UBC Faculty Research and Publications

Hearing loss in British Columbia sawmill workers: an epidemiologic analysis of audiometry data from industry.. Davies, Hugh 2008

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    Hearing Loss in British Columbia Sawmill Workers  An Epidemiologic Analysis of Audiometry Data from Industry Hearing Conservation Programs, 1979 – 1996    Report to:  Hearing Conservation Section,  Workers’ Compensation Board of British Columbia, PO Box 5350 Station Terminal, Vancouver BC      By:  Hugh Davies1, Steve Marion2, Kay Teschke1,2   Final Version: June 30, 2000   1 School of Occupational and Environmental Hygiene,  University of British Columbia, 2206 East Mall, Vancouver, BC, V6T 1Z3  2 Department of Health Care and Epidemiology,  University of British Columbia, 5804 Fairview Avenue, Vancouver, BC, V6T 1Z3   2 Summary  The purpose of this study was to investigate the relative risk of hearing loss among sawmill workers in British Columbia since the initiation of hearing conservation programs in the late 1970s. Data from two Workers’ Compensation Board data bases, audiometry and noise exposure, were analyzed using epidemiologic methods to estimate the relative risks of  "OSHA" standard threshold shifts associated with cumulative noise exposure and use of hearing protection devices, and to determine if the relative risks changed with time The study utilized survival-analysis techniques to estimate the risk of threshold shifts while simultaneously controlling for multiple potential confounders. Age, a strong confounder because of its relationship to both hearing loss and cumulative noise exposure, was controlled for, but its effects were not estimated. The effects of pre-existing hearing loss at initial hearing test, and non-occupational noise exposure, were estimated. The results indicated that there was an increased risk of hearing loss among sawmill workers, and that the relative risk increased with increasing cumulative noise exposure, reaching 6.6 in the most highly exposed group (an increase of 560%). The use of hearing protection was shown to have a protective effect, reducing the risk of hearing loss by approximately 30%. While calendar year itself was not predictive of threshold shift, the year in which a person had their first hearing test was: those entering hearing conservation programs after 1988 had a 30% reduced risk of threshold shift. To improve the utility of WCB data for future research, recommendations were made to improve data collection and quality control. In addition, it would be useful to obtain more audiometry data from employees in noisy industries who themselves are not exposed, to provide an unexposed comparison group for epidemiologic analyses such as this.     3 Contents Contents .......................................................................................................................................... 3 Introduction.................................................................................................................................... 4 Objectives .................................................................................................................................................4 Outline of Work Program and Methods................................................................................................4 Methods........................................................................................................................................... 5 Subject Selection ......................................................................................................................................5 Preparatory Work (Noise Exposure Assessment).................................................................................5 Preparatory Work (Audiometric Data).................................................................................................5 Results............................................................................................................................................. 9 Subject demographics .............................................................................................................................9 Univariate analyses................................................................................................................................14 Multivariate Modeling...........................................................................................................................16 Discussion..................................................................................................................................... 19 Relative Risk of Hearing Loss in the Sawmill Cohort ........................................................................19 The Effect of Hearing Protection Use ..................................................................................................19 Changes in the Relative Risk for Hearing Loss with Time ................................................................19 Estimating Overall Impact of Hearing Conservation Programs.......................................................20 Other hearing conservation program issues .......................................................................................20 Risk estimates for non occupational-noise factors..............................................................................20 Limitations of the study.........................................................................................................................20 Limitations of the Data..........................................................................................................................21 Application of Analytical Technique by WCB in Other Industry Sectors .......................................21 Possible areas for further investigation ...............................................................................................22 References..................................................................................................................................... 23 Appendix A: Audiometry Database Fields .................................................................................. 24 Appendix B: Noise Exposure Levels in Sawmill-Related Occupations ..................................... 26 Appendix C: Sources of data error on audiometric database..................................................... 30    4 Introduction Objectives The Hearing Conservation Section of the Workers’ Compensation Board of British Columbia (WCB) asked the authors to analyze sawmill industry audiometry data managed by the WCB. Within the context of evaluating the impact of hearing conservation programs, the objectives were to ascertain: 1. the relative risk of developing hearing loss in noise-exposed BC sawmill workers as compared to a group not occupationally exposed to noise; and 2. to what degree noise induced hearing loss had been reduced in sawmill workers over the period 1980 – 1996 A secondary objective was to develop an analysis methodology that could be applied by the WCB to other audiometry data from other industry sectors. Outline of Work Program and Methods Data Sources Data for the study was provided by the WCB in 3 databases: ! Audiometric database: An extract of the full WCB audiometric database. It contained 316,476 observations relating to 66,130 subjects, obtained during the period 1979 to 1996. From the inception of the database, the rate of deposition of hearing tests from sawmills was steady at approximately 15,000 – 20,000 per annum. Appendix A lists the database structure. ! WCB noise exposure database: An extract of the WCB noise exposure database of field measurements for the industry subclass 10501. This file contains noise exposure measurements made by WCB regulatory officers, and measurements made by the sawmills as part of their noise control programs, and voluntarily submitted to the WCB. ! NIOSH audiometry databases: The WCB provided extracts from 4 audiometric databases commissioned by NIOSH and selected by the "ANSI S12.13 Working Group on Hearing Conservation Program Evaluation" as standards for evaluating program effectiveness. Background To date, hearing conservation programs have been evaluated using several methods: the investigation of variability in audiometry results ("audiometric database analysis", ANSI, 1991, Royster and Royster, 1990); the investigation of hearing-related outcomes such as hearing threshold levels (Ridgely, 1991, Bertrand and Zeidan, 1999) and standardized threshold shifts (Wolgemuth  et al, 1995). The ANSI S12.13 draft standard has been criticized for its restrictive subject eligibility criteria, poor reliability and generalizability, limitations in handling the effects of pre- existing hearing loss and sensitivity to audiometric test method (Adera et al, 1993a, 1995, Simpson, Stewart and Kaltenbach, 1993, Simpson, Amos and Rintelman, 1993). Alternative methods of evaluation continue to be sought. Although established epidemiological techniques have been previously recommended (Erdreich and Erdreich, 1984, Adera, et al, 1995), few studies that utilized such techniques have been published.  Only Adera and his colleagues (1993a, 1993b) have approached the problem in this way.  