Sex Differences in Waiting Times for Cataract Surgery in Sweden, 2010–2022: Nationwide Analysis of 1.4 Million Patients

Philip Jute

M.D.

Associate professor

Gustav Stålhammar

M.D. Ph.D. FEBO

1,2,3✉ Phone0046 8 123 230 00 Emailgustav.stalhammar@ki.se

St. Erik Eye Hospital Stockholm Sweden

2 Department of Clinical Neuroscience, Division of Eye and Vision Karolinska Institutet Stockholm Sweden

3 Department of Clinical Neuroscience St. Erik Eye Hospital, Karolinska Institutet Eugeniavägen 12 17164 Stockholm Sweden

Philip Jute, M.D.¹, Gustav Stålhammar, M.D., PhD.^1,2

¹St. Erik Eye Hospital, Stockholm, Sweden

²Department of Clinical Neuroscience, Division of Eye and Vision, Karolinska Institutet, Stockholm, Sweden

Gustav Stålhammar

Associate professor, M.D. Ph.D. FEBO

ORCID: 0000-0001-9401-8911

St. Erik Eye Hospital

Department of Clinical Neuroscience, Karolinska Institutet

Eugeniavägen 12, 17164 Stockholm, Sweden

Email: gustav.stalhammar@ki.se

Phone: 0046 8 123 230 00

Running title

Corresponding author

Sex differences in cataract surgery waiting time

Word count excluding abstract, tables, legends, and references

2926

ABSTRACT

Background

Sex-based disparities in healthcare access and outcomes remain a challenge. Understanding differences in waiting times for cataract surgery between males and females can reveal inequities in care delivery.

Methods

This nationwide retrospective cohort study used data from the Swedish National Cataract Register, which covers > 93% of all cataract surgeries in Sweden. A total of 1,413,652 patients aged > 40 years who underwent first-eye cataract surgery between 2010 and 2022 were included. Exclusions were made for patients with waiting times > 24 months, those residing outside Sweden, and those with missing sex data. The primary outcome was waiting time, defined as the interval between preoperative assessment and surgery.

Secondary analyses included stratification by visual acuity, regional variations, and the influence of demographic and clinical factors.

Results

The mean waiting time was 64 days for females (SD 126) and 60 days for males (SD 102), with a significant difference (P < 0.001). This disparity persisted across all visual acuity strata and regions. Multivariate Cox regression identified female sex, older age, specific comorbidities, and residence region as significant predictors of longer waiting times. Differences in comorbidities, including higher rates of pseudoexfoliation syndrome in females and endophthalmitis in males, were observed. Despite fluctuations in overall waiting times, the sex-based disparity remained consistent over the study period.

Conclusions

Persistent sex-based differences in waiting times for cataract surgery were identified in Sweden over 13 years. While small and unlikely to affect clinical outcomes, these differences highlight systemic inequities that merit further investigation and intervention to ensure equitable access to care.

PLAIN LANGUAGE SUMMARY

This study looked at differences in waiting times for cataract surgery between males and females in Sweden, using data from over 1.4 million patients between 2010 and 2022. Cataracts cause clouding of the eye's lens and require surgery for treatment. Females waited an average of 64 days for surgery compared to 60 days for males. This small but consistent difference was seen across all levels of vision impairment and regions in Sweden. Even after accounting for factors like age, other eye conditions, and location, females still faced longer delays. While these differences are unlikely to affect health outcomes, they may point to inequities in the healthcare system. Efforts are needed to ensure fair and equal access to cataract surgery for everyone.

