAXES

Province Rate NotesAlberta 0British Columbia 7% Alcohol 10%Saskatchewan 5% Alcohol 10%Manitoba 7%Ontario 8% Lodging 5%

Alcohol and entertainment at restaurants 10%Alcohol at retail stores 12%

Quebec 7.5% Also applied to Federal GST, so effectively 7.875%Prince Edward Island 10% Also applied to Federal GST, so effectively 10.5%

Source: www.taxtips.ca

From these sources it is possible to estimate taxation revenue forgone due to VL. Both Federal and Provincial direct taxes have progressive rates. For a Canadian on the average income of $40,082, total Federal income tax would be $6,166 at an average rate of 15.4%. Given the multiplicity of Provincial direct taxes, Quebec was chosen as being representative as it has one of the largest populations and its tax rates are roughly mid range. A Quebecois on an income of $40,082 would pay $2,551 in direct taxes at an average tax rate of 6.4%. These average taxation rates are sourced from the Canadian Revenue Authority.

For indirect taxes, although Federal GST is 5%, the numerous Provincial indirect taxes (Table 4–55) mean that, again, Quebec is selected as a representative Province, with its effective indirect tax of 7.875%.

Personal income tax forgone is then calculated as the product of the average personal income tax rate (21.8%) and the forgone income. With VL and lower income, there will be less consumption of goods and services, with the indirect taxation rate estimated as 12.9%.

Around $1.75 billion in lost potential tax revenue is estimated to be incurred in 2007, due to the reduced productivity of people with VL.

Lost taxation revenue is considered a transfer payment, rather than an economic cost per se.

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4.2.2 Social security payments

The CNIB (2005) study on the needs of blind or visually impaired people briefly covered their sources of income.

The CNIB study encompassed 352 adult client participants nation-wide with VL. Of these, 61% were female (213), and 39% were male (139), while 57% of adult participants were working age (21–64), and 43% were seniors (65+).

The most frequent source of income for all adult client participants was some form of government income supplement program (federal or provincial). However, unsurprisingly there were age related differences in the programs that were providing benefits. The vast majority of senior participants reported receiving a federal pension (91%), compared to only 26% of working age participants. Conversely, 41% of working age participants reported receiving provincial disability benefits, compared to only 6% of seniors. Income from employment was low overall (12% for all adult consumer participants), and again age made a difference. Of working age participants 24% reported income from employment or self-employment, compared to 2% of seniors. Seniors were more likely to report receiving a private pension (31%) than were working age participants (8%). Table 4–56 provides an overview of income sources for adult participants.

TABLE 4–56: INCOME SOURCES (CNIB)Income Source All Working Age Seniors Federal pension* 54% 26% 91%

Provincial disability benefits 26% 41% 6%Private pension 18% 8% 31%Private income 13% 8% 19%Employment 12% 19% 1%Spousal support 8% 9.5% 5%Self-employment 4% 5.4% 1.3%Family support 2.3% 3% 1.3%Other 8% 8% 8%

* Federal pensions included Old Age Pension, Disability Pension, and Veterans Pension.Source: CNIB (2005).

Publicly available data exist for social security spending and recipients in Canada – reported by Human Resources and Social Development Canada as part of its Social Security Statistics Canada and Provinces 1978-79 to 2002-03.31 Selected payments that people with VL may access are presented in Table 4–57 – these data refer to aggregate payments to all recipients rather than payments to people with VL only.

31 See: http://www.hrsdc.gc.ca/en/cs/sp/sdc/socpol/tables/page02.shtml (accessed Wednesday 6 February, 2008).

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http://www.hrsdc.gc.ca/en/cs/sp/sdc/socpol/tables/page02.shtml


TABLE 4–57: VL-RELATED SOCIAL SECURITY PAYMENTS AND BENEFICIARIES

Total payments

($000)Beneficiaries (number)

$/beneficiary

Old age security 20,464,192 3,941,039 5,193Veterans' and civilians' disability pensions 1,473,118 164,805 8,939Canada and Quebec pension plans 3,330,019 340,116 9,791Employment assistance for persons with disabilities 378,318Provincial welfare programs 20,552,751

Total 46,198,398Source: Human Resources and Social Development Canada, Social Security Statistics Canada and Provinces 1978-79 to

2002-03.

The data from Table 4–57 can be used to calculate the excess number of people with VL who receive payment relative to population norms. These excess usage rates can then be multiplied by the average payment rates to estimate the social security payments for people with VL.

CNIB (2005) did not include unemployment benefits as a source of income for the visually impaired. Presumably then, working age people with VL are either employed or on disability pension.

TABLE 4–58: EXCESS USAGE OF SOCIAL SECURITY PAYMENTS

Income Source Working Age

Usage % of total

population

Excess usage

VL working age pop

VL who get

benefit

Pop who get benefit

% Attributable

to VL

Federal pension* 26% 2% 24.4% 209,122 54,372 504,921 10.8%Provincial disability benefits

41% 8% 32.8% 209,122 85,740 2,577,363 3.3%

4.2.3 Deadweight losses

The welfare payments calculated immediately above are, like taxation revenue losses, not themselves economic costs but rather a financial transfer from taxpayers to the income support recipients. The real resource cost of these transfer payments is only the associated DWL.

DWLs refer to the costs of administering welfare pensions and raising additional taxation revenues. For any given fiscal position, invalid and sickness benefits must be financed through taxation. Although welfare payments and forgone taxation are not real costs (so should not be included in the estimation of total costs), it is still worthwhile estimating them as that helps us understand how the total costs of VL are shared between the taxpayer, the individual and other financiers.

DWL is the loss of consumer and producer surplus, as a result of the imposition of a distortion to the equilibrium (society preferred) level of output and prices. Taxes alter the price and quantity of goods sold compared to what they would be if the market were not distorted, and thus lead to some diminution in the value of trade between buyers and sellers that would otherwise be enjoyed (Figure4-36).

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FIGURE 4-36: DWL OF TAXATION

Price ($)

Output

Supply

Demand

Price plus Tax

Price

Taxation Revenue

Actual Quantity Supplied

Potential Quantity Supplied

Deadweight Loss (cost of raising taxation revenue)

Usher (2002) estimates the DWL of raising revenue in Canada at 20.2%.

Access Economics estimates that around $1.75 billion in DWL is incurred in 2007, due to the additional taxation required to replace that forgone due to lost productivity of people with VL and welfare payments. Of this, $1.2 billion is a result of the government-financed component of health system expenditures, $348 million is due to taxation revenue forgone and $185 million is due to welfare expenditures.

4.3 CARE AND OTHER ASSISTANCE

Carers are people who provide informal care to others in need of assistance or support. Most informal carers are family or friends of the person receiving care. Carers may take time off work to accompany people with VL to medical appointments, stay with them in hospital, or care for them at home. Carers may also take time off work to undertake many of the unpaid tasks that the person with VL would do if they did not have VL and were able to do these tasks.

A recent study focusing on AMD only rather than overall VL calculated the burden of neovascular AMD in the Canadian population (Cruess et al, 2007). This cross-sectional, observational analysis was conducted in relation to self-reported functional health, wellbeing and disease burden among elderly subjects in Canada with (n=67) and without (n=99) neovascular AMD.

Subjects with neovascular AMD reported significantly worse vision-related functioning and overall wellbeing than controls (adjusted mean scores on the NEI-VFQ-2532: 48.0 vs. 87.5) and significantly more depression symptoms than controls (Hospital Anxiety and Depression Scale: 5.8 vs. 4.3). The annual neovascular AMD cost per patient was $11,334, which is over eight times that of elderly subjects without neovascular AMD ($1,412). Over half of the neovascular AMD costs were direct medical costs.

32 National Eye Institute Visual Functioning Questionnaire (25 questions). See, for example, http://www.nei.nih.gov/resources/visionfunction/vfq_ia.pdf

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Subjects with neovascular AMD also reported more than twice the need for assistance with daily activities compared with controls (19% vs. 9%). This allows us to calculate the excess care required by people with AMD relative to the rest of the population – by taking the difference between the two figures.

