Purpose
To evaluate the relationship between intraocular pressure (IOP) and various anthropometric measures.
Design
A population-based cross-sectional study.
Methods
A total of 5008 participants, 2080 men and 2928 women ≥19 years of age were included from the Korea National Health and Nutrition Examination Survey V database, focusing on the years 2010 and 2011. We selected IOP in the right eye of a normal healthy population as the outcome variable of our study. We analyzed the relationship between IOP and anthropometric parameters using dual-energy X-ray absorptiometry by sex. Lean body mass was calculated as total body mass minus fat mass. We used general linear models and logistic regression analysis to evaluate risk factors of high IOP. Our main outcome measure was correlation between anthropometric data and IOP.
Results
In multivariate general linear models, greater body mass index (BMI) and waist circumference were correlated with higher IOP for both men (BMI, β = 0.053, P = .026; waist circumference, β = 0.016, P = .067) and women (BMI, β = 0.074, P < .001; waist circumference, β = 0.028, P < .001). Greater fat mass (β = 0.027, P = .037) and fat mass/lean body mass (β = 1.170, P = .06) were correlated with higher IOP, while greater lean body mass/weight (β = −3.188, P = .025), lean body mass/BMI (β = −1.379, P = .002), appendicular skeletal muscle mass/BMI (β = −2.270, P = .022), and bone mineral content/BMI (β = −11.653, P = .031) were correlated with lower IOP in women, but not in men ( P > .10).
Conclusions
In healthy women, greater fat mass was associated with higher IOP, and greater muscle mass was associated with lower IOP after adjusting for weight and BMI. Fat and muscle influenced IOP in women independently.
Obesity is regarded as an increasingly common health concern across the globe and is a significant risk factor for metabolic syndrome, including coronary heart disease. However, with regard to eye disease, the importance of obesity is not well understood. Some eye diseases, such as cataracts, age-related macular degeneration (AMD), and open-angle glaucoma (OAG), have a suspected link to obesity, but these associations have not been consistently observed, making the pathophysiological explanations unclear. Some recent studies have suggested that metabolic syndrome may influence the risk of high intraocular pressure (IOP), which is important given that the relationship between obesity and metabolic syndrome is seen at the population level.
Glaucoma is associated with various ocular and systemic factors. Most risk factors, such as genetic factors and myopia, cannot be modified. IOP is regarded as the most important modifiable risk factor for OAG. IOP is maintained by the balance of inflow and outflow of aqueous solutions, and an individual’s IOP is thought to be influenced by different systemic and local ocular factors. Several studies have shown a relationship between obesity and IOP; however, the results have been inconsistent. Most obesity studies used only body mass index (BMI) or waist circumference as obesity parameters. Geloneck and associates reported that higher BMI was correlated with higher IOP, and Pasquale and associates reported that, among women, higher BMI was associated with a lower risk of normal-tension glaucoma. The World Health Organization (WHO) defines obesity as a BMI of >30 kg/m 2 , and overweight individuals are those with a BMI ranging from 25 to 29.9 kg/m 2 . BMI is a popular index, but it does not directly measure adiposity parameters. The human body consists of fat, muscle, bone, and other tissues. In addition, many studies have suggested that body composition varies between males and females. Gao and colleauges reported that the mean values of fat percentile were 37.36 for women and 25.33 for men. Jang and associates reported that the mean values of fat mass were 19.0 for women and 15.6 for men, and the mean values of fat percentile were 32.9 for Korean women and 22.0 for Korean men. Bowen and associates analyzed data from the Indian Migration Study (IMS) and Andhra Pradesh Children and Parents’ Study (APCAPS). In the IMS subjects, the mean values of fat mass using dual-energy X-ray absorptiometry (DEXA) were 23.8 for women and 16.7 for men, and the mean values of fat percentile were 37.7 for women and 24.3 for men. Prado and associates reported that the mean values of fat mass were 30.56 for women and 24.67 for men. Fat mass and fat mass/weight in females were significantly higher than those in males.
