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Abstract
Objectives This study aims to study the association between socioeconomic factors and risk of prevalent eye diseases, including glaucoma, cataract and retinal vein occlusion (RVO) in an elderly Danish population.
Design This study was a nationwide cohort study.
Setting and participants The included subjects were extracted from Danish nationwide health registers, and the association between socioeconomic factors and prevalent eye diseases was assessed by estimating the incidence rate and the cumulative incidence. The differences between the investigated groups were quantified using the Cox proportional hazard model.
Results Based on a 10-year follow-up period, the highest levels of education and household income were associated with higher rates and risks of glaucoma compared with the lowest and middle levels. This results in absolute risks ranging from 3.2% (3.1%–3.3%) in both the lowest educational and income group to 4.0% (3.9–4.1%) and 3.8% (3.8–3.9%) in the highest educational and income group, respectively. For cataract, the middle and lowest educational and income levels were associated with increased rates and risks, which were statistically significant compared with the highest levels. The risk of cataract ranged from 6.5% (6.4%–6.7%) to 8.1% (8.0%–8.2%) and 6.0% (5.9%–6.1%) to 8.7% (8.5%–8.8%) in the highest to the lowest educational and income group, respectively. For RVO, the event rate was low, showing no statistically significant differences. The risk of RVO remained constant in all investigated socioeconomic groups, with a risk of 0.3% (0.3%–0.3%).
Conclusion Our findings indicate that socioeconomic factors, such as education and household income, are associated with the diagnosis glaucoma and cataract. Incorporating socioeconomic considerations into public health initiatives may enhance the management of eye diseases and improve information and awareness about these conditions.
- EPIDEMIOLOGY
- OPHTHALMOLOGY
- PUBLIC HEALTH
Data availability statement
Data may be obtained from a third party and are not publicly available. The data used in this study were extracted from Danish national registers.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Previous research has explored the risk factors associated with retinal vein occlusion, glaucoma and cataract. However, the influence of socioeconomic factors on the risk of these eye diseases remains unelucidated.
WHAT THIS STUDY ADDS
This study reveals that higher levels of education and income are associated with increased rates of glaucoma, while lower educational and income levels are linked to higher rates of cataract.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The findings suggest that socioeconomic factors should be considered in eye disease prevention and management strategies. Future research could further investigate the underlying mechanisms, and policy-makers could enhance awareness and interventions targeting the socioeconomic disparities in eye health.
Introduction
Social inequality in healthcare is a known phenomenon and has been described as an independent risk factor for increased morbidity and shorter life span.1 2 Previous studies found that lower socioeconomic status, including education, income, sex and ethnicity, is associated with increased risk of visual impairment and blindness.3–6 For example, higher socioeconomic status is associated with better prevention of glaucoma progression, while individuals with higher educational level show increased understanding of glaucoma and necessity of eye care and healthcare adherence.7 Lower educational level is known to have an impact on a number of ocular diseases, for example, diabetic retinopathy, where lower educational level is associated with a higher incidence of the condition.8 Socioeconomic status may be a factor that should be more actively addressed in the clinical setting and which may help identify high-risk patients based on a more personal approach. However, the importance of socioeconomic status is often difficult to assess as socioeconomic factors influence the access to healthcare in many countries.
Denmark has an egalitarian healthcare system supported mainly through a progressive national income tax that ensures free, accessible healthcare for all.9 Furthermore, Denmark has nationwide healthcare registers where diagnoses, procedures, operations and treatments are registered.10 Additionally, socioeconomic factors, such as education and household income, are systematically registered for the Danish population. This makes investigations of the association between socioeconomic factors and selected diseases possible.
In this study, we focus on the association between socioeconomic factors and being diagnosed with some of the most prevalent and not previously investigated eye diseases, including cataract, glaucoma and retinal vein occlusion (RVO).