INTRODUCTION

Cataract remains the leading cause of blindness worldwide, posing a significant public health challenge. .^1,2 In Sweden, where healthcare is largely tax-financed, over 140,000 cataract surgeries are performed annually, representing approximately 1.4% of the country’s 10-million population.³

Previous research has identified female sex as a risk factor for cataract, even after adjusting for age and accounting for mortality as a competing risk.⁴ Globally, a greater proportion of women than men experience blindness or visual impairment, and this disparity is projected to increase in the future.⁵ Paradoxically, female sex has also been recognized as a barrier to accessing cataract surgery in Asia and Africa, and sex-based differences in ocular comorbidities, surgical complications, and preoperative best-corrected visual acuity (BCVA) have been documented in American and European cohorts.^6–10 In Sweden, we recently demonstrated that BCVA at the time of surgery is comparable between sexes, suggesting that differences in cataract surgery rates are unlikely to reflect disparities in healthcare-seeking behavior or surgical admission criteria.¹¹

A previous study of 102,532 Swedish patients undergoing cataract surgery between 2010 and 2011 found that women experienced longer waiting times than men, even when stratified by similar levels of visual acuity.¹² Despite ongoing efforts to provide equitable healthcare access, persistent sex-based disparities have been reported in several medical fields.^13,14

Here, we examine how sex-based differences in waiting times for cataract surgery in Sweden have evolved from 2010 to 2022. This study analyzes a cohort of over 1.4 million patients, covering approximately 93% of all cataract surgeries performed nationwide during this period, to provide a comprehensive understanding of trends in waiting times.

METHODS

Inclusion and Exclusion Criteria

Data for this study were retrieved from the Swedish National Cataract Register (NCR), established in 1992 to document all cataract surgeries performed nationwide.³ The register is governed by a steering committee comprising physicians representing both public and private healthcare sectors, academia, one nurse, and one patient representative. The NCR captures approximately 93% of all cataract surgeries conducted in Sweden, with data reliability continuously monitored and validated.^15–17

Patients eligible for inclusion were those over 40 years old undergoing a first-eye cataract operation between January 1, 2010, and December 31, 2022, following methods outlined in a previous study on cataract surgeries conducted in 2010 (n = 1,482,725).¹²

Patients aged 40 years or younger (n = 66,495) were excluded, as cataracts in this group are typically congenital, juvenile, or secondary to other diseases or trauma, meaning standard waiting time rules do not apply. Additionally, patients with waiting times over 24 months (n = 687) were excluded, as such extended delays are uncommon. These long waiting periods in the Swedish National Cataract Register (NCR) are likely due to registration errors or specific circumstances, such as a patient request for surgery by a particular surgeon.

Thirdly, 1816 patients residing outside Sweden were excluded, as clinicopathological data may be less reliable for these, and their waiting time for surgery may be influenced by factors non-typical to the standard situation in the Swedish healthcare system. Lastly, 75 patients without a recorded sex was excluded, leaving 1,413,652 patients for analysis.

The study was approved by the Swedish Ethical Review Authority (reference 2022-00930-02) and adhered to the tenets of the Declaration of Helsinki.

The requirement for informed consent was waived due to the study's retrospective nature, relying solely on previously collected data. This research did not involve any new treatments, interventions, tests, analysis of biological samples, or collection of additional sensitive information. Additionally, we followed the The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Guidelines, details of which are provided in a supplementary file.

Admission Visit

In Sweden, the typical pathway for patients experiencing diminished visual acuity and other symptoms of cataracts often begins at a local optician. If cataracts are suspected, patients are referred to an ophthalmologist for further evaluation. Alternatively, patients may be referred by ophthalmologists who diagnose the condition during routine examinations for other eye-related issues. During the initial assessment, the patient's best-corrected visual acuity (BCVA) is measured by either an optometrist or an ophthalmic nurse. This is done using a KM-chart in a well-lit light box at a distance of three meters, where the BCVA is recorded on a decimal scale.¹⁸ The test involves identifying the smallest line in which six out of seven letters are read correctly after subjective refraction. Patients may use their own spectacles if they prefer.The procedure for measuring BCVA has remained consistent throughout the study period. In addition, intraocular pressure is measured, and a detailed examination of the anterior segment, including the lens, is conducted using a slit-lamp biomicroscope. Biometry assessments, including keratometry and either optical or ultrasound biometry, are performed to calculate the precise power of the intraocular lens (IOL) to be implanted to achieve the desired refraction. Once the admission visit is completed, surgery is scheduled as soon as reasonably possible. Waiting times for the procedure can vary based on several factors, including the availability of surgical staff and operating rooms, patient travel constraints, personal preferences, and any coexisting conditions that might delay surgical intervention. In this study, the period from the admission visit to the day of surgery is defined as the waiting time.

