Abstract
Purpose:
To investigate the epidemiological characteristics of dry eye disease (DED) in Asian populations and among females.
Methods:
This study utilized the literature-derived database on DED risk factors, which includes data from 119 studies, and followed an evidence-based medicine retrieval strategy, searching globally for studies on risk factors for DED. Specifically, we focused on the Asian and Asian female populations. A descriptive statistical analysis was conducted on the definitions and prevalence of DED as provided in the database.
Results:
The study included a total of 139,556 participants, of which 74,258 were females. The overall prevalence of DED in Asians was found to be 23.9%, and it was observed to increase with age. Specifically, the prevalence was 16.2% in the group aged <30 years, and it increased to 26.7% in the group aged over 70 years. Among females, the prevalence of DED was higher at 28.1% compared to males at 20.1%. Furthermore, the prevalence of DED in females also increased with age, ranging from 39.9% in the group aged <40 years to 42.2% in the group aged over 60 years. The prevalence of DED between 2016 and 2022 was 35.3%, which indicated a significant increase of 14.6% compared to the period between 2008 and 2015. Notably, there were variations in the prevalence of DED across different regions and levels of development.
Conclusions:
This study reveals a common occurrence of DED among Asians and women. The prevalence rates vary among different countries, regions, development levels, and sample sizes, and there is an observed upward trend with the increase in survey year and age.
Keywords: Asian region, Descriptive study, Dry eye disease, Female
INTRODUCTION
Dry eye disease (DED) is a prevalent and complex ocular surface disease characterized by tear film instability. It leads to ocular discomfort, visual impairment, and damage to the ocular surface tissue.1 The occurrence of DED is influenced by various factors, including age, gender, environment, lifestyle, nutrition, cosmetics, drugs, systemic diseases, and ocular surgery.2,3 According to the Tear film and ocular surface Society’s Dry Eye Workshop II (TFOS DEWS II) epidemiological report,4 DED has a prevalence ranging from 5% to 50%, making it a significant global public health concern. Yu et al. estimated that managing DED in the United States costs approximately 5.5 billion USD annually.5 This condition imposes a substantial burden on patients’ quality of life and socioeconomic aspects, impacting their work efficiency, learning ability, mental health, and social activities.
Asia is known for having a high incidence of DED, and being of Asian race is considered a significant risk factor. In fact, the prevalence of DED among Asians is estimated to be 1.5–2.2 times higher compared to Caucasians.4 The Asian region is made up of several subregions, namely East Asia, Southeast Asia, South Asia, and West Asia. These subregions have large populations with varying densities, diverse lifestyles, and different levels of economic development. Consequently, the epidemiological characteristics of DED in the Asian region can exhibit significant variations and complexities.
Females are often considered a high-risk group for DED, exhibiting a higher prevalence compared to males.6,7 This difference may be attributed to changes in female hormone levels,8 including those associated with the menstrual cycle, pregnancy, lactation, and menopause. Other factors such as the use of certain drugs like contraceptives and diuretics,9 ocular structure, genetic susceptibility,8 and various other factors may also contribute to the occurrence of DED in women. Furthermore, the severity and impact of DED in female patients may be greater than in male patients.10
The studies of DED in Asia have mostly concentrated on various countries, with little information available on the overall prevalence among Asian people. Furthermore, there is a need to explore the prevalence of DED among Asian women to fill gaps in existing studies and highlight prevention in this specific demographic. This study aims to perform a descriptive analysis of the epidemiology of DED in Asia, particularly among females, and examine its prevalence, distribution characteristics, and associated factors.
METHODS
This study utilized a dataset on risk factors for DED (DrDED) developed by our team.11 The DrDED offers a comprehensive collection of demographic, clinical, and lifestyle data derived from both patients with DED and matched control groups across diverse geographical locations. The DrDED compiles risk factors for DED from a systematic review of 119 observational studies conducted from 2000 to 2022. These studies were carefully selected from databases including PubMed, Embase, Web of Science, and the Cochrane Library, following evidence-based medicine search strategies. Each study underwent a thorough quality assessment using the Newcastle–Ottawa Scale, ensuring that only high-quality data were incorporated. This meticulous approach provides a robust foundation for analyzing the complex risk factors associated with DED. The database is publicly accessible at https://doi.org/10.1038/s41597-023-01931-8. Given the reliance of database on publicly accessible data, whose original studies had already obtained the necessary ethical approvals and consents, no further ethical clearance was deemed necessary for this study.
