Skip to main content
CORESTA Meeting, Smoke Science/Product Technology, 2019, Hamburg, ST 45

Meta-analysis of two biomarkers of exposure of tobacco products

AYALA-FIERRO F.(1); ELAMIN A.(2); FROST-PINEDA K.(3); JIN T.(3); PRASAD G.L.(3); SARKAR M.(4); SCHMIDT E.(3); VERRON T.(5)
(1) ITG Brands LLC, Greensboro, NC, U.S.A.; (2) PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland; (3) RAI Services Company, Winston-Salem, NC, U.S.A.; (4) Altria Client Services LLC, Richmond, VA, U.S.A.; (5) SEITA - Imperial Brands, Paris, France

In the context of tobacco products, broadly two types of biomarkers exist, biomarkers of exposure (BoE) and biomarkers of potential harm (BoPH). BoE measure exposure to tobacco constituents, e.g. carbon monoxide (CO) and nicotine equivalents (NEQs). The purpose of the study (a project of the CORESTA Biomarkers Sub-Group) was to establish population level estimates for biomarkers of cigarette smoke exposure to serve as a baseline against change in exposure. A meta-analysis of data published 2008-2018 was conducted to estimate population levels for blood carboxyhemoglobin (COHb) and urinary NEQs.

A protocol for literature assessment was developed, followed by an evidence-based table to identify and select studies. The data template identified elements in four major categories: Labels, Design, Results and Demographics.

A total of 28 scientific articles met the pre-set criteria for COHb; 18 articles published by tobacco companies and ten by academia. By comparison only nine articles met the criteria for NEQs, and these were from tobacco companies. The database was organized by categories, filtered, and data weighted according to the size of the groups.

Much of the data for COHb was derived from smokers (19282) followed by never smokers (NS, 1949) and former smokers (FS, 278). Not surprisingly, smokers had the highest %COHb (5.22 %) compared to FS (1.75 %) and NS (1.05 %). Taking into account the spread of the data, only two groups were significantly different for %COHb: smokers vs NS and FS.

For NEQ the majority of data was from smokers (1506) followed by NS (129) and FS (129). Smokers had the highest %NEQ (14.14 %) compared to FS (0.68 %) and NS (0.06 %). Taking into account the spread of the data, only two groups were significantly different for %NEQ: smokers vs NS and FS.

In summary, baseline exposure for smokers is significantly different from NS and from FS, but FS are not significantly different from NS.