Open Access
Public Health  |   May 2024
Impact of Physical Activity Frequency, Duration, and Intensity on Senile Cataract Risk: A Mendelian Randomization Study
Author Affiliations & Notes
  • Yuze Mi
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
    State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Qinnan Zhu
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
    State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Yuxiang Chen
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Xinni Zheng
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
    State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Minghui Wan
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
    State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Yipao Li
    National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
    State Key Laboratory of Ophthalmology, Optometry and Vision Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
  • Correspondence: Yipao Li, National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, 270 Xueyuan Xi Rd, Wenzhou, Zhejiang 325035, P.R. China. e-mail: liyipao@eye.ac.cn 
  • Footnotes
     YM, QZ, and YC contributed equally to the work presented here and should be regarded as equivalent authors.
Translational Vision Science & Technology May 2024, Vol.13, 26. doi:https://doi.org/10.1167/tvst.13.5.26
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      Yuze Mi, Qinnan Zhu, Yuxiang Chen, Xinni Zheng, Minghui Wan, Yipao Li; Impact of Physical Activity Frequency, Duration, and Intensity on Senile Cataract Risk: A Mendelian Randomization Study. Trans. Vis. Sci. Tech. 2024;13(5):26. https://doi.org/10.1167/tvst.13.5.26.

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Abstract

Purpose: We aimed to determine the causal effects of physical activities with different frequencies, durations, and intensities on the risk of senile cataracts using Mendelian randomization (MR).

Methods: A bidirectional two-sample MR approach was used to determine the association between physical activity and senile cataract risk. Our primary analysis used the inverse variance weighted method, and secondary analyses included MR-Egger regression, MR-PRESSO, and Cochran's Q statistic to evaluate heterogeneity and pleiotropy. Causal estimates were presented as odds ratios (ORs) with 95% confidence intervals (95% CIs).

Results: Genetically predicted moderate physical activity ≥ 10 min/wk (OR = 0.765, 95% CI = 0.627–0.936, P = 8.73E-03), vigorous physical activity ≥ 10 min/wk (OR = 0.691, 95% CI = 0.521–0.917, P = 1.04E-02), moderate-to-vigorous physical activity levels (OR = 0.552, 95% CI = 0.369–0.823, P = 3.75E-03), and overall acceleration average (OR = 0.952, 95% CI = 0.926–0.978, P = 3.80E-04) were associated with a decreased risk of senile cataract while walking ≥ 10 min/wk (OR = 0.972, 95% CI = 0.741–1.275, P = 8.36E-01) had no significant correlation. The reverse MR analysis showed no reversal causality from senile cataract to physical activity except for walking ≥ 10 min/wk (OR = 0.951, 95% CI = 0.923–0.979, P = 7.30E-04).

Conclusions: Our findings suggest that moderate to vigorous physical activity with higher frequency and longer duration will causally reduce the risk of senile cataracts, and there is no reverse causal relationship.

Translational Relevance: These findings underscore the potential of incorporating physical activity into preventive health strategies for senile cataracts.

