Evaluation of mortality among Marines, Navy personnel, and civilian workers exposed to contaminated drinking water at USMC Base Camp Lejeune: a cohort study

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Bove This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4171975/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Drinking water at U.S. Marine Corps Base Camp Lejeune, North Carolina was contaminated with trichloroethylene and other industrial solvents from 1953 to 1985. Methods A cohort mortality study was conducted of Marines/Navy personnel who, between 1975 and 1985, began service and were stationed at Camp Lejeune (N = 159,128) or Camp Pendleton, California (N = 168,406), and civilian workers employed at Camp Lejeune (N = 7,332) or Camp Pendleton (N = 6,677) between October 1972 and December 1985. Camp Pendleton’s drinking water was not known to be contaminated between 1972 and December 1985. Mortality follow-up was between 1979 and 2018. Survival analyses were used to calculate hazard ratios (HRs) comparing mortality rates between Camp Lejeune and Camp Pendleton cohorts and assess the effects of duration at Camp Lejeune. The ratio of upper and lower 95% confidence interval (CI) limits, or CIR, was used to evaluate the precision of effect estimates. The study focused on underlying causes of death with HRs ≥ 1.20 and CIRs ≤ 3. Results from contributing causes were also presented. Results Deaths among Camp Lejeune and Camp Pendleton Marines/Navy personnel totaled 19,250 and 21,134, respectively. Deaths among Camp Lejeune and Camp Pendleton civilian workers totaled 3,055 and 3,280, respectively. Compared to Camp Pendleton Marines/Navy personnel, Camp Lejeune had adjusted HRs ≥ 1.20 with CIRs ≤ 3 for cancers of the kidney (HR = 1.21, 95% CI: 0.95, 1.54), esophagus (HR = 1.24, 95% CI: 1.00, 1.54) and female breast (HR = 1.20, 95% CI: 0.73, 1.98). Causes of death with HRs ≥ 1.20 and CIR > 3, included Parkinson disease, myelodysplastic syndrome and cancers of the testes, cervix and ovary. Compared to Camp Pendleton workers, Camp Lejeune had adjusted HRs ≥ 1.20 with CIRs ≤ 3 for chronic kidney disease (HR = 1.88, 95% CI: 1.13, 3.11) and Parkinson disease (HR = 1.21, 95% CI: 0.72, 2.04). Female breast cancer had an adjusted HR of 1.19 (95% CI: 0.76, 1.88). Sensitivity analyses indicated that confounding bias due to unmeasured risk factors (e.g., smoking) is unlikely to significantly impact the findings. Conclusion Marines/Navy personnel and civilian workers likely exposed to contaminated drinking water at Camp Lejeune had increased hazard ratios for several causes of death compared to Camp Pendleton. USMC base Camp Lejeune USMC base Camp Pendleton Marines/Navy personnel civilian workers mortality cancer drinking water trichloroethylene tetrachloroethylene benzene vinyl chloride hazard ratio Background Industrial solvents were detected in drinking water samples taken between 1980 and 1985 at United States Marine Corps (USMC) Base Camp Lejeune, North Carolina from drinking water supplied by two of the base’s eight treatment plants. Each drinking water treatment plant served a different area of the base. The Tarawa Terrace (TT) treatment plant began operating in 1952 and served approximately 1,850 family housing units. The TT system was contaminated by an off-base dry-cleaning business. Tetrachloroethylene (PCE) was the primary contaminant in the TT distribution system with measured concentrations of 104 micrograms per liter (µg/L) in July 1982 and a maximum level of 215 µg/L in January 1985. Much lower levels of trichloroethylene (TCE), trans-1,2-dichloroethylene (DCE), and vinyl chloride occurred in the distribution system due to PCE degradation in groundwater [ 1 ]. The Hadnot Point (HP) treatment plant began operation in 1942 and served the base’s “mainside” including most of the bachelor’s quarters (“barracks”), a small number of family housing units, field training areas (via mobile “water buffaloes”) and eating establishments. The HP system was contaminated by on-base sources – leaking underground storage tanks, industrial area spills, and waste disposal sites. TCE and PCE were the primary contaminants, with maximum measured levels in the distribution system of 1,400 µg/L and 100 µg/L, respectively, during 1982. A TCE concentration of 1,148 µg/L was measured in drinking water from the HP treatment plant in January1985. Also detected in the drinking water at the HP treatment plant during 1984 and/or 1985 were benzene, from fuel spills and leaks, and DCE and vinyl chloride, from the degradation of PCE and TCE in groundwater [ 2 ]. The Holcomb Boulevard (HB) treatment plant began operation in 1972 and served approximately 2,100 family housing units and a bachelor officer quarters (BOQ). The HB service area was uncontaminated except for intermittent dry periods when the HP system provided supplementary water. During a two-week period starting in late-January 1985, the HB plant was shut down for repairs and the HP system provided water to the HB service area [ 2 ]. No drinking water samples for volatile organic compounds were collected at Camp Lejeune prior to 1980, and there were a limited number of samples taken between 1982 and 1985. Therefore, ATSDR conducted historical reconstruction modeling to estimate the monthly average contaminant levels in the TT and HP distribution systems. Details of the methodology have been summarized elsewhere [ 1 – 2 ]. Based on the historical reconstruction modeling, it was estimated that the HP and TT drinking water systems were contaminated starting in the mid-1950s. The heavily contaminated supply wells were shut down by February 1985, although levels of benzene above its maximum contaminant level (MCL) of 5 µg/L were detected on 11/19/1985 (2,500 µg/L) and on 12/10/1985 (38 µg/L) in the HP distribution system. In each system, water from supply wells was mixed at the treatment plant prior to distribution. Contamination levels in each system varied depending on the wells in use, their levels of contamination, and their pumpage rates [ 1 – 2 ]. Estimated monthly average concentrations of PCE in the TT distribution system between January 1975 and February 1985 ranged from 0 to 158 µg/L with a median of approximately 85 µg/L [ 1 ]. Estimated monthly average concentrations of TCE in the HP distribution system during this period ranged from 0 to 783 µg/L, with a median level of approximately 366 µg/L [ 2 ]. In addition, estimated monthly average levels of PCE and vinyl chloride in the HP distribution system during this period ranged from 0 to 39 µg/L and 0 to 67 µg/L, respectively, with medians of the estimates of 15 µg/L and 22 µg/L, respectively [ 2 ]. The United States Environmental Protection Agency (EPA) MCLs are 5 µg/L for TCE, PCE and benzene, 2 µg/L for vinyl chloride, and 100 µg/L for DCE ( https://www.epa.gov/ground-water-and-drinking-water/national-primary-drinking-water-regulations#Organic ). EPA and the International Agency for Research on Cancer (IARC) classified TCE as a human carcinogen [ 3 – 5 ]. The EPA classified PCE as a “likely human carcinogen” [ 6 ] and IARC classified PCE as “probably carcinogenic to humans” [ 4 – 5 ]. Both benzene and vinyl chloride are known human carcinogens [ 7 – 9 ]. The carcinogenicity of DCE is not classified by EPA. Drinking water exposures to TCE, PCE, DCE, vinyl chloride, and benzene involve contributions to total internal body dose from three routes: ingestion, inhalation, and dermal. A Marine in training may consume as much as 6 liters/day of drinking water [ 10 ]. The combined dose from the inhalation and dermal routes may be as high or higher than the dose from the ingestion route. For example, an internal dose via inhalation to TCE during a 10-minute shower may equal the internal dose via the ingestion of 2 liters of TCE-contaminated drinking water [ 11 ]. An ATSDR report assessed the strength of the evidence supporting causality of cancers and other diseases from exposures to TCE, PCE, vinyl chloride and benzene [ 12 ]. The assessment integrated findings from previous ATSDR studies at Camp Lejeune and studies conducted by other researchers of populations exposed occupationally or via drinking water to these chemicals. The assessment found sufficient causal evidence for TCE exposure and kidney cancer and non-Hodgkin lymphoma (NHL), and “equipoise and above evidence” (i.e., evidence for causation that was at least as likely as not or greater) for TCE exposure and multiple myeloma, leukemias, liver cancer, Parkinson disease, end-stage renal disease, and scleroderma. Sufficient causal evidence was found for PCE exposure and bladder cancer, and “equipoise and above evidence” for PCE exposure and NHL and end-stage renal disease. Sufficient causal evidence was found for benzene exposure and NHL and leukemias, and “equipoise and above evidence” for benzene exposure and multiple myeloma. Sufficient evidence was concluded for vinyl chloride exposure and liver cancer. Few studies have evaluated drinking water exposures to TCE, PCE, vinyl chloride or benzene and the risk of specific causes of death. ATSDR previously conducted cohort mortality studies comparing Marines/Navy personnel and civilian workers stationed or employed at Camp Lejeune from 1975 to 1985 and 1973 to 1985, respectively, with similar cohorts over the same periods stationed or employed at USMC Base Camp Pendleton, California [ 13 – 14 ]. Both of the previous Camp Lejeune cohort mortality studies of Marines/Navy personnel and civilian workers found increased risks of death from cancers of the kidney, rectum, lung, prostate, leukemias, and multiple myeloma [ 13 – 14 ]. In addition, the previous Camp Lejeune cohort mortality study of Marines/Navy personnel found increased risks of death from cancers of the esophagus, liver, and cervix; Hodgkin lymphoma; and multiple sclerosis [ 13 ]. Although Parkinson disease mortality could not be evaluated in the previous Camp Lejeune cohort mortality study of Marines/Navy personnel because of sparse data, Parkinson mortality risk was increased in the Camp Lejeune cohort mortality study of civilian workers [ 14 ]. An increased risk of mortality due to oral cavity cancers was also found in the study of civilian workers [ 14 ]. The follow-up period for both of the previous Camp Lejeune mortality studies was between 1979 and 2008. The current cohort mortality study extends the follow-up period to 2018. The purpose of the current cohort study of Camp Lejeune Marines/Navy personnel and civilian workers was to determine if being stationed or employed at Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), a portion of the period when the drinking water was contaminated, increased the risk of specific causes of death during the follow-up period between 1979 and 2018 compared to being stationed or employed at Camp Pendleton. Camp Pendleton was not known to have contaminated drinking water during the years prior to 1986 [ 15 ]. Methods Study population ATSDR obtained quarterly personnel data from the Defense Manpower Data Center (DMDC) for Marines/Navy personnel stationed at Camp Lejeune (N = 217,988) and Camp Pendleton (N = 232,026) for the years 1975 through 1985, who were known to be alive at the start of follow-up on January 1, 1979. The end of the year 1985 was selected because drinking water distribution system samples taken at Camp Lejeune from 1986 onward indicated no contamination above the contaminants’ MCLs. Although drinking water contamination preceded 1975, the code for the unit (e.g., regiment, battalion, company, etc.) that an individual was assigned to, which is necessary to determine the base where the individual was stationed, was not available in the DMDC database until the second quarter of 1975. In addition to unit code, the DMDC data included date of birth, marital status, rank (paygrade), date active duty started, military occupation code, education level at the start of service, race, sex, full name, and social security number. The USMC provided a list of the codes for the units that were stationed at each base. From the DMDC data, it was estimated that during the period 1975–1985, the average duration that Marines/Navy personnel were stationed at Camp Lejeune was about 18 months. Some of the Marines/Navy personnel began active duty prior to 1975 when information on base location (i.e., unit code) was not available in the DMDC data. For these Marines, it would be unknown whether those stationed at Camp Pendleton between 1975 and 1985 were stationed at Camp Lejeune prior to 1975. Since it was not unusual for a Marine to be stationed at both bases, it was likely that some Marines who began active duty prior to 1975 and were stationed at Camp Pendleton between 1975 and 1985, were stationed at Camp Lejeune prior to 1975. To address this problem, a subgroup of the full cohort was identified consisting of Marines/Navy personnel who began active duty between 1975 and 1985, when information on base location was available in the DMDC database. This subgroup consisted of 154,821 at Camp Lejeune and 163,484 at Camp Pendleton who were known to be alive at the start of follow-up on January 1, 1979. Comparisons between the Camp Lejeune and Camp Pendleton subgroup constituted the main focus of the evaluation of mortality among Marines/Navy personnel. ATSDR also obtained quarterly personnel data from the DMDC for civilian workers employed at Camp Lejeune (N = 7,332) and Camp Pendleton (N = 6,677) between October 1972 and December 1985, who were known to be alive at the start of follow-up on January 1, 1979. October 1972 was the first quarter that the DMDC had personnel data for civilian workers. The DMDC information included base location of employment, social security number, full name (in the DMDC data beginning in the last quarter of 1981), date of birth, paygrade, education level, race, sex, and occupation code. Based on the DMDC data, the average duration of employment at Camp Lejeune between October 1972 and December 1985 was 64 months. Camp Pendleton Marines/Navy personnel and civilian workers were chosen as comparison groups in this study because the drinking water at the base was not known to be contaminated prior to 1986 [ 15 ]. Camp Pendleton Marines/Navy personnel and civilian workers were similar to their counterparts at Camp Lejeune in terms of demographics, socioeconomic and cultural factors, training activities, and types of military and civilian employee occupations. In addition, the Marines/Navy personnel at both bases had similar pre-enlistment screening and fitness requirements. Biases due to the healthy veteran effect [ 16 – 18 ] or the healthy worker effect [ 19 ], as well as due to unmeasured confounders, should be reduced by having comparison cohorts with similar risk factors as the Camp Lejeune cohorts. Vital status ascertainment To obtain vital status, personal identifier information from the DMDC database was submitted to a locator firm and subsequently to the Social Security Administration (SSA) for linkage with its Data for Epidemiological Researchers database. Data returned from SSA included a status code indicating vital status of “D” (deceased), “L” (living) or “U” (undetermined). SSA was able to match about 99% of the records. Finally, personal identifier information of deaths identified via matching with the locator firm and SSA that were not included in the previous mortality studies (i.e., deaths occurring after 2008 as well as deaths missed in the previous mortality studies) and of individuals with unknown vital status was submitted to the National Death Index (NDI) to obtain the International Classification of Diseases (ICD), Ninth and Tenth codes for underlying and contributing causes of death and date of death. Those whose vital status remained unknown after the NDI search were considered “lost to follow-up” but contributed person-years to the study until the last date they were known to be alive. About 1% of the Camp Lejeune and Camp Pendleton cohorts were lost to follow-up (Tables 1 – 2 , and S 1 - 1 ). Table 1 Demographic information for the Marines/Navy personnel subgroup at risk during the follow-up period, who began military service and were stationed at Camp Lejeune or Camp Pendleton between 1975 and 1985 Base Camp Lejeune N (%) Camp Pendleton N (%) (ref) Total N (%) Marines at risk 159,128 (48.6) 168,406 (51.4) 327,534 Sex Male 151,026 (94.9) 162,473 (96.5) 313,499 (95.7) Female 8,102 (5.1) 5,933 (3.5) 14,035 (4.3) Race White 116,501 (73.2) 131,011 (77.8) 247,512 (75.6) Black or African American 38,365 (24.1) 28,657 (17.0) 67,022 (20.5) Other race 4,262 (2.7) 8,738 (5.2) 13,000 (4.0) Rank E1 – E4 130,312 (81.9) 137,281 (81.5) 267,593 (81.7) E5 – E9 23,049 (14.5) 23,434 (13.9) 46,483 (14.2) WO or CO 5,767 (3.6) 7,691 ( 4.6) 13,458 (4.1) Education High school graduate 133,140 (83.7) 132,871 (78.9) 266,011 (81.2) <High school 19,951 (12.5) 27,362 (16.2) 47,313 (14.4) College graduate and higher 6,037 (3.8) 8,173 (4.9) 14,210 (4.3) Age, at start of follow-up (1/1/1979) Mean 20.2 years 20.5 years 20.3 years Median 20.0 years 20.0 years 20.0 years Age at end of follow-up * Mean 56.4 years 56.6 years 56.5 years Median 57.0 years 58.0 years 57.0 years % Age > 55 years 66.0% 67.6% 66.8% % Age > 65 years 1.7% 2.0% 1.9% Deaths ¥ Number 19,250 21,134 40,384 % of cohort 12.1% 12.5% 12.3% Base Camp Lejeune Camp Pendleton (ref) Total Length of follow-up (years) Mean 36.2 36.1 36.2 Median 38.0 38.0 38.0 Total person-years of follow-up 5,760,931 6,078,598 11,839,529 Total lost to follow-up 1,072 (0.7%) 1,231 (0.7%) 2,303 (0.7%) Quarters in the DMDC data, October 1972 – December 1985 € Camp Lejeune Camp Pendleton (ref) Mean 7.7 7.2 Median 7.0 6.0 Minimum 1 1 Maximum 41 42 Interquartile range (25th -75th percentiles) 8 (3–11) 8 (3–11) E1 – E4: private to corporal E5 – E9: sergeant to sergeant major WO: warrant officer CO: commissioned officer * Age at end of follow-up (12/31/2018 or date of death if earlier than 12/31/2018). ¥ Deaths occurring 1/1/1979–12/31/2018. € Number of quarters stationed at either Camp Lejeune or Camp Pendleton during 1975–1985. Some members of the Camp Lejeune cohort, who were stationed at least one quarter at Camp Lejeune during 1975–1985, were also stationed at Camp Pendleton during 1975–1985. So, the statistics for the Camp Lejeune cohort include quarters at Camp Pendleton during 1975–1985. The Camp Pendleton cohort members were not stationed at Camp Lejeune during 1975–1985. Table 2 Demographic information for civilian workers at risk during the follow-up period who were employed at Camp Lejeune or Camp Pendleton between 12/72 and 12/85 Factor Camp Lejeune N = 7,332 (52.3%) Camp Pendleton (ref) N = 6,677 (47.7%) Total N = 14,009 Male 3,708 (50.6%) 3,646 (54.6%) 7,354 (52.5%) Female 3,624 (49.4%) 3,031 (45.4%) 6,655 (47.5%) White 5,539 (75.5%) 5,199 (77.9%) 10,738 (76.7%) African American 1,409 (19.2%) 498 (7.5%) 1,907 (13.6%) Other or unknown race 384 (5.2%) 980 (14.7%) 1,364 (9.7%) Blue collar 2,819 (38.4%) 2,798 (41.9%) 5,617 (40.1%) White collar 4,513 (61.6%) 3,879 (58.1%) 8,392 (59.9%) Not a high school graduate 1,038 (14.2%) 679 (10.2%) 1,717 (12.3%) High school graduate 5,206 (71.0%) 5,539 (83.0%) 10,745 (76.7%) College graduate and higher 1,088 (14.8%) 459 (6.9%) 1,547 (11.0%) Age at start of follow-up (1/1/1979) Mean (years) 39.1 41.2 40.1 Median (years) 36 41 38 Age at end of follow-up (12/31/2018 or date of death) Mean 71.3 72.4 71.8 Median 70 72 71 Age > 65 years 5,185 (70.7%) 4,760 (71.3%) 9,945 (71.0%) Age > 70 years 3,574 (48.7%) 3,586 (53.7%) 7,160 (51.1%) Age > 75 years 2,377 (32.4%) 2,571 (38.5%) 4,948 (35.3%) Died during 1/2/1979–12/31/2018 3,055 (41.7%) 3,280 (49.1%) 6,335 (45.2%) Length of follow-up (years Mean (years) 31.5 30.5 31.0 Median (years) 36 34 35 Total person-years of follow-up 231,496 203,469 434,965 Total lost to follow-up 111 (1.5%) 84 (1.3%) 195 (1.4%) Quarters in the DMDC data, 10/1972-12/1985 * Camp Lejeune Camp Pendleton (ref) Mean 18.9 17.3 Median 12.0 11.0 Minimum 1 1 Maximum 53 53 Interquartile range (25th -75th percentiles) 30 (3–33) 23 (4–27) * Number of quarters employed at either Camp Lejeune or Camp Pendleton during 10/72 − 12/1985. Some members of the Camp Lejeune cohort, who were employed at least one quarter at Camp Lejeune during 10/72 − 12/1985, were also employed at Camp Pendleton during 10/72 − 12/1985. So, the statistics for the Camp Lejeune cohort include quarters at Camp Pendleton during 10/72 − 12/1985. The Camp Pendleton cohort members were not employed at Camp Lejeune during 10/72 − 12/1985. Data analysis Follow-up began on January 1, 1979, or at the start of employment or military service at Camp Lejeune or Camp Pendleton, whichever was later, and continued until December 31, 2018, if the individual was known to be alive, or to date of death. The previous mortality studies’ end of follow-up was on December 31, 2008 [ 13 – 14 ]. The present study included all the deaths in the previous studies and extended the follow-up period an additional ten years to December 31, 2018. The analyses of Marines/Navy personnel focused on comparisons between the Camp Lejeune and Camp Pendleton subgroup. For rare causes of death that primarily occur among older populations such as male breast cancer, the focus of the analyses included comparisons between Camp Lejeune and Camp Pendleton Marines/Navy personnel in the full dataset (“full cohort”). The descriptive analyses included the computing of cause-specific, standardized mortality ratios (SMRs) comparing Camp Lejeune and Camp Pendleton to the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death using the life table analysis system or “LTAS” [ 20 ]. Poisson regressions comparing the sex, race, and five-year age-specific underlying causes of death for Camp Lejeune versus Camp Pendleton were conducted as part of the descriptive analyses because comparisons of the SMRs between the two bases could be impacted by residual confounding bias due to differences in the distributions of age, sex, and/or race. The comparisons in this study are between ever stationed or ever employed at Camp Lejeune vs stationed or employed at Camp Pendleton but not Camp Lejeune during the periods 1975–1985 for Marines/Navy personnel and October 1972 and December 1985 for civilian workers. In apportioning person-years during the follow-up period to specific age, race, sex, and calendar period categories for each base, once an individual was stationed or employed at Camp Lejeune any quarter between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers) all subsequent person-years were assigned to Camp Lejeune. If the individual was stationed or employed at Camp Pendleton but not Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then person-years at risk were assigned to Camp Pendleton. If the individual was stationed or employed at both bases between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then once the individual was stationed or employed at Camp Lejeune, all subsequent person-years were assigned to Camp Lejeune. For the main analyses, Cox proportional hazards (Cox) regression was used to estimate hazard ratios (HRs) for each underlying cause of death comparing the Camp Lejeune and Camp Pendleton cohorts. Secondary analyses using Cox regression evaluated contributing causes of death. For the analyses of Marines/Navy personnel, the primary focus was on the subgroup comparisons between Camp Lejeune and Camp Pendleton. Secondary analyses evaluated the full cohort of Marines/Navy personnel comparing Camp Lejeune and Camp Pendleton. For civilian workers, the main analyses also focused on comparisons between Camp Lejeune and Camp Pendleton. Age was the time variable in the Cox regressions. If an individual was stationed or employed at both Camp Lejeune and Camp Pendleton between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then once the individual was stationed or employed at Camp Lejeune, all subsequent ages were assigned to Camp Lejeune. Unadjusted models were adjusted for age only. For the analyses of Marines/Navy personnel, the adjusted models included sex, race, rank, and education level. For the analyses of civilian workers, the adjusted models included sex, race, blue collar work (y/n), and education level. Blue collar work included manual jobs such as maintenance workers, mechanics, construction workers, laundry and dry-cleaning workers, pest control workers, and water treatment plant workers. The exposure (i.e., base location at Camp Lejeune) was not lagged in the analyses because more than 75% of the deaths occurred more than 10 years after the contamination ended at Camp Lejeune. Evaluation of Schoenfeld residuals was used to check the proportional hazards assumption. In the previous Camp Lejeune mortality studies, residential cumulative exposure to each contaminant was evaluated based on linking the estimated monthly concentrations in the TT, HP and HB water systems from the historical reconstruction modeling and Camp Lejeune base family housing records and information on the barrack location of each military unit [ 13 – 14 ]. In this study, cumulative residential exposure to each contaminant was not evaluated because drinking water exposures during training and other base activities would likely contribute significantly to overall cumulative exposure. Since information on training and other base activities was not available, the study instead evaluated duration of assignment (Marines/Navy personnel) or duration of employment (civilian workers) at Camp Lejeune as a surrogate for overall cumulative exposure. Cox regression analyses of underlying causes of death using categorical variables for duration were conducted with Camp Pendleton Marines/Navy personnel and civilian workers as the comparison groups. Information on smoking and alcohol consumption was not available. Occupational history prior to or after active-duty service or employment at Camp Lejeune or Camp Pendleton was also unavailable. To assess the possible confounding effects of smoking and alcohol consumption, the study evaluated the results for “negative control” causes of death that are associated with the unmeasured risk factor (i.e., the potential confounder) but were not known to be associated with the exposures of interest, i.e., the drinking water contaminants at Camp Lejeune [ 21 ]. The negative controls were used to estimate prevalence differences in smoking and alcohol consumption between Camp Lejeune and Camp Pendleton. The negative control causes of death for smoking were chronic obstructive pulmonary disease (COPD) and cardiovascular disease, and the negative control causes of death for alcohol consumption were alcoholism, alcoholic liver disease, and chronic liver disease. Lung cancer mortality was not considered a negative control for smoking because of some evidence that PCE exposures in drinking water and occupational PCE exposures, especially among dry cleaning workers, may be associated with the risk of lung cancer [ 22 – 28 ]. Occupational benzene exposure has also been associated with lung cancer in two studies [ 29 – 30 ]. Laryngeal cancer mortality also was not considered a negative control for smoking or for alcohol consumption because of some evidence that PCE and or TCE occupational exposures may be associated with laryngeal cancer [ 31 – 32 ]. Another smoking-related cancer, bladder cancer, has been linked to PCE exposure [ 12 ]. Several alcohol-related cancers, such as cancers of the oral cavity and pharynx, larynx, liver, esophagus, colon, and female breast [ 33 ], were not considered negative controls because there was at least some evidence linking these cancers to one or more of the contaminants in the drinking water [ 12 , 31 – 32 , 34 – 35 ]. Quantitative bias methods were conducted to estimate quantitatively, and adjust the HR estimates for, the systematic errors (or biases) due to unmeasured confounding factors and exposure misclassification. The analyses focused on the dichotomous comparisons between Camp Lejeune and Camp Pendleton, and used Excel spreadsheets included with the textbook, Applying Quantitative Bias Analysis to Epidemiologic Data, Second Edition [ 36 ]. The quantitative bias analyses of the impacts of unmeasured confounding due to smoking and alcohol consumption used the negative control results to estimate the differences in alcohol consumption and smoking between Camp Lejeune Marines/Navy personnel and civilian workers and their counterparts at Camp Pendleton. Quantitative bias analyses of exposure misclassification assumed that the misclassification was non-differential and independent because: (1) the base assignments derived from the unit codes for Marines/Navy personnel were completed prior to vital status and mortality data collection, and (2) the base location of employment for civilian workers was recorded in the DMDC database many years prior to vital status and mortality data collection [ 36 ]. Therefore, base location assignment was not affected by cause of death information. For Camp Lejeune Marines/Navy personnel and civilian workers, the sources of possible exposure misclassification were due to using unit assignment or employment at Camp Lejeune as a proxy for exposure to the drinking water. For Marines/Navy personnel, errors were possible in the historical research conducted by the DMDC and USMC to determine the base where each unit was located. Second, even if the base assignment of the unit was correct, some individuals may not have been exposed to the contaminated drinking water because they were deployed to a different base (e.g., outside the country) or trained at a different