FIGURE 4-37: COMPARISON OF ASSISTANCE WITH ACTIVITIES OF DAILY LIVING BETWEEN STUDY GROUPS

19%

13%

3%

5%

3%4%

0%

9%

4%

2%1%

4%5%

2%

Daily activities overall

Home care Other transportation

Administrative tasks

Self care Transportation for health care

Leisure activities

Neovascular AMD Control group


Cruess et al (2007) also reported unit costs for non-medical related costs of AMD with data sourced from the Canadian Management Information Systems database. These data relate to people with AMD only rather than people with VL as a whole.

The main unit cost categories were direct vision-related medical costs, direct non vision-related medical costs, and direct non-medical costs (living in government-sponsored assisted living facilities, assistance received for daily activities, and social benefits received). Given that other health-related costs data sources have already been identified in this study (see Sections 3 and 4), the most useful data from Cruess et al (2007) related to the non-medical costs.

After collecting the unit costs, annual utilisation costs were then calculated by multiplying the number of units consumed by the unit cost. Overall, people with AMD had much higher non-medical costs ($2,553.25) which included home care/living assistance compared to the control group ($601.02).

TABLE 4–59: ANNUAL DIRECT AMD NON-MEDICAL RELATED UTILISATION COSTS PER PERSON (2005$)Direct non medical related utilisation costs per person AMD ControlTotal living situation related costs $240.68 $0.00Total costs of assistance for daily activities received $2,312.57 $601.02Total $2,553.25 $601.02


Cruess (2007) provides an overview of carer costs for AMD ($2,553.25 per person per annum) and for an age-matched control group ($601.02). Thus, the difference between the two groups

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($1,952.23 pa) is the cost of care that is specific to AMD. Access Economics has assumed that additional care is not due to having a particular eye disease as such, so much as to the VL caused by that disease. AMD’s disability weight (0.235) is 1.6 times higher than the average disability weight across all eye diseases (0.145). So, factoring down, the expected care costs for people with VL – above their fully sighted counterparts – would be $1,208.99 per person per year. Thus, for the total visually impaired population of 0.82 million, annual carer costs attributable to VL is $0.63 billion.

Rehabilitation and library costs

According to CNIB, the cost of provision of rehabilitation services for people with vision loss in 2007 was $32.8 million. In addition, the cost of special library services for people with vision loss was $7.4 million. Only 23% of these funds are provided by government. The rest is provided by support from the public.

Also, there are two other significant organizations providing services in Quebec – the Institut Nazareth et Louis Braille and MAB-Mackay (the Montreal Association for the Blind and the Mackay Rehabilitation Centre). Financial information from most recent annual reports on their websites33

suggests costs relating to these organisations are estimated as $12.8 million and $8.8 million respectively in 2007.

In total, the rehabilitation and library costs are estimated as $61.8 million and total cost of care is estimated as $0.693 billion.

4.4 AIDS AND DEVICES

People who are visually impaired or blind require a variety of devices, special equipment and home modifications to function adequately and to enhance their quality of life.

The greater need for devices and home modifications due to VL and blindness has been established in international studies (for example, Brezin, 2005; Access Economics, 2004a).

In the Australian study, the cost of devices and modifications was estimated as A$318 to A$571 per visually impaired person on average in 2004. The French study estimated only additional utilization, not costs.

Two sets of supports are provided for people with low vision and those who are blind because of the different needs of these two populations. For people who are blind, support primarily involves assistance using non-visual sensory data. For those with low vision, supports primarily involve magnifying or enlarging, brightening and enhancing contrast in visual displays or cues.

CNIB is the primary source for devices for the visually impaired and, as a result, prices reported are from CNIB price lists for the period 2000-01, weighted by the number of items sold of each of the brands/models available. Volumes of sales were reported in the December 2003 Price Survey of Assistive Devices and Supports for Persons with Disabilities produced by the Department of Human Resources and Social Development.

These data are inflated to 2007 by Consumer Price Inflation and population growth. They provide a good indication of the types of aids and modifications used, as well as the volume in which they are used across Canada and their price.

33 http://www.mab.ca/ and http://www.inlb.qc.ca/apropos/ra2006-2007.aspx#s11

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4.4.1 Canes and accessories

Two different brands/types of canes were priced—a mobility (way-finding) cane and a support cane. Each is available in three identically priced models. In 2000, 1,278 canes were sold at an average price of $21.78.

The mobility cane folds, comes with a rubber tip grip bottom, handle and connecting elastics. The average price for the 626 mobility canes sold was $20.00.

The support cane is made of moulded plastic, has a height adjustment and a rubber tip grip bottom. A total of 652 of these were purchased at an average price of $23.50. These types of cane can also be used by some people with mobility limitations.

In addition, three frequently purchased accessories were priced.

Replacement cane elastics for the folding mobility canes—163 were purchased at a price of $0.30 each.

Roller tips used for some types of mobility canes (the cane slides on a ball bearing allowing continuous contact with the ground, providing an alternative method for way finding—a sweeping motion rather than the more common tapping motion)—163 of these were purchased at $11.00 each.

Flip-up ice spikes which replace grip bottoms on support canes—166 were purchased at a price of $8.80 each.

TABLE 4–60: CANES/ACCESSORIES FOR THE BLIND (2000-01$)Product Number

sold per

year

Average price

Cost per year (in

2000-01)

Canes 1,278 $21.78 $27,834.84 Way Finding Canes 626 $20.00 $12,520.00 Support Canes 652 $23.50 $15,322.00

AccessoriesFor Way finding Canes:

Replacement cane plastics 163 $0.30 $48.90 Roller Tips 163 $11.00 $1,793.00

For Support Canes:Ice Spikes (flip-up) 166 $8.80 $1,460.80

Sub total 1,770 n/a $31,144.70 Note: Numbers may not sum exactly due to rounding.

4.4.2 Writing aids/stationery

Writing and reading for the blind primarily uses the Braille system of embossed dot patterns. Braille embossers are devices designed to produce Braille writing on paper. They can be as simple as slates/frames and stylus or manual, Braille typewriters such as the Perkins Brailler. However, there are also more advanced computerized brailing devices such as the Mountbatten Brailler. There are also high speed computer Braille printers.

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4.4.2.1 BRAILLE SLATES/FRAMES AND STYLUSES

Braille slates/frames and stylus systems are used to manually emboss Braille dots. Braille slates are part of a frame such that a two-line slate can be stepped down a page with a hinge system to give a whole page of Braille. Plastic slates are lighter than metal ones but tend to have a lower life expectancy. Frames without hinges only work with a fixed size of paper, but are very popular as a highly portable note-taking device.

The stylus handle design significantly affects ease of use. The easier to use, large handle styluses, however, are less convenient to carry.

The weighted average price of the 16 slates commonly purchased at CNIB is $56.61. A total of 790 basic four-line plastic slates were sold at $6.50. However, this was the minimum price slate – and prices varied to a maximum of $158.50 for a 28-line, full page, heavy duty metal slate.

The average price of the six CNIB styluses available at CNIB is $6.00. The ‘Erasable’ stylus is priced at $21.50.

4.4.2.2 BRAILLE TYPEWRITERS

The average price of the five manual Perkins Braillers sold at CNIB is $1,393.20. The electric Perkins Brailler is priced at $1,750.

4.4.2.3 NOTE TAKERS

Note takers are computerized devices which have either standard or Braille-input keyboards. They usually have built-in speech output and/or Braille displays. They may be either palmtop or laptop devices. Standard-key note takers are used by persons with vision impairment, Braille note takers by persons who are blind.

Common features that come with note takers include word processing, diary, telephone directory, database and communications functions, and plugs which allow the user to connect peripheral devices such as printers, modems and Braille embossers.

