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Presbyopia and quality of life among the Latino population

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Presbyopia and quality of life among the Latino population

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Content Presbyopia and Quality of Life Among the Latino Population
by
Jayson De La O
A Thesis Presented to the
FACULTY OF THE USC KECK SCHOOL OF MEDICINE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOSTATISTICS)
December 2024
Copyright 2024 Jayson De La O

ii
Table of Contents
List of Tables..................................................................................................................................iii
Abstract.......................................................................................................................................... iv
Chapter 1. Introduction ................................................................................................................... 1
Chapter 2. Methods......................................................................................................................... 4
Study Design and Population...................................................................................................... 4
Definition of Presbyopia ............................................................................................................. 4
Visual Function Questionnaire.................................................................................................... 5
Statistical Analysis...................................................................................................................... 6
Chapter 3. Results........................................................................................................................... 8
Population Characteristics .......................................................................................................... 8
Impact of Presbyopia on Quality of Life .................................................................................... 8
Item-Specific Effects of Presbyopia Within Subscales............................................................... 9
Effect Modification by Vision and Health Insurance................................................................ 10
Chapter 4. Discussion ....................................................................................................................11
References..................................................................................................................................... 15
Appendix....................................................................................................................................... 17

iii
List of Tables
Table 1. Demographic characteristics by Presbyopia Status......................................................... 17
Table 2. Linear Regression of Presbyopia on Quality of Life ...................................................... 18
Table 3. Item-specific Multiple Linear Regression of Presbyopia on Quality of Life Subscales
Adjusting for Covariates............................................................................................................... 19
Table 4. Stratified Multiple Linear Regression by Health Insurance Status................................. 20
Table 5. Mean, Medians, and Missing Values for Quality of Life Subscales............................... 21

iv
Abstract
Background: As people age, they are likely to be affected by presbyopia to some extent.
Understanding the effects of presbyopia on vision specific quality of life is important for
identifying the aspects of daily life that are impacted and for providing improved treatment
options or accommodations.
Methods: For this analysis, we utilized data from the Los Angeles Latino Eye Study (LALES), a
cross-sectional, population-based study of Latinos aged 40 years or older residing in Los Angeles
County. Vision specific quality of life was measured using the National Eye Institute’s Visual
Function Questionnaire (NEI VFQ-25). Individuals were defined as having presbyopia if they
had a Best-Corrected Visual Acuity (BCVA) measurement of 20/40 or better in their betterseeing eye but had a near vision visual acuity of 20/50 or worse, or if they required an additional
correction prescription during near vision testing. Linear regression analyses were conducted to
assess the relationship between overall and subscales of vision specific quality of life and
presbyopia status. Covariate-adjusted models controlled for age, gender, income, education level,
and insurance status. Additionally, we tested for possible effect modification of having health
and/or vision insurance on the association between presbyopia and vision specific quality of life.
Results: In our sample, 4,023 individuals (63.74%) were classified as having presbyopia.
Presbyopia was associated with lower vision specific quality of life scores across all subscales of
the National Eye Institute’s Visual Function Questionnaire (all p<0.05). After adjusting for age,
gender, income, education level, and insurance status, significant associations were observed
between presbyopia and 7 subscales of the NEI-VFQ-25, including ocular pain, near vision,
mental health, role function, dependency, color vision, peripheral vision, and the overall
composite score. Health insurance was found to modify the association between presbyopia and

v
vision related dependency; the deleterious effect of presbyopia was stronger in individuals
without health insurance.
Conclusion: Presbyopia was found to significantly reduce overall vision-specific quality of life,
with tasks relating to near vision being the most affected. There was no evidence of effect
modification by vision insurance status in the association between presbyopia and vision specific
quality of life. However, health insurance was found to be an effect modifier with it significantly
reducing the negative impacts of presbyopia on vision related dependency. These findings
highlight that access to health insurance may help mitigate some of the negative effects of
presbyopia. Given the prevalence of presbyopia in aging populations, understanding the impacts
of presbyopia and addressing any healthcare disparities among uninsured individuals is crucial
for improving treatments and enhancing the quality of life for those affected.

