| Home | E-Submission | Sitemap | Contact Us |  
top_img
J Prev Med Public Health > Volume 44(4); 2011 > Article
Biswas, Raman, Koluthungan, and Sharma: Intraocular Pressure and Its Determinants in Subjects With Type 2 Diabetes Mellitus in India

ABSTRACT

Objectives

This study was conducted to show the intraocular pressure (IOP) distribution and the factors affecting IOP in subjects with type 2 diabetes mellitus (DM) in India.

Methods

We measured the anthropometric and biochemical parameters for confirmed type 2 DM patients. A comprehensive ocular examination was performed for 1377 subjects aged > 40 years and residing in Chennai.

Results

A significant difference in IOP (mean ± standard deviation) was found between men and women (14.6±2.9 and 15.0±2.8 mmHg, p = 0.005). A significantly elevated IOP was observed among smokers, subjects with systemic hypertension and women with clinically significant macular edema (CSME). After a univariate analysis, factors associated significantly with higher IOP were elevated systolic blood pressure, elevated resting pulse rate and thicker central corneal thickness (CCT). In women, elevated glycosylated hemoglobin was associated with a higher IOP. After adjusting for all variables, the elevated resting pulse rate and CCT were found to be associated with a higher IOP.

Conclusions

Systemic hypertension, smoking, pulse rate and CCT were associated with elevated intraocular pressure in type 2 DM. Women with type 2 DM, especially those with CSME, were more prone to have an elevated IOP.

INTRODUCTION

The range of intraocular pressure (IOP), among the general population, varies from 8-22 mmHg [1]. This variation can be explained by the numerous factors affecting IOP. Previous studies have shown that the factors associated with elevated IOP include smoking [2], older age [3], gender [2,3], blood pressure [2-4] family history of glaucoma [2,3], pulse rate [2,3], diabetes (elevated glycosylated hemoglobin) [2,3], myopia [5], alcohol usage [2], race (African) [4], nuclear sclerosis [3,5], body mass index (BMI) [2-4] and iris color [5].
Subjects with type 2 diabetes mellitus (DM) have an increased risk of developing open angle glaucoma [6]. It is important to study the distribution and effect of the factors affecting IOP among subjects with DM in India, as there are few population-based studies regarding the same [7]. Based on the procedure used and the population chosen, the distribution of intraocular pressure among type 2 DM varied from 14.86 to 21.5 mmHg [2,3,7-18].
However, these studies did not have standardized procedures like goldmann applanation tonometer (GAT) and fundus photography based standardized retinopathy grading. The aim of this study is to describe the IOP distribution and the factors affecting IOP in subjects with type 2 DM. It also elucidates the gender-specific influence of these factors on the IOP.