DEXA can accurately detect adiposity and provide information about total and regional fat mass, lean body mass, and bone mineral content. We investigated the association between various anthropometric measures (e.g., BMI, waist circumference, fat mass, lean body mass, appendicular skeletal muscle [ASM] mass, and bone mineral content) and IOP using a nationally representative dataset of South Korean adults from the Korea National Health and Nutrition Examination Survey (KNHANES).
Methods
This population-based cross-sectional study, including the KHANES survey, adhered to the tenets of the Declaration of Helsinki for human research, and all participants provided written informed consent. The survey protocol was approved by the Institutional Review Board of the Korea Center for Disease Control and Prevention (KCDCP). As all of the KNHANES data are deidentified and available to the public, the Institutional Review Board of the Kangbuk Samsung Hospital determined that this study was exempt from approval.
Study Design and Population
The KNHANES is an ongoing, population-based, cross-sectional survey in South Korea conducted by the KCDCP and the Korean Ministry of Health and Welfare. It uses a multistage, stratified, probability cluster survey with a rolling sampling design. The data from the KNHANES are representative of the civilian, noninstitutionalized South Korean population. A detailed description of the KNHANES design has been previously published.
A total of 17,476 subjects were enrolled in KNHANES V (2010–2011). In the KNHANES V dataset, patient medical history, including refractive surgery, was recorded. We included subjects that were ≥19 years of age, had undergone an eye examination that satisfied the International Society of Geographical and Epidemiological Ophthalmology (ISGEO) criteria, and underwent DEXA. We excluded subjects with any missing data from our analyses. Participants were also excluded if they were pseudophakic or aphakic, had undergone cataract, retinal or refractive surgery, had evidence of retinal detachment on examination, had signs of glaucoma and AMD on examination, or had a history of stroke influencing visual field defect. Finally, 5008 subjects (2080 men and 2928 women) were included in analysis.
Ophthalmologic Examination
All ophthalmic examinations were performed by ophthalmologists. Visual acuity was measured using an international standard vision chart (Jin’s Vision Chart; Seoul, Korea) at a distance of 4 m. Refractive errors were measured with an autorefractor-keratometer (KR8800; Topcon, Tokyo, Japan). We performed slit lamp examinations, including assessment of the peripheral anterior chamber depth, using the Van Herick method (Haag-Streit model BQ-900; Haag-Streit AG, Koeniz, Switzerland). We defined an open angle as a peripheral anterior chamber depth of >1/4 of the peripheral corneal thickness, according to the Van Herick method. Fundus photographs were taken with a digital nonmydriatic fundus camera (TRC-NW6S [Topcon, Tokyo, Japan] and Nikon D-80 digital camera [Nikon, Tokyo, Japan]). IOP was measured with a Goldmann applanation tonometer (GAT, Haag-Streit model BQ-900; Haag-Streit AG), once for each eye, from right to left. We chose to analyze the IOP of the right eye in the healthy group (described below).
Healthy subjects were defined as those who met all the following criteria in both eyes: (1) IOP ≤21 mm Hg; (2) presence of an open angle (peripheral anterior chamber depth >1/4 of corneal thickness); (3) nonglaucomatous optic disc (vertical and horizontal cup-to-disc ratio <0.7 and intereye differences of vertical and horizontal cup-to-disc ratio <0.2); (4) absence of optic disc hemorrhage or retinal nerve fiber layer defects; and (5) optic disc satisfying the inferior≥superior≥nasal≥temporal rule.
Anthropometric Measurements and Body Composition
Specially trained examiners performed all anthropometric measurements on all subjects. Body weight and height were measured with the subjects barefoot and wearing light clothing. Waist circumference was measured at the midpoint between the lower border of the rib cage and the iliac crest while subjects were standing.
Total and regional (ie, arm and leg) body fat mass and lean mass were measured using whole-body DEXA scans (QDR 4500A fanbeam densitometer; Hologic Inc, Bedford, MA) by qualified technicians according to the manufacturer’s acquisition procedures. We recorded total and regional fat mass, lean body mass, ASM mass, and bone mineral content from DEXA scans.
BMI was calculated as kg/m 2 , and lean body mass was calculated as total body mass minus fat mass. Nonbone lean body mass was calculated as lean body mass minus bone mineral contents. ASM mass was calculated as the sum of nonbone lean body mass of the arms and legs, following the Heymsfield method.
