The influence of sociodemographic characteristics on vision-related quality of life in visually impaired patients

Abstract

Objectives
Self-reported vision-related quality of life (VRQOL) allows us to assess the effect of disease and treatments from the patient’s perspective, focusing on an individual’s subjective satisfaction and functional ability. The previous studies mostly focused on the impact of visual function deficits on VRQOL in patients with visual impairment. This study seeks to investigate the influence of sociodemographic characteristics on VRQOL in visually impaired patients.

Material and Methods
This prospective cross-sectional study included consecutive adult patients with visual impairment at the University of Calabar Teaching Hospital eye clinic. All patients had presenting visual acuity worse than 6/18 in the better eye. VRQOL was assessed by the validated English version 25-item National Eye Institute Visual Functioning Questionnaire. Sociodemographic characteristics and ocular parameters were recorded. Sociodemographic characteristics were evaluated based on age, sex, area of residence, marital status, religion, educational attainment, and monthly income. Each characteristic was stratified into groups or levels. Analysis of variance, including post hoc analysis was used to evaluate the association between sociodemographic characteristics and VRQOL.

Results
A total of 270 patients were enrolled. After adjustments for category and causes of visual impairment, older age ( P < 0.001), rural dwellers ( P < 0.001), widowhood ( P = 0.006), and no formal education ( P < 0.001) were significantly associated with low mean visual function (VF) scores. Similarly, older age ( P < 0.001), rural dwellers ( P < 0.001), widowhood ( P = 0.003), and no formal education ( P < 0.001) were significantly associated with low mean QOL scores. The difference in the mean score of VF and QOL by religion, sex, and monthly income was not statistically significant.

Conclusion
Besides the degree of visual impairment, the interplay of certain social and demographic factors plays a remarkable role in determining the QOL in visually impaired patients. Therefore, an individualized management plan, including psychosocial therapy is imperative in the care of visually impaired patients.

