Abstract
PURPOSE
Although night shift work has been associated with elevated risk of breast cancer in numerous epidemiologic studies, evidence is not consistent. We conducted a nested case-cohort study to investigate a possible association between shift work including a night shift and risk of breast cancer within a large cohort of women textile workers in Shanghai, China.
METHODS
The study included 1709 incident breast cancer cases and 4780 non-cases. Data on historical shift-work schedules were collected by categorized jobs from the factories where the study subjects had worked, and then were linked to the complete work histories of each subject. No jobs in the factories involved exclusively night shift work. Therefore, night shift was evaluated as part of a rotating shift work pattern. Hazard ratios and 95% confidence intervals were calculated using Cox proportional hazards modeling adapted for the case-cohort design for years of night-shift work and the total number of nights worked. Additionally, analyses were repeated with exposures lagged by 10 and 20 years.
RESULTS
We observed no associations with either years of night-shift work, or number of nights worked during the entire employment period, irrespective of lag intervals. Findings from the age-stratified analyses were very similar to those observed for the entire study population.
CONCLUSIONS
The findings from this study provide no evidence to support the hypothesis that shift work increases breast cancer risk. The positive association between shift work and breast cancer observed in Western populations, but not observed in this and other studies of the Chinese population, suggest that the effect of shift work on breast cancer risk may be different in Asian and Caucasian women.
Keywords: Breast cancer, night-shift work, shift work, dose-response
BACKGROUND
Breast cancer is the most frequent non-skin cancer among women, and incidence is increasing worldwide [1]. Although intensive research has been conducted to improve the understanding of the biology of breast cancer, the etiology of breast cancer remains poorly explained.
The etiologic contributions of occupational risk factors have not been adequately studied, especially in view of the large numbers of women in the workforce worldwide with potentially hazardous exposures. A potential effect of shift work on cancer risk, presumably caused by disruption of circadian rhythms, has received increasing attention in recent years. In 2007, the International Agency for Research on Cancer (IARC) classified shift work that involves disruption of circadian rhythms a probable cause of human cancer (group 2A), based on sufficient evidence from animal studies and limited evidence from epidemiological research, focused primarily on risk of breast cancer [2]. The IARC review considered eight epidemiological studies investigating the effects of shift work at night on breast cancer, of which five reported a moderate increased risk of breast cancer with shift work. The most convincing evidence came from two cohort studies [3, 4] and one nested case-control study [5], all conducted among US nurses, in which significantly increased risks of breast cancer were observed for long-term shift work (more than 20-30 years), although no effects were found for shorter durations of shift work in those studies. Since then, the results of a number of population based case-control or cohort studies [6-8] have been published on the possible association between shift work and breast cancer risk. They were further included in three updated review and meta-analyses of shift work and breast cancer risk. [9-12] Based on 15 carefully selected and newly published studies, which included three studies on flight attendants and four studies on nurses [9], Kamdar et al. conducted a meta-analysis and found a weak association (21% increased risk for workers with ever night-shift work and 4% increased risk for workers worked on night shifts eight years or longer) between night-shift work and the risk of breast cancer. The other two subsequent reports on review and meta-analysis of the same studies, excluding three studies on flight attendants and using an improved study assessment method, found a positive association between night work and the risk of breast cancer when data from the case-control studies were pooled, but no association in pooled cohort studies [10, 12].In all three reports, the authors acknowledged the large heterogeneity between studies in study design, exposure assessment, and confounding adjustment. Most of the studies examined suffered from a low quality of exposure assessment, often based on self-report.
To date, the evidence from epidemiological studies for a causal association between night-shift work and breast cancer risk remains inconclusive. Apart from the published study by Pronk et al. [7], all epidemiologic studies on shift work and breast cancer had been conducted in predominantly Caucasian women.
We undertook the current study to determine whether shift work altered the risk of breast cancer in a large, well-characterized cohort of textile workers in China.
MATERIALS AND METHODS
Study Population and Case Finding
The present study was an extension of a series of case-cohort studies of textile industry exposures to dusts, chemicals and other physical agents in relation to risks of various cancers [13-17]. Briefly, the previous studies were based in a cohort of 267,400 workers from 503 textile factories in the Shanghai Textile Industry Bureau (STIB) who were recruited in 1989-1991 for a randomized trial of the effect of breast self-examination on breast cancer mortality [13, 18]. The cohort consisted of active and retired employees who were permanent residents of Shanghai born between January 1, 1925 and December 31 1958. At enrollment into the trial, women were administered a baseline questionnaire that elicited information on demographic variables, lifestyle habits, and reproductive history.
Follow-up of the cohort has been described previously [13]. All women were followed for breast cancer incidence through July 2000 by frequent review of factory medical records, and from annual medical reports submitted by each factory clinic to a cancer and death registry maintained by the Station for the Prevention and Treatment of Cancer of the Shanghai Textile Industry Bureau (STIB). Case identification was supplemented by manual reviews of records from the Shanghai Cancer Registry (SCR), and a computerized matching of the trial cohort to the SCR data. All incident breast cancer cases were verified by review of pathology reports or histologic review of tissue slides as part of the trial. A total of 1763 breast cancer cases was identified and verified.