We also obtained data on the body composition ratio, including fat mass, lean body mass, ASM mass, bone mineral content, and weight. In addition, to understand the effect of each component on IOP among patients of the same weight or BMI, we analyzed the ratio of body composition and BMI and the ratio of fat mass and other body compositions, with the exception of fat mass.
Lifestyle Variables
All subjects were asked about their lifestyle characteristics, including alcohol consumption, smoking status, and physical activity. Based on their average alcohol intake per day in the month before the interview, subjects were categorized as heavy drinkers (>60 g/day in men, >40 g/day in women, ≥2 times a week) or not. Subjects were categorized as current smokers (>100 cigarettes over their lifetime and current smoking status) or not. On the basis of their responses to the International Physical Activity Questionnaire, subjects were considered regular physical exercisers if they participated in moderate exercise >5 times per week for >30 minutes per session or performed vigorous exercise >3 times per week for >20 minutes per session.
Statistical Analyses
Statistical analyses were performed using SPSS software (version 21.0; IBM SPSS, Inc, Chicago, IL) to account for the complex sampling design. Strata, sampling units, and sampling weights were used to obtain point estimates and standard error (SE) of the means. All data analyses were performed using weighted data and SE of the means. Population estimates were calculated using Taylor linearization methods. Participant characteristics were summarized for the entire sample using means and SE for continuous variables, and percentages and SE for categorical variables.
Baseline demographic information and clinical parameters were compared between groups with the Pearson chi-square test for categorical variables and general linear models for continuous variables. General linear models were used to examine the relationships between anthropometric parameters and IOP. In addition, logistic regression analysis was used to examine the relationships between anthropometric parameters and IOP divided into categorical variables. The categorical variables of IOP were IOP ≤14 mm Hg and IOP ≥15 mm Hg because the mean value of IOP of total subjects was 14.0 (0.1) mm Hg. In model 1, we adjusted for age. In model 2, we adjusted for age and lifestyle variables (eg, heavy drinking, current smoking, regular physical exercise, hypertension, and diabetes). We selected these variables for adjustment because of previously documented associations between lifestyle variables, IOP, and obesity. After dividing the healthy subjects into quartiles for each anthropometric parameter, we analyzed the relationship between IOP and anthropometric parameters for each quartile. After all subjects were divided into quartiles for each anthropometric parameter, the differences in IOP with respect to the quartiles were estimated. The β-coefficient value or odds ratio (OR) and 95% confidence interval (CI) were obtained for the age-adjusted model (model 1) and the age and lifestyle–adjusted model (model 2). Because of the differences between male and female body composition, we stratified our analyses by sex and then adjusted for age. P values were 2-tailed, and we considered P < .05 to be statistically significant. P values > .05 but ≤ .10 were considered marginally significant.
Results
Of 17,476 patients, the number of subjects who underwent ocular examination was 15,932. Among them, the number of subjects who underwent ocular examination and belonged to either the OAG group (ie, categories 1, 2, and 3) or the healthy group according to the ISGEO criteria was 9925. Among the subjects satisfying the ISGEO criteria, the number of subjects who underwent anthropometric measurements with DEXA, including BMI, waist circumference, fat mass, lean body mass, and ASM mass was 6585. Of these 6585, 1577 subjects were excluded. The number of subjects excluded because of slit lamp findings was as follows: 338 because of pseudophakia and aphakia in the right eye and 339 in the left eye. In addition, the number of subjects excluded because of a history of ocular surgery (determined by questionnaire) included 355 who underwent cataract surgery; 15, retina surgery; 212, refractive surgery; 8, cataract and retina surgery; and 1, cataract and refractive surgery. Evidence of retinal detachment or AMD in the right and left eyes led to exclusion of 556 and 560 subjects, respectively, and 376 glaucoma subjects were also excluded. Sixty-one subjects who had a history of stroke, which can affect visual field testing, were excluded. Study subjects’ baseline characteristics are presented in Table 1 . The mean age was 41.9 (SE = 0.4) years and the proportion of male subjects was 48.9%. The mean IOP in healthy men and women was 14.2 (SE = 0.1) mm Hg and 13.8 (SE = 0.1) mm Hg, respectively; this difference was significant ( P < .001). All baseline anthropometric parameters were significantly different by sex ( Table 2 ). The mean values for BMI, waist circumference, lean body mass, ASM mass, and bone mineral content were significantly higher in men than in women, while fat mass and fat mass–related factors were higher in women than in men.