Statistical analyses

Statistical significance was defined as a two-sided P < 0.05 unless otherwise specified. Continuous variables were assessed for normality using the Shapiro-Wilk test. If the data deviated from a normal distribution (P < 0.05), the Mann-Whitney U test was used for group comparisons; otherwise, Student’s t-test was applied. Categorical baseline characteristics were compared using Pearson’s chi-square test. To control for type I errors due to multiple comparisons, the two-stage step-up False Discovery Rate (FDR) method by Benjamini, Krieger, and Yekutieli was employed, with additional Bonferroni correction applied by multiplying P-values by the total number of statistical tests (n = 38). Yearly trends in waiting times were analyzed using linear regression models, including interaction terms to assess sex-based differences over time. A Kaplan-Meier survival curve for time to cataract surgery was generated, with differences assessed using the log-rank test. A multivariate Cox regression model was constructed to identify predictors of waiting times, with independent variables including sex, age, ocular comorbidities (pseudoexfoliation syndrome, cornea guttata, macular disease, diabetes, and glaucoma), and regional differences. Supplementary analyses included stratification by visual acuity groups, categorizing waiting times by decimal visual acuity equivalents. For each stratum, mean waiting times were compared between sexes using unpaired t-tests with Welch correction. All statistical analyses were conducted using IBM SPSS Statistics (version 29, Armonk, NY), GraphPad Prism (version 10.0.2, San Diego, CA, USA), and R (R Core Team, Vienna, Austria, 2022), with relevant packages including dplyr, ggplot2, tidyr, knitr, survminer, and survival.

RESULTS

A total of 1,413,652 patients were included in the study, of whom 828,515 (59%) were female. Males had slightly better BCVA in the non-operated eye and were more likely to receive multifocal intraocular lenses (IOLs). Capsular tension rings were more commonly used, and postoperative endophthalmitis occurred more frequently in male patients, while pseudoexfoliations were more common among females. Detailed baseline characteristics are presented in Table 1.

The average waiting time from preoperative assessment to surgery was 64 days for females (standard deviation [SD] 126) and 60 days for males (SD 102). A Shapiro-Wilk test confirmed non-normal distribution in both groups (P < 0.001 for both males and females); thus, a Mann-Whitney U test was conducted, indicating a significant difference in waiting times between males and females (W = 2.51×10¹¹, P < 0.001).

Differences in waiting times between females and males were observed across all visual acuity groups of the surgery eye, with females consistently experiencing longer average waiting times. These groups, categorized by visual acuity (≤ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and ≥ 1.0 on the decimal scale, which is equivalent to ≤ 20/200, 20/100, 20/66, 20/50, 20/40, 20/33, 20/28, 20/25, 20/22, and ≥ 20/20 on the Snellen scale, and 1.0, 0.7, 0.52, 0.40, 0.30, 0.22, 0.15, 0.10, 0.05, and 0.0 on the LogMAR scale.), demonstrated statistically significant disparities. For instance, in the ≤ 0.1 group, females had an average waiting time of 63 days (SD 71), compared to 57 days (SD 66 days) for males, a difference of 7 days (SE < 1 day, P < 0.001). Similar differences were evident across all other groups, with statistical significance consistently retained after adjusting for multiple comparisons using FDR. Unpaired t-tests with Welch correction confirmed statistically significant differences between males and females in all groups, with all P values < 0.001. The magnitude of differences ranged from 2 days (SE 18, P < 0.001) in the BCVA 0.7 group, to 7 days (SE 18, P < 0.001) in the BCVA ≤ 0.1 group (Fig. 1). These findings highlight a consistent trend of longer waiting times for females across all levels of preoperative visual acuity.