The note taker available at CNIB provides a Braille-input keyboard and Braille display/computer output at a price of $5,365.

4.4.2.4 COMMON STATIONERY

Three types of Braille paper were priced. Each is rawhide tag manila and regular weight, and contains approximately 250 sheets per package. The average price paid for 1,094 purchases of the best selling Braille paper was $24.34.

In addition, CNIB sells a number of Braille calendars. In 2000-01, 532 were sold at a price of $2.00.

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TABLE 4–61: WRITING AND STATIONERY ITEMS (2000-01$)

Product Number sold per year

Average price

Cost per year (in

2000-01)Braille Paper (250 sheet package) 1,094 $24.34 $26,627.96 8.5 x 11 inches 560 $14.25 $7,980.00 11 x 11 inches 322 $17.75 $5,715.50 Computer paper, 12.5 x 11 Cerlox 212 $61.00 $12,932.00 Embossing Sheets 1,319 $3.00 $3,957.00 Braille Calendar 532 $2.00 $1,064.00

Total 2,945 n/a $36,783.50 Note: Numbers may not sum exactly due to rounding.

4.4.3 Variable speed tape recorders

A total of 12 cassette recorders were available from CNIB at an average price of $263.33. Prices varied from a minimum of $62.50 for a portable to $528.50 for a large, desk-top model. Most prices were near or at the overall average.

4.4.4 Computer voice synthesizer software

Five types of common computer software used by people who are blind are available from CNIB. Three of these convert data from either a file or a screen display to voice.

The average price of this software was $1,328.33. Two also included scanning capacity and convert written documents to computer files, as well as providing a voice synthesizer. The average price of these two packages was $1,795. These software packages can also be used with electronic Braille display systems (see next sub-section).

4.4.5 Electronic Braille display systems

An electronic Braille display system is a device designed to present computer screen text as Braille. A Braille display uses a series of electronic ‘pins’, which are either in the up or down position. Text on the screen is displayed as Braille through the pattern of up and down pins. Braille displays make excellent computer access devices for Braille-literate persons but are very expensive. The model available at CNIB is priced at $18,708.

4.4.6 Talking time pieces

Three types of time pieces were priced—talking clocks, wrist watches and a talking key chain. All prices include batteries.

A total of 1,406 talking clocks were purchased in 2000 at an average price of $20.65. The cost of the four different devices ranged from a low of $14.95 to a high of $28.50.

In 2000, a total of 4,650 talking wrist watches were purchased, at an average price of $19.24. Four different brands were commonly sold, varying from a price of $9.00 to a high of $65.00. Price varies considerably with watch style and features. For example, the more expensive watches have a gold or silver casing and choice of alarm sounds, while the lower range watches are encased in plastic.

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Talking time-keeping key chains cost an average of $11.00 and in 2000, 1,652 were sold.

TABLE 4–62: TALKING TIME PIECES (2000-01$)


Average price

Cost per year (in 2000-01)

Talking clocks 1,278 $21.78 $27,834.84 Talking wrist watches 4,650 $19.24 $89,466.00 Talking key chain 1,652 $11.00 $18,172.00 Total 7,580 n/a $135,472.84

Note: Numbers may not sum exactly due to rounding.

4.4.7 Sunglasses with non-corrective lenses

A total of 4,570 regular sunglasses were sold by CNIB in 2000 at an average price of $12.35. Sunglasses with UV protection were most popular. A total of 3,544 pairs were sold in 2000 at an average price of $13.00. The remaining 631 pairs of regular sunglasses were sold at $8.00.

TABLE 4–63: SUNGLASSES WITH NON-CORRECTIVE LENSES (2000-01$)


Average price


Sunglasses with UV protection 3,544 $13.00 $46,072.00 Regular sunglasses 631 $8.00 $5,048.00 Total 4,175 n/a $51,120.00

4.4.8 Hand held magnifiers

Magnifiers vary in strength and can come with small lights or ‘illuminators’. The average price of the 4,531 magnifiers sold in the year 2000 by CNIB was $33.70. At one end of the spectrum in this group are simply-designed, light, plastic magnifiers, which are priced in the $9.50-$14.50 range. At the other end are more solidly built models with glass lenses and/or illuminators, which are priced in the $43.50 to $50.00 range.

Magnifying sheets were also priced. These are plastic covers that fit over and magnify book or newspaper pages. A total of 2,180 sheets were sold in 2000 at a price of $2.20.

TABLE 4–64: HAND HELD MAGNIFIERS (2000-01$)


Average price


Magnifiers/hand readers 4,521 $33.70 $152,357.70Total 4,521 n/a $152,357.70

4.4.9 Video magnifiers/CCTVs

Screen magnifiers enlarge what is displayed on a computer monitor so people with vision problems can read the text on the screen. Closed Circuit Televisions (CCTVs) are devices that use a camera

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to magnify printed text and images placed under it. These are then presented enlarged on a television screen or computer monitor.

CNIB has two electronic video magnifiers that connect to an ordinary TV. The black and white only magnifier is priced at $1,119, while the colour model costs $1,499. CNIB also has a number of full CCTV systems, which include the monitor and TV screen and which can be connected to a computer. The average price of the black and white CCTVs offered is $2,875 and the colour CCTVs have an average price of $4,348.

4.4.10 Screen magnification software

Screen magnification software significantly enlarges screen text and graphics to a size that a vision impaired users can easily view. CNIB offers two such products at an average price of $814.50

4.4.11 Other aids for the sight impaired

4.4.11.1 STATIONERY

Three different writing pads with bolded lines were priced. These pads include 100 white sheets of black thick lined writing paper. In total, 1,200 pads were purchased in 2000, each at $3.80. In addition, 10,829 large print calendars were purchased at a price of $2.00.

TABLE 4–65: OTHER STATIONERY (2000-01$)


Average price


Writing pads 1,200 $3.80 $4,560.00 Large print calendars 10,829 $2.00 $21,658.00 Total 12,029 n/a $26,218.00

4.4.11.2 LARGE BUTTON TELEPHONES

Two prices for large button telephones with high sales volumes were obtained from CNIB price list. The first model phone also has speaker phone capacity. A total of 244 of these phones were sold in 2000 at a price of $33.00.

The second phone provides features for persons who are also hearing impaired—a hearing aid attachment and an adjustable very loud ringer. In 2000, 226 of these were sold at $70.00.

TABLE 4–66: LARGE BUTTON TELEPHONES (2000-01$)


Average price


Phone with speaker phone capacity 244 $33.00 $8,052.00 Phone for hearing impaired 226 $70.00 $15,820.00 Total 470 n/a $23,872.00

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4.4.12 Summary of aids and devices

Overall, available CNIB data on prices and volumes show that there was around $456,968.74 spent on vision impairment-related aids and devices (Table 4–67) in 2000-01. In today’s dollars that would equate to around $524,046.72 (after inflating by the Consumer Price Index).