base. Third, some individuals stationed at Camp Lejeune may not have been exposed because all their water consumption (including showering and other water uses) occurred off-base (e.g., in off-base housing) or in areas of the base not served by the HP or TT drinking water systems. On the other hand, most of those classified as stationed at Camp Pendleton likely were truly unexposed to the contaminated drinking water. For Camp Lejeune civilian workers, a main source of exposure misclassification was due to water consumption (including showering and other water uses) occurring mostly or entirely off-base (e.g., at their residences). In addition, the workplaces of some of the Camp Lejeune civilian workers may have been located in areas not served by the contaminated drinking water. On the other hand, all civilian workers at Camp Pendleton were assumed to be truly unexposed to contaminated drinking water. To conduct the quantitative bias analyses, it was assumed that the sensitivity of the exposure classification, i.e., the probability that the truly exposed were correctly classified as exposed (i.e., assigned to Camp Lejeune) was near 1.0 because it was highly unlikely that a truly exposed individual would be assigned only to Camp Pendleton. On the other hand, the specificity of the exposure classification, i.e., the probability that the truly unexposed were correctly classified as unexposed (i.e., assigned to Camp Pendleton) was assumed to range from 0.81 to 0.91. The chosen values for sensitivity and specificity used in the quantitative bias analysis reflected the assumptions that between 75% and 90% of those stationed or employed at Camp Lejeune were truly exposed, and all (or virtually all) of those stationed or employed at Camp Pendleton were truly unexposed. Interpretation of study findings was based primarily on the magnitude of the adjusted HR, its precision, and whether a finding was supported by other studies of occupational or drinking water exposures to the chemicals found in the drinking water at Camp Lejeune. Because meta-analyses published in the scientific literature for TCE occupational exposures and kidney cancer, NHL, and liver cancer observed summary risk ratios between 1.20 and 1.40 [ 12 ], the study emphasized HRs ≥ 1.20. An HR of 1.20 implies that the cause of death occurs 1.2 times more often in the Camp Lejeune cohort compared to the Camp Pendleton cohort. For rare causes of death such as male breast cancer, the HRs from the analyses of contributing causes of death were also considered. In addition, for rare causes of death among Marines/Navy personnel, the analyses of underlying and contributing causes in the full cohort were also considered in the interpretation of the findings. The analyses of underlying cause of death and duration at Camp Lejeune provided additional information that was used in the interpretation of the findings. Emphasis was on monotonic trends in the duration. A monotonic trend occurs when every change in the HR with increasing duration is in the same direction (e.g., the HR increases), although the trend could have flat segments but never reverse direction [ 37 ]. The 95% confidence interval ratio (CIR), measured by the quotient of the upper to lower limit, was used to indicate the precision (or degree of random variability) of the effect estimates (i.e., the SMR, RR and HR estimates) [ 38 – 39 ]. The CIR is primarily impacted by the level of the CI (e.g., a 95% CI) and the number of deaths from a specific cause in the cohorts being compared. The smaller the number of deaths, the wider the confidence interval. The study emphasized adjusted HRs ≥ 1.20 with CIRs ≤ 3. However, adjusted HRs ≥ 1.20 with CIRs > 3 should not be considered as lacking importance. Because p-values and statistical significance testing are “commonly misused and misinterpreted” [ 40 ], significance testing was not used to interpret findings [ 37 , 41 ]. Instead, the interpretation is based on: (1) the magnitude of the adjusted HR estimate (i.e., ≥ 1.20), (2) the precision of the estimate (i.e., the 95% CIR), (3) the quantitative impacts of unmeasured potential confounders (e.g., smoking and alcohol consumption) and exposure misclassification on the adjusted HR estimate, and (4) supporting information from the scientific literature on the health effects of TCE, PCE, vinyl chloride, and benzene [ 39 , 41 – 42 ]. Analyses were conducted using SAS 9.4 and STATA 16, and SPSS was used for data management. This study was approved by the Centers for Disease Control and Prevention Institutional Review Board.[1] Results Demographic information for the civilian workers and the subgroup of Marines/Navy personnel is provided in Tables 1 and 2 . Tables providing demographic information and all statistical results for the Camp Pendleton and Camp Lejeune full cohort of Marines/Navy personnel are included in Supplemental file, Tables S1 to S4. The Marines/Navy personnel in the Camp Lejeune and Camp Pendleton subgroup generally appeared similar on sex, rank, age, length of follow-up and the percent of the cohort that died. There appeared to be small differences in attained education level and race. The combined subgroup was mostly male (95.7%), white (75.6%) and ranged in rank from E1 to E4 (81.7%). Of note was that about 2% were above the age of 65 years at the end of follow-up. The average length of follow-up was about 36 years, and the total amount of person-years was 11,839,529. About 12% of the Marines/Navy personnel in the subgroup had died by the end of follow-up. Among the Camp Lejeune and Camp Pendleton civilian workers, the percentages of women were 49.4% and 45.4%, respectively. Most of the Camp Lejeune and Camp Pendleton civilian workers were White. A much higher percentage of the Camp Lejeune workforce was African American (19.2%) compared to Camp Pendleton (7.5%). A higher percentage at Camp Lejeune graduated from college (14.8%) compared to Camp Pendleton (6.9%). Over half of the civilian workers in the study were above 70 years of age at the end of follow-up. The average length of follow-up was about 31 years, and the total amount of person-years was 434,965. About 42% (N = 3,055) of the Camp Lejeune civilian workers and 49% (N = 3,280) of Camp Pendleton civilian workers had died by the end of follow-up. The results of the SMR and Poisson regression analyses for the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup are shown in Table 3 . The SMRs for most of the underlying causes of death, including death from all causes and all cancer malignancies, were less than 1.00, consistent with a “healthy veteran effect” [ 16 – 18 ]. The healthy veteran effect could be due to several factors including the initial physical screening for healthy recruits, physical fitness standards during military service, and access to quality health care during and after service. The healthy veteran effect may have been especially strong in this relatively young subgroup: at the end of follow-up about 98% were less than 65 years of age and about 43% were less than 55 years of age. SMRs above 1.00 at Camp Lejeune were observed for cancers of the esophagus, pancreas, cervix, prostate, kidney, connective tissue, and Parkinson disease, amyotrophic lateral sclerosis (ALS) and suicide. SMRs above 1.00 at Camp Pendleton were observed for cancers of the uterus, male breast, prostate, thyroid, and for alcoholism, ALS, and suicide. Table 3 Standardized mortality ratios (SMR), Poisson regression risk ratios, and 95% confidence intervals (CI) for the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup: Underlying cause of death Cause of Death Camp Lejeune (CL) Camp Pendleton (CP) Risk Ratio (95% CI) Observed SMR (95% CI) Observed SMR (95% CI) CL vs CP All Causes 19,250 0.90 (0.89, 0.91) 21,134 0.93 (0.92, 0.94) 0.99 (0.97, 1.01) All Cancer Malignancies 3,689 0.92 (0.89, 0.95) 3,760 0.87 (0.84, 0.90) 1.07 (1.02, 1.12) Oral Cavity and Pharynx 106 0.85 (0.70, 1.03) 124 0.92 (0.77, 1.10) 0.95 (0.73, 1.23) Esophagus 171 1.01 (0.87, 1.18) 154 0.83 (0.70, 0.97) 1.25 (1.00, 1.55) Stomach 89 0.78 (0.62, 0.95) 100 0.83 (0.68, 1.01) 0.93 (0.70, 1.24) Colon 266 0.87 (0.77, 0.98) 264 0.81 (0.71, 0.91) 1.07 (0.91, 1.27) Rectum 83 0.79 (0.63, 0.98) 94 0.83 (0.67, 1.02) 0.93 (0.69, 1.26) Liver/Biliary System 268 0.84 (0.75, 0.95) 289 0.85 (0.76, 0.96) 1.01 (0.86, 1.20) Pancreas 265 1.06 (0.94, 1.19) 250 0.92 (0.81, 1.04) 1.15 (0.97, 1.37) Larynx 36 0.76 (0.53, 1.06) 39 0.77 (0.55, 1.05) 1.04 (0.66, 1.64) Lung/Trachea/Bronchus 982 0.97 (0.91, 1.03) 915 0.83 (0.78, 0.89) 1.19 (1.08, 1.30) Connective Tissue 53 1.03 (0.77, 1.34) 50 0.90 (0.67, 1.19) 1.17 (0.80, 1.73) Melanoma 105 0.98 (0.80, 1.18) 109 0.89 (0.73, 1.07) 1.09 (0.84, 1.43) Breast Cancer - Female 41 0.92 (0.66, 1.25) 25 0.72 (0.47, 1.07) 1.23 (0.75, 2.03) Breast Cancer - Male 4 0.69 (0.19, 1.75) 11 1.76 (0.88, 3.15) 0.39 (0.12, 1.22) Cervix 9 1.07 (0.49, 2.03) 5 0.79 (0.26, 1.85) 1.21 (0.39, 3.72) Uterus 5 0.91 (0.30, 2.12) 7 1.59 (0.64, 3.28) 0.59 (0.19, 1.88) Ovary 8 0.72 (0.31, 1.42) 6 0.67 (0.24, 1.45) 1.19 (0.41, 3.44) Prostate 95 1.01 (0.81, 1.23) 108 1.06 (0.87, 1.28) 0.94 (0.71, 1.24) Testis 18 0.72 (0.42, 1.15) 12 0.45 (0.23, 0.79) 1.72 (0.83, 3.58) Kidney and Renal Pelvis 139 1.11 (0.93, 1.31) 126 0.91 (0.76, 1.09) 1.21 (0.95, 1.54) Urinary Bladder 61 0.97 (0.74, 1.24) 66 0.94 (0.73, 1.20) 1.02 (0.72, 1.45) Brain and CNS 178 0.91 (0.78, 1.06) 217 1.00 (0.87, 1.15) 0.90 (0.74, 1.10) Thyroid 8 0.78 (0.34, 1.55) 12 1.07 (0.55, 1.88) 0.72 (0.30, 1.77) Hematopoietic Cancers 354 0.83 (0.75, 0.92) 380 0.83 (0.74, 0.91) 1.00 (0.87, 1.16) Hodgkin Lymphoma 30 0.93 (0.63, 1.32) 32 0.91 (0.62, 1.29) 1.00 (0.61, 1.65) NHL 122 0.73 (0.60, 0.87) 151 0.83 (0.70, 0.97) 0.87 (0.68, 1.10) Multiple Myeloma 62 0.99 (0.77, 1.26) 61 0.92 (0.70, 1.18) 1.08 (0.76, 1.54) Leukemias 142 0.87 (0.73, 1.02) 136 0.77 (0.65, 0.91) 1.13 (0.89, 1.43) Diabetes 400 0.71 (0.64, 0.78) 452 0.75 (0.69, 0.83) 0.94 (0.82, 1.08) Alcoholism 242 0.93 (0.81, 1.05) 302 1.07 (0.95, 1.20) 0.88 (0.74, 1.04) Multiple Sclerosis 29 0.78 (0.52, 1.12) 27 0.68 (0.45, 0.99) 1.12 (0.66, 1.89) Parkinson Disease 15 1.47 (0.73, 2.21) 8 0.69 (0.21, 1.17) 2.00 (0.85, 4.73) ALS 64 1.12 (0.85, 1.39) 67 1.05 (0.80, 1.30) 1.05 (0.75, 1.48) Cardiovascular Disease 4,316 0.90 (0.87, 0.93) 4,650 0.91 (0.88, 0.94) 1.00 (0.96, 1.04) COPD 312 0.96 (0.86, 1.07) 320 0.89 (0.79, 0.99) 1.10 (0.94, 1.28) Chronic Liver Disease 614 0.79 (0.73, 0.86) 775 0.91 (0.84, 0.97) 0.88 (0.79, 0.97) Cause of Death Camp Lejeune (CL) Camp Pendleton (CP) Risk Ratio (95% CI) Observed SMR (95% CI) Observed SMR (95% CI) CL vs CP Chronic Kidney Disease 133 0.62 (0.52, 0.74) 139 0.64 (0.54, 0.75) 0.99 (0.78, 1.25) Suicide 1,664 1.21 (1.16, 1.27) 2,002 1.32 (1.27, 1.38) 0.92 (0.86, 0.98) CNS: central nervous system NHL: non-Hodgkin lymphoma ALS: amyotrophic lateral sclerosis COPD: chronic obstructive pulmonary disease SMRs were calculated using the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death. Risk ratios were adjusted for sex, race, and five-year age groups. In the Poisson regression analyses of underlying cause of death comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup, risk ratios (RRs) ≥ 1.20 with CIRs ≤ 3 were observed for cancers of the esophagus (RR = 1.25, 95% CI: 1.00, 1.55), and kidney (RR = 1.21, 95% CI: 0.95, 1.54). Female breast cancer had a RR of 1.23 with CIR ≤ 3 (95% CI: 0.75, 2.03). A few other causes of death with RRs ≥ 1.20 but with CIRs > 3 included cancers of the cervix and testes and Parkinson disease. The results of the SMR and Poisson regression analyses for the Camp Lejeune and Camp Pendleton civilian workers are presented in Table 4 . The SMRs for most of the causes of death, including deaths from all causes and all cancer malignancies, were less than 1.00. These findings indicated the impact of the “healthy worker effect” [ 19 ]. In the Poisson regression analyses comparing Camp Lejeune versus Camp Pendleton civilian workers, RRs ≥ 1.20 with CIRs ≤ 3 were observed for female breast cancer (RR = 1.21, 95% CI: 0.77, 1.89) and chronic kidney disease (RR = 1.77, 95% CI: 1.07, 2.93). A few other causes of death had RRs ≥ 1.20 but with CIRs > 3 and included cancers of the kidney, pharynx, and larynx, and melanoma, Hodgkin lymphoma, and anemias. Table 4 Standardized mortality ratios (SMRs) and Poisson regression risk ratios for the Camp Lejeune and Camp Pendleton civilian workers: Underlying cause of death Cause of Death CL CP Risk Ratio (95% CI) Observed SMR (95% CI) Observed SMR (95% CI) CL vs CP All causes 3,055 0.89 (0.85, 0.92) 3,280 0.90 (0.87, 0.94) 0.96 (0.91, 1.01) All cancers 882 0.93 (0.87, 0.99) 890 0.93 (0.87, 0.99) 1.01 (0.92, 1.12) All malignant cancers 859 0.91 (0.85, 0.98) 874 0.91 (0.85, 0.98) 1.01 (0.91, 1.11) Oral cavity and pharynx 10 0.62 (0.31, 1.10) 10 0.62 (0.31, 1.10) 1.06 (0.43, 2.61) Pharynx 8 0.95 (0.41, 1.88) 4 0.48 (0.13, 1.24) 2.14 (0.61, 7.46) Esophagus 13 0.51 (0.27, 0.88) 24 0.96 (0.61, 1.43) 0.63 (0.31, 1.27) Stomach 21 0.85 (0.53, 1.30) 21 0.87 (0.54, 1.33) 1.00 (0.53, 1.90) Colon 46 0.61 (0.45, 0.82) 55 0.70 (0.53, 0.92) 0.85 (0.56, 1.29) Rectum 13 0.87 (0.46, 1.48) 14 0.92 (0.50, 1.54) 0.95 (0.43, 2.08) Liver/Biliary system 20 0.62 (0.38, 0.96) 29 0.92 (0.62, 1.32) 0.73 (0.40, 1.32) Pancreas 41 0.78 (0.56, 1.06) 63 1.20 (0.92, 1.53) 0.72 (0.48, 1.08) Larynx 8 0.94 (0.41, 1.86) 5 0.59 (0.19, 1.38) 1.36 (0.42, 4.40) Lung 310 1.08 (0.96, 1.20) 281 0.96 (0.85, 1.08) 1.15 (0.97, 1.36) Kidney and renal pelvis 24 1.16 (0.74, 1.73) 15 0.70 (0.39, 1.16) 1.49 (0.76, 2.92) Urinary bladder 18 0.85 (0.50, 1.34) 25 1.06 (0.69, 1.57) 0.65 (0.34, 1.24) Melanoma 12 1.03 (0.53, 1.80) 5 0.41 (0.13, 0.97) 2.59 (0.89, 7.56) Connective tissue 5 0.90 (0.29, 2.11) 6 1.10 (0.40, 2.40) 0.65 (0.19, 2.22) Brain and CNS 17 0.87 (0.50, 1.39) 28 1.44 (0.96, 2.09) 0.66 (0.36, 1.23) Thyroid 1 0 Hematopoietic cancers 84 1.00 (0.80, 1.24) 90 1.02 (0.82, 1.25) 1.00 (0.73, 1.36) Hodgkin lymphoma 3 1.47 (0.30, 4.29) 2 0.98 (0.12, 3.55) 1.81 (0.30, 11.0) NHL 35 1.12 (0.78, 1.56) 38 1.13 (0.80, 1.55) 0.98 (0.61, 1.58) Multiple myeloma 15 0.79 (0.44, 1.30) 13 0.68 (0.36, 1.16) 0.99 (0.45, 2.16) Leukemias 31 0.98 (0.67, 1.39) 37 1.11 (0.78, 1.53) 1.00 (0.61, 1.64) Breast cancer - Female 48 0.84 (0.62, 1.12) 33 0.63 (0.44, 0.89) 1.21 (0.77, 1.89) Breast cancer - Male 0 0 Cervix 1 3 0.55 (0.11, 1.60) Uterus 10 1.01 (0.49, 1.87) 9 1.00 (0.46, 1.90) 0.97 (0.39, 2.43) Ovary 14 0.75 (0.41, 1.26) 22 1.28 (0.80, 1.94) 0.57 (0.29, 1.13) Prostate 71 0.99 (0.78, 1.25) 59 0.80 (0.61, 1.04) 1.01 (0.69, 1.50) Testis 0 0 Diabetes 94 0.90 (0.72, 1.10) 103 0.98 (0.80, 1.19) 0.78 (0.58, 1.05) Alcoholism 7 0.56 (0.23, 1.16) 10 0.87 (0.42, 1.61) 0.63 (0.23, 1.74) Multiple sclerosis 3 0.63 (0.13, 1.85) 3 0.73 (0.15, 2.12) 0.70 (0.14, 3.52) Parkinson disease 30 1.34 (0.86, 1.82) 31 1.19 (0.77, 1.60) 1.15 (0.68, 1.93) ALS 5 0.57 (0.07, 1.07) 10 1.12 (0.43, 1.82) 0.44 (0.14, 1.32) Anemias 7 1.20 (0.48, 2.47) 3 0.48 (0.10, 1.41) 1.61 (0.39, 6.61) Cause of Death CL CP Risk Ratio (95% CI) Observed SMR (95% CI) Observed SMR (95% CI) CL vs CP Heart/Circulatory disease 1105 0.88 (0.83, 0.93) 1271 0.93 (0.88, 0.98) 0.92 (0.85, 1.00) COPD 171 0.99 (0.85, 1.15) 213 1.13 (0.99, 1.30) 0.91 (0.73, 1.11) Chronic liver disease 36 0.70 (0.49, 0.97) 51 1.04 (0.77, 1.36) 0.71 (0.46, 1.10) Chronic kidney disease 49 0.84 (0.62, 1.11) 26 0.43 (0.28, 0.63) 1.77 (1.07, 2.93) Suicide 29 0.84 (0.56, 1.21) 45 1.36 (0.99, 1.82) 0.68 (0.42, 1.10) CL: Camp Lejeune CP: Camp Pendleton SMR: Standardized mortality ratio CI: Confidence interval CNS: Central nervous system cancers NHL: Non-Hodgkin lymphoma ALS: Amyotrophic Lateral Sclerosis COPD: Chronic obstructive pulmonary disease SMRs were calculated using the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death. Risk ratios were adjusted for sex, race, and five-year age groups. The unadjusted and adjusted HRs for underlying cause of death from the Cox proportional hazards regressions comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup are shown in Table 5 . The adjusted HR for all cancer malignancies was 1.05 (95% CI: 1.02, 1.08). Adjusted HRs ≥ 1.20 with CIRs ≤ 3 were observed for cancers of the kidney (HR = 1.21, 95% CI: 0.95, 1.54), esophagus (HR = 1.24, 95% CI: 1.00, 1.54), and female breast cancer (HR = 1.20, 95% CI: 0.73, 1.98). HRs ≥ 1.20 with CIRs > 3 included Parkinson disease, myelodysplastic syndrome, and cancers of the testes, cervix, and ovary. Table 5 Hazard ratios (HR) and 95% confidence intervals (CI) for the Marines/Navy personnel subgroup analysis of base location at Camp Lejeune (CL) vs. Camp Pendleton (CP); Underlying cause of death Outcome Total Camp Lejeune # Unadjusted HR (95% CI) Adjusted HR (95% CI) Camp Pendleton # All causes 40,384 19,250 0.98(0.96, 1.00) 0.99(0.97, 1.01) 21,134 All cancer malignancies 7,449 3,689 1.06(1.01, 1.11) 1.06(1.02, 1.11) 3,760 Oral cancers 230 106 0.92(0.71, 1.19) 0.95(0.73, 1.24) 124 Pharyngeal cancer 121 56 0.93(0.65, 1.33) 0.94(0.66, 1.35) 65 Esophageal cancer 325 171 1.20(0.97, 1.49) 1.24 (1.00, 1.54) 154 Stomach cancers 189 89 0.96(0.72, 1.28) 0.92(0.69, 1.23) 100 Colorectal cancers 707 349 1.05(0.91, 1.22) 1.03(0.88, 1.19) 358 Colon cancer 530 266 1.09(0.92, 1.29) 1.05(0.89, 1.25) 264 Rectal cancer 177 83 0.95(0.71, 1.27) 0.94(0.70, 1.27) 94 Liver cancer 557 268 1.00(0.85, 1.19) 1.06(0.89, 1.25) 289 Pancreatic cancer 515 265 1.14(0.96, 1.36) 1.14(0.96, 1.36) 250 Laryngeal cancer 75 36 1.00(0.64, 1.57) 1.01(0.64, 1.58) 39 Lung cancer 1,897 982 1.16(1.06, 1.27) 1.18(1.07, 1.29) 915 Bone cancers 40 16 0.71(0.38, 1.34) 0.74(0.39, 1.39) 24 Soft tissue cancers 103 53 1.14(0.77, 1.67) 1.12(0.76, 1.65) 50 Melanoma 214 105 1.03(0.79, 1.35) 1.07(0.82, 1.40) 109 Female Breast cancer 66 41 1.27(0.77, 2.08) 1.20 (0.73, 1.98) 25 Male Breast cancer 15 4 0.39(0.13, 1.24) 0.36 (0.12, 1.14) 11 Cervical cancer 14 9 1.19(0.39, 3.65) 1.25 (0.40, 3.85) 5 Uterine cancer 12 5 0.62(0.20, 1.97) 0.62 (0.20, 1.98) 7 Ovarian cancer 14 8 1.12(0.39, 3.24) 1.23 (0.42, 3.59) 6 Prostate cancer 203 95 0.97(0.74, 1.28) 0.93 (0.71, 1.23) 108 Testicular cancer 30 18 1.62(0.78, 3.36) 1.76 (0.85, 3.67) 12 Bladder cancer 127 61 1.00(0.71, 1.42) 1.02(0.72, 1.45) 66 Kidney cancer 265 139 1.19(0.93, 1.51) 1.21(0.95, 1.54) 126 Brain and CNS cancers 395 178 0.88(0.72, 1.07) 0.89(0.73, 1.09) 217 Thyroid cancer 20 8 0.71(0.29, 1.74) 0.71(0.29, 1.74) 12 Hematopoietic cancers 734 354 1.00(0.86, 1.16) 0.99(0.86, 1.14) 380 Hodgkin lymphoma 62 30 1.00(0.61, 1.64) 0.98(0.59, 1.61) 32 Non-Hodgkin lymphoma 273 122 0.87(0.68, 1.10) 0.87(0.68, 1.10) 151 Multiple myeloma 123 62 1.10(0.77, 1.56) 1.07(0.75, 1.53) 61 Leukemias 278 142 1.12(0.89, 1.42) 1.10(0.87, 1.40) 136 ALL 45 20 0.85(0.47, 1.53) 0.85(0.47, 1.53) 25 CLL 15 7 0.94(0.34, 2.59) 0.89(0.32, 2.48) 8 AML 122 62 1.12(0.78, 1.59) 1.11(0.78, 1.59) 60 CML 28 11 0.69(0.32, 1.47) 0.65(0.30, 1.40) 17 MDS 17 11 1.96(0.73, 5.30) 2.26(0.83, 6.17) 6 Outcome Total Camp Lejeune # Unadjusted HR (95%CI) Adjusted HR (95% CI) Camp Pendleton # Lymphoid cancers 63 27 0.82(0.50, 1.35) 0.80(0.49, 1.33) 36 Myeloid cancers 157 79 1.12(0.82, 1.53) 1.10(0.80, 1.50) 78 Diabetes 852 400 0.96(0.84, 1.10) 0.96(0.83, 1.09) 452 Anemias 25 12 1.00(0.46, 2.19) 0.89(0.41, 1.97) 13 Cardiovascular disease 8,966 4,316 1.00(0.96, 1.04) 0.99(0.95, 1.03) 4,650 Heart disease 7,331 3,512 0.99(0.95, 1.04) 0.99(0.94, 1.03) 3,819 Stroke 861 432 1.08(0.95, 1.24) 1.05(0.92, 1.20) 429 Circulatory diseases 773 371 0.99(0.86, 1.14) 0.95(0.82, 1.09) 402 COPD 632 312 1.06(0.91, 1.24) 1.08(0.93, 1.27) 320 Chronic Liver disease 1,389 614 0.85(0.77, 0.95) 0.93(0.83, 1.03) 775 Cirrhosis 1,560 693 0.86(0.78, 0.95) 0.93(0.84, 1.03) 867 Alcoholic Liver disease 901 381 0.79(0.69, 0.90) 0.86(0.76, 0.99) 520 Nonalcoholic Liver disease 488 233 0.98(0.82, 1.17) 1.06(0.89, 1.27) 255 Acute Kidney disease 42 18 0.81(0.44, 1.50) 0.81(0.44, 1.50) 24 Chronic Kidney disease 272 133 1.03(0.82, 1.31) 0.96(0.75, 1.22) 139 Parkinson disease 23 15 2.09(0.89, 4.94) 2.05(0.86, 4.87) 8 ALS 131 64 1.03(0.73, 1.45) 1.04(0.73, 1.46) 67 Multiple sclerosis 56 29 1.18(0.70, 1.99) 1.18(0.70, 2.00) 27 Alcoholism 544 242 0.86(0.72, 1.02) 0.90(0.76, 1.07) 302 Suicide 3,666 1,664 0.88(0.83, 0.94) 0.93(0.87, 0.99) 2,002 CL = 159,128 Males = 151,026 Females = 8,102 CP = 168,406 Males = 162,473 Females = 5,933 Total = 327,534 Males = 313,499 Females = 14,035 COPD: chronic obstructive pulmonary disease ALS: amyotrophic lateral sclerosis MDS: myelodysplastic syndrome CML: chronic myeloid leukemia AML: acute myeloid leukemia CLL: chronic lymphocytic leukemia ALL: acute lymphocytic leukema CNS: central nervous system HRs adjusted for sex, race, rank and education level; age was the time variable. In the analyses of the full cohort of Marines/Navy personnel, in addition to causes listed above, additional underlying causes of death with adjusted HRs ≥ 1.20 and CIRs ≤ 3 included acute myeloid leukemia (HR = 1.21, 95% CI: 0.94, 1.56), Hodgkin lymphoma (HR = 1.25, 95% CI: 0.82, 1.90), multiple sclerosis (HR = 1.37, 95% CI: 0.92, 2.06) and acute kidney disease (HR = 1.32, 95% CI: 0.91, 1.90) (Supplemental file, Table S3). Evaluation of contributing causes of death in the Marines/Navy personnel subgroup, comparing Camp Lejeune with Camp Pendleton, is presented in (Supplemental file, Table S5).. The findings were generally similar to the subgroup analyses of underlying causes from Table 5 , with no additional causes of death having HRs ≥ 1.20 and CIRs ≤ 3 except for multiple sclerosis (HR = 1.29, 95% CI: 0.83, 2.01). Evaluation of contributing causes of death in the full cohort of Marines/Navy personnel observed an HR for male breast cancer of 1.27 but with CIR > 3 (95% CI: 0.61, 2.64) (Supplemental file, Table S4). Analysis of the Marines/Navy personnel subgroup, for underlying cause of death and duration stationed between 1975 and 1985 at Camp Lejeune compared with Camp Pendleton as the reference group is presented in (Supplemental file, Table S6). The categorical levels of duration were approximately tertiles of the data after removal of the reference group. Since the DMDC data is quarterly, the levels of the categorical variable consisted of the number of quarters the individual was stationed at Camp Lejeune: “low” duration (1–2 quarters), “medium” duration (> 2–7 quarters), and “high” duration (> 7 quarters). A monotonic trend was observed for myelodysplastic syndrome, with the adjusted HR ranging from 1.77 (95% CI: 0.44, 7.11) in the low duration to 3.11 (95% CI: 0.86, 11.20) in the high duration strata. CIRs at all durations were > 3. Other underlying causes of death with monotonic trends were non-alcoholic liver disease (low duration HR = 1.03, 95% CI: 0.79, 1.34); high duration HR = 1.18, 95% CI: 0.81, 1.52) and pancreatic cancer (low duration HR = 1.11, 95% CI: 0.86, 1.43; high duration HR = 1.15, 95% CI: 1.01, 1.30), both with CIRs ≤ 3. The unadjusted and adjusted HRs from the Cox proportional hazards regressions for underlying cause of death comparing the Camp Lejeune versus Camp Pendleton civilian workers are shown in Table 6 . Adjusted HRs ≥ 1.20 with CIRs ≤ 3 were observed for chronic kidney disease (HR = 1.88, 95% CI: 1.13, 3.11) and Parkinson disease (HR = 1.21, 95% CI: 0.72, 2.04). An HR of 1.19 was observed for female breast cancer (95% CI: 0.76, 1.88). Other underlying causes of death with HRs ≥ 1.20 but with CIRs > 3 included cancers of the kidney and pharynx, melanoma, Hodgkin lymphoma, chronic myeloid leukemia (CML), and anemias. Table 6 Comparison of Camp Lejeune (CL) and Camp Pendleton (CP) civilian workers: Underlying cause of death Outcome Total Camp Lejeune # Unadjusted HR (95% CI) Adjusted HR (95% CI) Camp Pendleton # All causes 6,335 3,055 0.96 (0.91, 1.01) 0.96(0.91, 1.01) 3,280 All cancers 1,772 882 0.99(0.91, 1.09) 1.00(0.91, 1.11) 890 All malignancies 1,733 859 0.98(0.90, 1.08) 1.00(0.91, 1.10) 874 Oral cancers 20 10 1.00(0.42, 2.41) 1.03(0.41, 2.58) 10 Pharynx 12 8 2.02(0.61, 6.71) 2.21(0.63, 7.78) 4 Esophagus 37 13 0.54(0.28, 1.07) 0.63(0.31, 1.28) 24 Stomach 42 21 0.98(0.53, 1.79) 0.92(0.48, 1.76) 21 Colorectal cancers 126 58 0.86(0.61, 1.23) 0.86(0.59, 1.24) 68 Colon 101 46 0.85(0.57, 1.26) 0.85(0.56, 1.28) 55 Rectum and Rectosigmoid junction 27 13 0.93(0.43, 1.97) 0.95(0.43, 2.09) 14 Rectum only 17 8 0.87(0.34, 2.27) 0.84(0.31, 2.27) 9 Liver, biliary, gall bladder 49 20 0.71(0.40, 1.25) 0.77(0.43, 1.39) 29 Liver and bile ducts 38 16 0.75(0.39, 1.43) 0.80(0.41, 1.57) 22 Primary liver 15 6 0.68(0.24, 1.92) 0.87(0.31, 2.48) 9 Pancreas 104 41 0.64(0.43, 0.95) 0.71(0.47, 1.06) 63 Larynx 13 8 1.52(0.50, 4.67) 1.19(0.37, 3.83) 5 Lung 591 310 1.10(0.94, 1.30) 1.13(0.96, 1.34) 281 Urinary bladder 43 18 0.78(0.43, 1.43) 0.65(0.34, 1.26) 25 Kidney 39 24 1.56(0.82, 2.98) 1.44(0.73, 2.84) 15 Brain and CNS 45 17 0.58(0.32, 1.07) 0.61(0.33, 1.13) 28 Connective tissue 11 5 0.81(0.25, 2.65) 0.60(0.17, 2.14) 6 Melanoma 17 12 2.42(0.85, 6.89) 3.03(1.05, 8.76) 5 Hematopoietic cancers 174 84 0.95(0.70, 1.28) 1.00(0.73, 1.36) 90 Lymphoid cancers 17 6 0.57(0.21, 1.53) 0.84(0.30, 2.34) 11 Myeloid cancers 40 19 0.89(0.48, 1.66) 0.98(0.51, 1.88) 21 Hodgkin lymphoma 5 3 1.48(0.25, 8.86) 1.65(0.27, 9.96) 2 Non-Hodgkin lymphoma 73 35 0.97(0.61, 1.53) 0.95(0.59, 1.54) 38 Multiple myeloma 28 15 1.11(0.53, 2.33) 1.02 (0.47, 2.24) 13 Leukemias 68 31 0.85(0.53, 1.37) 1.00(0.61, 1.64) 37 CLL 13 5 0.68(0.22. 