Distribution of intraocular pressure and its determinants in an Iranian adult population

Intraocular Pressure Fluctuation Throughout the Day

Purpose To compare intraocular pressure (IOP) values at different time points, both in the total sample and according to iridocorneal angle aperture, to assess whether IOP fluctuations were constant throughout the day, and to examine correlations with other factors. Methods Over a single day, the IOP of 34 volunteers was measured at three-hour intervals from 9:00 a.m. to 6:00 p.m. To avoid any IOP value being affected by other measurements, anamnesis, slit-lamp evaluation (with iridocorneal angle measurement), and refractive status were performed after the final measurement. The differences between IOP values at different time points and IOP fluctuation at three-hour intervals were compared by ANOVA and Friedman test, respectively, both for the total group and according to iridocorneal angle aperture. For relationships, Pearson's correlation was performed for parametric variables and Spearman's correlation for nonparametric variables. Results Significant differences were observed in IOP between time points for the total sample (p < 0.001), but not for a narrow-angle group (p = 0.058). No significant differences were found in IOP fluctuations at three-hour intervals either in the total sample or according to angle aperture (all p ≥ 0.332). There was a positive correlation of IOP at different time points (all r ≥ 0.646, all p < 0.001) but no relationship with spherical equivalent, age, or sleep duration (all p ≥ 0.057). IOP at 12:00 p.m. was correlated with a 12:00 p.m. to 3:00 p.m. fluctuation (r = 0.428, p = 0.012); and IOP fluctuation between 9:00 a.m. and 12:00 p.m. was correlated with age (r = 0.485, p = 0.004). Conclusion As IOP decreases from morning until at least 6:00 p.m., measuring these two values during clinical evaluation is essential for the effective monitoring and prevention of IOP-related diseases.

Distribution and associated factors of intraocular pressure in the older population: Tehran Geriatric Eye Study

AIM

To determine the distribution and associated factors of intraocular pressure (IOP) in an Iranian elderly population 60 years of age and above.

METHODS

The present report is part of the Tehran Geriatric Eye study (TGES), a population-based cross-sectional study that was conducted on the residents of Tehran 60 years of age and above. The sampling was performed using multistage stratified random cluster sampling methods from 22 districts of Tehran, Iran. Demographic and history information, blood samples, and blood pressure were collected from all participants. Ocular examinations included measurement of uncorrected and best-corrected visual acuity, objective and subjective refraction, and slit-lamp biomicroscopy. The IOP was measured using Goldmann applanation tonometry (GAT). Corneal imaging and ocular biometry were performed using Pentacam AXL.

RESULTS

The data of 3892 eyes of 2124 individuals were analyzed for this report. The mean age of the study participants was 66.49±5.31y (range: 60 to 95y). The mean IOP was 15.2 mm Hg (95%CI: 15.1 to 15.4), 15.3 mm Hg (95%CI: 15.1 to 15.5) and 15.1 mm Hg (95%CI: 15.0 to 15.3) in all participants, males, and females, respectively. Of the study participants, 1.3% had an IOP of ≥20 mm Hg. The mean IOP increased from 15.1 mm Hg in the age group 60-64y to 16.3 mm Hg in the age group ≥80y. According to the final multiple GEE model, the IOP was statistically significantly higher in men than in women. All the studied age groups, except for the 75-79-year-old age group, had significantly higher IOP compared to the 60-64-year-old age group. The IOP was significantly higher in underweight compared to other body mass index groups. Moreover, the IOP had a statistically significant direct relationship with the mean corneal power (mean CP), central corneal thickness (CCT), and systolic blood pressure.

CONCLUSION

The present study presents the distribution of IOP in an Iranian elderly population. A higher IOP (within the range 14 to 17 mm Hg) is significantly associated with older age, male sex, high systolic blood pressure, increased mean CP, and CCT. These factors should be considered in the clinical interpretation of IOP.

