This study substantiates the importance of FEV1 rate of decline as a predictor of all‐cause mortality. The mortality trends were similar regardless of smoking status, as well as among participants with normal lung function at the first survey. The trend based on the spline analysis is as follows: below 30 ml/year the mortality risk is not significant (that is, the lower 95% CI is below the null value). Between 30 and 60 ml/year, the log hazard ratio crosses the null value as it ascends, but is not statistically significant. The risk continues to increase between 60 and 90 ml/year and becomes statistically significant around 60 ml/year in never smokers and in those with neither restrictive nor obstructive patterns at first survey and around 75 ml/year in all other cohorts. The multivariate Cox regression model without splines quantifies the risk of the FEV1 rates of decline shown in the smoothing curves. For example, in the overall cohort, the risk in the “90 ml/year and above” category is nearly double compared to FEV1 rates of decline below 30 ml/year.
Overall, the study's findings are consistent with published literature. The Honolulu Heart Program12
showed an association between FEV1
rate of decline and mortality in smokers. The Busselton Health Study13
observed a risk of all‐cause mortality for FEV1
rate of decline that was statistically non‐significant in males but significant in females, after adjusting for risk factors. The Baltimore Study on Aging14
compared individuals in the first quintile of decline to those in the second quintile, the adjusted relative mortality risk was not significant while those in the third and fourth quintiles had statistically significant risks. The fifth quintile risk was elevated but did not reach statistical significance. In Finnish cohorts of the Seven Countries Study,11
the adjusted relative mortality risk was significant for “intermediate” decliners and “rapid” decliners, compared to “slow” FEV0.75
decliners (tertile of lowest decline). Another study of coal miners, using a matched case control study design, found that rapid decliners (having an average FEV1
decline around 90 ml/year) had significantly increased mortality compared to those with a low rate of decline.33
Lastly, in the US Six Cities Study, rapid decliners had an increased mortality compared to slow decliners among males.15
Our study extends the findings from prior research by investigating in greater detail the mortality risk in relation to specific cut‐off points for the FEV1
rate of decline. In past studies, rates of decline were analysed as a continuous variable,13
divided into categories11,14,15
or defined into groups not relevant to clinical practice and research. For example, the Honolulu Heart Program12
split slopes of FEV1
into tertiles, slopes “between +15 to −12 ml/year”, “between −13 to −38 ml/year” and “between −39 to −232 ml/year”. Thus, declines of 60 and 90 ml/year would have both fallen into the latter category. Our analysis was able to demonstrate a difference in the mortality risk ratio in those with declines “60 to less than 90 ml/year” and “90 ml/year and above”, categories which may be important to research and clinical practice. A better understanding of mortality risks of these cut‐off points should be helpful in designing preventive programmes to preserve lung health and to prevent premature death.
Several factors with recognised potential to influence the results were taken into account in this study. Level of FEV1
is a well‐established predictor of mortality.1,2,3,4,5,6,7,8,9,10
Additionally, an interaction may be observed between initial FEV1
level and rate of decline, attributed either to regression to the mean or a so‐called “horseracing effect”. To address these concerns, initial FEV1
was added to the multivariate model. Pre‐existing medical conditions related to lung function may act as a confounder in the relation between FEV1
rate of decline and mortality rate. Working miners are generally quite healthy, but the cohort may have included individuals with pre‐existing disease. To reduce this effect, a separate analysis was completed excluding those with restrictive or obstructive patterns that have already had a measurable effect on pulmonary function (table 3D and fig 1D). Extremes of weight may also affect mortality risk and the impact of lung function and weight together may be synergistic.34
Association between FEV1
rate of decline and both BMI and weight gain have been observed.35
The physiological reasons are thought to be multifactorial and complex.36,37
Our study cohort consisted of working miners who were generally not obese. Change in weight was added to the multivariate model to account for its influence on FEV1
rate of decline. In addition, those who survived gained more weight than those who died. Therefore, neither initial BMI nor weight gain was thought to have had an important impact on the association between mortality and rate of decline.