2.09) 0.85(0.27, 2.63) 8 AML 31 15 0.93(0.46, 1.88) 0.97(0.47, 2.02) 16 CML 8 4 0.99(0.25, 3.96) 1.26(0.29, 5.48) 4 Female Breast 81 48 1.24 (0.79, 1.93) 1.19 (0.76, 1.88) 33 Uterus 19 10 1.00 (0.41, 2.48) 0.99 (0.39, 2.49) 9 Ovary 36 14 0.58 (0.29, 1.13) 0.60 (0.30, 1.19) 22 Prostate 130 71 1.32 (0.93, 1.86) 1.03 (0.71, 1.51) 59 Diabetes 197 94 0.94(0.71, 1.24) 0.81(0.60, 1.10) 103 Cardiovascular disease 2,377 1,105 0.91(0.84, 0.99) 0.91(0.83, 0.99) 1,272 Outcome Total Camp Lejeune # Unadjusted HR (95% CI) Adjusted HR (95% CI) Camp Pendleton # Anemias 10 7 2.38(0.61, 9.24) 1.91(0.48, 7.65) 3 Chronic liver disease 87 36 0.64(0.42, 0.98) 0.74(0.48, 1.15) 51 Alcoholic liver disease 49 16 0.43(0.24, 0.78) 0.54(0.29, 1.00) 33 Nonalcoholic liver disease 36 19 1.04(0.54, 2.01) 1.11(0.57, 2.17) 17 Alcoholism 17 7 0.63(0.24, 1.65) 0.67(0.24, 1.83) 10 Chronic kidney disease 75 49 2.04(1.27, 3.29) 1.88(1.13, 3.11) 26 COPD 384 171 0.86(0.70, 1.05) 0.91(0.74, 1.12) 213 Multiple sclerosis 6 3 0.97(0.19, 4.80) 0.83(0.16, 4.25) 3 Amyotrophic Lateral Sclerosis 15 5 0.50(0.17, 1.47) 0.44(0.15, 1.34) 10 Parkinson disease 61 30 1.09(0.66, 1.80) 1.21(0.72, 2.04) 31 Suicide 74 29 0.59(0.37, 0.94) 0.72(0.45, 1.16) 45 HR: hazard ratio CI: confidence interval CNS: Central nervous system cancers CLL: Chronic lymphcytic leukemia AML: Acute myeloid leukemia CML: Chronic myeloid leukemia COPD: Chronic obstructive pulmonary disease Totals: Camp Lejeune = 7,332 Females = 3,624 Males = 3,708 Camp Pendleton = 6,677 Females = 3,031 Males = 3,646 Causes of death that were not evaluated because the number of cases were < 2 for CL and/or CP: Testicular cancer Male breast cancer Thyroid cancer Acute lymphocytic leukemia HRs adjusted for sex, race, blue collar work (y/n) and education level; age was the time variable. The unadjusted and adjusted HRs from the Cox proportional hazards regressions for contributing causes of death comparing the Camp Lejeune versus Camp Pendleton civilian workers are shown in Supplemental file, Table S7). An adjusted HR ≥ 1.20 with CIR ≤ 3 was observed for female breast cancer (HR = 1.33, 95% CI: 0.87, 2.03). Other contributing causes of death with adjusted HRs ≥ 1.20 but with CIRs > 3 included cancers of the pharynx and larynx, melanoma, Hodgkin lymphoma, and CML. Analysis of underlying causes of death and duration of employment at Camp Lejeune between October 1972 and December 1985 with Camp Pendleton as the referent group is shown in Supplemental file, Table S8. The categorical levels of duration were approximately tertiles of the data after removal of the reference group. Since the DMDC data is quarterly, the levels of the categorical variable consisted of the number of quarters the worker was employed at Camp Lejeune: “low” duration (1–5 quarters), “medium” duration (6–22 quarters), and “high” duration (≥ 23 quarters). A monotonic trend was observed for kidney cancer, with low duration HR of 1.36 (95% CI: 0.48, 3.82) and high duration HR of 1.68 (95% CI: 0.75, 3.76) and CIR > 3 across all durations. The negative control diseases for alcohol consumption were alcoholism, alcoholic liver disease and chronic liver diseases. The negative control diseases for smoking were COPD and cardiovascular disease. In the analyses of underlying and contributing causes of death comparing Camp Lejeune and Camp Pendleton Marines/Navy personnel in the subgroup (Table 5 ; Supplemental file, Table S5), COPD as an underlying cause had an HR of 1.08 (95% CI: 0.93, 1.27) and CIR ≤ 3. All other negative control diseases for smoking and alcohol consumption had HRs < 1.00. In the analyses of underlying and contributing causes of death comparing Camp Lejeune and Camp Pendleton civilian workers (Table 6 ; Supplemental file, Table S7 ), COPD as a contributing cause had an HR of 1.04 (95% CI: 0.91, 1.20) and CIR ≤ 3. All other negative control diseases for smoking and alcohol consumption had HRs < 1.00. The findings for the negative control diseases for alcohol consumption and smoking suggest that the prevalence of smoking and alcohol consumption were not greater at Camp Lejeune compared to Camp Pendleton. Even though the HRs for COPD were slightly greater than 1.00 for the Marines/Navy personnel and civilian workers, the cardiovascular disease HRs were < 1.00. Moreover, the HRs for all the negative control diseases for alcohol consumption were < 1.00. To evaluate the impact of possible confounding due to smoking and alcohol consumption, quantitative bias analyses were conducted using the results for COPD (smoking) and chronic liver disease (alcohol use). To fully explain the HR for COPD of 1.08, the difference in smoking prevalence between Camp Lejeune and Camp Pendleton Marines/Navy personnel would be about 6%, assuming a range of RRs between 3.00 and 5.50 for smoking and COPD mortality [ 43 ] (Supplemental file, Figure S1 ). (Assuming a higher RR for smoking and COPD would decrease the difference in smoking prevalence between Camp Lejeune and Camp Pendleton and would therefore reduce the potential impact of confounding due to smoking in this study.) Assuming a 6% difference in smoking prevalence and a range of RRs for smoking and kidney cancer between 1.25 and 1.75 [ 44 ], the observed adjusted HR for kidney cancer of 1.21 would be reduced to between 1.17 and 1.18, a change of about 3.3% (Supplemental file, Figure S2). Assuming a range of RRs for smoking and esophageal cancer between 1.5 and 3.5 [ 44 – 45 ], the observed adjusted HR of 1.24 would be reduced to between 1.17 and 1.21, a change of no more than 5.6% (Supplemental file, Figure S3). Smoking has been observed to decrease the risk of Parkinson disease [ 46 ]. Adjusting for smoking, the observed adjusted HR of 2.05 would increase to between 2.07 and 2.12, a change of no more than 3.4% (Supplemental file, Figure S4). Finally, since smoking is a strong risk factor for lung cancer, the impact of adjusting for smoking on the observed adjusted HR for lung cancer should be the greatest. Assuming a 6% prevalence difference in smoking and assuming that the RR for smoking and lung cancer ranges between 7.00 and 12.00 [ 44 ], the observed adjusted HR of 1.18 for lung cancer as an underlying cause would be reduced to between 1.07 and 1.08, a change of no more than 9.3% (Supplemental file, Figure S5). For smoking to fully explain the HR for COPD of 1.04, the difference in smoking prevalence between the Camp Lejeune and Camp Pendleton civilian workers would be no more than 3% (Supplemental file, Figure S6). Adjusting for a smoking prevalence difference of 3% and assuming RRs for smoking and cancers of the lung and larynx ranging between 7.00 and 12.00 [ 44 ], the underlying cause HRs of 1.13 for lung cancer and 1.19 for laryngeal cancer would decrease no more than about 5.3% (Supplemental file, Figures S7 to S8). The HR for laryngeal cancer as a contributing cause of 1.69 would also decrease by no more than 5.3% (Supplemental file, Figure S9). The adjusted HR for cancer of the pharynx as an underlying cause would decrease from 2.21 to 2.10, assuming the RR for smoking and cancer of the pharynx ranges from 5.0 to 7.5 [ 44 ] (Supplemental file, Figure S10). Assuming RRs for smoking and kidney cancer and chronic kidney disease ranging from 1.30 to 1.80 [ 44 , 47 ], the underlying cause HRs of 1.44 for kidney cancer and 1.88 chronic kidney disease would decrease by no more than about 2% (Supplemental file, Figures S11 to S12). Adjusting for smoking and assuming RRs for smoking and Parkinson disease ranging between 0.40 and 0.90, the underlying cause HR for Parkinson disease of 1.21 would increase by no more than 2.5% (Supplemental file, Figure S13). For the subgroup of Marines/Navy personnel, the adjusted HRs for chronic liver disease mortality as an underlying and contributing cause were 0.93 and 0.88, respectively. A recent systematic review of alcohol consumption and mortality due to liver cirrhosis found RRs of 2.65, 6.83 and 16.38 for drinking 25g/day (2 drinks/day), 50g/day (4 drinks/day) and 100g/day (8 drinks/day) compared to those who never drank alcoholic beverages [ 48 ]. A military survey conducted in 1980 found that about 30% of Marines were heavy drinkers defined as drinking five or more drinks per typical drinking occasion at least once a week in the past 30 days. [ 49 ]. To determine what prevalence differences in alcohol consumption between Camp Lejeune and Camp Pendleton Marines/Navy personnel would be necessary to fully explain the chronic liver disease mortality HRs of 0.93 and 0.88, a quantitative bias analysis was conducted assuming that at least 2/3 of Marines/Navy personnel at Camp Lejeune consumed ≥ 1 drink/day. It was also assumed that the RRs for alcohol consumption and chronic liver disease mortality ranged between 2.5 and 10 [ 48 ]. To fully explain the RRs of 0.93 and 0.88, the prevalence differences would range between 6% and 10% and between 11% and 16%, respectively (Supplemental file, Figures S14 to S15). (Assuming a lower percentage of Camp Lejeune drinkers would decrease the prevalence difference range, e.g., if only half the Marines/Navy personnel at Camp Lejeune were drinkers, then the percentage difference ranges would be 5% − 9% and 9% -15% for chronic liver disease mortality as underlying cause and as contributing cause, respectively.) Adjusting for an alcohol prevalence difference of 10% between Camp Lejeune and Camp Pendleton Marines/Navy personnel, and assuming RRs for alcohol consumption and esophageal cancer ranging from 1.25 to 5.25 [ 50 , 51 ], the HR of 1.24 for esophageal cancer as an underlying cause would increase to between 1.27 and 1.38 (Supplemental file, Figure S16). The HR of 1.14 for laryngeal cancer as a contributing cause would increase to between 1.15 and 1.23 (Supplemental file, Figure S17). The female breast cancer HR of 1.20 as an underlying cause would increase to between 1.21 and 1.26 (Supplemental file, Figure S18). For the civilian workers, the adjusted HR for chronic liver disease mortality as an underlying cause was 0.74. To fully explain this HR, the prevalence difference in alcohol consumption between Camp Lejeune and Camp Pendleton workers would range between 15% and 25%, assuming that about 1/3 of the Camp Lejeune workers consumed ≥ 1 drink/day and assuming that the range of RRs for alcohol consumption and chronic liver disease mortality range between 2.5 and 10 (Supplemental file, Figure S19). (Assuming that only 20% of Camp Lejeune workers consumed ≥ 1 drink/day, the prevalence difference would range from 11–21%. Assuming a higher percentage of Camp Lejeune drinkers would increase the prevalence difference range, e.g., if 50% of Camp Lejeune workers consumed ≥ 1 drink/day, the prevalence difference would range from 21–31%.) Adjusting for an alcohol prevalence difference of 15% between Camp Lejeune and Camp Pendleton workers, the HR of 1.12 for oral cancers as a contributing cause would increase to between 1.13 and 1.41; the HR of 1.19 for laryngeal cancer as an underlying cause would increase to between 1.20 and 1.40; the HR of 2.21 for pharyngeal cancer as an underlying cause would increase to between 2.24 and 2.79; and the HR of 1.19 for female breast cancer as an underlying cause would increase to between 1.20 and 1.27 (Supplemental file, Figures S20-S23). The impact of non-differential exposure misclassification on the adjusted HRs for the Marines/Navy personnel and civilian workers assumed that between 10% and 25% of those assigned to Camp Lejeune were truly unexposed and virtually none of those assigned to Camp Pendleton were truly exposed (Supplemental file, Tables S9-S10). For underlying cause of death in the Marines/Navy personnel subgroup, after accounting for exposure misclassification the observed adjusted HR for kidney cancer of 1.21 would increase to between 1.23 and 1.27, a change of no more than 5% (Supplemental file, Table S9). For esophageal cancer, the observed adjusted HR of 1.24 would increase to between 1.27 and 1.32, a change of no more than 6.5%. For Parkinson disease, the observed adjusted HR of 2.05 would increase to between 2.17 and 2.40, a change of no more than 17%. For lung cancer, the observed adjusted HR of 1.18 would increase to between 1.20 and 1.23, a change of no more than 4.2%. For civilian workers, adjusting for non-differential exposure misclassification would increase the underlying cause HRs for lung cancer and female breast cancer by no more than about 3% (Supplemental file, Table S10). However, the underlying cause HR for kidney cancer would increase between 6.3% and 12.5%, and the underlying cause HR for chronic kidney disease would increase between 4.8% and 13.3%. The underlying cause HR for Parkinson disease would increase between 2.5% and 5% and the contributing cause HR for female breast cancer would increase between 2.3% and 6%. Discussion This cohort study evaluated whether Marines/Navy personnel and civilian workers stationed or employed at Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), a portion of the period when the drinking water was contaminated, had increased risks for specific causes of death during the follow-up period between 1979 and 2018. The focus of the study was on the Cox regression analysis of underlying cause of death occurring among civilian workers and the Marines/Navy personnel subgroup, comparing Camp Lejeune versus Camp Pendleton. Secondary analyses evaluated (1) duration stationed or employed at Camp Lejeune, (2) contributory causes of death, and (3) underlying and contributing causes of death in the full cohort of Marines/Navy personnel. The possible impact of unmeasured confounders and non-differential exposure misclassification bias on the HRs for underlying cause of death were evaluated. The analyses of Marines/Navy personnel focused on the subgroup because the full cohort was more likely than the subgroup to be impacted by non-differential exposure misclassification bias due to the lack of information on an individual’s base location prior to 1975. However, the analysis of the full cohort had the advantage of greater numbers of individuals and therefore more deaths, as well as being much older than the individuals in the subgroup. In the full cohort, nearly 12% were above the age of 65 at the end of follow-up compared to less than 2% in the subgroup. Therefore, for those rare causes of death primarily occurring among older populations, the full cohort analyses might have provided more useful information than the subgroup analyses. However, over a quarter of the individuals in the full cohort were 55 years of age or younger, and nearly 90% were 65 years of age or younger, indicating that the full cohort represents a relatively young population for evaluating mortality. In the Marines/Navy personnel subgroup analysis of underlying cause of death comparing Camp Lejeune versus Camp Pendleton, adjusted HRs ≥ 1.20 with CIRs ≤ 3 were observed for cancers of the kidney, esophagus, and female breast. HRs ≥ 1.20 but with CIRs > 3 included Parkinson disease, myelodysplastic syndrome, and cancers of the testes, cervix, and ovary. In the analyses of the full cohort of Marines/Navy personnel, additional underlying causes of death with adjusted HRs ≥ 1.20 and CIRs ≤ 3 included acute myeloid leukemia, Hodgkin lymphoma, multiple sclerosis, and acute kidney disease. Male breast cancer had an adjusted HR ≥ 1.20 but with CIR > 3 in the analysis of contributory causes of death in the full cohort analysis. In the analysis of civilian workers comparing Camp Lejeune versus Camp Pendleton, HRs ≥ 1.20 with CIRs ≤ 3 were observed for chronic kidney disease and Parkinson disease as underlying causes and female breast cancer as a contributing cause. Other underlying causes with HRs ≥ 1.20 but with CIRs > 3 due to small number of cases included cancers of the kidney and pharynx, melanoma, Hodgkin lymphoma, CML and anemias. Laryngeal cancer had a RR ≥ 1.20 in the Poisson regression analysis of underlying causes and a HR ≥ 1.20 as a contributing cause, but CIRs for these estimates were > 3. The analysis of duration at Camp Lejeune assumed that contamination levels did not fluctuate greatly each month. However, the estimated monthly average contaminant levels for TCE and PCE in the HP distribution system, and for PCE in the TT distribution system varied widely between 1972 and 1985. Therefore, the results of the duration analysis should be interpreted with caution. In the Marines/Navy personnel subgroup analysis of duration at Camp Lejeune with Camp Pendleton as the reference group, a monotonic trend was observed for myelodysplastic syndrome, with a HR ≥ 1.20 in the high duration stratum and CIR > 3. Other causes of death with monotonic trends but with HRs < 1.20 in the high duration stratum were non-alcoholic liver disease and pancreatic cancer. In the analysis of civilian workers’ duration of employment at Camp Lejeune, a monotonic trend was observed for kidney cancer with an HR ≥ 1.20 in the high duration category but with CIR > 3. HRs ≥ 1.20 were observed for cancers of the kidney and female breast and for Parkinson disease in the analyses of Marines/Navy personnel and civilian workers. HRs ≥ 1.20 were also observed for kidney cancer in the previous mortality studies of Marines/Navy personnel and civilian workers [ 13 – 14 ]. TCE exposure is a known cause of kidney cancer [ 5 ]. Some occupational studies of female breast cancer incidence and mortality have not supported a causal association with exposures to TCE, PCE, vinyl chloride, or benzene [ 12 ]. However, one case-control study found an increased risk of female breast cancer among pre-menopausal women who predominantly worked in dry cleaning [ 52 ]. Exposure to PCE-contaminated drinking water at Cape Cod, MA found an increased risk for breast cancer among women with the highest cumulative exposures [ 34 ]. Two recently published occupational studies of female breast cancer provide support for a causal association with TCE and/or PCE exposure [ 35 , 53 ]. A study in Taiwan found elevated risks for female breast cancer among workers exposed to TCE/PCE and benzene [ 35 ]. A case-control study of postmenopausal women found increased odds ratios for occupationally ever exposed to benzene and PCE and postmenopausal breast cancer ranging between 1.18 and 1.32 and between 1.92 and 2.83, respectively but with CIRs > 3 [ 53 ]. The current evidence for a causal association between TCE exposure and Parkinson disease is at least as likely as not or greater [ 12 , 54 – 55 ]. Animal studies support a causal association between TCE and Parkinson disease, showing that TCE exposure reproduces key pathological features of the disease including “…mitochondrial impairment, intraneuronal aggregation of phosphorylated α-synuclein protein, and regionally specific degeneration of nigrostriatal dopaminergic neurons.” [ 55 ]. An increased risk of Parkinson disease was also observed in the previous mortality study of civilian workers but could not be evaluated in the previous mortality study of Marines/Navy personnel due to a lack of cases [ 13 – 14 ]. HRs ≥ 1.20 were observed for cancers of the esophagus and cervix in the previous mortality studies of Marines/Navy personnel at Camp Lejeune [ 13 ]. In this study, the HR for esophageal cancer in Marines/Navy personnel was 1.24 with CIR ≤ 3 (95% CI: 1.00, 1.54), and for cervical cancer the HR was 1.25 with CIR > 3 (95% CI: 0.40, 3.85). The current evidence for causal associations between esophageal and cervical cancers and TCE, PCE, vinyl chloride or benzene exposures is not strong [ 5 , 7 – 8 , 12 ]. HRs ≥ 1.20 were observed for Hodgkin lymphoma in the previous mortality study of Marines/Navy personnel [ 13 ] and in the current study of the Marines/Navy full cohort (HR = 1.25, 95% CI: 0.82, 1.90). For civilian workers, the observed HR for Hodgkin lymphoma in this study was 1.65 (95% CI: 0.27, 9.96) based on ≤ 3 cases at each base. The previous mortality study of civilian workers could not evaluate Hodgkin lymphoma because of a lack of cases [ 14 ]. There is no information in the scientific literature indicating whether exposures to TCE, PCE, vinyl chloride or benzene are associated with Hodgkin lymphoma. An HR ≥ 1.20 was observed for multiple sclerosis in the previous mortality study of Marines/Navy personnel [ 13 ]. The current study observed a HR of 1.37 (95% CI: 0.92, 2.06) in the full cohort of Marines/Navy personnel. Exposure to organic solvents has been associated with multiple sclerosis, although exposure to specific organic solvents has not been studied [ 56 ]. Mortality due to myelodysplastic syndrome, acute myeloid leukemia, and cancers of the testes and ovary were not evaluated in the previous Camp Lejeune mortality study of Marines/Navy personnel [ 13 ]. The current study found HRs ≥ 1.20 but with CIRs > 3 for myelodysplastic syndrome (HR = 2.26, 95% CI: 0.83, 6.17), testicular cancer (HR = 1.76, 95% CI: 0.85, 3.67) and ovarian cancer (HR = 1.23, 95% CI: 0.42, 3.59) in Marines/Navy personnel subgroup. In the full cohort analysis, acute myeloid leukemia was observed to have a HR of 1.21 (95% CI: 0.94, 1.56). Benzene exposure has been associated with myelodysplastic syndrome [ 57 ] and is a known cause of acute myeloid leukemia [ 8 ]. The current evidence for causal associations between occupational or environmental exposures to TCE, PCE, vinyl chloride or benzene and the risks of mortality from cancers of the testes and ovary is not strong [ 5 , 7 – 8 ]. An HR of 1.27, but with CIR > 3 (95% CI: 0.61, 2.64), was observed for male breast cancer as a contributing cause in the analysis of the full cohort of Marines/Navy personnel. A previous case-control study of male breast cancer incidence found an increased risk among Camp Lejeune Marines compared to Marines from all other bases [ 58 ]. Occupational TCE exposure has been associated with male breast cancer in three studies [ 59 – 61 ]. An HR ≥ 1.20 was observed for chronic kidney disease (HR = 1.88, 95% CI: 1.13, 3.11) in the analysis of the civilian workers but not Marines/Navy personnel. An HR ≥ 1.20 was observed for acute kidney disease in the analysis of the full cohort of Marines/Navy personnel (HR = 1.32, 95% CI: 0.91, 1.90). The EPA toxicological reviews of TCE and PCE indicated that both epidemiological and animal studies support associations between TCE or PCE exposure and chronic kidney disease [ 3 , 6 ]. The current evidence for a causal association between kidney diseases and occupational exposures to TCE or PCE is at least as likely as not or greater [ 12 ]. HRs ≥ 1.20 with CIRs > 3 were observed for cancers of the pharynx and larynx in the analysis of the civilian workers, but HRs < 1.20 were observed in the analyses of Marines/Navy personnel. Two studies of head and neck cancers in men and women and occupational exposures to solvents found associations between occupational exposures to PCE and/or TCE and cancers of the larynx and pharynx [ 31 – 32 ]. In the previous mortality study of Camp Lejeune civilian workers, an HR ≥ 1.20 was observed for oral cavity cancers, which included cancer of the pharynx [ 14 ]. Other causes of death with HRs ≥ 1.20 and CIRs > 3 in the analysis of the civilian workers were chronic myeloid leukemia (HR = 1.26, 95% CI: 0.29, 5.48), melanoma (HR = 3.03, 95% CI: 1.05, 8.76) and anemias (HR = 1.91, 95% CI: 0.48, 7.65). One study found an association between “substantial” occupational exposure to TCE and melanoma (OR = 3.2, 95% CI: 1.0, 9.9), but precision was poor [ 62 ]. Two of the anemias were aplastic anemia, both among Camp Lejeune civilian workers. Benzene is a known cause of aplastic anemia [ 63 ]. The results of a meta-analysis provided support for a causal association between benzene occupational exposure and chronic myeloid leukemia [ 64 ]. A more recent study found an excess of chronic myeloid leukemia among benzene workers in China [ 65 – 66 ]. This study did not include information on important risk factors such as smoking and alcohol consumption as these data were unavailable. However, confounding due to failure to adjust for unmeasured risk factors was likely to be minor because of the demographic and socio-economic similarity of the Camp Lejeune and Camp Pendleton cohorts. The prevalence of smoking and “heavy alcohol” consumption among Marines in 1980 was estimated at 53.4% and 28.6%, respectively [ 49 ]. Smoking and alcohol consumption among Marines at both Camp Lejeune and Camp Pendleton were encouraged by the military culture, the stress of service, targeted advertising by the tobacco and alcoholic beverage industry, and the lower cost and tax-free availability of these products on base compared to civilian stores off-base [ 49 , 67 ]. The negative control diseases for alcohol consumption were mortality due to alcoholism, alcoholic liver disease, and chronic liver disease. All of the HRs for these diseases were less than 1.00, indicating that the prevalence and amount of alcohol consumption among Camp Lejeune Marines/Navy personnel and civilian workers were not greater than at Camp Pendleton. The negative control diseases for smoking selected in this study were mortality due to COPD and cardiovascular disease. The HRs for cardiovascular disease in this study were < 1.00. However, the HRs for COPD as an underlying cause in the subgroup analysis of Marines/Navy personnel and as a contributing cause in the analysis of civilian workers were 1.08 and 1.04, respectively. For smoking to fully explain the COPD adjusted HRs of 1.08 in the Marines/Navy personnel analysis and 1.04 in the civilian worker analysis, the differences in smoking prevalence between the two bases would need to be 6% and 3%, respectively, assuming a range of RRs between 3.00 and 5.50 for smoking and COPD mortality [ 43 ]. In the subgroup analysis of Marines/Navy personnel, other smoking related cancers that had HRs less than or close to 1.00 included cancers of the larynx, oral cavity, pharynx, colorectal, and bladder. These results suggested that there was little, if any, difference in the prevalence of smoking between Camp Lejeune and Camp Pendleton Marines/Navy personnel. In the analysis of civilian workers, esophageal cancer and oral cancers other than pharyngeal cancer were less than or close to 1.00, suggesting that there was little difference in the prevalence of smoking between Camp Lejeune and Camp Pendleton civilian workers. Smoking-related cancers such as cancer of the lung, larynx and pharynx had HRs > 1.00 but were not considered negative controls because of evidence linking them to TCE or PCE occupational exposures. For smoking to fully explain the lung cancer adjusted HRs of 1.18 and 1.13 in the analyses of Marines/Navy personnel and civilian workers, respectively, the difference in smoking prevalence between the two bases of 11% (Marines/Navy personnel) and 8% (civilian workers) would be necessary. The adjusted HR of 1.19 for cancer of the larynx in the analysis of civilian workers would require a smoking prevalence difference of at least 12% between the two bases. Smoking prevalence differences of these magnitudes were unlikely given the results for the negative control diseases for smoking. Assuming a 6% prevalence difference in smoking between Camp Lejeune and Camp Pendleton Marines/Navy personnel based on the result for COPD, the impact of adjusting for smoking on the HRs for kidney cancer, esophageal cancer and Parkinson disease would be less than 6%, and for lung cancer, no more than 9.3%. Using a 3% smoking prevalence difference between Camp Lejeune and Camp Pendleton civilian workers, based on the result for COPD, would reduce the HRs for cancers of the lung, pharynx, and larynx by no more than 5.3%. The HRs for kidney cancer and chronic kidney disease would be reduced by no more than 2%. The HR for Parkinson disease would increase by about 2.5%. The findings for the negative control diseases for alcohol consumption, i.e., mortality due to alcoholism, alcoholic liver disease and chronic liver disease, suggest that Camp Lejeune Marines/Navy personnel and civilian workers had a lower prevalence of alcohol use than Camp Pendleton. The findings for these negative controls suggest that possible confounding due to alcohol consumption might have biased HRs towards the null for alcohol-related cancers such as oral cancers and cancers of the pharynx, esophagus, larynx, and female breast. For cancers that are both smoking-related and alcohol-related such as oral cancers and cancers of the pharynx, larynx, esophagus, adjusting for possible differences in alcohol consumption between the two bases might cancel out the impact of adjusting for possible smoking differences between the two bases (Supplemental file, Figures S3, S8-S10, S16-S17, S20-S22). The quantitative bias analysis of the impact of non-differential exposure misclassification assumed that between 10% and 25% of those assigned to Camp Lejeune were truly unexposed and virtually none of those assigned to Camp Pendleton were truly exposed. For the Marines/Navy personnel, the increases in the HRs after adjusting for this bias ranged from no more than 4.2% for lung cancer to no more than 17% for Parkinson disease. For civilian workers, the increases in the HRs ranged between 2% and 13%. These results suggested that for cancers and other causes of death that are smoking-related, the bias due to non-differential exposure misclassification in this study may cancel out the potential confounding bias due to smoking. For causes of death that are not smoking-related, it is likely that exposure misclassification had at least as large an impact in this study as potential confounding due to unmeasured risk factors other than smoking. This study had several strengths including a large number of individuals and causes of death, 40 years of follow-up, a comparison USMC base with similar demographic characteristics and other risk factors as Camp Lejeune, a small percentage of individuals lost to follow-up, and a majority of civilian workers over the age of 65 years by the end of follow-up. However, there were limitations such as: (1) a majority of the individuals in the Marines/Navy personnel subgroup were under 60 years of age at the end of follow-up which reduced the number of deaths for each cause; (2) the poor precision of the HRs for some of the causes of death in the analysis of civilian workers due at least in part to small numbers of cases; (3) the potential for exposure misclassification bias in the analyses of Marines/Navy personnel and civilian workers, and (4) the potential for confounding bias due to unmeasured risk factors such as smoking, alcohol consumption, and occupational exposures before or after military service or employment at the two bases. Disease misclassification bias (both false positives and false negatives) was also a possibility due to errors assigning causes of death on the death certificate. Such a bias was likely non-differential and would tend to bias the HRs for the dichotomous comparisons between Camp Lejeune and Camp Pendleton toward a value of 1.00. Conclusion Comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup, adjusted HRs ≥ 1.20 with CIRs ≤ 3 for underlying causes of death were observed for cancers of the kidney, esophagus and female breast. Underlying causes of death with HRs ≥ 1.20 but with CIRs > 3 included Parkinson disease, myelodysplastic syndrome and cancers of the testes, cervix and ovary. Comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel full cohort, adjusted HRs ≥ 1.20 with CIRs ≤ 3 for underlying causes of death were observed for cancers of the kidney and female breast, Hodgkin lymphoma, acute myeloid leukemia, myelodysplastic syndrome, acute kidney disease, Parkinson disease and multiple sclerosis. Adjusted HRs ≥ 1.20 but with CIRs > 3 were observed for cancers of the cervix and testes. Comparing Camp Lejeune and Camp Pendleton civilian workers, adjusted HRs ≥ 1.20 with CIRs ≤ 3 for underlying causes of death were observed for chronic kidney disease and Parkinson disease. Female breast cancer had an adjusted HR of 1.19 with a CIR ≤ 3. Several other causes of death had HRs ≥ 1.20 but with CIRs > 3 including cancers of the kidney and pharynx, melanoma, and chronic myeloid leukemia. Because 85% of the full cohort and 98% of the subgroup of the Marines/Navy personnel were under 65 years of age at the end of follow-up, additional years of follow-up would be necessary to fully evaluate mortality in this population. Few studies have evaluated drinking water exposures to these chemicals and causes of death. It has been estimated that up to one million people were exposed to the contaminated drinking water at Camp Lejeune, according to estimates made by staff at the USMC Base Camp Lejeune. However, the health impacts of the drinking water exposures to Marines/Navy personnel whose tour of duty at Camp Lejeune ended prior to 1975, civilian workers whose employment at the base ended prior to October 1972, and family members of the Marines/Navy personnel who resided in base family housing at Camp Lejeune have not been evaluated. Families living in base housing that received contaminated drinking water may have had exposure durations that were at least as long if not longer than the Marines/Navy personnel on base. The results of this study are relevant to all individuals exposed to the contaminated drinking water at Camp Lejeune and add to the literature on the health effects of these contaminants. It is hoped that this study encourages future research on the health effects of drinking water exposure to these chemicals. Abbreviations ALS: amyotrophic lateral sclerosis AML: acute myeloid leukemia ATSDR: Agency for Toxic Substances and Disease Registry BOQ: bachelor officer quarters CDC: Centers for Disease Control and Prevention CI: 95% confidence interval CIR: confidence interval ratio CL: Camp Lejeune CLL: chronic lymphocytic leukemia CML: chronic myeloid leukemia CNS: central nervous system cancers COPD: chronic obstructive pulmonary disease DCE: t-1,2-dichloroethylene DMDC: Defense Manpower Data Center DOD: U.S. Department of Defense EPA: U.S. Environmental Protection Agency HB: Holcomb Boulevard treatment plant HP: Hadnot Point treatment plant HR: hazard ratio IARC: International Agency for Research on Cancer LTAS: life table analysis system MCL: EPA maximum contaminant level in drinking water NDI: National Death Index MDS: myelodysplastic syndrome MS: multiple sclerosis NHL: non-Hodgkin lymphoma NTP: National Toxicology Program µg/L: micrograms per liter PCE: tetrachloroethylene (also known as perchloroethylene) RR: risk ratio SMR: standardized mortality ratio SSA: Social Security Administration SSN: social security number TCE: trichloroethylene TT: Tarawa Terrace treatment plant USMC: United States Marine Corps WHO: World Health Organization Declarations The author declares he has nothing to disclose. Competing interests The author declares no actual or potential competing financial interest. Authors’ contributions FJB designed the study, oversaw the data collection process, managed, analyzed and interpreted the data, and prepared the manuscript. Battelle and its subcontractors prepared the data for matching with TransUnion, Lexis-Nexis, SSA and NDI, conducted manual review of the matching results, and provided the final dataset to FJB. Acknowledgement The author would like to thank the following lead project staff of Battelle Memorial Institute who coordinated the data collection and provided data management support: April Greek (Project Director), Ruth Gatiba (Project Manager), Rona Boehm (Data Management team lead), and the supporting staff at Battelle. The author would also like to thank lead project staff of the North American Association of Central Cancer Registries (NAACCR) who also coordinated data collection: Betsy Kohler and Recinda Sherman. Richard Pinder of the University of Southern California, Los Angeles consulted on the NDI. Aaron Bernstein, director of NCEH and ATSDR provided editing assistance. Finally, the author would like to acknowledge the strong and essential support for the study by the Camp Lejeune Community Assistance Panel members. This work was supported by funding through interagency agreements with the U.S. Department of Health and Human Services’ Agency for Toxic Substances and Disease Registry and the U.S. Department of the Navy. The author did not receive payment or services from a third party for any aspect of the submitted work. ATSDR/CDC Disclaimer The findings and conclusions in this manuscript are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry. 