Vision Impairment and Associated
Factors in a Coastal Province of
Southern China: The Fujian Eye Study
Yang Li
1
,
2
,
3
†
, Qinrui Hu
1
,
2
,
3
†
, Xiaoxin Li
1
,
2
,
4
*, Yonghua Hu
3
*, Xueying Qin
3
, Bin Wang
1
,
2
and
Tao Ren
3
1
Eye Institute and Affiliated Xiamen Eye Center of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,
2
Fujian Provincial Key Laboratory of Corneal & Ocular Surface Diseases, Xiamen, China,
3
Department of Epidemiology and
Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China,
4
Department of Ophthalmology,
Peking University People’s Hospital, Beijing, China
Purpose: To evaluate the prevalence and correlations of vision impairment (VI) among
urban and rural adults in a coastal province of Southern China.
Design: Population-based cross-sectional study.
Methods: The study was designed to recruit residents aged over 50 years in randomly
sampled communities of Fujian Province from 2018 to 2019. Participants completed a
questionnaire about socioeconomic and biological factors and underwent visual
examinations. Best corrected visual acuity (BCVA) was measured for the participa nts
to assess VI, which was defined as best corrected visual acuity (BCVA) in better eyes of 20/
60 or worse.
Results: A total of 6,823 participants were included in this report. VI prevalence was higher
in inland populations, compared with that in coastal populations (5.08 vs. 2.79%, p <
0.001), but there was no significant difference between urban populations and rural
populations (2.97 vs. 3.73%, p = 0.082). VI was significantly associated with
sociodemographic and biological factors, which included age, educational
background, income, and refractive error. Sex and urbanization were not statistically
significantly associated with VI.
Conclusion: High prevalence of VI in southeast China suggested need for more
accessible services and favorable policies for enhancing eye health in rural and inland
elderly people.
Keywords: vision impairment (VI), associated factor, cross-sectional study, urban and rural, coastal and inland
INTRODUCTION
Vision impairment (VI) affects approximately 2.2 billion people globally, and the majority of them are over
the age of 50 years (World Health Organization Geneva, 2019). Thus, the improvement of visual function
has always been a major world health issue. The World Health Organization (WHO) adopted the
UniversalEyeHealth:AGlobalActionPlan2014–2019 at the World Health Assembly in 2013 (World
Health Organization, 2013), and one of the key objectives is to generate evidence on the magnitude of VI,
which affects quality of life, educational and economic opportunities, and risk of death (Bourne et al., 2017).
Edited by:
Xusan Yang,
Cornell University, United States
Reviewed by:
Dong Qin,
Henan Provincial Eye Hospital, China
Jing Feng,
Capital Medical University, China
*Correspondence:
Xiaoxin Li
Yonghua Hu
†
These authors have contributed
equally to this work and share first
authorship
Specialty section:
This article was submitted to
Biophotonics,
a section of the journal
Frontiers in Photonics
Received: 29 March 2022
Accepted: 11 May 2022
Published: 30 June 2022
Citation:
Li Y, Hu Q, Li X, Hu Y, Qin X, Wang B
and Ren T (2022) Vision Impairment
and Associated Factors in a Coastal
Province of Southern China: The Fujian
Eye Study.
Front. Photonics 3:906917.
doi: 10.3389/fphot.2022.906917
Frontiers in Photonics | www.frontiersin.org June 2022 | Volume 3 | Article 9069171
ORIGINAL RESEARCH
published: 30 June 2022
doi: 10.3389/fphot.2022.906917
According to the International Classification of Diseases
version 11, VI which includes presbyopia was classified as
mild VI, moderate VI, and severe VI, and only the definition
of distance visual acuity standard was given (World Health
Organization, 2019). It is obvious that VI has been reported
worldwide. However, various issues remain unclear, including the
prevalence and associations of general VI in the population. Most
of the studies reported urbanization and geographic location
separately. To address these gaps in knowledge, a population-
based cross-sectional survey, the Fujian Eye Study (FJES), was
conducted on residents aged 50 years and above in Fujian
Province of southern China. It is the initial report about the
prevalence and associations of VI in a whole province of southern
China. Also, the study assessed both urbanization and geographic
location factors under the same baseline. The aim of this study
was to estimate the overall VI and its related factors among adults
using a more comprehensive approach, so as to provide the latest
data for planning and policy-making.
