Dr. Burstyn, in his commentary (1), underscores the critical importance of using the best exposure assessment methods possible to minimize misclassification. We agree about the value of expert formulated models for systematically and transparently documenting exposure assessment1, but caution that many existing studies may not be readily adapted to such model building. For such studies, the best alternative exposure assessment methodology should be employed, such as job-exposure matrices (JEMs) or expert assessments of self-reported work histories. Even though the relationships between the true exposure and estimates by expert assessment and a JEM are unknown (which is the case for most exposure assessments) we believe that understanding the differences between the two methods is informative, especially given the considerable time and resources necessary to carry out an expert assessment.

As Dr. Burstyn indicates (1), neither assessment approach used in our study (2) allows us to claim that lead definitely causes brain tumors. However, if this is the standard for judging the success of an exposure assessment method, most methods are failures. Although only suggestive, we do see some evidence of an association and indicate that future studies would benefit from the most accurate exposure assessment method available. The intent of our analysis was to compare two widely used approaches and to encourage epidemiologists to pursue the best exposure assessment methods possible. We acknowledge limitations with the expert assessment approach and strongly support the development and use of new exposure assessment methods. However, expert assessment may be the best approach available to an existing study and could reveal important associations that future studies can explore in greater detail using more refined exposure assessment techniques.

1. Burstyn I. The ghost of methods past: exposure assessment versus job-exposure matrix studies. Occup Environ Med 2010.

2. Bhatti P, Stewart PA, Linet MS, Blair A, Inskip PD, Rajaraman P. Comparison of occupational exposure assessment methods in a case-control study of lead, genetic susceptibility and risk of adult brain tumours. Occup Environ Med 2010.

Conflict of Interest:

None declared

Dear Editor

The article titled mental ill health and fitness for work [1] by Glozier has focused on work related mental ill health issues and has discussed various topics like screening, safety and legal issues. However as the work environments differ considering bio-psycho-social factors and different levels of exposure, which are known to increase the vulnerability for the psychiatric disorder in the workers [2] it would be better to specify the work environments while considering the prevalence of mental ill health.

The informations in the article are mostly from the developed countries. It may be relevant here to give similar perspective from developing countries like India. It would also be interesting to note similar morbidity in specific population of industrial employees, as they are known to be more vulnerable for mental ill health.[2]

The available information of prevalence of psychiatric morbidity in industrial workers show that it is considerably higher than that in general population.[3] The reported prevalence of psychiatric morbidity in working population in Western countries 20-35% as reported in the article[1] is comparable with that from Indian industrial sites (14 - 37%).[4] However, comparison would be meaningful if the working environments are similar.

The types of the mental illness reported to be common in the Western countries are similar to what is observed in various industrial set-ups in India.[4] They are basically anxiety disorders, adjustment disorders, mood disorders especially depression, somatoform disorders, alcohol and tobacco harmful use and dependence. As reported[1] comorbidies are also commonly noted in the Indian studies. The most common comorbidities are with substance use disorders.

There has been an important observation that screening for common mental disorders is probably pointless because of rapid change in illness status, numbers of persons having problem may overwhelm the occupational health service and the predictive value is low.[1] In addition different assessing instruments will give different figures. It was observed in an epidemiological survey that even if around 36.2% of employees had psychiatric problem only 9.7% of them came for the psychiatric services (Kar et al, unpublished data). It suggests that various factors influence psychiatric service utilization, like unawareness and stigma to name a few. Though the clinic population reflect realistically the magnitude of the felt need of the workers for the mental health services, periodic screening with standardized and reliable instruments may suggest the mental health need of the population, based on which optimum care programmes can be planned.

References

(1) Glozier N. Mental ill health and fitness for work. Occup Environ Med 2002;59:714-720.

(2) WHO. Epidemiology of Occupational Health, Assessment of Occupational Health. 1986 Geneva: WHO.

(3) Kar N, Dutta S, Shaktibala P, Jagadisha, Nair S. Mental health in an Indian Industrial Population: screening for psychiatric symptoms. Indian Journal of Occupational and Environmental Medicine 2002;6(2): 86-88.

(4) Kar N, Dutta S, Patnaik S, Mishra BN, Singh P. A comparative study of psychiatric morbidity among managers and workers of a fertilizer factory. Industrial Psychiatry Journal 2001;10(2):7-18.

Dear Editor

The paper by Harrison et al.[1] and the accompanying editorial by Cherrie [2] address the important issue of personal exposure assessment (of air pollutants) in environmental epidemiology. After reading both papers we would like to make some comments with regard to the design, conduct and statistical analysis of the study by Harrison et al. and at the same time answer the question raised by Cherrie in his editorial.

Coming from the occupational exposure assessment arena it is interesting to see that our environmental colleagues are still relying on to a large extent on static (micro-environmental) sampling and even rely on shadowing to represent personal exposure. The latter brought back memories of old occupational hygiene textbooks with pictures of technicians standing with a sampling probe in the breathing zone of a worker (clearly hindered while carrying out his work task). It is interesting to note that Dr Cherrie´s very relevant earlier work [3] on whether wearing sampling pumps affects exposure (it hardly did) was not mentioned in both papers.

The paper by Harrison et al.[1] clearly states as one of its goals to answer the question "Does modelling through the use of microenvironment measurements and activity diaries produce reliable estimates of personal exposure to air pollutants". However in the only setting where personal exposures were actually measured (Phase 1, volunteers; with regard to Phase 2 we do not think that shadowing results can be seen as equivalent to personal measured exposure) it is hard to grasp from both Figure 1 and Table 2 which exposure was actually modelled (1-hour averages, 2-3 day averages) and how (a formula was only provided for measurements within the susceptible groups).