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TABLE 4–67: SUMMARY OF AIDS AND DEVICES (2000-01$)Product Number

sold per year

Average price

Cost per year

(in 2000-01)

Canes 1,278 $21.78 $27,834.84 Way Finding Canes 626 $20.00 $12,520.00 Support Canes 652 $23.50 $15,322.00 Accessories for Way Finding CanesReplacement cane plastics 163 $0.30 $48.90 Roller Tips 163 $11.00 $1,793.00 Accessories for Support CanesIce Spikes (flip-up) 166 $8.80 $1,460.80 Sub total 1,770 n/a $31,144.70Braille slates 790 $6.50 $5,135.00 Braille Paper (250 sheet package) 1,094 $24.34 $26,627.96 8.5 x 11 inches 560 $14.25 $7,980.00 11 x 11 inches 322 $17.75 $5,715.50 Computer paper, 12.5 x 11 Cerlox 212 $61.00 $12,932.00 Embossing Sheets 1,319 $3.00 $3,957.00 Braille Calendar 532 $2.00 $1,064.00 Sub total 2,945 n/a $36,783.50Talking clocks 1,278 $21.78 $27,834.84 Talking Wrist Watches 4,650 $19.24 $89,466.00 Talking Key Chain 1,652 $11.00 $18,172.00 Sub total 7,580 n/a $135,472.84Magnifiers/Hand Readers 4,521 $33.70 $152,357.70 3.5-4.4X magnifier 1,514 $32.52 $49,235.28 5X–11X magnifier w/light 1,076 $43.50 $46,806.00 Sub total 4,521 n/a $152,357.70 Sunglasses with UV protection 3,544 $13.00 $46,072.00 Regular sunglasses 631 $8.00 $5,048.00 Sub total 4,175 n/a $51,120.00Writing pads 1,200 $3.80 $4,560.00 Large print calendars 10,829 $2.00 $21,658.00 Sub total 12,029 n/a $26,218.00 Phone with speaker phone capacity 244 $33.00 $8,052.00 Phone for hearing impaired 226 $70.00 $15,820.00 Sub total 470 n/a $23,872.00Total $456,968.74

The above data are supplemented by estimates of volumes data on: Braille slates/frames and styluses; Braille typewriters; note takers; variable speed tape recorders; computer voice synthesiser

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software; electronic Braille display systems; video magnifiers/CCTVs; and screen magnification software. Volume data were estimated by using US usage per person data from Access Economics (2006).

These additional devices added $15.1 million for CNIB clients, resulting in an overall total for CNIB aids and modifications of $15.6 million.

TABLE 4–68: ESTIMATES OF ADDITIONAL AIDS AND DEVICES

Product Number sold per

year

Average price

Cost per year

(in 2000-01)

Stylus 835 6 $5,012 Erasable stylus 835 21.5 $17,959 Braille typewriter 835 1750 $1,461,742 Note takers 835 5365 $4,481,282 Variable speed tape recorders 835 263.33 $219,955 Computer voice synthesisers 281 1328.33 $372,977 Electronic Braille display systems 281 18708 $5,252,954 Video magnifiers (black and white) 281 1119 $314,200 CCTVs (black and white) 281 2875 $807,261 Screen magnification software 281 814.5 $228,701 Total $13,162,042 Total (inflated to 2007$) $15,094,084

Using an active CNIB client base of 42,000 people this translates to $371.86 per person with VL.

Multiplying this by the number of people with VL gives us a total cost of aids and modifications of $303.9 million. This cost has been allocated equally between individuals, family and friends, government, employment and society / other (health insurance entities).

4.5 SUMMARY OF OTHER FINANCIAL COSTS

In total, the non-health related financial costs of VL are estimated to be around $7.1 billion in 2007.

TABLE 4–69: SUMMARY OF OTHER FINANCIAL COSTS OF VL, 2007 $ millionProductivity costs 4431 Carer costs 693 Aids and modifications, funerals 305 DWL ,1,757 Total other financial costs 7,186

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5. BURDEN OF DISEASE The main cost of VL is the loss of wellbeing and quality of life that it entails. Access Economics adopts ‘burden of disease’ methodology in order to quantify this substantial cost component. This methodology was developed by the World Health Organization, the World Bank and Harvard University to comprehensively measure mortality and disability from diseases, injuries and risk factors in 1990, projected to 2020 (Murray and Lopez, 1996). The approach is non-financial, where pain, suffering and premature mortality are measured in terms of Disability Adjusted Life Years (DALYs), with 0 representing a year of perfect health and 1 representing death (the converse of a QALY or ‘quality-adjusted life year’ where 1 represents perfect health). The DALY approach has been successful in avoiding the subjectivity of individual valuation and is capable of overcoming the problem of comparability between individuals and between nations. This report treats the value of a life year as equal throughout the lifespan.

5.1 WILLINGNESS TO PAY AND THE VALUE OF A LIFE YEAR

5.1.1 Measuring burden: DALYs, YLLs and YLDs

In the last decade a non-financial approach to valuing human life has been derived, where loss of wellbeing and premature mortality – called the ‘burden of disease and injury’ – are measured in terms of Disability Adjusted Life Years, or DALYs. This approach was developed by the World Health Organization (WHO), the World Bank and Harvard University for a study that provided a comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990, projected to 2020 (Murray and Lopez, 1996). Methods and data sources are detailed further in Murray et al (2001) and the WHO continues to revisit the estimates for later years.

A DALY of 0 represents a year of perfect health, while a DALY of 1 represents death. Other health states are attributed values between 0 and 1 as assessed by experts on the basis of literature and other evidence of the quality of life in relative health states. For example, the disability weight of 0.18 for a broken wrist can be interpreted as losing 18% of a person’s quality of life relative to perfect health, because of the inflicted injury. Total DALYs lost from a condition are the sum of the mortality and morbidity components – the Year(s) of Life Lost due to premature death (YLLs) and the Year(s) of healthy life Lost due to Disability (YLDs).

The DALY approach has been successful in avoiding the subjectivity of individual valuation and is capable of overcoming the problem of comparability between individuals and between nations, although some nations have subsequently adopted variations in weighting systems, for example age-weighting for older people. This report treats the value of a life year as equal throughout the lifespan.

As these approaches are not financial, they are not directly comparable with most other cost and benefit measures. In public policy making, it is often desirable to apply a monetary conversion to ascertain the cost of an injury, disease or fatality or the value of a preventive health intervention, for example, in cost benefit analysis. Such financial conversions tend to utilise ‘willingness to pay’ or risk-based labour market studies as described in the next section.

5.1.2 Willingness to pay and the value of a statistical life year

The burden of disease as measured in DALYs can be converted into a dollar figure using an estimate of the Value of a ‘Statistical’ Life (VSL). As the name suggests, the VSL is an estimate of the value society places on an anonymous life. Since Schelling’s (1968) discussion of the

85


economics of life saving, the economic literature has focused on willingness to pay (WTP) – or, conversely, willingness to accept (WTA) – measures of mortality and morbidity, in order to develop estimates of the VSL.

Estimates may be derived from observing people’s choices in situations where they rank or trade off various states of wellbeing (loss or gain) either against each other or for dollar amounts eg, stated choice models of people’s WTP for interventions that enhance health or WTA poorer health outcomes or the risk of such states. Alternatively, risk studies use evidence of market trade-offs between risk and money, including numerous labour market and other studies (such as installing smoke detectors, wearing seatbelts or bike helmets and so on).

The extensive literature in this field mostly uses econometric analysis to value mortality risk and the ‘hedonic wage’ by estimating compensating differentials for on-the-job risk exposure in labour markets; in other words, determining what dollar amount would be accepted by an individual to induce him/her to increase the probability of death or morbidity by a particular percentage. Viscusi and Aldy (2002), in a summary of mortality studies, find the VSL ranges between US$4 million and US$9 million with a median of US$7 million (in year 2000 US dollars), similar but marginally higher than the VSL derived from studies of US product and housing markets. They also review a parallel literature on the implicit value of the risk of non-fatal injuries.

Weaknesses in the WTP approach, as with human capital approaches to valuing life and wellbeing, are that there can be substantial variation between individuals. Extraneous influences in labour markets such as imperfect information, income/wealth or power asymmetries can cause difficulty in correctly perceiving the risk or in negotiating an acceptably higher wage in wage-risk trade off studies, for example.

As DALYs are enumerated in years of life rather than in whole lives it is necessary to calculate the Value of a ‘Statistical’ Life Year (VSLY) based on the VSL. This is done using the formula:34

VSLY = VSL / Σi=0,…,n-1(1+r)i

Where: n = years of remaining life, and r = discount rate.

