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Does regression analysis of lung function data obtained from occupational epidemiologic studies lead to misleading inferences regarding the true effect of smoking?

Attfield-MD; Hodous-TK
Am J Ind Med 1995 Feb; 27(2):281-291
The distribution of forced expiratory volume in 1 second (FEV1) measurements in a cohort of working coal miners was examined to test the hypothesis that a subgroup of data exerted undue effects on the findings related to smoking. Medical data on ventilatory function, chest symptoms, age, height, occupational and smoking history for 7,154 miners, from the first round of the National Study of Coal Workers' Pneumoconiosis were analyzed. Dust exposure estimates calculated for each miner were based on job specific dust concentration estimates from an industrial hygiene survey and converted to units of gram hour/cubic meter. FEV1 was correlated to smoking and dust exposure through linear regression analysis. The analysis of influential observations was conducted through the use of several described methods. Basic statistics on lung function, anthropometric data, and cumulative dust exposure were presented. Regression estimates of the smoking effect showed clear effects of smoking and dust exposure. A graphical analysis was conducted due to the lack of substantial results from the analysis of influential observations. The FEV1 deviation distributions for smokers and nonsmokers were compared by age group, with similar results as those seen for the previous analysis. A suggestion of skewness was present for smokers in the oldest age group, but it was not found to be significant. The authors conclude that the current method of comparing smoking and dust exposure coefficients calculated through regression analysis of lung function data is valid and nonmisleading.
NIOSH-Author; Statistical-analysis; Coal-miners; Lung-function; Cigarette-smoking; Dust-exposure; Mine-workers; Pulmonary-function-tests; Epidemiology; Occupational-exposure
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Journal Article
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American Journal of Industrial Medicine