Table 1_Longitudinal associations between PM2.5 with gestational diabetes mellitus mediate

Shanshan Mei's dataset from the PMDAPO cohort in Guangzhou, China, contains longitudinal data from 1,248 pregnant women. It explores associations between PM2.5 exposure, gut microbiota dysbiosis, blood metabolites, circular RNAs, and gestational diabetes mellitus risk. The data was last updated on March 18, 2026.

Use Cases

• Modeling the mediating effect of specific gut bacteria on PM2.5 and blood glucose associations based on identified genera like Solobacterium and Fusicatenibacter.
• Analyzing correlations between GDM-associated metabolites (e.g., sphinganine-1-phosphate) and gut microbiota composition.
• Investigating the interaction network involving circRNAs, metabolites, and microbiota in pathways like sphingolipid metabolism.
• Assessing exposure-response relationships between station-monitored PM2.5 levels and clinical GDM outcomes.

Strengths

• Data is from a prospective cohort of 1,248 participants, providing a substantial sample size for analysis.
• Integrates multiple data types: 16S rRNA sequencing for microbiota, non-targeted metabolomics, and RT-qPCR for circRNAs.
• Uses longitudinal associations to study the progression of gestational diabetes mellitus.

Limitations

• Lifestyle factors (diet, physical activity) and residential mobility were not measured, which may contribute to residual confounding.
• Fecal microbiota was assessed at a single time point in mid-pregnancy, limiting causal inference about temporal dynamics.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

figshare, author Shanshan Mei.

Collection Method

Data collected from the Pregnancy Metabolic Disease and Adverse Pregnancy Outcome (PMDAPO) cohort; exposure levels from nearest monitoring stations.

Time Range

null

Freshness

Last updated 2026-03-18 07:44:09; freshness should be verified.

Geography

Guangzhou, China.