Two methods were utilized to construct a comparison group. The 3139 breast cancer free women who had been randomly selected from the cohort using an age stratification scheme for a series of occupational studies were utilized in the current study [15]. Some of the breast cancer cases had been previously included in two nested case-control studies of nutritional factors and induced abortion [19, 20]. The 1697 controls for those studies were selected from the cohort members such that their age distribution approximated that of the breast cancer cases. These controls were added to the comparison group. Thus, the total number of women in the comparison group in this study is 3139 + 1697 = 4836.
Exposure Assessment
Work History
Information on all textile industry jobs that were held by each study subject since the date of first employment in the STIB was collected by trained field workers from review of factory personnel records (80%), interviews of factory supervisors (12%), and in-person interviews of women or their relatives (8%). For each job that a woman held, the field workers recorded the dates of employment, workshop, and job tasks.
Shift Work
Each STIB factory had its own history of shift work that was mandated by government policy. Shift work policies changed over time, with changes having been relatively uniform across factories within the same sector (cotton, wool, etc.). Therefore, data on shift work was collected by major manufacturing processes (e.g., fiber processing, spinning, dyeing) from all factories.
Trained study interviewers obtained a historical shift work profile for all but three factories where cases and non-cases had worked, based on interviews of factory management personnel. Shift work patterns in those three factories (2 textile machinery manufacturing and 1 fabric bleaching and printing factory), in which 11 subjects ever worked, were estimated from other factories of the same sectors. No jobs in the STIB factories involved exclusively night shift work. Therefore, we only considered night shift as part of a rotating shift pattern. Whether a job involved a rotation schedule, shift rotation cycle, daily rotation schedule (start time and end time of each shift), and changes of shift policy over time were recorded.
The factory-level shift work information was linked to each study subject's work history data. Each job was first classified into never/ever involved a rotating night-shift work. Night shift was defined as continuous working between 2400 and 0500 hours. The number of total nights worked per month was computed for jobs involving a night shift. For example, a woman worked as an operator in the spinning process in Cotton Mill No.1 between 1975 and 1980. The shift work information from the factory indicates that machine operators in the spinning process worked on a three-shift rotation schedule from 1970 to 1985: 2 days on morning shifts (0600-1400), 2 days on swing shift (1400-2200), 2 days on night shift (2200-0600), then 2 days off-work before starting the rotation cycle again). Therefore, each rotation cycle took 8 days. The total number of nights for the woman worked per month would be 7.5 nights [2 nights × (30 days /8 days)]. Total nights the woman worked on the job is 7.5 nights × 12 months × 5 years.
In addition, the associations of breast cancer with night work exposure were examined by lagging exposure times by 10 or 20 years before the diagnosis of breast cancer to take into account a possible latency period of the effect of exposure to night work on breast cancer risk.
The study was approved by the Institutional Review Boards of the Fred Hutchinson Cancer Research Center, the University of Washington, and the Station for Prevention and Treatment of Cancer of the Shanghai Textile Industry Bureau, in accordance with an assurance filed with the Office for Human Research Protections (OHRP) of the U. S. Department of Health and Human Services.
Statistical Analysis
For the analysis addressing associations between night-shift work and breast cancer, we conducted Cox proportional hazards modeling, adapted for the age-stratified case-cohort design, to calculate relative risk estimates (hazard ratios [HRs] and 95% confidence intervals [CIs]) for breast cancer associated with various measures of night-shift work. Robust variance estimates were used to compute standard errors of hazard ratios. The risk period was defined as time since entry into the cohort until the date of breast cancer diagnosis, death, or end of follow-up on July 31, 2000, whichever came first. Because workers’ durations of shift work changed during the risk period, we organized the analytic dataset into risk sets to accommodate the time-dependent exposure, using the computational methods developed by Langholz and Jiao [21]. For each risk set, cumulative exposure to night-shift work was calculated first as the duration of years worked on rotating shift work including a night shift, then as cumulative number of nights worked, for the cases and non-cases up to the cases’ failure times. Cumulative exposure during the entire work history was categorized into five groups: unexposed and four quartiles of exposure, with the cutoff points defined by the distribution of cumulative exposure among the cases. Dose-response trends were tested by the statistical significance of the coefficient for linear trend on the median values of the quartile groups among exposed subjects only.
Analyses were also conducted in which exposures were lagged by 10 and 20 years to take into account disease latency. We repeated the analyses in a subgroup of all women to examine the effects of a more frequent shift rotation: 2 morning-2 swing-2 night clockwise rotating cycle on risk of breast cancer.
Reproductive history including the number of live births (grouped as 1, 2, 3, 4, >5), lifetime duration of breast feeding (grouped as never, <6, 7-12, 13-24, 25-36, 37-48, >49 months), and alcohol use (as yes/no) collected at baseline were examined as potential confounding factors. Prevalence of smoking was less than 10% in the cohort, and is not an established risk factor for breast cancer, and therefore was not examined as a potential confounding factor.
Although we did not have data on age at menopause, we examined possible effect modification by repeating the risk estimates as described separately for women <50 and ≥ 50 years old.
