Both our analysis and that of Sperduto et al.
4 draw on
NHANES data, yet prevalences calculated in
Table 1 are generally higher
by approximately 7 to 10 percentage points than those reported by
Sperduto et al.
4 There are three sources of missing data
in NHANES that may be responsible for these differences. Only 35 groups
of subjects of the planned 65 groups, or stands, received eye
examinations.
5 Medical history data for the full 65-stand
sample used in
Table 1 and the 35-stand subsample are very consistent,
however, resulting in similar estimates of the percentage wearing a
correction. Within the 35-stand sample, 27.2% of subjects were not
examined.
5 It was assumed that matching for age, sex,
race, and income class replaced missing data in an unbiased fashion. A
third source of missing data occurred because approximately 15% of
subjects either had missing data or wore no glasses, had acuity from
20/25 to 20/40 that improved with a pinhole, did not undergo
measurement of refractive error, and were therefore excluded from the
analysis. Roughly 4% of subjects had insufficient refractive
data,
5 placing perhaps 11% of subjects in the latter
category. Bias from excluding subjects who would be expected to have
low degrees of myopia was reported to be small, estimated at
approximately 1%, but the authors acknowledge that “there is no
substitute for complete ascertainment.”
4 Any of these
people who had glasses but did not bring them to the examination would
have been included as glasses wearers in the NHANES medical history and
as myopes in our analysis of NHANES data but would have been excluded
by Sperduto et al.
4 Additionally, the roughly 4% of
subjects with insufficient refractive data represent between 7.5% and
18.9% of subjects known to wear a correction.
5 Again,
these people would be represented as glasses wearers in our analysis
but would have been excluded by Sperduto et al.
4 It is
difficult to estimate the precise impact of these missing data, but it
may in part account for the 7- to 10-percentage-point difference seen
in
Figure 1 . It is encouraging that these data follow a pattern similar
to those from Sperduto et al.
4 We therefore assume that
scaling the data relative to the prevalence in a reference group
results in an unbiased picture of change as a function of age,
regardless of the source of the differences in prevalence for any one
age group.