METHODS

Sankara Nethralaya - Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS 1) is a population-based, cross-sectional, study to estimate the prevalence and risk factors of diabetes and diabetic retinopathy in the South-Indian population. The detail methodology and study design of SN-DREAMS 1 is given elsewhere [19].
The study population was selected by multistage, systematic random sampling based on the socio-economic status, which made the sample a true representation of subjects with type 2 DM in India. Out of the 5999 individuals, aged ≥40 , enumerated from the general population, 1816 subjects had diabetes (known 1349 and provisional 469); 1563 (86.1%) subjects came for further evaluation at the base hospital and of these, 138 subjects with no diabetes and 11 subjects with ungradable retinal photographs were excluded. Apart from this, 30 subjects having IOP ≥ 22 mmHg, three glaucoma suspects and four subjects under anti-glaucoma medication (one of them being ocular hypertensive) were excluded from the study. Finally, we had 1377 subjects for this study. Known diabetics and provisional diabetics were selected in accordance with the ADA criterion [20]. Known diabetes is when diabetes is diagnosed by a medical practitioner, or the patient uses hypoglycemic medication, either oral or insulin or both and provisional diabetes is when the condition is diagnosed in a new asymptomatic individual with a first fasting blood glucose level ≥110 mg/dL (Accutrend alpha). The right eye was chosen for analysis, alternatively the eye without any history of ocular surgery was selected for analysis.
The study was approved by the Institutional Review Board and a written informed consent was obtained from the subjects as per the Helsinki Declaration. Subjects with provisional diabetes were confirmed to be having diabetes by re-estimating fasting blood glucose by enzymatic assay based glucose oxidation method (Accutrend alpha) [20]. The biochemical analyses done using the Merck Micro Lab 120, semi automated analyzer included total serum cholesterol (CHOD-POD method), high-density lipoproteins (after protein precipitation CHOD-POD method), serum triglycerides (CHOD-POD), hemoglobin (calorimetric hemoglobinometer), packed cell volume (capillary method) and the glycosylated hemoglobin fraction (Bio-Rad DiaSTAT HbA1c Reagent Kit).
Anthropometric measurements, including weight, height, waist and hip, were obtained using standardized techniques. The blood pressure was recorded, in the sitting position, in the right arm, to the nearest 2 mmHg using the mercury sphygmomanometer (Diamond Deluxe BP apparatus, Pune, India). Two readings were taken, five minutes apart, and their mean, was taken as the blood pressure. Microalbuminuria was estimated using the first morning urine sample, by a semiquantitative procedure (Clintek 50 Bayer Urine Analyzer) in which the subjects were considered to have microalbuminuria, if the albumin creatinine ratio (ACR) was between 30 and 299 mg/g [21]. Diabetic neuropathy was assessed by measuring the vibration perception threshold (VPT) using a sensitometer by a single observer with a biothesiometer probe placed perpendicular to the distal plantar surface of the great toe in both legs. The mean VPT measure of the three readings of both legs was considered for the analysis. The presence of diabetic neuropathy was considered if the VPT value was >20 V [22].
After the initial phases of sampling, diabetes confirmation, biochemical and anthropometric examination, a comprehensive ophthalmic examination was conducted at a dedicated facility created in the base hospital in a pre-determined specific order - starting from the subject's medical and ophthalmic condition to recording the presenting and the best-corrected distance visual acuity using the modified ETDRS chart (Light House Low Vision Products, New York, NY, USA). For those who could not read the English alphabet, the Landolt's ring was shown. The pinhole visual acuity was assessed for those having visual acuity less than 4/4 (LogMAR 0.0). An objective refraction was performed with a streak retinoscope (Beta 200, Heine, Germany) and was followed by subjective refraction. The corneal endothelial status was assessed with the corneal specular microspcopy, the corneal thickness was measured using the Corneal Pachymeter (Alcon ultrasound pachymeter) after which the slit lamp examination was performed (Zeiss SL 130). The peripheral anterior chamber depth was assessed as per the van Herick grading [23] and the iris was examined for neovascularization. The IOP in both the eyes were measured using Goldmann applanation tonometer (Zeiss AT 030 Applanation Tonometer, Carl Zeiss, Jena, Germany), using 0.05% proparacaine eyedrops as topical anaesthesia and 2% fluorescein to stain the tear film [24]. The IOP in the right eye was measured first and taken for analysis (Intra correlation coefficient 0.84 between the eyes), with only one reliable measurement recorded for each. The instrument was calibrated on the first working day of every week. After dilating the pupils with 5% phenylephrine and 1% tropicamide eyedrops (if phenylephrine is contraindicated, 1% cyclopentolate eyedrops used), lens opacities were graded using the Lens Opacities Classification System (LOCS chart III, Leo T. Chylack, Harvard Medical School, Boston, MA), retro illuminated with a light box. Fundus photographs were taken using the 45° four-field stereoscopic digital photography Carl Zeiss fundus camera (Visucamlite, Jena, Germany). Diabetic retinopathy was diagnosed based on the modified Klein classification (Modified Early Treatment Diabetic Retinopathy Study scales) [25]. The diabetic retinopathy grading was done by two independent observers in a masked fashion and the grading agreement of both were high (k=0.83).
Glycemic control was categorized as normal (glycosylated hemoglobin [HbA1c] < 5.6), good (HbA1c 5.6-7.0), fair (HbA1c 7.1-8.0) and poor (HbA1c ≥ 8.1) [20]. The fasting plasma glucose was considered to be high if the value was >126 mg/dL [26]. The height and weight of all subjects were noted, after which the body mass index (BMI) was calculated using the formula: weight (kg)/height (m2) [27]. Based on the BMI, individuals were classified as lean (male, <20; female, <19), normal (male, 20-25; female, 19-24), overweight (male, 25-30; female, 24-29) or obese (male, >30; female, >29) [28]. The mean Indian height and weight (Indian Council of Medical Research, 1990), axial length [27], CCT [29], pulse beat [30] was taken for general characteristics, whereas, total cholesterol, high and low density cholesterol, triglycerides levels were taken from a previous study [31].
Along with the age and gender-specific mean IOP (± standard deviation [SD]), the mean IOP (± SD), based on the stratification of each categorical predictor, was also calculated. Analysis of variance (ANOVA) was used to compare the demographic, anthropometric, biochemical factors with the IOP. Beta values were calculated for the continuous variables. Both unadjusted and adjusted regression analysis was performed for the variables. All analysis was done using SPSS version 15.0 (SPSS Inc., Chicago, IL). A p value of ≤0.05 was considered significant.

RESULTS

Figure 1 shows the normal distribution of intraocular pressure among subjects with type 2 diabetes. The mean IOP was 14.8±2.9 mmHg (men 14.6±2.9 and women 15.0±2.8 mmHg, p=0.005). There was no significant difference between the mean IOP in the right and left eye (p=0.185). Table 1 shows the IOP distribution in various sub-groups. Subjects with hypertension and a raised systolic blood pressure (SBP) had a higher IOP than those without (14.9±2.9 vs 14.6±2.9 mmHg, p=0.03 and 14.9±2.9 vs 14.4±2.9 mmHg, p=0.001 respectively). Those with diabetic neuropathy had a lower IOP than those without (14.4±2.9 vs 14.9±2.8 mmHg, p=0.008). Among women subjects, those with clinically significant macular edema (CSME) had a higher IOP than those without CSME (17.4±2.2 vs 15.0±2.8 mmHg, p=0.02). Smokers had a higher IOP than non-smokers (14.9±2.9 vs 14.3±2.9, p=0.001) whereas, alcoholics had a lower IOP than non-alcoholics (14.4±2.9 vs 14.9±2.9, p=0.002). Short stature, high central cormeal thickness (CCT) and raised pulse beat were significantly associated with a higher IOP, whereas, longer axial length was significantly associated with a higher IOP only in men subjects. Table 2 describes the correlation of the continuous variables with the intraocular pressure. height, SBP, pulse, CCT and serum total cholesterol were the variables found to be significantly associated with intraocular pressure. Pulse (men: r=0.076, p=0.021 and women r=0.058, p=0.011) and CCT (men: r=0.12, p=0.001 and women r=0.182, p<0.001) were the variables associated with an elevated IOP in men and women.
Table 3 shows the gender-specific unadjusted analysis for continuous variables associated with IOP in subjects with type 2 diabetes. Factors associated with an elevated IOP included elevated systolic blood pressure (β=0.008, p=0.024), elevated resting pulse rate (β=0.019, p=0.006) and thicker central corneal thickness (β=0.011, p<0.001). Height was associated with a decrease in the IOP (β=-0.024, p=0.008). In men, the factors associated with an elevated IOP included higher resting pulse rate (β=0.021, p=0.04), thicker CCT (β=0.01, p=0.001) and systolic blood pressure (β=0.011, p=0.04); in women, elevated glycosylated hemoglobin (β=0.1, p=0.04) and CCT (β=0.015, p<0.001) were significant factors.
After adjusting the continuous variables associated with IOP in subjects with type 2 diabetes, the factors associated with elevated IOP are included in Table 4 as thicker central corneal thickness (β=0.011, p<0.001) and elevated resting pulse rate (β=0.001, p=0.03); height was associated with a decrease in the IOP (β=-0.028, p=0.008). A thicker central corneal thickness was the single variable associated with an elevated IOP in men and women (men: β=0.01, p=0.002 and women β=0.015, p<0.001).