Magnetic field (MF) exposures, which have been investigated previously [22], are thought to share similar mechanisms of melatonin suppression and hormonal dysregulation. Joint effects of shift work and MF exposures were evaluated by stratifying subjects into four groups based on two levels of each exposure (Cutpoints are 6.24 μT-yrs for MF exposure and 27.5 years for shift work duration).
All statistical analyses were performed in SAS, version 9.1 (SAS Institute Inc., Cary, North Carolina).
RESULTS
Characteristics of Study Subjects
The average age at diagnosis for 1709 cases was 53.4 years old. Breast cancer cases tended to be slightly younger than the comparison group (Table 1). All women entered the follow-up period between ages 30 and 66 years. The average duration of follow-up for cases and non-cases were 5.2 and 10.9 years respectively. Most of the subjects had worked >20 years, and few women had more than two jobs.
Table 1.
Characteristics of the cases and non-cases among woman textile workers in Shanghai, China
| Case (n=1709) | Non-case (n=4780) | |||
|---|---|---|---|---|
| n | % | n | % | |
| Birth year | ||||
| 1925-1929 | 266 | (15.56) | 1090 | (22.57) |
| 1930-1934 | 371 | (21.71) | 1158 | (23.98) |
| 1935-1939 | 173 | (10.12) | 523 | (10.83) |
| 1940-1944 | 113 | (6.61) | 251 | (5.20) |
| 1945-1949 | 252 | (14.75) | 453 | (9.38) |
| 1950-1954 | 335 | (19.60) | 625 | (12.94) |
| 1955-1958 | 199 | (11.64) | 730 | (15.11) |
| Age at beginning of follow-up (yrs) | ||||
| 30 - 40 | 568 | (33.24) | 1396 | (29.21) |
| >40 - 50 | 341 | (19.95) | 664 | (13.89) |
| >50 - 60 | 556 | (32.53) | 1721 | (36.00) |
| >60 - 66 | 244 | (14.28) | 999 | (20.90) |
| Duration of follow up (yrs) | ||||
| mean (SD) | 5.19 | (2.92) | 10.9 | (1.35) |
| Work history | ||||
| Years of employment in STIB | ||||
| <=20 | 524 | (30.66) | 1354 | (27.91) |
| >20 - 30 | 766 | (44.82) | 2183 | (45.67) |
| >30 - 40 | 414 | (24.22) | 1236 | (25.86) |
| > 40 | 5 | (0.29) | 27 | (0.56) |
| Average number of jobs held | ||||
| 1 | 761 | (44.53) | 2536 | (53.05) |
| 2 | 635 | (37.16) | 1555 | (32.53) |
| 3 | 224 | (13.11) | 474 | (9.92) |
| 4+ | 67 | (5.20) | 33 | (4.50) |
| Shiftwork | ||||
| No | 968 | (56.64) | 2341 | (48.97) |
| Yes | 741 | (43.36) | 2439 | (51.03) |
| Years doing shiftwork | ||||
| 1 -- <= 10 | 21 | (2.83) | 62 | (2.54) |
| 10--<=15 | 57 | (7.69) | 158 | (6.48) |
| 15--<=20 | 135 | (18.22) | 404 | (16.56) |
| More than 20 | 528 | (71.26) | 1815 | (74.42) |
Associations between risk of breast cancer and reproductive and life style risk factors for breast cancer cases compared to the breast cancer free women randomly selected from the cohort, using an age stratification scheme for a series of occupational studies, have been published previously [15]. The analyses were repeated with the expanded comparison group for this study. The results were similar to those previously published. Risk of breast cancer was elevated in nulliparous women and increased with age at first live birth. Risk decreased with increased number of live births and in women who breast fed for more than four years. There were few cigarette smokers, and about 20 % of the subjects ever consumed alcohol. Neither of these factors was associated with risk of breast cancer.
Shift Work
The hazard ratios for breast cancer in relation to the number of years worked on rotating night shift throughout the entire work history period, and for exposure lagged 10 and 20 years, respectively, are presented in Table 2. All relative risk estimates were close to unity except for a significantly decreased HR estimate for the 3rd quartile in the exposure lagged 10 years. Risk decreased with increasing duration of shift work in the lagged analyses, and the trend test for the exposure lagged 20 years was statistically significant, but the 95% confidence intervals of the risk estimates for all three incremental quartiles included unity.
Table 2.
Risk of breast cancer in relation to YEARS worked on rotating night shift among textile workers in the Shanghai textile industry (1709 cases and 4780 non-cases).