When comparing direct personal measurements for CO and PM₁₀ with the modelled results, the authors exclude all data which are not directly comparable, i.e. when the volunteer spent most of their time out of house, and all the data for smokers. It is therefore not surprising that good correlations were found between personal and static measurement results. Why were smokers excluded? Was their measured CO exposure representing a different kind of CO leading to a different health effect? We know that excluding smokers or people with unventilated gas heaters is common practice in the statistical analyses of environmental exposures, but this would only make sense if we were expecting different risks from the same exposure originating from different sources.

In Figure 1 the authors present 120 comparable data points for 11 individuals and given the repeated nature of the sampling these data points cannot be seen as statistically independent. Putting a simple regression line through these points is therefore not correct and application of a mixed model would have been more appropriate. Besides that, when estimating environmental exposure for instance for a panel study, we are interested in the full range of exposures both in the temporal and spatial sense (not only for the room with the static sampler). However, Harrison et al. conclude, "...modelled personal exposure is unable to reflect the variability of measured personal exposures occasioned by the spread of concentrations within given microenvironments."

Both Cherrie and Harrison et al. claim that micro-environmental sampling would be a good alternative for direct personal exposure measurements that supposedly are "costly and time consuming". However, the costs for sampling micro environments in a general population study will be far greater if we want to measure all the micro environments people end up in (for instance in Table 1 seven environments are indicated and most of them will most likely be different for each study participant). In addition, it will be practically impossible to measure some of these environments as the authors point out. In their study, it was not possible to collect data for all appropriate microenvironments even for a comparatively small number of subjects.

Recently, a very insightful paper was presented at the X2001 conference in Gothenburg. Seixas et al.[4] showed that in a study to assess noise exposure, a task-based methodology (analogous to micro-environmental sampling in occupational exposure assessment) could only account for 30% of variability in daily exposures. They even considered this estimate somewhat optimistic since their estimated noise exposures were derived from the same data on which the daily average exposures were estimated. In addition they clearly pointed out that using simple task-based averages that artificially compress exposure variability resulted in a very substantial negative bias in the estimated daily exposure.

In our opinion, we should aim to collect personal exposure measurements when estimating exposure for epidemiological studies. We agree that smaller and lighter sampling instruments will need to be developed, as was suggested by Cherrie in his editorial. Recent studies in both the occupational and environmental arena have shown that study subjects are capable to carry out personal measurements themselves (and by doing so, cutting out the costs of the technician).[5-9] In all these studies but one [7] far more than 100 personal measurements were generated, which shows that studies of this size are not exceptional as was suggested in the editorial by Cherrie.

The question that was raised by Cherrie "How important is personal exposure assessment in the epidemiology of air pollution?" can only be answered with a firm "Very important", if we want to capture the full range of personal exposures experienced in the general environment. In addition, given the relatively low concentrations in the general environment we will need to measure these accurately. Micro-environmental monitoring and consequent modelling based on diaries will not provide sufficient resolution and accuracy.

Hans Kromhout^1,2 Martie van Tongeren³

1. Environmental and Occupational Health Division, Institute for Risk Assessment Sciences, Utrecht University, PO Box 80176, 3508 TD Utrecht, The Netherlands

2. Research Unit Respiratory and Environmental Health, Municipal Institute of Medical Research, Barcelona, Spain

3. Centre for Occupational and Environmental Health, School of Epidemiology and Health Sciences, The University of Manchester, Manchester, United Kingdom

References

(1) Harrison RM, Thornton CA, Lawrence RG, et al. Personal exposure monitoring of particulate matter, nitrogen dioxide and carbon monoxide, including susceptible groups. Occup Environ Med 2002;59: 671–9.

(2) Cherrie JW. How important is personal exposure assessment in the epidemiology of air pollutants? Occup Environ Med 2002;59:653-54.

(3) Cherrie JW, Lynch G, Bord BS, Heathfield P, Cowie H, Robertson A. Does the wearing of sampling pumps affect exposure? Ann Occup Hyg 1994;38:827-38.

(4) Seixas N, Sheppard L, Neitzel R. Comparison of task-based and full -shift strategies for noise exposure assessment in the construction industry. Arbete och Hälsa 2001; 10:51-3.

(5) Kromhout H, Loomis DP, Mihlan GJ, Peipins LA, Kleckner RC, Iriye R, Savitz DA. Assessment and grouping of occupational magnetic field exposure in five electric utility companies. Scand J Work Environ Health 1995;21:43-50.

(6) Egeghy PP, Tornero-Velez R, Rappaport SM. Environmental and biological monitoring of benzene during self-service automobile refueling. Environ Health Perspect 2000;108:1195-202.

(7) Tielemans E, Heederik D, Burdorf A, Vermeulen R, Veulemans H, Kromhout H, Hartog K. Assessment of occupational exposures in a general population: comparison of different methods. Occup Environ Med 1999;56:145 -51.

(8) Rijnders E, Janssen NAH, Vliet PHN van, B. Brunekreef. Personal and outdoor nitrogen dioxide concentrations in relation to degree of urbanization and traffic density. Environ Health Perspect 2001;109:411-7.

(9) Liljelind IE, Rappaport SM, Levin JO, et al. Comparison of self- assessment and expert assessment of occupational exposure to chemicals. Scand J Work Environ Health 2001;27:311–7.