METHODS
Study Design
The Fujian Eye Study (FJES) is a population-based, cross-sectional
investigation on the residents’ state of eye health in Fujian Province,
southeast China. The report of the World Health Organization
(WHO) in 2019 showed VI affects approximately 2.2 billion people
globally, and the majority of them are over the age of 50 years
(World Health Organization Geneva, 2019). Most fundus diseases
also occur in people over 50 years old, and most of them are retired
at home, which makes them easy to recruit. With the aggravation of
population aging in China, research on eye diseases in people over
50 years old is imperative. Therefore, this study investigated the
prevalence and related factors of VI in community members aged
50 years and above. Random cluster sampling was used in this
investigation, and the calculation formula and sample size have been
reported (Li et al., 2022). The Ethics Commit tee of Xiamen Eye
Center affiliated with Xiamen University approved the 2018–2019
FJES protocol (Acceptance Number: XMYKZX-KY-2018-001).
Recruitment Procedures
Participants underwent a comprehensive physical examination in a
mobile clinic. Those who were unable to participate in on-site
examination in the screening were asked for the consent of home
visits and simple ophthalmic examinations. The main contents of this
study include the following: questionnaire (age, sex, and race;
educational background, income level, occupation, etc.); presenting
visual acuity; best corrected visual acuity (BCVA); and refractive state.
The flowchart of field screening has been reported (Li et al., 2022).
We used the E Standard Logarithmic Visual Acuity Chart (GB
11533–1989) for the visual acuity test at a distance of 5 m. The
study defined VI as BCVA in better eyes worse than 0.3 [equaled
with 20/60 in the WHO definition of VI (World Health
Organization, 2019)] and blindness as BCVA in better eyes of
0.05 or worse [equaled with 20/400 in the WHO definition of VI
(World Health Organization, 2019)].
Refractive errors [spherical (DS), cylinder (DC), axis (a)] were
conducted three times by Topcon KR800 (Topcon, Japan) in both
eyes, and the average was calculated as the final outcome.
Data Collation
Data were collated using double entry. Each resident has a unique
identification code to accurately locate their data. We
supplemented part of the missing data through telephone
follow-up. If we cannot contact the resident, it is considered
missing data.
Statistical Analysis
Data were analyzed using Stata/SE statistical software v15.1
(Stata for Windows, StataCorp LLC, Lakeway Drive, College
Station, TX, United States). Data are displayed in the mean ±
standard deviation (SD) form. Chi-square (x
2
) tests were used
for comparing proportions. Linear regression was used for
checking whether there was a correlation between VI and
research factors. Logistic regression was used to determine
the degree of correlation among each group. Multiple
regression was applied for testing the correlation between
VI (binary variable) and several parameters. The statistical
correlation was described using the correlation coef fi cient r
and the degree of correlation was shown as odds ratio (OR). A
p-value of less than 0.05 was considered statistically significant
for all the estimates.
RESULTS
Vision Impairment
A total of 6,823 participants were included in this study (Li et al.,
2022). The percentage and relationship of several VIs are
presented in Figure 1. There was no significant difference in
VI between the urban and rural groups, whereas VI was
significantly reduced in the coastal group compared with the
inland group (Figure 2).
Correlation of VI With Region
On the whole, VI (r = 0.017, p = 0.082) was independent of
urbanization. VI (r = 0.05, p < 0.001) showed a significant
correlation with geographic location.