To investigate the epidemiological characteristics of DED in Asian and female populations, the DrDED database underwent a systematic selection process. Initially, studies conducted in different regions of Asia including East Asia, Southeast Asia, West Asia, and South Asia were filtered based on the provided geographical information. Subsequently, studies that specifically focused on female populations were chosen. This included studies that either only had women as participants or did subgroup analyses for women in studies with people of both sexes. Finally, studies reflecting DED prevalence and distribution in Asian regions and female populations were chosen based on the provided information. Following these selection steps, the study identified 24 eligible articles. It is possible to get the 24 studies that were collected from DrDED information as well as all of the data that were used for statistical analysis from Supplementary Table 1.
This study conducted descriptive statistical analysis on the screened 24 literature, including basic information (such as author, year, country or region, and sample size), DED definition (such as diagnostic criteria and method), and DED prevalence (such as overall prevalence, stratified prevalence by gender, age, region, development level, and other factors). Statistical analyses were performed using the SPSS 20 (SPSS Inc., USA) and Stata 16 (Stata Corp., College Station, TX, USA). The results were summarized using a forest plot (random effects model) to present the prevalence data derived from DrDED. To ensure that the results are trustworthy, it is important to access them with updated studies.12 In this study, we followed the previous systematic search method and conducted an updated search for studies to compare our findings. The inclusion criteria for updated studies were as follows: (1) studies reported in the English language, (2) studies from which the prevalence of Asian females can be derived from the complete text, (3) studies of the same type as those extracted by DrDED: cross-sectional studies, and (4) studies providing complete information on the research and subjects (author, publication year, country, participant age, and gender). The exclusion criteria primarily included nonoriginal research, case reports, studies with unextractable data on Asian female populations, and noncross-sectional studies. Figure 1 provides a concise overview of the study selection process and the inclusion and exclusion criteria.
Figure 1.
A concise overview of the study selection process and the inclusion and exclusion criteria. DED: Dry eye disease
RESULTS
The characteristics of the 24 studies obtained from DrDED are summarized in Table 1. These studies were published between 2002 and 2020, with 66.7% of them being published in the last 10 years (2012–2022). The studies involved 7 countries or regions in Asia, primarily China (n = 6), South Korea (n = 9), and Japan (n = 4). The sample size of these studies ranged from 356 to 17,364 people, with a total sample size of 139,556 people, including 74,258 women, with a median of 2565 people and an average of 5815 people. All these studies were cross-sectional studies.
Table 1.
Characteristics of included studies exported from dataset on risk factors for dry eye disease
| Author | Year | Country | Sample | Prevalence (%, female) | Definition | Development level | Age | Survey year | PMID | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||||
| Total | Male | Female | |||||||||
| Lee et al. | 2002 | Indonesia | 1058 | 505 | 553 | 27.5 (24.9~30.3) | Symptom-based | Developing | >21 | 2001 | 12446361 |
| Lin et al. | 2003 | China | 1361 | 822 | 539 | 33.7 (31.3~36.3) | Symptom-based | Developing | >65 | 1999 | 12799232 |
| Lu et al. | 2008 | China | 1840 | 1031 | 809 | 52.4 (50.2~54.7) | Symptom-based | Developing | ≥40 | 2006 | 18520503 |
| Uchino et al. | 2008 | Japan | 4393 | 2640 | 909 | NA | Comprehensive assessment | Developed | 22–60 | 2006 | 18708259 |
