a Department of Community Health, University of Illinois, Champaign, IL 61820, USA.
b Department of Statistics, and Department of Medical Information Science, University of Illinois, Champaign, IL 61820, USA.
c Institute for Medical Research, Kuala Lumpur, 50588 Malaysia.
d Department of Preventive Medicine, University of Southern California School of Medicine, Los Angeles, CA 90033, USA.
e Department of Geography, Universiti Kebangsaan Malaysia, Bangi, 43600 Malaysia.
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Abstract |
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Methods Exposures to 20 kinds of workplace substances, solar and industrial heat, and cigarette smoke, were analysed by univariate and multivariate methods.
Results Nasopharyngeal carcinoma was associated with occupational exposures to construction, metal and wood dusts; motor fuel and oil; paints and varnishes; certain other chemicals; industrial heat; solar heat from outdoor occupations; certain smokes; cigarette smoking; and childhood exposure to parental smoking. After adjustment for risk from diet and cigarette smoke, only wood dust (OR = 2.36; 95% CI : 1.33 4.19), and industrial heat (OR = 2.21; 95% CI : 1.124.33) remained clearly associated. Wood dust remained statistically significant after further adjustment for social class. No significant crude or adjusted association was found between NPC and formaldehyde (adjusted OR = 0.71; 95% CI : 0.341.43).
Conclusions This study supports previous findings that some occupational inhalants are risk factors for NPC. The statistical effect of wood dust remained substantial after adjustment for diet, cigarette smoke, and social class. Intense industrial heat emerged as a previously unreported risk factor, statistically significant even after adjustment for diet and cigarette smoke. No association was found between NPC and formaldehyde.
Keywords Nasopharyngeal carcinoma, occupations, air particles, formaldehyde, heat, Malaysia
Accepted 10 May 2000
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Introduction |
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Methods |
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Between 1 July 1990 and 30 June 1992 we identified 530 Chinese cases with histologically confirmed NPC who had resided in the study area for at least 5 years, and been diagnosed between 1 January 1987 and 30 June 1992. Of these, 121 (23%) had died, 63 (12%) could not be located, 4 (1%) were too ill for interview, and 60 (11%) declined participation, leaving 282 cases (53%) for study. Of the 530 eligible cases, 282 were prevalent (diagnosed before 1990) and 245 were incident cases (1990 to mid-1992). The 282 NPC cases for study comprised 119 (42%) prevalent and 163 (58%) incident cases. The modest participation rate was largely due to the attempt to obtain a population-based sample, including non-hospitalized cases and prevalent cases with onset as much as 3.5 years prior to initiation of data collection. Specifically, of the 125 cases who could not be interviewed because they were too ill or had died, 104 (83%) were prevalent cases when ascertained. So were 41 (65%) of those who could not be located, some of whom may also have died.
Each case was matched by sex and age (within 3 years) to one control participant in good health with no history of cancer of the head, neck, or respiratory system, selected from the general Chinese population of the study area using a standard procedure of multistage area sampling. For each case, an interviewer began at a randomly chosen house in a randomly selected postal code district of a Chinese neighbourhood, and proceeded house-to-house by a standard algorithm15 until a qualified control, also resident in the study area for at least 5 years, was found. The overall refusal rate among eligible controls was 10%, but in affluent neighbourhoods it was 20%. Data were collected from each participant during two 4050-minute in-home, structured interviews by specially trained full-time Chinese interviewers fluent in all local dialects. The interviews requested complete residential and occupational history, information on use of alcohol and tobacco, and frequencies of consumption of 55 food items at age 10 and at 5 years prior to diagnosis of NPC for the case (for matched controls, same calendar year as the index case). For each job in the occupational history, the interview covered job description, work performed, calendar time, machines, tools and substances used, size and type of workplace, exposure to dusts, smoke, gases and chemicals. Exposures to 20 inhalants and heat from two sources were recorded by trade or profession with calendar years, frequency (days per week), and duration (hours per day) of exposure. Questions followed the format of Gerin et al.16 and Gerin and Siemiatycki.17 Inhalant selection was limited to those dusts, smoke, and gases associated with deposition or absorption in the nasopharynx, with special attention to formaldehyde.
