Nearly 570 million people worldwide suffer from visual impairment, low vision, or blindness, of which an estimated 80% is attributed to preventable causes (1). Glaucoma is the second leading cause of blindness and has led to blindness in 8 million people (2,3). It is predicted that by 2020, 80 million additional individuals will be diagnosed with glaucoma (2). This acquired optic neuropathy is characterized by the thinning of the neuroretinal rim of the optic nerve and the enlargement of the optic nerve cup.
Although intraocular pressure (IOP) is the primary modifiable risk factor for glaucoma, other risk factors include high myopia (nearsightedness); age; race, especially African Americans and Hispanics; diastolic diffusion pressure; family history; thin central cornea; inflammation; low levels of physical activity; high blood pressure in older adults; refractive error; optic disc diameter; and possibly cardiovascular disease (2,4–9).
Physical activity has been studied as a possible treatment for elevated IOP. Most interventions recommend exercise for glaucoma patients, but no specific recommendations have been established (10). Single bouts of light, moderate, and vigorous physical activity in healthy and glaucoma patients reduced IOP (11). Reductions were greater with higher exercise intensity and in glaucoma patients (11). A recent review of physical activity and IOP showed clear benefits of acute exercise and an inverse relationship between physical fitness and IOP (10,12). Although chronic exercise lowers resting IOP, long-term data on the effects of regular exercise in glaucoma patients is lacking (10). Observational data in a cohort of active male runners suggest that longer daily running distance and 10-km race performance, as an indirect measure of fitness, may be associated with lower risk for developing glaucoma (13). More epidemiological research may bring clarity to the necessary duration, intensity, and frequency of physical activity needed to reduce glaucoma risk. Physical activity levels measured by a week of accelerometer data were inversely associated with glaucomatous visual field loss in a study of adults 60–80 yr old (14). Furthermore, glaucoma patients may have impaired balance, higher rates of falls, and slower walking speeds, which could partially explain the decreased physical activity (14).
At present, there is limited epidemiological evidence exploring the associations of physical activity and cardiorespiratory fitness (hereafter fitness) with glaucoma. Therefore, the objective of this study is to evaluate the potential associations of physical activity and fitness with incident glaucoma while controlling for potential confounders, including lifestyle and health factors. We included participants 40 yr or older in this study because there are few cases of glaucoma in younger adults (8).
Participants were men and women between the ages of 40 and 81 yr old seen for preventative medical examinations at the Cooper Clinic in Dallas, Texas, between 1987 and 2005 and were enrolled in the Aerobics Center Longitudinal Study. About two thirds (69%) of participants were non-Hispanic Whites from middle-to-upper socioeconomic status. Among 9890 participants ≥40 yr old with at least 1 yr of follow-up, we excluded 108 individuals reporting glaucoma at baseline. A total of 263 individuals not achieving at least 85% of their age-predicted maximal heart rate (220 minus age in years) on the treadmill test were also additionally excluded for an accurate measure of fitness, resulting in 9519 individuals as the final study sample (19% women). All procedures involving human participants were approved by the Cooper Institute Institutional Review Board. All participants provided written informed consent for the baseline clinical examination and follow-up study.
All participants completed a comprehensive medical questionnaire, which consisted of demographic questions, lifestyle habits, past and present chronic disease history, and a clinical examination by a physician. Blood chemistries were analyzed after at least 12 h of fasting with automated bioassays in the Cooper Clinic Laboratory. Resting blood pressure was measured following standard auscultatory methods after being seated for at least 5 min (15). Body mass index was calculated as measured weight in kilograms divided by the square of measured height in meters. Smoking status and alcohol consumption were ascertained through a standardized medical questionnaire.
Participants reported the presence or absence of physician-diagnosed glaucoma on their medical history questionnaire. This definition was used for both excluding participants with glaucoma at baseline and determining incident glaucoma during the follow-up.
Self-reported history of physician-diagnosed hypertension, hypercholesterolemia, diabetes, cardiovascular disease (myocardial infarction and stroke), and cancer were reported on the medical history questionnaire. ECG was measured at rest and with exercise, and abnormal ECG response included rhythm and conduction disturbances and ischemic ST-T wave abnormalities. These conditions were then confirmed by the residing physician at the Cooper Clinic at baseline and follow-up examinations.
Physical activity was calculated from self-reported leisure time or recreational activities during the past 3 months, which was formerly validated (16). METs were assigned to activities (17), multiplied by frequency (number of times per week) and duration (number of minutes per workout), and summed to determine MET-minutes per week, the principal metric used in the 2008 Physical Activity Guidelines for Americans (18). When walking, jogging, running, treadmill exercise, and cycling were indicated, participants were then asked to report speed (e.g., average time per mile). Participants were grouped into three physical activity categories: inactive (0 MET·min·wk−1), insufficient (<500 MET·min·wk−1), and recommended (≥500 MET·min·wk−1), which is equivalent to the physical activity guidelines of 150 min of moderate-intensity or 75 min of vigorous-intensity aerobic activity per week, or an equivalent combination of both.
