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.

Editor,
Rushton's recent article on the reporting of occupational and environmental research raises a number of useful points that all researchers would do well to remember when writing up epidemiological findings for publication. Without expressly intending to do so, however, the article also emphasizes the hazards of establishing formal criteria or checklists for the evaluation of scientific work. Good epidemiological practices certainly exist, but one of the pitfalls inherent in attempts to codify them is that, by their nature, lists of the features of "good" research tend to impose a "one size fits all" standard, which - like clothing of the same description - fits nothing particularly well.

The prospect of developing formal guidelines for reporting analyses based on multivariable models illustrates the difficulties. Science involves many kinds of activities, but the significant advances come about through the creative application of human intellect, rather than by rote repetition of the familiar. Like other aspects of science, epidemiological data analysis blends attention to factual detail with creativity, intuition, judgement and even aesthetics. From the initial choice of model form to the final specification of covariates and interaction terms, there may be many reasonable ways to model a given data set. Researchers should be at liberty to analyze their data according to their individual scientific insights. In subsequent evaluations of methods and results, reviewers likewise should be encouraged to apply their scientific judgement, rather than following a recipe.

The opportunity cost involved in demonstrating compliance with guidelines for good practice may also be considerable, as Rushton suggests. Between the growing fear of litigation and mounting demands for accountability, especially in the United States, epidemiologists may soon spend more time documenting adherence to protocol than doing science.

My particular fear, however, is that guidelines will be used to assail sound research on the grounds that it fails to comply with supposed standards of good science. The misuse of Bradford Hill's ideas about causality illustrates the danger. Hill intended his suggestions as an aid to researchers, not as evaluative standards for critics; he wrote: "I do not believe...that we can usefully lay down some hard-and-fact rules of evidence that must be obeyed before we accept cause and effect. None of my nine viewpoints ... can be required as a sine qua non. What they can do, with greater or less strength, is help us to make up our minds on the fundamental question." [1] Yet, Hill's ideas are frequently presented as criteria that must be fulfilled for a study's evidence to be accepted.[2] The involvement of such obviously self-interested groups as the Chemical Manufacturers Association in promoting "good epidemiological practices" makes the potential misuse of guidelines to suppress good research seem all too likely.

I do not mean to suggest that all epidemiological research should be published or accepted at face value, far from it. There will always be a need for review to ensure the quality of published work and to protect the public from policies based on unsound science. I am convinced, however, that peer review coupled with the opportunity for criticism and debate in the open literature provide the best pathway to this goal. In contrast with standardized criteria, these processes allow multiple, independent readers' perspectives concerning the methodological quality, and the substantive importance of research to be heard. As a result, they reduce the chances that unconventional but valuable views will be suppressed or that an interested group could gain control over the process for their own purposes.

References
1. Hill AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295-300.
2. Gamble JF. PM2.5 and mortality in long-term prospective cohort studies: cause-effect or statistical association? Environ Health Perspect 1998;106:535-549.

Dear Editor

Dr Loomis draws attention to the potential dangers of the rigid use of checklists and guidelines to judge occupational and environmental research. I agree with these sentiments, in particular the concerns about the increasing number of papers that use compliance with these guidelines as a justification for conclusions regarding causality. There is, however, one rapidly expanding area of research that would benefit from the development of minimum standards for presentation of results. This is the field of epidemiological meta-analysis, in which data are generally abstracted from published papers. Difficulties can arise in deriving a common set of definitions for variables. For example, in a meta-analysis of oral contraceptive use and breast cancer risk,[1] 42 different categorisations of duration of oral contraceptive use were published in the 24 papers analysed for this variable. Debate within the scientific community is needed to decide categorisations that are most useful. Editors could then encourage authors either to use these in their papers or at least be prepared to make them available on request.

Reference

1. Rushton L, Jones DR. Oral contraceptive use and breast cancer risk: a meta-analysis of variations with age at diagnosis, parity and total duration of oral contraceptive use. Br J Obs Gyn 1992;99:239-246.

