Correlation between the presumed pterygium with dry eye and with systemic and ocular risk factors

Adriano, Leidiane; Persona, Etiene Lorriane de Souza; Persona, Isvander Gustavo de Souza; Pontelli, Regina Celia Nucci; Rocha, Eduardo M.

doi:10.5935/0004-2749.20220022

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ORIGINAL ARTICLE • Arq. Bras. Oftalmol. 85 (02) • 2022 • https://doi.org/10.5935/0004-2749.20220022 copy

Correlation between the presumed pterygium with dry eye and with systemic and ocular risk factors

Correlação entre o pterígio presumível com olho seco e com fatores de risco sistêmicos e oculares

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Objective:

To estimate the epidemiology of the pterygium and its correlation with dry eye symptoms and with the potential systemic and ocular predictors.

Methods:

This study is a population-based, cross-sectional study in which random visits were made to the 600 households of 600 participants of age ≥40 years in Ribeirão Preto-SP (n=420) and Cassia dos Coqueiros-SP (n=180) in Brazil. The participants were subjected to a structured interview with a detailed questionnaire to collect information on demography and the potential risk factors. Next, random participants with pterygium (n=63) or not (n=110) were evaluated for the ocular surface changes.

Results:

The frequency of pterygium in Ribeirão Preto was 21% (15.7% among women and 32.1% among men; p=0.0002). In Cássia dos Coqueiros, the corresponding frequency was 19.4% (17.3% among women and 25.5% among men; p=0.28). The mean age of the affected individuals was higher than that of the unaffected ones (65.6 ± 10.5 years vs. 61.2 ± 12.0 years, p=0.02). A positive correlation was noted between pterygium and any prior radiotherapy and chemotherapy (p<0.0001, for both). A higher score on corneal fluorescein and conjunctival lissamine green staining was asso ciated with pterygium (p=0.0003 and 0.0001, respectively).

Conclusion:

We noted a high frequency of pterygium in two Brazilian adult populations, mainly among the men and elderly. Ocular surface damage and a previous history of radiotherapy and/or chemotherapy were found to be associated with pterygium.