1
Chapter 1. Introduction
Presbyopia is a common refractive error that affects near vision, primarily affecting individuals
as they age1,3
. The American Optometric Association estimates 128 million Americans are
affected by presbyopia in the United States1
. Globally, it is estimated that up to 1.8 billion people
may be affected to some degree, with approximately 826 million experiencing impaired vision
due to inadequate or unavailable corrective treatments4
. Presbyopia is a normal part of aging that
affects the near vision of individuals typically aged 40 and older around the world3
.
Understanding the impact of presbyopia is crucial for creating policies that make treatments
more accessible and providing accommodations for those affected.
As individuals age, the lenses in their eyes become more rigid and lose the ability to
properly focus light on the retina. The age-related change in the lens causes the focal point of
light to fall behind the retina instead of on it, making close objects appear blurry. To compensate
for their near vision difficulties, people with presbyopia often hold objects at a distance to help
their eyes better focus on the object. In addition to blurred near vision, individuals with
presbyopia often experience eye strain and headaches, causing pain and discomfort9
. These
difficulties impose a burden on those affected, causing them to struggle with hobbies and daily
tasks such as reading7
.
Although no cure exists, presbyopia is commonly managed using corrective lenses.
Monovision correction techniques have also been used to treat presbyopia, where one eye is
corrected for near vision and the other for distance vision15
. A study investigating the impact of
corrective treatment on vision specific quality of life found that while monovision correction
improved quality of life for those affected, it remained lower in many areas compared to younger

2
individuals with perfect vision10
. These findings suggest that corrective treatment of presbyopia
may lead to improvement in quality of life compared to those without treatment. However,
despite the availability of cost-effective solutions like corrective lenses, presbyopia may
disproportionately affect those without insurance due to limited access to treatments. Health and
vision insurance are crucial in providing access to routine clinical examinations, treatments, and
other health services. The limited access to treatments raises the need to explore how insurance
status affects the relationship between presbyopia and quality of life.
Research on quality of life is an important area of study for public health and medical
advancements. Understanding how a disease or condition affects an individual’s quality of life is
necessary information for improving patient care and identifying the range of issues impacting a
person’s life6
. Various assessment tools exist to measure quality of life. The National Eye
Institute’s Visual Function Questionnaire is an assessment tool specifically focusing on areas of
vision specific quality of life. An assessment of visual specific quality of life is of particular
importance for individuals with eye conditions like presbyopia8
. By using the Visual Function
Questionnaire, this study aims to evaluate how presbyopia affects the overall well-being and
functional abilities related to vision.
Previous studies have shown that presbyopia has been associated with a reduced quality
of life
5,10,12,14
. These studies found that presbyopia impairs near vision, contributing to
difficulties in performing everyday tasks. Building on these findings, this study focuses on
investigating the relationship between presbyopia and vision specific quality of life specifically
within the Latino population of Los Angeles County. Additionally, by evaluating whether health
insurance and vision insurance status act as effect modifiers, this study seeks to provide a better
understanding of the impacts of presbyopia and identify disparities among uninsured individuals.

3
As the prevalence of presbyopia rises with an aging population, understanding its broader effects
and identifying disparities in healthcare are crucial in improving treatments and enhancing the
quality of life for those affected.

4
Chapter 2. Methods
Study Design and Population
The data for this study was collected as part of the Los Angeles Latino Eye Study (LALES), a
cross-sectional study investigating the prevalence, risk factors, and impact of visual impairments
and ocular diseases among the Latino population of Los Angeles17
. Eligibility criteria required
participants to (1) self-identify as Latino, (2) be age 40 or older, and (3) reside in the city of La
Puente, located in Los Angeles County.
Participants underwent an in-home interview followed by a clinical examination. The inhome interview confirmed eligibility, obtained informed consent, and collected participant
information. The interviews were administered in Spanish or English, depending on the
participant’s preference and included socio-demographic questions, medical and ocular history,
and ancestry details. Following the in-home interview, individuals were scheduled for a clinical
examination, which consisted of an in-clinic medical and ocular examination and in-clinic
interview. The in-clinic interview included questions relating to vision specific quality of life and
visits to an eye care provider.
Definition of Presbyopia
A major problem with research on presbyopia is the lack of a universally accepted definition for
those affected13
. For this study, an individual was classified as having presbyopia if they met the
following criteria: (1) they had a Best-Corrected Visual Acuity (BCVA) measurement of 20/40 or
better in their better-seeing eye and had a near vision visual acuity of 20/50 or worse, or (2) they
required an additional correction prescription during near vision testing.