They estimated age-adjusted risk ratios for standard threshold shift using an external control data set (ANSI, 1991) and Mantel-Haenszel stratified analysis. We felt that in order to make the best use of the longitudinal nature of audiometry data, however, a more appropriate technique would be to use survival analysis. Further, statistical modeling would allow us to simultaneously adjust for the multiple potential confounders of the relationship between noise exposure and hearing loss. Analytical approach Survival analysis is particularly suited to this data, as the outcome - hearing loss - is a common disease, and routine audiometry gives us a reasonable estimate of the time of onset. Survival analysis makes very efficient use of the information provided by those who do not suffer hearing loss during the follow up period, as well as those who do.   5 At periodic hearing tests (there may be several before the hearing loss “event” occurs) the audiometric technician records an individual's status for various risk factor for hearing loss, including: noise exposure, use of hearing protection, non-occupational exposure to noise, and health-related risk factors. All of these can change with time, and survival analysis is also well suited to handling this complexity. Modeling, using Cox’s proportional hazard model (a type of survival analysis) allows not only adjustment for multiple confounders, but also permits estimates of their effects. In addition, it provides very precise control of the effects of age, which is a particularly strong confounder of the relationship between hearing loss and duration of exposure to noise. Because individuals enter hearing conservation programs at different times, and remain in them for different periods, (but usually for several years) determining the effect of calendar year on risk of hearing loss is particularly complex. Cox modeling allows the estimation of these year-effects without multiple stratifications that might reduce the overall power of the analyses. Methods Subject Selection Subjects were excluded from analyses if: ! the job they held was likely not a permanent sawmill job (e.g. construction contractors) ! they had only one hearing test (prevents estimation of a shift in hearing threshold) ! their data had coding or logic errors (except missing values) at any of their hearing tests. After these exclusions, the number of subjects available for analyses was 42,282. Of these, only 22,376 subjects had all variables completed for every hearing test. All hearing tests following a test at which hearing loss (defined below) was identified were excluded, as they would provide no relevant explanatory information. Preparatory Work (Noise Exposure Assessment) The exposure database provided to UBC by the WCB contained 5,743 personal dosimetry measurements from 185 sawmill sites around BC. To allocate exposure levels to occupations, each observation in the exposure database was first assigned a UBC standardized job title (job titles in the WCB exposure database were text only and not standardized)1. The mean exposure level was calculated (using the WCB data) for each standardized job title. Standard job titles were then cross-referenced to WCB occupation codes used in the audiometry file, allowing each observation (hearing test) to be assigned the mean noise level associated with the job title held at that time. Some job titles (e.g. "Production line worker") were assigned mean values of a group of representative jobs. Occupation codes that were not sawmill jobs were referred back to the Hearing Conservation Section. Exposure data on the majority of the remaining occupation codes was obtained, and again mean exposure levels were estimated and allocated. A full list of occupation codes, job titles, the distribution of job titles among hearing tests and mean exposure levels is provided in Appendix B. Preparatory Work (Audiometric Data) The audiometric database was systematically checked for data errors (Appendix C). Wherever possible errors were corrected, else all observations for the affected individual were excluded. Each eligible subject had n (where n ≥ 2) hearing tests, resulting in n-1 periods between hearing tests. It was assumed that the personal information provided at a hearing test (job title, exposure and medical history) represented the conditions during the entire duration of the previous period.  1 This step had been performed earlier as part of another study conducted at UBC using the WCB exposure database.   6  Some data items (such as hearing level at initial audiogram) remain unchanged with time – they are said to be “fixed”. Other data items are free to change with time (such as cumulative exposure) and were therefore re- calculated at each hearing test. These are said to be “time-varying”. The variables used in the statistical analyses are summarized in Table 1. A detailed description of the variables follows. Table 1: Analysis Variables and Codes Variable Values Codes Fixed or Time-Varying Health outcome: OSHA STS in better ear. 0|12 0 = no STS 1 = STS during last period Time-varying  Use of hearing protection 0|1 0 = not a regular hearing protection devices wearer 1= regular HPS wearer Time - varying  Cumulative noise exposure 0 - 5 0 = reference 1 = 80.1 - 85.0 dB 2 = 85.1 - 90.0 dB 3 = 90.1 - 95.0 dB 4 = 95.1 - 100.0 dB 5 = > 100.0 dB Time - varying  Year of hearing test  1979 - 1996  Time - varying  Year of initial hearing test   1979 - 1996  Fixed  Pre-existing hearing loss at initial audiogram 0 - 4 0 =     ≤ 15 dB 1 = 16 - 30 dB 2 =  31 - 45 dB 3 =  46 - 60 dB 4 =      ≥ 61 dB Fixed  Ever had ear surgery? 0|1 0 = yes 1 = no Time - varying Ever had a serious head injury? 0|1 0 = yes 1 = no Time - varying Ever had dizziness or balance problems? 0|1 0 = yes 1 = no Time - varying Ever had a severe ear infection? 0|1 0 = yes 1 = no Time - varying Ever had a relative with hearing loss before age 50? 0|1 0 = yes 1 = no Time - varying  Ever exposed to loud noises in the armed forces? 0|1 0 = yes 1 = no Time - varying Ever exposed to loud noises off the job? 0|1 0 = yes 1 = no Time - varying Ever exposed to loud noises at a previous job? 0|1 0 = yes 1 = no Time - varying  Ever shot trap/skeet/target (not hand guns)? 0|1 0 = yes 1 = no Time - varying Ever hunted? 0|1 0 = yes 1 = no Time - varying Ever shot handguns 0|1 0 = yes 1 = no Time - varying Health Outcome The health outcome specified by WCB for the analysis was the OSHA standard threshold shift (STS), calculated as a cumulative average threshold shift of 10 dB or greater at 2000, 3000 and 4000 Hz in the better ear (i.e. the ear with the lower hearing threshold at time of audiogram). This is given by the equation: Y =  [{Hearing level at 2KHz + Hearing level at 3KHz + Hearing level at 4KHz }/3](periodic audiogram)  2 | = "or"   7 - [{Hearing level at 2KHz + Hearing level at 3KHz + Hearing level at 4KHz }/3](baseline audiogram) If Y ≥ 10 dB, the subject was considered to have an STS event. Cumulative Noise Exposure Each hearing test was assigned a noise exposure level corresponding to the current occupation reported by the subject. Cumulative noise exposure was estimated in decibels as the sum of the products of noise intensity and duration for all occupations reported up to and including the current hearing test (see "composite noise immision levels", Robinson and Shipton, 1977): For ith audiogram: Cumulative-exposurei (dB re: 20 microPascal-years) = 10 log10 (Σ1 to i (sound intensityi (microPascals) x duration of employmenti (years))) Thus a 3 dB increase in cumulative exposure represents a doubling of either the duration or the intensity of exposure. The elapsed time between hearing tests was used in estimating exposure duration. Self-reported "years at occupation" was not used, as it was only less than elapsed time in approximately 10% of observations, and was prone to reporting error. Exposure prior to the initial audiogram could not be used in our analyses, because we had no record of these exposures. Prior exposures were accounted for with the variable “Pre-Existing Hearing Loss at initial audiogram”. Hearing Protection Use At each hearing test the subject reported if they  “regularly wear ear protectors”. The proportion of follow up time that hearing protection was worn was calculated for each hearing test. This was dichotomized for analysis into those who continuously wore hearing protection devices during the follow up period and those who did not. Calendar Year Gives the year the hearing test was performed. Potentially reflects changes in the environment (or individual) that occur with time. This variable might estimate otherwise unmeasured effects of hearing conservation programs, beyond the effects of hearing protection use and cumulative noise exposure. Year of Initial Hearing Test This gives the year of the subject's first hearing test. This variable allows the model to adjust for a "cohort" effect, i.e., an effect associated with being in the group who began their hearing conservation program experience in a given year. Pre-Existing Hearing Loss at First Hearing Test Because of uncertainty regarding exposure levels and status of confounders prior to a subject's initial hearing test, we treated every subject's initial hearing test as a "baseline". All noise exposure prior to first audiogram was ignored and initial