Smoking and dust are causes of rapid FEV1 decline. Smoking, the most common cause of rapid lung function decline in the general population, is also a confounder. In addition to accelerating FEV1 declines with resulting mortality from non‐malignant respiratory disease, smoking leads to death through other biological pathways, such as malignancy. Similarly, dust, an occupational cause of rapid lung function decline, is also a confounder as it leads to death from pneumoconiosis. These variables, although in part confounders, were not added to the overall model because the true risk of FEV1 decline would be obscured and the risk ratio may be shifted towards the null. However, we investigated this issue by comparing multivariate risk ratios in the overall cohort with estimated total dust at first survey, smoking status and pack‐years included the model to multivariate risk ratios estimated without these factors. The rate ratios with these three variables in the model were as follows: 1.09, 1.41 and 1.83 in the “30 to less than 60 ml/year”, “60 to less than 90 ml/year” and “90 ml/year and above” rate of decline categories respectively where only the “90 ml/year and above” was statistically significant. The results of this analysis suggest that exclusion of the smoking and dust effect did not markedly influence the mortality risk.
Importantly, a significant increased risk of mortality in relation to the FEV1
rate of decline was observed in the subgroup of never smokers, a finding not identified in many studies. For example, the Honolulu Heart Program observed the association in current smokers but not in never smokers.12
Several studies such as, the US Six Cities Study15
and the Baltimore Longitudinal Study of Aging,14
did not stratify by smoking status. The Busselton Health Study13
observed a statistically significant relative risk in female, but not male, never smokers. In miners, coal dust exposure has been shown to increase the rate of decline in lung function and the effect is independent of smoking.20,38,39
It is also possible that in our study we may have been able to detect an effect of FEV1
decline on mortality in never smokers because of the influence of dust exposure on the relationship. Classification of smoking status in the study should have been reliable. Study participants generally reported their smoking status accurately, and in this study had to characterise their smoking status at two surveys performed more than seven years apart, thus reducing the chance of misclassification.40,41
A small number of participants showed an increase in FEV1
during follow‐up, and this increase appeared to be associated with increased mortality risk (fig 1A), although not significantly. The increased mortality in this group may be explained by baseline lung function impairment; whereas 31% of the entire cohort had obstructive and/or restrictive patterns at the first survey, that proportion was 50% (n
49/98) among participants whose FEV1
increased during follow‐up. Longitudinal FEV1
increases also may indicate excessive spirometry variability which has been associated with poorer heath.36,37
When those with restrictive or obstructive patterns at first survey are removed, increases in FEV1
were not associated with increased mortality.
There are several potential limitations in this study. The participation rates decreased between the first survey and the third and fourth surveys. Although there are several possible reasons for this decrease, a healthy worker survival effect is suggested, in which ill participants fail to have lung function follow‐up. Workers with excessive FEV1
declines are more likely to leave and thus not participate in follow‐up pulmonary function testing.33
Consequently, age‐adjusted mortality rates were higher, compared to the study cohort, among those who participated in the first survey but did not perform follow‐up testing in the third or fourth surveys and thus were not in the study cohort. In addition, table 2 shows that, at the first survey, obstructive and/or restrictive patterns were more prevalent in the non‐study cohort (43%) compared to the study cohort (31%), and there were more current smokers in the non‐study cohort (54.3%) than in the study cohort (36.5%). If the rate of decline was, on average, higher in those who were not included in the study cohort, then the reported mortality risks would be biased towards the null and the actual mortality risk due to decline in lung function would be higher than reported. We also have no information on lifestyle changes in the period between the last PFT and date of death. During that time period, participants may have made substantial modifications to their lifestyle known to affect FEV1
rate of decline and the risk of mortality, for example, quitting smoking or losing weight (if overweight or obese).
In conclusion, the results of this study help to quantify the relation between FEV1 rate of decline and mortality. The findings indicate that risk of mortality starts increasing for FEV1 rates of decline between 30 and 60 ml/year and is significant for declines above 90 ml/year. Statistically significant mortality risk was observed in non‐smokers with occupational dust exposure, suggesting that monitoring lung function is also important in this group. These results should provide information useful to healthcare providers in evaluating the importance of longitudinal changes in lung function observed in individuals.