Methods
Data sources
The data for this study were collected from comprehensive Danish nationwide registries. Data from the different registries were linked by a personal identification number that all Danish residents receive at birth or immigration. Information pertaining to individuals’ date of birth, gender, vital status, migration and date of death was sourced from the Danish Civil Registration System.11–13 All data on hospital admissions at public Danish hospitals, including diagnoses, procedures, operations and administrative information were retrieved from the Danish National Patient Register.14 15 The Danish National Prescription Database holds records of all pharmaceutical prescriptions dispensed at Danish pharmacies.16 17 Information about education were collected from the Population Education Register and household income from the Income Statistics Registry.18 19
All used registration codes are summarised in online supplemental table S1.
Supplemental material
Settings
The population for this study consisted of all Danish residents alive at age 60 within the period 2000–2018. Patients were excluded from the analysis if the register data were incomplete or if information on either educational level or household income was missing. At the index date, registered socioeconomic information, including education and household income, was collected for each individual and the risk of eye diseases was investigated. Education is often established early in life, whereas household income is often more dynamic throughout life, including both ensured both an early and a current indicator of socioeconomic status. For education, the lowest group consisted of individuals who completed primary school, the middle educational group consisted of individuals who finished high school or had vocational education and the highest educational group consisted of individuals who finished a higher education. For household income, the population was divided into tertiles (online supplemental figure S1).
The outcomes of this study included an incident diagnosis for glaucoma, cataract or RVO. The risk of each eye disease was investigated at 10 years of follow-up.
Statistical analyses
Baseline characteristics were summarised through descriptive analyses, presenting proportions for categorical covariates. The risk of eye diseases was assessed using time-to-event analyses, following the patients from their 60th birthday until a diagnosis of the investigated eye diseases, the competing event of death, censoring due to emigration, or administrative end of follow-up (31 December 2018). Patients with missing information were excluded from the analysis concerning the missing variable. We estimated the incidence rate for each included eye disease outcome. Using the Aalen Johansen estimator, we estimated the absolute risk of eye diseases for all investigated socioeconomic exposures, where death was included as a competing risk. Furthermore, we performed likelihood ratio tests to estimate whether the difference between the exposure levels was statistically significant. Cox proportional hazard models were used to estimate the HRs between investigated groups, using the highest level as the reference. We included two Cox models. The association between both education and household income and the included eye diseases was adjusted for sex. Furthermore, the association between household income and the included eye diseases was adjusted for both sex and educational level, to assess whether the observed effect was mediated by educational level. This adjustment was not applied when education was the exposure, as we do not expect an individual’s income level to influence their achieved level of education.
Patient involvement
No patient involvement was used in this study.
Results
The population for this study consisted of 1 094 928 individuals aged 60 at inclusion of which 50.4% were women (table 1). Comorbidities and distribution dependent on socioeconomic factors are summarised in table 1. When assessing the comorbidities according to socioeconomic group, there was a tendency for the lowest socioeconomic group to have a higher prevalence of the included comorbidities (online supplemental table S2).
Baseline characteristics for the study population, at age 60 observed between 2000 and 2018
RVO was the least frequent outcome considered in this study, with an overall rate of 0.29 events per 1000 person years. No statistically significant differences in rate and risk estimates for RVO were observed between the socioeconomic groups. The estimated risk of RVO was 0.3% for all investigated socioeconomic groups (table 2).
Ten-year risk of major eye diseases according to socioeconomic position at age 60
The highest educational level and highest household income were both associated with a higher rate and risk of having a glaucoma diagnosis compared with the lowest and middle education levels and household incomes, respectively. The differences between the investigated groups using the highest group as the reference were quantified yielding HRs of 0.82 (95% CI 0.79 to 0.84) and 0.88 (95% CI 0.85 to 0.91) for the lowest educational and household income group, respectively. For the middle educational and household income group, the HRs were 0.85 (95% CI 0.82 to 0.87) and 0.90 (95% CI 0.87 to 0.92), respectively (table 2).
