Epidemiologic research on environmental chemical exposures and ovarian and endometrial cancers: a systematic review.

Environ ResSep 16, 2026 (epub)

Samantha Ammons, Lydia Marcus Post, Caroline Pruitt et al.

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In 30 seconds

This systematic review and meta-analysis assessed epidemiologic evidence linking environmental chemical exposures with endometrial and ovarian cancer incidence or mortality. It included 145 studies, most commonly cohort studies, with outdoor air pollution and ultraviolet light the most frequently examined exposures. In a meta-analysis of fine particulate matter (PM2.5), there was no evidence of an association with ovarian cancer (HR meta per 5 μg/m³ = 1.02, 95%CI = 0.91-1.13). The pooled endometrial cancer estimate was weakly elevated (HR meta = 1.02, 95%CI = 0.99-1.05).

Key findings

  • The review included 145 studies; 78 (54%) focused only on ovarian cancer, and 58 (40%) used a cohort design.
  • For PM2.5 and ovarian cancer, the pooled estimate across four studies was HR meta per 5 μg/m³ = 1.02, 95%CI = 0.91-1.13.
  • For PM2.5 and endometrial cancer, the pooled estimate across five studies was HR meta = 1.02, 95%CI = 0.99-1.05.

Why it matters

Environmental exposures are plausible cancer risk factors, but the evidence base for ovarian and endometrial cancers remains sparse and uneven. The review’s pooled PM2.5 findings do not show a clear association with ovarian cancer and indicate only a weak elevation for endometrial cancer. The limited investigation of endometrial cancer is particularly relevant given the unexplained rise in incidence in some populations.

What to keep in mind

The review reports substantial heterogeneity in the exposures studied, and the PM2.5 meta-analyses drew on only four ovarian cancer studies and five endometrial cancer studies.

Source

Published in Environ Res. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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