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Goldman SM, Weaver FM, Stroupe KT et al. Risk of Parkinson disease among service members at Marine Corps Base Camp Lejeune. JAMA Neurol. 2023;80(7):673-681. Gerhardsson L et al. Work-related exposure to organic solvents and the risk for multiple sclerosis – a systematic review. Int Arch Occup Environ Health 2021;94:221-229. Schnatter AR et al. Myelodysplastic syndrome and benzene exposure among petroleum workers: An international pooled analysis. JNCI 2012;104:1724-1737. Ruckart PZ, Bove FJ, Shanley III E, Maslia M. Evaluation of contaminated drinking water and male breast cancer at Marine Corps Base Camp Lejeune, North Carolina: a case control study. Environ Health 2015;14:74. Hansen J et al. Risk of Cancer Among Workers Exposed to Trichloroethylene: Analysis of Three Nordic Cohort Studies J Natl Cancer Inst;2013;105:869–877. Laouali N et al. Occupational exposure to organic solvents and risk of male breast cancer: A European multicenter case-control study. Scand J Work Environ Health 2018;44:312-322. Talibov M et al. Occupational exposures and male breast cancer: A nested case-control study in the Nordic countries. The Breast 2019;48:65-72. Christensen KY, Vizcaya D, Richardson H et al. Risk of selected cancers due to occupational exposure to chlorinated solvents in a case-control study in Montreal. J Occup Environ Med 2013;55:198-208. Agency for Toxic Substances and Disease Registry (ATSDR). 2007. Toxicological Profile for Benzene. US Department of Health and Human Services Agency for Toxic Substances and Disease Registry. Available at: https://www.atsdr.cdc.gov/ToxProfiles/tp3.pdf Vlaanderen J et al. Occupational benzene exposure and the risk of chronic myeloid leukemia: a meta-analysis of cohort studies incorporating study quality dimensions. Am J Ind Med 2012;55:779-785. Linet MS et al. A retrospective cohort study of cause-specific mortality and incidence of hematopoietic malignancies in Chinese benzene-exposed workers. Int J Cancer 2015;137:2184-2197. Linet MS et al. Benzene Exposure Response and Risk of Myeloid Neoplasms in Chinese Workers: A Multicenter Case–Cohort Study. J Natl Cancer Inst (JNCI) 2019;111:465-474. Truth Initiative. Tobacco use in the military: Fact sheet. June 2018. Accessed on 3/27/2023. https://truthinitiative.org/sites/default/files/media/files/2022/05/Truth_Military_FactSheet_051722.pdf Footnotes § See 45 C.F.R. part 46.114; 21 C.F.R. part 56.114 Additional Declarations No competing interests reported. Supplementary Files supplementalfilenew.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4171975","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":284441326,"identity":"3469e69e-7d5e-4a88-956e-d2ad5727324d","order_by":0,"name":"Frank J. Bove","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAoElEQVRIiWNgGAWjYBAC9hkgsoKBsYFoLTw3QOQZkrUwtpGkRbr5mMTHeXay/Q3sFx/zEKVF5lia5MxtycYzDvAUGxOlxV4ix9iYd9uBxA0MPGmSM4iyBaTl7xwStRg+ZmwAaWE/JvGBKC0yxxIf9hwD+uUwD7MBcVqkmw8c+FEDDLH29ocPEojRggDMPAakaQAC9gckaxkFo2AUjIKRAQBibDETjCiYHAAAAABJRU5ErkJggg==","orcid":"","institution":"Agency for Toxic Substances and Disease Registry (ATSDR)/CDC","correspondingAuthor":true,"prefix":"","firstName":"Frank","middleName":"J.","lastName":"Bove","suffix":""}],"badges":[],"createdAt":"2024-03-26 19:30:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4171975/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4171975/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55593930,"identity":"69913a07-d2d6-4498-8ff8-2022cbab5b3b","added_by":"auto","created_at":"2024-04-30 10:08:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1572442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4171975/v1/ca65d07a-d7be-4cf7-a44b-a3ae0360ce8a.pdf"},{"id":53739338,"identity":"f840b6d9-e2c5-4f74-8a4e-2c696f3736ff","added_by":"auto","created_at":"2024-03-29 15:24:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":205317,"visible":true,"origin":"","legend":"","description":"","filename":"supplementalfilenew.docx","url":"https://assets-eu.researchsquare.com/files/rs-4171975/v1/29dcf4d4e1aa592f57523c4c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of mortality among Marines, Navy personnel, and civilian workers exposed to contaminated drinking water at USMC Base Camp Lejeune: a cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eIndustrial solvents were detected in drinking water samples taken between 1980 and 1985 at United States Marine Corps (USMC) Base Camp Lejeune, North Carolina from drinking water supplied by two of the base’s eight treatment plants. Each drinking water treatment plant served a different area of the base. The Tarawa Terrace (TT) treatment plant began operating in 1952 and served approximately 1,850 family housing units. The TT system was contaminated by an off-base dry-cleaning business. Tetrachloroethylene (PCE) was the primary contaminant in the TT distribution system with measured concentrations of 104 micrograms per liter (µg/L) in July 1982 and a maximum level of 215 µg/L in January 1985. Much lower levels of trichloroethylene (TCE), trans-1,2-dichloroethylene (DCE), and vinyl chloride occurred in the distribution system due to PCE degradation in groundwater [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Hadnot Point (HP) treatment plant began operation in 1942 and served the base’s “mainside” including most of the bachelor’s quarters (“barracks”), a small number of family housing units, field training areas (via mobile “water buffaloes”) and eating establishments. The HP system was contaminated by on-base sources – leaking underground storage tanks, industrial area spills, and waste disposal sites. TCE and PCE were the primary contaminants, with maximum measured levels in the distribution system of 1,400 µg/L and 100 µg/L, respectively, during 1982. A TCE concentration of 1,148 µg/L was measured in drinking water from the HP treatment plant in January1985. Also detected in the drinking water at the HP treatment plant during 1984 and/or 1985 were benzene, from fuel spills and leaks, and DCE and vinyl chloride, from the degradation of PCE and TCE in groundwater [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Holcomb Boulevard (HB) treatment plant began operation in 1972 and served approximately 2,100 family housing units and a bachelor officer quarters (BOQ). The HB service area was uncontaminated except for intermittent dry periods when the HP system provided supplementary water. During a two-week period starting in late-January 1985, the HB plant was shut down for repairs and the HP system provided water to the HB service area [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNo drinking water samples for volatile organic compounds were collected at Camp Lejeune prior to 1980, and there were a limited number of samples taken between 1982 and 1985. Therefore, ATSDR conducted historical reconstruction modeling to estimate the monthly average contaminant levels in the TT and HP distribution systems. Details of the methodology have been summarized elsewhere [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on the historical reconstruction modeling, it was estimated that the HP and TT drinking water systems were contaminated starting in the mid-1950s. The heavily contaminated supply wells were shut down by February 1985, although levels of benzene above its maximum contaminant level (MCL) of 5 µg/L were detected on 11/19/1985 (2,500 µg/L) and on 12/10/1985 (38 µg/L) in the HP distribution system. In each system, water from supply wells was mixed at the treatment plant prior to distribution. Contamination levels in each system varied depending on the wells in use, their levels of contamination, and their pumpage rates [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEstimated monthly average concentrations of PCE in the TT distribution system between January 1975 and February 1985 ranged from 0 to 158 µg/L with a median of approximately 85 µg/L [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Estimated monthly average concentrations of TCE in the HP distribution system during this period ranged from 0 to 783 µg/L, with a median level of approximately 366 µg/L [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition, estimated monthly average levels of PCE and vinyl chloride in the HP distribution system during this period ranged from 0 to 39 µg/L and 0 to 67 µg/L, respectively, with medians of the estimates of 15 µg/L and 22 µg/L, respectively [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe United States Environmental Protection Agency (EPA) MCLs are 5 µg/L for TCE, PCE and benzene, 2 µg/L for vinyl chloride, and 100 µg/L for DCE (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.epa.gov/ground-water-and-drinking-water/national-primary-drinking-water-regulations#Organic\u003c/span\u003e\u003cspan address=\"https://www.epa.gov/ground-water-and-drinking-water/national-primary-drinking-water-regulations#Organic\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ). EPA and the International Agency for Research on Cancer (IARC) classified TCE as a human carcinogen [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The EPA classified PCE as a “likely human carcinogen” [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and IARC classified PCE as “probably carcinogenic to humans” [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Both benzene and vinyl chloride are known human carcinogens [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The carcinogenicity of DCE is not classified by EPA.\u003c/p\u003e \u003cp\u003eDrinking water exposures to TCE, PCE, DCE, vinyl chloride, and benzene involve contributions to total internal body dose from three routes: ingestion, inhalation, and dermal. A Marine in training may consume as much as 6 liters/day of drinking water [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The combined dose from the inhalation and dermal routes may be as high or higher than the dose from the ingestion route. For example, an internal dose via inhalation to TCE during a 10-minute shower may equal the internal dose via the ingestion of 2 liters of TCE-contaminated drinking water [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn ATSDR report assessed the strength of the evidence supporting causality of cancers and other diseases from exposures to TCE, PCE, vinyl chloride and benzene [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The assessment integrated findings from previous ATSDR studies at Camp Lejeune and studies conducted by other researchers of populations exposed occupationally or via drinking water to these chemicals. The assessment found sufficient causal evidence for TCE exposure and kidney cancer and non-Hodgkin lymphoma (NHL), and “equipoise and above evidence” (i.e., evidence for causation that was at least as likely as not or greater) for TCE exposure and multiple myeloma, leukemias, liver cancer, Parkinson disease, end-stage renal disease, and scleroderma. Sufficient causal evidence was found for PCE exposure and bladder cancer, and “equipoise and above evidence” for PCE exposure and NHL and end-stage renal disease. Sufficient causal evidence was found for benzene exposure and NHL and leukemias, and “equipoise and above evidence” for benzene exposure and multiple myeloma. Sufficient evidence was concluded for vinyl chloride exposure and liver cancer.\u003c/p\u003e \u003cp\u003eFew studies have evaluated drinking water exposures to TCE, PCE, vinyl chloride or benzene and the risk of specific causes of death. ATSDR previously conducted cohort mortality studies comparing Marines/Navy personnel and civilian workers stationed or employed at Camp Lejeune from 1975 to 1985 and 1973 to 1985, respectively, with similar cohorts over the same periods stationed or employed at USMC Base Camp Pendleton, California [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Both of the previous Camp Lejeune cohort mortality studies of Marines/Navy personnel and civilian workers found increased risks of death from cancers of the kidney, rectum, lung, prostate, leukemias, and multiple myeloma [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, the previous Camp Lejeune cohort mortality study of Marines/Navy personnel found increased risks of death from cancers of the esophagus, liver, and cervix; Hodgkin lymphoma; and multiple sclerosis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although Parkinson disease mortality could not be evaluated in the previous Camp Lejeune cohort mortality study of Marines/Navy personnel because of sparse data, Parkinson mortality risk was increased in the Camp Lejeune cohort mortality study of civilian workers [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. An increased risk of mortality due to oral cavity cancers was also found in the study of civilian workers [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe follow-up period for both of the previous Camp Lejeune mortality studies was between 1979 and 2008. The current cohort mortality study extends the follow-up period to 2018.\u003c/p\u003e \u003cp\u003eThe purpose of the current cohort study of Camp Lejeune Marines/Navy personnel and civilian workers was to determine if being stationed or employed at Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), a portion of the period when the drinking water was contaminated, increased the risk of specific causes of death during the follow-up period between 1979 and 2018 compared to being stationed or employed at Camp Pendleton. Camp Pendleton was not known to have contaminated drinking water during the years prior to 1986 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy population\u003c/p\u003e\u003cp\u003eATSDR obtained quarterly personnel data from the Defense Manpower Data Center (DMDC) for Marines/Navy personnel stationed at Camp Lejeune (N = 217,988) and Camp Pendleton (N = 232,026) for the years 1975 through 1985, who were known to be alive at the start of follow-up on January 1, 1979. The end of the year 1985 was selected because drinking water distribution system samples taken at Camp Lejeune from 1986 onward indicated no contamination above the contaminants’ MCLs. Although drinking water contamination preceded 1975, the code for the unit (e.g., regiment, battalion, company, etc.) that an individual was assigned to, which is necessary to determine the base where the individual was stationed, was not available in the DMDC database until the second quarter of 1975. In addition to unit code, the DMDC data included date of birth, marital status, rank (paygrade), date active duty started, military occupation code, education level at the start of service, race, sex, full name, and social security number. The USMC provided a list of the codes for the units that were stationed at each base. From the DMDC data, it was estimated that during the period 1975–1985, the average duration that Marines/Navy personnel were stationed at Camp Lejeune was about 18 months.\u003c/p\u003e\u003cp\u003eSome of the Marines/Navy personnel began active duty prior to 1975 when information on base location (i.e., unit code) was not available in the DMDC data. For these Marines, it would be unknown whether those stationed at Camp Pendleton between 1975 and 1985 were stationed at Camp Lejeune prior to 1975. Since it was not unusual for a Marine to be stationed at both bases, it was likely that some Marines who began active duty prior to 1975 and were stationed at Camp Pendleton between 1975 and 1985, were stationed at Camp Lejeune prior to 1975. To address this problem, a subgroup of the full cohort was identified consisting of Marines/Navy personnel who began active duty between 1975 and 1985, when information on base location was available in the DMDC database. This subgroup consisted of 154,821 at Camp Lejeune and 163,484 at Camp Pendleton who were known to be alive at the start of follow-up on January 1, 1979. Comparisons between the Camp Lejeune and Camp Pendleton subgroup constituted the main focus of the evaluation of mortality among Marines/Navy personnel.\u003c/p\u003e\u003cp\u003eATSDR also obtained quarterly personnel data from the DMDC for civilian workers employed at Camp Lejeune (N = 7,332) and Camp Pendleton (N = 6,677) between October 1972 and December 1985, who were known to be alive at the start of follow-up on January 1, 1979. October 1972 was the first quarter that the DMDC had personnel data for civilian workers. The DMDC information included base location of employment, social security number, full name (in the DMDC data beginning in the last quarter of 1981), date of birth, paygrade, education level, race, sex, and occupation code. Based on the DMDC data, the average duration of employment at Camp Lejeune between October 1972 and December 1985 was 64 months.\u003c/p\u003e\u003cp\u003eCamp Pendleton Marines/Navy personnel and civilian workers were chosen as comparison groups in this study because the drinking water at the base was not known to be contaminated prior to 1986 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Camp Pendleton Marines/Navy personnel and civilian workers were similar to their counterparts at Camp Lejeune in terms of demographics, socioeconomic and cultural factors, training activities, and types of military and civilian employee occupations. In addition, the Marines/Navy personnel at both bases had similar pre-enlistment screening and fitness requirements. Biases due to the healthy veteran effect [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] or the healthy worker effect [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as well as due to unmeasured confounders, should be reduced by having comparison cohorts with similar risk factors as the Camp Lejeune cohorts.\u003c/p\u003e\u003cp\u003eVital status ascertainment\u003c/p\u003e\u003cp\u003eTo obtain vital status, personal identifier information from the DMDC database was submitted to a locator firm and subsequently to the Social Security Administration (SSA) for linkage with its Data for Epidemiological Researchers database. Data returned from SSA included a status code indicating vital status of “D” (deceased), “L” (living) or “U” (undetermined). SSA was able to match about 99% of the records. Finally, personal identifier information of deaths identified via matching with the locator firm and SSA that were not included in the previous mortality studies (i.e., deaths occurring after 2008 as well as deaths missed in the previous mortality studies) and of individuals with unknown vital status was submitted to the National Death Index (NDI) to obtain the International Classification of Diseases (ICD), Ninth and Tenth codes for underlying and contributing causes of death and date of death. Those whose vital status remained unknown after the NDI search were considered “lost to follow-up” but contributed person-years to the study until the last date they were known to be alive. About 1% of the Camp Lejeune and Camp Pendleton cohorts were lost to follow-up (Tables\u0026nbsp;\u0026lt;link rid=\"tb1\"\u0026gt;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u0026lt;/link\u0026gt;\u003c/span\u003e–\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and S\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information for the Marines/Navy personnel subgroup at risk during the follow-up period, who began military service and were stationed at Camp Lejeune or Camp Pendleton between 1975 and 1985\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune N (%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton N (%) (ref)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal N (%)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarines at risk\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159,128 (48.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168,406 (51.4)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e327,534\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151,026 (94.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162,473 (96.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e313,499 (95.7)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,102 (5.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,933 (3.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,035 (4.3)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116,501 (73.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131,011 (77.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e247,512 (75.6)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African\u003c/p\u003e \u003cp\u003eAmerican\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,365 (24.1)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,657 (17.0)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67,022 (20.5)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther race\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,262 (2.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,738 (5.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,000 (4.0)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE1 – E4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130,312 (81.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137,281 (81.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e267,593 (81.7)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE5 – E9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23,049 (14.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,434 (13.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46,483 (14.2)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWO or CO\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,767 (3.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,691 ( 4.6)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,458 (4.1)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133,140 (83.7)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132,871 (78.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e266,011 (81.2)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;High school\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,951 (12.5)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27,362 (16.2)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47,313 (14.4)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege graduate and higher\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,037 (3.8)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,173 (4.9)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,210 (4.3)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, at start of follow-up (1/1/1979)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.2 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.5 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.3 years\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.0 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.0 years\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at end of follow-up\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.4 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.6 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.5 years\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.0 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.0 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.0 years\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% Age \u0026gt; 55 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.6%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.8%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% Age \u0026gt; 65 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeaths\u003csup\u003e¥\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,250\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,134\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40,384\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% of cohort\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.1%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.3%\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton\u003c/p\u003e \u003cp\u003e(ref)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of follow-up (years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal person-years of follow-up\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,760,931\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,078,598\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,839,529\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal lost to follow-up\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,072 (0.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,231 (0.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,303 (0.7%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarters in the DMDC data, October 1972 – December 1985\u003csup\u003e€\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton\u003c/p\u003e \u003cp\u003e(ref)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterquartile range (25th -75th percentiles)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (3–11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (3–11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eE1 – E4: private to corporal\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eE5 – E9: sergeant to sergeant major\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eWO: warrant officer\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eCO: commissioned officer\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e*\u003c/sup\u003e Age at end of follow-up (12/31/2018 or date of death if earlier than 12/31/2018).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e¥\u003c/sup\u003e Deaths occurring 1/1/1979–12/31/2018.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e€\u003c/sup\u003e Number of quarters stationed at either Camp Lejeune or Camp Pendleton during 1975–1985. Some members of the Camp Lejeune cohort, who were stationed at least one quarter at Camp Lejeune during 1975–1985, were also stationed at Camp Pendleton during 1975–1985. So, the statistics for the Camp Lejeune cohort include quarters at Camp Pendleton during 1975–1985. The Camp Pendleton cohort members were not stationed at Camp Lejeune during 1975–1985.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information for civilian workers at risk during the follow-up period who were employed at Camp Lejeune or Camp Pendleton between 12/72 and 12/85\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune\u003c/p\u003e \u003cp\u003eN = 7,332 (52.3%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton (ref)\u003c/p\u003e \u003cp\u003eN = 6,677 (47.7%)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN = 14,009\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,708 (50.6%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,646 (54.6%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,354 (52.5%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,624 (49.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,031 (45.