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BMJ Open logoLink to BMJ Open
. 2013 Nov 19;3(11):e003787. doi: 10.1136/bmjopen-2013-003787

Geographical prevalence and risk factors for pterygium: a systematic review and meta-analysis

Lei Liu 1,2, Jingyang Wu 1, Jin Geng 1, Zhe Yuan 1, Desheng Huang 2,3
PMCID: PMC3840351  PMID: 24253031

Abstract

Objective

Pterygium is considered to be a proliferative overgrowth of bulbar conjunctiva that can induce significant astigmatism and cause visual impairment; this is the first meta-analysis to investigate the pooled prevalence and risk factors for pterygium in the global world.

Design

A systematic review and meta-analysis of population-based studies.

Setting

International.

Participants

A total of 20 studies with 900 545 samples were included.

Primary outcome measure

The pooled prevalence and risk factors for pterygium.

Results

20 studies were included. The pooled prevalence of pterygium was 10.2% (95% CI 6.3% to 16.1%). The pooled prevalence among men was higher than that among women (14.5% vs 13.6%). The proportion of participants with unilateral cases of pterygium was higher than that of participants with bilateral cases of pterygium. We found a trend that the higher pooled prevalence of pterygium was associated with increasing geographical latitude and age in the world. The pooled OR was 2.32 (95% CI 1.66 to 3.23) for the male gender and 1.76 (95% CI 1.55 to 2.00) for outdoor activity, respectively.

Conclusions

The pooled prevalence of pterygium was relatively high, especially for low latitude regions and the elderly. There were many modifiable risk factors associated with pterygium to which healthcare providers should pay more attention.

Keywords: Epidemiology, Ophthalmology


Strengths and limitations of this study.

  • We estimated the pooled prevalence data using meta-analysis, rather than the prevalence in a single national population-based study.

  • We only included studies written in English or Chinese and published from January 2000 to May 2013, so the pooled prevalence of pterygium in specific regions and periods is explained by the results.

  • As we cannot have access to unpublished results, a publication bias cannot be excluded.

  • The pooled analysis of some other risk factors was not produced due to insufficient data.

Introduction

Pterygium is a common fibrovascular proliferative disease affecting the ocular surface; it can result in ocular irritation, visual disturbances and so on.1 Many previous reports have shown the prevalence of, and risk factors for, pterygium in population-based studies, but the prevalence of pterygium varies widely with geography, age and gender in different samples,2 and the data remain limited and localised. Although the exact aetiology of pterygium is unknown, there seems to be an association between outdoor work and pterygium formation,3 especially with ultraviolet (UV) radiation. Increasing geographical latitude was associated with a reduced pterygium OR.4 Until now, there is no national, population-based study on the prevalence of pterygium in the world, and it would seem that a national, pooled estimate based on the global population is necessary. In this meta-analysis, we carried out a systematic review of previous population-based studies on the prevalence of, and risk factors for, pterygium in the world and investigated any differences among age groups, genders and geographical latitude.

Methods

Search strategy

We searched all English reports on population-based studies for the prevalence of, and risk factors for, pterygium using MEDLINE, EMBASE, Web of Science and Google (scholar), and all Chinese reports were searched manually and online using the Chinese Biochemical Literature on Disc (CBMDisc), Chongqing VIP database and China National Knowledge Infrastructure (CNKI) database. The search keywords were: pterygium, pterygia, prevalence, epidemiology and risk factor. Reference lists were checked and researchers contacted for additional literature. A total of 138 reports published in the period from January 2000 to May 2013 were identified.

Inclusion and exclusion criteria

The review and analysis were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Statement as a guide.5 Reports potentially eligible for inclusion in this systematic review and meta-analysis had to meet the following criteria: they had to be population-based studies, original, written in English or Chinese, and needed to provide sufficient information to estimate the pooled prevalence of, and risk factors for, pterygium. If more than one study was based on the same population sample, the study of the highest quality was included. We excluded studies that were on the duplicate population groups but were of lower quality, whose participants were drawn from a particular occupation or population, and that did not satisfy one or more inclusion criteria.

A total of 138 potentially relevant studies were identified and screened. After systematic review, only 20 of these were included in the meta-analysis. The progress for study inclusion is shown in figure 1.

Figure 1.

Figure 1

Flow chart demonstrating those studies that were processed for inclusion in the meta-analysis.