Clearly there is a need to know n (the years of remaining life), and to determine an appropriate value for r (the discount rate). There is a substantial body of literature, which often provides conflicting advice, on the appropriate mechanism by which costs should be discounted over time, properly taking into account risks, inflation, positive time preference and expected productivity gains. In reviewing the literature, Access Economics (2008) found the most common rate used to discount healthy life was 3%, perhaps the most eminent sources being Nordhaus, 2002 (Yale); Murphy and Topel, 2005 (University of Chicago); Cutler and Richardson, 1998 (Harvard); WHO, 2002; Aldy and Viscusi, 2006). This report assumes a discount rate for future streams of health in Canada of 3%. Further it is assumed that on average people have 40 years of life remaining.35

34 The formula is derived from the definition: VSL = ΣVSLYi/(1+r)^i where i=0,1,2….nwhere VSLY is assumed to be constant (i.e. no variation with age).

35 This assumption relates to the average years of life remaining for people included in VSL studies, not the years of life remaining for people with VL.

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Access Economics (2008a) identified 16 Canadian VSL studies (Table 5–70). Converting the study findings into 2007 Canadian dollars, the average of VSL estimates was $4.66 million 36. A discount rate of 3% was applied to calculate the 2007 Canadian VSLY at $195,837.

TABLE 5–70: VALUE OF A STATISTICAL LIFE IN CANADIAN STUDIES ($ MILLION)

Authors Year Currency Study Area Lowest estimate

Highest estimate

Single/ average estimate

VSL in 2007 $CAN

Belhadji 1994 CAD Transport 1.2 1.6Meng and Smith 1990 USD

Occupational Risk 1.2 2.1

Transport Canada 1996 USD Transport 0.4 3.2 1.8 2.7Krupnick et al. 2000 CAD Health 2.5 2.9

Viscusi 2005 USDOccupational Risk 3.9 4.7 2.4 3.0

Alberini et al. 2002 USD

Occupational Risk 0.5 0.9 2.4 3.3

Alberini et al. 2002 USD

Occupational Risk 1.3 3.7 2.4 3.3

Meng and Smith 1999 USD


Hara Associates 2000 USD Health 1.7 5.7 2.4 3.5Miller 2000 USD Mixed 2.1 3.1 2.5 3.6Martinello and Meng 1992 USD


Dionne and Lanoie 2002 CAD Mixed 4.7 5.3

Meng 1989 USDOccupational Risk 4.0 7.6

Vodden et al. 1994 CAD


Cousineau et al. 1991 USD


Bellavance et al. 2007 USD Mixed 9.2 11.2Average 4.7

5.2 BURDEN OF DISEASE FROM VISION LOSS

5.2.1 Disability weights

Disability weights for mild, moderate and severe VL are based on the Dutch weights from the global burden of disease study (Murray and Lopez, 1996). These are:

0.020 for mild VL;

0.170 for moderate impairment; and

36 Figures converted to $2007 Canadian using OECD Purchasing Power Parity rates. One additional study (Lanoie et al, 1995) was rejected as an outlier beyond reasonable parameters, given its VSL estimate was $37.5 million.

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0.430 for severe impairment (blindness).

Section 1.2 presents the distribution of severity for each of the major eye diseases. To derive a total for Canada, these individual disease distributions were weighted by their overall prevalence. This yields an average disability weighting for Canadian VL of 0.093.

The burden of disease is thus calculated on a prevalence basis from the prevalence estimates from Section 2.4, together with disability weights, for the year 2007.

5.2.2 Deaths from VL

The Australian Institute of Health and Welfare (Begg et al, 2007) estimates that in Australia in 2003, the visually impaired population numbered 510,761, and that the number of deaths due to that VL was 163. Given the number of visually impaired persons in Canada in 2007 is 817,171 on a pro-rata basis, the expected number of deaths caused by VL was 261.

5.2.3 Years of life lost due to disability

Based on the disability weight outlined above and the total number of people experiencing VL, the YLD for VL has been calculated by gender (Table 5–71), for the year 2007.

In total, YLD for VL was an estimated 75,891 DALYs in 2007.

TABLE 5–71: ESTIMATED YEARS OF HEALTHY LIFE LOST DUE TO DISABILITY (YLD), 2007 (DALYS)

Estimated disability weight Prevalence YLD

Males 0.093 340,097 31,572Females 0.093 476,854 44,268

5.2.4 Years of life lost due to premature death.

Based on the relative risk of mortality due to VL outlined above, it is estimated that there are around 261 deaths per year due to VL. YLL were estimated from the age-gender distribution of deaths by the corresponding YLL for the age of death in the Standard Life Expectancy Table (West Level 26) with a discount rate of 3% and no age weighting.

In total, YLL for VL was an estimated 1,467 DALYs in 2007.

TABLE 5–72: YEARS OF LIFE LOST DUE TO PREMATURE DEATH (YLL) DUE TO VL, 2007

15-29 30-39 40-49 50-59 60-69 70-79 80+ TotalMales 0 0 4 22 58 181 359 623Females 0 0 2 15 38 153 635 844Persons 0 0 6 37 96 334 993 1,467

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5.3 TOTAL DALYS DUE TO VL

The overall loss of wellbeing due to VL is estimated as 77,306 DALYs.

Figure 5-38 illustrates the YLD and YLL components by age and gender. The greatest impact of VL is in old age, reflecting the physiology of VL and higher YLD due to the large number of Canadians with VL in this cohort.

FIGURE 5-38: LOSS OF WELLBEING DUE TO VL (DALYS), BY AGE AND GENDER, 2007

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

0-4

5-9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85-8

9

90+

DAL

Ys

Age Groups

Female YLL

Male YLL

Female YLD

Male YLD

Multiplying the number of DALYs by the VSLY ($195,837) provides an estimate of the dollar value of the loss of wellbeing due to VL.

The estimated gross cost of lost wellbeing from VL is $15.2 billion in 2007.

Bearing in mind that the wage-risk studies underlying the calculation of the VSL take into account all known personal impacts – suffering and premature death, lost wages/income, out-of-pocket personal health costs and so on – the estimate of $15.2 billion should be treated as a ‘gross’ figure. However, costs specific to VL that are unlikely to have entered into the thinking of people in the source wage/risk studies should not be netted out (e.g. publicly financed health spending, care provided voluntarily). The results after netting out are presented in Table 5–73.

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TABLE 5–73: NET COST OF LOST WELLBEING, $MILLION, 2007

Gross cost of wellbeing 15,200Less health costs borne out-of-pocket 1,499Less individual production losses net of tax 2,847Less other indirect costs borne out-of-pocket 61Plus transfers to people with VL 917Net cost of lost wellbeing 11,710

The estimated net cost of lost wellbeing from VL is $11.7 billion in 2007.

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6. SUMMARYIn 2007, the financial cost of VL was $15.8 billion (Table 6–74). Of this:

$8.6 billion (54.6%) was direct health system expenditure;

$4.4 billion (28.0%) was productivity lost due to lower employment, absenteeism and premature death of Canadians with VL;

$1.8 billion (11.1%) was the DWL from transfers including welfare payments and taxation forgone;

$0.7 billion (4.4%) was the value of the care for people with VL; and

$305 million (1.9%) was other indirect costs such as aids and home modifications and the bring-forward of funeral costs.

Additionally, the value of the lost wellbeing (disability and premature death) was a further $11.7 billion.

TABLE 6–74: VL, TOTAL COSTS BY TYPE OF COST AND BEARER, 2007

Individuals Family/Friends

Federal Government

Provincial Governments Employers Society/

Other Total

Burden of disease 11,710 0 0 0 0 0 11,710.4Health system costs 1,499 0 388 5,670 0 1,081 8,637.9Productivity costs 2,847 0 886 619 80 0 4,431.4Carer costs 0 413 218 0 0 62 692.8Other Indirect costs 61 62 0 61 61 61 304.9Deadweight losses 0 0 0 0 0 1,757 1,757.0Transfers -917 0 917 0 0 0 0Total financial costs 3,490 474 2,409 6,350 141 2,960 15,824Total costs including burden of disease 15,200 474 2,409 6,350 141 2,960 27,534

Burden of disease 14,334 0 0 0 0 0 14,334Health system costs 1,835 0 475 6,941 0 1,323 10,573Productivity costs 3,485 0 1,084 757 98 0 5,424Carer costs 0 505 267 0 0 76 848Other Indirect costs 74 76 0 74 74 74 373Deadweight losses 0 0 0 0 0 2,151 2,151Transfers -1,122 0 1,122 0 0 0 0Total financial costs 4,272 581 2,948 7,773 172 3,624 19,370Total costs including burden of disease 18,606 581 2,948 7,773 172 3,624 33,704

Total cost ($ million)

Cost per person with visual impairment ($)

In per capita terms, this amounts to a financial cost of $19,370 per person with VL per annum. Including the value of lost wellbeing, the cost is $33,704 per person per annum.

