Int Arch Occup Environ Health DOI 10.1007/s00420-014-0940-y
ORIGINAL ARTICLE
Mortality among capacitor workers exposed to polychlorinated biphenyls (PCBs), a long-term update Renate D. Kimbrough • Constantine A. Krouskas Wenjing Xu • Peter G. Shields
•
Received: 4 August 2013 / Accepted: 13 March 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract Purpose Polychlorinated biphenyls (PCBs) are ubiquitous in the environment. Concerns have been raised about cancer and other disease risks. This follow-up mortality study of PCB workers addresses some of these concerns. Methods Mortality among 7,061 PCB capacitor workers was updated through 2008 (287,712 person-years; mean follow-up 41 years). Adjusted standardized mortality ratios (SMRs) and 95 % confidence intervals (CIs) were calculated for USA and New York State referent rates. Standardized rate ratios (SRRs) were calculated based on employment duration and latency. Results Standardized mortality ratios for all causes of death were statistically significantly lower in the total cohort (SMR 92; 95 % CI 89–96) and in males (SMR 88; 95 % CI 83–92), but not in females (SMR 100; 95 % CI 94–106). For all cancers combined, SMRs for the total cohort (SMR 103; 95 % CI 96–111) and for males (SMR 96; 95 % CI 87–105) did not differ from the expected rates, in contrast to females (SMR 114; 95 % CI 103–126).
Electronic supplementary material The online version of this article (doi:10.1007/s00420-014-0940-y) contains supplementary material, which is available to authorized users. R. D. Kimbrough C. A. Krouskas Center for Health Risk Evaluation, P.O. Box 15452, Washington, DC 20003, USA W. Xu KPMG, LLP, McLean 22102, Virginia P. G. Shields (&) Department of Medicine, Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, 300 W. 10th Avenue, Suite 519, Columbus, OH 43210-1280, USA e-mail:
[email protected]
Buccal cavity and pharyngeal cancers were statistically increased in the combined cohort (SMR 169; 95 % CI 108–251) and in females (SMR 273; 95 % CI 131–502). Respiratory system malignancies were statistically lower in males (SMR 83; 95 % CI 70–97), while they were increased in females (SMR 143; 95 % CI 118–172). Melanomas were statistically significantly increased in male salaried workers only. No positive trends (SRRs) with increasing length of employment and increasing latency were found. Conclusions The positive results lacking exposure– response relationships are subject to confounding and probably do not represent causal associations. Keywords Occupational mortality study Capacitor workers PCBs Cancer Lymphoma Melanoma Lung
Introduction Polychlorinated biphenyls (PCBs) were commercially produced in the USA from 1929 through 1977. Theoretically, the production of PCBs can result in 209 congeners. However, the number of congeners in commercial PCB mixtures consisted of 60–90 congeners (US EPA 1982). Commercial PCB mixtures were primarily used as dielectric fluids in capacitors and transformers. They also had limited uses in paint, plastics, sealants, dyes, newspaper print, in pesticides as extenders, and heat transfer and hydraulic fluids. PCBs are generally persistent chemicals and levels can be detected in air, water, soil, sediments, and in the tissues of wildlife, domestic animals and humans (Kimbrough and Krouskas 2003). The potential for adverse human health effects of PCBs has been a concern since the early 1970s due to the environmental persistence and
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experimental animal tumorigenicity studies (Kimbrough and Krouskas 2003; Mayes et al. 1998). In 1978, the Environmental Protection Agency (EPA) banned the production of PCBs in the USA. However, there remain concerns regarding the environmental impact for PCBs on cancer risk and other chronic diseases in the general population. Details about the manufacturing process in the two GE facilities where the workers worked have been provided previously (Kimbrough et al. 1999, 2003). Between 1946 and 1977, the General Electric Company (GE) manufactured small and large capacitors using PCBs as dielectric fluid in two production plants located one mile apart in upstate New York. Large capacitors were filled manually with PCBs from 1946 to 1960 resulting in excessive spillage and significant dermal and inhalation exposure to workers. In the mid 1960s, the filling process was automated. Small capacitors were impregnated by flooding racks of capacitors with heated PCBs under vacuum in large ovens. Upon removal of the capacitors from the ovens, a fog of condensed PCBs dispersed throughout the plant. Following impregnation, the capacitors dripping with PCBs were moved to the sealing station where the filling ports were soldered shut. Salvage and repair of large capacitors were also performed. It involved draining the PCBs, milling off the seal cover and manually removing and repairing the wet components. All of these activities including cleaning the outside of the capacitors entailed significant direct dermal and inhalation exposure. Exposed surfaces in the plants were coated with PCBs. Workers (winders) who prepared the paper and foil rolls for the canisters to be filled with PCBs were in a separate room. However, the plants only had one ventilation system. Consequently, these workers were also exposed to PCB air levels as were clerical workers and workers involved in shipping. Workers over time rotated through different jobs with more or less exposure. The degree of exposure to PCBs varied by specific jobs and by locations in the plant. Polychlorinated biphenyls manufactured in the USA had the trade name Aroclor. Different PCB mixtures were assigned different four digit numbers. Initially, the commercial PCB mixture used in the plants was Aroclor 1254 (54 % chlorine by weight). In the mid 1950s, Aroclor 1254 was primarily replaced in small capacitors by Aroclor 1242 (42 % chlorine by weight). Aroclor 1242 was a more volatile compound and increased airborne PCB levels and PCB deposits on surfaces and persons in the plant. As a result, the plant ventilation system was updated, airflow capacity was increased and laminar flow ventilation systems were installed at sealing stations to reduce worker exposure. After 1971, Aroclor 1016 was mostly used (Kimbrough et al. 2003). Aroclor 1016 (41 % chlorine by weight) consisting mainly of tri- and tetrachlorobiphenyls
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that are very volatile began to be used in 1971. Prior to use, the purchased PCBs were filtered by percolating them through a bed of Florida clay to remove polar impurities, which if present would contribute to dielectric loss. Available industrial hygiene data consisted of PCB area and personal air levels (grab samples) measured in both plants in 1975 by the General Electric Company (GE) (Lawton et al. 1981) and in 1977 by the National Institute for Occupational Safety and Health (NIOSH) (Jones 1983; NIOSH publication 83-137224). Air levels are not available for earlier time periods, e.g., when the less volatile Aroclor 1254 was predominantly used nor was information available to assess dermal exposures. In 1975, PCB air levels in PCB work areas ranged from 227 to 1,500 lg/m3, and in 1977 after PCB use was phased out, air levels in PCB work areas ranged from 170 to 576 lg/m3 and from 3 to 50 lg/m3 in other areas where PCBs were not used such as the winding, can and cover manufacture, assembly and shipping areas. Importantly, the air levels reported in 1975 were determined after the ventilation system was updated and after filling operations had been automated. Thus, neither the 1975 nor 1977 data were representative of probably much higher PCB air levels and dermal exposures in the plant before 1975, namely the prior 40 years. Between 1976 and 1979, the general population had PCB blood levels between 5 and 7 ppb (wet weight; parts per billion or ng/ml) with levels ranging from non-detectable to about 20 ppb (ng/ml) with occasional higher levels (Kreiss 1985). PCB blood levels are now much lower (Nichols et al. 2007). In contrast, in a population of 290 self-selected workers (volunteers) in the plants reported herein, in 1976, PCB serum levels on a wet weight basis ranged from 6 to 2530 ppb (ng/ml) for the lower chlorinated compounds and from 1 to 546 ppb (ng/ml) for the higher chlorinated PCBs (Wolff et al. 1982). Similar levels were found by Lawton et al. (1981, 1985a, b) in 190 workers and in other studies (Chase et al. 1982). None of these data are representative of the exposure incurred by the 7,000? workers working in the plants between 1946 and 1977, which would have been higher. Exposure to other chemicals in these plants was limited to toluene for a small number of workers involved in painting, trichloroethylene during degreasing and low levels of lead, aluminum and iron during soldering. For the most part, these levels were below permissible levels set by the Occupational Safety and Health Administration (Kimbrough et al. 1999, 2003). Several mortality studies have been conducted in PCBexposed capacitor workers as reviewed by Golden and Kimbrough (2009) and Shields (2006). There have not been consistent results for increased mortality for any disease, with some studies reporting different associations. The present study is a follow-up of a worker cohort with prior retrospective mortality studies (Kimbrough et al.
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1999, 2003). This cohort also was included in studies by Ruder et al. (2013), Prince et al. (2006), Brown and Jones (1981) and Brown (1987) in combination with workers from other plants. PCB exposure data on an individual basis were not available in any plant, but PCBs were ubiquitous in the various facilities and well above background exposures of the general population.