Full text

Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 27
Original Article
e inuence of sociodemographic characteristics on
vision-related quality of life in visually impaired patients
Ernest Ikechukwu Ezeh1, Bassey Archibong Etim1, Bassey Edet2, Roseline Nkeiruka Ezeh3, Roseline Ekanem Duke1
1Department of Ophthalmology, University of Calabar, 2Department of Psychiatry, Federal Neuro Psychiatric Hospital, 3Department of Ophthalmology,
University of Calabar Teaching Hospital, Calabar, Cross River, Nigeria.
*Corresponding author:
Ernest Ikechukwu Ezeh,
Department of Ophthalmology,
University of Calabar, Calabar,
Cross River, Nigeria.
ezehiyk@yahoo.com
Received : 06 January 2020
Accepted : 01 July 2020
Published : 24 August 2020
DOI
10.25259/CJHS_3_2020
Quick Response Code:
INTRODUCTION
Vision-related quality of life (VRQOL) describes an individual’s overall sense of well-being
that is related to the individual’s level of visual functioning.[1] Visual functioning is dened by
two terms: Functional vision and visual function.[1] Functional vision describes how a person
functions in vision-related activities; as opposed to visual function, which describes how the
eyes and the visual system function. Functional vision is a broader measure than visual acuity,
because it evaluates patients’ ability to conduct activities of daily living (e.g., reading, driving,
ABSTRACT
Objectives: Self-reported vision-related quality of life (VRQ OL) al lows us to assess the eect of disease and
treatments from the patient’s perspective, focusing on an individual’s subjective satisfaction and functional ability.
e previous studies mostly focused on the impact of visual function decits on VRQOL in patients with visual
impairment. is study seeks to investigate the inuence of sociodemographic characteristics on VRQOL in
visually impaired patients.
Material and Methods: is prospective cross-sectional study included consecutive adult patients with visual
impairment at the University of Calabar Teaching Hospital eye clinic. All patients had presenting visual acuity
worse than 6/18 in the better eye. VRQOL was assessed by the validated English version 25-item National Eye
Institute Visual Functioning Questionnaire. Sociodemographic characteristics and ocular parameters were
recorded. Sociodemographic characteristics were evaluated based on age, sex, area of residence, marital status,
religion, educational attainment, and monthly income. Each characteristic was stratied into groups or levels.
Analysis of variance, including post hoc analysis was used to evaluate the association between sociodemographic
characteristics and VRQOL.
Results: A total of 270 patients were enrolled. Aer adjustments for category and causes of visual impairment,
older age (P < 0.001), rural dwellers (P < 0.001), widowhood (P = 0.006), and no formal education (P < 0.001)
were signicantly associated with low mean visual function (VF) scores. Similarly, older age (P < 0.001), rural
dwellers (P < 0.001), widowhood (P = 0.003), and no formal education (P < 0.001) were signicantly associated
with low mean QOL scores. e dierence in the mean score of VF and QOL by religion, sex, and monthly
income was not statistically signicant.
Conclusion: Besides the degree of visual impairment, the interplay of certain social and demographic factors
plays a remarkable role in determining the QOL in visually impaired patients. erefore, an individualized
management plan, including psychosocial therapy is imperative in the care of visually impaired patients.
Keywords: Visual function, Quality of life, Sociodemographics, Visually impaired
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Ezeh, et al.: Sociodemographics and vision related quality of life
Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 28
writing, orientation and mobility, and face recognition),
for which peripheral vision, contrast sensitivity, color
vision, and visual acuity are important.[1] Visual function
is dened by visual acuity, visual eld, contrast sensitivity,
color vision, dark adaptation, and stereopsis.[1] At present,
the assessments of these parameters are the most-accepted
clinical evaluation of visual function.[2] However, they
have been shown to be inadequate in explaining poor
performance in vision-related activities of daily living
among visually impaired patients.
In recent years, self-perceptions of vision-related functioning
and well-being have gained recognition as important
measures to characterize more comprehensively the disability
associated with visual impairment (VI).[3] Vision-related
questionnaires and surveys have grown by a big margin[4-9] to
provide key information about the impact of visual damage
from the patients’ perspective. However, the degree of visual
impairment may not be the only factor that determines the
VRQOL. Certain factors, such as environmental factors,
personal factors, socio-cultural norms, social structure, age,
and gender,[10] interplay to aect the individual’s perception of
functional vision and, by extension, the VRQOL [Figure 1].
e interactions of several factors, therefore, inuence the
visually impaired patient’s perception of his/her QOL. us,
the impact of the degree of VI and associated factors denes
the concept of VRQOL.
Self-reported VRQOL allows us to assess the eect of disease
and treatments from the patient’s perspective, focusing
on an individual’s subjective satisfaction and functional
ability. e previous studies mostly focused on the impact
of visual function decits on VRQOL in patients with visual
impairment. is study seeks to investigate the inuence of
sociodemographic characteristics on VRQOL in visually
impaired patients attending a tertiary eye care facility in
South-South Nigeria.
MATERIAL AND METHODS
It was a prospective cross-sectional study conducted from
August 2015 to March 2016 at the Eye clinic, University
of Calabar Teaching Hospital (UCTH), Calabar, Cross
River State, Nigeria. e study population consisted of
consecutive patients aged ≥16 years presenting to the
Eye clinic, UCTH, with a presenting visual acuity (PVA)
of <6/18 in the better eye. Institutional ethical approval
was obtained from the UCTH Health Research and
Ethics Committee. Data were collected using a pretested,
structured pro forma consisting of sociodemographics
and oculo-visual parameters. e oculo-visual parameters
were obtained by the most senior ophthalmologist in each
clinic day. Each participant’s PVA was assessed using a
Snellen chart placed 6 m away from the participant in
a well-illuminated area. e tumbling E chart was used
for illiterate patients. Slit-lamp examination, tonometry,
and funduscopy were used by the ophthalmologist to
conrm the diagnosis. We took the o cular disease, which
best explains the patients’ visual reduction. For the cases
which have more than one disease which can cause a visual
reduction, we considered professional agreement done by
three senior ophthalmologists in each clinic day and took
the agreed cause of visual impairment which best explains
patients’ visual reduction as an ocular condition when at
least two of the senior ophthalmologists agree. Aerward,
the principal investigator administered on each participant
a face-to-face interview using the interviewer administered,
validated English version 25-item National Eye Institute
Visual Functioning Questionnaire[7,8] to estimate VRQOL.
Figure1: An interplay of factors that inuence the vision-related quality of life.[11]