hearing loss was assumed to reflect the effect of any prior noise exposure. The level of hearing loss at a subject’s initial hearing test was determined as the average threshold of both ears at 2, 3, 4 kHz. The level of existing hearing loss is also known to influence the rate of change of hearing threshold. This variable allowed us to control for this. Intrinsic Risk Factors These covariates report whether the subject ever had: 1. ear surgery 2. dizziness or balance problems 3. a serious head injury   8 4. a relative with hearing loss before age 50 5. a severe ear infection  These variables have dichotomous values (yes/no). The WCB hearing test protocol leaves a subject's response blank on the data entry form if there had been no change in status from the previous hearing test. Therefore we attempted to "fill in" all missing values for the medical risk factor variables with the last non-missing value reported, where available. As self-reporting was at all times voluntary, a great number of missing values nevertheless remained. Extrinsic risk factors All of these variables are dichotomous (yes/no). They were “filled in” as required (see intrinsic risk factors). These covariates report whether subject: 1. was ever exposed to loud noises at previous job 2. was ever exposed to loud noises off the job 3. was ever exposed to loud noises in the armed forces 4. ever hunted 5. ever shot trap/skeet/target (but not handguns) 6. ever shot handguns Statistical Analyses Statistical analyses were completed using STATA 5 (STATA Corp, Texas). Specific statistical tests used are referenced in the text. Means and standard deviations are given where the underlying distributions appeared normal, otherwise medians and interquartile ranges are provided. Comparisons to External Populations Cumulative incidence of STS in the sawmill worker cohort was compared with cumulative incidence in an external control group. For this purpose, we selected an extract of one of the NIOSH audiometry data sets  (ANSI0002). The extract was prepared for the WCB by a member of the ANSI working group (Royster, 1999) and contained only records for white males exposed to noise levels below 85 dB(A) in synthetic fiber manufacturing. These subjects were reported not to wear hearing protection. Relative risks were estimated using age-stratified contingency tables, and summary relative risks were estimated using Mantel Haenszel adjustment, following the method of Adera et al (1993b). Comparisons within the Sawmill Population Survival Time Definition Survival analyses allow us to model time-to-event (in this case time-to-STS) using a variety of possible time parameters. We elected to use age (in years) as the underlying "time variable". Thus the univariate (Kaplan Meier) survival analysis results are given as "median age at STS". This has the effect of "controlling" for age, a strong risk factor for hearing loss, in a very precise way (Checkoway et al., 1989). A drawback of this approach is that the effect of age on STS incidence cannot be simultaneously estimated. Preliminary analyses of the sawmill worker data showed the expected strong association between age and hearing loss. To overcome a potential bias caused by non-commensurate intervals between hearing tests among those who went on to have an STS event and those who did not, follow-up periods were restructured into 2 year "time periods". These time periods were then assigned the covariate values of the actual underlying period between audiograms. To prevent the possibility of individuals biasing their responses to personal risk questions based on knowledge of the status of their hearing, the data from each hearing test was applied "prospectively" to the following period. This also had the indirect effect of "lagging" exposures by up to two years (i.e. STS events and matched controls are associated with cumulative exposures received up to a point up to 2 years earlier, but not after that point). This lagging is appropriate if noise does not cause an immediate STS, but has its effect after an induction period of at least 2 years.   9 Univariate Analyses Kaplan Meier tests were used to examine the relationships between individual co-variates and STS. Only those with p ≤ 0.20 were retained and offered in initial multivariate modeling. Multivariate Model Building Covariates for exposure and initial hearing loss were offered in every model. Age was adjusted for in every model as it was entered as the “survival time” variable. All co-variates with p ≤ 0.20 in univariate tests were then added, and non-significant co-variates (p > 0.05) were removed one at a time. Each covariate's contribution to the model was gauged by the statistical significance of the covariate, the log-likelihood ratio, and the percentage change in the remaining co-variates (Hosmer and Lemeshow, 1999). Once the final model was built, all co-variates not previously offered in the model were offered to see if they were significant in a multivariate setting. Results Subject Demographics Gender and Age All 42,282 subjects were male, and ages at hearing tests ranged from 16 to 79 years. The median age at initial hearing test was 31, with an inter-quartile range of 24 – 43, and a range of 16 to 75. The mean age at first hearing test changed with time. In earlier calendar years, there was a larger proportion of older individuals receiving their first hearing test. The mean age at first hearing test dropped from 36.9 to 29.2 between 1979 and 1996 (Figure 1). Median age at end of follow up (at last hearing test, or when STS detected) was 40 (inter-quartile-range 31 – 51, range 16 – 79). Personal Risk Factors for Hearing Loss Table 2 shows median levels of pre-existing binaural hearing loss by decade of age. As expected, there is a substantial increase in hearing threshold with age, with an approximate doubling of median hearing loss with each decade. Age and pre-existing hearing loss were strongly correlated  (Pearson r = 0.6). Median binaural pre-existing hearing loss at initial hearing test was 9.2 dB. Median pre-existing hearing loss decreased with increasing calendar year (Figure 1).  Table 2: Pre-existing hearing loss by age Age group n Median binaural hearing loss (dB) Inter-quartile Range ≤ 30 10,020 3.3 1.7 - 7.5 31 - 40 11,657 5.8 2.5 - 11.7 41 - 50 9,522 11.7 5.0 - 21.7 51 - 60 8,076 25.8 14.2 - 39.2 > 60 3,007 38.3 25 - 51.7 All 42,282 9.2 3.3 - 22.5  Table 3 shows the proportion of subjects self-reporting personal risk factors, and the proportion of missing values. Despite our attempt to correct missing values by "filling forward" from the last non-missing value reported for a covariate, there remained a substantial amount of missing data.   10 Figure 1: Mean age and median pre-existing hearing loss at first hearing test, by calendar year. 0 2 4 6 8 10 12 14 16 18 1979 1981 1983 1985 1987 1989 1991 1993 1995 Year dB 20 22 24 26 28 30 32 34 36 38 40 Age pre-exisit ing hearing loss age   Table 3: Proportion of subjects self-reporting risk factors for hearing loss Risk Factor % responding positively on at least one hearing test, of those responding % subjects never responding Medical History Ear infection 11.5 36.9 Relative with HL before 50 7.5 37.6 Serious headinjury 6.3 37.4 Dizziness or balance 5.6 37.2 Ear surgery 3.2 37.3  Exposed to noise: At previous job 63.7 35.5 At home 49.2 37.3 In armed forces 11.3 38.0  Firearm use: Ever hunted 52.6 37.1 Ever shot trap/skeet/target 29.2 38.7 Ever shot handguns 22.0 38.7  Ear surgery and problems with balance or dizziness were the least frequently reported medical problems at 3.2% and 5.6% respectively. A severe ear infection was the most common medical condition, reported by 11.5% of those responding. Only 11.3% of subjects reported exposure to noise in the military, while 49.2% and 63.7% reported exposure to noise off the job and exposure in a previous job, respectively. Over half the respondents had hunted at some time, and between 20 and 30% had shot trap, skeet or targets, or shot handguns.   