Introduction
Cataracts, characterized by lens opacity, are among the most common causes of vision loss in older people.1 It is estimated that cataract affects 95 million people globally, leading to blindness in over 15 million individuals aged 50 years and older.2 Senile cataracts (SC), also known as age-related cataracts, commonly occur as a consequence of aging.3 They remain the leading cause of blindness in middle- and low-income countries.4 By 2020, the number of individuals blinded by age-related cataracts has been estimated to reach 13.4 million (accounting for 34.8% of blindness).5 At present, SC surgery remains the only definitive treatment for SC. Although surgical techniques continuously improve and yield significant benefits, numerous challenges persist, including variability in individual outcomes, increased surgical contraindications, complications, and a substantial economic burden.6,7 Given the limitations of surgical treatments in fully addressing patient needs, developing preventive measures is imperative. 
Physical activity (PA) is widely recognized as essential for health improvement and reducing the risk of non-genetic diseases.8 Regular and appropriate PA is associated with multiple health benefits,9 including reduced oxidative stress, reduced C-reactive protein levels, and increased high-density lipoprotein (HDL) formation, all vital for ocular health. Observational studies suggest high levels of PA may correlate with a decreased risk of SC. Thus, PA is identified as a critical factor in SC prevention, although findings on its association with SC vary. For instance, one study showed that high total PA, especially in the long term, was associated with a decreased risk of SC,10 whereas another study reported that SC was statistically independent of PA.11 A previous study observed a significant correlation between PA and SC in 15 to 69-year-olds living in Spain, but the specific relationship between activity intensity, frequency, or duration and SC had not been revealed.12 However, these studies are limited by potential residual confounding and reverse causality, hindering definitive causal inferences about the PA-SC risk relationship. 
Mendelian randomization (MR) studies are increasingly used to assess causal relationships between exposures and outcomes, utilizing genetic variants as instrumental variables (IVs).13,14 This approach leverages the random distribution of genetic variations, offering resilience to confounding factors and reverse causality, as these variants are assorted at conception and precede the disease's onset.15 Recognizing the advantages of MR, we used the MR analysis on two-sample genomewide association study (GWAS) data to elucidate the causal relationship between PA and SC risk. To mitigate the potential impact of SC on the causal PA, we incorporated a bidirectional approach to test the effect of PA on SC, which can be conducted with PA as (i) the exposure to assess whether it has a causal effect on SC, and as (ii) the outcome to assess whether SC has a causal effect on PA. 
Methods
Study Design
This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines, as detailed in the supplementary material.16 Based on GWAS summary statistics, the research aimed to conduct a two-sample MR analysis, exploring the causal link between PA and SC. In MR studies, the IV must satisfy three critical criteria,14 as outlined in Fig. 1: (1) a significant associati`on of the genetic variant with the exposure; (2) absence of correlation between the genetic variant and confounders related to the outcome; and (3) impact of the genetic variant on the outcome solely via the exposure, without other pathways. Ethical approval was not necessary for this study, given its exclusive reliance on accessible public GWAS summary statistics. 
Figure 1.
 
Design flow chart for the Mendelian randomization study. SNP, single nucleotide polymorphism; WM, weighted median; MR, Mendelian randomization; IV, instrumental variable.
Figure 1.
 
Design flow chart for the Mendelian randomization study. SNP, single nucleotide polymorphism; WM, weighted median; MR, Mendelian randomization; IV, instrumental variable.
GWAS Data for Physical Activity