DISCUSSION

The supplementary Table shows the comparison of the mean IOP in published population-based reports among type 2 diabetes. The mean IOP among diabetics in our study was lower than other studies [2,8,9]. When compared to other races, the IOP in the Asian ethnicity is lower [7,10]. The Barbados Eye Study and the Los Angeles Latino Eye Study, like our study, has also found a higher IOP among women with diabetes [2,11]. However, Kawase et al. [32] did not find any gender difference in IOP. We assume that the increased IOP among women with elevated glycosylated hemoglobin in our study is related to accumulation of fibronectin in trabecular meshwork [12]. Higher prevalence of obesity, hypertension and probably a higher life expectancy can best explain higher IOP among women [11]. Similar to our study, many other studies have reported a higher prevalence of elevated IOP among subjects with hypertension [2-4,11]. Although, the rationale for this is poorly understood, possible reasons could be increased aqueous humor production by ultrafiltration due to the elevated ciliary artery pressure, a generalized increase in the sympathetic tone or elevated serum corticosteroid levels as seen in hypertension subjects [4].
We found a higher IOP among women with CSME. The reason for this is unknown. But, this can probably be explained by a complex interplay between the change in retinal hemodynamics, ocular perfusion, scleral rigidity and hormonal influence among women [33].
We found an inverse relationship between the presence of diabetic neuropathy and IOP. al-Sereiti et al. [13] reported normal IOP among patients with diabetes having autonomic neuropathy. However, one study has shown that autonomic denervation may be a prerequisite of peripheral diabetic neuropathy [34]. It has been postulated that in autonomic neuropathy, the pupil/iris diameter is reduced, which increases the aqueous drainage, reducing the IOP [13].
Similar to previous studies, alcohol has been shown to lower the IOP, possibly through a reduction of net water movement into the eye [35], whereas, smoking was found to increase the IOP, hypothesized to be due to smoking induced degenerative changes in the arteries and increase in blood viscosity [36].
Wu et al. [3] found a positive association between pulse rate and IOP, similar to our study. Even on multivariate analysis after adjusting for variables like age, gender, duration of diabetes, BMI and glycemic control, the association between the resting pulse rate and the IOP remained the same.
Like earlier study [37], the present study also found a negative relationship between height and IOP. However, one study by Bulpitt et al. [4] found no relationship between the two. The height of an individual is related to genetic and acquired factors like status of growth hormone and childhood nutrition [38] which may probably affect the IOP. BMI and IOP being directly proportional, and height being inversely proportional to BMI [19], we can expect a similar inverse relationship between height and IOP.
Earlier study has reported a similar relationship between CCT and IOP among subjects with diabetes [11]. However, as diabetes affects corneal biomechanics, this results in lower corneal hysteresis values than those in healthy control subjects [39]. This may cause clinically relevant high IOP measurements independent of CCT. Also, the GAT gives an accurate intraocular pressure reading for an eye with average CCT, but tends to underestimate or overestimate the true intraocular pressure for thinner and thicker cornea, respectively [11]. Our study confirmed this correlation between increasing IOP and increasing CCT as measured by GAT.
The strength of this study was that it used photography and standard grading techniques. Further, the study was representative of a large population, and the results could be extrapolated to the whole of urban India. One of the limitations of this study was the absence of non-diabetic subjects, including them may have elicited a better relationship between IOP and subjects with DM. Also, in subjects with known DM, a second estimation of blood glucose was not performed; the diagnostic accuracy of the treating diabetologists was relied upon totally. The sample size for this study was calculated for the estimation of the prevalence of diabetic retinopathy in the general population; the power to elucidate associated risk factors in the subgroup analysis may be inadequate. This study does not have any data on progression, as no follow-up is envisaged. These data stress on the need for regular ocular examinations in subjects with type 2 DM in countries like India, especially for smokers and when associated with systemic hypertension. Even the IOP distribution in subjects with type 2 diabetes is gender specific. In conclusion, identifying the risk factors for high IOP in this population will prevent blindness in this vulnerable population.

CONFLICT OF INTEREST

The authors have no conflicts of interest with the material presented in this paper.

Notes

This article is available at http://jpmph.org/.

REFERENCES

1. Vijaya L, George R, Baskaran M, Arvind H, Raju P, Ramesh SV, et al. Prevalence of primary open-angle glaucoma in an urban south Indian population and comparison with a rural population. The Chennai Glaucoma Study. Ophthalmology 2008;115(4):648-654 17664010.
crossref
2. Wu SY, Leske MC. Associations with intraocular pressure in the Barbados Eye Study. Arch Ophthalmol 1997;115(12):1572-1576 9400792.
crossref pmid
3. Klein BE, Klein R, Linton KL. The Beaver Dam Eye Study. Intraocular pressure in an American community. Invest Ophthalmol Vis Sci 1992;33(7):2224-2228 1607232.