Ezeh, et al.: Sociodemographics and vision related quality of life
Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 29
Table 1: Sociodemographic characteristics of study participants
(n=270).
Variables Frequency Percentage
Age (years)
<20 51.9
20–39 63 23.3
40–59 111 41.1
60–79 80 29.6
≥80 11 4.1
Sex
Male 152 56.3
Female 118 43.7
Residence
Rural 73 27.0
Urban 197 73.0
Education
None 24 8.9
Primary 47 17.4
Vocational 10 3.7
Secondary 64 23.7
Tertia r y 125 46.3
Marital status
Single 61 22.6
Married 207 76.7
Widowed 2 0.7
Religion
Christianity 266 98.5
Islam 4 1.5
Occupation
Professional 32 11.9
Agric. Worker 34 12.6
Public servant 43 16.0
Trading 47 17.4
Student 34 12.6
Clergy 14 5.2
Retired 47 17.4
Unemployed 13 4.7
Others 62.2
Income class
High 4 1.5
Middle 190 70.4
Low 76 28.1
Ethnicity
Ek 97 35.9
Ekoi 54 20.0
Ibibio 42 15.6
Annang 13 4.8
Ibo 55 20.4
Others 93.3
Sociodemographic characteristics were evaluated based
on age, sex, area of residence, marital status, religion,
educational attainment, and monthly income. Each
characteristic was stratied into groups or levels [Table 1].
Data were entered and analyzed using Statistical Package for
the Social Sciences (SPSS) for Windows (version 20, SPSS
inc., Chicago, IL, USA). Descriptive statistics (frequencies,
proportions, means, and standard deviation) were used
to summarize variables. Analysis of variance, including
post hoc analysis was used to evaluate the association
between sociodemographic characteristics and VRQOL.
e statistical signicance levels were set at P < 0.05.
Denition of terms
e denitions below were with reference to the World
Health Organization[11]
• PVA: Was dened by the visual acuity in the better eye
using currently available refractive correction, if any.
Where the participant has no refractive correction
(distance glasses), the unaided distance VA denes the
presenting vision
• Normal vision: ≥6/18 in the better eye
• Moderate visual impairment (MVI): <6/18–6/60 in the
better eye
• Severe visual impairment (SVI): <6/60–3/60 in the
better eye
• Blindness: <3/60 in the better eye
• Moderate VI combined with severe VI is grouped under
the term “low vision:” Low vision taken together with
blindness represents all visual impairment (VI).
Income class:[12]
• High: Average monthly income of > ₦100,000
• Middle: Average monthly income of ₦75,000 to ₦100,000
• Low: Average monthly income of < ₦75,000.
RESULTS
A total of 270 patients aged 18–90 years were enrolled
and participated in the study. e mean age ± SD was
51.07 ± 16.91 years. Among study participants, 152 (56.3%)
were males, more than two-thirds 210 (77.8%) were urban
dwellers, and about half 125 (46.3%) had tertiary level of
education [Table1].
Sociodemographic features
Distribution of Sociodemographic characteristics and
category of visual impairment
Table 2 shows the category of visual impairment by
sociodemographic characteristics. Category of VI by
age group (P = 0.024), income class (P = 0.002), place of
residence (P = 0.036), marital status (P = 0.002), occupation
(P < 0.001), and educational level (P < 0.001) showed
statistical signicance. at is, those 40–59 years, those in
low-income class, rural dwellers, the married, the agricultural
workers, and those with primary education, were more likely
to be more severely impaired. However, the relationship