Correlation of VI With Age
In general, VI (r = 0.14) showed a significant (p < 0.001)
correlation with age. Differentiating participants into the
urban group and rural group or the coastal group and inland
group yielded similar results (Figure 3).
Correlation of VI With Refractive Error
In all, VI (r = 0.18) was significantly (p < 0.001) correlated with
refractive error. The whole population was grouped according to
the degree of refractive error. The prevalence of VI increased
significantly with diopter deviation. The prevalence of VI in the
mild hyperopia group was low and also significantly increased
with the deviation of diopter (Figure 4).
Frontiers in Photonics | www.frontiersin.org June 2022 | Volume 3 | Article 9069172
Li et al. Vision Impairment in Southern China
Correlation of VI With Education
Generally, VI showed a significant (p < 0.001) association with
the degree of educational background (r = 0.20).
Given that the urban group and inland group had a significantly
higher education level (p < 0.001) (Li et al., 2022), the whole
population was grouped based on the education level and
showed similar results. With the improvement of education level,
the prevalence of VI gradually decreased (Figure 5).
Correlation of VI With Income
In general, VI showed a significant (p < 0.001) association with
the degree of income (r = 0.13).
Given that the urban population group (p < 0.001) and inland
population group (p < 0.001) had a significantly higher income,
the whole population was grouped according to the income level.
As the income level increased, the prevalence of VI also gradually
decreased (Figure 6).
FIGURE 1 | Percentage and relationship of presenting near vision impairment (PNVI), distance vision impairment (DVI), and combined vision impairment (CVI) inthe
Fujian Eye Study and the distribution of several global reports mentioned in this article.
FIGURE 2 | Percentage and comparison of distance vision impairment between urban and rural population groups and between coastal and inland population
groups.
Frontiers in Photonics | www.frontiersin.org June 2022 | Volume 3 | Article 9069173
Li et al. Vision Impairment in Southern China
Correlation of VI With Sex
In univariate analysis, the prevalence of VI did not vary
significantly (x
2
= 0.04; p = 0.849) between males and females.
Multiple Regression
A multiple logistic regression analysis was performed because
some of these parameters, such as refractive error and age, had a
significant (p < 0.001) correlation with each other. The study
factors such as age, sex, degree of urbanization (urban vs. rural),
geographic location (coastal vs. inland), education, income, and
refractive error were analyzed, and their association with VI is
shown in Table 1. Age, refraction, education, and income were
correlated with VI, while sex and urbanization were independent
of VI.
DISCUSSION
With an aging global population, the demand for eye health
services is increasing. Hence, the exploration of related factors of
VI in different areas was required. Although plenty of studies
(Zou et al., 2002; He et al., 2006; Iwase et al., 2006; Xu et al., 2006;
Yonekawa et al., 2011; Hong et al., 2013; Patil et al., 2014; Guo
FIGURE 3 | Percentage and comparison of distance vision impairment
among age groups.
FIGURE 4 | Percentage and comparison of distance vision impairment
among refraction groups.
FIGURE 5 | Percentage and comparison of distance vision impairment
among education subgroups.
FIGURE 6 | Percentage and comparison of distance vision impairment
among income subgroups.
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Li et al. Vision Impairment in Southern China
et al., 2017; Salomão et al., 2018; Tham et al., 2018; Wolfram et al.,
2019; Bikbov et al., 2020) have shown the percentage of VI and its
correlations based on various factors, including age, sex, physical
health, and ethnic background, few studies have assessed the
differences between coastal and inland populations. Accordingly,
the present study aims to estimate the prevalence of VI and its
sociodemographic and biological associations among the same
population group both in urban and rural areas as well as inland
and coastal regions, and the study design was more detailed and
refined than ever before.
The prevalence of blindness and VI in this study was lower
than the global prevalence in a Lancet review (Bourne et al.,
2017). This may be due to China’ s positive response to WHO
Vision 2020’s emphasis on eye health and the formulation of
the 13th Five-Year Plan for National Eye Health (2016–2020)
(National Health Commi ssion of the People’sRepublicof
China, 2016)andthe“Bright in the Country” Pr oject (China
National Blindness Prevention and Treatment, 2020).