| Jie et al. | 2009 | China | 1957 | 845 | 1112 | 21.0 (19.3~22.9) | Clinical examination | Developing | ≥40 | 2001 | 18309341 |
| Guo et al. | 2010 | China | 2486 | 979 | 837 | 45.3 (43.3~47.2) | Symptom-based | Developing | ≥40 | 2006 | 20642346 |
| Uchino et al. | 2011 | Japan | 2644 | 1221 | 1423 | NA | Comprehensive assessment | Developed | ≥40 | 2010 | 21889799 |
| Tan et al. | 2015 | Singapore | 1004 | 443 | 561 | 13.2 (10.4~14.4) | Symptom-based | Developed | 15–83 | 2010 | 25269444 |
| Roh et al. | 2016 | Korea | 17,364 | 7365 | 9999 | 10.4 (10.0~10.9) | KNHANES-derived DED | Developed | ≥20 | 2010–2012 | 26488632 |
| Shanti et al. | 2020 | Palestine | 769 | 364 | 405 | 64.0 (60.5~67.3) | Comprehensive assessment | Developing | 18–90 | 2016–2017 | 31931756 |
| Um et al. | 2014 | Korea | 16,431 | 7033 | 9398 | NA | KNHANES-derived DED | Developed | ≥30 | 2010–2012 | 25128034 |
| Gong et al. | 2017 | China | 1015 | 301 | 714 | 27.8 (25.1~30.6) | Comprehensive assessment | Developing | >18 | 2013 | 28276756 |
| Ahn et al. | 2017 | Korea | 16,824 | 7104 | 9720 | NA | KNHANES-derived DED | Developed | ≥19 | 2010–2012 | 28860734 |
| Jeong et al. | 2018 | Korea | 9752 | 4441 | 5311 | 8.4 (7.9~9.0) | KNHANES-derived DED | Developed | ≥19 | 2010–2012 | 30049179 |
| Kim et al. | 2019 | Korea | 4185 | 1787 | 2398 | 19.3 (18.1~20.5) | KNHANES-derived DED | Developed | ≥65 | 2010–2012 | 30369215 |
| Inomata et al. | 2020 | Japan | 4454 | 1483 | 2972 | NA | Symptom-based | Developed | NA | 2016–2018 | 32113987 |
| Lee et al. | 2015 | Korea | 6023 | 3203 | 2820 | 16.0 (15.1~16.9) | KNHANES-derived DED | Developed | 25–65 | 2010–2012 | 26511443 |
| Park et al. | 2016 | Korea | 15,294 | 6526 | 8768 | 17.7 (17.1~18.3) | KNHANES-derived DED | Developed | ≥19 | 2010–2012 | 27366012 |
| Arita et al. | 2019 | Japan | 356 | 133 | 223 | 33.4 (28.7~38.5) | Comprehensive assessment | Developed | 6–96 | NA | 30851269 |
| Tandon et al. | 2020 | India | 9735 | 4426 | 5307 | 26.2 (25.3~27.1) | Comprehensive assessment | Developing | ≥40 | 2010–2016 | 32783926 |
| Chatterjee et al. | 2020 | India | 2378 | 1397 | 981 | 11.4 (10.2~12.7) | Symptom-based | Developing | ≥20 | 2019–2020 | 33913832 |
| Choi et al. | 2021 | Korea | 475 | 184 | 291 | 48.4 (44.0~52.9) | Symptom-based | Developed | <50–≥70 | 2013 | 33522358 |
| Wu et al. | 2021 | China | 1287 | 433 | 854 | 54.2 (51.4~56.9) | Comprehensive assessment | Developing | >40 | 2020–2021 | 34901096 |
| An et al. | 2022 | Korea | 16,471 | 6937 | 9534 | 17.8 (17.3~18.4) | KNHANES-derived DED | Developed | ≥20 | 2010–2012 | 35773440 |
PMID: PubMed unique identifier, NA: Not available, DED: Dry eye disease, KNHANES: Korea National Health and Nutrition Examination Survey
The primary definitions of DED encompass three approaches: symptom-based, clinical examination-based, and comprehensive assessment-based definitions, as shown in Table 2. Symptom-based definition is to use questionnaires or scales as tools to assess and diagnose dry eye symptoms. Questionnaires or scales usually include a series of questions about eye discomfort, visual symptoms, environmental factors, and impact on quality of life. The presence of dry eye and foreign body symptoms such as sensation is diagnosed as dry eye. The definition based on clinical examination is to evaluate the degree of eye dryness through examination indicators such as tear secretion volume and tear film break-up time (TBUT). If the examination indicators are lower than the threshold, dry eye is diagnosed. The definition based on comprehensive assessment is the presence of dry eye-related symptoms and the clinical examination index is below the threshold. Korea National Health and Nutrition Examination Survey (KNHANES)-derived DED is the analysis of DED data from the KNHANES. KNHANES included health interviews, nutritional status, and exams. Ophthalmologic questionnaires and examinations in KNHANES were administered to participants aged 40 years and older. The questionnaires covered various ocular diseases, including DED, but were not exclusively tailored for DED assessment.13
Table 2.