| Healthy Men (n = 2080, 48.9%) | Healthy Women (n = 2928, 51.1%) | P Value | |
|---|---|---|---|
| Age (y) | 41.0 (0.4) | 42.8 (0.4) | <.001 a |
| Intraocular pressure (mm Hg) | 14.2 (0.1) | 13.8 (0.1) | <.001 a |
| Current smoking, n (%) | 48.8 (1.4) | 6.7 (0.6) | <.001 b |
| Heavy drinking, n (%) | 24.2 (1.4) | 5.4 (0.5) | <.001 b |
| Regular physical exercise, n (%) | 24.4 (1.3) | 19.0 (1.0) | <.001 b |
| Hypertension, n (%) | 20.8 (1.1) | 17.1 (0.8) | .005 b |
| Diabetes, n (%) | 6.9 (0.7) | 5.4 (0.5) | .059 b |
| Postmenopause, n (%) | 33.0 (1.2) | ||
| Total cholesterol (mg/dL) | 187.92 (1.05) | 185.13 (0.85) | .033 a |
| HDL cholesterol (mg/dL) | 49.92 (0.35) | 56.07 (0.28) | <.001 a |
| LDL cholesterol (mg/dL) | 113.01 (1.39) | 109.42 (1.34) | .051 a |
| Triglycerides (mg/dL) | 157.89 (3.88) | 105.10 (1.68) | <.001 a |
| Healthy Men | Healthy Women | P Value a | |
|---|---|---|---|
| BMI (kg/m 2 ) | 24.2 (0.1) | 23.2 (0.1) | <.001 |
| Weight (kg) | 71.2 (0.3) | 57.9 (0.2) | <.001 |
| Height (cm) | 171.5 (0.2) | 158.0 (0.1) | <.001 |
| Waist circumference (cm) | 84.2 (0.3) | 77.4 (0.3) | <.001 |
| Fat mass (kg) | 16.4 (0.2) | 19.6 (0.2) | <.001 |
| Lean body mass (kg) | 54.2 (0.2) | 37.9 (0.1) | <.001 |
| ASM mass (kg) | 22.9 (0.1) | 14.5 (0.1) | <.001 |
| Bone mineral content (kg) | 2.6 (0.0) | 2.1 (0.0) | <.001 |
| Fat mass/weight | 0.23 (0.00) | 0.33 (0.00) | <.001 |
| Lean body mass/weight | 0.77 (0.00) | 0.66 (0.00) | <.001 |
| ASM mass/weight | 0.32 (0.00) | 0.25 (0.00) | <.001 |
| Fat mass/BMI | 0.66 (0.01) | 0.83 (0.00) | <.001 |
| Lean body mass/BMI | 2.26 (0.01) | 1.65 (0.01) | <.001 |
| ASM mass/BMI | 0.95 (0.00) | 0.63 (0.00) | <.001 |
| Bone mineral content/BMI | 0.11 (0.00) | 0.09 (0.00) | <.001 |
| Fat mass/lean body mass | 0.30 (0.00) | 0.52 (0.00) | <.001 |
| Fat mass/ASM mass | 0.72 (0.01) | 1.35 (0.01) | <.001 |
| Fat mass/bone mineral content | 6.22 (0.07) | 9.64 (0.08) | <.001 |
Relationship Between Anthropometric Parameters and IOP in Healthy Subjects
Tables 3 (age-adjusted model) and 4 (age and lifestyle–adjusted model) show the relationship between obesity parameters and IOP in healthy subjects on general linear modeling. In men, higher IOP was associated with greater BMI (age-adjusted, β = 0.055, P = .013; age and lifestyle–adjusted, β = 0.053, P = .026) and waist circumference (age-adjusted, β = 0.018, P = .023; age and lifestyle–adjusted, β = 0.016, P = .067). Greater BMI, weight, waist circumference, fat mass, and fat mass/lean body mass were associated with higher IOP in women ( P < .05). Greater height, lean body mass/weight, lean body mass/BMI, ASM mass/BMI, and bone mineral content/BMI were associated with lower IOP in women ( P < .05).