For cataract, we found increasing rate and risks for the middle and lowest educational and household income levels compared with the highest levels. The highest educational and household income levels were used as reference when quantifying the differences between the socioeconomic groups. Estimated HRs were 1.08 (95% CI 1.06 to 1.11) for the lowest educational level, 1.18 (95% CI 1.15 to 1.20) for the lowest household income level, 1.29 (95% CI 1.26 to 1.32) for the middle educational level and 1.57 (95% CI 1.53 to 1.60) for the middle household income level, thus statistically significantly higher than the reference groups (table 2).
Adjusting the association of household income for educational level only slightly altered the effect measures indicating a limited amount of confounding by education (table 2).
For the groups exhibiting statistically significant differences between the analysed socioeconomic categories, the difference gradually increased over the 10-year follow-up period indicating a constant incidence during the follow-up period (figure 1).
Cumulative incidence plots of the investigated eye diseases according to socioeconomic strata. Left column: the cumulative incidence plots for each ophthalmologic outcome according to educational level. Right column: the cumulative incidence plots for each ophthalmological outcome according to household income level.
Discussion
Varying results emerged from this nationwide cohort study. We found that higher education and higher household income were associated with a lower risk of cataract. Furthermore, higher education and higher income were associated with a higher risk of receiving a glaucoma diagnosis. Lastly, the development of RVO was not statistically significantly associated with the investigated socioeconomic factors.
Previous studies have demonstrated that low socioeconomic position increases the risk of different diseases, including diabetic retinopathy, age-related macular degeneration, stroke and ischaemic heart disease.8 20 21 However, we found that the risk of a glaucoma diagnosis was higher for both higher educational level and household income. These results were unexpected and did not align with the role of socioeconomic in the development of other investigated diseases. Previous studies have estimated that approximately 1.5% of the adult populations have glaucoma increasing to 10% of individuals aged 80 years or above; however, it is widely acknowledged that a substantial number of glaucoma cases remain undiagnosed.22 Glaucoma is a chronic progressive disease, where symptoms manifest late in the development of the disease.23 24 Glaucoma is hereditary and high-risk families can be screened, which may detect the disease early, before severe progression.24 25 Furthermore, glaucoma generally causes symptoms at very late stages.23 Screening requires knowledge and understanding of both the disease, increased risk and the screening programme. Patients of high socioeconomic status may be more likely to attend glaucoma screening due to higher awareness of the hereditary aspects of the disease. Patients with high socioeconomic status may also be more likely to consult an ophthalmologist in general thereby resulting in a higher number of diagnosed cases. It is important to note that our follow-up period was 10 years from the 60th birthday of the included patients. Therefore, these results suggest that the patients of lower socioeconomic groups are not diagnosed between the ages of 60 and 70 years to the same extend as patients of higher socioeconomic groups. Initiatives to increase awareness among patients with lower socioeconomic status about glaucoma screening and the irreversible visual loss related to the condition may potentially improve the outcome in this group of patients.
Cataract was the most common of the investigated eye diseases. Our study identified that the risk of cataract was increased in patients of lower socioeconomic groups. The increased risk could be attributed to lifestyle factors, such as smoking, alcohol consumption, physical activity and outdoor work, which are risk factors for cataract and have previously been associated with socioeconomic group.26–28 As opposed to glaucoma, our data indicate that cataract manifests with symptomatology that brings patients of lower socioeconomic status to consult an ophthalmologist. However, patients in higher socioeconomic groups may consult private ophthalmologists for a cataract surgery and the diagnosis will not be registered if the management is performed in private practice. This could partly explain the observed lower risk in these groups.
In this study, we found no differences in the risk of RVO diagnosis among different socioeconomic groups. This suggests that the abrupt change in vision prompts individuals from all socioeconomic backgrounds to seek medical attention. We did not identify any differences between the investigated socioeconomic groups, which we expected due to lifestyle risk factors, the same as for cataract. This could suggest that it may be another mechanism facilitating the increased risk in lower socioeconomic groups for cataract. Otherwise, the relatively low number of RVO cases could dilute a possible association. The rates and risks estimated for RVO were close to identical, while the HRs varied between the investigated groups. This may be caused by the incidence of RVO being relatively low, and the sample size of this study being large.
