Tea Consumption and Smoking Associations with Biological Aging Among Oilfield Workers

Data Sheet 1_Combined associations of tea consumption and smoking with accelerated biological aging among oilfield workers.pdf contains results from a study examining the individual and combined effects of tea consumption and cigarette smoking on accelerated biological aging, measured via the PhenoAge algorithm. The study, authored by Bowei Yang and published on figshare in June 2026, used logistic regression and interaction analyses on a cohort of oilfield workers, reporting odds ratios and confidence intervals. The dataset likely contains tabular data summarizing these statistical associations.

Use Cases

• Modeling the combined risk of tea consumption and smoking on biological aging based on reported odds ratios.
• Investigating interaction effects (additive and multiplicative) between lifestyle factors described in the study.
• Stratifying health risk analyses by occupational context, such as shift work status, as mentioned in the results.
• Benchmarking the PhenoAge algorithm's application in specific occupational populations like oilfield workers.

Strengths

• The study reports specific statistical results, including odds ratios (e.g., OR = 1.81 for smoking) and 95% confidence intervals.
• Analysis includes stratified results by shift work status and interaction metrics (RERI, AP, S).
• The dataset is published under a CC-BY-4.0 license, permitting open reuse with attribution.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (173.9 KB), suggesting limited scope, possibly containing only summary statistics.

Provenance

Source

Bowei Yang via figshare.

Collection Method

Logistic regression analysis of survey or clinical data from oilfield workers.

Freshness

Last updated 2026-06-03 04:47:27; freshness should be verified.