11 At their initial hearing test, 57.9% of subjects reported having been exposed to noise at a previous job. Even among those aged 20 years or less, 37.5% reported a previous noisy job; this increased to 69.7 % in those aged 60 years and older at their first hearing test. Table 4 shows levels of pre-existing hearing loss at initial hearing test associated with self-reported risk factors for hearing loss. Those reporting noise exposure during military service had an almost 3-fold increase in the level of pre-existing hearing loss. Those reporting exposure to noise in a previous job showed a more mild elevation. Those reporting exposure to noise off the job had a significant decrease of over 40% in pre-existing hearing loss. Increases were seen in those reporting prior ear surgery, dizziness or balance problems and severe ear infections, the largest increase being for those having had surgery. Firearm use in hunting prior to initial hearing test resulted in a very small increase in HL. Given the very large number of observations, it is advisable to regard the clinical significance of these results with more weight than the statistical significance. Table 4: Self- Reported Personal Risk Factors (at Initial Test) and Pre-existing Hearing Loss (dB) Risk Factor Yes No  n Pre- existing HL (dB) n Pre- existing HL (dB) Exposed to noise: Military 2636 21.7* 21433 7.5 Previous job 14430 10.0* 9937 7.5 Off the Job 11645 6.7† 12705 11.7  Ever had: Ear Surgery 649 16.7* 23663 8.3 Dizziness/balance problem 1167 12.5* 23188 8.3 Severe ear infection 2088 10.0* 22238 8.3 Head Injury 1369 8.3 22929 8.3 Familial hearing loss 1675 8.3 22552 8.3  Ever: Hunted 12593 9.2* 11844 8.3 Shot trap/skeet/target 6632 7.5† 17096 9.2 Shot handguns 5007 8.3† 18718 9.2 *Statistically significant (Mann-Whitney) at p <0.05, increase in pre-existing hearing loss †Statistically significant (Mann-Whitney) at p <0.05, decrease in pre-existing hearing loss Non-response to Health and Exposure Questions 35.4% (13,999) had missing values for all non-occupational exposure and medical history questions at all hearing tests. Compared to other subjects, these "non-responders" were older at first hearing test (mean age 35.5 vs. 32.5 years; t-test, p <0.05) This group also had slightly higher pre-existing hearing loss (16.3 dB vs. 14.6 dB, t-test, p < 0.05), and reported slightly less hearing protection usage (80% vs 83%, p<0.05). There was a very small difference in average noise exposure in the non-responding group; they were exposed to an average noise level of 91.1 compared to 91.2 dB (t-test, p <0.05). Hearing Protector Use Use of hearing protection was self-reported by subjects at each hearing test. The proportion of those using hearing protection (those responding positively to the question “do you regularly use ear protectors”) increased from 71.6% in 1979 to 91.1% in 1996. Use of hearing protection devices was greatest in the highest noise exposed groups (Figure 2) but has been increasing at all exposure levels. Use of hearing protection was also associated with subject age, with younger subjects more likely to be regular users (Figure 3).   12 Figure 2: Proportion Self-Reported Hearing Protection Use by Calendar Year and Average Noise Exposure Level  40 50 60 70 80 90 100 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Year Proportion using hearing protection < 85 dB(A) 85 - 94 dB(A)  95 dB(A)   Figure 3: Proportion Of Subjects Using Hearing Protection Devices By Age   0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 Š30 31 - 40 41 - 50 51 - 60 60 Age (years) Proportion using Hearing Protection    13 Frequency of Hearing Tests and Length of Follow-up The median period between hearing tests for an individual was 1.1 years, with 75% of periods less than 1.6 years and 90% of periods less than 2.4 years. The range of periods was 28 days to 18 years. The median period length was not significantly different between those who suffered STS and those who did not, nor between various average exposure groups (data not shown). The median number of hearing tests per person in the database was 9, with a range of 2 to 19 (after excluding subjects with single audiograms). The mean follow up time (from initial to final hearing test) was 7.1 years. This is consistent with the findings of a large cohort study of BC sawmill workers which found that among those employed for at least one year between 1950 and 1985, 60% of workers were employed for 9 years or less (Ostry, 1998). The mean length of follow up time was associated with average exposure level. Those having a lower average exposure level tended to be followed up for a shorter period of time (Table 5). The final group (≥ 101.7 dB) is comprised entirely of one job-group (those who have worked exclusively as chipper operators). Their relatively short follow up time may be biased by early migration from this job to "quieter" jobs. Table 5: Mean follow up time by average noise exposure category Average noise exposure dB(A) Number of hearing tests Mean follow up time (years) ≤ 85.0 3171 5.5 85.1 – 90.0 9567 7.2 90.1 – 95.0 22345 8.0 95.1 – 100.0 6792 8.4 100.1 – 101.6 206 9.2 ≥101.7 201 4.8 All 42282 7.1 Frequency of Standard Threshold Shift (STS) A total of 5,919 Standard Threshold Shifts (STS) were identified. An individual was only permitted a single STS, at which time follow up for the individual ceased (i.e. subsequent hearing tests were ignored). Noise Exposure A full list of occupation codes, job-titles and mean exposure levels is given in Appendix B. Cumulative exposure levels were estimated for each subject at each of their hearing tests, thus cumulative exposure levels increased throughout the follow-up period. The distribution of cumulative exposure levels is shown in Figure 4. The mean cumulative exposure level for all subjects at end of follow up was 98.1 dB(A) with a standard deviation of 6.1. Cumulative exposure measurements incorporate both an intensity and a time factor, and are in decibels (10 x log10 (noise intensity at jobi in Pascals x duration of employment in jobi in years)). This unit conforms to the equal energy hypothesis, thus a doubling of either sound intensity or duration of exposure will increase the cumulative exposure level by 3 dB. A small group of subjects comprised a “non-exposed” group, identified by the audiometric technician with an occupation code of “9999999”, for their entire work history. Only 0.8% of subjects fit this category (n=329). The median follow up time for this group was only 1.3 years, with 82.3% having 2 or fewer periodic hearing tests.   14 Figure 4: Frequency Distribution of Cumulative Exposure (dB) Cumulat ive Exposure, dB 70 80 90 100 110 120 1000 2000 3000 4000 5000 6000 7000  Univariate Analyses Table 6 shows the results of univariate Kaplan Meier analyses of all potential co-variates. All variables were tested as categorical (rather than continuous) variables. The likelihood ratio test tests the statistical significance of the difference of the univariate models and the null model. The median age at STS is the age at which half of the individuals in the category had suffered an STS. Only those variables with a P-value of ≤ 0.2 were retained for further analysis in the multivariate model.  Table 6: Univariate Analyses of Median Age of onset of STS Variable Category Likelihood Ratio Test (p-value) Median age at STS Retained for multi-variate Analysis Cumulative noise exposure (dB) ref <0.001 .  √  80 - 85  65.7  85 - 90  58.4  90 - 95  59.3  95 - 100  53.7  >100  49.9    3 unable to estimate (insufficient cases)   15 Table 6: Univariate Analyses of Median Age of onset of STS (continued)  Variable Category Likelihood Ratio Test (p-value) Median age at STS Retained for multi-variate Analysis Pre-existing HL(dB) ≤ 16 <0.001 54.1 √  17 - 31  52.3  32 - 46  54.7  47 - 61  61.2  ≥62  .  Year of first hearing test 1984 <0.001 54.7 √  1988  58.9  1992  63.5  1996  .  Hearing protection devices use No <0.001 53.6 √  Yes  56.0  Target shooting No 0.004 55.0 √  Yes  53.3  Calendar year of hearing test 1984 <0.001 63.2 √  1988  55.8  1992  52.1  1996  51.8  Handgun use No 0.018 55.1 √  Yes  53.1  Severe ear infection No 0.169 54.8 √  Yes  53.9  Noise in military No <0.001 54.2 √  Yes  57.5   Table 6: Univariate Analyses of Median Age of onset of STS (continued)    16 Variable Category Likelihood Ratio Test (p-value) Median age at STS Retained for multi-variate Analysis Hunting  No 0.794 54.7  Yes  54.3  Head injury No 0.438 54.7  Yes  54.6  Ear surgery No 0.923 54.7  Yes  54.8  Familial hearing loss No 0.619 54.7  Yes  55.8  Dizziness or balance impairment No 0.298 54.7  Yes  55.4  Non-occupational noise No 0.463 54.3  Yes  54.5  Noise in previous job No 0.933 54.9  Yes  54.7  Multivariate Modeling Table 7 shows the output of the final multivariate model. Because some of the co-variates had large numbers of missing values, the number of subjects examined in the model was 22,376 (from a total of 42,282) including 2,839 STS "events" (from a total of 5,919). Nevertheless the model had ample power to model the covariates of interest. Overall the model was very highly statistically significant (p <0.0001). All variables are categorical. If not dichotomous, they were grouped by logical breakpoints. Relative risks greater than one indicate an elevated risk of developing an STS, i.e. a relative risk of 2 means that the risk of developing STS is doubled (100% increase in risk). Relative risks below one suggest that the factor has a "protective" effect, i.e. a relative risk of 0.5 means the risk of developing STS is one half of the baseline risk. The multivariate model estimates the effect (relative risk) associated with each factor while simultaneously adjusting for all other factors. Thus each risk factor can be examined independent of the others - the same as saying "while holding all other factors constant, the relative risk, for example, associated with target shooting is 1.1".   