| Cumulative exposure (years) | Cases | HRa | 95% CI |
|---|---|---|---|
| Entire employment periodb | |||
| 0 | 557 | 1.00 | (ref) |
| >0-12.8 | 286 | 0.99 | (0.83, 1.17) |
| >12.8-19.92 | 290 | 0.97 | (0.82, 1.15) |
| >19.92-27.67 | 289 | 0.90 | (0.76, 1.06) |
| >27.67 | 287 | 0.88 | (0.74, 1.05) |
| p-value for trend* | 0.095 | ||
| 10-year lag | |||
| 0 | 577 | 1.00 | (ref) |
| >0-12.8 | 431 | 0.98 | (0.84, 1.15) |
| >12.8-19.92 | 266 | 0.99 | (0.83, 1.17) |
| >19.92-27.67 | 200 | 0.81 | (0.67, 0.98) |
| >27.67 | 235 | 0.91 | (0.75, 1.10) |
| p-value for trend | 0.060 | ||
| 20-year lag | |||
| 0 | 725 | 1.00 | (ref) |
| >0-12.8 | 516 | 1.03 | (0.89, 1.20) |
| >12.8-19.92 | 180 | 0.90 | (0.74, 1.10) |
| >19.92-27.67 | 179 | 0.90 | (0.74, 1.11) |
| >27.67 | 109 | 0.88 | (0.68, 1.14) |
| p-value for trend | 0.035 |
Hazard ratios (HR) and 95% Confidence Interval (CI) adjusted for age at the beginning of follow-up (as a continuous variable)
Exposure were categorized based on the distribution of the entire employment period of the exposed cases
Trend tests were restricted to the exposed subjects. Cutpoints were determined based on the median values of each quartile.
When exposure was assessed based on the cumulative number of nights worked (Table 4), most HRs were also close to unity and not statistically significant, and there were no significant trends in risk with number of nights worked.
Table 4.
Risk of breast cancer (1709 cases) in relation to the number of NIGHTS worked among textile workers in the Shanghai textile industry.
| Cumulative exposure (night shifts) | Cases | HRa | 95% CI |
|---|---|---|---|
| Entire employment periodb | |||
| 0 | 557 | 1.00 | (ref) |
| >0-1316.79 | 288 | 0.96 | (0.81, 1.14) |
| >1316.79-2018.71 | 287 | 1.00 | (0.84, 1.19) |
| >2018.71-2880 | 288 | 0.88 | (0.74, 1.04) |
| >2880 | 289 | 0.89 | (0.75, 1.07) |
| p-value for trend* | 0.155 | ||
| 10-year lag | |||
| 0 | 577 | 1.00 | (ref) |
| >0-1316.79 | 422 | 0.99 | (0.84, 1.15) |
| >1316.79-2018.71 | 250 | 0.99 | (0.83, 1.18) |
| >2018.71-2880 | 207 | 0.84 | (0.70, 1.02) |
| >2880 | 253 | 0.89 | (0.74, 1.08) |
| p-value for trend | 0.071 | ||
| 20-year lag | |||
| 0 | 725 | 1.00 | (ref) |
| >0-1316.79 | 497 | 1.08 | (0.94, 1.24) |
| >1316.79-2018.71 | 175 | 0.93 | (0.77, 1.14) |
| >2018.71-2880 | 134 | 0.89 | (0.71, 1.11) |
| >2880 | 178 | 0.92 | (0.74, 1.14) |
| p-value for trend | 0.046 |
The results in Table 2 and Table 4 were not appreciably altered by further adjusting for number of live births, age at first live birth, and alcohol intake. Findings from the age-stratified analyses (<50, ≥ 50 years) were very similar to those observed for the entire study population.
There were 1550 women (973 cases, 577 non-cases) who had changed their shift work pattern from a 6 morning - 6 swing - 6 night cycle to a 2 morning - 2 swing - 2 night cycle in the mid −80s, and had worked on the latter shift cycle for at least 3 years. Risks of breast cancer were not altered significantly for those women compared to the women who had never worked on shift work (data not shown).
There was no evidence of a combined effect on risk of breast cancer by exposures to magnetic fields and durations of shift work (table 6).
Table 6.
Joint effects of shift work and magnetic field exposure on risk of breast cancer (1709 cases and 4780 controls)
| Stratified group* | Cases | HRa | 95% CI |
|---|---|---|---|
| Entire employment period | |||
| MF ≤ 6.24 μT-yrs and shift work duration ≤ 27.5 yrs | 1101 | 1.00 | (ref) |
| MF ≤ 6.24 μT-yrs and shift work duration > 27.5 yrs | 165 | 0.94 | (0.77, 1.14) |
| MF > 6.24 μT-yrs and shift work duration ≤ 27.5 yrs | 299 | 1.02 | (0.88, 1.19) |
| MF > 6.24 μT-yrs and shift work duration > 27.5 yrs | 122 | 0.87 | (0.70, 1.08) |
| Redefined shift work groups | |||
| MF ≤ 6.24 μT and shift work = 0 | 467 | 1.00 | (ref) |
| MF ≤ 6.24 μT and shift work > 0 | 799 | 0.92 | (0.81, 1.06) |
| MF > 6.24 μT and shift work = 0 | 73 | 0.91 | (0.68, 1.22) |
| MF > 6.24 μT and shift work > 0 | 348 | 0.94 | (0.80, 1.11) |
MF: Magnetic fields. The cutoff points for categories were defined by the values at the 75th percentiles for the duration of years working on night-shift work and cumulative exposure of MF (μT -years)
HR: Hazard Ratio; 95% CI: confidence interval
DISCUSSION
We found no evidence for an association between rotating night-shift work and the risk of breast cancer in this large cohort of female textile workers in China. Our findings are consistent with the results of several previous studies [6, 8, 23], including the prospective cohort study among Chinese women [7], but not with the reports from several other studies in Caucasian populations. [3-5, 24-27] In a registry-based cohort study in Sweden, Schwartzbaum et al. [28] observed no increase (SIR=0.97, 95% CI: 0.67-1.4) in risk of breast cancer among female workers who likely worked on shift work. No association between shift work and breast cancer risk was reported in a cohort of telegraph operators in Norway [29]. Of five studies reporting an effect of shift work on breast cancer [3-5, 24, 25], three studies reported an increased risk of breast cancer with long-term rotating shift work (RR=1.36, 95% CI: 1.04-1.78 and RR=2.21, 95% CI: 1.10-4.45 for duration >= 30 years; RR=1.79, 95% CI: 1.06-3.01 for the duration >= 20 years) [3-5]; and two found the increased risk of breast cancer with ever worked night shift (RR=1.6, 95% CI: 1.0-2.5; RR=1.5, 95% CI: 1.3-1.7) [24, 25].