Exposure to inhalants was subsequently coded by one of us (RWA) who is familiar with Malaysian industries and hygiene. Coding was conducted blind to case-control status. Codes were adapted from Hoar et al.,18 Gerin et al.16 and Gerin et al.19 Jobs were classified using official Malaysian occupational codes.20 Level of exposure to inhalants (ever/never, low, medium, high) was assessed with reference to kind of job, work performed, mode of contact (respiratory and/or cutaneous), respondent's reporting of exposure to particular inhalants, years of exposure, frequency, and duration.
Participants were asked about history of active smoking and exposure to cigarette smoke from spouse and other family members, and from parents while growing up. They were also asked about educational level, occupation, job status (employed, retired, etc.), spouse's and parental occupation, and house type as a basis for establishing social class.
Data analysis
Consistent with most other studies, we focus on duration of exposure. Estimated hours of each work-site exposure was calculated by subject by summing 52 x (calendar years in job) x (workdays per week) x (hours per day) over jobs where the exposure was present.
Statistical significance of each exposure's crude association with NPC was examined by sign test of estimated hours exposed, excluding tied pairs. The sign test was used because of its robustness and good performance with heavy-tailed distributions.21,22 Cigarette smoking was studied by multiple logistic regression. Cigarette smoking history was defined as present if the subject reported ever having smoked for a period of 6 months or more, and absent otherwise. For subjects with smoking histories, cumulative pack-years were estimated as reported years of smoking multiplied by scores of 0.25, 0.75, 1.25, and 2.00 for smokers, respectively, averaging <10, 1120, 2130 and >30 cigarettes daily. We examined models using dichotomous variables for cigarette smoking history >6 months, exposure to parental cigarette smoking in childhood, and exposure to cigarette smoking by spouse or other household member. We considered estimated accumulated pack-years of smoking, years of living with smoking parents, and years of living with smoking spouse or other household member as crude indices of dose, and these were also evaluated as quantitative predictors. Social class categories (poor, lower middle, upper middle, high) based on Liberatos et al.23 were constructed for each participant for time of interview, and childhood (age 10). Social class coding was blind to case-control status.
To account for possible confounding, a dietary and cigarette risk-adjusted sign test (Appendix) was obtained from a conditional logistic regression model with linear predictor (ßDzD + ßCzC + ßSs), where zD is a dietary risk index derived previously from these data3 which summarizes past consumption of salted fish, salted egg, pork or beef liver, shrimp, Chinese flowering cabbage, oranges or tangerines, and beer; zC is a cigarette smoke risk index, where zC = 1 if the case or control had smoked cigarettes for >6 months and/or had been exposed to parental smoking, and zC = 0 if neither; and s = 1 or 0 is an indicator variable identifying the member of each matched pair with highest estimated hours of past exposure. The likelihood ratio test of H0: ßS = 0 from the model-based conditional likelihood gives the adjusted test.
To indicate the strength of observed statistical relationships, the median case-control difference in hourly exposures was calculated after excluding unexposed pairs. The maximum (conditional) likelihood point estimate of the odds ratio (OR) for any exposure versus none, with exact 95% CI, was obtained from the subset of pairs with exactly one exposed subject. A dietary and cigarette risk-adjusted OR and asymptotic 95% CI were obtained from the conditional logistic regression model with linear predictor ßDzD + ßCzC + ßS*s*, where s* = 1 or 0 depending on whether the subject was ever or never exposed.
To examine possible dose-response relationships, occupational exposure was represented by x = log10(t + 1), where t = estimated hours exposed, since t is a surrogate for cumulative dose of an hypothetically toxic agent, and the logistic tolerance distribution is typically more successful in describing quantal responses to log rather than absolute doses of toxic agents.24 Logistic regression models were then fit using x, with and without the dietary index zD and cigarette smoke index zC as covariates. Non-linearity was examined by sequential addition of quadratic and, as necessary, cubic terms in x to the model. Likelihood ratio tests were used for these and other logistic model comparisons. Upon choice of a dose-response curve of order k = 1, 2 or 3 as described, effect modification by diet and cigarette smoke were examined by separate sequential addition of interaction terms zDxi and zCxi, i = 1,...k, until the first non-significant interaction term of each type was reached. In these models, a one unit increase in the exposure measure x = log10(t + 1) represents, to a very close approximation, a tenfold increase in the estimated h exposed, and estimated OR from logistic regressions are presented corresponding to this exposure ratio.