As people age, most will require glasses or contact lenses and will therefore visit an optician at some point. During these visits, a fundus photograph and measurement of intraocular pressure could aid in the early detection of glaucoma and other presymptomatic eye diseases. This approach could facilitate the early detection of more patients, enabling prompt intervention and mitigating the impact on vision, ultimately improving patient prognoses. Additionally, targeted initiatives to raise awareness and understanding of eye diseases among lower socioeconomic groups could significantly optimise outcomes for these patients, particularly if our hypothesis regarding the prevalence of undiagnosed cases within this demographic is accurate.
The main strength of this study is the use of registry data with nationwide coverage,15 providing a relatively large study population with limited selection bias. Furthermore, we assessed both the absolute and relative risk, allowing for a more detailed interpretation of the results. A nationwide population ensure a high generalisability, since all demographic and geographical groups of the country will be represented.
Our study is accompanied by limitations. The investigated eye diseases become more prevalent as time progresses. However, the change in socioeconomic factors is more dynamic earlier in life, especially education which is predominantly established in the earlier adulthood. Income will also change less in a population with a large proportion of pensioners. Consequently, the socioeconomic status of the investigated individuals would be less prone to changes in elderly population. The comparable results between educational level and household income suggest that these differences in the characteristics of the socioeconomic factors did not affect the associations observed in this study.
Although the validity of the Danish health registers is generally considered high, incomplete data are present for the socioeconomic factors, especially for the older populations and immigrants. The missing socioeconomic information may be systematic and introduce selection bias.
The included socioeconomic factors were investigated separately. To assess the overall socioeconomic position of individuals, a combination of different socioeconomic factors would be relevant; however, combining the factors to create representative groups is challenging. Therefore, we investigated the socioeconomic factors independently and assessed the individual associations.
Conclusion
We found that socioeconomic factors were associated with a diagnosis of glaucoma and cataract. Individuals with high socioeconomic status were more likely to have a diagnosis of glaucoma. Our data suggest that glaucoma may be underdiagnosed in lower socioeconomic groups. Initiatives to improve awareness of glaucoma and the course of the disease may have the potential to improve the outcomes of glaucoma in populations with lower socioeconomic status. An elevated risk of cataract was identified among individuals with lower socioeconomic status, highlighting the intricate interplay between socioeconomic disparities and the development of cataract. As opposed to glaucoma, the symptomatology of cataract seems to motivate individuals of lower social status to consult an ophthalmologist.
In conclusion, public health initiatives should be tailored to address the specific challenges faced by individuals with lower socioeconomic status to improve the overall management of eye diseases, aiming to improve the information for this demographic and the general knowledge of specific eye diseases in the general population.
Data availability statement
Data may be obtained from a third party and are not publicly available. The data used in this study were extracted from Danish national registers.
Ethics statements
Patient consent for publication
Ethics approval
Per Danish law, this project did not have to notify or be approved by the North Denmark Region Committee on Health Research Ethics.
References
Footnotes
Contributors All authors contributed to the concept, design and planning of the study. MØ was responsible for the data collection and lead for the data analysis. FS assisted in the data analysis. FS, TBL, TB, LJC and HV supervised the process and contributed to the data analysis and methodology when needed. All authors contributed to the interpretation of the data. The first draft was written by MØ and revised by FS, TBL, TB, LJC and HV before submission. All authors revised the manuscript. MØ submitted the manuscript and is the guarantor for the study.
Funding This study was funded by The Danish Eye Research Foundation and Lions Club Bannerslund. The funders did not influence the design or execution of the study.
Competing interests LJC: AbbVie (Advisory Board, speaker fee), Bayer (Advisory Board, speaker fee), Novartis (Advisory Board), Roche (Advisory Board, grant support). HV: Bayer (Advisory Board), Roche (Advisory Board). TB, TBL, FS and MØ: no conflicts of interest.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.