4. Bulpitt CJ, Hodes C, Everitt MG. Intraocular pressure and systemic blood pressure in the elderly. Br J Ophthalmol 1975;59(12):717-720 1218183.
crossref pmid pmc
5. Weih LM, Mukesh BN, McCarty CA, Taylor HR. Association of demographic, familial, medical, and ocular factors with intraocular pressure. Arch Ophthalmol 2001;119(6):875-880 11405839.
crossref pmid
6. Chopra V, Varma R, Francis BA, Wu J, Torres M, Azen SP, et al. Type 2 diabetes mellitus and the risk of open-angle glaucoma the Los Angeles Latino Eye Study. Ophthalmology 2008;115(2):227-232 17716734.
crossref pmid
7. Arora VK, Prasad VN. The intraocular pressure and diabetes-a correlative study. Indian J Ophthalmol 1989;37(1):10-12 2807492.

8. Nemesure B, Wu SY, Hennis A, Leske MC. Barbados Eye Studies Group. Factors related to the 4-year risk of high intraocular pressure: the Barbados Eye Studies. Arch Ophthalmol 2003;121(6):856-862 12796259.
crossref pmid
9. Tielsch JM, Katz J, Quigley HA, Javitt JC, Sommer A. Diabetes, intraocular pressure, and primary open-angle glaucoma in the Baltimore Eye Survey. Ophthalmology 1995;102(1):48-53 7831041.
crossref pmid
10. Xu L, Xie XW, Wang YX, Jonas JB. The Beijing Eye Study. Ocular and systemic factors associated with diabetes mellitus in the adult population in rural and urban China. Eye (Lond) 2009;23(3):676-682 18259206.
crossref pmid
11. Memarzadeh F, Ying-Lai M, Azen SP, Varma R. Los Angeles Latino Eye Study Group. Associations with intraocular pressure in Latinos: the Los Angeles Latino Eye Study. Am J Ophthalmol 2008;146(1):69-76 18486096.
crossref pmid pmc
12. Oshitari T, Fujimoto N, Hanawa K, Adachi-Usami E, Roy S. Effect of chronic hyperglycemia on intraocular pressure in patients with diabetes. Am J Ophthalmol 2007;143(2):363-365 17258539.
crossref pmid
13. al-Sereiti MR, Turner P, Gale EA. Intraocular pressure and pupillary responses in patients with diabetes mellitus. Postgrad Med J 1991;67(785):250-251 2062771.
crossref pmid pmc
14. Bankes JL. Ocular tension and diabetes mellitus. Br J Ophthalmol 1967;51(8):557-561 6035958.
crossref pmid pmc
15. Bouzas AG, Gragoudas ES, Balodimos MC, Brinegar CH, Aiello LM. Intraocular pressure in diabetes. Relationship to retinopathy and blood glucose level. Arch Ophthalmol 1971;85(4):423-427 5554870.
crossref pmid
16. Williams BI, Peart WS, Letley E. Abnormal intraocular pressure control in systemic hypertension and diabetic mellitus. Br J Ophthalmol 1980;64(11):845-851 7426555.
crossref pmid pmc
17. Klein BE, Klein R, Moss SE. Intraocular pressure in diabetic persons. Ophthalmology 1984;91(11):1356-1360 6514302.
crossref pmid
18. Dielemans I, de Jong PT, Stolk R, Vingerling JR, Grobbee DE, Hofman A. The Rotterdam Study. Primary open-angle glaucoma, intraocular pressure, and diabetes mellitus in the general elderly population. Ophthalmology 1996;103(8):1271-1275 8764798.
crossref pmid
19. Agarwal S, Raman R, Paul PG, Rani PK, Uthra S, Gayathree R, et al. Sankara Nethralaya-Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS 1): study design and research methodology. Ophthalmic Epidemiol 2005;12(2):143-153 16019696.
crossref pmid
20. Expert Committee on the Diagnosis and Classification of Diabetes Melitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 2003;26(Suppl 1):S5-S20 12502614.

21. Molitch ME, DeFronzo RA, Franz MJ, Keane WF, Mogensen CE, Parving HH, et al. Nephropathy in diabetes. Diabetes Care 2004;27(Suppl 1):S79-S83 14693934.

22. Pradeepa R, Rema M, Vignesh J, Deepa M, Deepa R, Mohan V. Prevalence and risk factors for diabetic neuropathy in an urban south Indian population: the Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med 2008;25(4):407-412 18294224.
crossref
23. Palmberg P. In: Ritch R, Shields MB, Krupin T, editors. Gonioscopy. The glaucomas, vol. I. 1996. 4th ed. St. Louis: Mosby; p. 455-470.

24. Kass MA. Standardizing the measurement of intraocular pressure for clinical research. Guidelines from the Eye Care Technology Forum. Ophthalmology 1996;103(1):183-185 8628552.
crossref pmid
25. Klein R, Klein BE, Magli YL, Brothers RJ, Meuer SM, Moss SE, et al. An alternative method of grading diabetic retinopathy. Ophthalmology 1986;93(9):1183-1187 3101021.
crossref pmid
26. American Diabetes Association. Tests of glycemia in diabetes. Diabetes Care 2000;23(suppl 1):S80-S82 12017687.