Keywords:
Pterygium/epidemiology; Dry-eye syndrome; Prevalence; Risk factors

Author(s), year	Country	N	Age (years)	Prevalence (%)	Associated factors	Non associated factors
McCarty CA et al, 2000⁽⁽⁵5 McCarty CA, Fu CL, Taylor HR. Epidemiology of pterygium in Victoria, Australia. Br J Ophthalmol. 2000;84(3):289-92.⁾⁾	Australia	5147	40-101	2.8	Older age, male sex, rural residence, smoking, cataract, take vitamin C, and outdoor work	Take vitamin E
Gazzard G et al, 2002⁽⁽¹⁹19 Lu J, Wang Z, Lu P, Chen X, Zhang W, Shi K, et al. Pterygium in an aged Mongolian population: a population-based study in China. Eye (Lond). 2009;23(2):421-7.⁾⁾	Indonesia	1210	≥21	10	Older age, outdoor work, visual acuity, and astigmatism	Sex and smoking
Tan CSH et al, 2006⁽⁽¹³13 Tan CS, Lim TH, Koh WP, Liew GC, Hoh ST, Tan CC, et al. Epidemiology of pterygium on a tropical island in the Riau Archipelago. Eye (Lond). 2006;20(8):908-12.⁾⁾	Indonesia	477	All age	17	Older age and male sex	NI^† † = Not investigated;
Paula JS et al, 2006⁽⁽⁸8 Paula JS, Thorn F, Cruz AA. Prevalence of pterygium and cataract in indigenous populations of the Brazilian Amazon rain forest. Eye (Lond). 2006;20(5):533-6.⁾⁾	Brazil	624	Adults	18.4	Arawak and Tukano communities	Sex and age
Lu J et al,2009⁽⁽²⁰20 Viso E, Gude F, Rodríguez-Ares MT. Prevalence of pinguecula and pterygium in a general population in Spain. Eye (Lond). 2011; 25(3):350-7.⁾⁾	China	2486	≥40	17.9	Older age, cataract, low education level, alcohol, low income family situation, seldom use of sunglasses and hat	Sex
Shiratori CA et al, 2010⁽⁽⁷7 Shiratori CA, Barros JC, Lourenço RM, Padovani CR, Cordeiro R, Schellini SA. [Prevalence of pterygium in Botucatu city - São Paulo State, Brazil]. Arq Bras Oftalmol. 2010;73(4):343-5. Portuguese.⁾⁾	Brazil	2554	All age	8.1	Male sex and age range 40-50 years	NI^† † = Not investigated;
Landers J et al, 2011⁽⁽¹⁶16 Landers J, Henderson T, Craig J. Prevalence of pterygium in indigenous Australians within central Australia: the Central Australian Ocular Health Study. Clin Exp Ophthalmol. 2011;39(7):604-6.⁾⁾	Australia	1884	≥20	7.8	Older age	Sex, visual acuity, cataract, and climatic keratopathy
Viso E et al, 2011⁽⁽²¹21 McKnight CM, Sherwin JC, Yazar S, Forward H, Tan AX, Hewitt AW, et al. Pterygium and conjunctival ultraviolet autofluorescence in young Australian adults: the Raine study. Clin Exp Ophthalmol. 2015;43(4):300-7.⁾⁾	Spain	1155	≥40	5.9	Older age and outdoor work	Sex, education level, iris color, smoking, alcohol, rosacea, allergy, and diabetes
Zhong H et al, 2012⁽⁽⁴4 Zhong H, Cha X, Wei T, Lin X, Li X, Li J, et al. Prevalence of and risk factors for pterygium in rural adult Chinese populations of the Bai nationality in Dali: the Yunnan Minority Eye Study. Invest Ophthalmol Vis Sci. 2012;53(10):6617-21.⁾⁾	China	2133	≥50	39	Older age, female sex, low education level, visual acuity, height, weight, hypertension, and outdoor work	Diabetes, smoking, and alcohol
Ang M et al, 2012⁽⁽¹⁰10 Ang M, Li X, Wong W, Zheng Y, Chua D, Rahman A, et al. Prevalence of and racial differences in pterygium: a multiethnic population study in Asians. Ophthalmology. 2012;119(8):1509-15.⁾⁾	Singapore	8906	40-80	10.1	Older age, male sex, Malay ethnicity, low education level, hypertension, hypercholesterolemia	Low-density or high-density lipoprotein cholesterol levels, alcohol, diabetes, glycosylated hemoglobin A1c level, and previous ocular trauma
Rezvan F et al, 2012⁽⁽¹¹11 Rezvan F, Hashemi H, Emamian MH, Kheirkhah A, Shariati M, Khabazkhoob M, et al. The prevalence and determinants of pterygium and pinguecula in an urban population in Shahroud, Iran. Acta Med Iran. 2012;50(10):689-96.⁾⁾	Iran	5190	≥40	9.4	Male sex, older age, outdoor work, astigmatism, and low education level	Smoking and visual acuity
Tano T et al, 2013⁽⁽¹⁷17 Tano T, Ono K, Hiratsuka Y, Otani K, Sekiguchi M, Konno S, et al. Prevalence of pterygium in a population in Northern Japan: the Locomotive Syndrome and Health Outcome in Aizu Cohort Study. Acta Ophthalmol. 2013;91(3):e232-6.⁾⁾	Japan	2312	40-74	4.4	Older age	Sex, outdoor work, and smoking
Marmamula S et al, 2013⁽⁽⁶6 Marmamula S, Khanna RC, Rao GN. Population-based assessment of prevalence and risk factors for pterygium in the South Indian state of Andhra Pradesh: the Andhra Pradesh Eye Disease Study. Invest Ophthalmol Vis Sci. 2013;54(8):5359-66.⁾⁾	India	10293	≥30	11.7	Older age, rural residents, no education, outdoor work, and alcohol	Sex and smoking
Nangia V et al, 2013⁽⁽¹²12 Nangia V, Jonas JB, Nair D, Saini N, Nangia P, Panda-Jonas S. Prevalence and associated factors for pterygium in rural agrarian central India. The central India eye and medical study. PLoS One. 2013;8(12):e82439.⁾⁾	India	4711	≥30	12.9	Older age, male sex, low education level, height, weight, hypertension, smoking, BMI^* * = Body Mass Index; , and outdoor work	DBP^‡ ‡ = Diastolic blood pressure. and alcohol use
Jiao W et al, 2014⁽⁽³3 Jiao W, Zhou C, Wang T, Yang S, Bi H, Liu L, et al. Prevalence and risk factors for pterygium in rural older adults in Shandong Province of China: a cross-sectional study. BioMed Res Int. 2014;2014:658648.⁾⁾	China	17816	≥50	10.5	Older Age, low education level, outdoor time (hours per day), and wearing hat and/or sunglasses	Sex, alcohol, smoking, diabetes, hypertension, hyperlipidemia, and cardiac diseases
Chen T et al, 2015⁽⁽²2 Chen T, Ding L, Shan G, Ke L, Ma J, Zhong Y. Prevalence and racial differences in pterygium: a cross-sectional study in Han and Uygur adults in Xinjiang, China. Invest Ophthalmol Vis Sci. 2015;56(2):1109-17.⁾⁾	China	4617	≥30	11.9	Older age, rural residence, astigmatism, low education level, outdoor work, height, weight, hypertension, no exercise, heavy physical work, Han ethnicity, and smoking	Sex, BMI^* * = Body Mass Index; , diabetes, and alcohol
Mcknight CM et al,2015⁽⁽²²22 Hashemi H, Khabazkhoob M, Yekta A, Jafarzadehpour E, Ostadimoghaddam H, Kangari H. The prevalence and determinants of pterygium in rural areas. J Curr Ophthalmol. 2016;29(3):194-8.⁾⁾	Australia	1344	18-22	1.2	Male sex	Age, height, weight, education level
Pyo EY et al, 2016⁽⁽¹⁴14 Pyo EY, Mun GH, Yoon KC. The prevalence and risk factors for pterygium in South Korea: the Korea National Health and Nutrition Examination Survey (KNHANES) 2009-2010. Epidemiol Health. 2016;38:e2016015.⁾⁾	South Korea	9193	≥40	8.8	Older age, male sex, rural residence, low education level, low income, sunlight exposure, and hypertension	Alcohol, BMI^* * = Body Mass Index; , diabetes, and hypercholesterolemia
Hashemi H et al, 2017⁽⁽²³23 Instituto Brasileiro de Geografia e Estatística (IBGE). Censo demográfico 2010: Ribeirão Preto, 2010. Rio de Janeiro, IBGE; 2020 [citado 2020 Nov 29]. Disponível em: https://cidades.ibge.gov.br/brasil/sp/ribeirao-preto/panorama⁾⁾	Iran	3312	All age	13.1	Older age	Sex, education level
Fernandes, A. G, 2019⁽⁽⁹9 Fernandes AG, Salomao SR, Ferraz NN, Mitsuhiro MH, Furtado JM, Munoz S, et al. Pterygium in adults from the Brazilian Amazon Region: prevalence, visual status and refractive errors. Br J Ophthalmol. 2020;104(6):757-63.⁾⁾	Brazil	2041	≥45	58.8	Male sex, older age, and rural residence	Higher education was a protective factor