Moreover, as a port of Southeast China, Fujian Province has
relatively developed economy, so people could access better eye
health services. Besides, the difference in lifestyle among co astal
Chinese may also be an important factor. Because of its
particularity, such as tea consumption and living habits, its
influence on eye health will be discussed in our future articles.
An Ireland study highlighted the inequality of access to
appropriate transport for rural vision-impaired people
(Gallagher et al., 2011), and the Brazilian Amazon Region
Eye Sur vey reported that older adults living in remote
regions with limited access to eye health services were at
higher risk of de veloping VI and blindness (Salomão e t al.,
2018). While our study found no difference between urban and
rural areas in VI prevalence. A possible explanation may be that
the southeast coastal area of China is more developed than the
northwest inland a rea on the whole, so the gap between urban
and rural regions is small, and the proportion of medical
insurance burden is close, so there is no significant
difference in the prevalence of VI between urban and rural
regions in this study population. Besides, the data of the WHO
Study on Global Aging and Adult Health revealed that the
intercountry heterogeneity of correlations observed among
countries might also be present within countries (e.g.,
between Eastern China and Western China) (Bourne et al.,
2019), which confirmed t he differe nce betwee n southeas t China
and other countrie s. VI in inland regions is worse than that of
coastal regions, which is consistent with the Papua New Guinea
nationwide survey that demonstrated that MVI (moderate
vision impairment) was observed in coastal areas compared
with NCD (National Capital Dist rict) and islands. F or all areas,
untreated cataract was the most common reason for blindness
(88.6%), SVI (89.3%, severe VI), and MVI (76.1%). The second
probable cause of blindness (3.9%) w as other poste rior segme nt
eye diseases. The chief cause of EVI (45.3%, early VI) w as
uncorrected refractive error (Lee et al ., 2019). The Coimbra Eye
StudyalsodemonstratedthattheincidenceoflateAMDwas
reduced in a coastal town in central Portugal compared with
major epidemiological stud ies of European-descen t
populations (Farinha et al., 2019). Thus, these results
indicate that the high prevalence of eye diseases may be the
main reason for the difference.
The present study revealed a large gap of VI existed between
urban and rural areas or coastal and inland regions. Our study found
that the population in urban areas with a higher education level and
higher income has less refractive error, which is consistent with other
studies (Zou et al., 2002; He et al., 2006; Iwase et al., 2006; Xu et al.,
2006; Yonekawa et al., 2011; Hong et al., 2013; Patil et al., 2014; Guo
et al., 2017; Salomão et al., 2018
; Tham et al., 2018; Wolfram et al.,
2019; Bikbov et al., 2020). Compared with the inland group, the
coastal group has better vision function and less myopia on the
whole. The potential differences in education level, economic level,
transportation, environmental reasons, and lifestyle causes may be
important factors in vision change development, such as the coastal
seafood diet (Joachim et al., 2015; Ghasemi Fard et al., 2019), higher
UV levels (Williams et al., 2017; Bose et al., 2019; Vergneau-Grosset
and Péron, 2020) in coastal regions, the higher comprehensive
degrees of sustainable education development in coastal regions
and the Central-south China (Geng and Zhao, 2020), and the faster
economic development in coastal areas (Small, 2004; Ren et al.,
2019).
Many studies have reported that age and refractive error are
associated with VI and blindness on the surface (Zou et al., 2002; He
et al., 2006; Iwase et al., 2006; Xu et al., 2006; Yonekawa et al., 2011;
Hong et al., 2013; Patil et al., 2014; Guo et al., 2017; Salomão et al.,
2018; Tham et al., 2018; Wolfram et al., 2019; Bikbov et al., 2020).