| Men | Women | |||
|---|---|---|---|---|
| β (95% CI) | P Value a | β (95% CI) | P Value a | |
| BMI (kg/m 2 ) | 0.055 (0.012–0.099) | .013 | 0.071 (0.035–0.106) | <.001 |
| Weight (kg) | 0.011 (−0.002–0.024) | .108 | 0.015 (0.002–0.028) | .027 |
| Height (cm) | −0.017 (−0.043–0.008) | .176 | −0.040 (−0.067 to −0.013) | .004 |
| Waist circumference (cm) | 0.018 (0.003–0.034) | .023 | 0.027 (0.013–0.042) | <.001 |
| Fat mass (kg) | 0.015 (−0.010–0.041) | .243 | 0.027 (0.003–0.050) | .028 |
| Lean body mass (kg) | 0.016 (−0.005–0.037) | .138 | 0.013 (−0.012–0.039) | .312 |
| ASM mass (kg) | 0.033 (−0.013–0.078) | .158 | 0.040 (−0.016–0.096) | .165 |
| Bone mineral content (kg) | 0.108 (−0.264–0.480) | .569 | 0.150 (−0.263–0.562) | .476 |
| Fat mass/weight | 0.686 (−1.986–3.357) | .615 | 2.482 (−0.205–5.170) | .070 |
| Lean body mass/weight | −0.888 (−3.524–1.748) | .509 | −3.177 (−5.856 to −0.499) | .020 |
| ASM mass/weight | −0.987 (−6.397–4.422) | .720 | −4.229 (−9.933–1.476) | .146 |
| Fat mass/BMI | 0.080 (−0.781–0.941) | .855 | 0.254 (−0.746–1.253) | .618 |
| Lean body mass/BMI | −0.480 (−1.141–0.180) | .154 | −1.350 (−2.177 to −0.523) | .001 |
| ASM mass/BMI | −0.788 (−2.141–0.565) | .253 | −2.291 (−4.143 to −0.438) | .015 |
| Bone mineral content/BMI | −6.305 (−15.232–2.622) | .166 | −11.710 (−21.883 to −1.538) | .024 |
| Fat mass/lean body mass | 0.473 (−1.114–2.060) | .558 | 1.170 (0.002–2.338) | .050 |
| Fat mass/ASM mass | 0.175 (−0.480–0.830) | .600 | 0.366 (−0.063–0.795) | .095 |
| Fat mass/bone mineral content | 0.039 (−0.030–0.109) | .266 | 0.049 (−0.006–0.104) | .078 |
| Men | Women | |||
|---|---|---|---|---|
| β (95% CI) | P Value a | β (95% CI) | P Value a | |
| BMI (kg/m 2 ) | 0.053 (0.006–0.099) | .026 | 0.074 (0.036–0.111) | <.001 |
| Weight (kg) | 0.011 (−0.003–0.025) | .127 | 0.015 (0.001–0.029) | .034 |
| Height (cm) | −0.013 (−0.038–0.011) | .284 | −0.041 (−0.069 to −0.013) | .005 |
| Waist circumference (cm) | 0.016 (−0.001–0.034) | .067 | 0.028 (0.012–0.043) | <.001 |
| Fat mass (kg) | 0.013 (−0.014–0.041) | .343 | 0.027 (0.002–0.052) | .037 |
| Lean body mass (kg) | 0.018 (−0.004–0.039) | .113 | 0.014 (−0.013–0.040) | .319 |
| ASM mass (kg) | 0.037 (−0.009–0.083) | .117 | 0.043 (−0.016–0.103) | .155 |
| Bone mineral content (kg) | 0.092 (−0.290–0.475) | .636 | 0.179 (−0.254–0.613) | .416 |
| Fat mass/weight | 0.407 (−2.467–3.281) | .781 | 2.484 (−0.324–5.292) | .083 |
| Lean body mass/weight | −0.598 (−3.455–2.258) | .681 | −3.188 (−5.971 to −0.406) | .025 |
| ASM mass/weight | −0.277 (−6.068–5.514) | .925 | −3.878 (−9.840–2.083) | .202 |
| Fat mass/BMI | 0.031 (−0.897–0.960) | .947 | 0.217 (−0.820–1.254) | .682 |
| Lean body mass/BMI | −0.359 (−1.038–0.320) | .300 | −1.379 (−2.236 to −0.522) | .002 |