stayed in a specific job, rotations to different jobs with a high, low or undefinable exposure and time periods of absence such as maternity leave, layoffs, strikes and illness. This information was summed for each worker to provide the length of time spent in high and low exposure jobs. The records also included social security numbers and demographics (Kimbrough et al. 1999). Study population
Methods Exposure classification As previously reported, all jobs were classified according to PCB exposure prior to the determination of vital status (Kimbrough et al. 1999). Jobs with direct dermal contact and/or inhalation to high PCB aerosols while filling, impregnating, repairing or moving PCB-filled capacitors were classified as high exposure jobs. Jobs in which PCBs were not directly used such as winding, can and cover manufacture with their assembly, shipping and office workers were classified as low exposure. Thus, these low exposure jobs did not entail direct dermal contact to liquid PCBs, although these workers still had inhalational and dermal exposure due to the general plant contamination. There were also jobs for which PCB exposure varied depending on the location in the plant. However, information on the location of the job was not available. These jobs were designated as ‘‘undefinable.’’ Many workers rotated through different jobs over time. An exposure database from worker employment records (microfilmed by GE) was created based on job classification codes and length spent in different jobs that included the following information: the length of time a worker
Hourly and salaried workers employed for at least 90 days between January 1, 1946, and June 15, 1977, were included in the analysis (Table 1). Salaried workers were included because they were often involved in the manufacturing process and all personnel were housed in the same building with a shared ventilation system. Personal identifiers included social security numbers, demographics and each worker’s job history information. Almost all workers were white (99? %). Completeness of the cohort was established by our reviewing all available company records such as pension rosters and quarterly earnings reports (form 941) of the Social Security Administration (SSA). In our two prior studies (Kimbrough et al. 1999, 2003), the cohort had 7,075 workers. However, based on updated information from the SSA, 14 duplicates (0.19 %) were found. They were removed (more than one social security number, name changes in females) resulting in the present cohort with 7,061 workers. For the present study, vital status and death information were obtained through December 2008 from the SSA, the National Center for Health Statistics National Death Index (NDI), ancestry.com operations incÒ and Omni Trace CorporationÒ, a private search firm. Workers with unknown vital status were considered lost to follow-up and
Table 1 Demographics of male and female capacitor workers Characteristic
Hourly Male
Salary Female
Male
Total Female
Number of workers
2,977
2,539
1,079
466
7,061
Number of person-years
115,923
104,107
45,952
21,730
287,712
Number of deaths
1,192
993
431
151
2,767
Number of lost to follow-up
45
16
44
6
111
Mean age at death
65.6
71.5
69.8
71.8
68.7
Mean age for workers alive on 12/31/2008
64.9
68.5
72.2
71.5
67.8
Mean follow-up time (years)
40.0
41.0
42.6
46.7
40.8
The range of age at death
(21–96)
(21–98)
(29–100)
(33–97)
(21–100) (50–99)
The range of age for workers alive on 12/31/2008
(50–95)
(50–99)
(54–95)
(54–94)
Mean length of time worked in the plants in years
6.74
6.49
5.98
5.36
Median length of time worked in the plants in years
2.97
3.29
2.82
3.08
Mean latency in years
38.94
41.00
42.59
46.63
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contributed person-years through their last date of employment. Workers lost to follow-up were considered alive through the last date observed and contributed the corresponding person-years. The ICD-10 codes for 92 (general US population) and 119 causes of death (NY State population) to which all codes were converted by the program can be downloaded from the links: http://www.cdc.gov/niosh/LTAS/net20130330/Rate%20Info %20Table%203.pdf and http://www.cdc.gov/niosh/LTAS/ net20130330/NIOSH-119%20table%202007.pdf. The only available state rates provided by NIOSH were for 119 causes of death starting in 1960. The state rates differed from the US rates for 92 causes of death mostly for disease outcomes not germane to this study (12 causes related to other injuries, 5 causes related to falls. There were HIV-related causes, conductive disorders, asbestosis, silicosis, other pneumoconiosis). The neurological disorders were also expanded in the ICD-10. However, these causes of deaths were not really relevant to our study. Death certificates were obtained from the state where the death occurred and were coded by a trained nosologist. We purchased the causes of death codes from NDI (NDI?) from 1998 to 2008. For deaths, where a death certificate could not be obtained, we used the NDI? codes. The NDI? codes provide comparable information (Doody et al. 2001, Sathiakumar et al. 1998). Statistical analyses We used age-, gender-, race- and time-specific mortality rates for the US population compiled by NIOSH for 92 underlying causes of deaths for the years 1940–2014 (LTAS.NET Version 3.0.3, Robinson et al. 2006 and http:// www.cdc.gov/niosh/ltas/). For this general population comparison, the start date of our analysis was 1946 when the capacitor manufacture began. As a separate analysis, New York State mortality rates starting in 1960 also were used, excluding New York City. For this analysis, 35 workers were removed because they died prior to 1960 and 23,305 person-years were lost. Person-years of observation were accumulated starting on the 91st day of employment and continued to December 31, 2008, date of death, or date lost to follow-up. Person-years were combined into 5-year age-, sex-, race- and calendar-specific categories and multiplied by the corresponding age-, sex-, and calendar-specific US categories to yield the expected number of deaths. Twosided p values and 95 % confidence intervals (CIs) for standardized mortality ratios (SMRs) were calculated under the assumption that observed deaths follow a Poisson’s distribution and the expected deaths are invariant. Exact confidence intervals and p values were calculated for observed deaths less or equal to five. For larger numbers of deaths, approximation of the confidence interval and the
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exact Poisson’s test were used. SMRs were calculated for all 92 underlying causes of death. However, in the interest of space, only observed causes with three or more causes of deaths are presented in the tables and information on injuries are also not included in the tables. All 92 causes of deaths are provided electronically as supplemental table 1s. Internal analysis of the cohort was performed using directly standardized rate ratios (SRRs) for five or more specific observed causes of deaths that had a statistically significantly increased SMR. A trend was calculated in a regression of directly standardized rates (Rothman 1986; Rothman and Greenland 1998). The midpoints of the categories were used as the independent variable. The cutoff point plus 50 % served as the midpoint of the highest category (Rothman 1986). Categories of cumulative length of employment (\1 year, 1 to\5 years, 5 to\10 years and C10 years) and years of latency (\30 years or C30 years since first exposure) were used to stratify the cohort. These analyses were performed to determine whether the SRR increased significantly over the cumulative length of employment and latency. A significant increase would suggest a trend consistent with a dose–response relationship.