5
Visual Function Questionnaire
As part of the clinical examination, participants responded to National Eye Institute 25-item
Visual Function Questionnaire (NEI VFQ-25), a survey used to measure a patient’s self-reported
vision specific quality of life. Interviews were conducted in either Spanish or English, depending
on the individual’s preference. The NEI VFQ-25 consist of 25 vision-related questions and
measures the impact that vision disorders have across the twelve health and task-related
subscales: general health, general vision, ocular pain, near vision, distance vision, vision related
social functioning, vision related mental health, vision related role function, vision related
dependency, driving difficulties, color vision, and peripheral vision. The questionnaire used in
this study is the 1996 version of the NEI VFQ-25, an earlier iteration that does not include the
supplementary driving item in the driving subscale.
The scoring for each question was conducted according to the NEI-VFQ-25 instructional
manual. Numerical responses from the survey were recoded into values ranging from 0 to 100,
with higher scores indicating better functioning. Each question corresponds to one of the twelve
subscales, which represent the domains of vision specific quality of life. After recoding each
response, the values corresponding to each vision specific quality of life domain were averaged
to create subscale scores, with each subscale consisting of 1 to 4 questions. Participants must
have answered at least one question within each subscale to generate a subscale score. Missing
scores were excluded from calculations. An overall composite score for vision specific quality of
life was calculated by averaging all subscales scores, excluding the general health subscale.
Averaging subscale scores instead of each question allowed each subscale to be weighted equally
instead of giving subscales with more questions more weight.

6
Statistical Analysis
Pearson’s chi-square tests were used to test for an association between categorical demographic
characteristics and presbyopia status (absent/present), while Wilcoxon rank-sum tests were used
to test for difference in medians between continuous demographic variables and presbyopia
status. To evaluate the magnitude of differences in vision specific quality of life scores between
participants with and without presbyopia, effect sizes (ES) were calculated using Glass’s delta.
A series of simple linear regression models were conducted to examine the univariate
linear relationship between presbyopia and each of the vision specific quality of life subscales.
Similarly, multiple linear regression models were used to explore the multivariate relationship
between presbyopia and each of the subscales while adjusting for covariates. The covariates
included in the models were selected based on demographic and socioeconomic factors that may
influence an individual’s outcome and were likely to be confounders. These factors included age,
gender, education, income, health insurance, and vision insurance.
The vision specific quality of life variables were found to be left-skewed; therefore, we
transformed them to better meet the assumptions of linear regression. Specifically, the variables
were transformed using the formula: ln(101- (Quality of Life Score)), a transformation used in
similar studies of vision specific quality of life11
. The standard error of parameter estimates in
our regression models for the vision specific quality of life subscales were bootstrapped using
1,000 iterations to generate estimates that were robust to violations of regression assumptions.
Item-specific multivariate analyses were conducted to observe the influence of
presbyopia on each individual question within the subscales. These analyses evaluated the
strength of the association between presbyopia and each question or item, to identify which
components of the subscales were most strongly affected by presbyopia. Lastly, an interaction
term between presbyopia and health and vision insurance status was included in the model and

7
retained if the Wald test for the interaction term was found to be statistically significant. If there
was evidence of effect modification, the analysis was then stratified by the effect modifier to
observe the impacts of presbyopia on each group.
All analyses were conducted using R version 4.3.2 at a significance level of 0.05.

8
Chapter 3. Results
Population Characteristics
From the 10,663 households that completed the eligibility screening, a total of 7,789
subjects were eligible for the study, of which 6,357 completed a clinical examination, and 6,346
of those completed both the in-home interview and the clinical examination. Observations with
missing information on presbyopia status were excluded from analysis, leading to a sample of
6,312 individuals.
Among the 6,312 participants, 4,023 (63.74%) were classified as having presbyopia.
The average age of participants was 54.88 years (range:40 to 98 years). Of the participants, 3,695
(59%) were female, 4,088 (65%) had health insurance, 3,191 (51%) had vision insurance, 2,731
(49%) had a yearly income of over $20,000, and 2,106 (33%) had at least a high school
education (Table 1). Individuals with presbyopia were more likely to be older, female, and have
vision and health insurance, but were less likely to have an income of over $20,000 a year or
have at least a high school education compared to individuals without presbyopia. Univariate
analysis of age, gender, income, education level, and insurance status revealed significant
associations with presbyopia status (p <0.001). Missing values for vision specific quality of life
subscales, along with the mean, and median values for each subscale can be found in Table 5.
Impact of Presbyopia on Quality of Life
Univariate linear regression of each vision specific quality of life subscale by presbyopia status
(Table 2) revealed significant associations between presbyopia and the subscales (all p <0.05).
Presbyopia was associated with lower scores in all subscales, with the strongest negative
association seen in the near vision subscale (ES=0.28; p<0.001; Mean Ratio (MR)=0.6376; 95%
CI: 0.5827, 0.6977). The overall composite score, which is an average of the vision related