Definitions of dry eye disease used in the included studies
| Definition types | Definition | Diagnostic criteria/method | PMID |
|---|---|---|---|
| Symptom-based definition | Frequently or always have one or more of the six common dry eye symptoms | Assess symptoms according to the six-item questionnaire on dry eye symptoms by Schein et al. | 12446361; 12799232; 18520503; 20642346 |
| Frequently or always have one of the five common self-reported symptoms | Assess symptoms according to the McMonnies scale | 25269444 | |
| OSDI ≥13 | Assess symptoms according to the OSDI questionnaire | 32113987; 33522358 | |
| Clinical examination-based definition | Involving six definitions that combined TBUT, Schirmer score, fluorescein score eyelid margin features, and meibomian gland status | Asian Dry Eye Society diagnostic criteria; China Dry Eye Diagnostic Criteria | 18309341 |
| Comprehensive assessment-based definition | OSDI score ≥13 and at least one of the following signs in the affected eye: TBUT ≤10 s, Schirmer score ≤5 mm, fluorescein corneal staining ≥1 grade | Assess symptoms according to the OSDI questionnaire; China Dry Eye Diagnostic Criteria | 31931756 |
| Presence of dry eye symptoms and at least two clinical signs | Asian Dry Eye Society diagnostic criteria | 28276756 | |
| Presence of any DED symptoms; FBUT ≤5 seconds | Japan Dry Eye Diagnostic Criteria | 30851269 | |
| OSDI score ≥13 and either TBUT <10 s or evidence of ocular surface staining in either eye | Assess symptoms according to the OSDI questionnaire; TFOS DEWS II report | 32783926 | |
| OSDI score ≥13 and one of the following: (1) TBUT ≤10 s (2) Schirmer score ≤10 mm | Assess symptoms according to the OSDI questionnaire; China Dry Eye Diagnostic Criteria | 34901096 | |
| Presence of previous clinical diagnosis of DED by an eye specialist or severe symptoms of DED (persistent or frequent dryness and irritation) | Japan Dry Eye Diagnostic Criteria; Assess symptoms based on the dry eye questionnaire by Schaumberg et al. | 18708259; 21889799 | |
| KNHANES- derived DED | Diagnosed with DED by an ophthalmologist | Assess symptoms using the KNHANES | 35773440; 26488632 |
| Diagnosed with DED by an ophthalmologist or presence of dry eye symptoms | Assess symptoms using the KNHANES | 25128034; 28860734; 30049179; 30369215 | |
| Have dry eye-related symptoms | Assess symptoms using the KNHANES | 26511443; 27366012 |
PMID: PubMed unique identifier, OSDI: Ocular surface disease index, KNHANES: Korea National Health and Nutrition Examination Survey, TBUT: Tear break-up time, FBUT: Fluorescein break-up time, TFOS DEWS II: Tear film and ocular surface Society’s Dry Eye Workshop II, DED: Dry eye disease
The literature commonly uses a symptom-based definition, which was employed in seven studies. Questionnaires or scales such as the ocular surface disease index and McMonnies scales were frequently utilized for this approach. In contrast, the use of a clinical examination-based definition was less common, with only one study employing it. Indicators such as TBUT and the Schirmer I score were commonly used in this approach. A comprehensive assessment-based definition was employed in 7 studies, with commonly used standards such as the Chinese dry eye diagnostic criteria and the Asian dry eye society diagnostic criteria. Furthermore, eight studies focused on defining KNHANES-derived DED, representing a noteworthy segment of the research.
The overall prevalence of DED in the Asian population was 23.9% (95% confidence interval [CI]: 21.2%~26.7%). Figure 2 presents an overview of the prevalence rates for Asian individuals as a whole, along with separate rates for Asian women and Asian men. Notably, there has been a significant increase in DED prevalence from 2016 to 2022, reaching 35.3% (95% CI: 22.2%~48.4%). This represents a 14.6% increase compared to the period from 2008 to 2015 [Table 3]. The overall prevalence of DED varies significantly across different samples, ranging from a minimum of 5.2%9 to a maximum of 64.0%,14 with a median of 17.8%.15
Figure 2.
A comprehensive summary of prevalence rates, encompassing rates for the Asian population, Asian women, and Asian men. CI: Confidence interval. I2: Statistical measure used to assess the degree of heterogeneity, P: The significance test for I2, with P < 0.05, suggests a significant heterogeneity among the results
Table 3.