Ezeh, et al.: Sociodemographics and vision related quality of life
Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 30
Table2: Category of visual impairment by sociodemographic characteristics (n=270).
Vari a b l e Moderate VI n=208 (38.5%) Severe VI n=23 (4.3%) Blindness n=39 (7.2%) Chi-square test P-value
Age group (years)
<20 5 (0.9) 0 (0.0) 0 (0.0) Fisher’s exact 0.024*
20–39 43 (8.0) 9 (1.7) 11 (2.0)
40–59 91 (16.9) 6 (1.1) 14 (2.6)
60–79 65 (12.0) 8 (1.5) 7 (1.3)
≥80 4 (0.7) 0 (0.0) 7 (1.3)
Sex
Male 113 (20.9) 15 (2.8) 24 (4.4) 1.507 0.681
Female 95 (17.0) 8 (1.5) 15 (2.8)
Income class
High 4 (0.7) 0 (0.0) 0 (0.0) 16.003 0.002*
Middle 159 (29.4) 13 (2.4) 18 (3.3)
Low 45 (8.3) 10 (1.9) 21 (3.9)
Residence
Rural 39 (7.2) 8 (1.5) 26 (4.8) Fisher’s exact 0.036*
Urban 169 (31.3) 15 (2.8) 13 (2.4)
Marital status
Single 40 (7.4) 9 (1.7) 12 (2.2) Fisher’s exact 0.002*
Married 168 (31.1) 14 (2.6) 25 (4.6)
Widowed 0 (0.0) 0 (0.0) 2 (0.4)
Religion
Christianity 204 (37.8) 23 (4.3) 39 (7.2) 0.802 0.770
Muslim 4 (0.7) 0 (0.0) 0 (0.0)
Occupation
Agricultural worker 22 (4.1) 2 (0.4) 10 (1.9) 43.749 <0.001*
Clergy 9 (1.7) 2 (0.4) 3 (0.6)
Retired 39 (7.2) 4 (0.7) 4 (0.7)
Professional 28 (5.2) 2 (0.4) 2 (0.4)
Public servant 42 (7.8) 0 (0.0) 1 (0.2)
Student 25 (4.6) 5 (0.9) 4 (0.7)
Trading 32 (5.9) 5 (0.9) 10 (1.9)
Unemployed 8 (1.5) 2 (0.4) 3 (0.6)
Others 3 (0.6) 1 (0.2) 2 (0.4)
Education
None 13 (2.4) 2 (0.4) 9 (1.7) 54.240 <0.001*
Primary 27 (5.0) 4 (0.7) 16 (3.0)
Secondary 56 (10.4) 2 (0.4) 6 (1.1)
Vocational 6 (1.1) 2 (0.4) 2 (0.4)
Tertia r y 106 (19.6) 13 (2.4) 6 (1.1)
*Statistically signicant
between the category of VI and sex (P = 0.681), and religion
was not statistically signicant.
Distribution of causes of visual impairment
Table3 shows the distribution of causes of visual impairment
(VI) among the participants. Of decreasing frequency,
refractive errors 97 (36.0%), cataract 75 (27.8%), and
glaucoma 55 (20.4%) were the common causes of visual
impairment. Among 75 participants who had cataract, 21
(28.0) were blind, and 10 (13.3%) had SVI, while 44 (58.7%)
had MVI. Among 55 participants who had glaucoma, 12
(21.8%) were blind, and 2 (0.7%) had SVI while 41 (74.5%)
had MVI. Refractive error was found among 97 participants,
of which 2 (2.1%) were blind, and 7 (7.2%) had SVI while 88
(90.7%) had MVI. Other causes of visual impairment had a
frequency of 43: 4 (9.3%) being blind, 4 (9.3%) having SVI,
and 35 (81.4%) having MVI. In general, cataract accounted
for the highest frequency among those who had blindness
and SVI from a single cause, followed by glaucoma, then
refractive errors, and other causes. is distribution of causes
of visual impairment was statistically signicant (P < 0.001).

