1. M. Wang, J. Wood, J. Hale, L. Petsonk, and M. Attfield
Risk factors associated with progressive massive fibrosis among U.S. coal miners - A case-control study
M. Wang, J. Wood, J. Hale, L. Petsonk, and M. Attfield
138th APHA Annual Meeting
Denver, CO
Nov. 10, 2010
Good afternoon. The topic for today’s presentation is
The findings and conclusions in this presentation are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.

2. Presenter Disclosure Mei Lin Wang I have no relationships to disclose.

3. MINING
This study addresses the Occupational lung disease associated with underground coal mining in U.S.

4. Background
● Coal Workers’ Pneumoconiosis (CWP) is a lung disease caused by inhaling coal mine dust.
● Progressive Massive Fibrosis (PMF) is the most disabling form of pneumoconiosis. Progression to PMF is a risk factor for premature death.

5. Objectives
● To investigate the relationship between development of PMF and exposures to respirable coal mine dust and crystalline silica
● To identify chest radiographic appearances associated with PMF

6. Methods – Database sources
● NIOSH Coal Workers’ Chest X-Ray Surveillance Program (CWXSP)
● Mine Safety and Health Administration (MSHA) Coal Mine Safety and Health Information System (CMIS)
● Energy Information Administration (EIA) Coal Production Data Files (CPDF)
This study based on three database sources:

7. Methods – Databases available (1)
● NIOSH CWXSP data from 1970 to 2000
Health outcomes of CWP, PMF, and other radiographic appearances
Miner’s job history
year started mining
work tenure
current mine location
current job category
The CWXSP is a NIOSH-administered occupational health program which screens miners for coal workers‘ pneumoconiosis (CWP). Job history was also taken at the time of x-ray, including year started mining, mine location and years of underground or surface mining. This study using the data from 1970 to 2000.

8. International Labour Office Classification of Radiographs
Profusion of
small opacities
Large
opacities
ILO
classification
0/-
0/0
0/1
1/0
1/1
1/2
2/1
2/2
2/3
3/2
3/3
3/+ A B C
The NIOSH program uses the International Labor Office classification of the radiographs of pneumoconioses. This is a standardized system to categorize the small opacity profusion and also the large opacities. Here we can observe some examples from the standard films: this shows a normal x-ray, then category 1, 2, and 3 CWP.
When the disease progresses, the small opacities tend to move together, forming large masses of fibrosis. This is called progressive massive fibrosis – PMF. We classify PMF according to the size of these large opacities: Stage A, B and C.

9. Methods – Databases available (2)
● MSHA CMIS data from 1970 to 1999
5,468,719 coal mine dust and quartz compliance sampling results by mine operators, and by MSHA inspectors
Date
Mine
Job category (underground face, non-face, and surface)
Respirable coal dust concentration
Respirable quartz concentration
The Mine Safety and Health Administration’s (MSHA) Coal’s Management Information System (CMIS) is a national database containing information on mine status, personnel, time and activity, sampling entities, respirable dust and respirable quartz sample results measured by MSHA inspectors and coal mine operators since 1970.

10. Methods – Databases available (3)
● EIA Coal Production Data Files
Years of mine operation
Mine seam height
Coal rank in this study:
High rank group: anthracite, low or medium volatile bituminous
Low rank group: high volatile bituminous
A third database from the Energy Information Administration (EIA) containing information on years of mine operation, mine seam height, and also coal rank. In the current study, we define coal rank as high and low groups, the high rank group including anthracite, low or medium volatile bituminous. The low rank group including high volatile bituminous

11. Methods – Define cases and controls
● Define PMF cases by last x-ray film large opacity coded as A, B, or C
● Select controls by SAS macro program
● Matching items:
calendar year started mining
year and age at the first x-ray
● 347 PMF cases matched with one to multiple controls, selecting only the first controls for 1-1 matching pairs

12. Methods – Exposure assessment
● Estimate each miner’s cumulative respirable coal dust and quartz exposure:
Based on sampling results of dust and quartz concentration by mine, year, and job category
Merge with job history records
● Calculate total years of mining and years worked at the underground face
Using job history
● Evaluate mine seam height and coal rank
Based on EIA database

