OBJECTIVEPreviously documented indirect adjustment methods could only adjust for the confounding effects from cigarette smoking. The aim of this paper is to introduce a novel method for dealing with the effects of smoking in occupational, epidemiological cohort studies using a 'smoking adjustment factor'.

METHODSA retrospective cohort study among male silicotic workers purely exposed to silica dusts in Hong Kong (1981 - 1999) was used as an example. 'Smoking adjustment factor' in occupationally exposed smoking and nonsmoking sub-cohorts was expressed as 1/(1- PAR% )xRR and 1/1- PAR% respectively. Relative exposure effect and Synergy index were estimated to assess the multiplicative and additive interactions.

RESULTS'Smoking adjustment factor' for non-smoking and smoking silicotic workers was 1/0.33 and 1/1.62 respectively. Lung cancer standardized mortality ratio(SMR) of all cohort members was reduced from 1.61(95% CI: 1.22-2.10) to 1.08(95% CI:0.81-1.41) after indirectly adjusted for smoking effect. Results from our novel indirect method were in line with that from Axelson' s approach. Relative silicosis effect and synergy index were estimated to be 0.63 (95% CI:0.08-0.79) and 0.90 (95 % CI:0.42-1.94) ,suggesting a significant but negative multiplicative interaction between smoking and silicosis on the risk of lung cancer mortality.

CONCLUSIONThe merit of this new method was the ability to adjust for the confounding effect and evaluate the interactive effect with smoking. However, comparability of age distribution between occupationally exposed smoking and nonsmoking sub-cohorts was a prerequisite for the accurate estimations of the smoking indirectly adjusted SMR, relative exposure effect, and/or synergy index.

Cohort Studies ; Epidemiologic Methods ; Hong Kong ; epidemiology ; Humans ; Lung Diseases ; epidemiology ; mortality ; Male ; Occupational Exposure ; Retrospective Studies ; Silicosis ; epidemiology ; mortality ; Smoking ; adverse effects ; epidemiology

When study on epidemiological causation is carried out,logistic regression has been commonly used to estimate the independent effects of risk factors.as well as to examine possible interactions among individual risk factor by adding one or more product terms to the regression model.In logistic or Cox's regression model.the regression coefficient of the product term estimates the interaction on a muhiplicative scale while statistical significance indicates the departure from multiplicativity.Rothman argues that when biologic interaction iS examined,we need to focus on interaction as departure from additivity rather than departure from multiplicativity.He presents three indices to measure interaction on an additive scale or departure from additivity.using logarithmic models such aS logistic or Cox's regression model.In this paper,we use data from a case-control study of female lung cancer in Hong Kong to calculate the regression coefficients and covariance matrix of logistie model in SPSS.We then introduce an Excel spreadsheet set up by Tomas Andersson to calculate the indices of interaction on an additive scale and the corresponding confidence intervals.The results can be used as reference by epidemiologists to assess the biologic interaction between factors.The proposed method is convenient and the Excel spreadsheet is available online for free.

Rothman argued that interaction estimated as departure from additivity better reflected the biological interaction. In a logistic regression model, the product term reflects the interaction as departure from multiplicativity. So far, literature on estimating interaction regarding an additive scale using logistic regression was only focusing on two dichotomous factors. The objective of the present report was to provide a method to examine the interaction as departure from additivity between two continuous variables or between one continuous variable and one categorical variable.We used data from a lung cancer case-control study among males in Hong Kong as an example to illustrate the bootstrap re-sampling method for calculating the corresponding confidence intervals.Free software R (Version 2.8.1) was used to estimate interaction on the additive scale.

OBJECTIVETo investigate the relationship between silica or silicosis and lung cancer in a large cohort of silicotic workers in Hong Kong.

METHODSAll workers with silicosis in Hong Kong diagnosed between 1981 and 1998 were followed up till the end of 1999 to ascertain their vital status and causes of death, using the corresponding mortality rates of Hong Kong males of the same period as external comparison. Standardized mortality ratios (SMR) for lung cancer and other major causes of death were calculated. Person-year method was used. Axelson's indirect method was performed to adjust for the confounding effect of smoking. Penalized smoothing spline (p-spline) models were used to evaluate the exposure-response relationship between silica dust exposure and lung cancer mortality.

RESULTSA total of 2789 newly diagnosed cases of silicosis were included in the cohort, with an overall 24 992.6 person-years of observations. The loss-to-follow-up rate was only 2.9%. Surface construction workers (51%) and underground caisson workers (37%) constituted the major part of the cohort. There were 853 silicotics observed with an average age at death of 63.8 years. The SMR for all causes and all cancers increased significantly. The leading cause of death was non-malignant respiratory diseases. About 86 deaths were from lung cancer, giving a SMR of 1.69 (95% CI: 1.35 approximately 2.09). The risk of lung cancer death among workers in surface construction, underground caisson, and entire cohort was reduced to 1.12 (95% CI: 0.89 approximately 1.38), 1.09 (95% CI: 0.82 approximately 1.42) and 1.56 (95% CI: 0.98 approximately 2.36) respectively, after indirectly adjusting for smoking.

RESULTSfrom P-spline model did not show a clear exposure-response relationship between silica dust (CDE and MDC) and lung cancer mortality.

CONCLUSIONThis cohort study did not show an increased risk of lung cancer mortality among silicotic workers. P-spline model does not support an exposure-response relationship between silica dust exposure and lung cancer mortality.

Adult ; Aged ; Dust ; Follow-Up Studies ; Hong Kong ; epidemiology ; Humans ; Lung Neoplasms ; etiology ; mortality ; Male ; Middle Aged ; Occupational Exposure ; adverse effects ; Retrospective Studies ; Silicosis ; complications ; mortality

Background: E-waste workers in Hong Kong are handling an unprecedented amount of e-waste, which contains various neurotoxic chemicals. However, no study has been conducted to evaluate the neurological health status of e-waste workers in Hong Kong. This study aimed to evaluate the prevalence of neurobehavioral alterations and to identify the vulnerable groups among Hong Kong e-waste workers. Methods: We recruited 109 Hong Kong e-waste workers from June 2021 to September 2022. Participants completed standard questionnaires and wore a GENEActiv accelerometer for seven days. Pittsburgh Sleep Quality Index and Questionnaire 16/18 (Q16/18) were used to assess subjective neurobehavioral alterations. The GENEActiv data generated objective sleep and circadian rhythm variables. Workers were grouped based on job designation and entity type according to the presumed hazardous level. Unconditional logistic regression models measured the associations of occupational characteristics with neurobehavioral alterations after adjusting for confounders. Results: While dismantlers/repairers and the workers in entities not funded by the government were more likely to suffer from neurotoxic symptoms in Q18 (adjusted odds ratio: 3.18 [1.18–9.39] and 2.77 [1.10–7.46], respectively), the workers from self-sustained recycling facilities also have poor performances in circadian rhythm. Results also showed that the dismantlers/repairers working in entities not funded by the government had the highest risk of neurotoxic symptoms compared to the lowest-risk group (i.e., workers in government-funded companies with other job designations). Conclusion This timely and valuable study emphasizes the importance of improving the working conditions for high-risk e-waste workers, especially the dismantlers or repairers working in facilities not funded by the government.