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,655 (47.5%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,539 (75.5%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,199 (77.9%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,738 (76.7%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican American\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,409 (19.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e498 (7.5%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,907 (13.6%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther or unknown race\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e384 (5.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e980 (14.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,364 (9.7%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlue collar\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,819 (38.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,798 (41.9%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,617 (40.1%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite collar\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,513 (61.6%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,879 (58.1%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,392 (59.9%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot a high school graduate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,038 (14.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e679 (10.2%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,717 (12.3%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,206 (71.0%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,539 (83.0%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,745 (76.7%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege graduate and higher\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,088 (14.8%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e459 (6.9%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,547 (11.0%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at start of follow-up (1/1/1979)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at end of follow-up (12/31/2018 or date of death)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge \u0026gt; 65 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,185 (70.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,760 (71.3%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,945 (71.0%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge \u0026gt; 70 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,574 (48.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,586 (53.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,160 (51.1%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge \u0026gt; 75 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,377 (32.4%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,571 (38.5%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,948 (35.3%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDied during 1/2/1979–12/31/2018\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,055 (41.7%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,280 (49.1%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,335 (45.2%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of follow-up (years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (years)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal person-years of follow-up\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e231,496\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203,469\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e434,965\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal lost to follow-up\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (1.5%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (1.3%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195 (1.4%)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarters in the DMDC data, 10/1972-12/1985\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton\u003c/p\u003e \u003cp\u003e(ref)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterquartile range (25th -75th percentiles)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (3–33)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (4–27)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e*\u003c/sup\u003e Number of quarters employed at either Camp Lejeune or Camp Pendleton during 10/72 − 12/1985. Some members of the Camp Lejeune cohort, who were employed at least one quarter at Camp Lejeune during 10/72 − 12/1985, were also employed at Camp Pendleton during 10/72 − 12/1985. So, the statistics for the Camp Lejeune cohort include quarters at Camp Pendleton during 10/72 − 12/1985. The Camp Pendleton cohort members were not employed at Camp Lejeune during 10/72 − 12/1985.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eFollow-up began on January 1, 1979, or at the start of employment or military service at Camp Lejeune or Camp Pendleton, whichever was later, and continued until December 31, 2018, if the individual was known to be alive, or to date of death. The previous mortality studies’ end of follow-up was on December 31, 2008 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The present study included all the deaths in the previous studies and extended the follow-up period an additional ten years to December 31, 2018.\u003c/p\u003e\u003cp\u003eThe analyses of Marines/Navy personnel focused on comparisons between the Camp Lejeune and Camp Pendleton subgroup. For rare causes of death that primarily occur among older populations such as male breast cancer, the focus of the analyses included comparisons between Camp Lejeune and Camp Pendleton Marines/Navy personnel in the full dataset (“full cohort”).\u003c/p\u003e\u003cp\u003eThe descriptive analyses included the computing of cause-specific, standardized mortality ratios (SMRs) comparing Camp Lejeune and Camp Pendleton to the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death using the life table analysis system or “LTAS” [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Poisson regressions comparing the sex, race, and five-year age-specific underlying causes of death for Camp Lejeune versus Camp Pendleton were conducted as part of the descriptive analyses because comparisons of the SMRs between the two bases could be impacted by residual confounding bias due to differences in the distributions of age, sex, and/or race.\u003c/p\u003e\u003cp\u003eThe comparisons in this study are between ever stationed or ever employed at Camp Lejeune vs stationed or employed at Camp Pendleton but not Camp Lejeune during the periods 1975–1985 for Marines/Navy personnel and October 1972 and December 1985 for civilian workers. In apportioning person-years during the follow-up period to specific age, race, sex, and calendar period categories for each base, once an individual was stationed or employed at Camp Lejeune any quarter between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers) all subsequent person-years were assigned to Camp Lejeune. If the individual was stationed or employed at Camp Pendleton but not Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then person-years at risk were assigned to Camp Pendleton. If the individual was stationed or employed at both bases between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then once the individual was stationed or employed at Camp Lejeune, all subsequent person-years were assigned to Camp Lejeune.\u003c/p\u003e\u003cp\u003eFor the main analyses, Cox proportional hazards (Cox) regression was used to estimate hazard ratios (HRs) for each underlying cause of death comparing the Camp Lejeune and Camp Pendleton cohorts. Secondary analyses using Cox regression evaluated contributing causes of death. For the analyses of Marines/Navy personnel, the primary focus was on the subgroup comparisons between Camp Lejeune and Camp Pendleton. Secondary analyses evaluated the full cohort of Marines/Navy personnel comparing Camp Lejeune and Camp Pendleton. For civilian workers, the main analyses also focused on comparisons between Camp Lejeune and Camp Pendleton.\u003c/p\u003e\u003cp\u003eAge was the time variable in the Cox regressions. If an individual was stationed or employed at both Camp Lejeune and Camp Pendleton between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), then once the individual was stationed or employed at Camp Lejeune, all subsequent ages were assigned to Camp Lejeune.\u003c/p\u003e\u003cp\u003eUnadjusted models were adjusted for age only. For the analyses of Marines/Navy personnel, the adjusted models included sex, race, rank, and education level. For the analyses of civilian workers, the adjusted models included sex, race, blue collar work (y/n), and education level. Blue collar work included manual jobs such as maintenance workers, mechanics, construction workers, laundry and dry-cleaning workers, pest control workers, and water treatment plant workers. The exposure (i.e., base location at Camp Lejeune) was not lagged in the analyses because more than 75% of the deaths occurred more than 10 years after the contamination ended at Camp Lejeune. Evaluation of Schoenfeld residuals was used to check the proportional hazards assumption.\u003c/p\u003e\u003cp\u003eIn the previous Camp Lejeune mortality studies, residential cumulative exposure to each contaminant was evaluated based on linking the estimated monthly concentrations in the TT, HP and HB water systems from the historical reconstruction modeling and Camp Lejeune base family housing records and information on the barrack location of each military unit [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, cumulative residential exposure to each contaminant was not evaluated because drinking water exposures during training and other base activities would likely contribute significantly to overall cumulative exposure. Since information on training and other base activities was not available, the study instead evaluated duration of assignment (Marines/Navy personnel) or duration of employment (civilian workers) at Camp Lejeune as a surrogate for overall cumulative exposure. Cox regression analyses of underlying causes of death using categorical variables for duration were conducted with Camp Pendleton Marines/Navy personnel and civilian workers as the comparison groups.\u003c/p\u003e\u003cp\u003eInformation on smoking and alcohol consumption was not available. Occupational history prior to or after active-duty service or employment at Camp Lejeune or Camp Pendleton was also unavailable. To assess the possible confounding effects of smoking and alcohol consumption, the study evaluated the results for “negative control” causes of death that are associated with the unmeasured risk factor (i.e., the potential confounder) but were not known to be associated with the exposures of interest, i.e., the drinking water contaminants at Camp Lejeune [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The negative controls were used to estimate prevalence differences in smoking and alcohol consumption between Camp Lejeune and Camp Pendleton. The negative control causes of death for smoking were chronic obstructive pulmonary disease (COPD) and cardiovascular disease, and the negative control causes of death for alcohol consumption were alcoholism, alcoholic liver disease, and chronic liver disease.\u003c/p\u003e\u003cp\u003eLung cancer mortality was not considered a negative control for smoking because of some evidence that PCE exposures in drinking water and occupational PCE exposures, especially among dry cleaning workers, may be associated with the risk of lung cancer [\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e–\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Occupational benzene exposure has also been associated with lung cancer in two studies [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e–\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Laryngeal cancer mortality also was not considered a negative control for smoking or for alcohol consumption because of some evidence that PCE and or TCE occupational exposures may be associated with laryngeal cancer [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e–\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Another smoking-related cancer, bladder cancer, has been linked to PCE exposure [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Several alcohol-related cancers, such as cancers of the oral cavity and pharynx, larynx, liver, esophagus, colon, and female breast [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], were not considered negative controls because there was at least some evidence linking these cancers to one or more of the contaminants in the drinking water [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e–\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e–\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eQuantitative bias methods were conducted to estimate quantitatively, and adjust the HR estimates for, the systematic errors (or biases) due to unmeasured confounding factors and exposure misclassification. The analyses focused on the dichotomous comparisons between Camp Lejeune and Camp Pendleton, and used Excel spreadsheets included with the textbook, \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eApplying Quantitative Bias Analysis to Epidemiologic Data, Second Edition\u003c/span\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The quantitative bias analyses of the impacts of unmeasured confounding due to smoking and alcohol consumption used the negative control results to estimate the differences in alcohol consumption and smoking between Camp Lejeune Marines/Navy personnel and civilian workers and their counterparts at Camp Pendleton.\u003c/p\u003e\u003cp\u003eQuantitative bias analyses of exposure misclassification assumed that the misclassification was non-differential and independent because: (1) the base assignments derived from the unit codes for Marines/Navy personnel were completed prior to vital status and mortality data collection, and (2) the base location of employment for civilian workers was recorded in the DMDC database many years prior to vital status and mortality data collection [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Therefore, base location assignment was not affected by cause of death information.\u003c/p\u003e\u003cp\u003eFor Camp Lejeune Marines/Navy personnel and civilian workers, the sources of possible exposure misclassification were due to using unit assignment or employment at Camp Lejeune as a proxy for exposure to the drinking water. For Marines/Navy personnel, errors were possible in the historical research conducted by the DMDC and USMC to determine the base where each unit was located. Second, even if the base assignment of the unit was correct, some individuals may not have been exposed to the contaminated drinking water because they were deployed to a different base (e.g., outside the country) or trained at a different base. Third, some individuals stationed at Camp Lejeune may not have been exposed because all their water consumption (including showering and other water uses) occurred off-base (e.g., in off-base housing) or in areas of the base not served by the HP or TT drinking water systems. On the other hand, most of those classified as stationed at Camp Pendleton likely were truly unexposed to the contaminated drinking water.\u003c/p\u003e\u003cp\u003eFor Camp Lejeune civilian workers, a main source of exposure misclassification was due to water consumption (including showering and other water uses) occurring mostly or entirely off-base (e.g., at their residences). In addition, the workplaces of some of the Camp Lejeune civilian workers may have been located in areas not served by the contaminated drinking water. On the other hand, all civilian workers at Camp Pendleton were assumed to be truly unexposed to contaminated drinking water.\u003c/p\u003e\u003cp\u003eTo conduct the quantitative bias analyses, it was assumed that the sensitivity of the exposure classification, i.e., the probability that the truly exposed were correctly classified as exposed (i.e., assigned to Camp Lejeune) was near 1.0 because it was highly unlikely that a truly exposed individual would be assigned only to Camp Pendleton. On the other hand, the specificity of the exposure classification, i.e., the probability that the truly unexposed were correctly classified as unexposed (i.e., assigned to Camp Pendleton) was assumed to range from 0.81 to 0.91. The chosen values for sensitivity and specificity used in the quantitative bias analysis reflected the assumptions that between 75% and 90% of those stationed or employed at Camp Lejeune were truly exposed, and all (or virtually all) of those stationed or employed at Camp Pendleton were truly unexposed.\u003c/p\u003e\u003cp\u003eInterpretation of study findings was based primarily on the magnitude of the adjusted HR, its precision, and whether a finding was supported by other studies of occupational or drinking water exposures to the chemicals found in the drinking water at Camp Lejeune. Because meta-analyses published in the scientific literature for TCE occupational exposures and kidney cancer, NHL, and liver cancer observed summary risk ratios between 1.20 and 1.40 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], the study emphasized HRs ≥ 1.20. An HR of 1.20 implies that the cause of death occurs 1.2 times more often in the Camp Lejeune cohort compared to the Camp Pendleton cohort.\u003c/p\u003e\u003cp\u003eFor rare causes of death such as male breast cancer, the HRs from the analyses of contributing causes of death were also considered. In addition, for rare causes of death among Marines/Navy personnel, the analyses of underlying and contributing causes in the full cohort were also considered in the interpretation of the findings.\u003c/p\u003e\u003cp\u003eThe analyses of underlying cause of death and duration at Camp Lejeune provided additional information that was used in the interpretation of the findings. Emphasis was on monotonic trends in the duration. A monotonic trend occurs when every change in the HR with increasing duration is in the same direction (e.g., the HR increases), although the trend could have flat segments but never reverse direction [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe 95% confidence interval ratio (CIR), measured by the quotient of the upper to lower limit, was used to indicate the precision (or degree of random variability) of the effect estimates (i.e., the SMR, RR and HR estimates) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e–\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The CIR is primarily impacted by the level of the CI (e.g., a 95% CI) and the number of deaths from a specific cause in the cohorts being compared. The smaller the number of deaths, the wider the confidence interval. The study emphasized adjusted HRs ≥ 1.20 with CIRs ≤ 3. However, adjusted HRs ≥ 1.20 with CIRs \u0026gt; 3 should not be considered as lacking importance.\u003c/p\u003e\u003cp\u003eBecause p-values and statistical significance testing are “commonly misused and misinterpreted” [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], significance testing was not used to interpret findings [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Instead, the interpretation is based on: (1) the magnitude of the adjusted HR estimate (i.e., ≥ 1.20), (2) the precision of the estimate (i.e., the 95% CIR), (3) the quantitative impacts of unmeasured potential confounders (e.g., smoking and alcohol consumption) and exposure misclassification on the adjusted HR estimate, and (4) supporting information from the scientific literature on the health effects of TCE, PCE, vinyl chloride, and benzene [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e–\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Analyses were conducted using SAS 9.4 and STATA 16, and SPSS was used for data management.\u003c/p\u003e\u003cp\u003e This study was approved by the Centers for Disease Control and Prevention Institutional Review Board.[1]\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDemographic information for the civilian workers and the subgroup of Marines/Navy personnel is provided in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Tables providing demographic information and all statistical results for the Camp Pendleton and Camp Lejeune full cohort of Marines/Navy personnel are included in Supplemental file, Tables S1 to S4.\u003c/p\u003e \u003cp\u003eThe Marines/Navy personnel in the Camp Lejeune and Camp Pendleton subgroup generally appeared similar on sex, rank, age, length of follow-up and the percent of the cohort that died. There appeared to be small differences in attained education level and race. The combined subgroup was mostly male (95.7%), white (75.6%) and ranged in rank from E1 to E4 (81.7%). Of note was that about 2% were above the age of 65 years at the end of follow-up. The average length of follow-up was about 36 years, and the total amount of person-years was 11,839,529. About 12% of the Marines/Navy personnel in the subgroup had died by the end of follow-up.\u003c/p\u003e \u003cp\u003eAmong the Camp Lejeune and Camp Pendleton civilian workers, the percentages of women were 49.4% and 45.4%, respectively. Most of the Camp Lejeune and Camp Pendleton civilian workers were White. A much higher percentage of the Camp Lejeune workforce was African American (19.2%) compared to Camp Pendleton (7.5%). A higher percentage at Camp Lejeune graduated from college (14.8%) compared to Camp Pendleton (6.9%). Over half of the civilian workers in the study were above 70 years of age at the end of follow-up. The average length of follow-up was about 31 years, and the total amount of person-years was 434,965. About 42% (N\u0026thinsp;=\u0026thinsp;3,055) of the Camp Lejeune civilian workers and 49% (N\u0026thinsp;=\u0026thinsp;3,280) of Camp Pendleton civilian workers had died by the end of follow-up.\u003c/p\u003e \u003cp\u003eThe results of the SMR and Poisson regression analyses for the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The SMRs for most of the underlying causes of death, including death from all causes and all cancer malignancies, were less than 1.00, consistent with a \u0026ldquo;healthy veteran effect\u0026rdquo; [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The healthy veteran effect could be due to several factors including the initial physical screening for healthy recruits, physical fitness standards during military service, and access to quality health care during and after service. The healthy veteran effect may have been especially strong in this relatively young subgroup: at the end of follow-up about 98% were less than 65 years of age and about 43% were less than 55 years of age. SMRs above 1.00 at Camp Lejeune were observed for cancers of the esophagus, pancreas, cervix, prostate, kidney, connective tissue, and Parkinson disease, amyotrophic lateral sclerosis (ALS) and suicide. SMRs above 1.00 at Camp Pendleton were observed for cancers of the uterus, male breast, prostate, thyroid, and for alcoholism, ALS, and suicide.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStandardized mortality ratios (SMR), Poisson regression risk ratios, and 95% confidence intervals (CI) for the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup: Underlying cause of death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCause of Death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCamp Lejeune (CL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Pendleton (CP)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCL vs CP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll Causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19,250 0.90 (0.89, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,134 0.93 (0.92, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.97, 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll Cancer Malignancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,689 0.92 (0.89, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,760 0.87 (0.84, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (1.02, 1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral Cavity and Pharynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 0.85 (0.70, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 0.92 (0.77, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.73, 1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophagus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 1.01 (0.87, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154 0.83 (0.70, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25 (1.00, 1.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 0.78 (0.62, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 0.83 (0.68, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.70, 1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266 0.87 (0.77, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264 0.81 (0.71, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.91, 1.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 0.79 (0.63, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 0.83 (0.67, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.69, 1.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver/Biliary System\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268 0.84 (0.75, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289 0.85 (0.76, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.86, 1.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265 1.06 (0.94, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250 0.92 (0.81, 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15 (0.97, 1.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 0.76 (0.53, 1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 0.77 (0.55, 1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04 (0.66, 1.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung/Trachea/Bronchus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e982 0.97 (0.91, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e915 0.83 (0.78, 0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19 (1.08, 1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnective Tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 1.03 (0.77, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 0.90 (0.67, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.17 (0.80, 1.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 0.98 (0.80, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 0.89 (0.73, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09 (0.84, 1.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast Cancer - Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 0.92 (0.66, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 0.72 (0.47, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.23 (0.75, 2.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast Cancer - Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 0.69 (0.19, 1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 1.76 (0.88, 3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39 (0.12, 1.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 1.07 (0.49, 2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 0.79 (0.26, 1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.21 (0.39, 3.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 0.91 (0.30, 2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 1.59 (0.64, 3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59 (0.19, 1.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 0.72 (0.31, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 0.67 (0.24, 1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19 (0.41, 3.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 1.01 (0.81, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 1.06 (0.87, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.71, 1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTestis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 0.72 (0.42, 1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 0.45 (0.23, 0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.72 (0.83, 3.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney and Renal Pelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 1.11 (0.93, 1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126 0.91 (0.76, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.21 (0.95, 1.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrinary Bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 0.97 (0.74, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 0.94 (0.73, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.72, 1.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain and CNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 0.91 (0.78, 1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e217 1.00 (0.87, 1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90 (0.74, 1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 0.78 (0.34, 1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 1.07 (0.55, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72 (0.30, 1.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematopoietic Cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e354 0.83 (0.75, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e380 0.83 (0.74, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.87, 1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHodgkin Lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 0.93 (0.63, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 0.91 (0.62, 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.61, 1.