Baseline fitness, taken at the time of enrollment, was measured by maximal treadmill test (19). The protocol began at 0% elevation and a speed of 88 m·min−1. The grade was increased to 2% at 1 min and 1% per minute until 25 min. After 25 min, the speed was increased by 5.4 m·min−1 without grade change. The test terminated when the individual reached exhaustion or stopped by the supervising physician for medical reasons. Participants not reaching 85% of their age-predicted maximal heart rate were excluded from the current analysis (2.7% of all study participants) because such a threshold is needed for an accurate measure of fitness. Participants were divided into tertiles (low, middle, and high) based on the overall age- and sex-specific fitness of the current cohort because no consensus cut points for fitness classification exist.
Differences in groups at baseline (Table 1) were examined by using χ2, ANOVA, and t-tests where appropriate. Cox proportional hazard regression was used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of developing glaucoma across physical activity and fitness levels at baseline. Follow-up time was computed from the difference between the date of baseline examination and the first follow-up event of glaucoma or the last clinical examination through 2005 for noncases. Cox regression models included physical activity category (inactive, insufficient, and recommended), fitness (low, middle, and high), age (yr), sex, race (white, black, others, and not reported), examination year, smoking status (current, former, and nonsmoker), and heavy alcohol consumption (above or below 14 drinks per week for males or 7 drinks per week for females). In addition, the models were adjusted for the presence or absence of hypertension, hypercholesterolemia, abnormal ECG, diabetes, cardiovascular disease, and cancer. The proportional hazards assumption was examined and satisfied by comparing the log–log survival plots grouped on exposure categories. To test the interaction between physical activity or fitness and sex with glaucoma, the interaction terms were entered into the multivariable Cox regression models. The risk estimates in the sex-stratified analyses were also compared. We found no significant interaction, thus we presented the results of pooled analyses. We also tested the interaction of physical activity and fitness with incident glaucoma and found no significant interaction (P = 0.87). To examine the possible dose–response relationship of physical activity and fitness with incident glaucoma, we used restricted cubic spline regression. We chose the model with 3 knots at the 25th, 50th, and 75th percentile based on the Akaike information criterion. For physical activity, the analysis included men and women who were participating in physical activity after excluding the participants with 0 MET·min·wk−1. The analyses were truncated to the upper 95% of the data because data were sparse at the upper extreme of the distribution for both physical activity and fitness. All statistical tests were two-sided and used SAS software (version 9.4).
From 1987 to 2005, 9519 eligible individuals were followed for an average of 5.7 ± 4.3 yr for a total of 54,258 person-years of follow-up. During the follow-up, 128 new cases of glaucoma were observed. The incidence rate of glaucoma was 2.36 per 1000 person-years. Study population descriptive information is presented in Table 1. There were significant differences (P < 0.05) in each variable among physical activity groups (inactive, insufficient, and recommended) except for sex, race, systolic blood pressure, heavy alcohol drinking, abnormal ECG, and cancer. Significant differences (P < 0.05) were found in all variables among fitness groups (low, middle, and high) except for sex, heavy alcohol drinking, cardiovascular disease, and cancer. However, significant difference was found only in age (P < 0.01) comparing individuals who developed glaucoma compared with those who did not develop glaucoma during follow-up.
The HR values of glaucoma across physical activity and fitness groups are presented in Table 2. Significant linear trends were observed across the three levels of physical activity (P < 0.001) and fitness (P = 0.01) in model 1 after adjustment for age, sex, race, and examination year. After further adjustment for smoking status, alcohol intake, and medical conditions (hypertension, hypercholesterolemia, abnormal ECG, diabetes, cardiovascular diseases, and cancer) in model 2, the association remained significant for both physical activity and fitness. With further adjustment for fitness on the association between physical activity and incident glaucoma, the associations were remained significant (P for trend = 0.01, HR = 0.87, 95% CI = 0.52–1.47 in insufficient group and HR = 0.57, 95% CI = 0.37–0.89 in recommended group). However, the association between fitness and incident glaucoma was no longer significant after further adjustment for physical activity (P for trend = 0.32, HR = 0.87, 95% CI = 0.56–1.36 in the middle group and HR = 0.78, 95% CI = 0.47–1.28 in the high group).
Table 3 presents the HR of combined physical activity and fitness groups. We found that participants meeting physical activity guidelines had a lower risk of developing glaucoma in both unfit and fit groups compared with the reference group of unfit participants not meeting physical activity guidelines. Individuals who were active and fit had the lowest risk of incident glaucoma (HR = 0.49, 95% CI = 0.31–0.79). In this joint analysis, inactive and insufficient physical activity groups as well as low and middle fitness groups were combined to strengthen statistical power by increasing number of glaucoma cases based on the similar insignificant associations of inactive and insufficient physical activity and low and middle fitness with glaucoma shown in Table 2. Similar trends were observed in the analyses using three levels of physical activity (inactive, insufficient, and recommended) and fitness (low, middle, and high) (data not shown).
