Abstract
Purpose.:
To describe the distribution of ocular perfusion pressure and its relationship with open-angle glaucoma (OAG) in a Malay population.
Methods.:
This was a population-based, cross-sectional study comprising 3280 (78.7% response) ethnic Malays. Intraocular pressure (IOP) was measured with Goldmann applanation tonometry. Systolic and diastolic blood pressure (SBP and DBP) was measured with a digital automatic blood pressure monitor. Mean ocular perfusion pressure (MOPP) = ⅔(mean arterial pressure − IOP), where mean arterial pressure (MAP) = DBP + ⅓(SBP − DBP), systolic perfusion pressure (SPP) = SBP − IOP, and diastolic perfusion pressure (DPP) = DBP − IOP, was calculated. The diagnosis of OAG was based on International Society for Geographical and Epidemiologic Ophthalmology criteria.
Results.:
A total of 3261 persons (mean age, 58.7 ± 11 years, including 131 [4.0%] cases of OAG) were available for analyses. Among persons without glaucoma, the mean ± SD IOP, MOPP, SPP, and DPP were 15.3 ± 3.5, 52.8 ± 9.3, 131.5 ± 23.3, and 64.5 ± 11.3 mm Hg, respectively. Among persons with OAG, the corresponding values were 16.8 ± 5.9, 51.6 ± 10.2, 134.5 ± 24.6, and 61.4 ± 11.5 mm Hg, respectively. In multiple logistic regression models adjusting for IOP, age, sex, and IOP- and BP-lowering treatments, OAG risk was significantly higher in participants with DBP, MOPP, or DPP in the lowest quartile (Q1) than in participants in the highest quartile (Q4) (Q1 vs. Q4: odds ratio [OR], 1.71 [95% confidence interval (CI), 1.04–2.96] for DBP; OR, 1.73 [95% CI, 1.05–3.15] for MOPP; OR, 1.75 [95% CI, 1.02–3.01] for DPP).
Conclusions.:
Low DBP, low MOPP, and low DPP are independent risk factors for OAG in ethnic Malays, providing further evidence of a vascular mechanism in glaucoma pathogenesis across different populations.
A vascular mechanism has been postulated in the pathogenesis of glaucomatous optic nerve damage
1–4 ; specifically, an inadequate or unstable ocular blood supply causes ischemic damage and/or reperfusion injury to the optic nerve tissue and axons. This vascular concept is support by the reported associations of glaucomatous optic neuropathy with arterial hypertension, arterial hypotension, cardiovascular disease, migraines, vasospasm, and other circulation disorders.
1–4
Perfusion pressure, equal to mean blood pressure (BP) minus intraocular pressure (IOP), is an important determinant of ocular blood flow.
4 A decrease in perfusion pressure may significantly decrease the ocular blood flow in the absence of vascular autoregulation.
3–4 Cross-sectional, population-based studies in Baltimore,
5 Bolzano,
6 southern Arizona,
7 and Rotterdam
8 and recently published prospective studies in Barbados
9 and Sweden
10 have shown that lower diastolic perfusion pressure (DPP), defined as diastolic blood pressure (DBP) minus IOP, is an independent risk factor for open-angle glaucoma (OAG), after adjustment for IOP and other risk factors.
11–13 Clinic-based studies have further shown that nonphysiologic nocturnal BP and wider circadian fluctuation in mean ocular perfusion pressure (MOPP) are significantly associated with the development and progression of OAG.
14,15 However, the relationship between perfusion pressure and glaucoma has not been well documented in Asians.
16 As both BP and IOP vary considerably in whites, blacks, and Asians,
17–19 it is probable that the distribution and determinants of perfusion pressure and its relationship with glaucoma is different in Asians.
In the Singapore Malay Eye Study (SiMES),
20 we have reported that the prevalence of OAG in Malays 40 to 80 years of age was 2.5%, similar to that in white populations.
17 However, the mean IOP was 15.3 mm Hg, substantially lower than that in white populations.
11 Furthermore, only 17% of those with OAG had IOP greater than 21 mm Hg.
20 Thus, the identification of vascular risk factors may be of particular relevance to Asians. The purpose of this study was to describe the distribution of perfusion pressure and its relationship with OAG in Malays.