The shares by each type of financial cost are illustrated in Figure 6-39, while the financial cost shares by bearer are shown in Figure 6-40.

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FIGURE 6-39: FINANCIAL COSTS OF VL, BY TYPE OF COST (% TOTAL)

Health System Costs54.6%

Productivity Costs28.0%

Carer Costs4.4%

Indirect Costs1.9%

DWL11.1%

Individuals with VL bear 22.1% of the financial costs, and their families and friends bear a further 3.0%. Federal government bears 15.2% of the financial costs (mainly through taxation revenues forgone and welfare payments). Provincial governments bear 40.1% of the costs, reflecting the nature of Canada’s Federal system, while employers bear 0.9% and the rest of society bears the remaining 18.7%.

If the burden of disease (lost wellbeing) is included, individuals bear 55.2% of the costs and Provincial governments bear 23.1% while the Federal government bears a lesser 8.7%, with family and friends 1.7%, employers 0.5% and others in society 10.8%.

FIGURE 6-40: FINANCIAL COSTS OF VL, BY BEARER (% TOTAL)

Individuals22.1%

Family/Friends3.0%

Federal Government15.2%

Provincial Governments

40.1%

Employers0.9%

Society/Other18.7%

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As well as cost information, an important finding from this analysis was the observation that, for an advanced Western nation, Canada has a serious deficiency in eye health data. CNIB’s Health Economic Statement (http://www.costofblindness.org/media/health-state.asp) observes that, with respect to blindness and vision loss, there is ‘strong argument for saying that Canada has the worst record of supporting research of all the G8 countries’. The importance of good eye health to Canadians is shown from survey data in the same document revealing that two-thirds of Canadians would cash in all their savings or sell everything they owned to save their eyesight. With a rapidly aging population, it is high time for a Canadian population eye health study to monitor incidence, prevalence and morbidity outcomes and economic impacts more robustly in the future.

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http://www.costofblindness.org/media/health-state.asp


APPENDIX A: EDPRG PREVALENCE TABLESRecognizing the need for national estimates of VL, Prevent Blindness America and the National Eye Institute invited the principal investigators of several population-based vision studies to a meeting in Fort Lauderdale, Florida, in May 2001, to standardize disease definitions and methods of data reporting so that available data from many of these studies might be analysed together.

Prevalence of eye disease and associated blindness and low vision were calculated based on studies from the US, Western Europe, the West Indies and Australia. The number of individuals with each disease and the total number in the respective populations were provided in five year age increments by age, gender and ethnicity for the adult population from each of the studies. Prevalence rates were then combined using a meta-analysis technique for reducing the overall variance of the pooled rate.

TABLE A-1: SOURCE STUDIES FOR EDRPG DATA

Study and location B/VL RE AMD Cataract DR Glaucoma

Baltimore Eye Survey, US B W B W B W B WBarbados Eye Studies, West Indies B B BBeaver Dam Eye Study, US W W W W W WBMES, Australia W W W W WMVIP, Australia W W W W WProyecto Vision Evaluation Research, US

H H H H

Rotterdam Eye Study, The Netherlands W W W WSalisbury Eye Evaluation Project, US B W B W B W

Note: B = Black, H = Hispanic, W = White, B/VL = Blindness / VLSource: Congdon et al (2004a).

TABLE A-2: PREVALENCE OF AMD BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

50-54 0.2 0.3 0.9 0.255-59 0.2 0.4 1.1 0.460-64 0.4 0.6 1.4 0.665-69 0.7 1.1 1.7 0.970-74 1.5 2.1 2.1 1.575-79 3.2 3.9 2.5 2.480-84 6.8 6.9 2.9 3.885+ 13.6 12.0 3.3 5.9

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TABLE A-3: PREVALENCE OF CATARACT BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40-49 1.8 2.8 2.2 1.750-54 5.0 4.9 7.3 4.555-59 9.4 8.2 12.8 7.660-64 16.8 13.8 20.0 11.965-69 27.5 22.4 28.5 17.570-74 40.8 34.0 37.4 24.175-79 54.5 47.2 46.1 31.380+ 72.9 67.2 58.2 43.3

TABLEA-4: PREVALENCE OF DR BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

18-39 1.1 0.7 0.8 0.640-49 1.9 1.5 1.9 1.950-64 3.3 4.2 6.3 4.365-74 5.3 7.6 6.8 4.275+ 5.2 5.3 5.8 4.9

TABLE A-5: PREVALENCE OF GLAUCOMA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40-49 0.8 0.4 2.3 1.550-54 0.9 0.6 3.0 2.255-59 1.0 0.8 3.5 2.960-64 1.2 1.2 4.1 3.765-69 1.6 1.7 4.8 4.870-74 2.2 2.3 5.6 6.275-79 3.3 3.2 6.5 7.980+ 6.9 5.5 8.3 11.6

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TABLE A-6: PREVALENCE OF MYOPIA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40-49 46.4 37.0 18.4 22.550-54 30.3 26.2 13.2 16.355-59 23.7 22.0 11.4 13.160-64 19.4 19.4 10.3 10.465-69 16.8 17.9 9.8 8.170-74 15.5 17.5 9.9 6.375-79 15.2 18.0 10.4 4.980+ 16.8 21.1 12.7 3.1

TABLE A-7: PREVALENCE OF HYPEROPIA BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40-49 3.7 3.6 3.1 2.250-54 7.4 6.4 5.4 3.355-59 10.5 8.7 7.1 3.860-64 14.1 11.4 8.9 3.965-69 17.9 14.2 10.6 3.870-74 21.6 17.1 12.0 3.375-79 24.7 19.9 13.1 2.680+ 28.0 23.5 13.6 1.5

TABLE A-8: PREVALENCE OF ALL VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40- 49 0.3 0.3 0.1 0.350-54 0.4 0.3 0.4 0.755-59 0.5 0.4 0.7 1.260-64 0.7 0.6 1.3 2.265-69 1.2 1.0 2.4 3.870-74 2.3 1.9 4.2 6.475-79 4.8 4.0 7.0 10.480 + 24.1 20.2 15.1 23.7

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TABLE A-9: PREVALENCE OF MILD VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black

40-49 0.2 0.1 0.050-54 0.2 0.2 0.155-59 0.3 0.2 0.360-64 0.4 0.3 0.665-69 0.7 0.6 1.270-74 1.3 1.0 2.375-79 2.8 2.2 3.880 + 12.3 9.5 7.7

TABLE A-10: PREVALENCE OF MODERATE VL BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black

40-49 0.1 0.1 0.050-54 0.1 0.1 0.155-59 0.1 0.1 0.160-64 0.2 0.1 0.365-69 0.3 0.2 0.570-74 0.5 0.4 0.975-79 1.1 0.9 1.580 + 4.9 3.8 3.1

TABLE A-11: PREVALENCE OF BLINDNESS BY AGE, GENDER AND WHITE/BLACK (% POPULATION)Age White Female White Male Black Female Black Male

40-49 0.1 0.1 0.1 0.350-54 0.1 0.1 0.2 0.555-59 0.1 0.1 0.3 0.860-64 0.2 0.2 0.4 1.365-69 0.2 0.2 0.7 2.070-74 0.4 0.4 1.1 3.275-79 0.9 0.9 1.7 5.180 + 6.8 6.8 4.2 12.8