Results The cohort consisted of 7,061 workers with a total of 2,767 (39 %) deaths (Table 1). The removal of 14 duplicates from our data base is very small (0.19 %) and should not impact this or our previous studies. The mean follow-up time of the entire cohort was 40? years with an upper age for alive and deceased workers of 99 and 100 years, respectively. A total of 111 (1.6 %) workers were lost to follow-up. The time interval between last exposure and the date of death for many workers was over 40 years. Male and female workers contributed 161,875 and 125,837 person-years with a total of 287,712 person-years for all workers. Females primarily held jobs with lower exposures, e.g., winding operations and clerical jobs. About 12 % of females and 33 % of males were ever in high exposure jobs. Observed deaths, expected deaths, SMRs and 95 % CIs for specific causes of deaths compared to the US population and the New York State are presented in Tables 2 and 3 for all workers and separately for male and female workers. For the US comparison, the observed mortality rates for all causes of death were statistically significantly lower in the total cohort and in male workers (SMR 92; 95 % CI 89–96 and SMR 88; 95 % CI 83–92, respectively; p \ 0.01), while they were the same as the general population in females. For all cancers combined, the US SMRs for all workers and for males separately did not differ from the expected rates, while female workers had an increased rate (SMR 114; 95 % CI 103–126;
Int Arch Occup Environ Health Table 2 Observed and expected deathsa in 7,061 totalb, 4,056 malec and 3,005 femaled workers compared to the US population Cause of deaths (MN = malignant neoplasms)
Total
Males
Females
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
All causes
2,767/ 3,000.36
92** (89–96)
1,623/ 1,854.09
88** (83–92)
1,144/ 1,146.27
100 (94–106)
All cancers
838/811.36
103 (96–111)
461/481.53
96 (87–105)
377/329.83
114* (103–126)
MN buccal and pharynx
24/14.24
169* (108–251)
14/10.58
132 (72–222)
10/3.66
273** (131–502)
MN tongue
6/3.37
178 (65–388)
3/2.48
121 (25–354)
3/0.89
338 (70–988)
MN other buccal
8/3.89
206 (89–406)
5/2.71
184 (60–430)
3/1.17
256 (53–749)
MN pharynx
10/6.81
147 (70–270)
6/5.23
115 (42–250)
4/1.58
253 (69–648)
MN digestive and peritoneum
204/187.59
109 (94–125)
121/117.55
103 (83–123)
83/70.04
119 (94–147)
MN esophagus
20/17.67
113 (69–175)
18/14.56
124 (73–195)
2/3.11
64 (8–232)
MN stomach
18/20.01
90 (53–142)
12/13.83
87 (45–152)
6/6.18
97 (36–211)
MN intestine MN rectum
77/69.61 24/14.33
111 (87–138) 167* (107–249)
37/40.20 14/9.12
92 (65–127) 154 (84–258)
40/29.41 10/5.22
136 (97–185) 192 (92–352)
MN biliary, liver, gall bladder
18/21.26
85 (50–134)
10/13.43
74 (36–137)
8/7.83
102 (44–201)
MN pancreas
44/41.62
106 (77–142)
28/24.81
113 (75–163)
16/16.81
95 (54–155)
MN peritoneum, other and unspec. sites
3/3.09
97 (20–284)
2/1.62
124 (15–446)
1/1.47
68 (2–379)
MN respiratory system
256/252.26
101 (89–115)
144/174.00
83* (70–97)
112/78.26
143** (118–172)
MN larynx
7/6.68
105 (42–216)
6/5.60
107 (39–233)
1/1.08
93 (2–518)
MN trachea, bronchus, lung
245/243.55
101 (88–114)
136/166.98
81* (68–96)
109/76.57
142** (117–172) 195 (5–1,086)
MN other respiratory sites
3/1.51
198 (41–579)
2/1.00
200 (24–722)
1/0.51
MN breast
58/61.69
94 (71–122)
2/0.60
332 (40–1,200)
56/61.08
92 (69–119)
MN female genital organs
44/38.16
115 (84–155)
–
–
44/38.16
115 (84–155)
MN cervix
10/7.44
134 (64–247)
–
–
10/7.44
134 (64–247)
MN other parts of uterus
13/8.58
151 (81–259)
–
–
13/8.58
151 (81–259)
MN ovary
18/20.77
87 (51–137)
–
–
18/20.77
87 (51–137)
MN other female genital organs
3/1.38
218 (45–637)
–
–
3/1.38
218 (45–637)
MN male genital organs
44/39.03
113 (82–151)
44/39.03
113 (82–151)
–
–
MN prostate
44/37.36
118 (86–158)
44/37.36
118 (86–158)
–
–
MN urinary tract
33/35.62
93 (64–130)
22/26.05
84 (53–128)
11/9.57
115 (57–206)
MN kidney
21/18.52
113 (70–173)
14/12.94
108 (59–182)
7/5.57
126 (51–259)
MN bladder and other urinary
12/17.11
70 (36–123)
8/13.11
61 (26–120)
4/3.99
100 (27–256)
MN other and unspec. sites
103/104.55
99 (80–119)
71/65.14
109 (85–137)
32/39.41
81 (56–115)
MN skine
22/16.40
134 (84–203)
17/11.66
146 (85–234)
5/4.74
105 (34–246)
Mesothelioma
5/1.61
310* (101–724)
3/1.38
217 (45–634)
2/0.23
875* (106–3,161)
MN brain and other nervous
17/21.71
78 (46–125)
14/13.63
103 (56–172)
3/8.09
37 (8–108)
MN connective tissue
6/4.67
128 (47–279)
2/2.69
74 (9–268)
4/1.98
202 (55–517)
MN other and unspec. sites
49/56.03
87 (65–116)
33/33.40
99 (68–139)
16/22.64
71 (40–115)
MN lymphatic and hematopoietic
72/78.22
92 (72–116)
43/48.57
89 (64–119)
29/29.65
98 (65–140)
Non-Hodgkin’s lymphoma
20/31.33
64* (39–99)
10–18.98
53* (25–97)
10/12.35
81 (39–149)
Hodgkin’s disease
3/4.13
73 (15–212)
2/2.78
72 (9–260)
1/1.35
74 (2–413)
Leukemia
29/29.43
99 (66–142)
18/18.81
96 (57–151)
11/10.62
104 (52–185)
Multiple myeloma
20/13.33
150 (92–232)
13/7.99
163 (87–278)
7/5.34
131 (53–270)
Benign and unspec. neoplasms
9/11.13
81 (37–153)
5/6.05
83 (27–193)
4/5.08
79 (21–201)
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Int Arch Occup Environ Health Table 2 continued Cause of deaths (MN = malignant neoplasms)
Total
Males
Females
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Unspec. neoplasms eye, brain, other nervous tissue
5/4.35
115 (37–268)
3/2.47
122 (25–355)
2/1.88
106 (13–384)
Other benign and unspec. neoplasms
4/5.30
75 (21–193)
2/2.93
68 (8–247)
2/2.37
84 (10–304)
Diabetes mellitus
64/72.89
88 (68–112)
35/40.75
86 (60–119)
29/32.14
90 (60–130)
Dis. blood and blood-forming organs
14/12.12
115 (63–194)
9/6.89
131 (60–248)
5/5.24
95 (31–223)
Other and unspec. anemia
5/4.05
124 (40–288)
3/2.04
147 (30–429)
2/2.00
100 (12–361)
Coagulation and hemorrhagic cond. Other dis. blood-forming organs
5/2.75 4/5.22
182 (59–425) 77 (21–196)
2/1.50 4/3.30
134 (16–483) 121 (33–311)
3/1.25 0/1.93
240 (49–701) 0 (0–192)
Mental and psych. disorders
31/44.52
70* (47–99)
13/22.89
57* (30–97)
18/21.63
83 (49–132)
Alcoholism
5/10.66
47 (15–109)
3/8.85
34* (7–99)
2/1.81
110 (13–399)
Other mental disorders
26/33.86
77 (50–113)
10/14.04
71 (34–131)
16/19.82
81 (46–131)
Nervous system disorders
90/77.36
116 (94–143)
40/38.96
103 (73–140)
50/38.40
130 (97–172)
Multiple sclerosis
5/4.54
110 (36–257)
3/2.00
150 (31–437)
2/2.54
79 (10–285)
Other nervous system diseases
85/72.82
117 (93–144)
37/36.96
100 (70–138)
48/35.86
134 (99–177)
Heart disease
826/938.02
88** (82–94)
554/618.72
90** (82–97)
272/391.30
85** (75–96)
Rheumatic heart disease
14/15.04
93 (51–156)
9/7.25
124 (57–236)
5/7.79
64 (21–150)
Ischemic heart disease
645/744.93
87** (80–94)
437/508.50
86** (78–94)
208/236.42
88 (76–101)
Chronic dis. endocardium
15/17.11
88 (49–145)
12/8.76
137 (71–239)
3/8.35
36 (7–105)
Hypertension w/heart disease
16/28.52
56* (32–91)
10/15.97
63 (30–115)
6/12.54
48 (18–104)
Other heart diseases
136/132.44
103 (86–121)
86/78.24
110 (88–136)
50/54.19
92 (68–122)
Other dis. circulatory system
226/258.98
87* (76–99)
118/140.12
84 (70–101)
108/118.86
91 (75–110)
Hypertension w/o heart disease Cerebrovascular disease
17/14.74 139/172.40
115 (67–185) 81** (68–95)
8/7.41 68/89.25
108 (47–213) 76* (59–97)
9/7.33 71/83.15
123 (56–233) 85 (67–108)
Dis. arteries, vein, pulm. circ
70/71.84
97 (76–123)
42/43.47
97 (70–131)
28/28.37
99 (66–143)
Dis. respiratory system
260/253.37
103 (91–116)
124/150.99
82* (68–98)
136/102.47
133** (111–157)
Pneumonia
72/69.05
104 (82–131)
36/40.26
89 (63–124)
36/28.78
125 (88–173)
Chronic obstructive pulmonary disease
147/136.83
107 (91–126)
67/82.40
81 (63–103)
80/54.43
147** (117–183)
Asthma
6/5.26
114 (42–248)
2/2.34
85 (10–309)
4/2.92
137 (37–351)
Pneumoconiosis and other resp. dis. Diseases digestive system
31/39.56 100/126.90
78 (53–111) 79* (64–96)
16/24.45 62/79.91
65 (37–106) 78* (59–99)
15/15.11 38/46.99
99 (56–164) 81 (57–111)
Diseases stomach and duodenum
4/10.26
39* (11–100)
2/6.78
29 (4–107)
2/3.48
58 (7–208)
Hernia and intestinal obstruction
3/7.42
40 (8–118)
0/3.58
0 (0–103)
3/3.84
78 (16–228)
Cirrhosis and other chronic liver dis.
46/57.37
80 (59–107)
31/40.80
76 (52–108)
15/16.58
90 (51–149)
Other disease digestive syst.
47/51.85
91 (67–121)
29/28.75
101 (68–145)
18/23.10
78 (46–123)
Diseases genitourinary syst.
35/51.72
68* (47–94)
16/28.31
57* (32–92)
19/23.41
81 (49–127)
Acute glomeruloneph. and renal failure
4/5.48
73 (20–187)
1/3.10
32 (1–180)
3/2.38
126 (26–369)
Chr. and unsp nephritis and renal failure
19/27.30
70 (42–109)
8/16.00
50* (22–99)
11/11.30
97 (49–174)
Other genito-uninary dis.
9/14.26
63 (29–120)
4/6.68
60 (16–153)
5/7.58
66 (21–154)
Dis. musculoskeletal and connective
9/11.75
77 (35–145)
5/4.43
113 (37–263)
4/7.32
55 (15–140)
Other dis. musculoskeletal
7/6.43
109 (44–224)
5/2.19
228 (74–533)
2/4.24
47 (6–171)
Sympt. and ill-def. conditions
20/28.63
70 (43–108)
12/17.93
67 (35–117)
8/10.70
75 (32–147)
* p \ 0.05, ** p \ 0.01 (two sided) a
Expected numbers of deaths based on age-, sex-, race- and calendar-specific US mortality rates coded according to the rules of the international classification of diseases in force at the time of death. Person-years of observation: b287,712, c161,875, d125,837.