PA summary statistics were obtained from a recent GWAS within the UK Biobank cohort,17 involving approximately 400,000 individuals aged 40 to 69 years.18,19 Self-reported levels of PA were assessed using a touchscreen questionnaire, similar to the International Physical Activity Questionnaire, and included three categories: light, moderate, and vigorous PA.20 Specifically, participants were queried regarding their engagement in light PA with the following question: “In a typical week, how many days did you engage in walking for at least 10 minutes at a time, including walking at work, during commutes, and for sports or leisure activities?” “Walking ≥ 10 min/wk” was used as an abbreviation for “number of days per week of walking for 10 or more minutes.” A total of 454,783 participants were included in this category. For moderate PA, participants were asked: “In a typical week, how many days did you engage in moderate physical activity for 10 minutes or more, such as carrying light loads or cycling at a normal pace (excluding walking)?” “MPA ≥ 10 min/wk” was used to represent the abbreviation of “number of days per week of moderate physical activity for 10 or more minutes.” This category comprised 440,266 participants. In the case of vigorous PA, participants were queried as follows: “In a typical week, how many days did you engage in vigorous physical activity for 10 minutes or more, such as activities that induce sweating or heavy breathing, like fast cycling, aerobics, or heavy lifting?” “VPA ≥ 10 min/wk” was used to represent the abbreviation of “number of days per week of vigorous physical activity for 10 or more minutes.” A total of 440,512 participants were included in this category.18 
Participants who reported engaging in these activities on at least 1 day were further queried about the duration of their activities, “How many minutes did you typically spend engaging in moderate/vigorous activities on a typical day?” Participants were instructed to consider activities performed during work, leisure, travel, and around the house. Exclusions were made for individuals who selected “prefer not to answer” or “do not know” for these questions, as well as those who reported being unable to walk or individuals reporting more than 16 hours of either moderate PA or vigorous PA per day. Participants reporting more than 3 hours per day of moderate PA or vigorous PA were adjusted to 3 hours, following the recommended procedures. This study also analyzed the duration of PA, represented by moderate-to-vigorous physical activity (MVPA). The MVPA was computed by summing the total minutes per week of moderate PA multiplied by four and the total minutes per week of vigorous PA multiplied by eight, corresponding to their respective metabolic equivalents, as previously outlined.18,21 It was construed as an activity performed continuously,22 with 377,234 participants in this category. In a separate GWAS involving 377,234 individuals of European descent, researchers used Axivity AX3 wrist-worn triaxial accelerometers to calculate the PA level and defined a measure called the overall acceleration average (OAA).23,24 
Data Sources for Senile Cataract
Comprehensive information on participant data, genotyping methods, and analysis protocols is accessible on the FinnGen website (https://www.finngen.fi/en/). This dataset includes 406,781 individuals of European ancestry, with 65,235 cases and 341,546 controls.25 Characterized by lens thickening and loss of transparency, SC's multifactorial etiology is closely linked with aging. According to the International Classification of Diseases, Tenth Revision, SC is classified under the H25.0 code within the cataract category. 
Genetic Instrument Selection
A rigorous filtering process was implemented to ensure the quality of single-nucleotide polymorphisms (SNPs) before conducting the MR analysis. Initially, we selected SNPs significantly associated with PA with genome-wide significance (P < 5E-08). Linkage disequilibrium (LD) among SNPs was assessed using the 1000 Genomes LD reference panel and the PLINK clumping method.26 SNPs with LD (r2 > 0.001) in a clump window under 10 kilobases were excluded.2729 Additionally, the Phenoscanner was used to identify instrumental variables linked to potential confounders or outcomes, with the relevant SNPs extracted from the outcome GWAS data.30 The “harmonize” function was used to align and remove palindrome and incompatible SNPs. Finally, the F-statistic (F = β2/se2) was calculated,31 with the analysis yielding a value significantly above 10 indicating a strong IV.32,33 Within MR, the R2 value indicates how well instrumental variables explain exposure and the F-value assesses the strength of these variables. The formulas for R2 and general F are provided below34,35:  
\begin{eqnarray*} R^2 &\;=& \Sigma \left[\frac{2 \times (1 - MAF) \times MAF \times \beta^2}{(SE^2 \times N)}\right]\\ F &\;=& \frac{(N - k - 1)R^2}{k(1 - R^2)}.\end{eqnarray*}
 