27. Nangia V, Jonas JB, Sinha A, Matin A, Kulkarni M, Panda-Jonas S. Ocular axial length and its associations in an adult population of central rural India: the Central India Eye and Medical Study. Ophthalmology 2010;117(7):1360-1366 20363029.
crossref
28. Mohan V, Vijayaprabha R, Rema M, Premalatha G, Poongothai S, Deepa R, et al. Clinical profile of lean NIDDM in South India. Diabetes Res Clin Pract 1997;38(2):101-108 9483373.
crossref pmid
29. Vijaya L, George R, Arvind H, Ve Ramesh S, Baskaran M, Raju P, et al. Central corneal thickness in adult South Indians: the Chennai Glaucoma Study. Ophthalmology 2010;117(4):700-704 20079536.
crossref pmid
31. Fauci AS. Harrison's principles of internal medicine. 2008. 17th ed. New York: McGRaw-Hill; p. 1335.

31. Menon VU, Guruprasad U, Sundaram KR, Jayakumar RV, Nair V, Kumar H. Glycaemic status and prevalence of comorbid conditions among people with diabetes in Kerala. Natl Med J India 2008;21(3):112-115 19004140.

32. Kawase K, Tomidokoro A, Araie M, Iwase A, Yamamoto T, et al. Tajimi Study Group. Ocular and systemic factors related to intraocular pressure in Japanese adults: the Tajimi study. Br J Ophthalmol 2008;92(9):1175-1179 18669541.
crossref pmid
33. Ciulla TA, Harris A, Latkany P, Piper HC, Arend O, Garzozi H, et al. Ocular perfusion abnormalities in diabetes. Acta Ophthalmol Scand 2002;80(5):468-477 12390156.
crossref pmid
34. Ryder RE, Kennedy RL, Newrick PG, Wilson RM, Ward JD, Hardisty CA. Autonomic denervation may be a prerequisite of diabetic neuropathic foot ulceration. Diabet Med 1990;7(8):726-730 2147635.
crossref
35. Harris A, Swartz D, Engen D, Beck D, Evans D, Caldemeyer K, et al. Ocular hemodynamic effects of acute ethanol ingestion. Ophthalmic Res 1996;28(3):193-200 8829177.
crossref pmid
36. Lee AJ, Rochtchina E, Wang JJ, Healey PR, Mitchell P. Does smoking affect intraocular pressure? Findings from the Blue Mountains Eye Study. J Glaucoma 2003;12(3):209-212 12782837.
crossref pmid
37. Carel RS, Korczyn AD, Rock M, Goya I. Association between ocular pressure and certain health parameters. Ophthalmology 1984;91(4):311-314 6717917.
crossref pmid
38. Hellgren G, Andersson B, Nierop AF, Dahlgren J, Hochberg Z, Albertsson-Wikland K. A proteomic approach identified growth hormone-dependent nutrition markers in children with idiopathic short stature. Proteome Sci 2008;6: 35. 19077222.
crossref pmid pmc
39. Sahin A, Bayer A, Ozge G, Mumcuğlu T. Corneal biomechanical changes in diabetes mellitus and their influence on intraocular pressure measurements. Invest Ophthalmol Vis Sci 2009;50(10):4597-4604 19443722.
crossref pmid

Appendices

Appendix.

Comparison of mean IOP in published population-based reports among type 2 diabetes

Study name Country Publication year Ethnicity Gender Age range (y) Age (mean SD) (y) Sample (n) IOP measurement technique IOP (mean SD) (mmHg)
Bankes JL [14] England 1967 Mixed Both ≥40 NA 212 GAT 16.69 ± 3.32
Bouzas AG, et al [15] New England 1971 Mixed Both 51 - 68 NA 56 GAT 15.19 ± 3.15
Williams B, et al [16] England 1980 Mixed Both 25 - 70 53.36±13.3 14 Perkins handheld 18.9 ± 2.25
Wisconsin epidemiologic study [17] USA 1984 Mixed Both 0 to >75 NA 2990 GAT 16.3 ± 4.12
Arora VK, et al [7] India 1989 Asian Males NA NA 46 Schiotz 19.26
al-Sereiti MR, et al [13] England 1991 Mixed Both NA .0040±15 38 Non-contact Pneumotonometer 15.5±3.9
Beaver dam eye study [3] USA 1992 Mixed Both 43 - 84 NA 438 GAT 16.05 ± 3.8
Baltimore eye survey [9] USA 1995 Mixed Both ≥40 NA 714 GAT 17.9 ± 0.24
Rotterdam study [18] Netherland 1996 White Both ≥ 55 55 - 94 256 GAT 14.86 ± 2.91
Barbados eye study [2] West Indies 1997 Mixed Both 40 - 84 58 17 GAT 18.6 ± 3.7
Barbados incidence study of eye diseases [8] West Indies 2003 Mixed Both 40 - 84 057.5 ± 11.5 559 GAT 21.5 ± 4.7
Oshitari T [12] Japan 2007 Japanese Both NA 60.86 ± 10.76 190 GAT 16.0 ± 2.5
Los Angeles Latino eye study [11] USA 2008 Mexicans Both ≥ 40 NA 1416 GAT 15.2 ± 3.3
Beijing eye study [10] China 2009 Chinese Both 45 - 89 060.4 ± 10 381 Non-contact Pneumotonometer 16.14 ± 2.96
Present study India 2010 Asian Both ≥ 40 56.32 ± 10.02 1414 GAT 14.8 ± 2.9

GAT: goldmann applanation tonometry, IOP: intraocular pressure, SD: standard deviation.