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 0.73 (0.60, 0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 0.83 (0.70, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87 (0.68, 1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Myeloma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 0.99 (0.77, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 0.92 (0.70, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (0.76, 1.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 0.87 (0.73, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136 0.77 (0.65, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.89, 1.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e400 0.71 (0.64, 0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e452 0.75 (0.69, 0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.82, 1.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242 0.93 (0.81, 1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302 1.07 (0.95, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.74, 1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 0.78 (0.52, 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 0.68 (0.45, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12 (0.66, 1.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 1.47 (0.73, 2.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 0.69 (0.21, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00 (0.85, 4.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 1.12 (0.85, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 1.05 (0.80, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.75, 1.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,316 0.90 (0.87, 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,650 0.91 (0.88, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.96, 1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312 0.96 (0.86, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e320 0.89 (0.79, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 (0.94, 1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Liver Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e614 0.79 (0.73, 0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e775 0.91 (0.84, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.79, 0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCause of Death\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCamp Lejeune (CL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCamp Pendleton (CP)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRisk Ratio (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCL vs CP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133 0.62 (0.52, 0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 0.64 (0.54, 0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.78, 1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuicide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,664 1.21 (1.16, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,002 1.32 (1.27, 1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.86, 0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCNS: central nervous system\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNHL: non-Hodgkin lymphoma\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eALS: amyotrophic lateral sclerosis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCOPD: chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSMRs were calculated using the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eRisk ratios were adjusted for sex, race, and five-year age groups.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the Poisson regression analyses of underlying cause of death comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup, risk ratios (RRs)\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for cancers of the esophagus (RR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.00, 1.55), and kidney (RR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.95, 1.54). Female breast cancer had a RR of 1.23 with CIR\u0026thinsp;\u0026le;\u0026thinsp;3 (95% CI: 0.75, 2.03). A few other causes of death with RRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included cancers of the cervix and testes and Parkinson disease.\u003c/p\u003e \u003cp\u003eThe results of the SMR and Poisson regression analyses for the Camp Lejeune and Camp Pendleton civilian workers are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The SMRs for most of the causes of death, including deaths from all causes and all cancer malignancies, were less than 1.00. These findings indicated the impact of the \u0026ldquo;healthy worker effect\u0026rdquo; [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In the Poisson regression analyses comparing Camp Lejeune versus Camp Pendleton civilian workers, RRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for female breast cancer (RR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.77, 1.89) and chronic kidney disease (RR\u0026thinsp;=\u0026thinsp;1.77, 95% CI: 1.07, 2.93). A few other causes of death had RRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 and included cancers of the kidney, pharynx, and larynx, and melanoma, Hodgkin lymphoma, and anemias.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStandardized mortality ratios (SMRs) and Poisson regression risk ratios for the Camp Lejeune and Camp Pendleton civilian workers: Underlying cause of death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCause of Death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCL vs CP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,055 0.89 (0.85, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,280 0.90 (0.87, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.91, 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e882 0.93 (0.87, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e890 0.93 (0.87, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.92, 1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll malignant cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e859 0.91 (0.85, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e874 0.91 (0.85, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.91, 1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral cavity and pharynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 0.62 (0.31, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 0.62 (0.31, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06 (0.43, 2.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 0.95 (0.41, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 0.48 (0.13, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.14 (0.61, 7.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophagus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 0.51 (0.27, 0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 0.96 (0.61, 1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63 (0.31, 1.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 0.85 (0.53, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 0.87 (0.54, 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.53, 1.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 0.61 (0.45, 0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 0.70 (0.53, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.56, 1.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 0.87 (0.46, 1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 0.92 (0.50, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.43, 2.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver/Biliary system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 0.62 (0.38, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 0.92 (0.62, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73 (0.40, 1.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 0.78 (0.56, 1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 1.20 (0.92, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72 (0.48, 1.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 0.94 (0.41, 1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 0.59 (0.19, 1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (0.42, 4.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310 1.08 (0.96, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e281 0.96 (0.85, 1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15 (0.97, 1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney and renal pelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 1.16 (0.74, 1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 0.70 (0.39, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.49 (0.76, 2.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrinary bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 0.85 (0.50, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 1.06 (0.69, 1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 (0.34, 1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 1.03 (0.53, 1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 0.41 (0.13, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.59 (0.89, 7.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnective tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 0.90 (0.29, 2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 1.10 (0.40, 2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 (0.19, 2.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain and CNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 0.87 (0.50, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 1.44 (0.96, 2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 (0.36, 1.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematopoietic cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 1.00 (0.80, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 1.02 (0.82, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.73, 1.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 1.47 (0.30, 4.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 0.98 (0.12, 3.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.81 (0.30, 11.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNHL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 1.12 (0.78, 1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 1.13 (0.80, 1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.61, 1.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple myeloma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 0.79 (0.44, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 0.68 (0.36, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.45, 2.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 0.98 (0.67, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 1.11 (0.78, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.61, 1.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast cancer - Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 0.84 (0.62, 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 0.63 (0.44, 0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.21 (0.77, 1.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast cancer - Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 0.55 (0.11, 1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 1.01 (0.49, 1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 1.00 (0.46, 1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.39, 2.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 0.75 (0.41, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 1.28 (0.80, 1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57 (0.29, 1.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 0.99 (0.78, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 0.80 (0.61, 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.69, 1.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTestis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 0.90 (0.72, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 0.98 (0.80, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78 (0.58, 1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 0.56 (0.23, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 0.87 (0.42, 1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63 (0.23, 1.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 0.63 (0.13, 1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 0.73 (0.15, 2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 (0.14, 3.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 1.34 (0.86, 1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 1.19 (0.77, 1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15 (0.68, 1.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 0.57 (0.07, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 1.12 (0.43, 1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44 (0.14, 1.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 1.20 (0.48, 2.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 0.48 (0.10, 1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.61 (0.39, 6.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCause of Death\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRisk Ratio (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObserved SMR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCL vs CP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart/Circulatory disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1105 0.88 (0.83, 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1271 0.93 (0.88, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.85, 1.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 0.99 (0.85, 1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 1.13 (0.99, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.73, 1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 0.70 (0.49, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 1.04 (0.77, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71 (0.46, 1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 0.84 (0.62, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 0.43 (0.28, 0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77 (1.07, 2.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuicide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 0.84 (0.56, 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 1.36 (0.99, 1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.42, 1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCL: Camp Lejeune\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCP: Camp Pendleton\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSMR: Standardized mortality ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCI: Confidence interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCNS: Central nervous system cancers\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNHL: Non-Hodgkin lymphoma\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eALS: Amyotrophic Lateral Sclerosis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCOPD: Chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSMRs were calculated using the age-, sex-, race- and calendar period-specific U.S. mortality rates for underlying causes of death.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eRisk ratios were adjusted for sex, race, and five-year age groups.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe unadjusted and adjusted HRs for underlying cause of death from the Cox proportional hazards regressions comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The adjusted HR for all cancer malignancies was 1.05 (95% CI: 1.02, 1.08). Adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for cancers of the kidney (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.95, 1.54), esophagus (HR\u0026thinsp;=\u0026thinsp;1.24, 95% CI: 1.00, 1.54), and female breast cancer (HR\u0026thinsp;=\u0026thinsp;1.20, 95% CI: 0.73, 1.98). HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included Parkinson disease, myelodysplastic syndrome, and cancers of the testes, cervix, and ovary.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHazard ratios (HR) and 95% confidence intervals (CI) for the Marines/Navy personnel subgroup analysis of base location at Camp Lejeune (CL) vs. Camp Pendleton (CP); Underlying cause of death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Lejeune #\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCamp Pendleton #\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98(0.96, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99(0.97, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21,134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cancer malignancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06(1.01, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06(1.02, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92(0.71, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.73, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharyngeal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93(0.65, 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94(0.66, 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophageal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20(0.97, 1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.24 (1.00, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomach cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96(0.72, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92(0.69, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05(0.91, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03(0.88, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09(0.92, 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.05(0.89, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95(0.71, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94(0.70, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.85, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06(0.89, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14(0.96, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14(0.96, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaryngeal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.64, 1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01(0.64, 1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16(1.06, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18(1.07, 1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71(0.38, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74(0.39, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft tissue cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14(0.77, 1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12(0.76, 1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03(0.79, 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07(0.82, 1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale Breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27(0.77, 2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20 (0.73, 1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale Breast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39(0.13, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36 (0.12, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19(0.39, 3.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25 (0.40, 3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterine cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62(0.20, 1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62 (0.20, 1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvarian cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(0.39, 3.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23 (0.42, 3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97(0.74, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.71, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTesticular cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.62(0.78, 3.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.76 (0.85, 3.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBladder cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.71, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02(0.72, 1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19(0.93, 1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.21(0.95, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain and CNS cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88(0.72, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89(0.73, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71(0.29, 1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71(0.29, 1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematopoietic cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.86, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99(0.86, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.61, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98(0.59, 1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87(0.68, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87(0.68, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple myeloma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10(0.77, 1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07(0.75, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(0.89, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10(0.87, 1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85(0.47, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85(0.47, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94(0.34, 2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89(0.32, 2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(0.78, 1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11(0.78, 1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69(0.32, 1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65(0.30, 1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.96(0.73, 5.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.26(0.83, 6.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Lejeune #\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCamp Pendleton #\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoid cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82(0.50, 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80(0.49, 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyeloid cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(0.82, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10(0.80, 1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96(0.84, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96(0.83, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.46, 2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89(0.41, 1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.96, 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99(0.95, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.95, 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99(0.94, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08(0.95, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.05(0.92, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirculatory diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.86, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.82, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e402\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06(0.91, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.08(0.93, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85(0.77, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93(0.83, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.78, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93(0.84, 1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholic Liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79(0.69, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86(0.76, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonalcoholic Liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98(0.82, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.06(0.89, 1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81(0.44, 1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81(0.44, 1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03(0.82, 1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96(0.75, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.09(0.89, 4.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.05(0.86, 4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03(0.73, 1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04(0.73, 1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18(0.70, 1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18(0.70, 2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.72, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.90(0.76, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuicide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88(0.83, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93(0.87, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCL\u0026thinsp;=\u0026thinsp;159,128 Males\u0026thinsp;=\u0026thinsp;151,026 Females\u0026thinsp;=\u0026thinsp;8,102\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCP\u0026thinsp;=\u0026thinsp;168,406 Males\u0026thinsp;=\u0026thinsp;162,473 Females\u0026thinsp;=\u0026thinsp;5,933\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTotal\u0026thinsp;=\u0026thinsp;327,534 Males\u0026thinsp;=\u0026thinsp;313,499 Females\u0026thinsp;=\u0026thinsp;14,035\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCOPD: chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eALS: amyotrophic lateral sclerosis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMDS: myelodysplastic syndrome\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCML: chronic myeloid leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAML: acute myeloid leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCLL: chronic lymphocytic leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eALL: acute lymphocytic leukema\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCNS: central nervous system\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eHRs adjusted for sex, race, rank and education level; age was the time variable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the analyses of the full cohort of Marines/Navy personnel, in addition to causes listed above, additional underlying causes of death with adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 included acute myeloid leukemia (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.94, 1.56), Hodgkin lymphoma (HR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 0.82, 1.90), multiple sclerosis (HR\u0026thinsp;=\u0026thinsp;1.37, 95% CI: 0.92, 2.06) and acute kidney disease (HR\u0026thinsp;=\u0026thinsp;1.32, 95% CI: 0.91, 1.90) (Supplemental file, Table S3).\u003c/p\u003e \u003cp\u003eEvaluation of contributing causes of death in the Marines/Navy personnel subgroup, comparing Camp Lejeune with Camp Pendleton, is presented in (Supplemental file, Table S5).. The findings were generally similar to the subgroup analyses of underlying causes from Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, with no additional causes of death having HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 except for multiple sclerosis (HR\u0026thinsp;=\u0026thinsp;1.29, 95% CI: 0.83, 2.01). Evaluation of contributing causes of death in the full cohort of Marines/Navy personnel observed an HR for male breast cancer of 1.27 but with CIR\u0026thinsp;\u0026gt;\u0026thinsp;3 (95% CI: 0.61, 2.64) (Supplemental file, Table S4).\u003c/p\u003e \u003cp\u003eAnalysis of the Marines/Navy personnel subgroup, for underlying cause of death and duration stationed between 1975 and 1985 at Camp Lejeune compared with Camp Pendleton as the reference group is presented in (Supplemental file, Table S6). The categorical levels of duration were approximately tertiles of the data after removal of the reference group. Since the DMDC data is quarterly, the levels of the categorical variable consisted of the number of quarters the individual was stationed at Camp Lejeune: \u0026ldquo;low\u0026rdquo; duration (1\u0026ndash;2 quarters), \u0026ldquo;medium\u0026rdquo; duration (\u0026gt;\u0026thinsp;2\u0026ndash;7 quarters), and \u0026ldquo;high\u0026rdquo; duration (\u0026gt;\u0026thinsp;7 quarters). A monotonic trend was observed for myelodysplastic syndrome, with the adjusted HR ranging from 1.77 (95% CI: 0.44, 7.11) in the low duration to 3.11 (95% CI: 0.86, 11.20) in the high duration strata. CIRs at all durations were \u0026gt;\u0026thinsp;3. Other underlying causes of death with monotonic trends were non-alcoholic liver disease (low duration HR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 0.79, 1.34); high duration HR\u0026thinsp;=\u0026thinsp;1.18, 95% CI: 0.81, 1.52) and pancreatic cancer (low duration HR\u0026thinsp;=\u0026thinsp;1.11, 95% CI: 0.86, 1.43; high duration HR\u0026thinsp;=\u0026thinsp;1.15, 95% CI: 1.01, 1.30), both with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3.\u003c/p\u003e \u003cp\u003eThe unadjusted and adjusted HRs from the Cox proportional hazards regressions for underlying cause of death comparing the Camp Lejeune versus Camp Pendleton civilian workers are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for chronic kidney disease (HR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.13, 3.11) and Parkinson disease (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.72, 2.04). An HR of 1.19 was observed for female breast cancer (95% CI: 0.76, 1.88). Other underlying causes of death with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included cancers of the kidney and pharynx, melanoma, Hodgkin lymphoma, chronic myeloid leukemia (CML), and anemias.