Portuguese version	English version
1. Você sente os olhos secos?	1. Do you feel your eyes dry?
( ) Nunca ( ) Raramente ( ) Frequentemente ( ) Sempre	( ) Never ( ) Rarely ( ) Often ( ) Always
2. Você sente os seus olhos irritados?	2. Do you feel your eyes irritated?
( ) Nunca ( ) Raramente ( ) Frequentemente ( ) Sempre	( ) Never ( ) Rarely ( ) Often ( ) Always
3. Você já teve diagnóstico de olho seco?	3. Have you ever had a dry eye diagnosis?
( ) Sim ( ) Não	( ) Yes ( ) No
a) Dry eye symptom questionnaire: Portuguese and English versions
Systemic	Ocular
Diabetes mellitus	Eye surgery
Postmenopausal women	Computer and/or mobile 2 hours or more daily
Rheumatological diseases	Contact lens
Leprosy	Trachoma
Chemotherapy	Pterygium
Radiotherapy
Thyroid disease
Antidepressants
Antiallergic
Chronic Pelvic Pain
Fibromyalgia
Dyslipidemia

Factor (N)	N with PT^* * = Pterygium (%)	OR ^† † = Odss ration. (95% CI)	Fisher's exact test p value
Systemic
Female (419)	68 (16.23)	0.44 (0.29-0.67)	0.0002
Male (181)	55 (30.39)	2.25 (1.50-3.39)	0.0002
Dibetes (160)	123 (76.88)	0.81 (0.51-1.29)	0.42
Women menopause (302)	53 (17.55)	1.45 (0.78-2.68)	0.30
Rheumatic disease (86)	17 (19.77)	0.95 (0.53-1.68)	1.00
Past of leprosy (4)	2 (50)	3.93 (0.55-28.17)	0.19
Chemotherapy (24)	2 (8.33)	30.08 (8.91-101.6)	<0.0001
Radiotherapy (24)	2 (8.33)	30.08 (8.91-101.6)	<0.0001
Thyroid disease (86)	20 (23.25)	1.21 (0.70-2.08)	0.47
Oral antidepressants (142)	29 (20.42)	0.99 (0.62-1.58)	1.00
Oral Antiallergics (60)	11 (18.33)	0.86 (0.43-1.70)	0.74
Dyslipidemia (191)	38 (19.89)	0.95 (0.62-1.45)	0.83
Ocular
Contact lens use (7)	1 (14.28)	0.64 (0.08-5.40)	1.00
Ocular surgery (80)	33 (41.25)	1.17 (0.74-1.83)	0.56
Past of trachoma (7)	1 (14.28)	0.64 (0.08-5.40)	1.00
Computer or cell phone 2h or more/day (74)	17 (22.97)	1.18 (0.66-2.11)	0.54

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[1] Corresponding author: Leidiane Adriano Pereira. E-mail: leidianeadriano@hotmail.com