Occupational noise exposure and blood pressure: longitudinal and cross-sectional observations in a group of underground miners – white male miners in South Africa
Patrick A. Hessel
THE EPIDEMIOLOGIC INVESTIGATION of the association between noise exposure and blood pressure has been characterized by a variety of approaches and by conflicting results. Most studies have been conducted in occupational settings; almost all have been cross-sectional; and most have not accounted for important potential confounders, such as obesity and the use of hypertensive medication by study participants. The studies can generally be dichotomized as (a) studies in which groups with high levels of occupational noise exposure are compared with those with relatively low exposures, and (b) studies in which individuals with significant hearing loss are compared with those with relatively normal hearing thresholds.
Several recent studies of noise exposure and blood pressure have shown positive associations. Parvizpoor found higher proportions of textile weavers exposed to an average of 96 dBA with hypertension and with borderline hypertension (classified according to WHO criteria than a control group of workers from light industrial plants in the same area. Neither use of hypertension medication nor obesity was mentioned in the report.
Singh et al. compared 75 healthy armed services personnel exposed to high noise levels with 36 healthy armed forces personnel not exposed to excessive noise. The exposed participants were slightly older (average age = 33.0 y) and had a lower average body mass index (BMI; 21.2 kg/[m.sup.2] than the group not exposed to noise (average age = 30.6 y; BMI = 22.2 kg/[m.sup.2]). The significance of BMI in a group of relatively young soldiers is questionable. Although the exposed group had significantly higher systolic and diastolic blood pressures, the average blood pressures were low by most standards (systolic = 121.95 mm Hg; diastolic = 79.20 mm Hg).
Belli et al. studied 490 textile workers in Italy and found that they were 34% more likely to have hypertension, compared with a group of 450 workers that included white-collar workers, the remaining blue-collar workers from the same plant, and municipal workers. The possible noncomparability of the control group, some inconsistencies in the data analysis, and a failure to consider obesity raised serious concerns about the results.
Wu and colleagues compared shipyard workers in Taiwan who were exposed to noise levels higher than 85 dBA with individuals exposed to levels lower than 80 dBA. Duration of employment, BMI, and age were comparable for the two groups in this matched study. A nested study indicated that workers exposed to higher noise levels were more than twice as likely to develop hypertension over an average of 7.25 y of retrospective follow up. A regression analysis showed that the slopes of both systolic and diastolic blood pressures on age did not differ for the high and low noise groups, but the intercepts were higher for the highly exposed group. This might indicate that noise exposure had an immediate acute effect oh blood pressure or that the highly exposed group began their working lives with higher blood pressure for reasons not apparent in the report.
Among the negative studies examining the relationship between noise exposure and blood pressure is a large study in which workers in a car assembly plant and a wire mill were compared with workers from one of these plants who were not exposed to intense noise.6 The analysis was fairly cursory and did not consider obesity or use of hypertension medication.
Lees et al. conducted a retrospective cohort study in which 70 subjects exposed to at least 90 dBA for 3-15 y were compared with a matched group exposed to no more than 85 dBA. More subjects in the low noise group were hypertensive than in the high noise group. However, the numbers were very small and the study was inclusive in this regard.
Lees et al. compared 62 workers with noise-induced hearing loss who had worked in high noise areas with 62 matched workers from quiet areas. No differences in mean systolic or diastolic blood pressure or prevalence of hypertension were noted in this small study. Obesity and use of hypertension medications were not considered.
In a cursory analysis, Delin found that employees of a ferry line in Sweden exposed to noise levels between 100 and 114 dBA in the engine room showed a prevalence of hypertension, as expected, based on Swedish rates (13.7%). He noted that 12 of the 15 men who had hypertension at the start of the investigation were overweight and that 6 of these were successful in reducing their blood pressure to normal levels after losing weight.
Talbott et al. conducted a careful study in the United States in which workers in a metal fabrication plant (average noise level = 89 dBA) were compared with workers in a less noisy plant manufacturing and assembling heating elements. No differences in systolic or diastolic blood pressure (mean of four readings) were found. Alcohol intake, BMI, and family history of hypertension were comparable for the two groups.
