Impact of environmental tobacco smoke on airline cabin air quality

Indoor air quality investigation on commercial aircraft

Sixteen flights had been investigated for indoor air quality (IAQ) on Cathay Pacific aircraft from June 1996 to August 1997. In general, the air quality on Cathay Pacific aircraft was within relevant air quality standards because the average age of aircraft was less than 2 years. Carbon dioxide (CO2) levels on all flights measured were below the Federal Aviation Administration (FAA) standard (30,000 ppm). The CO2 level was substantially higher during boarding and de-boarding than cruise due to low fresh air supply. Humidity on the aircraft was low, especially for long-haul flights. Minimum humidity during cruise was below the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) minimum humidity standard (20%). The average temperature was within a comfortable temperature range of 23 +/- 2 degrees C. The vertical temperature profile on aircraft was uniform and below the International Standard Organization (ISO) standard. Carbon monoxide levels were below the FAA standard (50 ppm). Trace amount of ozone detected ranged from undetectable to 90 ppb, which was below the FAA standard. Particulate level was low for most non-smoking flights, but peaks were observed during boarding and de-boarding. The average particulate level in smoking flights (138 micrograms/m3) was higher than non-smoking flights (7.6 micrograms/m3). The impact on IAQ by switching from low-mode to high-mode ventilation showed a reduction in CO2 levels, temperature, and relative humidity.

Bayesian meta-analysis, with application to studies of ETS and lung cancer

Meta-analysis enables researchers to combine the results of several studies to assess the information they provide as a whole. It has been used to give a systematic overview of many areas in which data on a possible association between an exposure and an outcome have been collected in a number of studies but where the overall picture remains obscure, both as to the existence or size of the effect. This paper outlines some innovations in meta-analysis, based on using Markov chain Monte Carlo (MCMC) techniques for implementing Bayesian hierarchical models, and compares these with a more well-known random effects (RE) model. The new techniques allow different aspects of variation to be incorporated into descriptions of the association, and in particular enable researchers to better quantify differences between studies. Both the classical and Bayesian methods are applied, in this paper, to the current collection of studies of the association between incidence of lung cancer in female never-smokers and exposure to environmental tobacco smoke (ETS), both in the home through spousal smoking and in the workplace. In this paper it is demonstrated that compared with the RE model, the Bayesian methods: (a) allow more detailed modeling of study heterogeneity to be incorporated; (b) are relatively robust against a wide choice of specifications of such information on heterogeneity; (c) allow for more detailed and satisfactory statements to be made, not only about the overall risk but about the individual studies, on the basis of the combined information. For the workplace exposure data set, the Bayesian methods give a somewhat lower overall estimate of relative risk of lung cancer associated with ETS, indicating the care that needs to be taken in using point estimates based on any one method of analysis. On the larger spousal data set the methods give similar answers. Some of the other concerns with meta-analysis are also considered. These include: consistency between different geographic areas (Asia and the United States), and our studies show that Bayesian methods permit an account of the overall picture to be taken, thus improving the ability to estimate accurately in the subgroups; and publication bias which, as shown with the spousal exposure data, may lead to an inflated excess risk.

Passive smoking in the workplace: classical and Bayesian meta-analyses

There are currently several classical and Bayesian methods of meta-analysis available for combining epidemiological results. We describe and compare these in a consistent framework, and apply them to published studies of the relative risk of lung cancer associated with exposure to environmental tobacco smoke in the workplace. We find that although all methods give reasonably similar combined estimates of relative risk of lung cancer associated with this exposure (none of which is significantly raised above unity, in either a frequentist or a Bayesian sense), the approximations arising from classical methods appear to be nonconservative and should be used with caution. The Bayesian methods, which account more explicitly for possible inhomogeneity in studies, give slightly lower estimates again of relative risk and wider posterior credible intervals, indicating that inference from the non-Bayesian approaches might be optimistic.