17  Table 7: Multivariate model, showing relative risks of STS Variable Relative Risk 95% confidence Interval Cumulative noise exposure (dB) ref 1 80 - 85 2.1 1.3 - 3.6 85 - 90 3.0 2.3 - 4.0 90 - 95 3.3 2.8 - 4.0 95 - 100 4.6 3.8 - 5.4 > 100 6.6 5.6 - 7.9  Pre-existing hearing loss (dB) ≤15 1 15 - 30 1.2 1.1 - 1.3 30 - 45 1.1 1.0 - 1.3 45 - 60 0.6 0.5 - 0.7 ≥ 60 0.3 0.2 - 0.4  Year of first hearing test ≤ 1988 1 > 1988 0.7 0.5 - 0.9  Always wore hearing protection device 0.7 0.7 - 0.8  Ever shot trap/skeet/target (no handguns) 1.1 1.0 - 1.2   The model indicates that the risk of STS increases with increasing cumulative exposure, from a RR of 2.1 for those exposed between 80 and 85 dB, to a RR of 6.6 in the group exposed to greater than 100 dB. Recall that cumulative exposure combines noise intensity with duration of exposure in accordance to the equal energy hypothesis. Therefore 100 dB (intensity) for one year duration in this scale is equal to 97 dB(intensity) for 2 years; both equal 100 dB (cumulative). The relative risks of the noise-exposed groups are given with reference to a control group exposed below 80 dB. This group primarily consists of all subjects at their initial hearing test. Increasing pre-existing hearing loss (at initial hearing test) is associated with a slightly increased risk in STS among those with an initial shift of 15 to 30 dB (a result of their prior noise exposure) but a reduced risk in those who started with an initial loss of more than 45 dB (a result of the smaller threshold shift possible among those who have already experienced substantial hearing loss).  The risk of STS drops sharply to 0.6 for those with 45 - 60 dB loss and to only 0.3 for those with pre-existing HL above 60 dB. The continuous use of hearing protection resulted in a reduced risk for STS (RR = 0.7).   18 The effect of time on the risk of STS was examined in two ways. Both year of test and year of first test were entered into the model. Calendar year of test had little impact on the risk of STS and was removed. Year of first hearing test showed a reduced risk in later years, with those who had their first hearing test after 1988 having a relative risk of 0.7. Finally, having ever shot trap, skeet or target (but excluding handgun) gave a slightly elevated risk of STS (RR = 1.2).  Incidence Rate Analysis; External Control Group. In a secondary analysis, the incidence of STS in the sawmill worker cohort was compared with an external control group provided by the NIOSH database, and adjusted for age (Table 8). Because of the relatively small number of controls, all subjects over 40 years were collapsed into a single category. The relative risk of STS increases from 0.5 in the youngest group (less than 30 years) to 10.5 in the 40 and over group. Combining these data gave an overall RR for the sawmill group of 2.6. Comparing the change in risk between earlier and later periods in the WCB dataset we found that the overall age- adjusted relative risk dropped from 2.7 to 2.1 in the latter period. This appears to be mainly due to reduction in risk in the oldest of the three age groups where the relative risk was reduced from 10.9 to 7.9. Table 8: Incidence Rate Analysis, External Comparison Group Age Sawmill Workers N (STS Cases) Comparison Group N (STS Cases) Relative Risk 95% Confidenc e Interval All Years ≤29 4128 (418) 47 (9) 0.5 0.3 - 1.0 30-39 5212 (940) 81 (5) 3.1 1.3 - 7.3 ≥40 6696 (2189) 62 (2) 10.5 2. 7 - 40.9 Age-adjusted   2.6 1.6 - 4.1  1982 and earlier ≤29 1941 (225) 47 (9) 0.6 0.3 - 1.1 30-39 2902 (562) 81 (5) 3.3 1.4 - 7.8 ≥40 4512 (1526) 62 (2) 10.8 2.8 - 42.4 Age-adjusted    2.7 1.7 - 4.4 1990 and later ≤29 347 (37) 47 (9) 0.6 0.3 - 1.1 30-39 313 (54) 81 (5) 3.0 1.2 - 7.2 ≥40 222 (53) 62 (2) 7.9  2.0 - 31.3 Age-adjusted   2.1 1.3 - 3.4    19 Discussion Relative Risk of Hearing Loss in the Sawmill Cohort The analysis indicated that there was an increased risk of hearing loss in sawmill workers. After adjusting for age, level of hearing loss at first hearing test, year of first test, trap shooting and hearing protection use, there remained an elevated relative risk associated with cumulative exposure to noise. The relative risk showed an increasing trend with increasing levels of cumulative exposure, ranging from 2.1 for low (80 - 85 dB) to 6.6 for high (> 100 dB) cumulative noise levels. These relative risks for noise exposure were estimated with reference to an internal comparison group who were exposed to less than 80 dB (cumulative). This control group was constructed from those truly exposed to less than 80 dB, but also included each subject at their first periodic hearing test following baseline (or at 2 years, which ever was smaller). The model is interpreted thus: a sawmill worker, when all other factors are held constant, exposed to one year at (say) 102 dB (or the equal energy equivalent, e.g. 2 years at 99 dB, 4 years at 96 dB, 16 at 90 dB etc) has approximately 6.6 times the risk of STS of a worker exposed to <80 dB. An internal comparison group gives the benefit of a characteristically similar comparison group. However, it does not permit the estimation of the "absolute risk", the excess risk above background (i.e. STS due to presbycusis), because by definition there are no (or very few) truly non-occupationally exposed subjects in the hearing conservation program.  Because of this, it is likely that the absolute risk would be higher than that found in the internal analysis. We also conducted an external, age adjusted, cumulative incidence analysis using a NIOSH control data set. We found that the overall RR for STS was approximately 2.6 in sawmill workers, but that it ranged from 0.5 in the youngest to 10.9 in the oldest age groups. It is likely that the fairly broad age groups incompletely controlled for age, but the trend in RR demonstrated is consistent with that within the sawmill group. The Effect of Hearing Protection Use The continuous use of hearing protection devices during the follow-up period reduced the risk of STS by approximately 30% (RR = 0 .7). Given that there is inevitably misclassification of true hearing protection device use it seems likely that their use would be over-reported rather than under-reported. This would lead to an under- estimate of their true protective effect. Changes in the Relative Risk for Hearing Loss with Time We were able to measure only one aspect of hearing conservation programs directly, that being hearing protection device usage (noise control was also partially reflected in cumulative noise exposure). It was hoped that the influence of other hearing conservation program elements (noise control, education, audiometry, etc) and of the program as a whole, would be reflected in a reduction in STS incidence with time. Reduced risks were associated with those having more recent initial hearing tests. This suggests that those entering a hearing conservation program later in the study period were less likely (after adjusting for all other factors) to suffer STS than those who entered a hearing conservation program in an earlier period. Other data showed that in recent years, the average age of those entering hearing conservation programs was lower. The reduction in risk could in part be explained if hearing conservation programs were more effective for those entering them at a younger age, and/or with less industrial experience. The corollary is that hearing conservation programs may be less effective for older, experienced workers with perhaps more established work and hygiene habits. The external cumulative incidence analysis using the NIOSH/ANSI comparison file also showed a moderate decrease in risk between the sawmill groups from before 1984 and after 1992. This analysis was limited however as that both sawmill time-groups had to be compared to the same group from the ANSI file, and therefore did not adequately control for possible changes in incidence with time in the comparison group.   20 Estimating Overall Impact of Hearing Conservation Programs Because the relative risks are multiplicative, we can estimate the combined effects of hearing protection devices and year of entry into hearing conservation program. The combined protective effects of recent entry into a hearing conservation program and continual use of hearing protection devices is 0.7 X 0.7 = 0.49, or a 51% reduction in the risk of STS. Thus the RR for a worker in the lowest cumulative exposure category, hearing protection use and a recent entry into a hearing conservation program is approximately one (2.1 X 0.49 = 1.0). This assumes a pre-existing hearing loss ≤ 15 dB. However the risk of STS for workers with higher cumulative exposure levels and similar conditions would be greater than 1, and increases to 3.2 in the highest exposure group. Other Hearing Conservation Program Issues Thirty-seven percent of those under 20 years reported on their initial audiograms noise exposure at a previous job. While it is possible that they had had earlier baseline tests done elsewhere, it is a potential concern that a large percentage of young workers are exposed to noise before entering an hearing conservation program. It may be helpful to examine the full audiometric database to gauge the full impact of this. The analyses show a clear increase in the use of hearing protection devices over the 18 years of follow up. Not surprisingly, the proportion of noised-exposed workers using hearing protection was dependent on the level of noise exposure, although in an ideal situation all participants in a hearing conservation program should report regular use. Prior to 1996 however, the regulation only required hearing protection devices use at exposures above an 8-hour Leq of 90 dB(A), while audiometry was required for those with an 8-hour Leq of 85 dB(A) or greater. Risk Estimates for Non Occupational-Noise Factors The audiometry data demonstrated a strong negative association between pre-existing hearing loss and STS. This is consistent with