Increasing Prevalence of Myopia in Europe and the Impact of Education

PURPOSE: To investigate whether myopia is becoming more common across Europe and explore whether increasing education levels, an important environmental risk factor for myopia, might explain any temporal trend.

DESIGN: Meta-analysis of population-based, cross-sectional studies from the European Eye Epidemiology (E(3)) Consortium.

PARTICIPANTS: The E(3) Consortium is a collaborative network of epidemiological studies of common eye diseases in adults across Europe. Refractive data were available for 61 946 participants from 15 population-based studies performed between 1990 and 2013; participants had a range of median ages from 44 to 78 years.

METHODS: Noncycloplegic refraction, year of birth, and highest educational level achieved were obtained for all participants. Myopia was defined as a mean spherical equivalent ≤-0.75 diopters. A random-effects meta-analysis of age-specific myopia prevalence was performed, with sequential analyses stratified by year of birth and highest level of educational attainment.

MAIN OUTCOME MEASURES: Variation in age-specific myopia prevalence for differing years of birth and educational level.

RESULTS: There was a significant cohort effect for increasing myopia prevalence across more recent birth decades; age-standardized myopia prevalence increased from 17.8% (95% confidence interval [CI], 17.6-18.1) to 23.5% (95% CI, 23.2-23.7) in those born between 1910 and 1939 compared with 1940 and 1979 (P = 0.03). Education was significantly associated with myopia; for those completing primary, secondary, and higher education, the age-standardized prevalences were 25.4% (CI, 25.0-25.8), 29.1% (CI, 28.8-29.5), and 36.6% (CI, 36.1-37.2), respectively. Although more recent birth cohorts were more educated, this did not fully explain the cohort effect. Compared with the reference risk of participants born in the 1920s with only primary education, higher education or being born in the 1960s doubled the myopia prevalence ratio-2.43 (CI, 1.26-4.17) and 2.62 (CI, 1.31-5.00), respectively-whereas individuals born in the 1960s and completing higher education had approximately 4 times the reference risk: a prevalence ratio of 3.76 (CI, 2.21-6.57).

CONCLUSIONS: Myopia is becoming more common in Europe; although education levels have increased and are associated with myopia, higher education seems to be an additive rather than explanatory factor. Increasing levels of myopia carry significant clinical and economic implications, with more people at risk of the sight-threatening complications associated with high myopia.

Prevalence of germ-line mutations in p16, p19ARF, and CDK4 in familial melanoma:analysis of a clinic-based population

Five to ten percent of individuals with melanoma have another affected family member, suggesting familial predisposition. Germ-line mutations in the cyclin-dependent kinase (CDK) inhibitor p16 have been reported in a subset of melanoma pedigrees, but their prevalence is unknown in more common cases of familial melanoma that do not involve large families with multiple affected members. We screened for germ-line mutations in p16 and in two other candidate melanoma genes, p19ARF and CDK4, in 33 consecutive patients treated for melanoma; these patients had at least one affected first or second degree relative (28 independent families). Five independent, definitive p16 mutations were detected (18%, 95% confidence interval: 6%, 37%), including one nonsense, one disease-associated missense, and three small deletions. No mutations were detected in CDK4. Disease-associated mutations in p19ARF, whose transcript is derived in part from an alternative codon reading frame of p16, were only detected in patients who also had mutations inactivating p16. We conclude that germ-line p16 mutations are present in a significant fraction of individuals who have melanoma and a positive family history.

Prevalence of the factor VR506Q mutation in two Irish control populations:use of a novel nested polymerase chain reaction approach

The prevalence of factor V (FV) Leiden among normal populations has primarily been determined using blood donors. This control group is carefully selected and therefore may not accurately reflect the true prevalence within the population. We assessed the prevalence of FV Leiden within the Irish population using Guthrie card samples randomly selected from all newborns. We compared this result with the prevalence of FV Leiden within blood donors. A novel nested polymerase chain reaction (PCR) method for FV Leiden was developed for analysis of the Guthrie card samples. There was no significant difference between the allele frequency within the Guthrie card samples and blood donors (2.07% vs. 2.35%, P = 0.66)

Prevalence of the prothrombin G20210A mutation in the Irish populations:use of a novel polymerase chain reaction approach

The prothrombin G20210A polymorphism is associated with a threefold-increased risk of venous thrombosis. There is considerable variation in the reported prevalence of this polymorphism within normal populations, ranging from 0 to 6.5%. The prevalence within the Irish population has not been determined. A restriction fragment length polymorphism (RFLP)-based assay is commonly used for the detection of the prothrombin 20210A allele. This assay does not include a control restriction digest fragment and, consequently, failure of the enzyme activity or lack of addition of enzyme to the sample cannot be distinguished from wild-type prothrombin. We developed a RFLP-based assay, which incorporates an invariant digest site, resulting in the generation of a control digest fragment. Furthermore, we developed a nested polymerase chain reaction (PCR) method for the amplification and digestion of poor-quality or low-concentration DNA. In the Irish population studied, five of 385 (1.29%) were heterozygous and one patient was homozygous for the prothrombin 20210A polymorphism. This is the first reported data on an Irish or Celtic population and suggests that the allele frequency is similar to Anglo-Saxon populations. The nested PCR method successfully amplified and digested 100/100 (100%) of the archived samples; none of these samples could be analyzed by the standard single-round PCR method. In conclusion, nested PCR should be considered in the analysis of archived samples. Single-round PCR is appropriate for recently collected samples; however, an invariant control digest site should be incorporated in RFLP-based assays to validate the integrity of the digestion enzyme and limit the risk of false-negative results.

Using interviewer random effects to remove selection bias from HIV prevalence estimates

Background: Selection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results. Methods: The identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated. Results: Using nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive. Conclusions: Our approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

On the Assumption of Bivariate Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence

Background: Heckman-type selection models have been used to control HIV prevalence estimates for selection bias when participation in HIV testing and HIV status are associated after controlling for observed variables. These models typically rely on the strong assumption that the error terms in the participation and the outcome equations that comprise the model are distributed as bivariate normal.
Methods: We introduce a novel approach for relaxing the bivariate normality assumption in selection models using copula functions. We apply this method to estimating HIV prevalence and new confidence intervals (CI) in the 2007 Zambia Demographic and Health Survey (DHS) by using interviewer identity as the selection variable that predicts participation (consent to test) but not the outcome (HIV status).
Results: We show in a simulation study that selection models can generate biased results when the bivariate normality assumption is violated. In the 2007 Zambia DHS, HIV prevalence estimates are similar irrespective of the structure of the association assumed between participation and outcome. For men, we estimate a population HIV prevalence of 21% (95% CI = 16%–25%) compared with 12% (11%–13%) among those who consented to be tested; for women, the corresponding figures are 19% (13%–24%) and 16% (15%–17%).
Conclusions: Copula approaches to Heckman-type selection models are a useful addition to the methodological toolkit of HIV epidemiology and of epidemiology in general. We develop the use of this approach to systematically evaluate the robustness of HIV prevalence estimates based on selection models, both empirically and in a simulation study.