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        <datestamp>2026-10-01T04:30:20Z</datestamp>
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          <dc:title>Supplementary file 1_Air pollution exposure and cataract outcomes: a systematic review and pollutant-specific meta-analysis.docx</dc:title>
          <dc:creator>Bin Zhang (64682)</dc:creator>
          <dc:creator>Bing Xu (69508)</dc:creator>
          <dc:creator>Kasra Pakdaman (22916128)</dc:creator>
          <dc:subject>Foetal Development and Medicine</dc:subject>
          <dc:subject>environmental ophthalmology</dc:subject>
          <dc:subject>environmental risk factors</dc:subject>
          <dc:subject>lens opacity</dc:subject>
          <dc:subject>ocular epidemiology</dc:subject>
          <dc:subject>traffic emissions</dc:subject>
          <dc:description>Background&lt;p&gt;Air pollution is increasingly recognized as a potentially modifiable environmental determinant of age-related ocular disease, but its association with cataract remains incompletely characterized. Epidemiological evidence remains heterogeneous across pollutants and study methods, although emerging experimental findings support biological plausibility for pollution-related lens injury.&lt;/p&gt;Objectives&lt;p&gt;To systematically evaluate the epidemiologic evidence linking air-pollution exposure with cataract-related outcomes and to quantitatively synthesize pollutant-specific associations where sufficiently comparable data were available.&lt;/p&gt;Methods&lt;p&gt;PubMed, Embase, Scopus, Web of Science, and Google Scholar were searched through August 10, 2026 for observational studies reporting cataract-specific associations with specific air pollutants. Risk of bias was assessed using ROBINS-E for longitudinal follow-up studies and the WHO air-quality epidemiology instrument for cross-sectional and aggregate studies. Comparable hazard ratios (HRs) were synthesized using restricted maximum-likelihood random-effects models in Stata 18, with Knapp–Hartung sensitivity analyses.&lt;/p&gt;Results&lt;p&gt;Fifteen studies were included in the systematic review, of which seven contributed to at least one meta-analysis. The pooled HR was 1.036 (95% CI, 0.988–1.086) per 1 µg/m&lt;sup&gt;3&lt;/sup&gt; increase in PM₂.₅, 1.041 (95% CI, 1.013–1.070) per 10 µg/m&lt;sup&gt;3&lt;/sup&gt; increase in NO₂, and 1.010 (95% CI, 0.983–1.038) per study-specific interquartile-range increase in black carbon. Heterogeneity was substantial for PM₂.₅ (I&lt;sup&gt;2&lt;/sup&gt; = 99.68%) and NO₂ (I&lt;sup&gt;2&lt;/sup&gt; = 86.04%) but lower for black carbon (I&lt;sup&gt;2&lt;/sup&gt; = 33.41%). The highest-versus-lowest quartile analysis also showed a positive association for NO₂ (HR, 1.094; 95% CI, 1.057–1.133; I&lt;sup&gt;2&lt;/sup&gt; = 0.11%), whereas corresponding PM₂.₅ and PM₁₀ estimates were not statistically significant. Knapp–Hartung adjustment widened the NO₂ confidence intervals, indicating sensitivity to the small number of contributing studies.&lt;/p&gt;Conclusion&lt;p&gt;NO₂ showed the most consistent association with cataract outcomes, whereas evidence for PM₂.₅ remained heterogeneous and that for black carbon was limited. Although these findings support further investigation of traffic-related and other ambient pollution mixtures in cataract epidemiology, the sensitivity of NO₂ estimates to small-study inference precludes firm causal conclusions. Independent prospective studies with improved exposure assessment and standardized cataract phenotyping are needed.&lt;/p&gt;Systematic Review Registration&lt;p&gt;https://www.crd.york.ac.uk/PROSPERO/recorddashboard#, identifier CRD420261509514.&lt;/p&gt;</dc:description>
          <dc:date>2026-10-01T04:30:20Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fmed.2026.1969759.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Supplementary_file_1_Air_pollution_exposure_and_cataract_outcomes_a_systematic_review_and_pollutant-specific_meta-analysis_docx/34038150</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
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