Subgroup analysis of the prevalence of dry eye disease in female population in Asia
| Study (n) | Population (N) | Prevalence (%) (95% CI) | I 2 | P | |
|---|---|---|---|---|---|
| Gender | |||||
| Female | 24 | 101,701 | 28.1 (25.0~31.2) | 99.4 | <0.001 |
| Male | 24 | 82,560 | 20.1 (17.5~22.8) | 99.4 | <0.001 |
| Age (total) | |||||
| <30 | 5 | 7269 | 16.2 (11.9~20.5) | 95.9 | <0.001 |
| 30~40 | 7 | 20,011 | 15.3 (11.9~18.7) | 97.7 | <0.001 |
| 40~50 | 12 | 26,396 | 18.4 (14.8~22.0) | 98.6 | <0.001 |
| 50~60 | 12 | 24,533 | 22.0 (18.0~26.0) | 98.6 | <0.001 |
| 60~70 | 13 | 22,785 | 25.7 (21.0~30.4) | 98.9 | <0.001 |
| >70 | 12 | 23465 | 26.7 (21.1~32.2) | 99.4 | <0.001 |
| Age (female) | |||||
| <40 | 3 | 5707 | 39.9 (1.20~90.0) | 99.9 | <0.001 |
| 40~60 | 4 | 10,673 | 40.7 (7.20~74.1) | 99.9 | <0.001 |
| >60 | 4 | 7917 | 42.2 (7.60~76.9) | 99.9 | <0.001 |
| Region | |||||
| East Asia | 19 | 93,894 | 28.4 (19.4~37.3) | 99.8 | <0.001 |
| China | 6 | 4865 | 41.8 (30.1~53.6) | 98.7 | <0.001 |
| Japan | 4 | 15,226 | 26.2 (19.1~33.4) | 99.2 | <0.001 |
| Korea | 9 | 73,803 | 21.9 (18.6~25.3) | 99.3 | <0.001 |
| Southeast Asia | 2 | 1114 | 18.7 (10.9~26.6) | 91.5 | <0.001 |
| Indonesia | 1 | 553 | 22.8 (19.3~26.3) | NA | <0.001 |
| Singapore | 1 | 561 | 14.8 (11.9~17.7) | NA | <0.001 |
| South Asia | 2 | 6288 | 24.7 (23.7~25.8) | NA | <0.001 |
| India | 2 | 6288 | 24.7 (23.7~25.8) | NA | <0.001 |
| West Asia | 1 | 405 | 70.4 (65.9~74.8) | NA | <0.001 |
| Palestine | 1 | 405 | 70.4 (65.9~74.8) | NA | <0.001 |
| Definition | |||||
| Symptom-based | 8 | 13,487 | 31.7 (23.0~40.5) | 99.3 | <0.001 |
| Comprehensive assessment | 7 | 13,590 | 34.1 (24.4~43.8) | 99.5 | <0.001 |
| Clinical examination | 1 | 1112 | 23.9 (21.5~26.5) | NA | <0.001 |
| KNHANES-derived DED | 8 | 73,512 | 19.5 (16.2~22.8) | 99.4 | <0.001 |
| Development level | |||||
| Developed | 14 | 89,590 | 23.4 (20.5~26.3) | 99.2 | <0.001 |
| Developing | 10 | 12,111 | 37.9 (26.8~49.0) | 99.5 | <0.001 |
| Survey year | |||||
| 2000–2007 | 5 | 5129 | 36.5 (24.5~48.5) | 98.9 | <0.001 |
| 2008–2015 | 13 | 88,208 | 20.7 (18.0~23.3) | 99.0 | <0.001 |
| 2016–2022 | 4 | 11,156 | 35.3 (22.2~48.4) | 99.7 | <0.001 |
| Sample | |||||
| <1000 | 3 | 919 | 55.0 (38.0~72.0) | 96.5 | <0.001 |
| 1000–5000 | 13 | 14,662 | 28.6 (22.6~34.6) | 99.3 | <0.001 |
| >5000 | 8 | 67,023 | 20.0 (16.5~23.5) | 99.4 | <0.001 |
I2: Statistical measure used to assess the degree of heterogeneity, N/A: Not applicable, CI: Confidence interval, DED: Dry eye disease, KNHANES: Korea National Health and Nutrition Examination Survey
The prevalence of DED in the female population was 28.1% (95% CI: 25.0%~31.2%), which was higher than the prevalence of DED in the male population at 20.1% (95% CI: 17.5%~22.8%). Among different samples, there was also significant variation in the prevalence of DED among females, ranging from a minimum of 7.9% to a maximum of 70.4%. The median prevalence was 23.5%, with an average of 28.4%.
