Prevalence and epidemiological characteristics of congenital cataract: a systematic review and meta-analysis

Abstract

Congenital cataract (CC) is the primary cause of treatable childhood blindness worldwide. The establishment of reliable, epidemiological estimates is an essential first step towards management strategies. We undertook an initial systematic review and meta-analysis to estimate the prevalence and other epidemiological characteristics of CC. PubMed, Medline, Web of Science, Embase, and Cochrane Library were searched before January 2015. A meta-analysis with random-effects model based on a proportions approach was performed to determine the population-based prevalence of CC and to describe the data regarding the laterality, morphology, associated comorbidities and etiology. Heterogeneity was analyzed using the meta-regression method, and subgroup analyses were performed. 27 studies were selected from 2,610 references. The pooled prevalence estimate was 4.24 per 10,000 people, making it a rare disease based on WHO standards. Subgroup analyses revealed the highest CC prevalence in Asia, and an increasing prevalence trend through 2000. Other epidemiological characteristics showed CC tended to be bilateral, isolated, hereditary and in total/nuclear morphology. Huge heterogeneity was identified across most estimates (I(2) > 75%). Most of the variations could be explained by sample size, research period and age at diagnosis. The findings provide suggestions for etiology of CC, improvements in screening techniques and development of public health strategies.

Figure 1. Flowchart of study selection process.

Figure 2. Forest plot for the prevalence of CC in population-based studies.

Figure 3. Publication bias testing for population-based CC prevalence studies.

(a) Funnel plots. Each point represents a separate study on the indicated association. The vertical line represents the mean effect size. The points are distributed asymmetrically, indicating the existence of publication bias. (b) Linear regression test of funnel plot asymmetry (Egger test). The intercept indicating bias is 3.07. P-value = 0.21, indicating insignificant publication bias.

Figure 4. Forest plots for the subgroup analysis of population-based CC prevalence.

(a) Forest plot of the subgroup analysis by world region. (b) Forest plot of the subgroup analysis by research period. (c) Forest plot of the subgroup analysis by age at diagnosis. (d) Forest plot of the subgroup analysis by sample size. (e) Forest plot of the subgroup analysis by study design.