Data extraction

Two researchers (LL and JG) independently searched the literature. Data were extracted from each article using a standardised form including first author, publication year and et al. The characteristics of the population-based studies included in this meta-analysis on the pooled prevalence of pterygium in the world are shown in table 1.

Table 1.

Characteristics of population-based studies on the prevalence of pterygium

No. First author Publication year Country Regional Area Ethnic Rural/urban Survey year Age range (years) Sample size (n) Cases (n)
1 Cajucom-Uy et al6 2010 Singapore 1°09′-1°29N,103°38′-104°6′E South-western part of Singapore Malay NA 2004–2006 40–79 3280 508
2 Wu et al7 2002 China 22°12″N,113°15″E Doumen County Chinese Rural 1997 50 years or over 4214 1391
3 Paula et al8 2006 Brazil 0°9′S,68°54′W Sao Gabriel da Cachoeira City Indian Rural 1997–1999 NA 624 115
4 Viso et al9 2011 Spain 42°N O Salnes Spanish Urban 2005–2006 40–96 619 42
5 Fotouhi et al10 2009 Iran 35°N,50°E Tehran Persian Urban 2002 All age 4564 66
6 Durkin et al11 2008 Myanmar 20°53′N,95°53′E Meiktita Burmese Rural 2005 40 years and over 2076 NA
7 Wong et al12 2001 Singapore 1°16′N,103°51′E Tanjong Pagar Chinese NA 1997–1998 40–79 1232 120
8 Lu et al13 2009 China 34°4′-55′N,100°53′-102°15′E Henan County Mongolian Rural 2006 40 years and over 2112 378
9 Tan et al14 2006 Indonesia 1°53′N,101°44′E Pulau Jaloh Indonesia NA NA All age 477 81
10 Liang et al15 2010 China 39.6°-40.3°N Beijing Chinese Rural 2008–2009 55–85 37 067 1395
11 Bueno-Gimeno et al16 2002 Algeria 27°42′N,8°10′W Tindouf Saharan NA 1997 6–80 1322 138
12 Luthra et al17 2001 Barbados 13°11′N,60°27′W Barbados Barbadian Urban NA 40–84 2781 613
13 McCarty et al18 2000 Australia 38°53′S,144°45′E Victoria Victorians Rural/urban 40 years and over 5147 142
14 Shiroma et al19 2009 Japan 26°20′N,126°48′E Kumejima Japanese NA 2005–2006 40 years and over 3747 1154
15 Ma et al20 2007 China 39°54′N,116°23′E Beijing Chinese Rural/urban 2001 40 years and over 4439 128
16 West and Muñoz21 2009 USA 31°-32°N,111°3′-4′W Nogales and Tucson Hispanic NA NA 40 years and over 4774 NA
17 Liu et al22 2001 China 18°-19°N,108°-109°E Hainan Chinese Rural 1999 12–88 7990 628
18 Gazzard et al23 2002 Indonesia 1°N Riau province Malay/Indonesians Rural 2001 21 years and over 1210 NA
19 Sherwin et al24 2013 Australia 29°2′S,167°56′E NA NA 2007 15 years and over 641 70
20 Lu et al2 2007 China 35°2′N,101°5′E Zeku Tibetan Rural/urban 2006 40 years and over 2229 323

E, east latitude; N, north latitude; NA, not available; S, south latitude; W, west latitude.

We systematically assessed several key points of study quality proposed by the MOOSE Collaboration25 The quality of the included studies is shown in table 2.

Table 2.

Quality for the population-based studies on the prevalence of pterygium

No. First author Publication year Sampling scheme Population characteristics Prevalence definition Diagnostic criteria Response rate Total score
1 Cajucom-Uy et al6 2010 Yes Yes Yes Yes 0.787% 5
2 Wu et al7 2002 Yes Yes Yes Yes 88.49% 5
3 Paula et al8 2006 NA Yes NA Yes NA 2
4 Viso et al9 2011 Yes Yes Yes Yes 66.10% 5
5 Fotouhi et al10 2009 Yes Yes Yes Yes 70.30% 5
6 Durkin et al11 2008 Yes Yes Yes Yes 83.70% 5
7 Wong et al12 2001 Yes Yes Yes Yes 71.80% 5
8 Lu et al13 2009 Yes Yes Yes Yes 84.90% 5
9 Tan et al14 2006 Yes Yes Yes Yes 86.70% 5
10 Liang et al15 2010 Yes Yes Yes Yes 84% 5
11 Bueno-Gimeno et al16 2002 Yes Yes Yes Yes NA 4
12 Luthra et al17 2001 Yes Yes Yes Yes 93% 5
13 McCarty et al18 2000 Yes Yes Yes Yes NA 4
14 Shiroma et al19 2009 Yes Yes Yes Yes 81.20% 5
15 Ma et al20 2007 Yes Yes Yes Yes NA 4
16 West and Muñoz B21 2009 Yes Yes Yes Yes NA 4
17 Liu et al22 2001 Yes Yes Yes Yes NA 4
18 Gazzard et al23 2002 Yes Yes Yes Yes 96.70% 5
19 Sherwin et al24 2013 Yes Yes Yes Yes 61.50% 5
20 Lu et al2 2007 Yes Yes Yes Yes 84.69% 5