Ezeh, et al.: Sociodemographics and vision related quality of life
Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 31
Table4: Association of visual function and quality of life with sociodemographic characteristics of study participants.
Characteristics Total VF mean (95% CI) Test statistics (P-value) Total QOL Mean (95% CI) Test statistics (P-value)
Age group (years)
<20 74.2 (59.7–88.7) ANOVA (0.560) 70.9 (53.3–88.4) ANOVA (0.215)
20–39 80.2 (75.5–84.9) ANOVA (<0.001*) 80.2 (75.0–85.4) ANOVA (<0.001*)
40–59 76.4 (72.8–80.0) ANOVA (0.003*) 79.7 (75.6–83.7) ANOVA (<0.001*)
60–79 71.3 (67.2–75.5) ANOVA (0.062) 72.8 (68.1–77.6) ANOVA (<0.001*)
≥80 54.2 (38.3–70.2) Reference category 44.0 (27.4–60.7) Reference category
Sex
Male 73.8 (70.6–77.0) Reference category 75.9 (72.3–79.4) Reference category
Female 76.1 (72.6–79.6) t-test (0.337) 76.5 (72.5–80.6) t-test (0.798)
Residence
Rural 66.8 (70.6–77.0) Reference category 64.9 (58.7–71.1) Reference category
Urban 77.5 (75.0–80.1) t-test (<0.001*) 79.7 (76.9–82.5) t-test (<0.001*)
Marital status
Single 74.7 (69.1–80.3) Reference category 73.0 (67.0–79.1) Reference category
Married 75.2 (72.6–77.7) ANOVA (1.000) 77.3 (74.4–80.2) ANOVA (0.609)
Widowed 13.5 (13.5–13.5) ANOVA (0.006*) 0 (0.0–0.0) ANOVA (0.003*)
Religion
Christianity 74.7 (72.3–77.0) ANOVA (0.222) 76.0 (73.3–78.7) ANOVA (0.276)
Islam 87.6 (75.1–100.0) Reference category 89.0 (69.7–108.2) Reference category
Education
None 51.2 (37.6–64.9) Reference category 48.5 (33.5–63.5) Reference category
Primary 62.7 (55.5–70.0) ANOVA (0.385) 64.6 (56.8–72.5) ANOVA (0.101)
Secondary 77.7 (74.2–81.3) ANOVA (<0.001*) 78.2 (73.9–82.5) ANOVA (<0.001*)
Vocational 57.8 (37.1–78.9) ANOVA (1.000) 55.9 (31.8–9.9) ANOVA (1.000)
Tertia r y 81.1 (78.3–83.9) ANOVA (<0.001*) 83.3 (80.2–86.5) ANOVA (<0.001*)
Income class
High 80.4 (59.7–101.1) Reference category 85.0 (64.0–106.0) Reference category
Middle 77.1 (74.5–79.7) ANOVA (1.000) 79.0 (76.1–82.0) ANOVA (1.000)
Low 67.3 (62.0–72.5) ANOVA (0.501) 66.5 (60.5–72.5) ANOVA (0.248)
*Statistically signicant. ANOVA: Analysis of variance
Association of visual function and quality of life with
sociodemographic characteristics of study participants
Table 4 shows the association of visual function (VF)
and QOL with sociodemographic characteristics of study
participants.
Visual function
A significant association was found between VF and
age, residence, marital status, and level of education
(P < 0.05). Significantly low mean VF scores occurred
among those who were older, rural dwellers, widowed,
and those who had no formal education. The difference
in the mean score of VF by religion and sex was not
statistically significant.
QOL
A signicant association was found between QOL and age,
residence, marital status, and level of education (P < 0.05).
Signicantly, low Q OL mean scores occurred among those
Table3: Distribution of causes of visual impairment (n=270).
Causes Moderate VI
n=208 (77.0%)
Severe VI
n=23 (8.6%)
Blindness
n=39 (14.4%)
Total
n=270 (100.0%)
Chi-square test P-value
Cataract 44 (58.7) 10 (13.3) 21 (28.0) 75 (100.0) 34.712 <0.001*
Glaucoma 41 (74.5) 2 (0.7) 12 (21.8) 55 (100.0)
Refractive error 88 (90.7) 7 (7.2) 2 (2.1) 97 (100.0)
Others#35 (81.4) 4 (9.3) 4 (9.3) 43 (100.0)
*Statistically signicant. #Retinal diseases, corneal opacity, ocular trauma