Mendelian Randomization Analysis
All statistical tests were 2-sided, and analyses were performed using TwoSampleMR, Mendelian Randomization, and MR-PRESSO packages in R software (version 4.4.1). The inverse variance weighted (IVW) approach served as the primary statistical method.26,36 Additional analyses encompassed the weighted median,37 MR-Egger,34,38 simple mode, and weighted mode. Several sensitivity analyses were conducted to evaluate the robustness of the results. The MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test39 and MR-Egger regression were used to assess potential horizontal pleiotropy. A non-zero MR-Egger regression intercept signifies pleiotropy.38 MR-PRESSO was used to identify and correct significant outliers indicative of horizontal pleiotropy. Cochrane's Q test statistic was utilized to assess IV heterogeneity, with P < 0.05 denoting substantial variation.39,40 We also performed a “leave one out” analysis to investigate whether the causal relationship between exposure and outcome was influenced by a single SNP.41 Causal estimates were presented as odds ratios (ORs) with 95% confidence intervals (CIs). The Bonferroni correction was applied to address multiple testing across five MR methods.42,43 This involved calculating a corrected P threshold (0.05 divided by the number of tests), assuming the independence of each test. Exposures with MR analysis results falling below the Bonferroni correction threshold for multiple testing (P < 0.01, i.e. 0.05/5 tested exposures) were considered to have strong evidence of association with SC. Results with P values greater than 0.0125 but less than 0.05 were suggestive of statistical significance in the univariable MR analysis.43 
Reverse MR Analysis
To investigate whether SC has a causal impact on PA, we conducted a reverse MR analysis, with SC as the exposure and PA as the outcome. This analysis utilized SNPs associated with SC as IVs. A nonsignificant result in reverse MR analysis between SC and PA could exclude the possibility of SC causally leading to PA, thus strengthening the reliability of evidence regarding the causal effect of PA on SC risk. This contributes to a more comprehensive understanding of the potential effects of PA on SC risk. 
Results
Causal Relationship Between PA and SC
When treating PA as the exposure, our findings revealed that MPA ≥ 10 min/wk, VPA ≥ 10 min/wk, MVPA, and OAA were significantly associated with a decreased risk of SC after controlling known confounders, such as drinking and smoking, by excluding the related SNPs from the analysis. In total, we selected 14 SNPs for walking ≥ 10 min/wk, 11 SNPs for MPA ≥ 10 min/wk, 9 SNPs for VPA ≥ 10 min/wk, 16 SNPs for MVPA, and 7 SNPs for OAA as IVs. The primary data analyzed through MR is summarized in Figure 2. Detailed information regarding these 57 genetic variants can be found in Supplementary Tables S1S5. MR analysis using the IVW method showed no significant association between walking ≥ 10 min/wk and SC risk (OR = 0.972, 95% CI = 0.741–1.275, P = 8.36E-01). However, it also indicated that MPA ≥ 10 min/wk (IVW: OR = 0.765, 95% CI = 0.627–0.936, P = 8.73E-03) and VPA ≥ 10 min/wk (IVW: OR = 0.691, 95% CI = 0.521–0.917, P = 1.04E-02) may be potential factors in preventing SC. MVPA (IVW: OR = 0.552, 95% CI = 0.369–0.823, P = 3.75E-03) were negatively correlated with SC risk, revealing that continuous moderate and high intensity of PA may be more effective in preventing SC. We also successfully established a causal link between OAA and a diminished risk of SC (OR = 0.952, 95% CI = 0.926–0.978, P = 3.80E-04). Comprehensive MR data and the forest plots regarding the association between PA and the risk of SC are presented in Figure 2. Despite the P values of MR-Egger, the weighted median, simple mode, and weighted mode assessment results possibly exceeding 0.05, the OR values remained in line with the IVW trend, suggesting the IVW estimates to be credible. Supplementary Figure S1 provides scatter plots to represent the causal relationship between PA and SC risk visually. 
Figure 2.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of physical activity on senile cataract. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted, Walking ≥ 10 min/wk: number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Figure 2.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of physical activity on senile cataract. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted, Walking ≥ 10 min/wk: number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Causal Relationship Between SC and PA
According to the same screening principles and methods, a total of 36 SNPs related to SC were obtained (Supplementary Table S6S10). Analyses conducted using the IVW indicated that there was no genetically predicted causal effect of SC on VPA ≥ 10 min/wk (IVW: OR = 1.002, 95% CI = 0.967–1.038, P = 9.22E-01), VPA ≥ 10 min/wk (IVW: OR = 0.981, 95% CI = 0.954–1.008, P = 1.62E-01), MVPA (IVW: OR = 0.993, 95% CI = 0.974–1.013, P = 4.89E-01), or OAA (OR = 0.952, 95% CI = 0.926–0.978, P = 3.80E-04). However, SC was causally associated with a lower probability of walking ≥ 10 min/wk (IVW: OR = 0.951, 95% CI = 0.923–0.979, P = 7.30E-04). No remarkable horizontal pleiotropy and heterogeneity were discovered using sensitivity analysis. The essential MR data and the forest plots between SC and PA are shown in Figure 3. The scatter plots of the causal effect of SC on PA are shown in Supplementary Figure S3
Figure 3.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of senile cataract on physical activity. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted; Walking ≥ 10 min/wk, number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Figure 3.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of senile cataract on physical activity. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted; Walking ≥ 10 min/wk, number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Sensitivity Analyses