The measurement and definition of glaucoma have been described elsewhere.
20,24,25 Before pupil dilation, Goldmann applanation tonometry (Haag-Streit, Köniz, Switzerland) was used to measure IOP once in each eye (right eye first).
21 Automated perimetry (SITA FAST 24-2, Humphrey Visual Field Analyzer II; Carl Zeiss, Feldbach, Switzerland) was performed with near refractive correction (1) on one in five consecutive participants without suspected glaucoma (
n = 641 persons) before examination by study ophthalmologists and (2) on all participants with suspected glaucoma. Central corneal thickness (CCT) was measured with a handheld ultrasound pachymeter (Advent; Mentor O&O, Norville, OH).
26 After pupil dilation, the optic disc was evaluated with a +78-D lens at ×16 magnification, and the vertical cup-to-disc ratio (VCDR) was determined.
24
Patients with suspected glaucoma all underwent visual field testing and were defined by any of the following criteria: (1) IOP greater then 21 mm Hg; (2) VCDR > 0.6 or VCDR asymmetry >0.2; (3) abnormal anterior segment deposit consistent with pseudoexfoliation or pigment dispersion syndrome; (4) occludable angle, defined as posterior trabecular meshwork seen for 180° or less of the angle circumference during static gonioscopy; (5) peripheral anterior synechiae or other findings consistent with secondary glaucoma; and (6) known history of glaucoma.
Glaucoma cases were classified into three categories, according to ISGEO criteria
20,25 : category 1, optic disc abnormality (VCDR/VCDR asymmetry ≥97.5th percentile or neuroretinal rim width between 11 and 1 o'clock or 5 and 7 o'clock <0.1 VCDR) with a corresponding glaucomatous visual field defect; category 2, a severely damaged optic disc (VCDR or VCDR asymmetry ≥99.5th percentile) in the absence of an adequate visual field test; category 3, no visual field or optic disc data, blindness (corrected visual acuity, <3/60), and prior glaucoma surgery IOP >99.5th percentile. For cases classified as category 1 or 2, there could be no other explanation for the VCDR finding (e.g., dysplastic disc or marked anisometropia) or visual field defect (e.g., branch retinal vein occlusion, macular degeneration, or cerebrovascular disease).
In this study, OAG was diagnosed, after the exclusion of cases of angle-closure, rubeosis or secondary glaucoma (other than pseudoexfoliation). All the participants (including those without visual field data) who were judged not to have definitive glaucoma were classified as nonglaucomatous and were included in our analyses.
Among all 3280 participants, 8 cases of primary angle-closure glaucoma, 8 cases of nonspecific glaucoma, 2 cases of developmental glaucoma, and 1 case of rubeotic glaucoma were excluded, leaving 131 cases of definitive OAG and 3130 persons without glaucoma for further analyses.
Among the 131 persons with OAG, the mean ± SD for IOP, SBP, DBP, MOPP, SPP, and DPP was 16.8 ± 5.9 (median, 16.0), 151.3 ± 24.5 (median, 150.5), 78.3 ± 10.6 (median, 77.0), 51.6 ± 10.2 (median, 52.0), 134.5 ± 24.6 (median, 135.0), and 61.4 ± 11.5 mm Hg (median, 61.0), respectively. The mean deviation (MD) and pattern SD (PSD) were −10.6 and 8.4 dB, respectively. Of the 131 patients, 94 (71.8%) had systemic hypertension (34/94 cases were on antihypertension treatment). Only nine patients had IOP-lowering treatment, probably because more than 90% of them had been undiagnosed.