Fig. 1

Comparison of mean waiting times for females (orange) and males (green) across best-corrected visual acuity (BCVA) strata. BCVA is reported on a decimal scale (e.g., Snellen 20/20 and LogMAR 0.00 correspond to 1.0, while Snellen 20/200 and LogMAR 1.00 correspond to 0.1). A) In all visual acuity groups, females had significantly longer mean waiting times than males (P < 0.001, unpaired t-tests with Welch correction). Asterisks denote statistically significant findings (q < Q after False Discovery Rate adjustment). B) Volcano plot illustrating q values (-log10 scale) against the magnitude of differences in mean waiting times between females and males. Points further from the origin indicate greater differences and stronger statistical significance. C) Line plot visualizing the mean waiting times for females and males across BCVA groups. BCVA refers to the best-corrected visual acuity recorded at the time of admission for cataract surgery. Error bars represent one standard deviation.

Similarly, regional differences in waiting times were also evident, with the largest discrepancy observed in Region 17 (mean difference: 9 days) and the smallest in Region 13 (mean difference: 1 day, Fig. 2). Females had significantly longer waiting times in all regions (unpaired t-tests with Welch correction, P < 0.001 for all comparisons, adjusted for multiple comparisons using FDR). A full list of regional designations is available in Supplementary Table 1.

Fig. 2

Average waiting time for females (orange) and males (green) across Swedish regions. The greatest discrepancy in waiting times was observed in Region 17 (9 days), while the smallest was in Region 13 (1 day). Asterisks denote statistically significant findings (q < Q after False Discovery Rate adjustment). The regions are highlighted on a map of Sweden, with shading representing the population in approximately corresponding areas.

For regression analyses, regions were categorized into four tiers based on the magnitude of waiting time differences between genders, with Tier 1 representing regions with the smallest gender differences and Tier 4 those with the largest.

When treating waiting time for cataract surgery as a time-to-event analysis, females experienced longer cataract-surgery-free periods than males, indicating a longer delay in undergoing surgery. At 30 days after admission, the estimated Kaplan-Meier cataract-surgery-free survival was 64.9% (95% CI 64.8–65.0) for females and 62.2% (95% CI 62.1–62.4) for males. At 60 days, the survival was 39.7% (95% CI 39.6–39.9) for females and 37.1% (95% CI 36.9–37.2) for males. By 90 days, the survival was 23.4% (95% CI 23.4–23.5) for females and 21.3% (95% CI 21.2–21.4) for males, and at 120 days, it declined to 13.7% (95% CI 13.6–13.7) for females and 12.1% (95% CI 12.1–12.2) for males (Fig. 3A).

Fig. 3

Cataract-Surgery-Free Survival and Trends in Cataract Waiting Times (2010–2022).

A) Kaplan-Meier curve of cataract-surgery-free survival stratified by sex, showing a significant difference (Log-rank P < 0.001). The median cataract-surgery-free survival was 43 days for males (95% confidence interval [CI]: 43–43) and 47 days for females (95% CI: 47–47). B) Annual mean waiting times from preoperative assessment to cataract surgery for females and males from 2010 to 2022, presented in months. Shaded bands indicate 95% CIs. Waiting times followed a U-shaped trend over the study period. Dashed lines represent linear regression fits, with a significant positive association between year and waiting time (P < 0.001; estimate: 0.3 days/year). The interaction term between year and sex was not significant (P = 0.29; estimate: 0.05 days/year), indicating no sex-related differences in the rate of change over time. Relative differences in waiting times between sexes remained stable throughout the study period. C) Annual mean difference in waiting times (in days) between females and males, calculated as the mean waiting time for females minus the mean waiting time for males. Error bars represent the standard deviation of the mean difference.