9
quality of life subscales, showed a similar significant decline in quality of life (ES=0.26; p <
0.001; MR=0.7616; 95% CI: 0.7276, 0.7973). Similarly, after adjusting for age, gender, income,
education level, and insurance status, presbyopia was found to be associated with lower vision
specific quality of life. Specifically, 7 out of the 12 subscales and the composite score showed a
significant decline in vision specific quality of life, while the general health, general vision,
distance vision, social functioning, and driving difficulties subscales did not show significant
associations (Table 2).
Item-Specific Effects of Presbyopia Within Subscales
Four subscales (near vision, distance vision, dependency, and driving) were selected for itemspecific analysis due to the potential impact that presbyopia may have on daily activities (Table
3). In the near vision subscale, all items were significant (p <.0001), with Question 6 (How much
difficulty do you have doing work or hobbies that require you to see well up close?) having the
greatest impact (ES=0.30; p<0.001; MR =0.6005; 95% CI:0.5326,0.6771). In the distance vision
and driving subscales, one item in each subscale showed evidence for a significant association:
Question 9 for distance activities (How much difficulty do you have going down steps in dim
light?) (ES=0.35; p<0.001; MR =0.8270; 95% CI:0.7334,0.9231), and Question 16 for driving
(How much difficulty do you have driving at night?) (ES=0.25; p=0.022; MR =0.8521; 95%
CI:0.7408,0.9802). Lastly, the dependency subscale showed a significant association with two
items, Question 23 (I have to rely too much on what other people tell me) ( ES=0.19; p=0.022;
MR=0.8958; 95% CI:0.8106,0.9900) and Question 24 (I need a lot of help from others because
of my eyesight) ( ES=0.18; p=0.022; MR=0.8781; 95% CI:0.7945,0.9802) with both questions
having similar impacts.

10
Effect Modification by Vision and Health Insurance
In our sample 4,088 individuals (65%) had health insurance and 3,191 individuals (51%) had
vision insurance (Table 1). Inclusion of interaction term revealed no evidence of effect
modification by vision insurance status on the relationship between presbyopia and any of the
vision specific quality of life subscales. Similarly, most subscales showed no evidence of effect
modification by health insurance (all p > 0.05). However, there was evidence of effect
modification by health insurance in the dependency subscale (p =0.003). Stratified analyses
indicated that individuals with presbyopia who did not have health insurance (ES=0.13; p<0.001;
MR=0.7261; 95% CI:0.6065,0.8694) experienced a greater decline in vision related dependency
compared to those with health insurance (ES=0.13; p=0.394; MR=0.9512; 95%
CI:0.8353,1.0725).

11
Chapter 4. Discussion
This study highlights the significant negative impact of presbyopia on vision related quality of
life. Univariate analyses indicated that presbyopia led to a decreased quality of life across all
vision specific subscales, with the strongest negative relationship found in the near vision
subscale. Specifically, individuals with presbyopia experienced a 36% reduction in near vision
related quality of life compared to those without presbyopia. The composite score analyses
showed that overall, individuals with presbyopia experienced a 24% lower vision specific quality
of life compared to those without presbyopia.
After adjusting for age, gender, income, education level, and both health and vision
insurance, presbyopia remained significantly associated with reduced vision specific quality of
life in most subscales and in the composite score. However, the general health, general vision,
distance vision, social functioning, and driving subscales did not show significant associations.
The adjusted composite score indicated a 15% decrease in vision specific quality of life for those
with presbyopia compared to those without presbyopia. The findings from this study are
consistent with previous studies on the association of presbyopia on reduced quality of life10,12,14
.
The item-specific analysis provides further insight into the impact of presbyopia on daily
life by taking a closer look at the questions from the near vision, distance vision, dependency,
and driving subscales. As expected, the strongest association was found in the items of near
vision subscale, where participants reported difficulty with tasks requiring near vision.
Significant associations were also found in vision-related activities concerning low light
situations, such as driving at night and walking downstairs in dim light, as well as in tasks that
required assistance from others. Although research on the relationship between presbyopia and

12
low-light activities is limited, a study by Renfeng et al. found that low light levels adversely
affected near distance reading for presbyopes16
. Our findings extend the literature on
presbyopia’s effects in low light to common daily activities beyond reading, emphasizing the
need for improved accommodations and interventions.
The effect of presbyopia on the dependency subscale was significantly modified by
health insurance status. Presbyopia appears to increase reliance on others for daily tasks, with
uninsured individuals experiencing a greater reduction in vision related dependency compared to
those with health insurance. Notably, Individuals in older age groups tended to have lower
average dependency scores, possibly due to a higher prevalence of presbyopia in older
individuals or a natural decline with age. These findings suggest that health insurance may
provide some support in mitigating the effects of presbyopia on vision specific quality of life.
Individuals with presbyopia that had health insurance experience a 4% reduction in
vision related dependency, while those without health insurance experience a 28% reduction
(Table 4). With 35% of the study population not having health insurance, this study emphasizes
the need to address health disparities in the Latino population of Los Angeles. However, this
effect modification was not observed in other subscales, indicating that while health insurance
may help mitigate the effects of presbyopia on vision related dependency, it may not fully help
with other areas. Interestingly, health insurance was an effect modifier rather than vision
insurance. This may be due to a broader range of services covered under health insurance, such
as occupational therapy, mental health support, or other social programs that may be out of the
scope for vision insurance. Future studies should investigate the role of vision and health
insurance on the association between presbyopia and quality of life.