e
One skin cancer each among the male and female hourly workers was a squamous cell carcinoma, while the rest were melanomas
123
Int Arch Occup Environ Health Table 3 Observed and expected deathsa in 7,026 workersb with 4,029 malec and 2,997 femaled workers compared to the New York State population Cause of deaths
Total
Males
Females
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
All causes
2,732/2,906
94** (90–98)
90** (85–94)
830/803.79 23/14.12 6/3.63 8/3.89 9/6.51 199/206.39 19/18.73 16/24.12 77/77 23/16.15 17/22.37 44/44.91 3/3.10 256/231.84 7/7.73 245/222.06 3/1.45 58/68.86 42/39.24 10/6.53 12/9.30 17/21.92 3/1.49 44/36.92 44/25.85 33/36.51 21/17.32 12/19.19 103/92.48 20/11.94 5/1.38
103 (96–111) 163* (103–244) 165 (61–359) 206 (89–405) 138 (63–262) 96 (83–111) 101 (61–158) 66 (38–108) 100 (79–125) 142 (90–214) 76 (44–122) 98 (71–132) 97 (20–283) 110 (97–125) 91 (36–187) 110 (97–125) 206 (43–603) 84 (64–109) 107 (77–145) 153 (73–282) 129 (67–225) 78 (45–124) 202 (42–590) 119 (87–160) 123 (89–165) 90 (62–127) 121 (75–185) 63 (32–109) 111 (91–135) 168* (102–259) 363* (118–846)
99 (90–108) 133 (73–223) 110 (23–322) 182 (59–425) 120 (44–261) 92 (76–110) 119 (71–188) 67 (33–119) 83 (58–114) 126 (67–216) 63 (29–120) 106 (71–154) 122 (15–441) 92 (78–109) 93 (34–203) 92 (77–109) 211 (26–762) 263 (32–952) – – – – – 119 (87–160) 123 (89–165) 82 (52–124) 116 (63–194) 55 (24–107) 125 (98–158) 196* (112–318) 257 (53–751)
1,135/ 1,123.55 372/339.15 9/3.59 3/0.91 3/1.15 3/1.15 81/77.70 1/3.61 5/7.62 40/32.44 10/5.86 8/8.14 16/18.57 1/1.46 112/76.04 1/1.28 109/74.15 1/0.51 56/68.10 42/39.24 10/6.53 12/9.30 17/21.92 3/1.49 – – 11/9.75 7/5.22 4/4.53 32/35.66 4/3.76 2/0.21
101 (95–107)
All cancers MN buccal and pharynx MN tongue MN other buccal MN pharynx MN digestive and peritoneum MN esophagus MN stomach MN intestine MN rectum MN biliary, liver, gall bladder MN pancreas MN peritoneum, other and unspec. MN respiratory MN larynx MN trachea, bronchus, lung MN other respiratory sites MN breast MN female genital organs MN cervix MN other parts of unspec. uterus MN ovary MN other female genital organs MN male genital organs MN prostate MN urinary tract MN kidney MN bladder and other urinary site MN other and unspec. sites Melanoma Mesothelioma
1,597/ 1,738.09 458/464.64 14/10.54 3/2.72 5/2.74 6/5.00 118/128.69 18/15.12 11/16.50 37/44.57 13/10.29 9/14.23 28/26.34 2/1.64 144/155.80 6/6.45 136/147.91 2/0.95 2/0.76 – – – – – 44/36.92 44/35.85 22/26.76 14/12.09 8/14.67 71/56.83 16/8.18 3/1.17
MN connective MN of brain and other nervous MN of other and unspec. sites MN lymphatic and hematopoietic Hodgkin’s disease Non-Hodgkin’s lymphoma Multiple myeloma Leukemia Benign and unspec. neoplasms Unspec. neoplasms eye, brain, other nervous Other benign and unspec. neoplasms Dis. blood and blood-forming organs Other and unspec. anemia Coagulation and hemorrhagic condition Other dis. blood-forming organs Diabetes mellitus Mental and psych. disorders
6/4.66 17/18.70 49/48.74 72/77.42 3/4.52 20/32.08 20/12.26 29/28.57 9/11.21 5/5.00
129 (47–280) 91 (53–146) 101 (74–133) 93 (73–117) 66 (14–194) 62* (38–96) 163 (100–252) 102 (68–146) 80 (37–152) 100 (32–233)
2/2.60 14/11.81 33/28.36 43/48.36 2/2.96 10/19.79 13/7.35 18/18.25 5/6.17 3/2.88
77 (9–278) 119 (65–199) 116 (80–162) 89 (64–120) 68 (8–244) 51* (24–93) 177 (94–303) 99 (58–156) 81 (26–189) 104 (21–304)
4/2.06 3/6.89 16/20.17 29/29.07 1/1.56 10/12.29 7/4.91 11/10.31 4/5.04 2/2.12
110 (99–121) 251* (115–476) 328 (68–960) 262 (54–765) 262 (54–765) 104 (83–130) 28 (1–154) 66 (21–153) 123 (88–168) 171 (82–314) 98 (42–194) 86 (49–140) 68 (2–381) 147** (121–177) 78 (2–435) 147** (121–177) 198 (5–1,103) 82 (62–107) 107 (77–145) 153 (73–282) 129 (67–225) 78 (45–124) 202 (42–590) – – 113 (56–202) 134 (54–286) 88 (24–226) 90 (61–127) 107 (29–273) 944** (114–3,410) 194 (53–498) 44 (9–127) 79 (45–129) 100 (67–143) 64 (2–358) 81 (39–150) 143 (57–294) 107 (53–191) 79 (22–203) 94 (11–341)
4/4.91 14/10.17 5/3.15 5/2.61 4/4.36 64/61.40 31/35.39
82 (22–209) 138 (75–231) 159 (52–371) 191 (62–447) 92 (25–235) 104 (80–133) 88 (60–124)
2/2.75 9/5.81 3/1.53 2/1.48 4/2.78 35/35.31 13/20.58
73 (9–263) 155 (71–294) 196 (40–573) 136 (16–490) 144 (39–369) 99 (69–138) 63 (34–108)
2/2.16 5/4.36 2/1.62 3/1.13 0/1.58 29/26.09 18/14.81
93 (11–334) 115 (37–267) 124 (15–447) 264 (54–770) 0 (0–234) 111 (74–160) 122 (72–192)
123
Int Arch Occup Environ Health Table 3 continued Cause of deaths
Total
Males
Females
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Obs/exp
SMR (95 % CI)
Alcoholism Other mental disorders Nervous system disorders
5/9.98 26/25.40 86/46.92
3/8.36 10/12.22 38/25.18
36 (7–105) 82 (39–150) 151* (107–207)
2/1.63 16/13.18 48/21.75
123 (15–444) 121 (69–197) 221** (163–293)
Multiple sclerosis Other nervous system diseases
5/4.41 81/42.51
3/1.98 35/23.19
151 (31–442) 151* (105–210)
2/2.43 46/19.32
82 (10–298) 238** (174–318)
Heart disease
550/665.98
83** (76–90)
272/380.62
71** (63–80)
Rheumatic heart disease Hypertension w/heart disease Ischemic heart disease Chronic dis. endocardium Cardiomyopathy Conductive disorder Other heart diseases
822/ 1,046.60 10/15.54 16/32.93 645/884.09 15/15.13 25/21.26 50/34.90 61/42.75
50 (16–117) 102 (67–150) 183** (147–226) 113 (37–265) 191** (151–237) 79** (73–84)
5/7.21 10/19.06 437/573.48 12/7.70 13/15.10 32/19.97 41/23.47
5/8.33 6/13.87 208/310.61 3/7.43 12/6.16 18/14.94 20/19.28
60 (19–140) 43* (16–94) 67** (58–77) 40 (8–118) 195* (101–340) 121 (71–190) 104 (63–160)
Other dis. circulatory system Cerebrovascular disease Hypertension w/o heart disease Dis. arteries, veins, lymph Dis. respiratory system Pneumonia Chronic obstructive pulmonary disease
225/208.10 138/132.05 17/14.44 70/61.60 259/225.15 71/80.46 147/107.66
118/114.68 68/69.37 8/7.44 42/37.86 123/132.29 35/47.95 67/62.95
69 (23–162) 52* (25–97) 76** (69–84) 156 (80–272) 86 (46–147) 160* (110–226) 175** (125–237) 103 (85–123) 98 (76–124) 107 (46–212) 111 (80–150) 93 (77–111) 106 (82–135) 106 (82–135)
107/93.42 70/62.68 9/7.00 28/23.74 136/92.86 36/32.86 80/44.71
115 (94–138) 112 (87–141) 128 (59–244) 118 (78–171) 146** (123–173) 110 (77–152) 179** (142–223)
Asthma Other respiratory system disease Diseases digestive system Dis. stomach and duodenum Hernia and intestinal obstruction Cirrhosis and other liver dis. Other diseases digestive syst. Dis. musculoskeletal and connective Other dis. musculoskeletal Diseases genitourinary syst. Acute glomeruloneph., renal failure Chron. and unspec. neph., renal fail. Other genitourinary dis. Sympt. and ill-def. cond.
6/5.50 31/29.08 100/123.59 4/10.43 3/6.25 46/61.83 47/45.07 8/8.41 6/4.95 34/46.93 4/5.07 18/24.08 9/13.85 18/27.37
2/2.56 16/17.62 62/80.91 2/6.90 0/3.16 31/45.44 29/25.40 4/3.31 4/1.68 16/26.17 1/2.89 8/14.34 4/6.71 10/18.22
78 (9–282) 91 (52–148) 77* (59–98) 29 (4–105) 0 (0–117) 68* (46–97) 114 (76–164) 121 (33–310) 237 (65–608) 61* (35–99) 35 (1–193) 56 (24–110) 60 (16–153) 55 (26–101)
4/2.94 15/11.47 38/42.68 2/3.53 3/3.09 15/16.29 18/19.67 4/5.10 2/3.27 18/20.76 3/2.18 10/9.74 5/7.14 8/9.15
136 (37–349) 131 (73–216) 89 (63–122) 57 (7–204) 97 (20–284) 92 (51–151) 92 (54–145) 78 (21–201) 61 (7–221) 87 (51–137) 138 (28–402) 103 (49–189) 70 (23–163) 87 (38–172)
64 (31–118) 49** (28–79) 73** (67–79) 99 (55–164) 118 (76–174) 143* (106–189) 143** (109–183) 108 (94–123) 105 (88–123) 118 (68–188) 114 (89–144) 115* (101–130) 88 (69–111) 137** (115–160) 109 (40–238) 107 (72–151) 81* (66–98) 38* (10–98) 48 (10–140) 74* (54–99) 104 (77–139) 95 (41–187) 121 (44–264) 72 (50–101) 79 (22–202) 75 (44–118) 65 (30–123) 66 (39–104)
* p \ 0.05, ** p \ 0.01 a Expected numbers of deaths based on age-, sex-, race- and calendar-specific NYS mortality rates coded according to the rules of the international classification of diseases in force at the time of death. A total of 35 workers were removed because they died prior to 1960. Adjusted person-years of observation: b264,407, c149,375, d115,032
p \ 0.05). Cancers of the buccal cavity and pharynx were statistically significantly increased in the combined cohort (SMR 169; 95 % CI 108–251; p \ 0.05) and in females (SMR 273; 95 % CI 131–502; p \ 0.01), but not in males. Carcinomas of the respiratory system and the subcategory trachea, bronchus and lung were significantly reduced in male workers (SMR 83; 95 % CI 70–97; p \ 0.05 and SMR 81; 95 % CI 68–96; p \ 0.05, respectively), while