Neither direction of MR analysis exhibited significant horizontal pleiotropy or heterogeneity. Figures 2 and 3 enumerate the main results of all tests of heterogeneity and pleiotropy of bidirectional analyses. No significant heterogeneity was detected according to Cochran's Q test (P > 0.05). No evidence of pleiotropy was found in the MR-Egger and MR-PRESSO globe tests (P > 0.05). Moreover, the leave-one-out plots are shown in Supplementary Figures S2 and S4. Furthermore, our bidirectional MR analyses did not identify any outlier or pleiotropic SNPs. 
Discussion
To our knowledge, this study is the first to explore the causal relationship between genetically proxied PA and SC risk using MR analysis within a European cohort. Specifically, PA was measured using subjective self-reports and objective biometric indicators and classified into different categories based on intensity, frequency, and duration: walking ≥ 10 min/wk, MPA ≥ 10 min/wk, VPA ≥ 10 min/wk, MVPA, and OAA, ensuring the measurement accuracy, reliability, and comprehensiveness. Complementary methods for pleiotropy and sensitivity analysis were utilized to ensure the robustness of results. Our results showed that PA causally led to a reduced risk of SC, with MVPA showing the strongest effect, followed by VPA ≥ 10 min/wk, MPA ≥ 10 min/wk, and OAA. Conversely, walking ≥ 10 min/wk showed no effect on SC risk. Furthermore, our reverse causality analysis revealed that SC (as an exposure) only significantly negatively affected walking ≥ 10 min/wk. 
Our findings suggest that moderate and high-intensity PA may have a preventive effect on SC, which is consistent with the abundant evidence showing a significant relationship between PA and SC risk. For instance, Klein et al.44 found that people with continuous, sweating PA thrice weekly had a lower SC risk than those with a sedentary lifestyle. Sweating PA in Klein et al.’s 44 study falls into the category of MPA ≥ 10 min/wk in our study, further supporting our hypothesis that moderate and high intensity of PA can decrease the risk of SC. Moreover, the different ORs between different levels of PA and SC risk revealed that the higher the exercise frequency, the lower the risk of SC. In the questionnaire survey of light, moderate, and vigorous PA, we set 10 min/week as the PA threshold, but the effect of PA with different durations on SC risk differs.45,46 In a study of German people, participants who kept 2.5 hours of MVPA/week gained more positive health outcomes than those who spent less than 5 minutes in MVPA.47 In our study, we also considered the causality between the duration of PA and SC. We focused on MVPA, assessed by metabolic equivalents, and included the intensity and duration of PA to analyze the genetically predicted relationship between PA and SC more thoroughly. A similar conclusion was reached by a Spanish study indicating that performing fewer than 600 MET-minutes of PA per week was associated with 32.4% increased odds of SC.12,48,49 Meanwhile, another study showed that bicycling more than 60 minutes/day (compared with hardly ever) and heavy manual labor (compared with mostly sitting) were associated with 12% and 16% decreased risk of SC, respectively, further supporting our analysis.10 Continuous PA promotes metabolism, further decreasing SC risk.50 Recognizing the potential bias associated with self-reported data on PA, we used the accelerometer-based PA measurement OAA to substantiate our research findings further, and the results remained consistent, showing a causally preventive effect of OAA in SC. In summary, our findings suggest that moderate and high-intensity PA with prolonged duration is beneficial to preventing SC. 
What is more, in reverse causality analysis, we found that when SC was considered as exposure, SC had no causal effects on MPA ≥ 10 min/wk, VPA ≥ 10 min/wk, MVPA, or OAA, but had a negative effect on walking ≥ 10 min/wk. Previous cross-sectional studies showed that people with poor vision were less likely to engage in PA and more likely to be sedentary.51,52 However, our MR analysis failed to establish a robust correlation between genetic predisposition to SC and PA, indicating that more MR research is needed to test whether visual impairment may lead to reduced engagement in moderate to high-intensity PA. 
The preventive effect of PA on SC may be explained by multiple mechanisms. The lens is highly impressionable to oxidative damage, potentially leading to opacities.5355 PA can potentially alleviate oxidative stress by activating antioxidant enzymes.53,56 Furthermore, PA can enhance the formation of HDL,57 which is vital in transporting lipophilic antioxidants. Elevated levels of HDL may thus facilitate the transport of more antioxidants from the plasma to the lens,58,59 effectively preventing oxidative damage and inflammation within the human eye lens.60 PA may also inhibit concentrations of circulating C-reactive protein, an inflammatory marker associated with a higher risk of SC. Additionally, physical activity can help control weight, maintain a healthy body mass index (BMI), and prevent chronic diseases caused by obesity, such as diabetes and hypertension, which are also associated with cataract development.61,62 Therefore, by actively engaging in PA, people can reduce the risk of developing SC. Furthermore, our study showed that different intensities and durations of PA had varying effects on SC, with higher PA intensity and longer duration associated with a lower risk of SC. This finding was consistent with previous studies reporting a strengthened protective effect of increased levels of PA in SC and may be explained by the dose-response relationship between PA and SC-preventive metabolism indicators, such as antioxidant enzymes, HDL, and C-reactive protein.10,63,64 Our findings carry significant public health implications and offer a novel genetic perspective on SC prevention by proposing a modifiable lifestyle intervention approach — PA. Specifically, increasing the frequency and duration of moderate and vigorous intensity PA may achieve the best effect in lowering the risk of SC, thereby reducing the likelihood of needing cataract surgery and related medical expenses and improving overall health. Therefore, promoting PA as a preventive measure for SC can bring dual benefits: promoting individuals’ health and reducing socioeconomic burdens to society. 