13
While this study provides valuable insights into the impact of presbyopia on vision
specific quality of life, there are limitations that should be acknowledged. Due to the reliance on
self-reported responses, the study may be subject to recall bias. Additionally, the participants in
our study are Latinos aged 40 years and older residing in Los Angeles County, which may limit
the generalizability of the findings to other populations. However, a key strength of this study is
its focus on the Latino population, which is a group that has not been extensively studied in the
context of presbyopia. This study adds new insights into the challenges faced by Latinos, making
an important contribution to the literature. To enhance the generalizability and applicability of
future studies, it would be beneficial to include more diverse populations or different sub-groups
for comparison.

14
Chapter 5. Conclusion
In summary, presbyopia was found to significantly reduce vision specific quality of life.
Presbyopia affects many different aspects of daily life with tasks that require near vision acuity
being the most affected. While health and vision insurance had limited effect modification
overall, there was evidence that health insurance reduced the impact of presbyopia on vision
related dependency. These findings suggest that access to health insurance may help alleviate
some aspects of presbyopia’s impact, specifically when relating to an individual’s dependence on
others.

15
References
1. American Optometric Association. “For 128 Million U.S. Presbyopes, Doctors of
Optometry Can Provide Treatment Options.” American Optometric Association (AOA),
www.aoa.org/news/clinical-eye-care/diseases-and-conditions/for-128-million-uspresbyopes-doctors-of-optometry-can-provide-treatment-options?sso=y. Accessed 25
Aug. 2024.
2. Berdahl, John et al. “Patient and Economic Burden of Presbyopia: A Systematic
Literature Review.” Clinical ophthalmology (Auckland, N.Z.) vol. 14 3439-3450. 22 Oct.
2020, doi:10.2147/OPTH.S269597
3. Boyd, Kierstan. “What Is Presbyopia?” Edited by Odalys Mendoza, American Academy
of Ophthalmology, 21 May 2024, www.aao.org/eye-health/diseases/what-is-presbyopia.
Accessed 23 Aug. 2024.
4. Fricke, T. R., Tahhan, N., Resnikoff, S., Papas, E., Burnett, A., Ho, S. M., Naduvilath, T.,
& Naidoo, K. S. (2018). Global Prevalence of Presbyopia and Vision Impairment from
Uncorrected Presbyopia: Systematic Review, Meta-analysis, and
Modelling. Ophthalmology, 125(10), 1492–1499.
https://doi.org/10.1016/j.ophtha.2018.04.013
5. Goertz, A. D., Stewart, W. C., Burns, W. R., Stewart, J. A., & Nelson, L. A. (2014).
Review of the impact of presbyopia on quality of life in the developing and developed
world. Acta ophthalmologica, 92(6), 497–500. https://doi.org/10.1111/aos.12308
6. Haraldstad, K et al. “A systematic review of quality of life research in medicine and
health sciences.” Quality of life research : an international journal of quality of life
aspects of treatment, care and rehabilitation vol. 28,10 (2019): 2641-2650.
doi:10.1007/s11136-019-02214-9
7. Kandel, H., Khadka, J., Goggin, M., & Pesudovs, K. (2017). Impact of refractive error on
quality of life: a qualitative study. Clinical & experimental ophthalmology, 45(7), 677–
688. https://doi.org/10.1111/ceo.12954
8. Mangione CM, Lee PP, Gutierrez PR, et al. Development of the 25-list-item National
Eye Institute Visual Function Questionnaire. Arch Ophthalmol. 2001;119(7):1050–1058.
doi:10.1001/archopht.119.7.1050
9. Mayo Clinic Staff. “Presbyopia.” Mayo Clinic, Mayo Foundation for Medical Education
and Research, 20 Nov. 2021, www.mayoclinic.org/diseasesconditions/presbyopia/symptoms-causes/syc-20363328. Accessed 12 Sept. 2024.