123
they were increased in female workers when compared to the US population (SMR 143; 95 % CI 118–172; and 142; 95 % CI 117–172; p \ 0.01, respectively). There were 5 cases of mesothelioma which were statistically significantly increased in the total cohort and in females when compared to the US population (SMR 310; 95 % CI 101–724 and SMR 875; 95 % CI 106–3,161; p \ 0.05, respectively). However, only 2 of the mesotheliomas were
6
8 –
C30 years
Total SRR (95 % CI)
3
3
–
C30 years
Total
SRR (95 % CI)
62
85
–
C30 years
Total
SRR (95 % CI)
2
3 –
C30 years
Total SRR (95 % CI)
25
28
–
C30 years
Total
SRR (95 % CI)
25
28
–
C30 years
Total
SRR (95 % CI)
3
\30 years
MN trachea, bronchus, lung
3
\30 years
MN respiratory system
1
\30 years
MN buccal and pharynx
23
\30 years
All cancers
Females
0
\30 years
MN rectum
2
\30 years
170*
211**
65
167*
207**
63
396
438
333
121
141*
88
97
152
0
250*
308*
160
0.93 (0.55, 1.57)
35
24
11
0.98 (0.58, 1.65)
36
24
12
1 0.29 (0.03, 2.84)
1
0
1.02 (0.77, 1.36)
122
84
38
4.39 (1.18, 16.29)
9
4
5
4 0.36 (0.11, 1.22)
2
2
No. of observed deaths
No. of observed deaths
SMR
1 to \5
\1
Length of employment (years)
MN buccal and pharynx
All workers
Cause/latency
138
129
165
139
126
174
87
142
0
114
123
100
221*
159
324*
98
84
119
SMR
1.02 (0.56, 1.88)
19
16
3
1.07 (0.59, 1.95)
20
16
4
2 0.78 (0.12, 5.16)
1
1
1.44 (0.67, 3.08)
52
34
18
2.40 (0.52, 11.07)
4
3
1
5 1.02 (0.32, 3.33)
3
2
No. of observed deaths
5 to \10
169*
198*
95
174*
194*
123
378
331
442
107
115
95
184
251
102
237
266
203
SMR
Table 4 SMRsa and SRRsb for all workers, female and male workers of statistically significantly increased cancers
0.76 (0.43, 1.36)
27
20
7
0.79 (0.45, 1.40)
28
20
8
4 1.14 (0.25, 5.32)
2
2
1.06 (0.74, 1.52)
118
81
37
2.21 (0.58, 8.40)
8
5
3
7 0.59 (0.20, 1.70)
3
4
No. of observed deaths
C10
115
108
142
116
105
156
326
248
473
113
109
122
160
154
173
144
100
213
SMR
0.85 (0.55, 1.35)
109
85
24
0.89 (0.57, 1.40)
112
85
27
10 0.74 (0.19, 2.91)
6
4
0.99 (0.77, 1.28)
377
261
116
2.87 (0.86, 9.64)
24
15
9
24 0.64 (0.27, 1.52)
14
10
No. of observed deaths
Total
142**
149**
124
143**
146**
135
273**
264
288
114*
121**
102
167*
168
167
169*
166
173
SMR
Int Arch Occup Environ Health
123
123
1.02 (0.44, 2.38) 0.72 (0.27,1.89)
Standardized mortality ratio using the US population to calculate the expected number of deaths Standardized rate ratio directly standardized for internal comparison b
a
5.78 (1.07, 31.3) 1.18 (0.45, 3.11) * p \ 0.05, ** p \ 0.01
7 SRR (95 %CI)
178**
150* 37 118 11 205 7 175 12
96
Total
138
29
8 117
119 8
3 70
301* 6
1 79
230* 10
2
5
110 2
[30 years
Intestinal cancer
\30 years
Female hourly workers
154
No. of observed deaths No. of observed deaths No. of observed deaths No. of observed deaths No. of observed deaths
SMR
1 to \5 \1
Cause/latency
Table 4 continued
Length of employment (years)
SMR
5 to \10
SMR
C10
SMR
Total
SMR
Int Arch Occup Environ Health
present in females. Based on death certificate information, one male worker (engineer) worked mainly in a plant making large steam turbines, another male worker (engineer) worked mainly in an electrical company and the third male worker was a general building contractor suggesting exposures occurred in jobs unrelated to the capacitor plants. No such information was available for the females. Based on the small number of tumors and the wide confidence intervals, these analyses are unstable and should be interpreted with caution. Carcinoma of the rectum was statistically significantly increased in the combined cohort (SMR 167; CI 107–249; p \ 0.05), but not separately among males or females. Non-Hodgkin’s lymphomas were statistically significantly lower in the total cohort and in males (SMR 64; CI 39–99 and SMR 53; CI 25–97, respectively, p \ 0.05). Some of the statistically significant associations identified for workers and diseases using the US comparison referent population were replicated using New York State rates. Comparison of the total cohort and male and female workers separately (Table 3) regardless of pay status with the population of the state of New York showed that the all-cancer rate was not increased in any of the groups. However, as in the US population comparison, cancers of the buccal cavity and the pharynx were statistically significantly increased among females (SMR 251; CI 115–476; p \ 0.05) and in the total cohort (SMR 163; CI 103–244; p \ 0.05). Also, cancer of the respiratory system and COPD as in the US population comparison were statistically significantly increased among females. Mesotheliomas were statistically significantly increased (SMR 363; CI 118–846; p \ 0.05) in the total cohort but not among male or female workers when analyzed separately. As in the comparison with the general population of the US, nonHodgkin’s lymphoma was again statistically significantly lower in the total cohort and among male workers. Cirrhosis of the liver and liver disease were also statistically significantly lower in the total cohort and among male workers. However, nervous system disorders other than multiple sclerosis were statistically significantly increased in all categories. This was not the case when the entire cohort was compared to the general population for 92 causes of deaths and using the entire cohort from 1946 to 2008. No increase in cancer of the rectum was found in any of the groups. For the New York comparison, the NIOSH life table analysis that started in 1960 for 119 causes of deaths was used. Here, the categories of other diseases of the nervous system and sensory organs were enlarged. This lumping for some end points has little clinical meaning. In Table 4, the trend analysis is presented for cancer of the buccal cavity and pharynx and cancer of the rectum in the total cohort, in females for all cancers, cancer of the buccal cavity and pharynx and cancer of the respiratory
Int Arch Occup Environ Health Table 5 Observed and expected deathsa,b in 1,346 males ever in highly exposed jobsc, 790 workers highly exposed for 6 months or mored and 528 workers exposed for 1 year or moree Cause of deathf
Ever highly exposedg
Highly exposed 6 months or moreh
Highly exposed 1 year or morei
Obs/exp
Obs/exp
Obs/exp
SMR (95 % CI)
SMR (95 % CI)
SMR (95 % CI)
All causes
560/571.19
98 (90–107)
359/369.43
97 (87–108)
261/275.75
95 (84–107)
All cancers
157/149.74
105 (89–123)
104/97.52
107 (87–129)
72/73.06
99 (77–124)
MN tongue MN other buccal
2/0.78 2/0.85
256 (31–923) 236 (29–852)
1/0.49 2/0.55
202 (5–1,127) 366 (44–1,322)
0/0.36 1/0.41
0 (0–1,017) 246 (6–1,368)
MN pharynx
2/1.65
121 (15–438)
2/1.05
191 (23–688)
1/0.77
129 (3–720)
MN esophagus
7/4.59
153 (61–315)
3/2.92
103 (21–300)
2/2.25
93 (11–335)
MN stomach
7/4.27
164 (66–338)
5/2.73
183 (59–427)
3/2.05
147 (30–428)
MN intestine
6/12.43
48 (18–105)
6/8.14
74 (27–160)
6/6.13
98 (36–213)
MN rectum
6/2.82
213 (78–463)
4/1.80
222 (61–569)
3/1.34
225 (46–656)
MN biliary, liver and gall bladder
6/4.21
142 (52–310)
4/2.68
149 (41–382)
4/1.98
202 (55–518)
MN pancreas
8/7.74
103 (45–204)
3/4.99
60 (12–176)
0/3.72
0* (0–99)
MN larynx
5/1.75
285 (93–666)
3/1.13
265 (55–774)
1/0.84
118 (3–660)
MN trachea, bronchus, lung
50/52.18
MN other respiratory sites
1/0.32
316 (8–1,763)
1/0.20
500 (13–2,798)
0/0.15
MN prostate
16/11.16
143 (82–233)
12/7.70
156 (80–272)
10/5.98
167 (80–307)
MN kidney
4/4.06
99 (27–252)
3/2.60
115 (24–337)
3/1.92
156 (32–456)
96 (71–126)
29/34.22
85 (57–122)
19/25.74
74 (44–115) 0 (0–2,536)
MN bladder and other urinary
8/3.98
201 (87–396)
5/2.65
188 (61–440)
4/2.02
198 (54–506)
MN skin MN brain and other nervous
4/3.69 2/4.34
108 (29–277) 46 (6–167)
2/2.31 2/2.70
87 (10–313) 74 (9–268)
2/1.68 2/1.95
119 (14–431) 103 (12–371)
MN other and unspec. site
12/10.39
116 (60–202)
9/6.74
133 (61–253)
6/5.04
119 (44–259)
Non-Hodgkin’s lymphoma
2/5.93
34 (4–122)
2/3.84
52 (6–188)
1/2.86
35 (1–195)
Leukemia
3/5.83
51 (11–150)
3/3.77
80 (16–232)
3/2.81
107 (22–312)
Multiple myeloma
4/2.48
161 (44–413)
3/1.63
184 (38–537)
1/1.23
81 (2–453)
* p \ 0.05 a
No deaths for diseases of the peritoneum, other and unspec sites, digestive organs, pleura, breast, other male genital, eye, thyroid, bone, connective tissue, Hodgkin’s disease, benign and unspec. neoplasms were observed