To date, our study is the largest study to have examined the association between shift work and breast cancer risk in an Asian population. Pronk et al. [7] investigated the association in a population-based prospective cohort study of 73,049 Shanghai women aged between 40 – 70 years. The cohort was followed for incident breast cancer for an average of 9 years and 717 breast cancer cases were identified. Similar to our findings, the results from the Pronk et al. cohort study showed no associations with shift work.
There are several possible explanations for the observed null association between breast cancer risk and shift work in our study. Shift work information was collected at the factory level, and then linked to subjects’ work histories. The main advantage of using such linkage was to avoid recall bias. However, using the aggregate level for exposure assessment has the possibility of exposure misclassification. In the STIB, when a factory instituted a shift work policy, it affected virtually all women in any particular job type; thus, applying the factory level information on shift work by job to each of the individuals in our study minimized misclassification. Also, misclassification was minimized by the stability of the jobs held by the study subjects. About 85% of women in our study had only one or two jobs in their whole work history and 72% of women worked longer than 20 years. It is also worth noting that, despite some probable degree of misclassification of our shift work assessment, the use of standardized factory shift work policy information and linkage to workers’ personnel records, avoided inaccuracies typically associated with study subjects’ recall bias. Therefore, it seems unlikely that exposure misclassification or other inaccuracies masked any strong associations in this study.
An alternative explanation for our null findings is that the association of shift work and breast cancer may vary by race and ethnicity. In fact, our findings are consistent with the reports in another Chinese population [7], but differ considerably from the findings reported from studies in Caucasians in the US and Scandinavia. It is possible that the conflicting findings reveal true biological differences between the populations. One of the hypothesized biological mechanisms to explain the possible causal effect of night shift on increasing risk of breast cancer is through melatonin suppression. Exposure to light at night, such as from working night shifts, suppresses the nocturnal rise in melatonin production and release by pineal gland [30]. This suppression results in increased gonadotropin production in the pituitary, and leads to increased levels of ovarian hormones, which have a simulative effect on the mammary epithelium. The dark eye color of Chinese women may prevent the suppression of melatonin secretion from nocturnal light. This hypothesis is supported by two recent studies mentioned by Girschik et al. [31] in their letter discussing the findings by Pronk et al. In a small intervention study (n=11) light-filtering goggles’ were effective in preventing the suppression of melatonin by nocturnal lighting in Caucasians but not Asian men [32]. In another study comparing the influence of eye colors of Caucasians and Asian on suppression of melatonin secretion by light, two groups of subjects were exposed to light (1000 lux) for 2 hours at night, and suppression of melatonin by light was found to be significantly stronger for Caucasians (88.9 +/− 4.2%) than for Asians (73.4 +/− 20.0%) [33].
There are a number of other reasons that could contribute to inconsistent findings among the published studies, such as different definitions for night shift work, variations in duration of shift work, differences in workshop light intensity and shift cycle, and uncontrolled confounding by other variables. In addition, it is still unclear which shift cycle or timing of exposure is most relevant to breast carcinogenesis.
There are several noteworthy strengths of our study. Our study was based in a well-defined occupational cohort, and included a very large case group. In addition, we were able to collect a complete work history for each woman and detailed information on shift work policy from each factory. We also had detailed shift work information for each job including shift type, schedule of each shift, rotation cycle, and change of shift policy, which enabled us to accurately calculate cumulative exposure to night shifts.
There are also limitations of our study that warrant mention. Because no assigned jobs were exclusively night shift, we could not investigate associations that may be specific to night shift. Instead, night-shift work was embedded within rotating shift work patterns. We did not have direct information on menopause, but instead, used age (<50 vs. >50 years) as a surrogate stratification variable. Nonetheless, it is unlikely that inferences regarding associations for pre- and post-menopausal women were erroneous. Information on women's Body Mass Index was not available. However, we do not expect women's Body Mass Index to be a confounder as it would be unlikely to relate to shift work. Women enrolled in the study were permanent or retired textile workers in STIB and have health insurance provided by STIB. Therefore, the likelihood of being diagnosed with breast cancer is the same for all workers regardless their work type and schedule.
In summary, rotating shift work was not associated with the risk of breast cancer in a cohort of female textile workers in Shanghai, China. Our results, although in conflict with findings of several studies in Caucasian women, are consistent with the findings in one other Chinese cohort. The effect of shift work on breast cancer risk may be different in Caucasian and Asian populations. More evidence from non-Western populations is needed.