evidence that accrual of hearing loss is non-linear (Arslan and Ozran, 1998), with most noise- induced hearing loss occurring in the first 5 - 10 years. The effect was only evident for those with > 45 dB of hearing loss. History of certain medical conditions (ear surgery, dizziness and severe ear infection) at initial hearing test were associated with pre-existing hearing loss, but in the final multivariate model no medical history factor significantly contributed. Target shooting (excluding handgun) and handgun use both resulted in an increase in relative risk of STS in univariate analysis, but only target shooting stayed in the final multivariate model, with a 10% increase in risk of STS. Limitations of the Study The ability of the analysis to examine the relationship between non-occupational factors and hearing loss was weakened by the selection of STS in the better ear (several of these risk factors could potentially produce unilateral hearing loss). There is little doubt that the majority of production and maintenance jobs in a sawmill are highly exposed to noise. However the exposure levels reflected by individuals in hearing conservation programs are a biased representation of overall exposure at sawmill because only those exposed to 85dB(A) Leq or above are required to participate in a hearing conservation program. This potentially restricts the range of exposure levels that can be investigated. Our method of exposure assessment has a number of limitations. Misclassification of job-title might have occurred both when assigning noise-exposure measurements to job-title but also while cross-referencing WCB occupation codes to the UBC standardized job titles. The noise measurements that were available only recorded noise intensity, and not other noise parameters that might modify the effect of noise on STS, for example impulsivity of noise and length of shift, that would influence recovery time. A further misclassification of noise exposure was due to an ignorance of the determinants of exposure for each mill/job/time-period combination to which we assigned exposure levels. For example we knew some jobs at certain points in time were likely to be done with the protection of a soundproof control booth. However the mean exposure level we estimated for a job title included both protected and unprotected workers. Thus assigning this value to all subjects in the same job title would have over-estimated exposure for those who work in booths and underestimated   21 for those who didn't. We didn't know the actual sampling strategy employed to collect data (e.g. random sampling vs. "worst-case" sampling) and this could potentially lead to bias toward overestimating exposures Despite these limitations, confidence in the exposure assignment was increased by having an occupational hygienist familiar with sawmills (HD) review the estimated exposures to check that the ranking of job exposures was reasonable. Further, the assigned exposure levels permitted us to discriminate among hearing protection device usage level quite clearly suggesting that the assigned exposure levels were defining discrete exposure groups (Figure 2). Noise exposure before initial audiogram was only partially known because subjects only reported current occupation and years at that occupation. Large proportions of subjects reported either exposure "off the job" or at a previous job (49.2% and 63.7%, respectively). It is unlikely that noise exposure is homogeneous among all those reporting some exposure, leading to misclassification of these variables. We adjusted for this by entering initial hearing loss in the model, and ignoring all prior noise exposure. All of the potential misclassificiation reported here is likely to be "non-differential" (equally probable to occur among any subgroup) and would usually be expected to reduce any apparent effect. Limitations of the Data Audiometry databases often lack data on those considered "non-exposed", because only at-risk workers are required to participate. This is a widespread problem, and true of the WCB database. While it was originally hoped that a control group could be formed from those individuals labeled unexposed (occupation code = 9999999) they were in fact too small a group, with too limited follow up time and relatively few audiograms. The bulk of the hearing tests for this group were from a short number of years in an earlier period. In addition the validity of the audiometry technician’s assessments of exposure could not be tested because no actual occupation code was recorded. Other studies of this type have utilized audiometry databases compiled for the purpose of developing and validating measures of the effectiveness of hearing conservation programs  (NIOSH, 1987). One of databases was used in this study for a secondary analysis, but there were a number of limitations associated with its use. Their status as a "control group" was based in part on the ANSI committee's judgement that the participants were part of a good hearing conservation program and therefore "effectively" unexposed. Further, the limited amount of data available was all from a single time period, one that was different from the sawmill data. It also lacked data on a number of potential confounders, and on measurement methods. Thirty-five percent of data was missing for the exposure history questions. Upon examination, these "non- responders" were found to be slightly older, to have slightly increased pre-existing hearing loss at their initial hearing test, but they were not exposed to a substantially different average noise level. Individuals with any missing data were not included in the multivariate model. There is a potential for selection bias if the non-response rate was different between those who go on to have an STS and those who do not. Regarding non-occupational exposures, very large numbers reported positively to shooting-hobbies; therefore we might assume very wide-range of noise exposure in each group and subsequent misclassification. No detailed information was available with respect to magnitude or timing of exposure, nor duration etc. This would have led to substantial variability in the actual exposure received by those who respond "yes" to any of these questions, and a bias in the relative risk toward the null. It might be possible to improve the outcome measure. A reported test of the reliability of the measure identified that only 51% of those with an audiogram after an initial STS were shown to have a STS on the follow-up audiogram. Several other measures of hearing loss have been reported with higher levels of reliability (NIOSH, 1998). Misclassification of the hearing loss outcome in our analyses would also be expected to decrease relative risk estimates towards the null. Application of Analytical Technique by WCB in Other Industry Sectors We do not recommend at this time that this analysis methodology be applied to other industry sectors without the guidance of a competent statistician. We identified a number of steps in the data preparation and analysis that required a sophisticated understanding of the mathematics underlying the statistical procedure. These required decisions that cannot, at this point, be generalized into a simple protocol.   22 Possible Areas for Further Investigation Several items were identified as areas worthy of further study: ! Repeat analyses on other industry groups to determine if protocol is generalizable. ! Examine relationship of exposure and hearing loss using other definitions of threshold shift (such as "Repeated 15 dB shift at any frequency"). ! Examine the effect of hearing conservation programs on noise exposure by investigating noise levels directly; combine UBC and WCB data to look for changes in noise exposure with time. ! Improve exposure assessment by reducing misclassification due to grouping by job, and by modifying exposure levels based on predicted adoption of noise control techniques such as sound-proof booths ! Identify more appropriate external control groups (such as WCB OHO's or  Sataloff (1999) group). ! Link audiometry file to UBC sawmill cohort file to improve individual work histories  Conclusions and Recommendations Sawmill workers participating in hearing conservation programs in British Columbia are at an increased risk of hearing loss as measured by the OSHA STS (better ear). This risk increases with increasing cumulative exposure levels in a typical dose-response fashion to a relative risk of 6.6 in the highest exposed group. Hearing protection devices are associated with a 30% reduction in risk of STS. Entering a hearing conservation program at a later period in time (after 1988) was associated with a further 30% reduction. These relative risks suggest that a sawmill worker in 1996, continually wearing hearing protection, still had an elevated risk of a STS. With respect only to the utilization of audiometry data for research purposes, it is recommended that: ! Data collection protocols be changed to encourage full completion of medical and exposure histories, and the coding be updated to reflect differences between "no status change" and "refused to answer". ! Improve quality control practices to reduce the number of data errors and missing values in the audiometry file. ! Increase testing of non-exposed workers in all sites (as recommended by NIOSH, 1998) to provide better internal control data.     23 References Adera, T., Donahue, A. M., Malit, B. D., and Gaydos, J. C. (1993a) Assessment of the proposed Draft American National Standard method for evaluating the effectiveness of hearing conservation programs. Journal of Occupational Medicine 35(6), 568-73. Adera, T., Donahue, A. M., Malit, B. D., and Gaydos, J. C. (1993b) An epidemiologic method for assessing the effectiveness of hearing conservation programs using audiometric data. Military Medicine 158(11), 698- 701. Amos, N. E. and Simpson, T. H. (1995) Effects of pre-existing hearing loss and gender on proposed ANSI S12.13 outcomes for characterizing hearing conservation program effectiveness: preliminary investigation. Journal of the American Academy of Audiology 6(6), 407-13. ANSI. Draft American National Standard: Evaluation of the Effectiveness of Hearing Conservation Programs. ANSI. New York., 1991 Arslan, E. and Orzan, E. (1998 ) Audiological management of noise induced hearing loss. [Review] [21 refs]. Scandinavian Audiology. Supplementum.  