Occupational exposure to pesticides, metals, and solvents - IOS Press

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Work 37 (2010) 205–215 DOI 10.3233/WOR-2010-1071 IOS Press

Occupational exposure to pesticides, metals, and solvents: The impact on mortality rates in the Honolulu Heart Program Luenda E. Charlesa,∗, Cecil M. Burchfiela, Desta Fekedulegna, Ja K. Gua , Helen Petrovitchb,c,d,e , Wayne T. Sandersonf , Kamal Masakic,d,e, Beatriz L. Rodriguezc,d,e, Michael E. Andrewa and G. Webster Rossb,c,d,e a

Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA b Veterans Affairs Pacific Islands Health Care System, Honolulu, Hawaii, USA c The Pacific Health Research Institute, Honolulu, HI, USA d Departments of Geriatric Medicine and Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA e Kuakini Medical Center and the Honolulu-Asia Aging Study, Honolulu, HI, USA f Department of Occupational and Environmental Health, the University of Iowa College of Public Health, Iowa City, IA, USA

Received 11 March 2009 Accepted 20 April 2009

Abstract. Objective: To investigate the impact of occupational exposure to pesticides, metals, and solvents on mortality. Participants: Middle-aged Japanese-American men (n = 7,540) who had participated in the Honolulu Heart Program during 1965–1968. Methods: Industrial hygienists assessed participants’ potential for exposure based on their primary job. Cumulative exposure scores were categorized as none, low, medium, and high. The underlying cause of death was ascertained by a physician panel. All associations were assessed using Cox proportional hazards models. Results: A total of 4, 485 deaths occurred. Compared to no exposure, pesticide exposure was significantly associated with mortality from all causes, circulatory diseases, stroke, and all cancers. Results for all-cause mortality at the 0-yr lag after risk-factor adjustment were: Low, hazard ratio (HR) = 0.85, 95% confidence interval (CI) = 0.68–1.08; medium, HR = 1.18, 95% CI = 1.01–1.37; and high, HR = 1.29, 95% CI = 1.06–1.57; trend, p = 0.002. Exposure to metals and solvents was significantly associated with mortality from all causes, cancer, and respiratory disease, and exposure to solvents was additionally associated with mortality from circulatory disease. Associations were strongest at the 15-yr lag. Conclusions: Results show that occupational exposures to pesticides, metals, and solvents during mid-life are independently associated with increased mortality, and indicate potential importance of exposures that occurred approximately 15 years prior to death. Keywords: Occupational health and safety, men’s health, mortality rates

1. Introduction ∗ Address for correspondence: Luenda E. Charles, PhD, MPH, National Institute for Occupational Safety and Health, HELD/BEB, MS L-4050, 1095 Willowdale Rd., Morgantown, WV 26505-2888, USA. Tel.: +1 304 285 5922; Fax: +1 304 285 6112; E-mail: lcharles @cdc.gov.

Research findings concerning the association between occupational exposure to pesticides, metals and solvents with increased mortality have been inconsistent. In some studies, occupational exposure to high

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L.E. Charles et al. / Occupational exposures and mortality

levels of pesticides have been associated with increased mortality rates from circulatory system diseases, cardiovascular disease, specific cancers, and from all causes combined [3,15,36]. Authors of other studies either did not find significantly elevated mortality rates from cancer or other conditions, or found lower than expected mortality rates linked to occupational pesticide exposure [2,5,28]. Occupational exposure to inorganic mercury has been associated with significant increases in mortality from hypertension, heart diseases other than ischemia, pneumoconiosis, nephritis and nephrosis, and overall mortality in men [6]. Exposures to some solvents, such as those used by dry-cleaners have been associated with higher mortality rates from several specific cancers (including lung cancer), cardiovascular disease, cerebrovascular disease, circulatory system diseases, diseases of the stomach and duodenum, and pneumonia [22,25,32]. However, one study found no evidence of an association between exposure to chlorinated organic solvents and cancer mortality [9]. In 2004, the five leading causes of death in the United States were heart disease (27.2% of total deaths), malignant neoplasms, cerebrovascular disease, chronic lower respiratory disease, and accidents or unintentional injuries [16]. Heart disease and cancer accounted for approximately 50% of all deaths. Therefore, the primary objective of this study was to investigate the association of occupational exposures to pesticides, metals, and solvents that occurred during middle age with mortality from several of these conditions over a 30-year period. This paper focused on mortality from all causes, circulatory diseases, cancer, and respiratory disease.