In the restricted cubic spline regression (Fig. 1), the P values for nonlinearity suggested linear dose–response relationships of both physical activity and fitness with incident glaucoma, similar to the results from the categorical data analyses in Table 2 (both P values for linear trend were <0.05). However, we observed potentially greater benefits at lower levels of physical activity, but the dose–response relationship was more linear for fitness. These results should be carefully interpreted because the CI values are wide due to the limited number of incident glaucoma (n = 128).
This study demonstrated that meeting the 2008 Physical Activity Guidelines for Americans (18) recommending 500 MET·min·wk−1 was associated with a lower risk for incident glaucoma (Table 2) after controlling for potential confounders, including lifestyle and health risk factors. Furthermore, fitness was associated with a protective trend of similar magnitude to that of physical activity. Williams (13) examined a group of 29,854 male runners from the National Runners’ Health Study for a mean of 7.7 yr. He found a protective effect of fitness (measured through a 10-km race performance) and physical activity (kilometers per week from self-report) on incident glaucoma.
When fitness was further adjusted to the analysis for physical activity and glaucoma, the reduction in risk was slightly attenuated although remained significant. However, when physical activity was further adjusted to the analysis for fitness and glaucoma, the association was no longer significant. This indicates that physical activity modifies the association between fitness and glaucoma because aerobic physical activity is the primary determinant of fitness (20). Another study controlling for physical activity in fitness and controlling for fitness in physical activity analyses showed that physical activity and fitness affect each other in their relationship to the development of glaucoma (13). However, physical activity was self-reported, which is more prone to measurement error, and fitness was objectively measured using the maximal treadmill test in this study; thus, the relative effects and contribution of physical activity and fitness on the development of glaucoma when controlling for the other factor remain unclear.
In the joint analysis, the combined effects of physical activity level and fitness are associated with greater protection from the development of incidence glaucoma than either physical activity or fitness independently (Table 3). Therefore, it may be possible to have the greatest health benefit by being fit and active to reduce the risk for incident glaucoma. In the current sample, among those who were unfit, 49% participants (3125 of 6410) were meeting the physical activity guidelines, whereas among fit individuals, there were 84% participants (2618 of 3109) meeting the guidelines. The average age at which incident glaucoma was developed was 61 yr old in 128 cases in this study, which is similar to the earlier report indicating that glaucoma increases with age (8).
The results are consistent with research evaluating the beneficial effect of physical activity or exercise on IOP, the leading modifiable risk factor for the development of glaucoma. Recent reviews (10,12) established that acute exercise lowers IOP in the acute postexercise period and noted a dose–response with intensity; the greater the intensity, the greater the reduction in IOP. Furthermore, the reduction in IOP after exercise is even greater in glaucoma patients (11,21). Exercise regimens that improved physical fitness result in chronically lower resting IOP (10). Unfortunately, the physiological mechanism by which exercise lowers IOP is not completely understood (21).
Some evidence suggests that exercise stimulates antioxidant networks (22–24). Oxidative stress may damage retinal ganglion cells (25) and damage DNA in the trabecular meshwork, thereby compromising outflow and increasing IOP (21), and increased oxidative stress has been linked to IOP in animal models (26,27). In animal studies, antioxidant treatments have some benefit in reducing oxidative stress in the retina (7). One novel study with mice demonstrated that increases in brain derived neurotropic factor resulting from aerobic training had a protective effect on retinal function and photoreceptor nuclei (28).
A major strength of the study was the use of regular, comprehensive clinical examinations and medical history data, as well as the use of physician-confirmed cases of incident glaucoma during an average of 5.7 yr of follow-up in a large cohort of 9519 men and women. The measure of physical activity was limited to self-report allowing for possible overreporting of physical activity leading to underestimation of the benefits of physical activity on glaucoma prevention. We did not have data to classify the type of glaucoma; thus, we were not able to examine the various magnitude of the effects of physical activity and fitness by type of glaucoma. Another limitation of the study is the lack of data on some potential confounders such as eye trauma, sports participation (as a risk factor of eye trauma), myopia, nocturnal hypotension, and use of inhalers for asthma that may be related to either or both risk of glaucoma and physical activity levels. Participants were mostly white, well educated, and from middle to upper socioeconomic strata; therefore, the results may not apply to the U.S. population as a whole. However, this homogeneity can reduce potential confounding of education, income, and ethnicity by increasing internal validity.
In summary, physical activity, when meeting the recommended guidelines, and higher level of fitness (upper third) were associated with a lower risk of incident glaucoma, compared with inactive or lower level of fitness (lower third). Furthermore, being fit in addition to being active may provide further protection from developing glaucoma.
This study was supported by the National Institutes of Health grants (AG06945, HL62508, DK088195, and HL133069). Steven N. Blair has received unrestricted research grants from The Coca-Cola Company, but the grants were not used to support this manuscript. Other authors declare no conflicts of interest. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
The authors have no conflicts of interest. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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