48:131-45, Bertrand RA  and J Zeidan. (1999) A Statistical  Approach Used to Evaluate the Effectiveness of a HEaring Conservation Program (HCP in the Quebec Mining Industry. Journal of Occupational Hearing Loss 2(2,3), 101-113 Checkoway H., N. Pearce, DJ Crawford-Brown (1989) Research Methods in Epidemiogy, page 241, Oxford University Press, New York, New York Erdriech J  and LS Erdreich (1982) Epidemiologic Strategies to Understanding Noise-Induced Hearing Loss. In: New Perspectives on Noise Induced Hearing Loss. R. Hamernik, D Henderson  and R Salvi, eds. Raven Press, New York, New York Hosmer, DW and S. Lemeshow (1999) Applied Survival Analysis, John Wiley and Sons, New York, NY NIOSH. (1998) Occupational Noise Exposure: Revised Criteria, National Institute Occupational Safety and Health, Cincinnati, OH Ostry AS (1998) Psychosocial Job Strain and Coronary Heart Disease in a Cohort of Blue Collar Workers, PhD Thesis, University of British Columbia. Ridgely, CD and JR Wilkins. (1991) A Comparison of Median Hearing Thresholds from US Navy and US Army Audiometric Databases. Military Medicine 156, 343-345. 91. Robinson, DW and MS Shipton. (1977) Tables for The Estimation of Noise Induced Hearing Loss. Royster, JD (1999) Personal communication with WCB Hearing Conservation Branch Simpson, TH, N. Amos, WF Rintelmann (1998) Effects of Pre-existing Hearing Loss on Proposed ANSI S12.13 Outcomes for Characterizing Hearing conservation Program Effectiveness: Follow-up Investigation, J. Am. Acad. Audiol. 9:112-120 Simpson, T. H., Stewart, M., and Kaltenbach, J. A. (1993) Effects of audiometric threshold step size on proposed ANSI S12.13 outcomes for characterizing hearing conservation program effectiveness. Journal of the American Academy of Audiology 4(4), 258-63. Wolgemuth, KS, AG Kamhi, WE Lutrell, DJ Wark (1995) The Effectiveness of the Navy's Hearing Conservation Program, Military Medicine, 160:219-222   24 Appendix A: Audiometry Database Fields  Table A.1 WCB Audiometry Database File Structure  Field Retained for Analysis Description ID √ Unique personal identifier AGE √ Age of subject DOB  Date of birth SIN  Social insurance number SUBCLASS  Industry subclass identifier FIRM_NO  Company identifier LOC_NO  Location identifier (within FIRM_NO) OCCUP √ WCB occupation code OCCYRS  Years at occupation HP_USER √ Hearing protection user? TESTDATE √ Date of test (YYMM) TESTTYPE  Baseline or periodic hearing test TESTCAT  Classification of test outcome TESTYEAR  Year of test AGEGROUP  Age category HRS_AWAY  Hours away from noise before test HRS_IN  Hours in noise before test HPWRNREG  Type of hearing protector regularly worn HPBEFTST  Type of hearing protection before test LE1000HZ √ Hearing threshold, left, 1000Hz LE2000HZ √ Hearing threshold, left, 2000Hz LE3000HZ √ Hearing threshold, left, 3000Hz LE4000HZ √ Hearing threshold, left, 4000Hz LE500HZ √ Hearing threshold, left, 500Hz LE6000HZ √ Hearing threshold, left, 6000Hz LE8000HZ  Hearing threshold, left ear, 8000 Hz RE1000HZ √ Hearing threshold, right, 1000Hz RE2000HZ √ Hearing threshold, right, 2000Hz RE3000HZ √ Hearing threshold, right, 3000Hz RE4000HZ √ Hearing threshold, right, 4000Hz   25 RE500HZ √ Hearing threshold, right, 500Hz RE6000HZ √ Hearing threshold, right, 6000Hz Field Retained for Analysis Description RE8000HZ  Hearing threshold, right ear, 8000 Hz MEDHXA  ENT visit in last 5 years MEDHXB √ Ever had severe ear infection MEDHXB2  Ear infection left or right MEDHXE √ Ever had ear surgery MEDHXE2  Ear surgery left or right MEDHXF √ Ever had dizziness or balance problem MEDHXG √ Ever had a serious head injury MEDHXG2  Head injury left or right MEDHXH  Ever Blast exposure MEDHXH2  Blast exposure left or right MEDHXI  Ever had hearing aid MEDHXI2  Hearing aid left or right MEDHXJ √ Ever had a relative with hearing loss before age 50 NOISEHXA √ Ever been exposed to loud noise at prior job NOISEHXB √ Ever been exposed to noise off job NOISEHXC √ Ever been exposed to noise in armed forces FIREARMA √ Ever hunted FIREARMB √ Ever shot trap/skeet/target (not handguns) FIREARMC √ Ever shot handguns FIREARMD  Hearing protection worn while shooting FIREARME  Shoulder shot from FIREARMF  Number of years shooting   26 Appendix B: Noise Exposure Levels in Sawmill-Related Occupations The following list gives WCB occupation code and standardized WCB job title (used in audiometry file), as well as the matched UBC standardized job title which had earlier been used to code WCB sawmill exposure data that has no standardized job coding in the raw Noise Exposure file. Where a UBC standardized job title exists, the number of dosimetry measurements used in the estimation of the 8-hr Leq is given. Where the UBC standardized job is blank, the noise level was estimated from non-sawmill exposure data provided at a later date by the WCB. In all cases the number of hearing tests to which the estimate was applied is given. The table is in order of occupation code.  Table B.1 Noise Exposure Assessment WCB Occupation Code WCB Standardized Job Title UBC Standardized Job title Number of dosimetry measurements used in estimate Noise Exposure Level  (dB(A) 8-hr Leq Number of observations in audiogram Database 1113129 OFFICE/CLERICAL WORKER                     CLERK                     8 80.8 546 1116621 SAFETY/HYGIENE/INSPECTION OFFICER          MANAGER/SUPERINTENDENT     88.2 37 1133699 TEACHER/INSTRUCTOR                         CLERK                      80.8 3 2142510 ENGINEER (PROF;ENVIRONMENTAL)              CLERK                      80.8 149 2145640 INSPECTOR/QUAL CTRL/ENV MONITOR/FIELD OP                            92.3 1004 2161510 TECHNICAL SPECIALIST/INSTRUMENT TECH       ELECTRICIAN                88 67 2163466 DRAFTSPERSON/LAYEROUT                      CLERK                      80.8 94 3135276 FIRST AID ATTENDANT                        FIRST AID                 2 67.5 754 4143149 COMPUTER OPERATOR                          CLERK                      80.8 28 4153731 SHIPPER/RECEIVER                                                     5 81.3 1173 4155138 TALLYPERSON/CHECKER                        TALLYMAN                  14 81.8 2309 4155790 PARTSMAN/STOCK CLERK/TOOL CRIB                                        79 180 4157677 WEIGH SCALE OPERATOR                       YARD WORKER                81.6 41 5133855 SALESPERSON/SERVICE PERSON                 YARD WORKER                81.6 210 5193204 DELIVERY DRIVER                                                       86.5 13 6111255 FIRE INSPECTOR                             MANAGER/SUPERINTENDENT     88.2 8 6115913 WATCHMAN/SECURITY                          WATCHMAN                  10 88 1552 6191349 CLEANUP/JANITOR/UTILITY/MAINTENANCE        CLEANUP                   113 93.3 14730 7112319 GARDENER/GROUNDSKEEPER/LANDSCAPER                                81.6 13 7511255 AVALANCHE CREW/TRAIL CREW/FOREST TECH FOREST CONSERVATION OFFIC  83 344 7511316 FIRE WARDEN/FIRE CHIEF                     MANAGER/SUPERINTENDENT     88.2 22 7513267 FALLER/BUCKER/POWERSAW OP/CHAINSAW OP BUCKER                    14 95.9 1021 7513450 CAT SWAMPER                                                           90 48 7513478 BUNCHER/FELLER/DELIMBER/LOG PROCESSOR BUCKER                    14 95.9 172 7517062 BOOM WORKER                                BOOMMAN                   28 84.3 2315 7517126 SKIDDER OPERATOR                                                     2 99.5 297 7517137 CHASER                                                                91.2 196 WCB Occupation Code WCB Standardized Job Title UBC Standardized Job title Number of dosimetry measurements used in estimate Noise Exposure Level  (dB(A) Number of observations in audiogram Database   27 estimate 8-hr Leq Database 7517202 FLUME TENDER/SLIP WORKER                   SLIPMAN                   12 89.4 18 7517255 FORESTER/CONSERVATION OFFICER                                         83 1235 7517425 LANDING WORKER/LOG DECK WORKER             LOG DECKMAN               33 89 383 8153327 SCREEN TENDER                              CHIPE SCREEN TENDER       3 93 4 8159521 MOULD HANDLER                                                         96.5 3 8171143 GRINDER/RUBBER                             