16
10. McDonnell PJ, Lee P, Spritzer K, Lindblad AS, Hays RD. Associations of Presbyopia
With Vision-Targeted Health-Related Quality of Life. Arch
Ophthalmol. 2003;121(11):1577–1581. doi:10.1001/archopht.121.11.1577
11. McKean-Cowdin, Roberta et al. “Severity of visual field loss and health-related quality of
life.” American journal of ophthalmology vol. 143,6 (2007): 1013-23.
doi:10.1016/j.ajo.2007.02.022
12. Muhammad, Nasiru et al. “Visual function and vision-related quality of life in presbyopic
adult population of Northwestern Nigeria.” Nigerian medical journal : journal of the
Nigeria Medical Association vol. 56,5 (2015): 317-22. doi:10.4103/0300-1652.170379
13. Patel, Ilesh, and Sheila K West. “Presbyopia: prevalence, impact, and
interventions.” Community eye health vol. 20,63 (2007): 40-1.
14. Patel, I., Munoz, B., Burke, A. G., Kayongoya, A., McHiwa, W., Schwarzwalder, A. W.,
& West, S. K. (2006). Impact of presbyopia on quality of life in a rural African
setting. Ophthalmology, 113(5), 728–734. https://doi.org/10.1016/j.ophtha.2006.01.028
15. Rodriguez-Lopez, Victor et al. “Contact lenses, the reverse Pulfrich effect, and antiPulfrich monovision corrections.” Scientific reports vol. 10,1 16086. 30 Sep. 2020,
doi:10.1038/s41598-020-71395-y
16. Renfeng Xu, Daniel Gil, Mohammed Dibas, William Hare, Arthur Bradley; The Effect of
Light Level and Small Pupils on Presbyopic Reading Performance. Invest. Ophthalmol.
Vis. Sci. 2016;57(13):5656-5664. https://doi.org/10.1167/iovs.16-20008.
17. Varma, R., Paz, S. H., Azen, S. P., Klein, R., Globe, D., Torres, M., Shufelt, C., PrestonMartin, S., & Los Angeles Latino Eye Study Group (2004). The Los Angeles Latino Eye
Study: design, methods, and baseline data. Ophthalmology, 111(6), 1121–1131.
https://doi.org/10.1016/j.ophtha.2004.02.001

17
Appendix
Table 1. Demographic characteristics by Presbyopia Status. Reported are N (%).
Characteristic N Overall, N =
6,3121
Presbyopia
Absent, N =
2,2891
Presbyopia
Present, N =
4,0231
p-value2
Age 6,312 54.88 (10.99) 49.03 (9.90) 58.21 (10.16) <0.001
Female 6,312 3,695 (59%) 1,230 (54%) 2,465 (61%) <0.001
Income (above
20k)
5,575 2,731 (49%) 1,096 (53%) 1,635 (46%) <0.001
High school or
college education
6,291 2,106 (33%) 865 (38%) 1,241 (31%) <0.001
Has health
insurance
6,293 4,088 (65%) 1,381 (61%) 2,707 (67%) <0.001
Has vision
insurance
6,229 3,191 (51%) 1,067 (47%) 2,124 (54%) <0.001
1 Mean (SD) ; n (%)
2 Wilcoxon rank sum test; Pearson’s Chi-squared test

18
Table 2. Linear Regression of Presbyopia on Quality of Life
NEI-VFQ-25
Subscale
Unadjusted Presbyopia
Mean Ratio (Exponentiated
Beta Coefficient) (95% CI)
P-value Adjusted Presbyopia
Mean Ratio
(Exponentiated Beta
Coefficient) (95% CI)
P-value
General Health 0.9048 (0.8521, 0.9512) <0.001 1.004 (0.9231, 1.0833) 0.906
General Vision 0.8601 (0.8025, 0.9231) <0.001 0.9324 (0.8694, 1.0101) 0.072
Ocular pain 0.8869 (0.8106, 0.9704) 0.006 0.8869 (0.7945, 0.9802) 0.018
Near Vision 0.6376 (0.5827, 0.6977) <0.001 0.7483 (0.6703, 0.8270) <0.001
Distance Vision 0.6771 (0.6126, 0.7334) <0.001 0.9418 (0.8521, 1.0513) 0.320
Vision Related
Social
Functioning
0.7788 (0.7189, 0.8437) <0.001 0.9608 (0.8607, 1.0408) 0.376
Vision Related
Mental Health
0.7118 (0.6637, 0.7634) <0.001 0.7189 (0.6637, 0.7866) <0.001
Vision Related
Role Function
0.6440 (0.5827, 0.7047) <0.001 0.8025 (0.7189, 0.8958) <0.001
Vision Related
Dependency
0.6839 (0.6313, 0.7483) <0.001 0.8607 (0.7711, 0.9418) 0.004
Driving Difficulty 0.7118 (0.6440, 0.7866) <0.001 0.9048 (0.7945, 1.0101) 0.082
Color Vision 0.8025 (0.7483, 0.8607) <0.001 0.9139 (0.8437, 0.9900) 0.034
Peripheral Vision 0.6637 (0.6065, 0.7261) <0.001 0.8437 (0.7558, 0.9418) 0.002
Composite Score 0.7616 (0.7276, 0.7973) <0.001 0.8528 (0.8090, 0.8990) <0.001