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APPENDIX B: PREVALENCE PROJECTIONS BY AGE, GENDER AND DISEASE

TABLE B-1: ALL VL BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 0

5-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 86 93 108 124 143 17225-29 24 26 31 35 41 4930-34 24 26 30 35 40 4835-39 87 94 108 125 144 17440-44 9,577 8,465 8,009 8,056 8,194 7,90345-49 5,028 5,090 4,278 4,076 4,128 4,20050-54 16,924 18,076 18,808 15,672 14,856 15,15555-59 28,842 30,861 35,009 36,928 32,110 31,49360-64 22,096 25,511 28,515 32,472 34,337 29,48865-69 36,555 41,772 54,331 61,212 70,126 71,67670-74 38,920 40,874 50,178 65,545 74,498 89,50275-79 59,237 60,658 64,591 80,323 106,150 130,35280-84 60,526 65,860 72,030 78,328 98,929 140,01785-89 42,877 49,695 61,082 70,652 80,104 113,65590+ 19,296 22,356 27,469 31,774 36,029 51,054Total males 340,097 369,458 424,576 485,355 559,828 684,941% of males 2.1% 2.2% 2.5% 2.7% 3.0% 3.6%% of total prevalence 41.6% 42.0% 42.8% 43.3% 43.7% 43.7%0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 49 53 61 70 81 9825-29 347 381 442 512 589 71230-34 345 377 435 502 579 70135-39 205 223 256 295 340 41340-44 9,469 8,388 7,904 7,997 8,149 7,90245-49 5,166 5,202 4,429 4,239 4,343 4,47150-54 17,390 18,376 18,850 15,750 14,869 15,32055-59 29,942 32,271 36,151 37,614 32,816 32,12760-64 23,148 26,902 30,400 34,116 35,531 30,50065-69 37,979 43,143 56,520 64,140 72,227 71,94070-74 44,041 46,199 56,063 73,219 83,586 97,68475-79 75,270 75,476 79,852 97,566 128,058 156,18880-84 94,066 96,399 99,527 106,756 131,653 183,91085-89 85,336 95,603 108,488 117,435 128,081 170,86090+ 54,101 60,609 68,785 74,469 81,229 108,336Total females 476,854 509,602 568,162 634,679 722,129 881,162% of females 2.9% 3.0% 3.2% 3.5% 3.8% 4.5%% of total prevalence 58.4% 58.0% 57.2% 56.7% 56.3% 56.3%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 135 147 169 195 224 27025-29 371 407 473 547 630 76230-34 369 403 465 537 619 74935-39 292 318 364 420 484 58740-44 19,046 16,853 15,912 16,053 16,342 15,80645-49 10,193 10,292 8,707 8,315 8,470 8,672

50-54 34,315 36,452 37,658 31,421 29,725 30,47555-59 58,784 63,132 71,159 74,541 64,925 63,62060-64 45,245 52,413 58,915 66,587 69,868 59,98765-69 74,534 84,915 110,851 125,352 142,353 143,61670-74 82,961 87,073 106,241 138,764 158,084 187,18675-79 134,507 136,134 144,443 177,889 234,208 286,54180-84 154,591 162,258 171,557 185,084 230,582 323,92885-89 128,212 145,298 169,570 188,087 208,185 284,51590+ 73,397 82,965 96,254 106,243 117,258 159,390Total persons 816,951 879,059 992,738 1,120,033 1,281,957 1,566,103% of total population 2.49% 2.63% 2.86% 3.10% 3.43% 4.01%

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TABLE B-2: VL FROM AMD BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

99


2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 519 591 762 861 987 1,02770-74 1,232 1,304 1,591 2,044 2,327 2,79975-79 6,787 6,973 7,462 9,249 12,148 14,90980-84 6,161 6,712 7,377 8,061 10,115 14,17985-89 10,577 12,251 15,051 17,411 19,743 27,96190+ 6,210 7,195 8,841 10,226 11,596 16,435Total males 31,486 35,027 41,084 47,853 56,917 77,309% of males 0.2% 0.2% 0.2% 0.3% 0.3% 0.4%% of total prevalence 35.4% 35.9% 37.1% 38.4% 39.3% 40.1%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 589 666 857 977 1,104 1,14070-74 1,427 1,511 1,826 2,341 2,675 3,14475-79 8,402 8,441 8,951 10,926 14,304 17,44380-84 9,190 9,436 9,777 10,513 12,938 18,00485-89 20,702 23,193 26,315 28,477 31,053 41,44090+ 17,227 19,300 21,889 23,675 25,806 34,465Total females 57,536 62,546 69,615 76,908 87,880 115,636% of females 0.3% 0.4% 0.4% 0.4% 0.5% 0.6%% of total prevalence 64.6% 64.1% 62.9% 61.6% 60.7% 59.9%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 1,108 1,257 1,619 1,839 2,092 2,16770-74 2,659 2,815 3,416 4,385 5,003 5,94375-79 15,189 15,414 16,413 20,175 26,452 32,35180-84 15,351 16,148 17,155 18,574 23,053 32,18385-89 31,279 35,445 41,366 45,888 50,796 69,40290+ 23,437 26,495 30,730 33,901 37,402 50,900Total persons 89,022 97,573 110,700 124,761 144,797 192,945% of total population 0.27% 0.29% 0.32% 0.35% 0.39% 0.49%

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TABLE B-3: VL FROM CATARACT BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 980 1,055 1,205 1,295 1,196 1,23760-64 141 160 183 210 230 23465-69 1,102 1,254 1,608 1,821 2,087 2,19070-74 4,434 4,711 5,727 7,298 8,316 10,00575-79 9,319 9,564 10,217 12,678 16,687 20,48380-84 14,164 15,420 16,903 18,421 23,197 32,68885-89 10,462 12,121 14,893 17,227 19,534 27,68090+ 7,344 8,505 10,446 12,084 13,704 19,393Total males 47,945 52,789 61,183 71,034 84,952 113,910% of males 0.3% 0.3% 0.4% 0.4% 0.5% 0.6%% of total prevalence 35.8% 36.3% 37.3% 38.3% 39.1% 39.8%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 967 1,046 1,180 1,247 1,139 1,16360-64 138 158 182 207 225 22665-69 1,371 1,547 1,969 2,251 2,550 2,69270-74 5,892 6,301 7,581 9,534 10,912 12,89775-79 12,651 12,810 13,715 16,672 21,597 26,31880-84 22,914 23,614 24,641 26,616 32,627 45,06785-89 21,170 23,716 26,949 29,233 31,930 42,46890+ 20,788 23,288 26,457 28,689 31,328 41,688Total females 85,891 92,480 102,673 114,448 132,307 172,519% of females 0.5% 0.5% 0.6% 0.6% 0.7% 0.9%% of total prevalence 64.2% 63.7% 62.7% 61.7% 60.9% 60.2%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 1,947 2,101 2,385 2,542 2,335 2,40060-64 279 318 365 417 455 46065-69 2,473 2,800 3,577 4,071 4,637 4,88270-74 10,325 11,012 13,308 16,831 19,228 22,90275-79 21,970 22,374 23,932 29,351 38,284 46,80180-84 37,077 39,034 41,544 45,037 55,824 77,75485-89 31,632 35,836 41,841 46,459 51,464 70,14890+ 28,133 31,793 36,903 40,773 45,032 61,081Total persons 133,836 145,268 163,856 185,482 217,259 286,428% of total population 0.41% 0.44% 0.47% 0.51% 0.58% 0.73%