Because an association of wood dust with NPC has previously been reported and is supported by our data, other occupational exposures with OR > 1.5 after adjustment for diet and cigarette smoke were also simultaneously adjusted for diet, cigarette smoke, and wood dust. This was done by adding zW, the log-transformed hours of exposure to wood dust to the models derived above. We also checked for confounding of each occupational exposure by social class by adding three dummy variables for social class to the diet and cigarette adjustment models.
To account for a possible long NPC latency, cumulative exposures were restricted to each of five time frames: >1, 5, 10, 15 and 20 years prior to NPC diagnosis. We also classified participants by exposures above each of three thresholds: 10+ years of exposure, 5+ years of high level exposure, and 20+ years of low level exposure, at any time in working life. The impacts of latency and exposure thresholds were examined by calculating unadjusted OR for NPC using each of the eight risk dichotomies implied by the five latency periods and three thresholds defined above, and screening for trends with time frame or exposure threshold.
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Results |
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Table 1 compares cases with controls for each occupational exposure, including results of crude and diet-adjusted sign tests for statistically significant association. Although 282 case-control pairs were studied, the number of informative pairs relative to each individual exposure (pairs with at least one exposed subject), varied widely from a low of 11 (dyes) to a high of 157 (other fumes), with median of 45 pairs. The power to detect existing associations with NPC thus varied substantially among the exposures. Exposures to construction, metal and wood dusts, solar heat from outdoor occupations, industrial heat (from furnaces, rolling mills, welding machines, etc.), motor fuel and oil, paints and varnishes, other chemicals (primarily acids, bases, solvents, detergents, and soaps), and other smoke (from oil, tars, grass and other non-metallic sources), show statistically significant (
= 5%) excesses among cases. The median hourly case-control differences in exposure were between 1000 and 8000, with the exception of motor fuel and oil where the difference was 460 hours. However, only wood dust, other chemicals, and industrial heat remain statistically significant (
= 5%) after adjustment for risk from diet and cigarette smoke.
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Discussion |
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Our results confirm earlier observations that NPC in Malaysia is crudely associated with occupational exposures to chemical fumes, smoke and dusts, particularly from wood and metals. The persistence of the association with wood dust after adjustment for cigarette smoke, diet, and social class, strengthens the epidemiologic plausibility of a causal pathway involving that exposure. However, cigarette smoke and diet partially confounded the relationships of NPC to other inhalants. We did not find dose-response effects of other inhalants with substantial explanatory power beyond that of presence or absence. This leaves open the question of whether these inhalants are biologically active contributors or simply common companions of other active agents.
Formaldehyde has been suggested as a possible cause of NPC since 1980, when animal studies showed that high doses cause nasal and paranasal cancers in rats. Epidemiological studies have since sought associations between occupational exposure to formaldehyde and various cancers in low-risk NPC populations in Europe and North America. Most of these found an elevated risk for NPC in association with formaldehyde,19,2830 but not all.31 The evidence for an association between NPC and formaldehyde has recently been reviewed by the US Agency for Toxic Substances and Disease Registry.32 In 1987, the US Environmental Protection Agency,32 and in 1995 the IARC,26 classified formaldehyde as probably carcinogenic for humans.
In moderate-risk populations, to date the only case-control study to report an association between NPC and formaldehyde is that by West et al.,12 in a non-Chinese Filipino population. Using occupational histories of 257 subjects, of whom 60 (23.3%) were exposed to formaldehyde, they found OR of 3.5 for cases first exposed 25 or more years prior to NPC diagnosis, and 3.2 for cases first exposed before the age of 25, relative to those never exposed. These analyses incorporated a 10-year latency period. In contrast, our study in Malaysia is the largest case-control investigation of the formaldehyde-NPC relationship in a high-risk population, and conveys no suggestion that occupational exposure confers NPC risk. Other differences between our data and those of West et al., e.g. regarding consumption of salted and fresh fish, suggest that these populations may indeed differ with respect to NPC risk factors. However, we identified formaldehyde exposure in only 51 of 564 subjects (9.0%) of our Malaysian Chinese sample, of whom only eight had accumulated 10 years of exposure outside a 10-year latency period. The Malaysian occupations included those where exposure to formaldehyde would be expected, namely: adhesives, foundries, latex processing, metalworking and welding, plywood manufacture, rubber tire manufacture, sawmilling, shoe making (glues), and textiles (permanent press fabrics). Furthermore, confidence intervals for formaldehyde OR from these two studies overlap substantially, so the apparent differences may not be material. Considerably more data are needed to resolve the formaldehyde question.