Findings from our age subgroup showed in detail that with
increasing age, the prevalence of VI was slightly lower in the 50-
to 59-year-old groups, increased gradually in the 60- to 74-year-old
groups, and doubled after 65 years of age. The VI prevalence of
people over 80 years old was greater than seven times that of the 50-
to 54-year-old group. This trend was initially reported and would be
helpful in understanding the objective laws of vision based on age.
The prevalence of VI of mild hyperopia was the lowest and
gradually increased with the deviation of diopter. It was previously
reported that refraction reflected the function of the eye and was
associated with damage. This notion was consistent with most
studies (Zou et al., 2002; He et al., 2006; Iwase et al., 2006; Xu
et al., 2006; Yonekawa et al., 2011; Hong et al., 2013; Patil et al., 2014;
Guo et al., 2017; Salomão et al., 2018; Tham et al., 2018; Wolfram
et al., 2019; Bikbov et al., 2020). The study also found that the VI
prevalence of the inland population was significantly increased
compared with that of the coastal population.
Our results also showed that as the level of education and income
increased, VI signifi
cantly decreased, demonstrating that the previous
TABLE 1 | Correlation between vision impairment and related factors in the Fujian
Eye Study.
Related Factors Odds ratio p-Value
Sex 0.63 0.138
Age 0.94 <0.001
Urbanization 1.37 0.241
Geographic location 2.43 0.001
Refraction 1.22 <0.001
Education 2.27 <0.001
Income 0.78 0.342
Frontiers in Photonics | www.frontiersin.org June 2022 | Volume 3 | Article 9069175
Li et al. Vision Impairment in Southern China
report was worthy of attention, which reported cash transfers to
incentivize health-promoting behavior appear to access more healthy
individuals with the disease cured (Strader et al., 2020).
Our study also had some limitations. Due to a lack of
consideration of population mobility, the response rate of this
study was slightly low, which might have biased our results.
Therefore, all kinds of non-response possibilities should be fully
considered in future research in order to ensure sufficient
representativeness. Because of the large amount of data, this
study only reported the correlation of several social
demographic factors, and further analysis on the correlation of
VI with eye diseases is in progress.
In conclusion, these findings showed VI was significantly
related to age, refractive error, education, and income in
Fujian Province of southern China. Therefore, our study
provided the latest data and played a theoretical and practical
supporting role in policy-making. Since the etiology of VI is
complicated, our observation could be incomplete and more in-
depth explorations are needed.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in
the article/Supplementary Material; further inquiries can be
directed to the corresponding authors.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by the Ethics Committee of Xiamen Eye Center
affiliated with Xiamen University. The patients/participants
provided their written informed consent to participate in this
study.
AUTHOR CONTRIBUTIONS
YL and QH took part in all parts of the study, including the study
design, data collection, data analysis, the preparation of related
data, writing, and revision. XQ and TR helped revise the data
analysis and article. BW assisted in plotting and article revision.
YH and XL oversaw the research, data, and article. All authors
contributed to the study design, analysis, and writing of the
article.
FUNDING
This study was supported by the National Natural Science
Foundation of China (NSFC, No. 81870672), the National
Natural Science Foundation of China Youth Fund (NSFC, No.
81900881), the Natural Science Foundation of Youth Innovation
Program of Fujian Province (No. 2019D007 and No. 2020D028),
the Xiamen Science and Technology Planning Project (No.
3502Z20184023), and the Medical and Healthcare Guiding
Program of Xiamen City (No. 3502Z20199074).
ACKNOWLEDGMENTS
We thank all members of the FJES group (Liting Wang, Yi Liu,
Wufu Qiu, Menging Lin, Yanhong Zhang, and Zhenglingling
Yao) for their great efforts to the success of this study, especially
in field inspection and data collation.
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Conflict of Interest: The authors declare that the research was conducted in the
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Frontiers in Photonics | www.frontiersin.org June 2022 | Volume 3 | Article 9069177
Li et al. Vision Impairment in Southern China