Figure 1
Distribution of intraocular pressure in subjects with type 2 diabetes mellitus.
jpmph-44-157-g001.jpg
Table 1.
Distribution of Intraocular pressure in various subgroups among subjects with type 2 diabetes mellitus Mean±SD
Risk factors Over all (n=1377)
Men (n=731)
Women (n=646)
n IOP (mmHg) p n IOP (mmHg) p n IOP (mmHg) p
Mean IOP 14.8 ± 2.9 14.6 ± 2.9 15.0 ± 2.8 0.005
 Demography
  Age (y)
   40 - 49 385 14.7 ± 2.7 0.69 210 14.4 ± 2.6 0.59 175 15.1 ± 2.8 0.94
   50 - 59 494 14.9 ± 2.9 245 14.8 ± 3.1 249 15.1 ± 2.8
   60 - 69 342 14.7 ± 2.9 178 14.6 ± 3.0 164 14.9 ± 2.9
   70 + 156 14.7 ± 2.9 98 14.6 ± 3.1 58 15.0 ± 2.6
  Duration of diabetes (y)
   < 5 799 14.8 ± 2.8 0.51 403 14.7 ± 2.9 0.21 396 14.9 ± 2.7 0.49
   ≥ 5 578 14.7 ± 2.9 328 14.4 ± 2.9 250 15.1 ± 2.9
  Nuclear cataract
   Absent 1011 14.8 ± 0.438 0.44 550 14.6 ± 2.9 0.57 461 15.1 ± 2.8 0.69
   Present 187 15.0 ± 0.439 93 14.8 ± 3.0 94 15.2 ± 2.1
  Alcohol history
   Absent 1074 14.9 ± 2.9 0.002 428 14.8 ± 2.9 0.06 646 15.0 ± 2.8 -
   Present 303 14.4 ± 2.9 303 14.4 ± 2.9 0 -
  Refractive error
   Absent 511 14.8 ± 2.9 0.67 287 14.5 ± 3.0 0.64 224 15.0 ± 2.7 0.93
   Present 866 14.8 ± 2.9 444 14.6 ± 2.9 422 15.0 ± 2.8
  Family history of glaucoma
   Absent 1371 14.8 ± 2.9 0.92 727 14.6 ± 2.9 0.50 224 15.0 ± 2.8 0.39
   Present 6 14.5 ± 2.8 4 13.5 ± 3.0 422 16.5 ± 0.71
  Smoking status
   Non smoker 1106 14.3 ± 2.9 0.001 460 14.3 ± 2.9 0.021 646 15.0 ± 2.8 -
   Smoker 271 14.9 ± 2.9 271 14.8 ± 2.9 0 -
  Insulin
   Non user of insulin 1310 14.8 ± 2.9 0.46 698 14.6 ± 2.9 0.42 612 15.0 ± 2.8 0.87
   User of insulin 67 15.1 ± 3.1 33 15.0 ± 3.3 34 15.1 ± 3.0
Anthropometry
 BMI
  Lean 87 14.2 ± 2.9 0.19 66 14.2 ± 2.9 0.50 21 14.1 ± 3.1 0.38
  Normal 522 14.8 ± 3.0 365 14.7 ± 3.1 157 14.9 ± 2.9
  Overweight 562 14.9 ± 2.7 258 14.5 ± 2.8 304 15.2 ± 2.7
  Obese 206 14.9 ± 2.9 42 14.6 ± 2.8 164 14.9 ± 2.9
 Height (cm)
  ≤ 156 586 15.0 ± 2.7 0.007 652 14.6 ± 2.9 0.95 619 15.1 ± 2.8 0.06
  > 156 791 14.6 ± 2.9 79 14.6 ± 2.8 27 14.0 ± 3.0
 Weight (kg)
  < 57.5 410 14.7 ± 2.9 0.50 208 14.7 ± 3.1 0.08 163 14.8 ± 2.8 0.26
  ≥ 57.5 967 14.8 ± 2.9 523 14.6 ± 2.9 483 15.1 ± 2.8
 Axial length (mm)
  < 22.6 565 14.7 ± 2.9 0.25 257 14.3 ± 2.9 0.03 308 15.0 ± 2.7 0.97
  ≥ 22.6 786 14.9 ± 2.9 465 14.8 ± 2.9 321 15.1 ± 2.9
 Hypertension
  No 499 14.6 ± 2.9 0.03 300 14.4 ± 2.9 0.10 199 14.9 ± 2.8 0.33
  Yes 878 14.9 ± 2.9 431 14.7 ± 2.9 447 15.1 ± 2.8
 Systolic BP (mmHg)
  < 130 401 14.4 ± 2.9 0.001 242 14.1 ± 2.8 0.003 159 14.8 ± 2.9 0.21
  ≥ 130 976 14.9 ± 2.9 489 14.8 ± 2.9 487 15.1 ± 2.8
 Diastolic BP (mmHg)
  < 80 429 14.7 ± 2.9 0.27 241 14.4 ± 2.9 0.17 188 15.0 ± 2.8 0.94
  ≥ 80 948 14.9 ± 2.9 490 14.7 ± 2.9 458 15.0 ± 2.8
Biochemical
 Serum total cholesterol (mg/dL)
  < 200 883 14.7 ± 2.9 0.30 511 14.6 ± 2.9 0.95 372 14.9 ± 2.8 0.36
  ≥ 200 493 14.9 ± 2.8 219 14.6 ± 2.8 274 15.2 ± 2.8
 Serum high density lipoproteins (mg/dL)
  ≥ 60 1327 14.8 ± 2.9 0.56 715 14.6 ± 2.9 0.93 612 15.0 ± 2.8 0.72
  < 60 49 15.0 ± 2.9 15 14.7 ± 3.1 34 15.2 ± 2.8
 Serum triglycerides (mg/dL)
  < 150 848 14.7 ± 2.9 0.37 448 14.5 ± 2.9 0.56 400 14.9 ± 2.7 0.46
  ≥150 528 14.9 ± 2.9 282 14.7 ± 2.9 246 15.1 ± 2.9
 HbA1c (%)
  Normal (< 5.6) 97 14.7 ± 2.9 0.31 49 14.9 ± 3.1 0.72 48 14.5 ± 2.8 0.06
  Good to Fair (5.6 - 8.0) 654 14.7 ± 2.8 346 14.5 ± 2.9 308 14.8 ± 2.7
  Poor (≥ 8.1) 626 14.9 ± 2.9 336 14.6 ± 2.9 290 15.3 ± 2.9
 Albuminuria
  No micro / macroalbuminuria 1123 14.8 ± 2.8 0.43 594 14.6 ± 2.9 0.96 529 14.9 ± 2.7 0.09
  Microalbuminuria 217 15.0 ± 3.1 115 14.5 ± 3.2 102 15.6 ± 2.9
  Macroalbuminuria 37 14.5 ± 2.7 22 14.5 ± 2.9 15 14.5 ± 2.6
 FBS (mg/dL)
  < 126 402 14.8 ± 2.9 0.85 226 14.6 ± 3.1 0.94 176 15.0 ± 2.6 0.97
  ≥ 126 975 14.8 ± 2.9 505 14.6 ± 2.9 470 15.0 ± 2.9
 CCT (microns)
  < 511 466 14.5 ± 2.8 0.002 233 14.3 ± 2.9 0.07 233 14.6 ± 2.7 0.004
  ≥ 511 911 14.9 ± 2.9 498 14.7 ± 2.9 413 15.3 ± 2.8
 Pulse (Beats/min)
  < 80 960 14.6 ± 2.9 < 0.0001 529 14.4 ± 2.9 0.003 431 14.9 ± 2.8 0.06
  ≥ 80 417 15.2 ± 2.8 202 15.1 ± 2.8 215 15.3 ± 2.8
Diabetes complications
 Diabetic retinopathy
  Absent 1130 14.8 ± 2.8 0.44 578 14.6 ± 2.9 0.39 554 15.0 ± 2.7 0.77
  Present 247 14.7 ± 3.1 155 14.2 ± 3.1 92 15.1 ± 3.1
 STDR
  Absent 1333 14.8 ± 2.9 0.54 702 14.6 ± 2.9 0.23 631 15.0 ± 2.7 0.38
  Present 44 14.5 ± 3.1 29 13.9 ± 2.9 15 15.7 ± 3.2
 CSME
  Absent 1361 14.8 ± 2.9 0.29 722 14.6 ± 2.9 0.62 639 15.0 ± 2.8 0.02
  Present 16 15.7 ± 3.1 9 14.1 ± 3.0 7 17.4 ± 2.2
 Diabetic neuropathy
  Absent 1113 14.9 ± 2.8 0.008 581 14.7 ± 2.9 0.06 532 15.1 ± 2.8 0.09
  Present 251 14.4 ± 2.9 146 14.2 ± 2.9 105 14.6 ± 2.9