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Camp Lejeune (CL) and Camp Pendleton (CP) civilian workers: Underlying cause of death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Lejeune #\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCamp Pendleton #\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.91, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96(0.91, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,280\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.91, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00(0.91, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll malignancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98(0.90, 1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00(0.91, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00(0.42, 2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03(0.41, 2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.02(0.61, 6.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.21(0.63, 7.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophagus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54(0.28, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.63(0.31, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98(0.53, 1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92(0.48, 1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.61, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86(0.59, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85(0.57, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85(0.56, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectum and\u003c/p\u003e \u003cp\u003eRectosigmoid junction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93(0.43, 1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.43, 2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRectum only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87(0.34, 2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84(0.31, 2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver, biliary, gall bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71(0.40, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77(0.43, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver and bile ducts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75(0.39, 1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80(0.41, 1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary liver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68(0.24, 1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87(0.31, 2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64(0.43, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71(0.47, 1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarynx\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.52(0.50, 4.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19(0.37, 3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10(0.94, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13(0.96, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrinary bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78(0.43, 1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65(0.34, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56(0.82, 2.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44(0.73, 2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain and CNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58(0.32, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61(0.33, 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnective tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81(0.25, 2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60(0.17, 2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.42(0.85, 6.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.03(1.05, 8.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematopoietic cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95(0.70, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00(0.73, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoid cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57(0.21, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84(0.30, 2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyeloid cancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89(0.48, 1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98(0.51, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48(0.25, 8.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.65(0.27, 9.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hodgkin lymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97(0.61, 1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.59, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple myeloma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11(0.53, 2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02 (0.47, 2.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85(0.53, 1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00(0.61, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68(0.22. 2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85(0.27, 2.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93(0.46, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97(0.47, 2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.25, 3.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26(0.29, 5.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale Breast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (0.79, 1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19 (0.76, 1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUterus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.41, 2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99 (0.39, 2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.29, 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60 (0.30, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32 (0.93, 1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03 (0.71, 1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94(0.71, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81(0.60, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91(0.84, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91(0.83, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamp Lejeune #\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCamp Pendleton #\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemias\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.38(0.61, 9.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.91(0.48, 7.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64(0.42, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74(0.48, 1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43(0.24, 0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54(0.29, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonalcoholic liver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04(0.54, 2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11(0.57, 2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63(0.24, 1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67(0.24, 1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04(1.27, 3.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.88(1.13, 3.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.70, 1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91(0.74, 1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97(0.19, 4.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83(0.16, 4.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmyotrophic Lateral Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50(0.17, 1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44(0.15, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParkinson disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09(0.66, 1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.21(0.72, 2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuicide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59(0.37, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72(0.45, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eHR: hazard ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCNS: Central nervous system cancers\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCLL: Chronic lymphcytic leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAML: Acute myeloid leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCML: Chronic myeloid leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCOPD: Chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTotals:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCamp Lejeune\u0026thinsp;=\u0026thinsp;7,332 Females\u0026thinsp;=\u0026thinsp;3,624 Males\u0026thinsp;=\u0026thinsp;3,708\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCamp Pendleton\u0026thinsp;=\u0026thinsp;6,677 Females\u0026thinsp;=\u0026thinsp;3,031 Males\u0026thinsp;=\u0026thinsp;3,646\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCauses of death that were not evaluated because the number of cases were \u0026lt;\u0026thinsp;2 for CL and/or CP:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eTesticular cancer\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMale breast cancer\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eThyroid cancer\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAcute lymphocytic leukemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eHRs adjusted for sex, race, blue collar work (y/n) and education level; age was the time variable.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe unadjusted and adjusted HRs from the Cox proportional hazards regressions for contributing causes of death comparing the Camp Lejeune versus Camp Pendleton civilian workers are shown in Supplemental file, Table S7). An adjusted HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIR\u0026thinsp;\u0026le;\u0026thinsp;3 was observed for female breast cancer (HR\u0026thinsp;=\u0026thinsp;1.33, 95% CI: 0.87, 2.03). Other contributing causes of death with adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included cancers of the pharynx and larynx, melanoma, Hodgkin lymphoma, and CML.\u003c/p\u003e \u003cp\u003eAnalysis of underlying causes of death and duration of employment at Camp Lejeune between October 1972 and December 1985 with Camp Pendleton as the referent group is shown in Supplemental file, Table S8. The categorical levels of duration were approximately tertiles of the data after removal of the reference group. Since the DMDC data is quarterly, the levels of the categorical variable consisted of the number of quarters the worker was employed at Camp Lejeune: \u0026ldquo;low\u0026rdquo; duration (1\u0026ndash;5 quarters), \u0026ldquo;medium\u0026rdquo; duration (6\u0026ndash;22 quarters), and \u0026ldquo;high\u0026rdquo; duration (\u0026ge;\u0026thinsp;23 quarters). A monotonic trend was observed for kidney cancer, with low duration HR of 1.36 (95% CI: 0.48, 3.82) and high duration HR of 1.68 (95% CI: 0.75, 3.76) and CIR\u0026thinsp;\u0026gt;\u0026thinsp;3 across all durations.\u003c/p\u003e \u003cp\u003eThe negative control diseases for alcohol consumption were alcoholism, alcoholic liver disease and chronic liver diseases. The negative control diseases for smoking were COPD and cardiovascular disease. In the analyses of underlying and contributing causes of death comparing Camp Lejeune and Camp Pendleton Marines/Navy personnel in the subgroup (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; Supplemental file, Table S5), COPD as an underlying cause had an HR of 1.08 (95% CI: 0.93, 1.27) and CIR\u0026thinsp;\u0026le;\u0026thinsp;3. All other negative control diseases for smoking and alcohol consumption had HRs\u0026thinsp;\u0026lt;\u0026thinsp;1.00. In the analyses of underlying and contributing causes of death comparing Camp Lejeune and Camp Pendleton civilian workers (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e; Supplemental file, Table S7 ), COPD as a contributing cause had an HR of 1.04 (95% CI: 0.91, 1.20) and CIR\u0026thinsp;\u0026le;\u0026thinsp;3. All other negative control diseases for smoking and alcohol consumption had HRs\u0026thinsp;\u0026lt;\u0026thinsp;1.00.\u003c/p\u003e \u003cp\u003eThe findings for the negative control diseases for alcohol consumption and smoking suggest that the prevalence of smoking and alcohol consumption were not greater at Camp Lejeune compared to Camp Pendleton. Even though the HRs for COPD were slightly greater than 1.00 for the Marines/Navy personnel and civilian workers, the cardiovascular disease HRs were \u0026lt;\u0026thinsp;1.00. Moreover, the HRs for all the negative control diseases for alcohol consumption were \u0026lt;\u0026thinsp;1.00. To evaluate the impact of possible confounding due to smoking and alcohol consumption, quantitative bias analyses were conducted using the results for COPD (smoking) and chronic liver disease (alcohol use).\u003c/p\u003e \u003cp\u003eTo fully explain the HR for COPD of 1.08, the difference in smoking prevalence between Camp Lejeune and Camp Pendleton Marines/Navy personnel would be about 6%, assuming a range of RRs between 3.00 and 5.50 for smoking and COPD mortality [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] (Supplemental file, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). (Assuming a higher RR for smoking and COPD would decrease the difference in smoking prevalence between Camp Lejeune and Camp Pendleton and would therefore reduce the potential impact of confounding due to smoking in this study.) Assuming a 6% difference in smoking prevalence and a range of RRs for smoking and kidney cancer between 1.25 and 1.75 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], the observed adjusted HR for kidney cancer of 1.21 would be reduced to between 1.17 and 1.18, a change of about 3.3% (Supplemental file, Figure S2). Assuming a range of RRs for smoking and esophageal cancer between 1.5 and 3.5 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], the observed adjusted HR of 1.24 would be reduced to between 1.17 and 1.21, a change of no more than 5.6% (Supplemental file, Figure S3).\u003c/p\u003e \u003cp\u003eSmoking has been observed to decrease the risk of Parkinson disease [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Adjusting for smoking, the observed adjusted HR of 2.05 would increase to between 2.07 and 2.12, a change of no more than 3.4% (Supplemental file, Figure S4). Finally, since smoking is a strong risk factor for lung cancer, the impact of adjusting for smoking on the observed adjusted HR for lung cancer should be the greatest. Assuming a 6% prevalence difference in smoking and assuming that the RR for smoking and lung cancer ranges between 7.00 and 12.00 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], the observed adjusted HR of 1.18 for lung cancer as an underlying cause would be reduced to between 1.07 and 1.08, a change of no more than 9.3% (Supplemental file, Figure S5).\u003c/p\u003e \u003cp\u003eFor smoking to fully explain the HR for COPD of 1.04, the difference in smoking prevalence between the Camp Lejeune and Camp Pendleton civilian workers would be no more than 3% (Supplemental file, Figure S6). Adjusting for a smoking prevalence difference of 3% and assuming RRs for smoking and cancers of the lung and larynx ranging between 7.00 and 12.00 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], the underlying cause HRs of 1.13 for lung cancer and 1.19 for laryngeal cancer would decrease no more than about 5.3% (Supplemental file, Figures S7 to S8). The HR for laryngeal cancer as a contributing cause of 1.69 would also decrease by no more than 5.3% (Supplemental file, Figure S9). The adjusted HR for cancer of the pharynx as an underlying cause would decrease from 2.21 to 2.10, assuming the RR for smoking and cancer of the pharynx ranges from 5.0 to 7.5 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] (Supplemental file, Figure S10). Assuming RRs for smoking and kidney cancer and chronic kidney disease ranging from 1.30 to 1.80 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], the underlying cause HRs of 1.44 for kidney cancer and 1.88 chronic kidney disease would decrease by no more than about 2% (Supplemental file, Figures S11 to S12).\u003c/p\u003e \u003cp\u003eAdjusting for smoking and assuming RRs for smoking and Parkinson disease ranging between 0.40 and 0.90, the underlying cause HR for Parkinson disease of 1.21 would increase by no more than 2.5% (Supplemental file, Figure S13).\u003c/p\u003e \u003cp\u003eFor the subgroup of Marines/Navy personnel, the adjusted HRs for chronic liver disease mortality as an underlying and contributing cause were 0.93 and 0.88, respectively. A recent systematic review of alcohol consumption and mortality due to liver cirrhosis found RRs of 2.65, 6.83 and 16.38 for drinking 25g/day (2 drinks/day), 50g/day (4 drinks/day) and 100g/day (8 drinks/day) compared to those who never drank alcoholic beverages [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. A military survey conducted in 1980 found that about 30% of Marines were heavy drinkers defined as drinking five or more drinks per typical drinking occasion at least once a week in the past 30 days. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo determine what prevalence differences in alcohol consumption between Camp Lejeune and Camp Pendleton Marines/Navy personnel would be necessary to fully explain the chronic liver disease mortality HRs of 0.93 and 0.88, a quantitative bias analysis was conducted assuming that at least 2/3 of Marines/Navy personnel at Camp Lejeune consumed\u0026thinsp;\u0026ge;\u0026thinsp;1 drink/day. It was also assumed that the RRs for alcohol consumption and chronic liver disease mortality ranged between 2.5 and 10 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. To fully explain the RRs of 0.93 and 0.88, the prevalence differences would range between 6% and 10% and between 11% and 16%, respectively (Supplemental file, Figures S14 to S15). (Assuming a lower percentage of Camp Lejeune drinkers would decrease the prevalence difference range, e.g., if only half the Marines/Navy personnel at Camp Lejeune were drinkers, then the percentage difference ranges would be 5% \u0026minus;\u0026thinsp;9% and 9% -15% for chronic liver disease mortality as underlying cause and as contributing cause, respectively.)\u003c/p\u003e \u003cp\u003eAdjusting for an alcohol prevalence difference of 10% between Camp Lejeune and Camp Pendleton Marines/Navy personnel, and assuming RRs for alcohol consumption and esophageal cancer ranging from 1.25 to 5.25 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], the HR of 1.24 for esophageal cancer as an underlying cause would increase to between 1.27 and 1.38 (Supplemental file, Figure S16). The HR of 1.14 for laryngeal cancer as a contributing cause would increase to between 1.15 and 1.23 (Supplemental file, Figure S17). The female breast cancer HR of 1.20 as an underlying cause would increase to between 1.21 and 1.26 (Supplemental file, Figure S18).\u003c/p\u003e \u003cp\u003eFor the civilian workers, the adjusted HR for chronic liver disease mortality as an underlying cause was 0.74. To fully explain this HR, the prevalence difference in alcohol consumption between Camp Lejeune and Camp Pendleton workers would range between 15% and 25%, assuming that about 1/3 of the Camp Lejeune workers consumed\u0026thinsp;\u0026ge;\u0026thinsp;1 drink/day and assuming that the range of RRs for alcohol consumption and chronic liver disease mortality range between 2.5 and 10 (Supplemental file, Figure S19). (Assuming that only 20% of Camp Lejeune workers consumed\u0026thinsp;\u0026ge;\u0026thinsp;1 drink/day, the prevalence difference would range from 11\u0026ndash;21%. Assuming a higher percentage of Camp Lejeune drinkers would increase the prevalence difference range, e.g., if 50% of Camp Lejeune workers consumed\u0026thinsp;\u0026ge;\u0026thinsp;1 drink/day, the prevalence difference would range from 21\u0026ndash;31%.)\u003c/p\u003e \u003cp\u003eAdjusting for an alcohol prevalence difference of 15% between Camp Lejeune and Camp Pendleton workers, the HR of 1.12 for oral cancers as a contributing cause would increase to between 1.13 and 1.41; the HR of 1.19 for laryngeal cancer as an underlying cause would increase to between 1.20 and 1.40; the HR of 2.21 for pharyngeal cancer as an underlying cause would increase to between 2.24 and 2.79; and the HR of 1.19 for female breast cancer as an underlying cause would increase to between 1.20 and 1.27 (Supplemental file, Figures S20-S23).\u003c/p\u003e \u003cp\u003eThe impact of non-differential exposure misclassification on the adjusted HRs for the Marines/Navy personnel and civilian workers assumed that between 10% and 25% of those assigned to Camp Lejeune were truly unexposed and virtually none of those assigned to Camp Pendleton were truly exposed (Supplemental file, Tables S9-S10).\u003c/p\u003e \u003cp\u003eFor underlying cause of death in the Marines/Navy personnel subgroup, after accounting for exposure misclassification the observed adjusted HR for kidney cancer of 1.21 would increase to between 1.23 and 1.27, a change of no more than 5% (Supplemental file, Table S9). For esophageal cancer, the observed adjusted HR of 1.24 would increase to between 1.27 and 1.32, a change of no more than 6.5%. For Parkinson disease, the observed adjusted HR of 2.05 would increase to between 2.17 and 2.40, a change of no more than 17%. For lung cancer, the observed adjusted HR of 1.18 would increase to between 1.20 and 1.23, a change of no more than 4.2%.\u003c/p\u003e \u003cp\u003eFor civilian workers, adjusting for non-differential exposure misclassification would increase the underlying cause HRs for lung cancer and female breast cancer by no more than about 3% (Supplemental file, Table S10). However, the underlying cause HR for kidney cancer would increase between 6.3% and 12.5%, and the underlying cause HR for chronic kidney disease would increase between 4.8% and 13.3%. The underlying cause HR for Parkinson disease would increase between 2.5% and 5% and the contributing cause HR for female breast cancer would increase between 2.3% and 6%.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cohort study evaluated whether Marines/Navy personnel and civilian workers stationed or employed at Camp Lejeune between 1975 and 1985 (Marines/Navy personnel) or between October 1972 and December 1985 (civilian workers), a portion of the period when the drinking water was contaminated, had increased risks for specific causes of death during the follow-up period between 1979 and 2018. The focus of the study was on the Cox regression analysis of underlying cause of death occurring among civilian workers and the Marines/Navy personnel subgroup, comparing Camp Lejeune versus Camp Pendleton. Secondary analyses evaluated (1) duration stationed or employed at Camp Lejeune, (2) contributory causes of death, and (3) underlying and contributing causes of death in the full cohort of Marines/Navy personnel. The possible impact of unmeasured confounders and non-differential exposure misclassification bias on the HRs for underlying cause of death were evaluated.\u003c/p\u003e \u003cp\u003eThe analyses of Marines/Navy personnel focused on the subgroup because the full cohort was more likely than the subgroup to be impacted by non-differential exposure misclassification bias due to the lack of information on an individual\u0026rsquo;s base location prior to 1975. However, the analysis of the full cohort had the advantage of greater numbers of individuals and therefore more deaths, as well as being much older than the individuals in the subgroup. In the full cohort, nearly 12% were above the age of 65 at the end of follow-up compared to less than 2% in the subgroup. Therefore, for those rare causes of death primarily occurring among older populations, the full cohort analyses might have provided more useful information than the subgroup analyses. However, over a quarter of the individuals in the full cohort were 55 years of age or younger, and nearly 90% were 65 years of age or younger, indicating that the full cohort represents a relatively young population for evaluating mortality.\u003c/p\u003e \u003cp\u003eIn the Marines/Navy personnel subgroup analysis of underlying cause of death comparing Camp Lejeune versus Camp Pendleton, adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for cancers of the kidney, esophagus, and female breast. HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included Parkinson disease, myelodysplastic syndrome, and cancers of the testes, cervix, and ovary. In the analyses of the full cohort of Marines/Navy personnel, additional underlying causes of death with adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 included acute myeloid leukemia, Hodgkin lymphoma, multiple sclerosis, and acute kidney disease. Male breast cancer had an adjusted HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIR\u0026thinsp;\u0026gt;\u0026thinsp;3 in the analysis of contributory causes of death in the full cohort analysis.\u003c/p\u003e \u003cp\u003eIn the analysis of civilian workers comparing Camp Lejeune versus Camp Pendleton, HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 were observed for chronic kidney disease and Parkinson disease as underlying causes and female breast cancer as a contributing cause. Other underlying causes with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 due to small number of cases included cancers of the kidney and pharynx, melanoma, Hodgkin lymphoma, CML and anemias. Laryngeal cancer had a RR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 in the Poisson regression analysis of underlying causes and a HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 as a contributing cause, but CIRs for these estimates were \u0026gt;\u0026thinsp;3.\u003c/p\u003e \u003cp\u003eThe analysis of duration at Camp Lejeune assumed that contamination levels did not fluctuate greatly each month. However, the estimated monthly average contaminant levels for TCE and PCE in the HP distribution system, and for PCE in the TT distribution system varied widely between 1972 and 1985. Therefore, the results of the duration analysis should be interpreted with caution.\u003c/p\u003e \u003cp\u003eIn the Marines/Navy personnel subgroup analysis of duration at Camp Lejeune with Camp Pendleton as the reference group, a monotonic trend was observed for myelodysplastic syndrome, with a HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 in the high duration stratum and CIR\u0026thinsp;\u0026gt;\u0026thinsp;3. Other causes of death with monotonic trends but with HRs\u0026thinsp;\u0026lt;\u0026thinsp;1.20 in the high duration stratum were non-alcoholic liver disease and pancreatic cancer. In the analysis of civilian workers\u0026rsquo; duration of employment at Camp Lejeune, a monotonic trend was observed for kidney cancer with an HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 in the high duration category but with CIR\u0026thinsp;\u0026gt;\u0026thinsp;3.\u003c/p\u003e \u003cp\u003eHRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 were observed for cancers of the kidney and female breast and for Parkinson disease in the analyses of Marines/Navy personnel and civilian workers. HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 were also observed for kidney cancer in the previous mortality studies of Marines/Navy personnel and civilian workers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. TCE exposure is a known cause of kidney cancer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome occupational studies of female breast cancer incidence and mortality have not supported a causal association with exposures to TCE, PCE, vinyl chloride, or benzene [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, one case-control study found an increased risk of female breast cancer among pre-menopausal women who predominantly worked in dry cleaning [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Exposure to PCE-contaminated drinking water at Cape Cod, MA found an increased risk for breast cancer among women with the highest cumulative exposures [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Two recently published occupational studies of female breast cancer provide support for a causal association with TCE and/or PCE exposure [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. A study in Taiwan found elevated risks for female breast cancer among workers exposed to TCE/PCE and benzene [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A case-control study of postmenopausal women found increased odds ratios for occupationally ever exposed to benzene and PCE and postmenopausal breast cancer ranging between 1.18 and 1.32 and between 1.92 and 2.83, respectively but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current evidence for a causal association between TCE exposure and Parkinson disease is at least as likely as not or greater [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Animal studies support a causal association between TCE and Parkinson disease, showing that TCE exposure reproduces key pathological features of the disease including \u0026ldquo;\u0026hellip;mitochondrial impairment, intraneuronal aggregation of phosphorylated α-synuclein protein, and regionally specific degeneration of nigrostriatal dopaminergic neurons.