In total, 4340 older people from the 20 practices had participated in the initial health screen between 1995 and 1999. Three to five years later 1465 participants had died, 252 had moved away and 34 could not be traced. Of the 2875 surviving participants, 2589 (90%) were invited to a vision test, 1807 participated (70%), 670 refused (26%) and 112 (4%) were too ill. The mean age of participants was 83 years (77 to101 years); and the majority were female (64%). Complete data, including a measure of visual acuity and a completed NEI-VFQ, were available for 1785 participants. The prevalence of reduced visual acuity less than 6/12 in the better eye was 33% (n = 585/1785), and 14% (n = 243/1785) for visual impairment (defined as visual acuity less than 6/18 in the better eye). The cause of visual impairment was only available for an unrepresentative minority of participants, and is not considered further.
Table shows the influence of age, gender, social economic status, NEI-VFQ sub-scale and total scores on visual impairment. The likelihood of visual impairment increased sharply with age. Females were more likely than males to be visually impaired even after adjustment for age. There was a weak association with Carstairs Index with those living in less privileged areas being less likely to have visual impairment; the association between Carstairs index and reduced visual acuity was similar but appeared stronger. Of the NEI-VFQ sub-scales, self-reported general health was moderately associated with visual impairment and there was no association with ocular pain. Reporting of problems in the remaining VFQ sub-scales and total scores were strongly related to visual impairment. In a subgroup that responded to questions concerning driving, visual impairment was strongly related to increased difficulties with driving. Associations with worst eye as well as better eye acuity were also examined; in general, associations were similar but weaker (data not presented).
Association between age, gender, social status, NEI-VFQ sub-scale scores and visual impairment
As different sub-scales scores may be inter-related (that is, difficulty with general vision may reflect difficulties with near and/or distance vision) the independent influence of these scores on visual impairment was determined (Table ). After adjustment for demographic and other sub-scale scores, difficulties with general vision, near activities, and social functioning remained associated with visual impairment. Difficulties with dependency and colour vision were of borderline statistical significance.
Association between NEI-VFQ sub-scale scores and visual impairment, adjusted for age, gender, practice and other sub-scale scores listed in the table
The independent influence of visual acuity, binocular status, and differences in visual acuity between eyes on log transformed scores for general vision, near activities, and total VFQ scores was examined using linear regression (Table ). Differences in acuity between eyes were defined as less than or equal to a 0.1 difference in LogMAR acuity (equivalent to a difference in Snellen acuity from 6/9 to 6/12) or greater, and compared to those with equal acuity. Although overall differences in these scores were small (e.g. inter quartile range 83 to 97 for the total score) compared to the possible range of measurement (from 0 to 100), scores were strongly related to differences in visual acuity, binocular or monocular status, and differences in acuity between eyes. To examine the relative contribution of visual acuity, demographic factors, binocularity, and between eye differences in acuity in explaining variation in total VFQ scores, the correlations of determination (R2 values) for different accumulative linear regression models are given in Table . The R2 value gives the proportion of the variability in total scores explained by different exposure variables. For instance, visual acuity alone explains 16% of the variability in the total score. The addition of demographic variables, binocular status, and difference in acuity between eyes results in 27% of the variability being explained (an increase of 19%). Hence, although visual acuity alone, only accounts for less than a fifth of the variability, it appears to be the most important determinant of total VFQ score.
Mean scores (95% CI) by visual acuity (better eye), binocular status, and by between eye differences in visual acuity
Variance in total domain scores explained by visual acuity (better eye), demographic variables, binocular status, and difference in acuity between eyes