NA, not available.

Data analysis

OR was analysed using the RevMan V.5.0 (Review Manager, Copenhagen: the Nordic Cochrane Centre, the Cochrane Collaboration, 2010) statistical software package. Meta-analyst statistical software offered by http://tuftscaes.org/meta_analyst/ was used to analyse the data for the pooled prevalence. All meta-analyses were evaluated for heterogeneity using the χ2-based I2 test and Q test.26 I2 Test estimated the percentage of the total variance in all of the data under consideration that was related to heterogeneity. The authors suggested using 25%, 50% and 75% to indicate low-level, moderate-level or high-level heterogeneity. If there was moderate-level or high-level heterogeneity, a random-effects meta-analysis was performed by the DerSimonian and Laird method, except where fixed-effects models were used. Publication bias was assessed by visually inspecting a funnel plot. A p value less than 0.05 was considered statistically significant.27 28

Results

The pooled prevalence rate of pterygium was 10.2% (95% CI 6.3% to 16.1%; I2=49.9%, Q=1.00; p<0.001) in the overall population (figure 2). The maximum (33%) and minimum (2.8%) prevalence rates of pterygium appeared in the studies by Wu et al7 and McCarty et al,18 respectively. The pooled prevalence was 13.2% (95% CI 4.7% to 31.8%; I2=50%, Q=1.00; p<0.001) for the rural population in five studies, and it was higher than the pooled prevalence of 6.3% (95% CI 0.9% to 32.3%; I2=49.9%, Q=0.99; p<0.001) for the urban population in three studies. The pooled prevalence rates for pterygium were 14.5% (95% CI 9.1% to 22.2%; I2=49.8%, Q=1.00; p<0.001) in men and 13.6% (95% CI 7.5% to 23.5%; I2=49.9%, Q=1.00; p<0.001) in women, respectively. The pooled prevalence rate for participants with unilateral cases of pterygium was higher than that for those with bilateral pterygium (8% vs 6.2%). After removing other countries, we found that the pooled prevalence of pterygium in six studies from China was 9.9% (95% CI 4% to 22.7%; I2=50%, Q=1.00; p<0.001), which was similar to the overall pooled prevalence of pterygium in the world.

Figure 2.

Figure 2

Forest plot displaying the pooled prevalence of pterygium in the population of the world.

There was a significant trend of greater prevalence for pterygium at older ages (40–49 vs 50–59 vs 60–69 years, 11% vs 15.6% vs 20.1%), and the trends were generally similar between the 60–69 and over 70 years age groups (20.1% vs 20.2%). This report presented trends in the pooled prevalence of pterygium varied with increasing geographical latitude. The pooled prevalence of pterygium (19.3%, 95% CI 12.4% to 28.9%; I2=49.8%, Q=0.99; p<0.001) whose stations were located in the latitude ranges of 20–30° was higher than for those in any other areas (figure 3). In addition, the prevalence rates comparing men and women, unilateral versus bilateral, Chinese articles, age and latitude are shown in table 3.

Figure 3.

Figure 3

Forest plot displaying the pooled ORs and trends of pterygium: (A) OR for male gender; (B) OR for outdoor activity; (C) trend for age groups and prevalence of pterygium; and (D) trend for geographical latitude and prevalence of pterygium.

Table 3.