In two studies from the Netherlands, Verbeek et al., after controlling for age, showed only a weak correlation between the length of employment in noisy occupations, after controlling for age. Use of medications and obesity were not considered. Van Dijk et al. compared workers in a shipbuilding (average noise = 98 dBA) and machine shop (average noise = 85.5 dBA) department of a shipyard and found no difference in blood pressure after correction for age and BMI.
Among the studies showing a positive association between blood pressure and hearing loss, Jonsson and Hansson found higher levels of systolic and diastolic blood pressure in a small group of workers with at least a 65-dBA loss at 3, 4, or 6 kHz, compared with a group with less than 20-dBA loss at any frequency. Obesity and use of hypertension medication were not considered.
Manninen and Aro found higher levels of blood pressure in both male and female workers who were aged 41-64 y and who had moderate hearing loss. No differences were found for males with severe hearing loss (females were not considered in this analysis because of small numbers), and no relationship between hearing loss and blood pressure was seen for subjects less than 41 y of age. Relative weight was found to be similar between hearing-loss groups, and subjects taking hypertension medication were excluded. The size of the age groupings may have resulted in residual confounding by age.
Talbott et al. found a positive association between hearing loss and blood pressure among older workers in a noisy metal fabrication plant. They did not see this association among younger workers in the same plant or among workers in a quieter plant. Potential confounders were evaluated thoroughly. A follow-up study among retired workers aged 56 to 68 y from the same industry failed to show a relationship between blood pressure and severe hearing loss. A logistic regression analysis with hypertension as the dependent variable showed that in those aged 64 to 68, severe hearing loss approached statistical significance (p = .052) when an indicator of speech discrimination was excluded from the model and became less significant when the speech discrimination variable was included in the model.
In a study of retired workers aged 56 to 68 y from the same plant, Talbott et al. were unable to demonstrate clearly an association between noise-induced hearing loss and blood pressure. Within the subgroup of workers aged 64 to 68 y, the coefficient for noise-induced hearing loss related to hypertension approached statistical significance when an indicator of speech discrimination was excluded from the logistic regression model. When the speech discrimination variable was included in the model, the variable for noise-induced hearing loss became even less significant.
A number of studies of hearing loss and blood pressure have shown negative results. Delin found no difference between ferry workers with (n = 13) and without (n = 28) hearing loss in a small study. In two larger community-based studies, Drettner et al. studied 1 000 men aged 50 y and found no association between hearing loss and blood pressure; Hedstrand et al. found similar results in a comparison of 393 hearing-impaired individuals with 375 subjects with normal hearing.
A study of United States Air Force aircrew members (n = 2 250) included a variety of parametric and categorical analysis strategies; no association was found between noise exposure an blood pressure. The study population included men referred for evaluation of “borderline conditions potentially disqualifying the aircrew member from flying duty.” Subjects on hypertensive medication were eliminated from the analysis of blood pressure data.
With regard to studies of hearing loss and blood pressure, it is interesting to note that the studies are split between those using hearing loss as a surrogate for cumulative noise dose (thereby attempting to assess the association between noise exposure and blood pressure indirectly) and those hypothesizing that hypertension predisposes to hearing loss.
The present study focused specifically on the issue of noise exposure and blood pressure. it differs from the studies described above in that estimates of noise exposure based on individual job descriptions were used and that the study subjects were followed longitudinally.
Materials and methods
Subjects. The Medical Bureau for Occupational Diseases (MBOD) began routine audiometric screening of white mine workers in 1982. Men with every fourth year of birth were screened. Those examined from May 1982 through january 1983 were selected for study.
For each subject, the medical files of the MBOD were searched and the blood pressures, height, weight, and mention of the use of hypertension medication were abstracted at approximately 3-y intervals. Miners generally undergo physical examinations annually. Blood pressure was measured with ordinary mercury sphygmomanometers, using the fifth sound to determine diastolic blood pressure. Weight and height were measured in light clothing, absent shoes, using a heavy-duty spring scale and a ruler taped to a wall. The quetelet index was calculated as the weight (kg) divided by the square of the height (m). Subjects undergoing examination were routinely asked about all medications being taken, and these were recorded in a specified space on the report form. All mine workers undergo pre-placement examinations as well. Hypertension is not an exclusion criterion. Previous studies in this population have shown a high degree of terminal digit preference in recording blood pressure readings and no apparent drift over time in body weight measurements.