\u0026rdquo; [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. An increased risk of Parkinson disease was also observed in the previous mortality study of civilian workers but could not be evaluated in the previous mortality study of Marines/Navy personnel due to a lack of cases [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 were observed for cancers of the esophagus and cervix in the previous mortality studies of Marines/Navy personnel at Camp Lejeune [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study, the HR for esophageal cancer in Marines/Navy personnel was 1.24 with CIR\u0026thinsp;\u0026le;\u0026thinsp;3 (95% CI: 1.00, 1.54), and for cervical cancer the HR was 1.25 with CIR\u0026thinsp;\u0026gt;\u0026thinsp;3 (95% CI: 0.40, 3.85). The current evidence for causal associations between esophageal and cervical cancers and TCE, PCE, vinyl chloride or benzene exposures is not strong [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 were observed for Hodgkin lymphoma in the previous mortality study of Marines/Navy personnel [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and in the current study of the Marines/Navy full cohort (HR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 0.82, 1.90). For civilian workers, the observed HR for Hodgkin lymphoma in this study was 1.65 (95% CI: 0.27, 9.96) based on \u0026le;\u0026thinsp;3 cases at each base. The previous mortality study of civilian workers could not evaluate Hodgkin lymphoma because of a lack of cases [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. There is no information in the scientific literature indicating whether exposures to TCE, PCE, vinyl chloride or benzene are associated with Hodgkin lymphoma.\u003c/p\u003e \u003cp\u003eAn HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 was observed for multiple sclerosis in the previous mortality study of Marines/Navy personnel [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The current study observed a HR of 1.37 (95% CI: 0.92, 2.06) in the full cohort of Marines/Navy personnel. Exposure to organic solvents has been associated with multiple sclerosis, although exposure to specific organic solvents has not been studied [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMortality due to myelodysplastic syndrome, acute myeloid leukemia, and cancers of the testes and ovary were not evaluated in the previous Camp Lejeune mortality study of Marines/Navy personnel [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The current study found HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 for myelodysplastic syndrome (HR\u0026thinsp;=\u0026thinsp;2.26, 95% CI: 0.83, 6.17), testicular cancer (HR\u0026thinsp;=\u0026thinsp;1.76, 95% CI: 0.85, 3.67) and ovarian cancer (HR\u0026thinsp;=\u0026thinsp;1.23, 95% CI: 0.42, 3.59) in Marines/Navy personnel subgroup. In the full cohort analysis, acute myeloid leukemia was observed to have a HR of 1.21 (95% CI: 0.94, 1.56). Benzene exposure has been associated with myelodysplastic syndrome [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and is a known cause of acute myeloid leukemia [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The current evidence for causal associations between occupational or environmental exposures to TCE, PCE, vinyl chloride or benzene and the risks of mortality from cancers of the testes and ovary is not strong [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn HR of 1.27, but with CIR\u0026thinsp;\u0026gt;\u0026thinsp;3 (95% CI: 0.61, 2.64), was observed for male breast cancer as a contributing cause in the analysis of the full cohort of Marines/Navy personnel. A previous case-control study of male breast cancer incidence found an increased risk among Camp Lejeune Marines compared to Marines from all other bases [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Occupational TCE exposure has been associated with male breast cancer in three studies [\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 was observed for chronic kidney disease (HR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.13, 3.11) in the analysis of the civilian workers but not Marines/Navy personnel. An HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 was observed for acute kidney disease in the analysis of the full cohort of Marines/Navy personnel (HR\u0026thinsp;=\u0026thinsp;1.32, 95% CI: 0.91, 1.90). The EPA toxicological reviews of TCE and PCE indicated that both epidemiological and animal studies support associations between TCE or PCE exposure and chronic kidney disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The current evidence for a causal association between kidney diseases and occupational exposures to TCE or PCE is at least as likely as not or greater [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 were observed for cancers of the pharynx and larynx in the analysis of the civilian workers, but HRs\u0026thinsp;\u0026lt;\u0026thinsp;1.20 were observed in the analyses of Marines/Navy personnel. Two studies of head and neck cancers in men and women and occupational exposures to solvents found associations between occupational exposures to PCE and/or TCE and cancers of the larynx and pharynx [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the previous mortality study of Camp Lejeune civilian workers, an HR\u0026thinsp;\u0026ge;\u0026thinsp;1.20 was observed for oral cavity cancers, which included cancer of the pharynx [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOther causes of death with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 in the analysis of the civilian workers were chronic myeloid leukemia (HR\u0026thinsp;=\u0026thinsp;1.26, 95% CI: 0.29, 5.48), melanoma (HR\u0026thinsp;=\u0026thinsp;3.03, 95% CI: 1.05, 8.76) and anemias (HR\u0026thinsp;=\u0026thinsp;1.91, 95% CI: 0.48, 7.65). One study found an association between \u0026ldquo;substantial\u0026rdquo; occupational exposure to TCE and melanoma (OR\u0026thinsp;=\u0026thinsp;3.2, 95% CI: 1.0, 9.9), but precision was poor [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Two of the anemias were aplastic anemia, both among Camp Lejeune civilian workers. Benzene is a known cause of aplastic anemia [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The results of a meta-analysis provided support for a causal association between benzene occupational exposure and chronic myeloid leukemia [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. A more recent study found an excess of chronic myeloid leukemia among benzene workers in China [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study did not include information on important risk factors such as smoking and alcohol consumption as these data were unavailable. However, confounding due to failure to adjust for unmeasured risk factors was likely to be minor because of the demographic and socio-economic similarity of the Camp Lejeune and Camp Pendleton cohorts. The prevalence of smoking and \u0026ldquo;heavy alcohol\u0026rdquo; consumption among Marines in 1980 was estimated at 53.4% and 28.6%, respectively [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Smoking and alcohol consumption among Marines at both Camp Lejeune and Camp Pendleton were encouraged by the military culture, the stress of service, targeted advertising by the tobacco and alcoholic beverage industry, and the lower cost and tax-free availability of these products on base compared to civilian stores off-base [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe negative control diseases for alcohol consumption were mortality due to alcoholism, alcoholic liver disease, and chronic liver disease. All of the HRs for these diseases were less than 1.00, indicating that the prevalence and amount of alcohol consumption among Camp Lejeune Marines/Navy personnel and civilian workers were not greater than at Camp Pendleton.\u003c/p\u003e \u003cp\u003eThe negative control diseases for smoking selected in this study were mortality due to COPD and cardiovascular disease. The HRs for cardiovascular disease in this study were \u0026lt;\u0026thinsp;1.00. However, the HRs for COPD as an underlying cause in the subgroup analysis of Marines/Navy personnel and as a contributing cause in the analysis of civilian workers were 1.08 and 1.04, respectively. For smoking to fully explain the COPD adjusted HRs of 1.08 in the Marines/Navy personnel analysis and 1.04 in the civilian worker analysis, the differences in smoking prevalence between the two bases would need to be 6% and 3%, respectively, assuming a range of RRs between 3.00 and 5.50 for smoking and COPD mortality [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the subgroup analysis of Marines/Navy personnel, other smoking related cancers that had HRs less than or close to 1.00 included cancers of the larynx, oral cavity, pharynx, colorectal, and bladder. These results suggested that there was little, if any, difference in the prevalence of smoking between Camp Lejeune and Camp Pendleton Marines/Navy personnel. In the analysis of civilian workers, esophageal cancer and oral cancers other than pharyngeal cancer were less than or close to 1.00, suggesting that there was little difference in the prevalence of smoking between Camp Lejeune and Camp Pendleton civilian workers.\u003c/p\u003e \u003cp\u003eSmoking-related cancers such as cancer of the lung, larynx and pharynx had HRs\u0026thinsp;\u0026gt;\u0026thinsp;1.00 but were not considered negative controls because of evidence linking them to TCE or PCE occupational exposures. For smoking to fully explain the lung cancer adjusted HRs of 1.18 and 1.13 in the analyses of Marines/Navy personnel and civilian workers, respectively, the difference in smoking prevalence between the two bases of 11% (Marines/Navy personnel) and 8% (civilian workers) would be necessary. The adjusted HR of 1.19 for cancer of the larynx in the analysis of civilian workers would require a smoking prevalence difference of at least 12% between the two bases. Smoking prevalence differences of these magnitudes were unlikely given the results for the negative control diseases for smoking.\u003c/p\u003e \u003cp\u003eAssuming a 6% prevalence difference in smoking between Camp Lejeune and Camp Pendleton Marines/Navy personnel based on the result for COPD, the impact of adjusting for smoking on the HRs for kidney cancer, esophageal cancer and Parkinson disease would be less than 6%, and for lung cancer, no more than 9.3%. Using a 3% smoking prevalence difference between Camp Lejeune and Camp Pendleton civilian workers, based on the result for COPD, would reduce the HRs for cancers of the lung, pharynx, and larynx by no more than 5.3%. The HRs for kidney cancer and chronic kidney disease would be reduced by no more than 2%. The HR for Parkinson disease would increase by about 2.5%.\u003c/p\u003e \u003cp\u003eThe findings for the negative control diseases for alcohol consumption, i.e., mortality due to alcoholism, alcoholic liver disease and chronic liver disease, suggest that Camp Lejeune Marines/Navy personnel and civilian workers had a lower prevalence of alcohol use than Camp Pendleton. The findings for these negative controls suggest that possible confounding due to alcohol consumption might have biased HRs towards the null for alcohol-related cancers such as oral cancers and cancers of the pharynx, esophagus, larynx, and female breast. For cancers that are both smoking-related and alcohol-related such as oral cancers and cancers of the pharynx, larynx, esophagus, adjusting for possible differences in alcohol consumption between the two bases might cancel out the impact of adjusting for possible smoking differences between the two bases (Supplemental file, Figures S3, S8-S10, S16-S17, S20-S22).\u003c/p\u003e \u003cp\u003eThe quantitative bias analysis of the impact of non-differential exposure misclassification assumed that between 10% and 25% of those assigned to Camp Lejeune were truly unexposed and virtually none of those assigned to Camp Pendleton were truly exposed. For the Marines/Navy personnel, the increases in the HRs after adjusting for this bias ranged from no more than 4.2% for lung cancer to no more than 17% for Parkinson disease. For civilian workers, the increases in the HRs ranged between 2% and 13%. These results suggested that for cancers and other causes of death that are smoking-related, the bias due to non-differential exposure misclassification in this study may cancel out the potential confounding bias due to smoking. For causes of death that are not smoking-related, it is likely that exposure misclassification had at least as large an impact in this study as potential confounding due to unmeasured risk factors other than smoking.\u003c/p\u003e \u003cp\u003eThis study had several strengths including a large number of individuals and causes of death, 40 years of follow-up, a comparison USMC base with similar demographic characteristics and other risk factors as Camp Lejeune, a small percentage of individuals lost to follow-up, and a majority of civilian workers over the age of 65 years by the end of follow-up. However, there were limitations such as: (1) a majority of the individuals in the Marines/Navy personnel subgroup were under 60 years of age at the end of follow-up which reduced the number of deaths for each cause; (2) the poor precision of the HRs for some of the causes of death in the analysis of civilian workers due at least in part to small numbers of cases; (3) the potential for exposure misclassification bias in the analyses of Marines/Navy personnel and civilian workers, and (4) the potential for confounding bias due to unmeasured risk factors such as smoking, alcohol consumption, and occupational exposures before or after military service or employment at the two bases.\u003c/p\u003e \u003cp\u003eDisease misclassification bias (both false positives and false negatives) was also a possibility due to errors assigning causes of death on the death certificate. Such a bias was likely non-differential and would tend to bias the HRs for the dichotomous comparisons between Camp Lejeune and Camp Pendleton toward a value of 1.00.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eComparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel subgroup, adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 for underlying causes of death were observed for cancers of the kidney, esophagus and female breast. Underlying causes of death with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 included Parkinson disease, myelodysplastic syndrome and cancers of the testes, cervix and ovary. Comparing the Camp Lejeune and Camp Pendleton Marines/Navy personnel full cohort, adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 for underlying causes of death were observed for cancers of the kidney and female breast, Hodgkin lymphoma, acute myeloid leukemia, myelodysplastic syndrome, acute kidney disease, Parkinson disease and multiple sclerosis. Adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 were observed for cancers of the cervix and testes.\u003c/p\u003e \u003cp\u003eComparing Camp Lejeune and Camp Pendleton civilian workers, adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 for underlying causes of death were observed for chronic kidney disease and Parkinson disease. Female breast cancer had an adjusted HR of 1.19 with a CIR\u0026thinsp;\u0026le;\u0026thinsp;3. Several other causes of death had HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 but with CIRs\u0026thinsp;\u0026gt;\u0026thinsp;3 including cancers of the kidney and pharynx, melanoma, and chronic myeloid leukemia.\u003c/p\u003e \u003cp\u003eBecause 85% of the full cohort and 98% of the subgroup of the Marines/Navy personnel were under 65 years of age at the end of follow-up, additional years of follow-up would be necessary to fully evaluate mortality in this population.\u003c/p\u003e \u003cp\u003eFew studies have evaluated drinking water exposures to these chemicals and causes of death. It has been estimated that up to one million people were exposed to the contaminated drinking water at Camp Lejeune, according to estimates made by staff at the USMC Base Camp Lejeune. However, the health impacts of the drinking water exposures to Marines/Navy personnel whose tour of duty at Camp Lejeune ended prior to 1975, civilian workers whose employment at the base ended prior to October 1972, and family members of the Marines/Navy personnel who resided in base family housing at Camp Lejeune have not been evaluated. Families living in base housing that received contaminated drinking water may have had exposure durations that were at least as long if not longer than the Marines/Navy personnel on base. The results of this study are relevant to all individuals exposed to the contaminated drinking water at Camp Lejeune and add to the literature on the health effects of these contaminants. It is hoped that this study encourages future research on the health effects of drinking water exposure to these chemicals.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eALS: amyotrophic lateral sclerosis\u003c/p\u003e\n\u003cp\u003eAML: acute myeloid leukemia\u003c/p\u003e\n\u003cp\u003eATSDR: Agency for Toxic Substances and Disease Registry\u003c/p\u003e\n\u003cp\u003eBOQ: bachelor officer quarters\u003c/p\u003e\n\u003cp\u003eCDC: Centers for Disease Control and Prevention\u003c/p\u003e\n\u003cp\u003eCI: 95% confidence interval\u003c/p\u003e\n\u003cp\u003eCIR: confidence interval ratio\u003c/p\u003e\n\u003cp\u003eCL: Camp Lejeune\u003c/p\u003e\n\u003cp\u003eCLL: chronic lymphocytic leukemia\u003c/p\u003e\n\u003cp\u003eCML: chronic myeloid leukemia\u003c/p\u003e\n\u003cp\u003eCNS: central nervous system cancers\u003c/p\u003e\n\u003cp\u003eCOPD: chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eDCE: t-1,2-dichloroethylene\u003c/p\u003e\n\u003cp\u003eDMDC: Defense Manpower Data Center\u003c/p\u003e\n\u003cp\u003eDOD: U.S. Department of Defense\u003c/p\u003e\n\u003cp\u003eEPA: U.S. Environmental Protection Agency\u003c/p\u003e\n\u003cp\u003eHB: Holcomb Boulevard treatment plant\u003c/p\u003e\n\u003cp\u003eHP: Hadnot Point treatment plant\u003c/p\u003e\n\u003cp\u003eHR: hazard ratio\u003c/p\u003e\n\u003cp\u003eIARC: International Agency for Research on Cancer\u003c/p\u003e\n\u003cp\u003eLTAS: life table analysis system\u003c/p\u003e\n\u003cp\u003eMCL: EPA maximum contaminant level in drinking water\u003c/p\u003e\n\u003cp\u003eNDI: National Death Index\u003c/p\u003e\n\u003cp\u003eMDS: myelodysplastic syndrome\u003c/p\u003e\n\u003cp\u003eMS: multiple sclerosis\u003c/p\u003e\n\u003cp\u003eNHL: non-Hodgkin lymphoma\u003c/p\u003e\n\u003cp\u003eNTP: National Toxicology Program\u003c/p\u003e\n\u003cp\u003e\u0026micro;g/L: micrograms per liter\u003c/p\u003e\n\u003cp\u003ePCE: tetrachloroethylene (also known as perchloroethylene)\u003c/p\u003e\n\u003cp\u003eRR: risk ratio\u003c/p\u003e\n\u003cp\u003eSMR: standardized mortality ratio\u003c/p\u003e\n\u003cp\u003eSSA: Social Security Administration\u003c/p\u003e\n\u003cp\u003eSSN: social security number\u003c/p\u003e\n\u003cp\u003eTCE: trichloroethylene\u003c/p\u003e\n\u003cp\u003eTT: Tarawa Terrace treatment plant\u003c/p\u003e\n\u003cp\u003eUSMC: United States Marine Corps\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe author declares he has nothing to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no actual or potential competing financial interest.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFJB designed the study, oversaw the data collection process, managed, analyzed and interpreted the data, and prepared the manuscript. Battelle and its subcontractors prepared the data for matching with TransUnion, Lexis-Nexis, SSA and NDI, conducted manual review of the matching results, and provided the final dataset to FJB.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author would like to thank the following lead project staff of Battelle Memorial Institute who coordinated the data collection and provided data management support: April Greek (Project Director), Ruth Gatiba (Project Manager), Rona Boehm (Data Management team lead), and the supporting staff at Battelle. The author would also like to thank lead project staff of the North American Association of Central Cancer Registries (NAACCR) who also coordinated data collection: Betsy Kohler and Recinda Sherman. Richard Pinder of the University of Southern California, Los Angeles consulted on the NDI. Aaron Bernstein, director of NCEH and ATSDR provided editing assistance. Finally, the author would like to acknowledge the strong and essential support for the study by the Camp Lejeune Community Assistance Panel members.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This work was supported by funding through interagency agreements with the U.S. Department of Health and Human Services\u0026rsquo; Agency for Toxic Substances and Disease Registry and the U.S. Department of the Navy. The author did not receive payment or services from a third party for any aspect of the submitted work.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eATSDR/CDC Disclaimer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings and conclusions in this manuscript are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMaslia ML, Sautner JB, Faye RE, Su\u0026aacute;rez-Soto RJ, Aral MM, Grayman WM, Jang W, Wang J, Bove FJ, Ruckart PZ, Valenzuela C, Green JW Jr, Krueger AL. Analyses of Groundwater Flow, Contaminant Fate and Transport, and Distribution of Drinking Water at Tarawa Terrace and Vicinity, U.S. Marine Corps Base Camp Lejeune, North Carolina: Historical Reconstruction and Present-Day Conditions\u0026mdash;Executive Summary. 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Dis. 2022;20(August):71.\u003c/li\u003e\n\u003cli\u003eMappin-Kasirer B, Pan H, Lewington S, Kizza J, Gray R, Clarke R, Peto R. Tobacco smoking and the risk of Parkinson disease: A 65-year follow-up of 30,000 male British doctors. Neurology 2020;94:e2132-e2138.\u003c/li\u003e\n\u003cli\u003eCarter BD, Abnet CC, Feskanich D, Freedman ND et al. Smoking and mortality \u0026ndash; beyond established causes. NEJM 2015;372:631-40.\u003c/li\u003e\n\u003cli\u003eLlamosas-Falcon L, Probst C, Buckler C, Jiang H et al. How does alcohol use impact morbidity and mortality of liver cirrhosis? A systematic review and dose-response meta-analysis. Hepatology International 08 September 2023 online ahead of print.\u003c/li\u003e\n\u003cli\u003eBray RM and Hourani LL. Substance use trends among active duty military personnel: findings from the United States Department of Defense Health Related Behavior Surveys, 1980\u0026ndash;2005. Addiction 2007;102:1092\u0026ndash;1101.\u003c/li\u003e\n\u003cli\u003eKunzmann AT, Coleman HG, Huang WY, Berndt SI. The association of lifetime alcohol use with mortality and cancer risk in older adults: A cohort study. PLoS Med 2018;15(6): e1002585\u003c/li\u003e\n\u003cli\u003eRumgay H, Murphy N, Ferrari P, Soerjomatatum I. Alcohol and cancer: Epidemiology and biological mechanisms. Nutrients 2021;13:3173\u003c/li\u003e\n\u003cli\u003eGlass DC et al. Occupational exposure to solvents and risk of breast cancer. Am J Ind Med 2015;58:915-922.\u003c/li\u003e\n\u003cli\u003eWestra S, Goldberg MS, Labr\u0026egrave;che F, et al. The association between the incidence of postmenopausal breast cancer and occupational exposure to selected organic solvents, Montreal, Canada, 2008-2011. Am J Ind Med 2023;66:911-927.\u003c/li\u003e\n\u003cli\u003eDorsey ER, Zafar M, Lettenberger SE et al. Trichloroethylene: An invisible cause of Parkinson\u0026rsquo;s disease? J Parkinsons Dis 2023;13:203-218.\u003c/li\u003e\n\u003cli\u003eGoldman SM, Weaver FM, Stroupe KT et al. Risk of Parkinson disease among service members at Marine Corps Base Camp Lejeune. JAMA Neurol. 2023;80(7):673-681.\u003c/li\u003e\n\u003cli\u003eGerhardsson L et al. Work-related exposure to organic solvents and the risk for multiple sclerosis \u0026ndash; a systematic review. Int Arch Occup Environ Health 2021;94:221-229.\u003c/li\u003e\n\u003cli\u003eSchnatter AR et al. Myelodysplastic syndrome and benzene exposure among petroleum workers: An international pooled analysis. JNCI 2012;104:1724-1737.\u003c/li\u003e\n\u003cli\u003eRuckart PZ, Bove FJ, Shanley III E, Maslia M. Evaluation of contaminated drinking water and male breast cancer at Marine Corps Base Camp Lejeune, North Carolina: a case control study. Environ Health 2015;14:74.\u003c/li\u003e\n\u003cli\u003eHansen J et al. 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Available at: https://www.atsdr.cdc.gov/ToxProfiles/tp3.pdf\u003c/li\u003e\n\u003cli\u003eVlaanderen J et al. Occupational benzene exposure and the risk of chronic myeloid leukemia: a meta-analysis of cohort studies incorporating study quality dimensions. Am J Ind Med 2012;55:779-785.\u003c/li\u003e\n\u003cli\u003eLinet MS et al. A retrospective cohort study of cause-specific mortality and incidence of hematopoietic malignancies in Chinese benzene-exposed workers. Int J Cancer 2015;137:2184-2197.\u003c/li\u003e\n\u003cli\u003eLinet MS et al. Benzene Exposure Response and Risk of Myeloid Neoplasms in Chinese Workers: A Multicenter Case\u0026ndash;Cohort Study. J Natl Cancer Inst (JNCI) 2019;111:465-474.\u003c/li\u003e\n\u003cli\u003eTruth Initiative. Tobacco use in the military: Fact sheet. June 2018. Accessed on 3/27/2023. https://truthinitiative.org/sites/default/files/media/files/2022/05/Truth_Military_FactSheet_051722.pdf\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e \u0026sect; See 45 C.F.R. part 46.114; 21 C.F.R. part 56.114\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"USMC base Camp Lejeune, USMC base Camp Pendleton, Marines/Navy personnel, civilian workers, mortality, cancer, drinking water, trichloroethylene, tetrachloroethylene, benzene, vinyl chloride, hazard ratio","lastPublishedDoi":"10.21203/rs.3.rs-4171975/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4171975/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDrinking water at U.S. Marine Corps Base Camp Lejeune, North Carolina was contaminated with trichloroethylene and other industrial solvents from 1953 to 1985.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cohort mortality study was conducted of Marines/Navy personnel who, between 1975 and 1985, began service and were stationed at Camp Lejeune (N\u0026thinsp;=\u0026thinsp;159,128) or Camp Pendleton, California (N\u0026thinsp;=\u0026thinsp;168,406), and civilian workers employed at Camp Lejeune (N\u0026thinsp;=\u0026thinsp;7,332) or Camp Pendleton (N\u0026thinsp;=\u0026thinsp;6,677) between October 1972 and December 1985. Camp Pendleton\u0026rsquo;s drinking water was not known to be contaminated between 1972 and December 1985. Mortality follow-up was between 1979 and 2018. Survival analyses were used to calculate hazard ratios (HRs) comparing mortality rates between Camp Lejeune and Camp Pendleton cohorts and assess the effects of duration at Camp Lejeune. The ratio of upper and lower 95% confidence interval (CI) limits, or CIR, was used to evaluate the precision of effect estimates. The study focused on underlying causes of death with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIRs\u0026thinsp;\u0026le;\u0026thinsp;3. Results from contributing causes were also presented.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDeaths among Camp Lejeune and Camp Pendleton Marines/Navy personnel totaled 19,250 and 21,134, respectively. Deaths among Camp Lejeune and Camp Pendleton civilian workers totaled 3,055 and 3,280, respectively. Compared to Camp Pendleton Marines/Navy personnel, Camp Lejeune had adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 for cancers of the kidney (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.95, 1.54), esophagus (HR\u0026thinsp;=\u0026thinsp;1.24, 95% CI: 1.00, 1.54) and female breast (HR\u0026thinsp;=\u0026thinsp;1.20, 95% CI: 0.73, 1.98). Causes of death with HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 and CIR\u0026thinsp;\u0026gt;\u0026thinsp;3, included Parkinson disease, myelodysplastic syndrome and cancers of the testes, cervix and ovary. Compared to Camp Pendleton workers, Camp Lejeune had adjusted HRs\u0026thinsp;\u0026ge;\u0026thinsp;1.20 with CIRs\u0026thinsp;\u0026le;\u0026thinsp;3 for chronic kidney disease (HR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.13, 3.11) and Parkinson disease (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 0.72, 2.04). Female breast cancer had an adjusted HR of 1.19 (95% CI: 0.76, 1.88). Sensitivity analyses indicated that confounding bias due to unmeasured risk factors (e.g., smoking) is unlikely to significantly impact the findings.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eMarines/Navy personnel and civilian workers likely exposed to contaminated drinking water at Camp Lejeune had increased hazard ratios for several causes of death compared to Camp Pendleton.\u003c/p\u003e","manuscriptTitle":"Evaluation of mortality among Marines, Navy personnel, and civilian workers exposed to contaminated drinking water at USMC Base Camp Lejeune: a cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-29 15:24:53","doi":"10.21203/rs.3.rs-4171975/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f527b93d-f9bc-4f67-9a47-9f72b8150acb","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-30T10:00:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-29 15:24:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4171975","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4171975","identity":"rs-4171975","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}