GRINDERMAN                21 85.7 145 8173478 PRESS OPERATOR                                                       1 89 186 8228458 PRODUCTION LINE WORKER                     AVG[…]                     93.1 287 8231059 SHAKE/SHINGLE WORKER                                                 2 90.8 116 8231088 SAWYER                                     HEAD SAWYER               168 87.8 10676 8231142 CHIP & SAW OPERATOR                        CHIPNSAW                  65 84.1 3049 8231216 DRAGSAW OPERATOR                           CUTOFF SAW                178 81.9 79 8231317 GANG OPERATOR                              GANG SAW                  4 96.3 1296 8231745 SLASHER                                                              24 91.4 362 8231806 SHAKE/SHINGLE SAWYER                                                 4 95.25 104 8231856 TRIMMER                                    TRMMER OPERATOR           523 96.8 11114 8233472 CLIPPER/JOINTER OPERATOR                                              94.7 585 8233473 GRADELINE/LATHE OPERATOR                                             3 93.3 317 8233474 STRIP SAW/RECOVERY                                                    90.8 381 8233893 MILL/PLYWOOD WORKER                        AVG[…]                     92.3 5689 8235413 KILN OPERATOR                              KILN OPERATOR             9 87.9 1065 8236455 GRADER/HANDLER/SORTER/SCALER               GRADER                    265 95.2 13957 8238038 BARKER OPERATOR/DEBARKER                   BARKER OPERATOR           244 82.9 5811 8238051 SAWMILL HAND                               LABOURER                   93.8 33874 8238134 GREENCHAIN OP/OFFBEARER/PLANER CH PULLER OFFBEARER                 229 87.8 18463 8238166 CONVEYOR WORKER                                                      14 92.5 63 8238240 EDGER OPERATOR                             EDGER OPERATOR            592 93.8 7065 8238241 EDGER/GANG TAILER                          TAILSAWYER                336 98.9 2425 8238359 HOG ATTENDANT                              HOG OPERATOR              27 90.4 417 8238595 PLANER OPERATOR                            PLANER FEEDER             81 99.2 6789 8238655 RESAW OPERATOR                             RESAWYER                  293 97.3 3941 8238756 DROP EDGE SORTER                           DROPSORT OPERATOR         312 97.8 6097 8238762 SPOTTER                                    SPOTTER                   137 98.1 179 8239202 DECK WORKER(SAWMILLS)                      LOG DECKMAN               33 88.9 1571 8239332 CHIPPER OP/BEATER/GRINDER                  CHIPPER OPERATOR          194 101.7 6106 8256830 TESTER                                                                94.6 107 8311708 TOOL & DIE MAKER                           MACHINIST                  80.7 17 8313477 MACHINE SHOP WORKER                                                   86.3 19 8313479 MACHINIST                                  MACHINIST                 9 80.7 1331 WCB Occupation Code WCB Standardized Job Title UBC Standardized Job title Number of dosimetry measurements used in estimate Noise Exposure Level  (dB(A) 8-hr Leq Number of observations in audiogram Database 8313718 MACHINE TOOL SETTER                        MILLWRIGHT                 90.9 2 8331048 BLACKSMITH/FORGER                          MILLWRIGHT                 90.9 37 8331497 CHAINMAKER                                                            94 246 8333725 SHEET METAL WORKER/TINSMITH                SHEET METAL WORKER        3 91.3 3   28 8333726 ASSEMBLER                                                             92.3 9 8335917 WELDER                                     WELDER                    20 87.4 3951 8339708 SAWMAKER/SAWSMITH                          SAWFILER                   90.5 34 8339925 WIRE ROPE WORKER                           WIRE-TIE                  7 86.3 13 8393707 FILER/FITTER                               SAWFILER (EXCL FITTER)    41 90.5 7760 8513497 AUTO BODY SHOP WORKER                                                 84.5 1 8523492 MECHANIC (AUTO, BOAT, GAS, CHAINSAW)       MECHANIC                  8 82.8 667 8549046 BENCH HAND                                 BENCHMAN                  20 90.6 859 8549931 WOODWORKER                                 CARPENTER                  87.3 141 8573894 TIREPERSON                                                            93 19 8579478 MACHINE OPERATOR                           AVG[…]                     93.9 1146 8584492 HEAVY DUTY MECHANIC                        MECHANIC                  8 82.8 4769 8584505 MILLWRIGHT                                 MILLWRIGHT                59 90.9 20048 8589556 WIPER/OILER/GREASER                        OILER                     10 88.8 2645 8592397 JOINER                                                                95 11 8595017 SPRAY BOOTH OPERATOR                       GRADER                     95.2 470 8595575 PAINTER (BRUSH)                                                       90.3 143 8715423 LABOURER                                   LABOURER                  4 93.8 2380 8719393 JACKHAMMER OPERATOR                                                   105 4 8733243 ELECTRICIAN (INCL. HELPER;APPRENTICE)      ELECTRICIAN               26 88 6810 8780768 STEAMFITTER                                PIPEFITER                 2 90.5 28 8781121 CARPENTER                                  CARPENTER                 9 87.3 1806 8791591 SPRINKLER FITTER/PIPEFITTER                PIPEFITTER                2 90.5 1122 9130811 YARDMASTER                                 YARD WORKER                81.6 3 9131444 ENGINEER(LOCOMOTIVE)                       TRAIN DRIVER              4 85.9 9 9131514 ENGINE WORKER                              MECHANIC                   82.8 42 9139119 UNLOADER                                   FORKLIFT                   90.1 58 9151054 CAPTAIN (MARINE)                           BOAT OPERATOR             67 90.8 163 9151201 MARINE DECK WORKER(DECK OFFICER,SEAMAN) BOAT OPERATOR             67 90.8 55 9159053 DOZER/BOOM BOAT OPERATOR                   BOAT OPERATOR             67 90.7 1384 9159201 BARGER/SCOW TENDER                         SCOWMAN                   9 81.8 269 9175860 TRUCK DRIVER                               TRUCK DRIVER              4 85.8 2012 9193676 PAINTER                                                              1 87 29 9238051 CAR BLOCKER                                                           88 395 9238187 CANT HOOK WORKER                           EDGER/GANG TAILER          98.9 270 9311361 HOIST/WINCH OPERATOR                       HOIST OPERATOR            24 95.2 2036 WCB Occupation Code WCB Standardized Job Title UBC Standardized Job title Number of dosimetry measurements used in estimate Noise Exposure Level  (dB(A) 8-hr Leq Number of observations in audiogram Database 9311362 CRANE CHASER/SLINGER                                                 5 82.6 112 9313214 WHARF WORKER/LONGSHORE WORKER             YARD WORKER                81.6 111 9313227 DUMPER                                                               1 94 15 9313801 SWAMPER                                                              8 90.2 470 9313908 WAREHOUSE WORKER                                                     2 75 318 9315119 TANK FARM OP/CAR LOADER (INCL. RAIL)                                 6 81.2 399 9315124 FRONT END LOADER/FORKLIFT OPERATOR        FORKLIFT                  141 90.1 23819 9315126 EQUIP OP/HEAVY(DOZER,CAT,BACKHOE,CRANE) CAT OPERATOR              65 90.6 3739   29 OP/HEAVY(DOZER,CAT,BACKHOE,CRANE) 9315457 AUTOSTACKER OP (SM;PM)                     STACKER OPERATOR          147 92 5153 9317101 BAGGER/WRAPPER/TIEUP/BUNDLER/STRAP/BA LER PACKAGE PRESS             21 85.8 4539 9317422 LABELLER/PACKER                                                       82.5 684 9318457 LUMBER PILER                               OFFBEARER                 229 87.8 10269 9319119 LOADER (BY HAND)                                                      81.5 2051 9393707 SAW FILER                                  SAWFILER                  41 90.5 1230 9539247 FIREPERSON/STATION.ENGINEER(POWER PLANT) POWER HOUSE MAINTENANCE 15 82.7 1778 9910390 CHARGEHAND/SUPERVISOR/FOREMAN              FOREMAN                   59 90.3 14221 9910518 MANAGER/SUPERINTENDENT/WARDEN              MANAGER/SUPERINTENDENT    19 88.2 1293 9918949 YARD WORKER                                                           81.6 291 9999999 NO NOISE                                                              75 7838    30 Appendix C: Sources of data error on audiometric database Only those variables listed in Appendix A as retained for analysis were checked. Among the issues that were identified were: ! "TESTTYPE" - baseline measurements: of 68027 aggregated trajectories, 18,943 had no baseline. ! "OCCUP" - Non-sawmill jobs attributed to sawmill industry ! "OCCUP": code "9999999" (non-exposed) couldn't be verified because no job title given. ! Unidentified codes in medical, noise exposure and firearm history variables ! Some birth dates had non-integer values in month, and some months = 13 or 18 ! Multiple occurrences where "OCCYRS"  > age (or implausible for given age) ! Multiple occurrences where individuals had inconsistent DOB 


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