| ASM mass/BMI | −0.530 (−1.914–0.854) | .453 | −2.270 (−4.205 to −0.335) | .022 |
| Bone mineral content/BMI | −6.032 (−15.152–3.089) | .195 | −11.653 (−22.252 to −1.054) | .031 |
| Fat mass/lean body mass | 0.311 (−1.385–2.007) | .719 | 1.170 (−0.051–2.391) | .060 |
| Fat mass/ASM mass | 0.099 (−0.599–0.796) | .782 | 0.357 (−0.092–0.806) | .119 |
| Fat mass/bone mineral content | 0.033 (−0.041–0.108) | .382 | 0.048 (−0.010–0.106) | .104 |
Relationship Between Anthropometric Parameter Quartiles and IOP in Healthy Subjects
Men with higher BMI and waist circumference exhibited an increasing trend toward higher IOP in both the age-adjusted (BMI, P = .022; waist circumference, P = .020) and age and lifestyle–adjusted (BMI, P = .030; waist circumference, P = .054) models. In the age-adjusted model, men in the higher BMI quartile had significantly higher IOP values than men in the lowest BMI quartile (quartile 4, β = 0.396, P = .042), and men in the higher waist circumference quartile had significantly higher IOP values than men in the lowest waist circumference quartile (quartile 3, β = 0.500, P = .010; quartile 4, β = 0.407, P = .044).
Table 5 shows the relationship between anthropometric parameters and IOP in healthy women by quartile. The quartiles for each anthropometric parameter are shown in detail in the Table 5 .
| Quartile of Anthropometric Measurements in Women | P Value | ||||
|---|---|---|---|---|---|
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | ||
| BMI (kg/m 2 ) | <22 | 22–23 | 24–25 | >25 | |
| Mean IOP (SE) | 13.5 (0.1) | 13.8 (0.1) | 13.9 (0.2) | 14.1 (0.1) | <.001 b |
| Model 1 | |||||
| β (95% CI) | Reference | 0.369 (0.089–0.649) c | 0.479 (0.133–0.825) c | 0.687 (0.365–1.008) c | <.001 b |
| OR (95% CI) | Reference | 1.190 (0.926–1.530) | 1.351 (0.995–1.835) | 1.524 (1.161–2.002) e | .002 d |
| Model 2 | |||||
| β (95% CI) | Reference | 0.455 (0.166–0.744) c | 0.573 (0.207–0.938) c | 0.746 (0.410–1.082) c | <.001 b |
| OR (95% CI) | Reference | 1.232 (0.950–1.598) | 1.436 (1.043–1.976) e | 1.551 (1.160–2.073) e | .003 d |
| Weight (kg) | <53 | 53–57 | 58–63 | >63 | |
| Mean IOP (SE) | 13.8 (0.1) | 13.6 (0.1) | 13.8 (0.1) | 14.1 (0.1) | .020 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.189 (−0.499–0.120) | 0.031 (−0.251–0.314) | 0.320 (−0.018–0.658) | .024 b |
| OR (95% CI) | Reference | 0.840 (0.635–1.112) | 0.980 (0.777–1.235) | 1.226 (0.938–1.604) | .063 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.168 (−0.481–0.145) | 0.042 (−0.256–0.339) | 0.341 (−0.016–0.698) | .026 b |
| OR (95% CI) | Reference | 0.854 (0.648–1.125) | 1.000 (0.784–1.275) | 1.245 (0.938–1.651) | .062 d |
| Height (cm) | <154 | 154–158 | 159–162 | >162 | |