Among the 24 pieces of literature screened, 19 came from East Asia, 2 from Southeast Asia, 2 from South Asia, and 1 from West Asia. This study found that the prevalence of DED in the female population in West Asia was 70.4% (95% CI: 65.7%~74.8%), significantly higher than other regions, followed by East Asia with a prevalence of 28.4% (95% CI: 19.4%~37.3%), among which China had the highest prevalence of 41.8% (95% CI: 30.1%~53.6%). In addition, it was also found that in Asia, the prevalence of DED in the female population in developing countries was 37.9% (95% CI: 26.8%~49.0%), significantly higher than that in developed countries, which was 23.4% (95% CI: 20.5%~26.3%) [Table 3]. Given that the sole study from Western Asia had the highest prevalence, the adjusted prevalence of DED in Asia, excluding Western Asia, stands at 21.6% (95% CI: 18.5%~24.8%). This prevalence may more accurately reflect the situation in Eastern and Central Asian countries, as the majority of the data in our study comes from Eastern and Central Asian populations, with a significant number of studies – 23 in total – originating from these regions.
The prevalence of DED in the Asian population has an increase with age, from 16.2% for the age group <30 years to 26.7% for the age group >70 years. Similarly, the prevalence of DED in the female population also showed a similar trend, from 39.9% for the age group <40 years to 42.2% for the age group >60 years, which means that elderly women are more likely to suffer from DED than middle-aged and young women. This study also described the prevalence distribution by sample size and other characteristics, as shown in Table 3.
When categorizing the prevalence of DED in Asia by definition, we noted variations across different diagnostic approaches. For the symptom-based definition, the lowest reported prevalence is 11.4%, and the highest is 52.4%. In the comprehensive assessment category, the lowest reported prevalence is 26.2%, and the highest reaches 64.0%. Under the clinical examination definition, there is only one study, which reports a prevalence of 21.0%. For KNHANES-derived DED, the lowest reported prevalence is 8.4%, and the highest is 19.3% [Table 1].
In analyzing the prevalence of DED among Asian females categorized by different diagnostic criteria, we find variations in the reported rates. The symptom-based definition, as represented by eight studies, reports an overall prevalence of 31.7% (range, 23.0%–40.5%). This indicates a relatively high prevalence, suggesting that symptom-based assessments commonly detect a significant prevalence of DED among females. The comprehensive assessment-based definition, represented by seven studies, shows the highest overall prevalence at 34.1% (range, 24.4%–43.8%), likely due to its inclusion of multiple diagnostic criteria which may capture a broader spectrum of symptoms and conditions. In contrast, the clinical examination-based definition, covered in only one study, reports the prevalence at 23.9% (range, 21.5%–26.5%). Finally, the KNHANES-derived DED, which includes eight studies, reveals a lower prevalence of 19.5% (range, 16.2%–22.8%), potentially reflective of the specific demographic and methodological approaches of the KNHANES studies [Table 3]. This analysis suggests that the method of assessment may influence the reported prevalence of DED among Asian females.
The system retrieved and screened three updated studies for comparison with the results from DrDED. These studies include research published by Albdaya et al. in 2022, a study by Murakami et al. published in March 2023, and a study by Li et al. published in May 2023.16,17,18 Figure 3 displays a comparison of the prevalence of DED among female participants in these three updated research studies and those that have been conducted by DrDED at the national and regional levels. About 71.6% of females are affected by DED, according to the findings of a study that was conducted by Albdaya et al.18 These data are consistent with the findings of another study included in DrDED, also originating from West Asia, indicating further evidence that the West Asian region exhibits the highest incidence rate among Asian women.14,18 The study by Li et al. reflects that the prevalence of diagnosed DED among women in the Xinjiang region of China is 41.9%, indicating a moderate distribution in the country.16 According to the findings of the study conducted by Murakami et al., the prevalence of women who experience DED, as perceived by them, is 39.8%, while the prevalence of female patients who are diagnosed with DED is 9.3%.17 Hence, when considering a combined prevalence, the results reported by Murakami et al. regarding the prevalence of DED in women could be considered moderately consistent with the evidence provided by DrDED. In conclusion, the observed consistency between the results of the three updated studies on the prevalence of DED in Asian women and those derived from internal studies in DrDED is relatively acceptable.
Figure 3.
The three update studies involve the prevalence rates of Asian women, comparing them with the previous research conducted by dataset on risk factors for dry eye disease at the national and regional levels
DISCUSSION
The objective of this study is to investigate the epidemiological characteristics of DED in Asian regions, particularly among female populations. The findings indicate a high prevalence of DED in Asian regions, especially among women. According to recent studies, the prevalence of DED in Europe is 13.7%, while South America and Oceania have rates of 14.7% and 14.9%, respectively.19 In our study, DED appears to be common in the Asian region at a rate of 23.9%, which is higher than in most other regions; furthermore, the prevalence grows with age, which is consistent with previous findings.4,20 Similar trends can be recognized among Asian women, with a notably higher prevalence of DED compared to males.