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TABLE B-4: VL FROM DR BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 86 93 108 124 143 17225-29 24 26 31 35 41 4930-34 24 26 30 35 40 4835-39 87 94 108 125 144 17440-44 87 94 108 124 143 17345-49 55 60 69 79 91 11050-54 933 998 1,045 889 856 88855-59 1,740 1,883 2,164 2,362 2,292 2,46760-64 1,717 1,957 2,225 2,551 2,772 2,70665-69 1,472 1,665 2,096 2,389 2,740 2,97770-74 869 933 1,124 1,397 1,596 1,92375-79 2,125 2,212 2,411 2,953 3,789 4,63980-84 2,138 2,330 2,566 2,807 3,516 4,91385-89 886 1,023 1,254 1,451 1,647 2,31090+ 318 367 449 519 590 822Total males 12,560 13,763 15,786 17,840 20,400 24,373% of males 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%% of total prevalence 42.0% 42.3% 42.8% 43.0% 43.1% 43.1%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 49 53 61 70 81 9825-29 347 381 442 512 589 71230-34 345 377 435 502 579 70135-39 205 223 256 295 340 41340-44 206 223 254 293 338 41045-49 232 252 289 333 384 46550-54 1,112 1,184 1,245 1,123 1,122 1,21755-59 1,997 2,177 2,493 2,719 2,697 2,94660-64 1,971 2,255 2,595 2,954 3,198 3,19765-69 1,544 1,738 2,196 2,515 2,854 3,05770-74 937 1,006 1,208 1,507 1,726 2,04575-79 2,643 2,704 2,931 3,545 4,529 5,51480-84 3,237 3,334 3,474 3,749 4,599 6,36285-89 1,706 1,911 2,174 2,363 2,585 3,42890+ 829 929 1,057 1,149 1,257 1,667Total females 17,360 18,746 21,112 23,630 26,877 32,230% of females 0.1% 0.1% 0.1% 0.1% 0.1% 0.2%% of total prevalence 58.0% 57.7% 57.2% 57.0% 56.9% 56.9%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 135 147 169 195 224 27025-29 371 407 473 547 630 76230-34 369 403 465 537 619 74935-39 292 318 364 420 484 58740-44 293 317 362 417 481 58445-49 287 312 358 413 475 57550-54 2,045 2,182 2,290 2,012 1,978 2,10455-59 3,737 4,060 4,658 5,081 4,989 5,41360-64 3,688 4,212 4,820 5,505 5,970 5,90365-69 3,015 3,403 4,292 4,904 5,594 6,03470-74 1,805 1,940 2,333 2,904 3,322 3,96875-79 4,769 4,917 5,342 6,497 8,318 10,15380-84 5,376 5,664 6,039 6,556 8,115 11,27585-89 2,591 2,934 3,428 3,814 4,231 5,73890+ 1,147 1,296 1,506 1,669 1,847 2,489Total persons 29,920 32,509 36,897 41,471 47,277 56,603% of total population 0.09% 0.10% 0.11% 0.11% 0.13% 0.15%

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TABLE B-5: VL FROM GLAUCOMA BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 1,288 1,460 1,855 2,107 2,417 2,58470-74 1,410 1,506 1,824 2,297 2,621 3,15575-79 1,364 1,402 1,502 1,860 2,441 2,99680-84 3,928 4,276 4,689 5,112 6,435 9,06285-89 1,611 1,865 2,291 2,650 3,005 4,25190+ 605 701 860 995 1,129 1,593Total males 10,206 11,211 13,020 15,021 18,047 23,641% of males 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%% of total prevalence 40.9% 41.7% 42.9% 43.7% 44.2% 44.5%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 1,099 1,245 1,614 1,836 2,072 2,10970-74 1,194 1,260 1,525 1,971 2,251 2,63975-79 1,853 1,880 2,018 2,450 3,165 3,85780-84 5,828 5,965 6,145 6,581 8,126 11,37985-89 3,119 3,495 3,965 4,290 4,677 6,24390+ 1,639 1,836 2,083 2,253 2,457 3,280Total females 14,731 15,680 17,349 19,381 22,749 29,507% of females 0.1% 0.1% 0.1% 0.1% 0.1% 0.1%% of total prevalence 59.1% 58.3% 57.1% 56.3% 55.8% 55.5%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 0 0 0 0 0 045-49 0 0 0 0 0 050-54 0 0 0 0 0 055-59 0 0 0 0 0 060-64 0 0 0 0 0 065-69 2,386 2,705 3,469 3,944 4,489 4,69270-74 2,605 2,766 3,348 4,268 4,872 5,79475-79 3,217 3,282 3,520 4,311 5,607 6,85280-84 9,755 10,241 10,834 11,693 14,561 20,44185-89 4,730 5,360 6,255 6,940 7,683 10,49490+ 2,244 2,537 2,943 3,248 3,585 4,873Total persons 24,937 26,891 30,368 34,403 40,797 53,147% of total population 0.08% 0.08% 0.09% 0.10% 0.11% 0.14%

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TABLE B6: VL FROM RE BY AGE AND GENDER, 2007-2032 SELECTED YEARS (PEOPLE)

2007 2010 2015 2020 2025 20320-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 9,490 8,371 7,901 7,932 8,051 7,73045-49 4,973 5,030 4,209 3,997 4,037 4,09050-54 15,991 17,078 17,763 14,783 14,000 14,26855-59 26,122 27,923 31,639 33,271 28,622 27,78860-64 20,239 23,395 26,108 29,711 31,334 26,54765-69 32,174 36,802 48,010 54,033 61,895 62,89870-74 30,975 32,419 39,912 52,508 59,638 71,62075-79 39,642 40,506 42,999 53,583 71,084 87,32680-84 34,134 37,121 40,495 43,927 55,665 79,17685-89 19,342 22,435 27,594 31,913 36,174 51,45490+ 4,819 5,589 6,873 7,949 9,011 12,812Total males 237,900 256,668 293,503 333,606 379,511 445,709% of males 1.5% 1.6% 1.7% 1.9% 2.1% 2.3%% of total prevalence 44.1% 44.5% 45.1% 45.5% 45.6% 45.6%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 9,264 8,165 7,649 7,704 7,811 7,49245-49 4,934 4,950 4,140 3,905 3,959 4,00750-54 16,278 17,193 17,605 14,626 13,748 14,10355-59 26,978 29,048 32,477 33,647 28,979 28,01860-64 21,039 24,489 27,623 30,954 32,108 27,07765-69 33,378 37,948 49,883 56,561 63,647 62,94370-74 34,592 36,121 43,923 57,867 66,021 76,96075-79 49,720 49,641 52,237 63,972 84,462 103,05780-84 52,897 54,050 55,491 59,297 73,363 103,09985-89 38,638 43,288 49,086 53,073 57,836 77,28190+ 13,617 15,256 17,299 18,703 20,381 27,235Total females 301,336 320,149 357,414 400,310 452,316 531,271% of females 1.8% 1.9% 2.0% 2.2% 2.4% 2.7%% of total prevalence 55.9% 55.5% 54.9% 54.5% 54.4% 54.4%

0-4 0 0 0 0 0 05-9 0 0 0 0 0 010-14 0 0 0 0 0 015-19 0 0 0 0 0 020-24 0 0 0 0 0 025-29 0 0 0 0 0 030-34 0 0 0 0 0 035-39 0 0 0 0 0 040-44 18,753 16,536 15,551 15,636 15,862 15,22245-49 9,907 9,980 8,349 7,902 7,996 8,09750-54 32,269 34,270 35,368 29,409 27,748 28,37155-59 53,100 56,971 64,116 66,918 57,601 55,80660-64 41,278 47,884 53,731 60,665 63,443 53,62465-69 65,552 74,750 97,893 110,594 125,542 125,84170-74 65,567 68,540 83,835 110,376 125,659 148,58075-79 89,362 90,147 95,236 117,555 155,547 190,38380-84 87,032 91,171 95,986 103,224 129,029 182,27585-89 57,980 65,724 76,680 84,986 94,010 128,73490+ 18,436 20,845 24,172 26,652 29,391 40,047Total persons 539,236 576,817 650,917 733,916 831,827 976,979% of total population 1.64% 1.73% 1.87% 2.03% 2.23% 2.50%

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