Table 3.
Risk of breast cancer in relation to YEARS worked on rotating night shift for two groups of women divided by age.
| Cumulative exposure (years) | Cases | HRa | 95% CI |
|---|---|---|---|
| women < 50 years old (732 cases) | |||
| Entire employment period | |||
| 0 | 273 | 1.00 | (ref) |
| >0-11.0 | 114 | 0.87 | (0.67, 1.12) |
| >11.0-16.8 | 118 | 0.94 | (0.73, 1.22) |
| >16.8-21.54 | 112 | 1.06 | (0.81, 1.37) |
| >21.54 | 115 | 0.94 | (0.72, 1.22) |
| p-value for trend* | 0.453 | ||
| 10-year lag | |||
| 0 | 292 | 1.00 | (ref) |
| >0-11.0 | 239 | 0.89 | (0.73, 1.10) |
| >11.0-16.8 | 125 | 1.02 | (0.80, 1.31) |
| >16.8-21.54 | 69 | 1.07 | (0.78, 1.46) |
| >21.54 | 7 | 0.88 | (0.39, 1.99) |
| p-value for trend | 0.344 | ||
| 20-year lagc | |||
| 0 | 437 | 1.00 | (ref) |
| >0-11.0 | 280 | 1.02 | (0.84, 1.25) |
| >11.0-16.8 | 15 | 0.98 | (0.55, 1.73) |
| p-value for trend | 0.896 | ||
| Women ≥ 50 years old (977 cases) | |||
| Entire employment period | |||
| 0 | 284 | 1.00 | (ref) |
| >0-14.5 | 173 | 1.23 | (0.97, 1.56) |
| >14.5-24.2 | 173 | 0.86 | (0.68, 1.09) |
| >24.2-31.17 | 174 | 0.85 | (0.67, 1.07) |
| >31.17 | 173 | 0.96 | (0.76, 1.23) |
| p-value for trend* | 0.430 | ||
| 10-year lag | |||
| 0 | 285 | 1.00 | (ref) |
| >0-14.5 | 177 | 1.22 | (0.97, 1.55) |
| >14.5-24.2 | 201 | 0.84 | (0.67, 1.06) |
| >24.2-31.17 | 156 | 0.87 | (0.68, 1.10) |
| >31.17 | 158 | 0.97 | (0.75, 1.25) |
| p-value for trend | 0.015 | ||
| 20-year lag | |||
| 0 | 288 | 1.00 | (ref) |
| >0-14.5 | 268 | 1.06 | (0.86, 1.30) |
| >14.5-24.2 | 225 | 0.91 | (0.73, 1.13) |
| >24.2-31.17 | 156 | 0.91 | (0.71, 1.18) |
| >31.17 | 40 | 0.88 | (0.59, 1.33) |
| p-value for trend | 0.015 |
Table 5.
Risk of breast cancer in relation to the number of NIGHTS worked for two groups of women stratified by age.
| Cumulative exposure (night shifts) | Cases | HRa | 95% CI |
|---|---|---|---|
| Women < 50 years old (732 cases) | |||
| Entire employment periodb | |||
| 0 | 273 | 1.00 | (ref) |
| >0-1114.29 | 115 | 0.83 | (0.64, 1.07) |
| >1114.29-1603.39 | 113 | 0.95 | (0.73, 1.23) |
| >1603.39-2116.61 | 117 | 1.08 | (0.83, 1.40) |
| >2116.61 | 114 | 0.96 | (0.74, 1.26) |
| p-value for trend* | 0.200 | ||
| Exposure Window 1: >20 yrs | |||
| 0 | 292 | 1.00 | (ref) |
| >0-1114.29 | 241 | 0.91 | (0.75, 1.12) |
| >1114.29-1603.39 | 112 | 1.10 | (0.85, 1.43) |
| >1603.39-2116.61 | 70 | 0.92 | (0.68, 1.26) |
| >2116.61 | 17 | 1.12 | (0.64, 1.97) |
| p-value for trend | 0.533 | ||
| Exposure Window 2: >10-20 yrsc | |||
| 0 | 437 | 1.00 | (ref) |
| >0-1114.29 | 271 | 1.05 | (0.87, 1.26) |
| >1114.29-1603.39 | 24 | 1.07 | (0.67, 1.71) |
| Women ≥ 50 years old (977 cases) | |||
| Entire employment periodb | |||
| Quartiles | |||
| 0 | 284 | 1.00 | (ref) |
| >0-1627.5 | 173 | 1.09 | (0.88, 1.36) |
| >1627.5-2588.21 | 172 | 0.84 | (0.68, 1.04) |
| >2588.21-3453.78 | 174 | 0.91 | (0.74, 1.13) |
| >3453.78 | 174 | 0.93 | (0.74, 1.16) |
| p-value for trend* | 0.140 | ||
| Exposure Window 1: >20 yrs | |||
| Quartiles | |||
| 0 | 285 | 1.00 | (ref) |
| >0-1208.57 | 177 | 1.08 | (0.87, 1.35) |
| >1208.57-1883.93 | 197 | 0.84 | (0.68, 1.03) |
| >1883.93-2911.07 | 145 | 0.90 | (0.71, 1.13) |
| >2911.07 | 173 | 0.97 | (0.78, 1.22) |
| p-value for trend | 0.243 | ||
| Exposure Window 2: >10-20 yrs | |||
| Quartiles | |||
| 0 | 288 | 1.00 | (ref) |
| >0-363.75 | 285 | 1.02 | (0.85, 1.24) |
| >363.75-630 | 185 | 0.94 | (0.76, 1.16) |
| >630-908.57 | 130 | 0.90 | (0.71, 1.14) |
| >908.57 | 89 | 0.97 | (0.74, 1.29) |
| p-value for trend | 0.156 |
ACKNOWLEDGEMENTS
We thank Wen Wan Wang, the Shanghai study manager and 30 field-workers for collecting women's work history records; and Georgia Green, Steve Weston, and Terri Watson for their technical and administrative support.