Individual information on factors, such as socioeconomic status, alcohol use, and smoking, were not abstracted. Anecdotal information would indicate that the use of tobacco and alcohol are quite common in this group. Wages are relatively high and educational requirements are modest.
Job titles were obtained for all subjects from personnel records and were recorded for the time of each blood pressure and anthropometric measurement. Noise levels time-weighted average, dBA) for each of the jobs were estimated by experienced mining engineers in the Office of the Government Mining Engineer. Estimates were based on noise levels measured for a number of jobs and work areas. In cases where there were no measurements for jobs, the estimates were based on similarities in the types of work, work areas, and the engineers’ knowledge of work processes. Approximately 600 job titles (which included many synonyms) were classified. No allowance for changes in noise levels over time were included. Changes in equipment and processes to reduce noise have been introduced relatively recently, and it was felt that noise levels for individual jobs did not change significantly over the period of employment of the study subjects. All subjects were currently employed on the mines, and all had worked at least part of their careers underground. Historic information on use of personal hearing protection was not available, but personal hearing protection was not used widely until relatively recently.
Analyses. The main analyses were performed, using linear regression techniques. Blood pressure was used as the dependent variable for cross-sectional analyses; age, BMI, and occupational noise level (dBA) were entered as independent variables in a backward elimination procedure.
With respect to the longitudinal analyses, linear regressions were calculated for each individual miner who had at least four observations. Again, the dependent variable was blood pressure (diastolic and systolic blood pressures were considered in separate analyses), and the independent variables were noise level, age, and BMI. Subjects with missing data or for whom there was no variability in noise levels were excluded because, in both instances, there was no variance in the regression coefficients, i. e., the model was saturated. These exclusions reduced the sample size for this analysis from 1 454 to 973.
Additional longitudinal regression analyses were performed by comparing, within individuals, the difference in blood pressure between two points in time (dependent variable) with the differences in noise level, BMI, and age (independent variables). All possible time period combinations were analyzed.
Given the concerns about the precision of the blood pressure measurements and noise level estimates, categorical analyses were performed, comparing those in high and low blood pressure categories by noise exposure (three categories). Blood pressure categories for the cross-sectional analyses were (a) systolic [greater than or equal to] 140 versus < 120 mm Hg, and (b) diastolic [greater than or equal to] 90 versus < 80 mm Hg. Noise levels were categorized as [less than or equal to] 85, 86-99, and [less than or equal to] 100 dBA.
For the longitudinal categorical analyses, subjects whose blood pressure increased by more than 5 mm Hg were compared with subjects whose blood pressure decreased by more than 5 mm Hg. These cutoff points were used for both systolic and diastolic blood pressures. Multivariate analyses were performed by comparing those whose blood pressure increased with those whose blood pressure decreased, controlling for changes in age and BMI.
Average values for the variables used in the analyses are presented in Table 1. The average ages changed by fewer than 3 y between time periods, despite the fact that measurements were recorded back in time at approximately 3-y intervals. This is the result of the disappearance of miners who were younger at the first time period and were, therefore, not old enough to be working during the earlier time periods. The declining sample size historically (from 2 197 to 432), therefore, is accompanied by a decline in the number of older miners in the analyses of the earlier time periods. It can be seen that average values for BMI and both systolic and diastolic blood pressures generally decreased in the earlier time period, linked with the decrease in mean age. Noise levels were generally lower for the more recent time periods but were fairly consistent for time periods 4-9. Noise levels for specific jobs ranged from less than 80 dBA for some of the managerial and surface jobs to 111 dBA for those in development areas. The average noise levels for all time periods were in excess of current standards.
[TABULAR DATA 1 OMITTED]
The change in age distribution, i. e., viewing the population historically at each of the time periods, is presented in Table 2. Similarly, the distribution of decibel levels for each of the time periods is displayed in Table 3.
[TABULAR DATA 2 & 3 OMITTED]
The results of the linear regression analyses of the cross-sectional data are presented in Table 4. Whereas age and BMI showed consistent and strong positive associations with both systolic and diastolic blood pressures, the associations between blood pressure and noise exposure were weak, not statistically significant, and varied from positive to negative.