The number of studies investigating the relationship between DED and socioeconomics is currently limited.21 A review indicated that the prevalence of DED tends to decrease from low- and middle-income nations to high-income countries when the economic level is measured by per capita GDP.22 According to our study, the prevalence of DED among women in developing countries was nearly 1.6 times higher than that of women in developed countries. However, further research is needed to confirm this association.
The prevalence of DED in Asian women raised further significantly between 2016 and 2022, increasing by 14.6% over the 2008–2015 period. This upward trend is believed to be associated with changes in lifestyle, particularly the increased use of visual display terminals, as well as the impact of the new coronavirus epidemic. Previous studies have shown a significant increase in the prevalence of DED among users of visual display terminals23 and individuals infected with the new coronavirus.24,25,26 The assumption has three supporting aspects. First, the popularity of video terminals such as mobile phones and computers in Asia during this period may have contributed to the development of video terminal-related DED.26 Furthermore, the emergence of the novel coronavirus in 2019 has caused a rise in individuals isolating at home, leading to heightened engagement with video screens, and a decrease in the demand for treatments associated with DED.26 Finally, direct infection with the virus may also be a contributing factor.25
The prevalence of DED in the Asian region has been extensively studied.19,27,28 Reports indicate rates ranging from 20.0% to 52.4% in East Asia (China, Japan, and Korea), as documented in the TFOS DEWS II epidemiological study on DED.4 Our findings in the same region align with these results, showing a prevalence of 28.4%. However, the study also reported a lower prevalence among Asian women at 21.6%, contrasting with our research result of 28.1%. In addition, a review of DED prevalence in China estimated it to be 13.55% based on symptoms and signs, which is lower than the result of our study of 41.8%.29 We identified several factors that could contribute to the disparities in these prevalence estimates. First, variations in participant characteristics, such as age, gender, race, level of development in the country or region, lifestyle, and environmental differences, may influence the results.30 Second, inconsistencies in the diagnostic criteria included in the literature may also play a role. While some studies suggest that 97.2% of patients diagnosed with DED in China also meet the criteria for Asian dry eye diagnosis,31 there is a lack of research on the concordance rates between other diagnostic criteria. Moreover, many studies relied on subjective symptoms as the definition of DED. Among the selected literature in this study, 10 articles used definitions based solely on patients’ subjective symptoms. Studies based on subjective symptoms often report higher and more variable disease prevalence, reaching up to 70.4% in certain populations.14 These discrepancies impact the comparability and reliability of DED prevalence data.
Our study has several limitations. First, the majority of our research focuses on East Asia, with limited studies from Southeast Asia and Western Asia. For instance, there is only one study from Western Asia that reports a notably higher prevalence, significantly influencing the overall prevalence. Future research should therefore prioritize these regions. Increased attention to these areas will contribute to a more accurate representation of the prevalence of DED across the entire Asian continent. In addition, we found significant variation in the prevalence of DED across the literature (I2 = 99.6%) [Figure 1]. Therefore, the representativeness of the entire Asian region may be compromised. Second, when designing DrDED, we only considered high-quality English studies, potentially excluding some high-quality studies in other languages. Third, the studies included in our analysis used different definitions of DED, so the results should be interpreted with caution added a discussion about the limitations of our study regarding the lack of attention to the male population. Finally, the lack of attention of our study to the male population may lead to an unbalanced representation of both genders.
Despite the aforementioned limitations, our study has several strengths. First, it is based on high-quality research included in the peer-reviewed DrDED. Second, at the regional and national levels, we compared updated studies with the prevalence of DED among Asian women derived from DrDED. The findings of this comparison are relatively similar, suggesting that DrDED is credible and could be employed to investigate the prevalence and distribution characteristics of DED in Asian populations, including Asian women. In addition, by utilizing this database of risk factors for DED, researchers can expedite the collection of more information about DED, contributing to advancements in this research field. Finally, building upon this foundation, our study explores the prevalence and distribution characteristics of DED in the Asian region and among female populations. The findings of a higher prevalence of DED in Asian populations and among Asian women, combined with the provided data support, can contribute to increasing awareness in the region and emphasize the need for preventive measures.