This work was supported by the National Institute for Occupational Safetyand Health (grant number R01OH008149); and the National Cancer Institute at the National Institutes of Health (grant number R01CA80180).
References
- 1.Althuis MD, Dozier JM, Anderson WF, Devesa SS, Brinton LA. Global trends in breast cancer incidence and mortality 1973-1997. Int J Epidemiol. 2005;34:405–12. doi: 10.1093/ije/dyh414. [DOI] [PubMed] [Google Scholar]
- 2.Straif K, Baan R, Grosse Y, et al. Carcinogenicity of shift-work, painting, and fire-fighting. The lancet oncology. 2007;8:1065–6. doi: 10.1016/S1470-2045(07)70373-X. [DOI] [PubMed] [Google Scholar]
- 3.Schernhammer ES, Kroenke CH, Laden F, Hankinson SE. Night work and risk of breast cancer. Epidemiology. 2006;17:108–11. doi: 10.1097/01.ede.0000190539.03500.c1. [DOI] [PubMed] [Google Scholar]
- 4.Schernhammer ES, Laden F, Speizer FE, et al. Rotating night shifts and risk of breast cancer in women participating in the nurses’ health study. Journal of the National Cancer Institute. 2001;93:1563–8. doi: 10.1093/jnci/93.20.1563. [DOI] [PubMed] [Google Scholar]
- 5.Lie JA, Roessink J, Kjaerheim K. Breast cancer and night work among Norwegian nurses. Cancer causes & control : CCC. 2006;17:39–44. doi: 10.1007/s10552-005-3639-2. [DOI] [PubMed] [Google Scholar]
- 6.Pesch B, Harth V, Rabstein S, et al. Night work and breast cancer - results from the German GENICA study. Scandinavian journal of work, environment & health. 2010;36:134–41. doi: 10.5271/sjweh.2890. [DOI] [PubMed] [Google Scholar]
- 7.Pronk A, Ji BT, Shu XO, et al. Night-shift work and breast cancer risk in a cohort of Chinese women. American journal of epidemiology. 2010;171:953–9. doi: 10.1093/aje/kwq029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Lie JA, Kjuus H, Zienolddiny S, Haugen A, Stevens RG, Kjaerheim K. Night work and breast cancer risk among Norwegian nurses: assessment by different exposure metrics. American journal of epidemiology. 2011;173:1272–9. doi: 10.1093/aje/kwr014. [DOI] [PubMed] [Google Scholar]
- 9.Kamdar BB, Tergas AI, Mateen FJ, Bhayani NH, Oh J. Night-shift work and risk of breast cancer: a systematic review and meta-analysis. Breast cancer research and treatment. 2013;138:291–301. doi: 10.1007/s10549-013-2433-1. [DOI] [PubMed] [Google Scholar]
- 10.Ijaz SI, Verbeek JH, Seidler A, et al. Night-shift work and breast cancer - a systematic review and meta-analysis. Scandinavian journal of work, environment & health. 2013;39:431–47. doi: 10.5271/sjweh.3371. [DOI] [PubMed] [Google Scholar]
- 11.Papantoniou K, Kogevinas M. Shift work and breast cancer: do we need more evidence and what should this be? Occupational and environmental medicine. 2013;70:825–6. doi: 10.1136/oemed-2013-101630. [DOI] [PubMed] [Google Scholar]
- 12.Jia Y, Lu Y, Wu K, et al. Does night work increase the risk of breast cancer? A systematic review and meta-analysis of epidemiological studies. Cancer epidemiology. 2013;37:197–206. doi: 10.1016/j.canep.2013.01.005. [DOI] [PubMed] [Google Scholar]
- 13.Thomas DB, Gao DL, Ray RM, et al. Randomized trial of breast self-examination in Shanghai: final results. Journal of the National Cancer Institute. 2002;94:1445–57. doi: 10.1093/jnci/94.19.1445. [DOI] [PubMed] [Google Scholar]
- 14.Li W, Ray RM, Gao DL, et al. Occupational risk factors for nasopharyngeal cancer among female textile workers in Shanghai, China. Occupational and environmental medicine. 2006;63:39–44. doi: 10.1136/oem.2005.021709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Ray RM, Gao DL, Li W, et al. Occupational exposures and breast cancer among women textile workers in Shanghai. Epidemiology. 2007;18:383–92. doi: 10.1097/01.ede.0000259984.40934.ae. [DOI] [PubMed] [Google Scholar]
- 16.Astrakianakis G, Seixas NS, Ray R, et al. Lung cancer risk among female textile workers exposed to endotoxin. Journal of the National Cancer Institute. 2007;99:357–64. doi: 10.1093/jnci/djk063. [DOI] [PubMed] [Google Scholar]