[TABULAR DATA 4 OMITTED]
The distribution of the regression coefficients for longitudinal change in blood pressure (dependent variable) associated with change in noise level (independent variable), controlling for age and BMI, are presented in Table 5. The confidence intervals for the regression coefficients for noise levels include zero for both systolic and diastolic blood pressures. Elimination of outliers (more than 3 standard deviations) did not change the results of either analysis.
[TABULAR DATA 5 OMITTED]
When change in blood pressure between two of the time periods was compared with the change in noise level, controlling for changes in age and BMI, the regression coefficients for change in noise level were generally not statistically significant and varied between positive and negative values (Table 6).
[TABULAR DATA 6 OMITTED]
The categorical analyses showed no evidence of a relationship between blood pressure or change in blood pressure and noise level or change in noise level, respectively.
Finally, those subjects excluded from the analysis because they reported taking hypertension medication were compared with those who did not report use; no differences in noise exposure were shown.
The data showed no association between occupational noise exposure and diastolic or systolic blood pressures when viewed cross-sectionally at several points in time, or when evaluated longitudinally in several ways. Obesity, as represented by BMI, and change in BMI were strong predictors of blood pressure and change in blood pressure, respectively.
Although the strengths of the study include the ability to examine the association between noise exposure and blood pressure, both cross-sectionally and longitudinally and over a wide range of noise exposures (including very intense noise exposures), the shortcomings relate primarily to inaccuracies in measuring blood pressure and in determining occupational noise levels. These shortcomings were unavoidable given that (a) available records of routine medical examinations were used to obtain blood pressure readings, (b) noise levels had to be estimated for a number of jobs that had not been measured specifically, and (c) longitudinal data on possible changes in noise levels within specific jobs were not available. These sources of error were explored by analyzing both the cross-sectional and longitudinal data categorically. Of particular interest were analyses comparing subjects at the extremes of the distributions of blood pressure and noise exposure (and changes in these). It was assumed that, although these categories might include some misclassified workers, the misclassifications would not be sufficient to erroneously include workers at one extreme of the distribution into the other extreme. Neither the cross-sectional nor the longitudinal analyses of the categorical data showed an association between noise exposure and blood pressure.
The inclusion of black mine workers would have added considerably to the study. Black mine workers are often exposed to very high noise levels. unfortunately, the required data were not available for these workers.
Although possible inaccuracies in the data represent shortcomings, it should be noted that previous studies of noise exposure and blood pressure have generally compared groups dichotomized according to exposure levels and have not taken advantage of job-specific exposure estimates. Furthermore, no other study has examined changes in these variables within individuals over time while controlling for relevant confounding variables.
The results of this investigation are comparable with the results of a number of the previous studies that examined the association between noise exposure and blood pressure,[6-12] but differ from others.[1,2-5] The importance of obesity as a predictor of blood pressure (as demonstrated in Table 4) raises questions about those studies that did not consider this factor.[1,4,6-9,11] Of the studies that did consider a measure of obesity, the negative studies of Talbott et al. and van Dijk et al. and the positive studies of Singh et al.3 and Wu et al. appear strongest on the basis of study methodology and sample size.
Although the studies of hearing loss and blood pressure are relevant to the discussion, questions about whether hearing loss (as a surrogate for cumulative noise dose) affects blood pressure or whether blood pressure has an (indirect or direct) effect on hearing loss adds uncertainty to a body of literature already characterized by inconsistent results.
The present analysis, which is unique among those reported in the literature, has not demonstrated an association between occupational noise exposure and blood pressure. Prospective follow up that incorporates carefully standardized recording of blood pressure (including multiple readings at each point in time) and monitoring of occupational noise exposures would be beneficial for future studies if these data are not available retrospectively.
This research was supported in part by the National Health Research and Development Program of Health and Welfare Canada through a National Health Research Scholar award to Dr. Hessel.
The authors would like to thank Sister Noeline Hamlet, Ms Sylvia Martinovic, and Ms Dawn Bezuidenhout for technical assistance in conducting the study, and the Office of the Government of Mining Engineer of South Africa, especially Mr. Andre van Rensburg, for providing the noise exposure estimates.
Submitted for publication November 30, 1992; revised; accepted for publication March 30, 1993.
Requests for reprints should be sent to: Patrick A. Hessel, Ph.D., Department of Health Services Administration and Community Medicine, Faculty of Medicine, 13-103 Clinical Sciences Building, University of Alberta, Edmonton, Canada T6G 2G3.
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