20
Among the 3130 persons without glaucoma, the mean ± SD for IOP, SBP, DBP, MOPP, SPP, and DPP was 15.3 ± 3.5 (median, 15.0), 146.9 ± 23.7 (median, 144.0), 79.8 ± 11.2 (median, 78.0), 52.8 ± 9.3 (median, 51.6), 131.5 ± 23.3 (median, 128.5), and 64.5 ± 11.3 mm Hg (median, 63.0 mm Hg), respectively. Of these, 2138 (68.3%) had systemic hypertension (669/2138 were on antihypertension treatment). MOPP and SPP increased with age (both
P < 0.001), whereas DPP was not related to age (
P = 0.59,
Fig. 1). Men tended to have higher MOPP and higher DPP, but lower SPP, than did women (
t-test, both
P < 0.05).
In multivariate logistic regression models treating the BP-related factors as categorical variables and added to the model, one at a time, lower DBP (OR, 1.71; 95% CI, 1.04–2.96, comparing persons in the lowest quartile with those in highest quartile [Q1 vs. Q4] of DBP), lower MOPP (OR, 1.73; 95% CI, 1.05–3.15; [Q1 vs. Q4]) and lower DPP (OR, 1.75; 95% CI, 1.02–3.01; [Q1 vs. Q4]) were significantly associated with OAG risk (
Tables 1,
2). When we treated the BP-related factors as continuous variables and added them to the model one at a time, the multivariate-adjusted ORs were the same (OR, 1.22) for every 10-mm Hg decrease in DBP (
P = 0.02), MOPP (
P = 0.058), and DPP (
P = 0.02). SBP, MAP, and SPP were not associated with OAG (all
P > 0.05). Perfusion pressure and IOP were not collinear (the CIs for both variables were narrow, data not shown, and the VIFs for the models were ∼1.0–1.2;
Tables 1,
2).
Table 1. Association of MOPP with OAG
Table 1. Association of MOPP with OAG
| MOPP (mm Hg), Quartiles | P for Trend | VIF |
Q4 | Q3 | Q2 | Q1 |
All persons | | | | | | |
n cases/n at risk* | 29/780 | 38/772 | 22/782 | 42/776 | | |
Values, mm Hg | >58 | 51–58 | 46–51 | ≤46 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.57 (0.93–2.64) | 0.95 (0.53–1.72) | 1.73 (1.05–3.15) | 0.01 | 1.06 |
Age groups | | | | | | |
Younger (<60 y) | | | | | | |
n cases/n at risk* | 7/432 | 11/420 | 7/440 | 16/423 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.58 (0.59–4.20) | 1.09 (0.37–3.15) | 2.51 (0.99–6.36) | 0.04 | 1.06 |
Older (≥60 years) | | | | | | |
n cases/n at risk* | 15/354 | 26/344 | 23/346 | 26/351 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.95 (0.97–3.92) | 1.79 (0.88–3.64) | 1.55 (0.75–3.22) | 0.09 | 1.04 |
Sex | | | | | | |
Male | | | | | | |
n cases/n at risk* | 20/371 | 22/359 | 11/386 | 22/375 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.41 (0.74–2.71) | 0.64 (0.29–1.41) | 1.12 (0.56–2.27) | 0.50 | 1.07 |
Female | | | | | | |
n cases/n at risk* | 9/408 | 15/404 | 13/405 | 19/402 | | |
OR (95% CI) of OAG | 1.00 (reference) | 2.28 (0.92–5.66) | 2.03 (0.79–5.26) | 3.26 (1.30–8.14) | 0.007 | 1.07 |
IOP status | | | | | | |
Low, <16 mm Hg | | | | | | |
n cases/n at risk* | 13/419 | 20/420 | 14/421 | 13/425 | | |
OR (95% CI) of OAG | 1.00 (reference) | 2.10 (0.97–4.51) | 1.63 (0.72–3.68) | 1.91 (0.82–4.47) | 0.22 | 1.06 |
High, ≥16 mm Hg | | | | | | |
n cases/n at risk* | 17/355 | 17/358 | 10/364 | 27/348 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.11 (0.54–2.29) | 0.55 (0.23–1.32) | 1.60 (0.80–3.20) | 0.05 | 1.06 |
Table 2. Association of DPP with OAG
Table 2. Association of DPP with OAG