In 19911992, we carried out baseline sampling of ambient air in 42 work sites in 10 industries in the study area. The industries were selected on the basis of occupational histories of NPC cases recorded in this and two previous Malaysian studies.2,14 Air particle sampling confirmed the presence of high-risk pollution for the nasopharynx of particles with diameter <10 µm in adhesives, metalworking, ricemills, sawmilling, and shoemaking, with mean values exceeding 150 µg/m3 which is the US Environmental Protection Agency's33 24-hour ambient air quality standard for PM-10. Formaldehyde levels exceeded the American Conference of Governmental Industrial Hygienists (ACGIH)34 threshold limit value (TLV-Ceiling) of 0.37 mg/m3 in only the adhesives industry but all others had mean 8-hour concentrations between 0.16 and 0.35 mg/m3.
To our knowledge, intense industrial heat has not previously been examined in relation to NPC. Dry heat from sources such as furnaces, welding machines, and rolling mills, combined with the tropical Malaysian climate, yields high working temperatures that may intensify the vulnerability of the nasopharynx to inspired dusts and fumes. The strength of the OR, and the persistent association after adjustment for other risk factors, indicate that this exposure warrants further investigation.
Analyses of our data by latency time frames of 5, 10, 15 and 20 years prior to diagnosis showed little difference in OR from those based on all exposure at least one year prior to diagnosis. Nor were there important differences by length of exposure (<10 versus 10 years), by age of worker (quartiles, and <45 versus
45 years), or by Chinese subethnicity. This may indicate short latency and that acute high-level exposures are more dangerous than chronic low-level exposures. Alternatively, this could be due to small numbers of participating pairs in stratified comparisons, or to measurement problems.
Cigarette smoke has been associated with cancers of the oral cavity, respiratory tract, and distant organs. Our data add to an accumulation of evidence associating cigarettes with NPC, and confirm the finding of Yu et al.5 that exposure to parental smoking during childhood plays a role. Social class has previously been associated with NPC.13 In this study, social class does not substantially confound the diet/smoking adjusted relationships to NPC of any of the occupational exposures examined.
Our study, as earlier case-control studies in high-risk NPC populations, is limited by the fairly small numbers of cases and controls reporting various uncommon occupational exposures.
Combined with random exposure measurement and occasional misclassification errors, this may have produced low power to detect statistically significant dose-response relationships. Also, in view of limited power, we did not adjust our significance testing for multiple comparisons; thus, occasional Type I errors would not be surprising. (However, the result for wood dust in Table 4 persists even after Bonferroni adjustment.) On the other hand, although standardized interviews were carried out by trained professional interviewers using structured questionnaires, recall and exposure-suspicion biases may have contributed to the predominance of positive over negative associations in our results. In addition, it should be noted that it is relatively easy to assess wood dust exposure in population-based case-control studies while it is much more difficult to assess formaldehyde exposure, and this may be a factor in our negative findings for the latter. Finally, 24% of the cases we ascertained had died or were too ill for interview at time of contact, most of these being prevalent cases, contributing to a 47% non-participation rate among diagnosed cases. Therefore, we cannot exclude the possibility of prevalence-incidence (Neyman) or other selection biases, though we are unaware of any specific presumptive rationale or evidence for their presence.
In summary, our data support previous findings that some occupational inhalants are risk factors for NPC. The statistical effect of wood dust remained substantial after adjustment for diet, cigarette smoke, and social class. Intense industrial heat emerged as a previously unreported risk factor, statistically significant even after adjustment for diet and cigarette smoke. No association was found between NPC and formaldehyde. Baseline sampling of ambient air conditions in Malaysian worksites confirms the presence of potentially high-risk particle pollution.
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Appendix |
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Acknowledgments |
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References |
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