Multivariate Cox Regression

We performed a multivariate Cox regression analysis to investigate the effect of various factors on waiting time for cataract surgery (Table 2). The analyzed variables included sex (male vs. female), age, baseline visual acuity of the operated eye (BCVA), specific health conditions (presence of pseudoexfoliation, cornea guttata, diabetes, macular disease, and glaucoma), and region-specific waiting time tiers. All covariates, including patient sex, were found to be independent predictors of waiting time after applying Bonferroni adjustment to P values. Notably, diabetes (type I or II) emerged as a significant predictor of shorter waiting time (Hazard ratio: 0.88, 95% CI: 0.87–0.89).

Table 2

Multivariate Cox Regression: Predictors of Time to Cataract Surgery
Variable	B	S.E.	Wald Test	P*	Exp(B)	95% Confidence Interval
Sex (Male)	-0.064	0.003	608.7	< 0.001	0.938	0.934–0.943
Age^†	-0.007	< 0.001	2,708.2	< 0.001	0.993	0.992–0.993
BCVA operated eye	0.172	0.006	838.2	< 0.001	1.188	1.174–1.202
Pseudoexfoliations	0.077	0.005	257.5	< 0.001	1.080	1.070–1.091
Cornea Guttata	-0.032	0.008	14.9	< 0.001	0.968	0.952–0.984
Diabetes, type I or II	-0.127	0.006	407.0	< 0.001	0.881	0.870–0.892
Macular Disease, any type	0.02	0.004	29.5	< 0.001	1.020	1.013–1.027
Glaucoma, any type	-0.052	0.005	130.2	< 0.001	0.949	0.941–0.958
Region tier^‡	-0.125	0.001	10,144.3	< 0.001	0.883	0.881–0.885
*Bonferroni correction was applied to the P values to adjust for multiple comparisons. ^†Patient age at the time of admission for cataract surgery. ^‡Regions were classified into four tiers based on average waiting time for cataract surgery, with Tier 1 containing regions with the longest waiting time, and Tier 4 those with the shortest. BCVA, best corrected visual acuity. S.E., standard error.

Time Trends

An analysis of time trends in cataract surgery waiting times from 2010 to 2022 revealed fluctuating overall waiting times throughout the study period, forming a U-shaped trend. The period from 2020 to 2022 may have been influenced by the COVID-19 pandemic. In 2010, the average waiting time was approximately 74 days for females and 69 days for males. A linear regression model, including an interaction term to assess gender differences over time, showed a significant positive association between year and waiting time, with an estimated annual increase of < 1 day/0.01 months (P < 0.001). However, the interaction term between year and sex did not reach statistical significance (Estimate < 1 day, P = 0.29), indicating that the trend in waiting times was consistent across genders. Thus, while waiting times for cataract surgery varied over the study period, no significant change was observed in the relative difference between males and females (Fig. 3B, 3C).

DISCUSSION

Main Findings

This study confirms persistent, albeit small, sex-based differences in waiting times for cataract surgery in Sweden over a 13-year period, with female patients consistently experiencing longer delays than their male counterparts. Despite efforts to improve healthcare equity, this disparity has remained stable and statistically significant across the study period. Importantly, these differences are unlikely to be explained by clinical factors, such as visual acuity at the time of admission for surgery, age, or comorbidities, which were comparable between sexes or adjusted for in the analyses.

Cataract is typically a slowly progressive condition, and although the absolute differences of a few days in waiting times are small and unlikely to have a major impact on health or long-term well-being, they may reflect underlying systemic inequalities or biases that warrant further investigation. In 2004, the National Board of Health and Welfare (NBHW) identified differences in access to care for females and elderly patients as examples of discrimination.¹⁹ The persistent disparity observed suggests the need for targeted interventions to achieve more equitable access to surgery.