In summary, this article described the epidemiological characteristics of DED in the Asian region and among female populations, revealing its widespread presence in both groups along with an increasing trend and significant disparities and variations. The study also found that there are substantial differences and inconsistencies in the definitions, diagnostic criteria, and methods for DED across different literature sources, which affected the comparability and credibility of DED prevalence data. Therefore, it is suggested that future epidemiological studies of DED should follow internationally recognized or recommended DED definitions or diagnostic criteria or methods to improve the quality and comparability of DED prevalence data. In addition, future epidemiological studies of DED should conduct causal inference analysis to determine the relationship or mechanism between DED prevalence and various potential risk factors, as well as the sources or explanations of heterogeneity among different literature. This study aspires to contribute to the prevention and treatment of DED.
Conflicts of interest
There are no conflicts of interest.
Acknowledgments
This study was supported by grants from the Scientific Research Fund Project of Aier Eye Hospital Group (No. AR2210D2). The funders had no role in the design, data acquisition, or manuscript preparation of the present study.
SUPPLEMENTARY FILE
Supplementary Table 1 provides detailed prevalence of dry eye disease (DED) derived from dataset on risk factors for DED sources, including data related to Asia, Asian women, and Asian men. Also include specific distribution information on the age, countries, regions, survey periods, and sample sizes of Asian women.
Supplementary Table 1.
Inclusion of literature prevalence - related data
| PMID | Age 40-50 (Case_Total) | Age 50-60 (N_Total) | Age 50-60 (Case_Total) | Age 60-70 (N_Total) | Age 60-70 (Case_Total) | Age >70 (N_Total) | Age >70 (Case_Total) | Age <40 (N_Women) | Age <40 (Case_Women) | Age 40-60 (N_Women) | Age 40-60 (Case_Women) | Age >60 (N_Women) | Age >60 (Case_Women) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 12446361 | 70 | 90 | 30 | 94 | 28 | ||||||||
| 12799232 | 481 | 155 | 880 | 304 | |||||||||
| 18520503 | 279 | 396 | 205 | 389 | 238 | 362 | 243 | ||||||
| 18708259 | 69 | 411 | 26 | ||||||||||
| 18708259 | 196 | 411 | 93 | ||||||||||
| 18309341 | |||||||||||||
| 20642346 | 297 | 539 | 273 | 317 | 189 | 204 | 150 | ||||||
| 21889799 | 5 | 289 | 10 | 290 | 6 | 426 | 4 | ||||||
| 21889799 | 21 | 289 | 33 | 290 | 30 | 426 | 56 | ||||||
| 21889799 | 24 | 289 | 38 | 290 | 33 | 426 | 58 | ||||||
| 25269444 | |||||||||||||
| 26488632 | 284 | 3,371 | 371 | 3,017 | 385 | 2,894 | 285 | 2,950 | 392 | 3,703 | 526 | 3,346 | 482 |
| 31931756 | |||||||||||||
| 25128034 | 284 | 3,534 | 371 | 3,146 | 385 | 3,054 | 285 | ||||||
| 25128034 | 463 | 3,534 | 595 | 3,146 | 582 | 3,054 | 519 | ||||||
| 28276756 | |||||||||||||
| 28860734 | 275 | 2,876 | 367 | 2,526 | 374 | 2,518 | 274 | ||||||
| 28860734 | 462 | 2,653 | 590 | 2,324 | 576 | 2,274 | 518 | ||||||
| 30049179 | |||||||||||||
| 30369215 | 1,392 | 287 | 2,793 | 519 | |||||||||
| 32113987 | |||||||||||||
| 32113987 | |||||||||||||
| 32113987 | |||||||||||||
| 26511443 | |||||||||||||
| 27366012 | 2,709 | 2,108 | 3,328 | 2,613 | 2,731 | 2,087 | |||||||
| 30851269 | 15 | 64 | 21 | 74 | 24 | 100 | 41 | 48 | 15 | 71 | 32 | 104 | 46 |
| 32783926 | 828 | 2,438 | 653 | 1,981 | 576 | 1,316 | 490 | 3,571 | 896 | 1,736 | 589 | ||
| 33913832 | |||||||||||||
| 33522358 | 155 | 68 | 171 | 93 | 120 | 58 | |||||||
| 34901096 | |||||||||||||
| 35773440 | 451 | 3,194 | 584 | 2,857 | 573 | 2,618 | 493 |
Funding Statement
Nil.
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