b
Expected numbers based on age-, sex-, race- and calendar-specific US mortality rates coded according to the rules of the International Classification of Diseases in force at the time of death. Person-years of observation: c52,322, d29,781, e20,075
f
Causes with observed cases. Mean time in high exposure:
g
1.8 years,
system, as well as trachea, bronchus and lungs and for cancer of the intestines of the female hourly workers using the data from the comparison to the US general population. There was no increasing trend for any of these cancers with increasing length of exposure or latency. While some of the category-specific SMRs were statistically significantly increased in and of themselves, they were calculated using small numbers and therefore were unstable. Diseases of the heart, ischemic heart disease, were statistically significantly lower in all groups, while hypertension with heart disease was only statistically significantly lower in the total cohort, as were other diseases of the circulatory system (Tables 2, 3). Diseases of the respiratory system were statistically significantly lower among males (SMR 82; CI 68–98; p \ 0.05), while they were statistically significantly increased among females (SMR 133; CI 111–157; p \ 0.01). Chronic obstructive pulmonary disease (COPD) was also
h
2.9 years, i 4.0 years
highly significantly increased among females (SMR 147; CI 117–183; p \ 0.01) but was not observed in males (Tables 2, 3). Among the total cohort and among male workers, diseases of the digestive system and the genitourinary system were statistically significantly decreased. Comparison to the NY population showed similar results. In Table 5, all-cause, all-cancer and specific cancer mortality of all male workers ever in highly exposed jobs are presented. No statistically significantly increased SMRs were found. Carcinoma of the pancreas was statistically significantly lower than expected among workers highly exposed for more than a year (SMR 0; CI 0–99 p \ 0.05). In the two earlier mortality studies of this cohort (Kimbrough et al. 1999, 2003), hourly and salaried workers were analyzed separately because of the more pronounced ‘‘healthy worker effect’’ observed among salaried workers. These subcategories are presented in Table 6. For the
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Int Arch Occup Environ Health Table 6 Standardized mortality ratios (95 % CI)a based on US death rates of all causes, all cancers and specific cancers in hourly and salaried male and female workers Cause of death
Hourly
Salary
Males (n = 2,977; PYb = 115,923)
Females (n = 2,539; PY = 104,107)
Males (n = 1,079; PY = 45,952)
Females (n = 466; PY = 21,730)
Obs/exp
SMR
Obs/ exp
SMR
Obs/ exp
SMR
Obs/ exp
SMR
All causes
1,192/ 1,197
100 (94–105)
993/ 961
103 (97–110)
431/ 657
66** (60–72)
151/ 185
81* (69–95)
All cancers
320/305
105 (94–117)
329/ 275
120** (107–133)
141/ 176
80** (67–94)
48/55.2
87 (64–115)
MN buccal and pharynx
12/6.93
173(89–203)
8/3.06
261*(113–515)
2/3.65
55(7–198)
2/0.60
335(41–1,211)
MM tongue
3/1.6
183 (38–535)
2/0.7
269 (33–973)
0/0.8
0 (0–438)
1/0.1
7 (18–3,858)
MN other buccal
4/1.8
227 (62–581)
2/0.98
204 (25–735)
1/0.95
105 (3–584)
1/0.2
530 (13–2,953)
MN pharynx
5/3.4
146 (47–341)
4/1.3
303 (83–775)
1/1.8
55 (1–309)
0/0.3
0 (0–1,417)
MN esophagus
15/9.3
161 (90–266)
2/2.6
77 (9–279)
3/5.2
57 (12–167)
0/0.5
0 (0–710)
MN stomach
10/9.0
111 (53–204)
5/5.2
96 (31–224)
2/4.8
42 (5v150)
1/0.98
102 (3–569)
MN intestine MN rectum
24/25.5 9/6.0
94 (60–140) 151 (69–287)
37/24.7 9/4.4
150* (106–207) 205 (94–390)
13/14.7 5/3.2
88 (47–151) 158 (51–369)
3/4.8 1/0.8
63 (13–185) 120 (3–666)
MN biliary, liver and gallbladder
8/8.7
92 (40–182)
8/6.5
122 (53–241)
2/4.8
42 (5–152)
0/1.3
0 (0–285)
MN pancreas
19/15.9
120 (72–187)
13/14.0
93 (49–159)
9/9
100 (46–191)
3/2.8
107 (22–313)
MN larynx
6/3.6
166 (61–362)
1/0.9
112 (3–624)
0/2
0 (0–185)
0/0.2
0 (0–2,016)
MN trachea, bronchus, lung
100/104.8
95 (78–116)
97/63.1
154** (125–187)
36/62.1
58** (41–80)
12/13.4
89 (46–156)
MN breast
2/0.4
517 (63–1,868)
48/51
94 (69–125)
0/0.2
0 (0–1,710)
8/10.1
79 (34–156)
MN cervix Uteri
–
–
6/6.2
96 (35–309)
–
–
4/1.2
335 (91–859)
MN other parts of uterus
–
–
13/7.2
181 (96–209)
–
–
0/1.4
0 (0–266)
MN ovary
–
–
14/17.3
81 (44–136)
–
–
4/3.5
116 (31–296)
MN other female genital
–
–
3/1.2
260 (54–760)
–
–
0/0.2
0 (0–1,649)
MN prostate
28/22.7
123 (82–178)
–
–
16/14.7
109 (62–177)
–
–
MN kidney
12/8.3
145 (75–252)
6/4.7
129 (48–282)
2/4.6
43 (5–156)
1/0.9
107 (3–595)
MN bladder and other urinary
5/8.2
61 (20–143)
2/3.4
60 (7–216)
3/5
61 (13–177)
2/0.7
310 (38–1,120)
MN skinc
8/7.6
105 (45–207)
5/3.9
127 (41–296)
9/4
223* (102–424)
0/0.8
0 (0–461)
MN brain and other nervous
5/9.0
55 (18–129)
2/6.7
30 (4–108)
9/4.6
196 (90–373)
1/1.4
73 (2–408)
MN other and unspec. sites
22/21.2
104 (65–157)
15/18.9
79 (44–131)
11/12.2
90 (45–162)
1/3.7
27 (1–149)
Non-Hodgkin’s lymphoma
8/12.1
66 (29–131)
10/10.3
97 (47–178)
2/6.9
29 (3–104)
0/2.0
0 (0–181)
Leukemia
11/12.0
92 (46–164)
10/8.9
113 (54–208)
7/6.8
102 (41–211)
1/1.8
57 (1–316)
Multiple myeloma
9/5.0
180 (83–343)
6/4.4
135 (50–294)
4/3.0
133 (36–341)
1/0.9
112 (3–624)
Benign and unspec. tumors
2/3.9
51 (6–168)
3/4.3
70 (15–206)
3/2.2
139 (29–405)
1/0.8
121 (3–672)
* p \ 0.05, ** p \ 0.01 a Expected numbers of deaths based on age-, sex-, race- and calendar-specific US mortality rates coded according to the rules of the international classification of diseases in force at the time of death b
PY person-years
c
One skin cancer each among the male and female hourly workers was a squamous cell carcinoma, while the rest were melanomas
salaried male and female workers, the all-cause mortality was statistically significantly decreased compared to the US general population (SMR 66; CI 60–72, p [ 0.01 and
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SMR 81; CI 69–95 p \ 0.05, respectively), which could be a healthy worker effect or a more likely effect related to a higher socioeconomic status (SES).
Int Arch Occup Environ Health Table 7 Melanoma SMRsa and SRRsb for salaried male workers by length of employment and latency Cause/ latency
Length of employment (years) \1
1 to \5
5 to \10
C10
Total
No.c
SMR
No.
SMR
No.
SMR
No.
SMR
No.
SMR
\30 years
2
549
1
211
0
0
0
0
3
226
C30 years
4
589*
1
131
0
0
1
130
6
222
Total SRR (95 % CI)
6 –
575**
2 161 39 (8, 195)
0 –
0
1 99 28 (3, 234)
9 223* 27 (7, 109)
* p \ 0.05, ** p \ 0.01 a
Standardized mortality ratio using the US population to calculate the expected number of deaths
b
Standardized rate ratio directly standardized for internal comparison
c
Observed deaths
Among male hourly workers, none of the specific causes of death were significantly increased. Compared to the general population of the USA (Table 6), intestinal cancer of female hourly workers was significantly increased (SMR 150; CI 106–207; p \ 0.05) but there was no trend of increasing SRRs with increasing duration of employment and latency. When this analysis was done for New York State mortality rates, the difference between the observed and expected rate was no longer statistically significant (37 observed/27 expected, SMR 136; CI 96–187). Among female hourly workers, lung cancer and COPD also were significantly increased using US rates (SMR 154; CI 125–187; p \ 0.01 and SMR 155; CI 121–196; p \ 0.01, respectively), while they both were significantly decreased in male salaried workers. The increase in cancer of the respiratory system and diseases of the respiratory system was confined to the hourly female workers. However, there was no trend of increasing SRRs with increasing duration of employment. The male salaried workers’ skin cancer rate (melanomas) was significantly increased with an SMR of 223 (p \ 0.05, CI 102–424). However, there was no trend of increasing SRRs with increasing duration of employment (Table 7). None of these salaried workers were ever in a high-exposure job, and there was no increase for the hourly workers. Such an increase was also not observed in the total cohort or when salaried and hourly workers were combined, suggesting that lifestyle rather than working in the plant was responsible (Williams and Horm 1977).