Summary table of the data with the significance test results

Subgroups The pooled prevalence rates of pterygium (%) p Value
Gender
 Males 14.5 0.03
 Females 13.6
Unilateral or bilateral
 Unilateral pterygium cases 8 <0.01
 Bilateral pterygium cases 6.2
Area
 Pterygium in China 9.9 0.06
 Pterygium in the world 10.2
Age group, years
 40–49 11 <0.01
 50–59 15.6
 60–69 20.1
Old age group, years
 60–69 20.1 0.12
 70–79 20.2
Different parallel latitude
 0–10 14.8 0.01
 10–20 13.4
 20–30 19.3
 30–40 5.9
 40–50 4.1

Six studies investigated the association between male gender and pterygium. The pooled OR was 2.32 (95% CI 1.66 to 3.23; I2=85%, p<0.001) for the male gender. There were six articles which provided information on the relationship between outdoor sun exposure and pterygium, and the OR was 1.76 (95% CI 1.55 to 2; I2=0%, p=0.76) for outdoor sun exposure (figure 3).

There were other risk factors for pterygium by logistic regression in the reviewed studies, but the pooled ORs could not be calculated because little information in estimating. The risk factors are shown in table 4.

Table 4.

Risk factors of the population-based studies by logistic regression for prevalence of pterygium

First author Publication year Risk factors OR 95% CI
Cajucom-Uy et al6 2010 Age 1.3 1.1 to 1.4
Male gender 1.9 1.5 to 2.6
High systolic blood pressure 1.6 1.2 to 2.1
Viso et al9 2011 Outer activity 2.28 1.04 to 4.98
fluorescein staining 2.64 1.08 to 6.46
Fotouhi et al10 2009 Age (60+) 73.6 17.1 to 316.1
Durkin et al11 2008 Primarily outdoor 1.54 1.19 to 2
Wong et al12 2001 Male gender 5.1 2.9 to 9.3
Age (50–59) 3.7 1.5 to 9.4
Age (60–69) 6.3 2.6 to 15.1
Age (70–81) 7.8 3.2 to 18.8
Lu et al13 2009 Age (70–79) 2 1.4 to 2.8
Alcohol intake 1.5 1 to 2
Education (<3 years) 2.1 1.4 to 3.2
Dry eye symptoms 1.9 1.5 to 2.5
Poor family situation 1.3 1 to 1.6
Schirmer's test (≤5 mm) 2.4 1.9 to 3.1
Tear break-up time (≤10 s) 2.3 1.8 to 2.9
Seldom use of sunglasses 1.5 1.2 to 1.9
Seldom use of hat 1.3 1.1 to 1.7
Cataract 1.5 1.1 to 1.9
Tan et al14 2006 Male gender 3.1 1.72 to 5.61
Luthra et al17 2001 Age 1.01 1 to 1.02
Education (<12 years) 1.43 1.01 to 2.03
Outer activity 1.87 1.52 to 2.29
Darker skin complexion 0.66 0.52 to 0.83
Using sunglasses outdoor 0.18 0.06 to 0.59
Use of prescription glasses 0.75 0.6 to 0.93
McCarty et al18 2000 Age group (10 year) 1.23 1.06 to 1.44
Male gender 2.02 1.35 to 3.03
Rural residence 5.28 3.56 to 7.84
Lifetime ocular sun exposure 1.63 1.18 to 2.25
Shiroma et al19 2009 Male gender 1.33 1.03 to 1.63
Age (years) 1.02 1.01 to 1.03
Refractive error 1.08 1.03 to 1.13
Experience of outdoor jobs 1.82 1.33 to 2.5
Intraocular pressure 0.96 0.94 to 0.98
Ma et al20 2007 Male gender 2.67 2.25 to 3.18
West and Muñoz B21 2009 Education (<6 years) 2.81 2.18 to 3.62
Income <20 000 1.24 1.03 to 1.51
Smoking 0.75 0.59 to 0.94
Bilateral cataract surgery 0.54 0.35 to 0.83
Gazzard et al23 2002 Age (51 and above) 7.31 2.36 to 22.7
Smoking 0.46 0.24 to 0.9
Sherwin et al24 2013 Outdoor >3/4 day 2.22 1.2 to 4.09
Ultraviolet autofluorescence (per 10 mm) 1.16 1.05 to 1.28
Skin type (tans) 2.17 1.2 to 3.92
Lu et al2 2007 Age (70–79) 2 1.4 to 2.8
Female gender 1.6 1.2 to 2
Education (<3 years) 1.6 1.1 to 2.4
Dry eye symptoms 1.3 1 to 1.7
Use of sunglasses/stone glasses 0.3 0.1 to 0.8
Use of hats 0.3 0.2 to 0.5
Seldom use of sunglasses/stone glasses 4.6 1.9 to 11.3
Seldom use of hats 3.6 2.4 to 5.4
Low socioeconomic status 1.9 1.5 to 2.4

All comparisons passed the test of heterogeneity, as previously defined random-effects models were used for meta-analyses. The funnel plot of the overall pooled prevalence of pterygium is shown in figure 4. The funnel plot had the expected funnel shape. There was no significant publication bias in this meta-analysis.