13. Methods – Data analysis
● 314 pairs included in the analysis:
33 pairs excluded after data quality assessment
● For continuous variables - Paired T-test
● For dichotomous variables - McNemar’s test
● Explore the association of PMF to various potential risk factors using logistic regression model for 1-1 matched case-control study (SAS proc mdc)

14. Methods – Data analysis (Cont.)
● Logistic regression model
Coal mine dust by quartiles of distribution
Quartz exposure by median and Q3 values
Seam height - dichotomous by median value
Coal rank - high vs. low
Variable
Reference
Level 2
Level 3
Level 4
Cumulative Dust*
<43.5
43.5 – 90.2
>90.2 – 132.4
>132.4
Cumulative Quartz*
<0.774
0.774 – 2.607
>2.607
Seam height
> 56.5
< 56.5
Coal rank
Low
High
Independent variables examined in the model were coal mine dust, quartz, mine seam height, and coal rank. Create three design variables for cumulative coal dust exposure by the quartiles of distribution; using the first quartile as the reference group. Similarly, create three design variables for cumulative quartz exposure, and categorize the mine seam height and coal rank as dichotomous variables.
* Units for cumulative coal dust and quartz: mg-yr/m3

15. Methods – Data analysis (Cont.)
● Logistic regression model structure:
● Model (1) including all 314 pairs
PMF (1, 0) = cum-dust cum-quartz coal-rank
● Model (2) including only 58 pairs with complete seam height values
PMF (1, 0) = cum-dust cum-quartz seam-height
Presented here are two final models: model one including all 314 pairs, examining for the association between PMF and cumulative dust, cumulative quartz exposure, and the coal rank high vs. low. The second model including only 58 pairs with complete seam height values, the seam height effect to PMF was examined in this model

16. Results ● All 314 cases were males with 94% whites.
● Cases – PMF by size of large opacity
A (n=201) – smallest
B (n=97)
C (n=16) – largest
● Controls – Small opacity evidence of CWP
No (n=205)
Yes (n=109)
PMF was classified by the size of the large opacity as A (n=201), B (n=97), or C (n=16)
In 205 pairs, the controls without CWP, and in 109 pairs the controls also had CWP.

17. Paired case-control comparison (1)
Cases, n=314
Controls, n=314
P value
Age at first x-ray
51.0
N/A
Year first x-ray
1976
Age started mining
22.1
0.4407
Year started mining
1947
Proportion with small opacity “r” shape*
44%
15%
<.0001
Small opacity profusion at first x-ray
5.0 (2/1)
1.6 (0/1 – 1/0)
Small opacity profusion at last x-ray
5.7 (2/1 – 2/2)
1.5 (0/1 – 1/0)
Age and year at the first x-ray, and year started mining were matching items. Age started mining was similar. The proportion with small opacity “r” shape was significantly higher in cases. Small opacity profusion at the first and last x-ray was both significantly higher in cases comparing to controls.
* For 109 pairs, in which both cases and controls had CWP

18. Paired case-control comparison (2)
Cases, n=314
Controls, n=314
P value
Coal mine dust (mg-yr/m3 )
120.7
82.9
<.0001
Quartz (mg-yr/m3 )
2.48
1.53
0.0002
Years at UG face
24.1
19.0
Tenure total
31.5
30.9
0.0474
Mine seam height (inch)
75.1 (n=119)
65.7 (n=113)
0.3488
Coal rank high (yes/no)
63 (21.4%)
41 (13.9%)
0.0023

19. P = 0.001
P = 0.004
P = 0.030
Based on the parameter estimates from model 1 results, this graphic shows the Odds Ratio and P values for three independent variables. Miners worked in the highest dust or quartz exposure groups or in high coal rank mine increased significantly the likelihood to develop PMF.

20. P = 0.018
P = 0.015
P = 0.023
Based on the model 2 results, as we can see that the Odds Ratio was significantly higher in the group miners worked in lower seam height mine.

21. Conclusion
● PMF cases were significantly associated with higher cumulative coal mine dust and quartz exposures; and also with lower seam height and higher coal rank ● PMF cases had higher category of small opacity profusion (category “2” or above) ● Small opacity “r” shape was highly associated with PMF

22. Recommendation
● Analysis using data from has confirmed previously recognized risk factors ● Further studies, including more recent data, may be useful in investigating recent trends of severe and rapidly progressive lung disease in coal miners