19
Table 3. Item-specific Multiple Linear Regression of Presbyopia on Quality of Life Subscales
Adjusting for Covariates.
NEI-VFQ-25 Itemized questions Adjusted Presbyopia Mean
Ratio (Exponentiated Beta
Coefficient) (95% CI)
P-value Effect Size
(Glass’s Delta)
Near Activities
5- Difficulty reading ordinary print
6- Difficulty with near vision hobbies/work
7- Difficulty finding things on a crowded
shelf
0.7408 (0.6570, 0.8437)
0.6005 (0.5326, 0.6771)
0.7634 (0.6839,0.8607)
<0.001
<0.001
<0.001
0.17
0.30
0.26
Distance Activities
8- Difficulty reading street/store signs
9- Difficulty going down steps in dim light
14- Difficulty going out to see movies/plays
1.0305 (0.9139, 1.1618)
0.8270 (0.7334,0.9231)
0.9900 (0.8958,1.0942)
0.626
<0.001
0.826
0.10
0.35
0.10
Vision Related Dependency
20- Stay home due to eyesight
23- Feel frustrated due to eyesight
24- Have less control due to eyesight
0.9324 (0.8353,1.0305)
0.8958 (0.8106,0.9900)
0.8781 (0.7945,0.9802)
0.142
0.022
0.022
0.16
0.19
0.18
Driving Difficulty
15c- Difficulty driving in familiar places
during daytime
16- Difficulty driving at night
0.9512 (0.8694,1.0513)
0.8521 (0.7408,0.9802)
0.306
0.022
0.08
0.25

20
Table 4. Stratified Multiple Linear Regression by Health Insurance Status
NEI-VFQ-25
Subscale
Health Insurance
Adjusted Mean Ratio
(Exponentiated Beta
Coefficient) (95% CI)
No Health Insurance
Adjusted Mean Ratio
(Exponentiated Beta
Coefficient) (95% CI)
General Health 1.0033 (0.9324, 1.0833) 0.9802 (0.8607, 1.1163)
General Vision 0.9048 (0.8187, 1.0101) 0.9900 (0.8958, 1.0942)
Ocular Pain 0.8694 (0.7711, 0.9900) 0.9231 (0.7866, 1.0833)
Near Vision 0.7118 (0.6250, 0.8187) 0.7788 (0.6505, 0.9512)
Distance Vision 0.8958 (0.7866, 1.0202) 1.0513 (0.8781, 1.2461)
Vision Related
Social
Functioning
0.9923 (0.8869, 1.1163) 0.8958 (0.7634, 1.0408)
Vision Related
Mental Health
0.6977 (0.6250, 0.7711) 0.7711 (0.6703, 0.8869)
Vision Related
Role Function
0.8353 (0.7408, 0.9512) 0.7634 (0.6440, 0.9231)
Vision Related
Dependency*
0.9512 (0.8353, 1.0725) 0.7261 (0.6065, 0.8694)
Driving
Difficulty
0.8958 (0.7788, 1.0408) 0.9231 (0.7408, 1.1503)
Color Vision 0.9324 (0.8353, 1.0408) 0.8869 (0.7634, 1.0305)
Peripheral
Vision
0.8106 (0.6977, 0.9324) 0.9048 (0.7558, 1.1052)
Composite
Score
0.8521 (0.7945, 0.9139) 0.8607 (0.7866, 0.9418)
*Only Vision Related Dependency differed significantly between insurance status.