Figure 4.

Figure 4

Funnel plot of studies conducted on the prevalence of pterygium in the world.

Discussion

The prevalence of pterygium varied widely across studies. A simple meta-analysis to combine the findings of studies would be informative. To our knowledge, this is the first meta-analysis of prevalence rate and risk factors for pterygium in the world. In this meta-analysis, a total of 20 studies with 900 545 samples were included. We showed that the pooled prevalence rate of pterygium was 10.2% (95% CI 6.3% to 16.1%) in the general population. The eligible studies covered 12 countries. There was a similarity in prevalence of pterygium between China and the world, which might have resulted in the region of China being located mostly in the low-to-high latitude regions, but the prevalence of pterygium (33%) in the Doumen County of China was highest in this systematic review.7 This indicates a strong requirement for prevention and treatment strategies to control pterygium disease.

Researches on whether gender is related to pterygium have been uncertain.2 6–24 Many previous studies suggested that the prevalence of pterygium was higher in the male gender than in the female gender,6 14 15 19 24 which is consistent with the results of this meta-analysis (men vs women, 14.5% vs 13.6%). The pooled OR was 2.32 (95% CI 1.66 to 3.23) for the male gender. Previous studies by Lu et al2 reported that women were at higher risk than men (OR 1.6, 95% CI 1.2 to 2) after logistic regression, which involved in the lifestyle for Tibetan women who had much rural and outdoor work.

Results by this meta-analysis suggested that the prevalence of pterygium in the rural population was higher than that in the urban population, because rural people were often involved in much outdoor work. We found a significant positive trend between increasing age and the prevalence of pterygium, so the importance of organising healthcare for the elderly to prevent pterygium cannot be underestimated.

Epidemiological associations have been suggested between outdoor activity and the prevalence of pterygium,9 11 1719 24 and the pooled OR of outdoor activity for pterygium was 1.76 (95% CI 1.55 to 2). Adding even more outdoor activity makes it a great time to get more exposure to sunlight. A strong positive correlation between climatic UV radiation and the prevalence of pterygium29 was found. It is also known that the low geographical latitude regions are exposed to higher sunlight. There was a trend between higher geographical latitude and lower prevalence of pterygium beside areas located in the latitude range of 20–30°. We are not aware of the reason why the prevalence of pterygium was a little higher in the latitude range of 20–30° than that in low latitude regions.

However, the findings had substantial heterogeneity (p<0.001), possibly due to the confounding effects of differences in age, distribution of participants and so on.

Although we have estimated the pooled prevalence of pterygium in the world, which is very important for preventative public health, there are some limitations in this meta-analysis. First, we only included studies written in English or Chinese and published from January 2000 to May 2013, so the pooled prevalence of pterygium in specific regions and periods is explained by the results. In addition, further evidence might have emerged subsequent to our original search, and the results of the meta-analysis must be updated in time. Second, as we cannot have access to unpublished results, a publication bias cannot be excluded. Third, a pooled analysis of some other risk factors was not produced due to insufficient data.

Described as an ‘ophthalmic enigma’,30 the prevalence of pterygium was 10.2% in the world. Healthcare providers should be aware of preventing pterygium, especially in the elderly and people in low latitude regions.

Supplementary Material

Author's manuscript
Reviewer comments

Acknowledgments

This study was supported by the Liaoning Diabetic Eye Center, the Liaoning Provincial Key Laboratory of Endocrine Diseases and the Endocrine Institute of China Medical University. The authors would like to thank Jingpu Shi, PhD, Professor of the Department of Clinical Epidemiology and Evidence Medicine in the First Affiliated Hospital of China Medical University. They also thank Dr Sharon Forsyth, Director of Biomedical Editing International for English editing.

Footnotes

Contributors: LL and DH conceived and designed the experiments. LL, ZY and JW performed the experiments. DH, LL, JG and JW analysed the data. LL, JG and DH wrote the article.

Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests: None.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data sharing statement: No additional data are available.

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