The present study has several strengths. First, we used MR analysis, which is less vulnerable to non-differential measurement mistakes, reverse causation, and confounding than observational research, thus strengthening the validity of our findings. Second, we utilized a large sample size to ensure sufficient power to detect statistical significance. Third, this study featured a comprehensive analysis of the frequency and duration of exercise grounded in existing observational studies and combined subjective and objective measurements, thus ensuring reliability and comprehensiveness. Finally, the adoption of a bidirectional causal analysis approach to examine the relationship between PA and SC risk provides a more holistic perspective of the interconnectedness between PA and SC. 
Nevertheless, several limitations warrant discussion. First, our bidirectional MR was based on the GWAS data focusing solely on European ancestry populations, which may limit the broader applicability of our findings to other populations, who may have different causes of visual impairment.65,66 For instance, whereas age-related macular degeneration is the primary cause of blindness in European populations, SC is a leading cause in Black populations.67 Future studies should test our findings in more diverse populations. Second, although SC occurs more commonly after the age of 50 years, the mean age at the first event for SC in our study was 71.91 years old, with only 1.79% of the affected population being under 50 years old, which hinders us from conducting age-stratified analysis based on the age of 50 years. Future studies should consider recruiting more young SC samples to explore the association between PA and SC stratified by the age of 50 years. Third, cases of SC were obtained from FinnGen using various data collection methods yet defined solely based on International Classification of Diseases, Tenth Revision (ICD-10), which may result in an underestimate of the SC occurrence. Future studies should consider using more inclusive definitions to identify SC cases to get a more accurate incidence estimate. Fourth, our study failed to reveal the relationships between PA and specific subtypes of SC (namely cortical, nuclear, and posterior subcapsular cataracts) which may present with different clinical symptoms. This warrants further research in the future. Finally, our study lacks replication due to its reliance on the GWAS data and a lack of validation sample, as there are no other publicly available data that satisfy the assumptions of MR, which may limit the interpretation of our study findings. However, our study still provides important hints to unveil the causal relationship between PA and SC and paves the way for future research when more public MR data are available. 
Conclusions
This bidirectional MR study suggests that MPA ≥ 10 min/wk, VPA ≥ 10 min/wk, MVPA, and OAA are causally associated with a decreased risk of SC while walking ≥ 10 min/wk did not show a significant association with SC risk. In reverse MR analysis, SC was only causally associated with a lower probability of walking ≥ 10 min/wk. Our findings suggest that moderate and vigorous intensity PA with higher frequency and longer duration could be effectively implemented in the prevention and management of SC. 
Acknowledgments
The authors thank the participants and investigators of the FinnGen study.25 
Supported by the Foundation of Wenzhou Science & Technology Bureau (Grant no. Y20210997). 
The data that supports the finding of this work is available in the UK Biobank at https://www.ukbiobank.ac.uk/ and the recently published article at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195860/. These data were derived from the IEU OpenGWAS Project at https://gwas.mrcieu.ac.uk/
Disclosure: Y. Mi, None; Q. Zhu, None; Y. Chen, None; X. Zheng, None; M. Wan, None; Y. Li, None 
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Figure 1.
 
Design flow chart for the Mendelian randomization study. SNP, single nucleotide polymorphism; WM, weighted median; MR, Mendelian randomization; IV, instrumental variable.
Figure 1.
 
Design flow chart for the Mendelian randomization study. SNP, single nucleotide polymorphism; WM, weighted median; MR, Mendelian randomization; IV, instrumental variable.
Figure 2.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of physical activity on senile cataract. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted, Walking ≥ 10 min/wk: number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Figure 2.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of physical activity on senile cataract. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted, Walking ≥ 10 min/wk: number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Figure 3.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of senile cataract on physical activity. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted; Walking ≥ 10 min/wk, number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
Figure 3.
 
MR estimates, heterogeneity, and pleiotropy analysis for the causal effect of senile cataract on physical activity. MR, Mendelian randomization; OR, odds ratio; CI, confidence interval; IVW, inverse variance weighted; Walking ≥ 10 min/wk, number of days per week walked for 10 or more minutes; MPA ≥ 10 min/wk, number of days per week of moderate physical activity for 10 or more minutes; VPA ≥ 10 min/wk, number of days per week of vigorous physical activity for 10 or more minutes; MVPA, moderate-to-vigorous physical activity levels; OAA, overall acceleration average.
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