Ezeh, et al.: Sociodemographics and vision related quality of life
Calabar Journal of Health Sciences • Volume 4 • Issue 1 • January-June 2020 | 32
who were older, rural dwellers, widowed, and those who had
no formal education.
DISCUSSION
e limitations in health-care resources in developing
countries like Nigeria may necessitate considering cost-
eective measures for optimizing health care; hence, the
QOL measures for interventions may gain increasing
relevance in clinical practice in a setting like ours. is
study had highlighted a hospital-based distribution of visual
impairment and its eect on QOL.
In general, visual acuity is thought to be the most
signicant factor inuencing VF and QOL scores; however,
the variation of these scores observed with dierent
causes of VI category suggests that factors other than
VA also inuence the VF and QOL scores. In this study,
aer controlling for VA, it was found that VF and QOL
scores were signicantly lower among specic groups.
Signicantly, low mean VF/QOL scores were noted among
those who were older, rural dwellers, widowed, and those
who had no formal education. Onakoya et al.[13] on QOL
among glaucoma patients found that older age, female
gender, and poor educational level negatively impacted
on the QOL. Similarly, Tran et al.[14] had reported in their
study on QOL and VF in Nigeria that people who are blind,
older people, women, manual laborers, people living in
rural areas, those living in the northern geopolitical zones,
those practicing Islamic and Traditionalism faith, those
not currently married, and those who have undergone
coaching, had lower VF/QOL scores.
e ndings in this study further corroborate the relationship
between social and demographic factors to VRQOL.
Although poor visual health status inuences the QOL of an
individual, the social and demographic milieu or disposition
of such an individual also determines how far-reaching the
impact of the deviation on daily functioning. Trillo and
Dickinson[15] had observed that socially disadvantaged
individuals such as widowhood, poor household class, are
more impacted by visual impairment. ey had opined
that these specic groups are generally characterized
by socio-economic deprivation, increasing competing
health comorbidities, nancial dependence, depreciating
self-esteem, and poor socio-cultural orientation. For example,
the social and emotional trauma of losing a spouse could lead
to despair, loneliness, and helplessness. Cumulatively, these
could negatively impact on the individual’s sense of well-
being independent of the degree of visual impairment.
CONCLUSION
Besides the degree of visual impairment, the interplay of
certain social and demographic factors play remarkable role
in determining the QOL in visually impaired adult patients.
erefore, an individualized management plan, including
psychosocial therapy, is imperative in the care of visually
impaired adult patients. Moreso, a targeted approach to eye
delivery is highly recommended.
Declaration of patient consent
e authors certify that they have obtained all appropriate
patient consent.
Financial support and sponsorship
Nil.
Conicts of interest
ere are no conicts of interest.
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How to cite this article: Ezeh EI, Etim BA, Edet B, Ezeh RN, Duke RE. e
inuence of sociodemographic characteristics on vision-related quality of
life in visually impaired patients. Calabar J Health Sci 2020;4(1):27-33.