Meta analysis of the prevalence of DED in different latitude intervals
Description
The cause of DED is unclear, and there is a high degree of variability in global prevalence. To date, a latitudinal gradient effect has been identified for several ocular diseases, but the relationship between latitude and DED prevalence is unclear. The aim of this study was to provide a comprehensive understanding of the differences in the prevalence of DED among populations at different latitudes and regions of the world through meta-analysis. According to the preferred reporting items of the PRISMA2020 guidelines, we searched the PubMed, Embase, Cochrane, and Web of Science databases for prevalence reports on DED, and finally screened 34 articles according to the inclusion and exclusion criteria, and extracted data from the articles as follows: the name of the researcher, date of publication of the literature, period of the study (specific years and months), region of the study, type of study (population- and healthcare system-based epidemiological study, or a single-institution clinic-based or hospital-based study), specific information about the study population (mean age, gender, ethnicity), prevalence rate, and total number of people with the disease.后。All statistical data analyses were performed in the STATA software (version 12.0) using the metan, metarag, and metafor packages.
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The prevalence rate belongs to a binomial distribution, so the variance was determined using the binomial distribution formula. To quantify variance heterogeneity, random-effect models were fitted using the constrained maximum-likelihood estimation approach, and 95% confidence intervals for summary measures were computed using the Knapp-Hartung variance estimator. Inconsistency was evaluated using the I2 statistic, which describes the fraction of variation ascribed to between-sample heterogeneity, with values greater than 75% indicating significant heterogeneity. The Begg and Egger's test and related Funnel plots were used with a significance threshold of 0.05 to assess the publication bias because of the large number of samples included in the study. All statistical data analyses were performed in the STATA software (version 12.0) using the metan, metarag, and metafor packages.