Discussion This updated PCB capacitor worker study with a high number of deaths now represents a very long (40? years) follow-up. The plants were heavily contaminated with PCBs, and employees had levels of exposure exceeding
those of the general population. Since the industrial hygiene data were only available for the time when PCB uses were being phased out, we used the job classifications, length of exposure and latency as a surrogate. The results reported herein update our previous studies and add to the body of literature on PCB-exposed capacitor workers. There were no increases for all-cause mortality, mortality for all cancers combined for the total cohort and among males, but all-cancer mortality was statistically significantly increased among females. The increased allcancer mortality in females results from the excess of cancers of the pharynx, buccal cavity, the respiratory system and the intestines. The lack of internal consistency and biological plausibility for one group of workers has a decreased risk of cancer while another has an increased risk, and a lack of a relation to exposure intensity and duration (Table 4) makes the all cancer combined results likely to be a spurious association. Most PCB worker studies have not reported an increased risk of all cancers combined, such as Brown and Jones (1981), Brown (1987), Prince et al. (2006) which included workers from the GE plants, as well as Sinks et al. (1992), Ruder et al. (2006), Bertazzi et al. (1987), Tironi et al. (1996) and Mallin et al. (2004). However, in a recent study, Ruder et al. (2013) reported that the all-cancer mortality among females was increased. The study by Ruder et al. (2013) included workers from the GE plants studied here and from other plants. In their subset of GE workers, melanoma and multiple myeloma were increased. However, only melanoma was statistically significantly increased among salaried male workers in our study. In our present study, several specific cancers were statistically significantly increased or decreased in one subset of workers (total, males, females, salaried males or females and hourly males or females); the lack of consistency within the study by gender and pay status, and the lack of relationships with duration of exposure and latency indicate that these results
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were likely spurious associations due to multiple comparisons. To be able to compare the present findings with the results obtained in our prior updates, we also again analyzed female and male hourly workers and female and male salaried workers separately. As in our prior updates, cancer of the respiratory tract was only increased among female hourly workers reaching statistical significance for the first time in the present study, and again melanoma was only increased among salaried male workers. Analyzing the hourly and salaried workers separately by gender did not attenuate the results. For instance, for the category trachea, bronchus and lung, the SMR for hourly females was 154 (95 % CI 125–187), while when all females were combined, the SMR was 142 (95 % CI 117–172). Intestinal cancer was not statistically significantly increased when hourly and salaried females were combined. However, as in our prior updates as well as in the present study, intestinal cancer was statistically significantly increased in female hourly workers when using US comparison rates, but not when using NY rates, and there was no trend with increasing length of employment and latency (Table 4). The NY population may be a more appropriate comparison group for intestinal cancer, because the incidence as well as the annual death rate from intestinal cancer is higher in the northeastern portion of the USA and greatly influenced by ethnicity and access to medical care (Ries et al. 2000; Schottenfeld and Winawer 1996). Among other capacitor worker studies, in only one of five cohorts, a statistically significant increase in intestinal cancers was reported in women (Prince et al. 2006; Ruder et al. 2013). However, this observation was also not related to duration of employment, included workers from the same cohort, as studied herein and was therefore not an independent observation. Intestinal cancer was not increased in male workers. Currently, there are no supportable hypotheses why there would be an increased risk by gender for intestinal cancer related to PCBs. Among the female hourly workers, lung cancer was statistically significantly increased. This result could be confounded by smoking given the lifestyle of working women at the time compared with homemakers (Brackbill et al. 1988; Covey et al. 1992; Ersoy and Imamoglu 2006; Sterling and Weinkam 1976 and Sterling and Weinkam 1978). Consistent with the concept of confounding by smoking, in this study, COPD was also statistically significantly increased among the hourly female workers, but not in other workers, and so was cancer of the pharynx and buccal cavity. Salaried males uniquely had a statistically significant increase in skin cancer, which was malignant melanoma based on death certificate information. A consideration of risks related to malignant melanoma dates back to 1976,
123
when Bahn et al. (1976) first reported an increased number of melanomas among 31 workers exposed to PCBs. Since then, an increased rate of melanomas (Sinks et al. 1992; Ruder et al. 2013; Loomis et al. 1997) was reported in some worker cohorts. Recently, the International Agency for Research on Cancer (IARC) reclassified PCBs as a known human carcinogen based on melanoma, considering that the human epidemiological evidence was sufficient (Lauby-Secretan et al. 2013). Although our study ambiguously supports the IARC reclassification, the lack of internal consistency among the worker subgroups in our study and the lack of a relationship to employment duration argue against this. Melanomas are more prevalent among white males with a college education and high income according to Williams and Horm (1977). This may explain why the increase in melanomas was only noted among salaried workers in our study. Prostate cancer mortality was not increased in this study. In the studies reported by Prince et al. (2006) and Ruder et al. (2013), overall mortality of prostate cancer was also not increased, but there was a trend with increasing length of exposure that was reported as statistically significant. Furthermore, in an analysis of the most heavily exposed workers in our study, cancer of the prostate was not increased. Most prior studies also have been null or did not report a result for prostate cancer while examining many other cancers (Mallin et al. 2004; Prince et al. 2006; Ruder et al. 2006; Sinks et al. 1992; Tironi et al. 1996). Since cancer of the prostate was not increased in the total cohort of Prince et al. (2006) and Ruder et al. (2013), but increases were only seen with increasing length of exposure and latency, this observation should be regarded with caution. Cancer of the prostate is a cancer of old age, and in our mortality study, the majority of workers with cancer of the prostate died between the ages of 75 and 87 years. Further studies are needed to elucidate these findings. Several case–control and cohort studies for non-Hodgkin’s lymphoma and PCB exposure have been conducted in the general population (Bertrand et al. 2010; Brauner et al. 2012; Cocco et al. 2008; De Roos et al. 2005; Hardell et al. 1996, 2001 Laden et al. 2001, 2010; Maifredi et al. 2011; Quintana et al. 2004; Spinelli et al. 2007; Engel et al. 2007a, b). In these studies, some PCB congeners are inconsistently associated with risk, but for the sum of PCBs, none have reported an increased risk. The study herein and other worker studies show no risk of lymphoma from PCBs, and if the background exposure studies represented true findings, then the worker studies with much higher exposures should show large and consistent risks. There are numerous strengths to this study. The high exposures, long duration of follow-up and latency analysis provide significant power to reveal increased risks. Another
Int Arch Occup Environ Health
strength is the comparison of cases to NY population rates (excluding New York City), allowing for an indirect assessment of local health, life style and medical confounding variables. Also, while it may be possible that there is some misclassification of exposures within the plant, given the widespread contamination in the plant with their shared ventilation system, it is reasonable to assume that all workers were exposed to PCBs above background, including workers not directly working with PCBs (e.g., clerical workers). Another strength of the study is that we have analyzed the data in many ways that would have revealed consistent increases, if they existed, using an exposure assessment with firsthand knowledge of actual workplace practices over many years. We had considered conducting a subset analysis before and after 1965 as there were ventilation improvements at that time and different Aroclors were used over time in the plants, (for many years, it was totally or partially Aroclor 1254). However, there were very few workers who worked only before 1965. There are also limitations to this study, which are typical for retrospective cohort studies. Many comparisons were made, and the positive and/or negative findings may be due to chance, particularly because in some cases the numbers per specific end points were small combined with wide confidence intervals. For some cancers, there may be limited power to assess low-level risk, but this large cohort combined with 40? years of follow-up in workers improves power, and therefore reduces concerns for the general population with much lower levels of exposure. Other limitations are the inability to assess potential confounding such as smoking, lifestyle and sun exposure. Also, the lack of pathological confirmation through pathology reports could lead to misclassification. This would be particularly important for organs with frequent metastases, such as the lung and brain. Another limitation was the inability to consider individual PCB congener exposure, although the biological plausibility for an effect of a particular congener independent of total PCB exposure as happens for people is unlikely. A further issue is the healthy worker survival effect which was pronounced in our initial study (Kimbrough et al. 1999). Here, the all causes of deaths were statistically significantly lower than expected among the different groups of capacitor workers. However, this was attenuated in the second analysis (Kimbrough et al. 2003) among the hourly workers but was still pronounced in the salaried workers. If the salaried workers were combined with the hourly workers in the present study, total mortality and mortality among all males were also statistically significantly lower, suggesting that the removal of the salaried workers attenuated the healthy worker survival effect and or the effect of a
higher SES of the salaried workers since a higher SES is positively associated with better health and well being. Unfortunately, the available PCB air levels in the plants and the PCB blood levels measured in the workers were sparse and only obtained in 1975 and 1977 when PCBs were being phased out. We do not know which workers participated in the serum PCB determinations by Wolff et al. (1982). The PCB levels measured by GE (Lawton et al. 1981, 1985) and by Wolff et al. (1982) were obtained when Aroclor 1016 was used and when the use of PCBs was phased out. Thus, the available data are likely not representative of levels in the plant and in the workers for the prior 31 years. As a likely underestimate, however, they confirm the high level of exposures compared to the general population, and support the use of job classifications. Thus, using job classifications and length of exposure represent a reasonable surrogate for the inadequate industrial hygiene data. We note that other investigators have included the workers in these plants in their mortality studies and have analyzed their data with exposure assessments that they created from the limited amount of air data covering periods of time when Aroclor 1016 was used in 1975 and 1977 (Prince et al. 2006; Hopf et al. 2010; Ruder et al. 2013). In these assessments, assumptions were made about both inhalation and dermal absorption prior to 1975 and as far back as the 1940s for other types of Aroclors, in spite of the inadequate data base. In 2009, a weight of evidence review and causation assessment for PCBs and cancer risk, using Bradford Hill guidelines, was published (Hill 1965; Golden and Kimbrough 2009) with the conclusion that no causal association between PCB exposure and any specific cancer or all cancers combined among PCB-exposed workers exists. In the last 4 years, PCB and cancer risk have remained an active area of epidemiological research (Bertrand et al. 2010; Brauner et al. 2012; Gallagher et al. 2011; Laden et al. 2010; Maifredi et al. 2011, Tomassallo et al. 2010, Viel et al. 2011; Pesatori et al. 2013; Ruder et al. 2013). The varied findings in this and other recent studies are hypothesis generating but do not prove a causal association, especially in the context of inconsistencies among the worker studies. Acknowledgments This research study was funded by the General Electric Company; not all authors received support for the data analysis and manuscript preparation. Conflict of interest Dr. Shields served as a consultant and expert witness for companies that have manufactured and/or used PCBs. Dr. Krouskas is remunerated by the Center for Health Risk Evaluation. The Center receives money from the General Electric Company. Dr. Kimbrough receives funding from the General Electric Company for the execution of this study and in the past for consulting services. Wenjing Xu receives no funding and no remuneration.