21
Table 5. Mean, Medians, and Missing Values for Quality of Life Subscales
Characteristic Overall, N = 6,312 Presbyopia
Absent, N =
2,289
Presbyopia
Present, N =
4,023
Effect Size
(Glass’s
Delta)
V25-General Health 0.19
Mean (SD) 46.14 (23.72) 49.08 (23.01) 44.65 (23.93)
Median (IQR) 50.00 (25.00, 50.00) 50.00 (25.00,
50.00)
50.00 (25.00,
50.00)
Unknown 907 472 435
V25-General Vision 0.14
Mean (SD) 68.22 (16.72) 69.83 (17.06) 67.40 (16.49)
Median (IQR) 60.00 (60.00, 80.00) 60.00 (60.00,
80.00)
60.00 (60.00,
80.00)
Unknown 932 480 452
V25-Ocular Pain 0.12
Mean (SD) 77.81 (20.77) 79.35 (19.90) 77.03 (21.15)
Median (IQR) 87.50 (62.50, 100.00) 87.50 (75.00,
100.00)
87.50 (62.50,
100.00)
Unknown 931 480 451
V25-Near Vision 0.29
Mean (SD) 79.42 (20.48) 83.18 (19.46) 77.52 (20.73)
Median (IQR) 83.33 (66.66, 100.00) 91.66 (75.00,
100.00)
83.33 (66.66,
91.66)
Unknown 933 481 452
V25-Distance Vision 0.25
Mean (SD) 85.62 (19.11) 88.55 (17.61) 84.14 (19.66)
Median (IQR) 91.66 (75.00, 100.00) 100.00 (83.33,
100.00)
91.66 (75.00,
100.00)
Unknown 937 483 454
V25-Vision Related
Social Function
0.14
Mean (SD) 92.56 (14.86) 93.90 (14.20) 91.88 (15.14)
Median (IQR) 100.00 (87.50, 100.00) 100.00 (100.00,
100.00)
100.00 (87.50,
100.00)
Unknown 936 481 455
V25-Vision Related
Mental Health
0.27
Mean (SD) 76.29 (22.42) 80.00 (20.91) 74.41 (22.92)
Median (IQR) 81.25 (68.75, 93.75) 87.50 (75.00,
93.75)
81.25 (62.50,
93.75)
Unknown 932 481 451
V25-Vision Related Role
Function
0.25
Mean (SD) 87.68 (21.87) 90.97 (19.70) 86.02 (22.71)

22
Median (IQR) 100.00 (87.50, 100.00) 100.00 (87.50,
100.00)
100.00 (75.00,
100.00)
Unknown 933 481 452
V25-Vision Related
Dependency
0.20
Mean (SD) 89.16 (20.88) 91.69 (19.10) 87.88 (21.61)
Median (IQR) 100.00 (83.33, 100.00) 100.00 (91.66,
100.00)
100.00 (83.33,
100.00)
Unknown 936 482 454
V25-Driving Difficulties 0.20
Mean (SD) 87.61 (18.42) 89.74 (17.02) 86.41 (19.05)
Median (IQR) 87.50 (87.50, 100.00) 100.00 (87.50,
100.00)
87.50 (87.50,
100.00)
Unknown 2,448 902 1,546
V25-Color Vision 0.15
Mean (SD) 93.82 (15.56) 95.29 (14.34) 93.07 (16.10)
Median (IQR) 100.00 (100.00, 100.00) 100.00 (100.00,
100.00)
100.00 (100.00,
100.00)
Unknown 940 483 457
V25-Peripheral Vision 0.24
Mean (SD) 86.71 (21.09) 89.76 (19.25) 85.17 (21.80)
Median (IQR) 100.00 (75.00, 100.00) 100.00 (75.00,
100.00)
100.00 (75.00,
100.00)
Unknown 938 482 456
V25-Composite Score 0.27
Mean (SD) 83.83 (14.52) 86.35 (13.83) 82.55 (14.69)
Median (IQR) 88.92 (78.67, 93.75) 90.91 (83.50,
94.77)
87.58 (76.10,
93.07)
Unknown 931 480 451

Abstract (if available)

Abstract Background: As people age, they are likely to be affected by presbyopia to some extent. Understanding the effects of presbyopia on vision specific quality of life is important for identifying affected aspects of daily life and for providing improved treatment options.
Methods: For this analysis, we utilized data from the Los Angeles Latino Eye Study (LALES), a population-based study of Latinos aged 40 years or older in Los Angeles County. Vision specific quality of life was measured using the National Eye Institute’s Visual Function Questionnaire (NEI VFQ-25). Linear regression analyses were conducted to assess the relationship between overall and subscales of vision specific quality of life and presbyopia status. Covariate-adjusted models controlled for age, gender, income, education level, and insurance status.
Results: Presbyopia was associated with lower vision specific quality of life scores across all subscales of the NEI-VFQ-25 (all p<0.05). After adjusting for covariates, significant associations were observed in 7 subscales and the overall composite score. Health insurance was found to modify the association between presbyopia and vision related dependency; the deleterious effect of presbyopia was stronger in individuals without health insurance.
Conclusion: Presbyopia significantly reduced overall vision-specific quality of life, with near vision tasks being the most affected. While vision insurance showed no evidence of effect modification, health insurance was found to be an effect modifier with it significantly reducing the negative impacts of presbyopia on vision related dependency. These findings highlight that access to health insurance may help mitigate some of the negative effects of presbyopia.

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Creator De La O, Jayson (author)

Core Title Presbyopia and quality of life among the Latino population

School Keck School of Medicine

Degree Master of Science

Degree Program Biostatistics

Degree Conferral Date 2024-12

Publication Date 12/09/2024

Defense Date 12/07/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

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