| Mean IOP (SE) | 14.2 (0.2) | 13.9 (0.1) | 13.6 (0.1) | 13.7 (0.1) | .003 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.253 (−0.598–0.093) | −0.580 (−0.969 to −0.191) c | −0.542 (−0.983 to −0.102) c | .010 b |
| OR (95% CI) | Reference | 0.863 (0.678–1.097) | 0.647 (0.490–0.853) e | 0.683 (0.506–0.924) e | .005 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.262 (−0.611–0.086) | −0.591 (−0.979 to −0.202) c | −0.571 (−1.020 to −0.121) c | .008 b |
| OR (95% CI) | Reference | 0.877 (0.687–1.120) | 0.656 (0.496–0.868) e | 0.695 (0.510–0.947) e | .009 d |
| Waist circumference (cm) | < 72 | 72–77 | 78–84 | > 84 | |
| Mean IOP (SE) | 13.4 (0.1) | 13.8 (0.1) | 14.0 (0.1) | 14.1 (0.1) | <.001 b |
| Model 1 | |||||
| β (95% CI) | Reference | 0.493 (0.124–0.863) c | 0.704 (0.335–1.073) c | 0.804 (0.419–1.189) c | <.001 b |
| OR (95% CI) | Reference | 1.352 (1.010–1.809) e | 1.610 (1.192–2.175) e | 1.698 (1.248–2.312) e | <.001 d |
| Model 2 | |||||
| β (95% CI) | Reference | 0.530 (0.144–0.915) c | 0.745 (0.352–1.138) c | 0.834 (0.427–1.242) c | <.001 b |
| OR (95% CI) | Reference | 1.361 (1.004–1.844) e | 1.639 (1.186–2.267) e | 1.691 (1.222–2.339) e | .001 d |
| Fat mass (kg) | <15.90 | 15.90–19.02 | 19.03–22.72 | >22.72 | |
| Mean IOP (SE) | 13.6 (0.1) | 13.8 (0.1) | 13.9 (0.1) | 14.0 (0.2) | .042 b |
| Model 1 | |||||
| β (95% CI) | Reference | 0.200 (−0.137–0.537) | 0.301 (−0.010–0.611) | 0.330 (−0.007–0.666) | .055 b |
| OR (95% CI) | Reference | 1.052 (0.791–1.400) | 1.131 (0.867–1.475) | 1.184 (0.911–1.538) | .181 d |
| Model 2 | |||||
| β (95% CI) | Reference | 0.267 (−0.093–0.627) | 0.321 (−0.008–0.650) | 0.346 (−0.014–0.706) | .067 b |
| OR (95% CI) | Reference | 1.115 (0.826–1.505) | 1.152 (0.864–1.534) | 1.190 (0.899–1.574) | .230 d |
| Bone mineral content (kg) | < 1.82 | 1.82–2.02 | 2.03–2.22 | > 2.22 | |
| Mean IOP (SE) | 13.7 (0.1) | 13.9 (0.1) | 13.7 (0.1) | 13.9 (0.1) | .523 b |
| Model 1 | |||||
| β (95% CI) | Reference | 0.236 (−0.110–0.581) | 0.108 (−0.275–0.491) | 0.262 (−0.112–0.636) | .312 b |
| OR (95% CI) | Reference | 1.179 (0.913–1.524) | 1.020 (0.769–1.354) | 1.033 (0.784–1.361) | .789 d |
| Model 2 | |||||
| β (95% CI) | Reference | 0.214 (−0.139–0.567) | 0.135 (−0.271–0.541) | 0.272 (−0.112–0.656) | .261 b |
| OR (95% CI) | Reference | 1.194 (0.916–1.556) | 1.045 (0.772–1.414) | 1.059 (0.797–1.406) | .932 d |
| Lean body mass/weight | <0.63 | 0.63–0.66 | 0.67–0.69 | >0.69 | |
| Mean IOP (SE) | 14.0 (0.2) | 14.0 (0.1) | 13.8 (0.1) | 13.6 (0.1) | .030 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.036 (−0.380–0.307) | −0.211 (−0.590–0.168) | −0.382 (−0.785–0.020) | .042 b |
| OR (95% CI) | Reference | 0.931 (0.710–1.221) | 0.879 (0.676–1.144) | 0.810 (0.601–1.093) | .135 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.020 (−0.373–0.334) | −0.162 (−0.550–0.227) | −0.385 (−0.803–0.033) | .051 b |