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References Bahn AK, Rosenwaike I, Hermann N et al (1976) Letter: Melanoma after exposure to PCB’s. N Engl J Med 295:450 Bertazzi PA, Riboldi L, Pesatori A et al (1987) Cancer mortality of capacitor manufacturing workers. Am J Ind Med 11:165–176 Bertrand KA, Spiegelman D, Aster JC et al (2010) Plasma organochlorine levels and risk of non-Hodgkin lymphoma in a cohort of men. Epidemiology 21:172–180 Brackbill R, Frazier T, Shilling S (1988) Smoking characteristics of US workers, 1978–1980. Am J Ind Med 13:5–41 Brauner EV, Sorensen M, Gaudreau E et al (2012) A prospective study of organochlorines in adipose tissue and risk of nonHodgkin lymphoma. Environ Health Perspect 120:105–111 Brown DP (1987) Mortality of workers exposed to polychlorinated biphenyls—an update. Arch Environ Health 42:333–339 Brown DP, Jones M (1981) Mortality and industrial hygiene study of workers exposed to polychlorinated biphenyls. Arch Environ Health 36:120–129 Chase KH, Wong O, Thomas D et al (1982) Clinical and metabolic abnormalities associated with occupational exposure to polychlorinated biphenyls (PCBs). J Occup Med 24(2):109–114 Cocco P, Brennan P, Ibba A et al (2008) Plasma polychlorobiphenyl and organochlorine pesticide level and risk of major lymphoma subtypes. Occup Environ Med 65:132–140 Covey LS, Zang EA, Wynder EL (1992) Cigarette smoking and occupational status: 1977 to 1990. Am J Public Health 82:1230–1234 De Roos AJ, Hartge P, Lubin JH et al (2005) Persistent organochlorine chemicals in plasma and risk of non-Hodgkin’s lymphoma. Cancer Res 65:11214–11226 Doody MM, Hayes HM, Bilgrad R (2001) Comparability of national death index plus and standard procedures for determining causes of death in epidemiologic studies. Ann Epidemiol 11:46–50 Engel LS, Laden F, Andersen A et al (2007a) Polychlorinated biphenyl levels in peripheral blood and non-Hodgkin’s lymphoma: a report from three cohorts. Cancer Res 67:5545–5552 Engel LS, Lan Q, Rothman N (2007b) Polychlorinated biphenyls and non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev 16:373–376 Ersoy C, Imamoglu S (2006) Comparison of the obesity risk and related factors in employed and unemployed (housewife) premenopausal urban women. Diabetes Res Clin Pract 72:190–196 Gallagher RP, Macarthur AC, Lee TK et al (2011) Plasma levels of polychlorinated biphenyls and risk of cutaneous malignant melanoma: a preliminary study. Int J Cancer 128:1872–1880 Golden R, Kimbrough R (2009) Weight of evidence evaluation of potential human cancer risks from exposure to polychlorinated biphenyls: an update based on studies published since 2003. Crit Rev Toxicol 39:299–331 Hardell L, Van Havel B, Lindsrom G et al (1996) Higher concentrations of specific polychlorinated biphenyl congeners in adipose tissue from non-Hodgkin’s lymphoma patients compared with controls without a malignant disease. Int J Oncol 9:603–608 Hardell E, Eriksson M, Lindstrom G et al (2001) Case-control study on concentrations of organohalogen compounds and titers of antibodies to Epstein-Barr virus antigens in the etiology of nonHodgkin lymphoma. Leuk Lymphoma 42:619–629 Hill AB (1965) The environment and disease: association or causation. Proc R Soc Med 58:295–300 Hopf NB, Waters MA, Ruder AM et al (2010) Development of a retrospective job exposure matrix for PCB exposed workers in capacitor manufacturing. J Occup Health 52(4):199–208
123
Jones M (1983) Industrial hygiene survey Washington. In: DC National Institute for Occupational Safety and Health NIOSH publication 83-137224. Reprinted by the National Technical Information Service Kimbrough RD, Krouskas CA (2003) Human exposure to polychlorinated biphenyls and health effects: a critical synopsis. Toxicol Rev 22:217–233 Kimbrough RD, Doemland ML, LeVois ME (1999) Mortality in male and female capacitor workers exposed to polychlorinated biphenyls. J Occup Environ Med 41:161–171 Kimbrough RD, Doemland ML, Mandel JS (2003) A mortality update of male and female capacitor workers exposed to polychlorinated biphenyls. J Occup Environ Med 45:271–282 Kreiss K (1985) Studies on populations exposed to polychlorinated biphenyls. Environ Health Perspect 60:193–199 Laden F, Hankinson SE, Wolff MS, Colditz GA, Willett WC, Speizer FE, Hunter DJ (2001) Plasma organochlorine levels and the risk of breast cancer: an extended follow-up in the Nurses’ Health Study. Int J Cancer 91:568–574 Laden F, Bertrand KA, Altshul L et al (2010) Plasma organochlorine levels and risk of non-Hodgkin lymphoma in the Nurses’ Health Study. Cancer Epidemiol Biomarkers Prev 19:1381–1384 Lauby-Secretan B, Loomis D, Grosse Y et al (2013) Carcinogenicity of polychlorinated biphenyls and polybrominated biphenyls. Lancet Oncol. doi: 10.1016/S1470-2045(13)70104-9(0) Lawton RW, Sack BD, Ross MR et al (1981) Studies of employees occupationally exposed to PCBs, a progress report. General Electric Company, Environmental Protection Agency (submitted) Lawton RW, Brown JF Jr, Ross MR et al (1985a) Comparability and precision of serum PCB measurements. Arch Environ Health 40:29–37 Lawton RW, Ross MR, Feingold J et al (1985b) Effects of PCB exposure on biochemical and hematological findings in capacitor workers. Environ Health Perspect 60:165–184 Loomis D, Browning SR, Schenk AP et al (1997) Cancer mortality among electrical workers exposed to polychlorinated biphenyls. Occup Environ Med 54:720–728 Maifredi G, Donato F, Magoni M et al (2011) Polychlorinated biphenyls and non-Hodgkin’s lymphoma: a case-control study in Northern Italy. Environ Res 111:254–259 Mallin K, McCann K, D’Aloisio A et al (2004) Cohort mortality study of capacitor manufacturing workers, 1944–2000. J Occup Environ Med 46:565–576 Mayes BA, McConnell EE, Neal BH et al (1998) Comparative carcinogenicity in Sprague Daley rats of the polychlorinated biphenyl mixtures Aroclor 1016, 1242, 1254 and 1260. Toxicol Sci 41:62–76 Nichols BR, Hentz KL, Aylward L, Hays SM, Lamb JC (2007) Agespecific references for polychlorinated biphenyls (PCB) based on the NHANES 2001–2002 survey. J Toxicol Environ Health A 70:1873–1877 Pesatori AC, Grillo P, Consonni D et al (2013) Update of the mortality study of workers exposed to polychlorinated biphenyls (PCBs) in two Italian capacitor manufacturing plants. Med Lav 104:107–114 Prince MM, Ruder AM, Hein MJ et al (2006) Mortality and exposure response among 14,458 electrical capacitor manufacturing workers exposed to polychlorinated biphenyls (PCBs). Environ Health Perspect 114:1508–1514 Quintana PJ, Delfino RJ, Korrick S et al (2004) Adipose tissue levels of organochlorine pesticides and polychlorinated biphenyls and risk of non-Hodgkin’s lymphoma. Environ Health Perspect 112:854–861 Ries LA, Wingo PA, Miller DS et al (2000) The annual report to the nation on the status of cancer, 1973–1997, with a special section on colorectal cancer. Cancer 88:2398–2424
Int Arch Occup Environ Health Robinson CF, Schnorr TM, Cassinelli RT et al (2006) Tenth revision U.S. mortality rates for use with the NIOSH Life Table Analysis System. J Occup Environ Med 48:662–667 Rothman K (1986) Modern epidemiology. Little Brown, Boston Rothman KJ, Greenland S (1998) Modern epidemiology. Lippincott Williams & Wilkins, Philadelphia Ruder AM, Hein MJ, Nilsen N et al (2006) Mortality among workers exposed to polychlorinated biphenyls (PCBs) in an electrical capacitor manufacturing plant in Indiana: an update. Environ Health Perspect 114:18–23 Ruder AM, Hein MJ, Hopf NB, Waters MA (2013) Mortality among 24, 865 workers exposed to polychlorinated biphenyls (PCBs) in three electrical capacitor manufacturing plants: a ten year update. Int J Hyg Environ Health. doi:10.1016/.ijheh.2013.04. 006 Sathiakumar N, Delzell E, Abdalla O (1998) Using the National Death Index to obtain underlying cause of death codes. J Occup Environ Med 40:808–813 Schottenfeld D, Winawer SJ (1996) Cancers of the large intestines. In: Schottenfeld D, Fraumeni JF (eds) Cancer, epidemiology, prevention. Oxford University Press, New York, pp 813–840 Shields PG (2006) Understanding population and individual risk assessment: the case of polychlorinated biphenyls. Cancer Epidemiol Biomarkers Prev 15:830–839 Sinks T, Steele G, Smith AB et al (1992) Mortality among workers exposed to polychlorinated biphenyls. Am J Epidemiol 136: 389–398
Spinelli JJ, Ng CH, Weber JP et al (2007) Organochlorines and risk of non-Hodgkin lymphoma. Int J Cancer 121:2767–2775 Sterling TD, Weinkam JJ (1976) Smoking characteristics by type of employment. J Occup Med 18:743–754 Sterling TD, Weinkam JJ (1978) Smoking patterns by occupation, industry, sex, and race. Arch Environ Health 33:313–317 Tironi A, Pesatori A, Consonni D et al (1996) The mortality of female workers exposed to PCBs. Epidemiol Prev 20:200–202 Tomassallo C, Anderson H, Haughwout M et al (2010) Mortality among frequent consumers of Great Lake sport fish. Environ Res 110(1):62–9 U.S. Epa (US Environmental Protection Agency) (1982) Polychlorinated Biphenyls (PCBs): manufacturing, processing, distribution in commerce and use prohibition: use in electrical equipment. Fed Reg 47:37–342 Viel JF, Floret N, Deconinck E et al (2011) Increased risk of nonHodgkin lymphoma and serum organochlorine concentrations among neighbors of a municipal solid waste incinerator. Environ Int 37:449–453 Williams RH, Horm JW (1977) Association of cancer sites with tobacco and alcohol consumption and socioeconomic status of patients: interview study from the third national cancer survey. J Natl Cancer Inst 58:525–547 Wolff MS, Fischbein A, Thornton J et al (1982) Body burden of polychlorinated biphenyls among persons employed in capacitor manufacturing. Int Arch Occup Environ Health 49:199–208
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