Contextualizing with Previous Studies

Our findings align with earlier research indicating sex-based disparities in waiting times for cataract surgery. A 2010–2011 study of Swedish patients reported similar patterns of longer waiting times for women.¹² Smirthwaite and colleagues reported, based on focus interviews with ophthalmologists, that females and males were regarded differently with respect to ascribed traits such as assertiveness and care-seeking behavior, and that their need for visual acuity in working life was perceived as distinct.²⁰

These disparities are not unique to Sweden; studies from other regions have reported sex-based differences in access to ophthalmic care, with women facing barriers to timely treatment even in high-resource settings.⁹ Such differences are often attributed to social, economic, or systemic factors rather than biological differences in disease burden or progression.^21,22

Factors Influencing Waiting Times

In addition to sex, other predictors of waiting time included age, home region, and specific comorbidities. Older patients tended to wait longer, potentially reflecting the prioritization of working-age individuals or the need to address comorbidities before surgery. Regional variations were notable, with differences likely driven by healthcare resource allocation, availability of surgeons, and logistical factors such as travel distance. Previous studies have also highlighted variations in complication rates of cataract surgery at regional, clinic, and even individual surgeon levels.²³

Although differences in surgical technique and complications between sexes were observed, these were minor and unlikely to account for the disparity in waiting times. For example, capsular tension rings and postoperative endophthalmitis were slightly more common in male patients, while pseudoexfoliation syndrome was more frequent among females. While statistically significant due to the large sample size, these differences are of limited clinical relevance.

Strengths and Limitations

A major strength of this study is its comprehensive dataset, encompassing over 1.4 million patients and covering approximately 93% of all cataract surgeries performed in Sweden during the study period. This extensive coverage ensures a robust representation of real-world clinical practice and reduces the risk of selection bias.

However, the study's retrospective registry-based design limits causal inferences. While we identified significant predictors of waiting time, the underlying reasons for sex-based disparities remain unclear.

Additionally, the accuracy of the findings relies on the quality of data entered into the Swedish National Cataract Register. Although previous audits have validated the register’s reliability, occasional inaccuracies in reporting cannot be excluded.¹⁵

Implications and Future Directions

The persistence of sex-based differences in waiting times for cataract surgery highlights the need for targeted interventions to address healthcare inequities. Potential strategies include improving referral practices, standardizing prioritization criteria, and ensuring adequate resource allocation across regions. Further research is needed to elucidate the root causes of these disparities, including qualitative studies to explore potential biases in clinical decision-making and patient preferences.

Finally, while the observed differences may not have a significant impact on clinical outcomes, they could contribute to perceptions of inequity and undermine trust in the healthcare system. Addressing even small disparities is essential for ensuring that healthcare delivery is both equitable and perceived as fair by all patients.

Conclusions

In conclusion, females in Sweden experienced slightly longer waiting times for cataract surgery than males during the period 2010–2022. This disparity was consistent across the study period and remained significant after adjusting for clinical and demographic factors. While the differences are unlikely to have major clinical implications, they highlight the need for continued efforts to achieve equitable access to ophthalmic care.

Data availability statement

Patient-level data analyzed in this study are available from the Swedish National Cataract Register (https://rcsyd.se/anslutna-register/nationella-kataraktregistret). Access to these data requires approval from the Swedish Ethical Review Authority and the Swedish National Cataract Register's record keeper. Requests for data can be submitted through the register’s website and must comply with Swedish regulations governing the use of healthcare data for research purposes.

Funding

Support for this study was provided to Gustav Stålhammar from:

Region Stockholm (RS-2019-1138)

The funding organization had no role in the design or conduct of this study.

Author contributions

Philip Jute: Conceptualization, Writing – Review & Editing. Gustav Stålhammar: Conceptualization, Methodology, Software, Formal Analysis, Investigation, Data curation, Writing – Original Draft, Visualization, Project administration, Funding acquisition.