| OR (95% CI) | Reference | 0.942 (0.711–1.246) | 0.944 (0.723–1.232) | 0.815 (0.593–1.119) | .207 d |
| Lean body mass/BMI | <1.51 | 1.51–1.62 | 1.63–1.76 | >1.76 | |
| Mean IOP (SE) | 14.3 (0.2) | 13.8 (0.1) | 13.8 (0.1) | 13.5 (0.1) | <.001 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.469 (−0.809 to −0.128) c | −0.553 (−0.931 to −0.175) c | −0.818 (−1.255, −0.382) c | <.001 b |
| OR (95% CI) | Reference | 0.747 (0.577–0.966) e | 0.624 (0.481–0.809) e | 0.598 (0.451–0.794) e | <.001 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.419 (−0.771 to −0.067) c | −0.542 (−0.918 to −0.166) c | −0.800 (−1.248 to −0.353) c | .001 b |
| OR (95% CI) | Reference | 0.722 (0.594–1.003) | 0.627 (0.484–0.812) e | 0.628 (0.467–0.843) e | .002 d |
| ASM mass/BMI | <0.58 | 0.58–0.62 | 0.63–0.68 | >0.68 | |
| Mean IOP (SE) | 14.2 (0.1) | 13.8 (0.2) | 13.8 (0.1) | 13.6 (0.1) | .008 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.402 (−0.722 to −0.082) c | −0.409 (−0.765 to −0.054) c | −0.600 (−1.049 to −0.151) c | .018 b |
| OR (95% CI) | Reference | 0.713 (0.570–0.890) e | 0.728 (0.557–0.951) e | 0.646 (0.479–0.872) e | .015 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.409 (−0.743 to −0.076) c | −0.444 (−0.810 to −0.079) c | −0.607 (−1.070 to −0.145) c | .018 b |
| OR (95% CI) | Reference | 0.706 (0.562–0.889) e | 0.726 (0.555–0.950) e | 0.659 (0.483–0.897) e | .024 d |
| Bone mineral content/BMI | <0.09 | 0.09–0.09 | 0.10–0.10 | >0.10 | |
| Mean IOP (SE) | 14.1 (0.2) | 13.9 (0.1) | 13.7 (0.1) | 13.6 (0.1) | .002 b |
| Model 1 | |||||
| β (95% CI) | Reference | −0.264 (−0.608 to 0.081) | −0.541 (−0.947 to −0.136) c | −0.623 (−1.093 to −0.154) c | .006 b |
| OR (95% CI) | Reference | 0.737 (0.561–0.969) e | 0.586 (0.435–0.789) e | 0.582 (0.417–0.812) e | .001 d |
| Model 2 | |||||
| β (95% CI) | Reference | −0.220 (−0.577–0.138) | −0.518 (−0.924 to −0.112) c | −0.610 (−1.094 to −0.127) c | .007 b |
| OR (95% CI) | Reference | 0.782 (0.589–1.039) | 0.601 (0.446–0.810) e | 0.609 (0.432–0.860) e | .003 d |
| Fat mass/bone mineral content | <7.83 | 7.83–9.56 | 9.57–11.51 | >11.51 | |
| Mean IOP (SE) | 13.7 (0.1) | 13.7 (0.1) | 14.0 (0.1) | 14.0 (0.2) | .020 b |
| Model 1 | |||||
| β (95% CI) | Reference | 0.014 (−0.309–0.337) | 0.345 (−0.006–0.695) | 0.363 (−0.055–0.781) | .038 b |
| OR (95% CI) | Reference | 1.043 (0.794–1.370) | 1.269 (0.958–1.681) | 1.289 (0.945–1.758) | .050 d |
| Model 2 | |||||
| β (95% CI) | Reference | 0.076 (−0.257–0.410) | 0.363 (−0.007–0.734) | 0.350 (−0.084–0.784) | .055 b |
| OR (95% CI) | Reference | 1.092 (0.821–1.451) | 1.278 (0.948–1.723) | 1.244 (0.888–1.743) | .114 d |
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