- 17.Wernli KJ, Ray RM, Gao DL, Thomas DB, Checkoway H. Cancer among women textile workers in Shanghai, China: overall incidence patterns, 1989-1998. American journal of industrial medicine. 2003;44:595–9. doi: 10.1002/ajim.10265. [DOI] [PubMed] [Google Scholar]
- 18.Thomas DB, Gao DL, Self SG, et al. Randomized trial of breast self-examination in Shanghai: methodology and preliminary results. Journal of the National Cancer Institute. 1997;89:355–65. doi: 10.1093/jnci/89.5.355. [DOI] [PubMed] [Google Scholar]
- 19.Li W, Ray RM, Lampe JW, et al. Dietary and other risk factors in women having fibrocystic breast conditions with and without concurrent breast cancer: A nested case-control study in Shanghai, China. International journal of cancer. Journal international du cancer. 2005 doi: 10.1002/ijc.20964. [DOI] [PubMed] [Google Scholar]
- 20.Ye Z, Gao DL, Qin Q, Ray RM, Thomas DB. Breast cancer in relation to induced abortions in a cohort of Chinese women. Br J Cancer. 2002;87:977–81. doi: 10.1038/sj.bjc.6600603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Langholz B, Jiao J. Computatioal methods for case-cohort studies. Computational Statistics and Data Analysis. 2007;51:3737–48. [Google Scholar]
- 22.Li W, Ray RM, Thomas DB, et al. Occupational exposure to magnetic fields and breast cancer among women textile workers in shanghai, china. American journal of epidemiology. 2013;178:1038–45. doi: 10.1093/aje/kwt161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.O'Leary ES, Schoenfeld ER, Stevens RG, et al. Shift work, light at night, and breast cancer on Long Island, New York. American journal of epidemiology. 2006;164:358–66. doi: 10.1093/aje/kwj211. [DOI] [PubMed] [Google Scholar]
- 24.Davis S, Mirick DK, Stevens RG. Night shift work, light at night, and risk of breast cancer. Journal of the National Cancer Institute. 2001;93:1557–62. doi: 10.1093/jnci/93.20.1557. [DOI] [PubMed] [Google Scholar]
- 25.Hansen J. Increased breast cancer risk among women who work predominantly at night. Epidemiology. 2001;12:74–7. doi: 10.1097/00001648-200101000-00013. [DOI] [PubMed] [Google Scholar]
- 26.Hansen J, Stevens RG. Case-control study of shift-work and breast cancer risk in Danish nurses: impact of shift systems. European journal of cancer. 2012;48:1722–9. doi: 10.1016/j.ejca.2011.07.005. [DOI] [PubMed] [Google Scholar]
- 27.Grundy A, Schuetz JM, Lai AS, et al. Shift work, circadian gene variants and risk of breast cancer. Cancer epidemiology. 2013;37:606–12. doi: 10.1016/j.canep.2013.04.006. [DOI] [PubMed] [Google Scholar]
- 28.Schwartzbaum J, Ahlbom A, Feychting M. Cohort study of cancer risk among male and female shift workers. Scandinavian journal of work, environment & health. 2007;33:336–43. doi: 10.5271/sjweh.1150. [DOI] [PubMed] [Google Scholar]
- 29.Tynes T, Hannevik M, Andersen A, Vistnes AI, Haldorsen T. Incidence of breast cancer in Norwegian female radio and telegraph operators. Cancer causes & control : CCC. 1996;7:197–204. doi: 10.1007/BF00051295. [DOI] [PubMed] [Google Scholar]
- 30.Mirick DK, Davis S. Melatonin as a biomarker of circadian dysregulation. Cancer Epidemiol Biomarkers Prev. 2008;17:3306–13. doi: 10.1158/1055-9965.EPI-08-0605. [DOI] [PubMed] [Google Scholar]
- 31.Girschik J, Heyworth J, Fritschi L. Re: “Night-shift work and breast cancer risk in a cohort of Chinese women”. American journal of epidemiology. 172:865–6. doi: 10.1093/aje/kwq275. author reply 7-8. [DOI] [PubMed] [Google Scholar]
- 32.Kayumov L, Lowe A, Rahman SA, Casper RF, Shapiro CM. Prevention of melatonin suppression by nocturnal lighting: relevance to cancer. Eur J Cancer Prev. 2007;16:357–62. doi: 10.1097/01.cej.0000215622.59122.d4. [DOI] [PubMed] [Google Scholar]
- 33.Higuchi S, Motohashi Y, Ishibashi K, Maeda T. Influence of eye colors of Caucasians and Asians on suppression of melatonin secretion by light. American journal of physiology. Regulatory, integrative and comparative physiology. 2007;292:R2352–6. doi: 10.1152/ajpregu.00355.2006. [DOI] [PubMed] [Google Scholar]