Electronic Supplementary Material

Below is the link to the electronic supplementary material

Supplementary Material 1

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Table 1. Baseline Patient Characteristics
Variable	Females, n = 828,515	Males, n = 585,137	P*
Age, mean (SD)	74.5 (8.6)	74.3 (9.0)	< 0.001
BCVA operated eye^†, mean (SD)			< 0.001
Decimal scale	0.46 (0.22)	0.45 (0.23)
LogMAR	0.34 (0.21)	0.35 (0.22)
Snellen	20/44	20/45
BCVA non-operated eye^‡, mean (SD)			< 0.001
Decimal scale	0.86 (0.34)	0.89 (0.31)
LogMAR	0.07 (0.04)	0.05 (0.04)
Snellen	20/23	20/23
Surgery type, n (%)			< 0.001
Phaco. and IOL	822,193 (99.24)	579,420 (99.02)
Phaco. and ACL	532 (0.06)	284 (0.05)
Trab., phaco., and IOL	273 (0.03)	242 (0.04)
Other**	5517 (0.67)	5191 (0.89)
Lens material, n (%)			< 0.001
Hydrophobic acrylic	791,681 (95.55)	559,208 (95.57)
Hydrophilic acrylic	30,920 (3.73)	21,662 (3.70)
Patient left aphakic	1,670 (0.20)	1,323 (0.23)
Silicone	1,335 (0.16)	897 (0.15)
PMMA	219 (0.03)	136 (0.02)
Multifocal, material unspecified	131 (0.02)	125 (0.02)
PMMA HSM	26 (0.00)	12 (0.00)
Other	2,520 (0.30)	1,772 (0.30)
Not specified	13 (0.00)	2 (0.00)
Lens type, n (%)
Aspherical	65,805 (7.94)	43,203 (7.38)	< 0.001
Multifocal	16,337 (1.97)	13,670 (2.34)	< 0.001
Use of capsular tension rings, n (%)	15,207 (1.84)	15,925 (2.07)	< 0.001
Postoperative endophthalmitis, n (%)	131 (0.02)	154 (0.03)	< 0.001
Other systemic and ocular conditions, n (%)
Glaucoma, any type	70,398 (8.50)	53,113 (9.08)	< 0.001
Macular disease, any type	129,126 (15.59)	88,747 (15.17)	< 0.001
Pseudoexfoliations	86,697 (10.46)	47,472 (8.12)	< 0.001
Cornea Guttata	25,294 (3.05)	13,419 (2.29)	< 0.001
Diabetes, type I or II	26,713 (3.23)	32,663 (5.58)	< 0.001

*Mann-Whitney U test was used for continuous variables, and chi-square tests were used for categorical variables. Bonferroni correction was used to adjust P-values for multiple comparisons. ^†Eye planned for surgery, or the first eye operated if both were treated in the same session. ^‡Eye not planned for surgery, or the second eye operated if both were treated in the same session. **e.g., phacoemulsification (Phaco), intraocular lens (IOL), and simultaneous corneal surgery. ACL, anterior chamber lens; BCVA, best corrected visual acuity; HSM, heparin surface modified; IOL, intraocular lens; PMMA, polymethyl methacrylate; SD, standard deviation; Trab, trabeculectomy.

Table 1. Baseline Patient Characteristics
Variable	Females, n = 828,515	Males, n = 585,137	P*
Age, mean (SD)	74.5 (8.6)	74.3 (9.0)	< 0.001
BCVA operated eye^†, mean (SD)			< 0.001
Decimal scale	0.46 (0.22)	0.45 (0.23)
LogMAR	0.34 (0.21)	0.35 (0.22)
Snellen	20/44	20/45
BCVA non-operated eye^‡, mean (SD)			< 0.001
Decimal scale	0.86 (0.34)	0.89 (0.31)
LogMAR	0.07 (0.04)	0.05 (0.04)
Snellen	20/23	20/23
Surgery type, n (%)			< 0.001
Phaco. and IOL	822,193 (99.24)	579,420 (99.02)
Phaco. and ACL	532 (0.06)	284 (0.05)
Trab., phaco., and IOL	273 (0.03)	242 (0.04)
Other**	5517 (0.67)	5191 (0.89)
Lens material, n (%)			< 0.001
Hydrophobic acrylic	791,681 (95.55)	559,208 (95.57)
Hydrophilic acrylic	30,920 (3.73)	21,662 (3.70)
Patient left aphakic	1,670 (0.20)	1,323 (0.23)
Silicone	1,335 (0.16)	897 (0.15)
PMMA	219 (0.03)	136 (0.02)
Multifocal, material unspecified	131 (0.02)	125 (0.02)
PMMA HSM	26 (0.00)	12 (0.00)
Other	2,520 (0.30)	1,772 (0.30)
Not specified	13 (0.00)	2 (0.00)
Lens shape, n (%)
Aspherical	65,805 (7.94)	43,203 (7.38)	< 0.001
Multifocal	16,337 (1.97)	13,670 (2.34)	< 0.001
Use of capsular tension rings, n (%)	15,207 (1.84)	15,925 (2.07)	< 0.001
Postoperative endophthalmitis, n (%)	131 (0.02)	154 (0.03)	< 0.001
Other systemic and ocular conditions, n (%)
Glaucoma, any type	70,398 (8.50)	53,113 (9.08)	< 0.001
Disease of the macula, any type	129,126 (15.59)	88,747 (15.17)	< 0.001
Pseudoexfoliations	86,697 (10.46)	47,472 (8.12)	< 0.001
Cornea Guttata	25,294 (3.05)	13,419 (2.29)	< 0.001
Diabetes, type I or II	26,713 (3.23)	32,663 (5.58)	< 0.001

