RT Journal Article
SR Electronic
T1 Estimation of the global burden of mesothelioma deaths from incomplete national mortality data
JF Occupational and Environmental Medicine
JO Occup Environ Med
FD BMJ Publishing Group Ltd
SP 851
OP 858
DO 10.1136/oemed-2017-104298
VO 74
IS 12
A1 Odgerel, Chimed-Ochir
A1 Takahashi, Ken
A1 Sorahan, Tom
A1 Driscoll, Tim
A1 Fitzmaurice, Christina
A1 Yoko-o, Makoto
A1 Sawanyawisuth, Kittisak
A1 Furuya, Sugio
A1 Tanaka, Fumihiro
A1 Horie, Seichi
A1 Zandwijk, Nico van
A1 Takala, Jukka
YR 2017
UL http://oem.bmj.com/content/74/12/851.abstract
AB Background Mesothelioma is increasingly recognised as a global health issue and the assessment of its global burden is warranted.Objectives To descriptively analyse national mortality data and to use reported and estimated data to calculate the global burden of mesothelioma deaths.Methods For the study period of 1994 to 2014, we grouped 230 countries into 59 countries with quality mesothelioma mortality data suitable to be used for reference rates, 45 countries with poor quality data and 126 countries with no data, based on the availability of data in the WHO Mortality Database. To estimate global deaths, we extrapolated the gender-specific and age-specific mortality rates of the countries with quality data to all other countries.Results The global numbers and rates of mesothelioma deaths have increased over time. The 59 countries with quality data recorded 15 011 mesothelioma deaths per year over the 3 most recent years with available data (equivalent to 9.9 deaths per million per year). From these reference data, we extrapolated the global mesothelioma deaths to be 38 400 per year, based on extrapolations for asbestos use.Conclusions Although the validity of our extrapolation method depends on the adequate identification of quality mesothelioma data and appropriate adjustment for other variables, our estimates can be updated, refined and verified because they are based on commonly accessible data and are derived using a straightforward algorithm. Our estimates are within the range of previously reported values but higher than the most recently reported values.