| DPP (mmHg), Quartiles | P for Trend | VIF |
Q4 | Q3 | Q2 | Q1 |
All persons | | | | | | |
n cases/n at risk* | 22/757 | 29/794 | 34/750 | 46/809 | | |
Values, mmHg | >71 | 63–71 | 56–63 | ≤56 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.30 (0.74–2.30) | 1.57 (0.90–2.74) | 1.75 (1.02–3.01) | 0.002 | 1.08 |
Age groups | | | | | | |
Younger, <60 y | | | | | | |
n cases/n at risk* | 6/418 | 9/426 | 10/437 | 16/434 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.38 (0.47–4.04) | 1.70 (0.61–4.76) | 2.55 (0.96–6.78) | 0.02 | 1.10 |
Older, ≥60 y | | | | | | |
n cases/n at risk* | 16/352 | 22/345 | 22/323 | 30/375 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.44 (0.74–2.81) | 1.45 (0.74–2.86) | 1.48 (0.76–2.86) | 0.07 | 1.07 |
Sex | | | | | | |
Male | | | | | | |
n cases/n at risk* | 16/356 | 16/377 | 17/385 | 26/373 | | |
OR (95% CI) of OAG | 1.00 (reference) | 0.89 (0.43–1.83) | 0.93 (0.46–1.89) | 1.02 (0.52–2.02) | 0.28 | 1.06 |
Female | | | | | | |
n cases/n at risk* | 7/388 | 14/408 | 15/402 | 20/421 | | |
OR (95% CI) of OAG | 1.00 (reference) | 2.10 (0.82–5.35) | 2.31 (0.92–5.84) | 2.53 (1.03–6.24) | 0.02 | 1.06 |
IOP status | | | | | | |
Low, <16 mm Hg | | | | | | |
n cases/n at risk* | 10/410 | 13/434 | 16/419 | 21/422 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.32 (0.57–3.06) | 1.61 (0.71–3.64) | 2.42 (1.10–5.31) | 0.03 | 1.07 |
High, ≥16 mm Hg | | | | | | |
n cases/n at risk* | 12/340 | 17/362 | 17/373 | 25/349 | | |
OR (95% CI) of OAG | 1.00 (reference) | 1.46 (0.67–3.14) | 1.31 (0.61–2.84) | 1.46 (0.68–3.11) | 0.07 | 1.09 |
In a logistic regression model adjusting for age, sex, IOP, and IOP- and BP-lowering treatment, the OR of OAG was 0.61 (95% CI, 0.38–0.97; P = 0.02) in persons with systemic hypertension. The significant association remained (OR, 0.61; P = 0.048) when SBP was included in the model, but the significance disappeared (P > 0.05) when DBP or MBP was included. Including SBP, DBP, or MBP in the models did not improve the VIFs (range, 1.0–1.2).
The association between DPP and OAG was stronger in younger persons (Q1 vs. Q4; OR, 2.55;
P = 0.02) than in older persons (Q1 vs. Q4; OR, 1.48;
P = 0.07), in lower IOP (Q1 vs. Q4; OR, 2.42;
P = 0.03) than in higher IOP (Q1 vs. Q4; OR, 1.46;
P = 0.07), and in women (Q1 vs. Q4; OR, 2.53;
P = 0.02) than in men (Q1 vs. Q4; OR, 1.02;
P = 0.28;
Table 2). Similar associations were found between MOPP and OAG (
Table 1).
To explore the possible nonlinear relationship of DPP and IOP with OAG risk, we implemented a GAM model with the Loess smoothing function in R.
29 The Akaike information criterion (AIC) was used to assist in selecting explanatory variable terms. The starting GAM model included IOP, DPP, age, sex, and IOP- and BP-lowering treatment as explanatory variables and prevalence of OAG as the responder. Any explanatory variable could be excluded if its exclusion would result in a better fit. In addition, every continuous explanatory variable (IOP, DPP, or age) could be fitted with either a linear function or a Loess smoothing function. As a result, the final best-fit GAM model (AIC = 1023.27,
df = 6.73) for our data included IOP (Loess smoothing function, span = 0.9), DPP (linear function), age (linear function), and sex (binary factor) as explanatory variables.