Table 2. Multivariate Cox Regression: Predictors of Time to Cataract Surgery

Variable	B	S.E.	Wald Test	P*	Exp(B)	95% Confidence Interval
Sex (Male)	-0.064	0.003	608.7	< 0.001	0.938	0.934–0.943
Age^†	-0.007	< 0.001	2,708.2	< 0.001	0.993	0.992–0.993
BCVA operated eye	0.172	0.006	838.2	< 0.001	1.188	1.174–1.202
Pseudoexfoliations	0.077	0.005	257.5	< 0.001	1.080	1.070–1.091
Cornea Guttata	-0.032	0.008	14.9	< 0.001	0.968	0.952–0.984
Diabetes, type I or II	-0.127	0.006	407.0	< 0.001	0.881	0.870–0.892
Macular Disease, any type	0.02	0.004	29.5	< 0.001	1.020	1.013–1.027
Glaucoma, any type	-0.052	0.005	130.2	< 0.001	0.949	0.941–0.958
Region tier^‡	-0.125	0.001	10,144.3	< 0.001	0.883	0.881–0.885

*Bonferroni correction was applied to the P values to adjust for multiple comparisons. ^†Patient age at the time of admission for cataract surgery. ^‡Regions were classified into four tiers based on average waiting time for cataract surgery, with Tier 1 containing regions with the longest waiting time, and Tier 4 those with the shortest. BCVA, best corrected visual acuity. S.E., standard error.

Yes

Abstract

BackgroundSex-based disparities in healthcare access and outcomes remain a challenge. Understanding differences in waiting times for cataract surgery between males and females can reveal inequities in care delivery.MethodsThis nationwide retrospective cohort study used data from the Swedish National Cataract Register, which covers >93% of all cataract surgeries in Sweden. A total of 1,413,652 patients aged >40 years who underwent first-eye cataract surgery between 2010 and 2022 were included. Exclusions were made for patients with waiting times >24 months, those residing outside Sweden, and those with missing sex data. The primary outcome was waiting time, defined as the interval between preoperative assessment and surgery. Secondary analyses included stratification by visual acuity, regional variations, and the influence of demographic and clinical factors.ResultsThe mean waiting time was 64 days for females (SD 126) and 60 days for males (SD 102), with a significant difference (P<0.001). This disparity persisted across all visual acuity strata and regions. Multivariate Cox regression identified female sex, older age, specific comorbidities, and residence region as significant predictors of longer waiting times. Differences in comorbidities, including higher rates of pseudoexfoliation syndrome in females and endophthalmitis in males, were observed. Despite fluctuations in overall waiting times, the sex-based disparity remained consistent over the study period.ConclusionsPersistent sex-based differences in waiting times for cataract surgery were identified in Sweden over 13 years. While small and unlikely to affect clinical outcomes, these differences highlight systemic inequities that merit further investigation and intervention to ensure equitable access to care.