STDR: sight threatening diabetic retinopathy (severe Nonproliferative diabetic retinopathy, proliferative diabetic retinopathy and clinically significant macular edema), CSME: clinically significant macular edema, HbA1c: glycosylated hemoglobin, BP: blood pressure, CCT: central corneal thickness, BMI: body mass index, FBS: fasting blood sugar.

Table 2.
Correlation with intraocular pressure
Variable r p
Over All
 Age (y) -0.015 0.29
 Duration of diabetes (y) -0.035 0.09
 Weight (Kg) -0.012 0.33
 Height (cm) -0.012 0.004
 Systolic BP (mmHg) 0.061 0.01
 Diastolic BP (mmHg) 0.041 0.06
 Pulse (Beats/min) 0.074 0.003
 CCT (μ) 0.139 <0.001
 Axial Length (mm) 0.026 0.16
 Serum Total cholesterol (mg/dL) 0.047 0.04
 Serum high density lipoproteins (mg/dL) 0.003 0.45
 Serum Triglycerides (mg/dL) 0.021 0.16
 HbA1C (%) 0.035 0.10
 FBS (mg/dL) 0.045 0.04
Men
 Age (y) 0.014 0.35
 Duration of diabetes (y) -0.061 0.05
 Weight (Kg) -0.011 0.38
 Height (cm) -0.029 0.215
 Systolic BP (mmHg) 0.076 0.02
 Diastolic BP (mmHg) 0.057 0.06
 Pulse (Beats/min) 0.076 0.02
 CCT (μ) 0.12 0.00
 Axial length (mm) 0.057 0.06
 Serum total cholesterol (mg/dL) 0.013 0.36
 Serum high density lipoproteins (mg/dL) -0.008 0.41
 Serum triglycerides (mg/dL) 0.027 0.23
 HbA1C (%) -0.003 0.47
 FBS (mg/dL) 0.047 0.10
Women
 Age (y) -0.041 0.14
 Duration of diabetes (y) 0.025 0.26
 Weight (kg) 0.016 0.34
 Height (cm) -0.027 0.24
 Systolic BP (mmHg) 0.029 0.23
 Diastolic BP (mmHg) 0.015 0.35
 Pulse (Beats/min) 0.058 0.01
 CCT (μ) 0.182 <0.001
 Axial length (mm) 0.018 0.33
 Serum total cholesterol (mg/dL) 0.063 0.05
 Serum high density lipoproteins (mg/dL) -0.008 0.41
 Serum triglycerides (mg/dL) 0.037 0.17
 HbA1C (%) 0.08 0.02
 FBS (mg/dL) 0.039 0.16

BP: blood pressure, CCT: central corneal thickness, HbA1c: glycosylated hemoglobin, FBS: fasting blood sugar.