Editor

Chronic hand vibration exposure is now a well-described cause of Raynaud's phenomenon. According to Palmer et al, it is estimated that 220,000 cases of Raynaud's phenomenon are attributable to vibration exposure in Great Britain.[1] These epidemiological data, based on a questionnaire, are considered reasonably accurate.[2] About 4.2 million workers are exposed to hand transmitted vibration but the real health and economic impact is unknown.[3] More precise clinical data are therefore necessary before implementing a large preventive program. The hand-arm vibration syndrome encompass a wide range of disorders being responsible for digital blanching and paresthesias.[4] Different vascular problems such as a pure vasospastic phenomenon, a digital organic microangiopathy or an occlusive arterial thrombosis can be observed. A diffuse vibration neuropathy with mechanical skin receptors involvement or a carpal tunnel syndrome are also often associated.[5] The relationship between these neurovascular disorders is not clear but autonomic dysfunction in carpal tunnel syndrome can induce a Raynaud's phenomenon which is curable with surgery.[6] The prognosis of these neurovascular troubles is dependant on the underlying trouble and cannot be evaluated with a simple questionnaire. As no single test can reliably stage the vascular and neurological component, the use of a battery of tests is necessary. Digital capillaroscopy and plethysmography with nerve conduction studies are recommended as the basic tests. Cold provocation tests are effective for grading a pure vasospastic Raynaud's phenomenon but is less reliable in other forms of vibration-induced white finger explaining why this test is not always well correlated with the vascular symptoms.[7][8] Doppler and duplex studies are useful to assess the severity of an occlusive arterial disease. Workers using hand-held vibrating tools are also exposed to diverse environmental and occupational factors accounting for the wide clinical spectra of the disease. Epidemiological studies have pointed out that the prevalence of vibration-induced white finger is very wide, ranging from 0- 5% in warm climate to 80-100% in northern climate.[9] In the pure vasospastic Raynaud's phenomenon, cold exposure is probably the most important triggering factor and cold protection the most effective preventive measure. In the case of digital blanching associated with carpal tunnel syndrome, other ergonomic factors such as repetitive forceful use of the hands are likely to play a dominant role and a workplace ergonomic modification is indicated.[10] Hypothenar hammer syndrome is a another frequent cause of digital blanching in mechanics and carpenters requiring prevention of repetitive hand trauma.[11][12] For the digital organic microangiopathy and the diffuse vibration neuropathy, vibration exposure is the only identified factor and suppression of the exposition is essential. In consequences, a detailed and precise clinical diagnosis with objective tests is important to determine the real cause of the vascular symptoms. The impact of vibration exposure on health will be more precisely evaluated and prevention will be more effective.

1. Palmer KT, Griffin MJ, Syddall H, et al. Prevalence of Raynaud's phenomenon in Great Britain and its relation to hand transmitted vibration: a national postal survey. Occup Environ Med 2000;57:448-52.

2. Palmer KT, Haward B, Griffin MJ, et al. Validity of self reported occupational exposures to hand transmitted and whole body vibration. Occup Environ Med 2000;57:237-41.

3. Palmer KT, Griffin MJ, Bendall H, et al. Prevalence and pattern of occupational exposure to hand transmitted vibration in Great Britain: findings from a national survey. Occup Environ Med 2000;57:218-28.

4. Noel B. Pathophysiology and classification of the vibration white finger. Int Arch Occup Environ Health 2000;73:150-5.

5. Stromberg T, Dahlin LB, Rosen I, et al. Neurophysiological findings in vibration-exposed male workers. J Hand Surg [Br] 1999;24:203-9.

6. Verghese J, Galanopoulou AS, Herskovitz S. Autonomic dysfunction in idiopathic carpal tunnel syndrome. Muscle Nerve 2000;23:1209-13.

7. McLafferty RB, Edwards JM, Ferris BL, et al. Raynaud's syndrome in workers who use vibrating pneumatic air knives. J Vasc Surg 1999;30:1-7.

8. McGeoch KL, Gilmour WH. Cross sectional study of a workforce exposed to hand-arm vibration: with objective tests and the Stockholm workshop scales. Occup Environ Med 2000;57:35-42.

9. Bovenzi M. Exposure-response relationship in the hand-arm vibration syndrome: an overview of current epidemiology research. Int Arch Occup Environ Health 1998;71:509-19.

10. Gemne G. Diagnostics of hand-arm system disorders in workers who use vibrating tools. Occup Environ Med 1997;54:90-5.

11. Little JM, Ferguson DA. The incidence of the hypothenar hammer syndrome. Arch Surg 1972;105:684-5.

12. Ferris BL, Taylor LM Jr, Oyama K, et al. Hypothenar hammer syndrome: proposed etiology. J Vasc Surg 2000 Jan;31:104-13.