Age-specific distribution of intraocular pressure in elderly Iranian population and its associated factors

Background

The purpose of this study was to determine the distribution of intraocular pressure (IOP) and assess its association with age, sex, systemic blood pressure, diabetes mellitus, body mass index (BMI) and tobacco smoking in Iranian elderly population.

Methods

This cohort-based, cross-sectional study assessed elderly individuals aged 60-90 years in Amirkola, northern Iran, in 2016-2017. Past medical history, blood pressure, diabetes mellitus, BMI and tobacco smoking were recorded through an interview and physical examination. IOP was assessed using non-contact tonometry.

Results

Total of 1377 individuals participated in this study, out of which 1346 IOP measurements were included for the final analysis. The mean age of participants was 69.4 ± 7.1 years and mean IOP was determined to be 16.7 ± 3.2 mmHg. Majority of the participants were males (56.1% vs 43.1%), 73.8% of participants were overweight or obese, 6.1% smoked tobacco, 28.9% had diabetes mellitus and 84.9% had higher than normal blood pressure. Through multiple regression analysis, it was determined that age (β=-0.132, p<0.001) was negatively associated with IOP, and the presence of diabetes mellitus (β=0.118, p<0.001), systolic blood pressure (β=0.101, p<0.001), and BMI (β=0.020, P=0.020) were positively associated with IOP.

Conclusion

Mean IOP of individuals in this study was higher than average based on other studies. Age, was negatively and systemic blood pressure, BMI and presence of diabetes mellitus were positively associated with mean IOP of elderly Iranian population. Sex and tobacco smoking were not correlated with IOP.

The Effects of Sex, Oral Contraception, and Menstrual Cycle Phase on Intraocular Pressure, Central Corneal Thickness, and Foveal Thickness: A Descriptive Analysis

The primary goal of this study was to investigate the effects of sex, oral contraceptive (OC) use, and menstrual cycle phase on common ocular parameters assessed during ophthalmic evaluations, namely intraocular pressure (IOP), central corneal thickness (CCT), and foveal thickness (FT), in young healthy adults. We measured IOP, CCT, and FT in 60 participants (16 men, 16 contraceptive users, and 28 cycling women) over two sessions that characterized the menstrual cycle phase in women. For men in our study, two sessions were separated by two weeks. For women, the two sessions were scheduled during the follicular and luteal phases of the menstrual cycle. There was a trend towards higher IOP in men, and the difference was significant for white, non-Hispanic subjects and for white subjects considered separately. There was also a trend for thicker corneas in women, but men had significantly thicker foveae. CCT and FT were not different between men and OC-users, hinting at a moderating hormonal effect of oral contraceptive use. We found that IOP, CCT, and FT were equivalent between the follicular and luteal phases, which may be owing to the timing of our sessions. However, our findings strongly suggest that clinicians should consider contraceptive use during routine ophthalmic evaluations, as it could inform glaucomatous risk in women.

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes

PURPOSE

A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits.

DESIGN

Cross-sectional study.

METHODS

We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure [IOP], central corneal thickness [CCT], corneal hysteresis [CH], corneal resistance factor [CRF], cup-to-disc ratio [CDR], and primary open-angle glaucoma [POAG]). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank, and the International Glaucoma Genetics Consortium. We calculated genetic correlation (rg) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT, and select diabetes-related traits based on individual level phenotype data in 2 Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines.

RESULTS

Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a nonsignificant negative correlation between T2D and POAG (rg = -0.14; P = .16). Using Sequential Oligogenic Linkage Analysis Routines, the genetic correlations between measured IOP, CCT, FBS, fasting insulin, and hemoglobin A1c were null. In contrast, genetic correlations between IOP and POAG (rg ≥ 0.45; P ≤ 3.0 × 10-4) and between CDR and POAG were high (rg = 0.57; P = 2.8 × 10-10). However, genetic correlations between corneal properties (CCT, CRF, and CH) and POAG were low (rg range -0.18 to 0.11) and nonsignificant (P ≥ .07).

CONCLUSION

These analyses suggest that there is limited genetic correlation between diabetes- and glaucoma-related traits.