Table 3.
Univariate associations with Intraocular Pressure (IOP) in participants of SN DREAMS 1
Risk factors Unadjusted
β 95% CI
SE p
Lower bound Upper bound
Over All
 Age (y) -0.004 -0.02 0.011 0.008 0.58
 Duration of diabetes (y) -0.016 -0.041 0.008 0.013 0.19
 Weight (Kg) -0.003 -0.017 0.011 0.007 0.66
 Height (cm) -0.024 -0.041 -0.006 0.009 0.008
 Systolic BP (mmHg) 0.008 0.001 0.016 0.004 0.02
 Diastolic BP (mmHg) 0.01 -0.003 0.024 0.007 0.13
 Pulse (Beats/min) 0.019 0.005 0.033 0.007 0.006
 CCT (μ) 0.011 0.007 0.016 0.002 <0.0001
 Axial length (mm) 0.061 -0.062 0.183 0.063 0.33
 Serum total cholesterol (mg/dL) 0.003 0.000 0.007 0.002 0.08
 Serum high density lipoproteins (mg/dL) 0.001 -0.014 0.016 0.008 0.91
 Serum triglycerides (mmg/dL) 0.001 -0.001 0.002 0.001 0.32
 HbA1C (%) 0.045 -0.024 0.115 0.035 0.20
 FBS (mg/dL) 0.002 0.000 0.005 0.045 0.09
Men
 Age (y) 0.004 -0.016 0.024 0.01 0.70
 Duration of diabetes (y) -0.027 -0.058 0.005 0.016 0.10
 Weight (Kg) -0.003 -0.023 0.017 0.01 0.77
 Height (cm) -0.013 -0.044 0.019 0.016 0.43
 Systolic BP (mmHg) 0.011 0.001 0.022 0.005 0.04
 Diastolic BP (mmHg) 0.015 -0.004 0.034 0.01 0.12
 Pulse (Beats/min) 0.021 0.001 0.041 0.01 0.04
 CCT (μ) 0.01 0.004 0.016 0.003 0.001
 Axial length (mm) 0.131 -0.038 0.299 0.086 0.12
 Serum total cholesterol (mg/dL) 0.001 -0.005 0.007 0.003 0.73
 Serum high density lipoproteins (mg/dL) -0.003 -0.025 0.02 0.011 0.82
 Serum triglycerides (mg/dL) 0.001 -0.001 0.003 0.001 0.46
 HbA1C (%) -0.004 -0.102 0.094 0.05 0.99
 FBS (mg/dL) 0.002 -0.001 0.006 0.047 0.20
Women
 Age (y) -0.012 -0.035 0.011 0.012 0.29
 Duration of diabetes (in years) 0.013 -0.027 0.053 0.02 0.53
 Weight (kg) 0.004 -0.015 0.023 0.01 0.68
 Height (cm) -0.013 -0.049 0.023 0.018 0.49
 Systolic BP (mmHg) 0.004 -0.006 0.014 0.005 0.47
 Diastolic BP (mmHg) 0.004 -0.015 0.022 0.009 0.70
 Pulse (Beats/min) 0.014 -0.005 0.032 0.009 0.14
 CCT (μ) 0.015 0.009 0.021 0.003 <0.0001
 Axial length (mm) 0.041 -0.142 0.224 0.093 0.66
 Serum total cholesterol (mg/dL) 0.004 -0.001 0.009 0.003 0.11
 Serum high density lipoproteins (mg/dL) -0.005 -0.026 0.016 0.011 0.63
 Serum triglycerides (mg/dL) 0.001 -0.001 0.004 0.001 0.35
 HbA1C (%) 0.1 0.003 0.197 0.049 0.04
 FBS (mg/dL) 0.002 -0.002 0.005 0.002 0.78

CCT: central corneal thickness, HbA1c: glycosylated hemoglobin, FBS: fasting blood sugar, CI: confidence interval, SE: standard error, SN-DREAMS 1: Sankara Nethralaya-diabetic Retinopathy Epidemiology and Molecular Genetic Study.

Table 4.
Multivariate associations with intraocular pressure (IOP) in participants of SN-DREAMS 1
Risk factors Adjusted
p
Coefficient (β) 95% CI
Standard error Partial r2
Lower bound Upper bound
Over All
 Height (cm) -0.028 -0.048 -0.007 0.01 0.005 0.007
 Pulse (Beats/min) 0.015 0.001 0.029 0.007 0.003 0.03
 CCT (μ) 0.011 0.007 0.016 0.002 0.018 <0.001
 Model r2 0.037 <0.001
Men
 CCT (μ) 0.01 0.004 0.016 0.003 0.014 0.002
 Model r2 0.035 <0.02
Women
 CCT (μ) 0.015 0.008 0.021 0.003 0.031 <0.001
 Model r2 0.052 0.002

CCT: central corneal thickness, CI: confidence interval, SN-DREAMS 1: Sankara Nethralaya-diabetic Retinopathy Epidemiology and Molecular Genetic Study.

The variables adjusted in multiple regression analysis are age, duration of diabetes, weight, height, systolic and diastolic blood pressure, pulse, central corneal thickness, axial length, total serum cholesterol, serum high density lipoproteins, serum triglycerides, glycosylated hemoglobin and fasting blood sugar.

Editorial Office
Graduate School of Public Health, Seoul National University
1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
Tel : +82-2-740-8328   Fax : +82-2-764-8328   E-mail: jpmphe@gmail.com
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © 2019 by Korean Society for Preventive Medicine. All rights reserved.                 powerd by m2community