2. Methods 2.1. Study sample Data from the Honolulu Heart Program (HHP) participants were used for this study. The HHP began in 1965 as a prospective study of cardiovascular disease and stroke in Japanese-American men living on Oahu. Detailed descriptions of the methods have been previously published [31,33]. Briefly, these men, all non-institutionalized, were identified through Selective Service records from World War II and located through searches of telephone, business, and state agency records. Informed consent was obtained from the study participants.

Several examinations have been conducted to date. The baseline examination took place during 1965–1968 and included 8, 006 men who were between the ages of 45 and 68 years. Using standardized criteria described previously [18,35], 466 men were excluded from the study: 460 cases of coronary heart disease, cerebrovascular disease, and cancer identified as of the first examination and six men with unknown causes of death. Among the 7, 540 men who remained, 4, 485 men died during the observation period (1965–1998) and 3, 055 men were alive at the end of the follow-up period on December 31, 1998. No one was lost to follow-up. 2.2. Assessment of occupational exposures Occupational exposure information collected during the baseline examination was used in these analyses. Participants were asked questions about their present and usual occupation, and the age that they started and finished working in these occupations. Approximately 66% of the participants had jobs involving manual labor: craftsmen (e.g., crane men, bulldozer operators), farmers, laborers, operatives (e.g., delivery men, welders), and service workers; 7.8% were in professional occupations (e.g., chemist, agricultural scientist, chemical engineer); 9% were clerks; 7.6% were managers; 7.3% were salesmen; and 2% were technicians. Industrial hygienists from the National Institute for Occupational Safety and Health (NIOSH) assessed the potential for pesticide, metal, and solvent exposure in each reported occupation. They created four levels of exposure to each agent indicating a score of 0 for no potential of exposure, 1 for low exposure, 2 for medium exposure, and 3 for potential of high exposure based on usual occupation [1]. The “high” classification was assigned to those occupation/industry pairings judged to have significant exposures that were frequently well above analytically detectable concentrations and were at least occasionally near or greater than the OSHA permissible exposure limits (PELs), if a PEL existed. A “high” score meant that the industrial hygienists were confident that the industry/occupation pairing would frequently have exposure to the agent. The “medium” exposure classification was assigned to those occupation/industry pairings judged to involve tasks with detectable exposures to the selected agents, but which were considered usually to be below the OSHA PELs. The “low” exposure classification was assigned to those industry/occupation pairings judged to occasionally have detectable exposures to the selected agents but which would rarely approach the OS-


HA/PEL. A “0” score indicated that workers in these industry/occupation pairings were believed to have little potential exposure to the agent. The scores not only reflected the industrial hygienists’ view of the intensity of exposure, but also their confidence that jobs in these industries would have exposure to these agents. Although information was collected on present and usual jobs, usual job was used primarily to assign participants to specific industry-occupation groups. A cumulative exposure intensity score was calculated by multiplying the appropriate levels of exposure (0, 1, 2, 3) by the number of years of exposure for each participant. If exposure to the agents did not occur in the usual job but did occur in the present job, the exposure assigned for the present job was used in calculating the exposure intensity score. Occupational exposures were in the form of usual jobs, duration of jobs in years, and intensity scores at the baseline examination. Cumulative exposure scores for the three primary occupational exposures of interest were developed; pesticides, metals, and solvents were categorized into four levels, 0, 1–39, 40–79, and > 80. The cut points were selected to allow for sufficient sample sizes in each group. 2.3. Assessment of mortality Mortality data were obtained through a comprehensive surveillance system that has been used successfully since the beginning of the HHP [24]. All deaths were ascertained by continuous monitoring of obituaries in local newspapers, mortuary notices, hospital discharge records, and death certificates. The underlying cause of death was determined by a panel of study physicians at bimonthly conferences using standardized criteria, and was based on all available information, including HHP examinations, hospital records, death certificates, autopsy reports, and telephone inquires to physicians and families. Three major categories were used to classify the underlying cause according to the eighth revision of the International Classification of Disease: diseases of the circulatory system (codes 390 to 459), cancer (codes 140 to 208), and all other causes combined. The date of death was the criterion used to assign vital status. If the date of death was not missing and was documented prior to December 31, 1998, then the individual was assumed to be deceased; otherwise the individual was assumed to be alive. For calculation of hazard ratios, individuals were considered at risk from the date of their baseline examination until date of death (for those who died during the follow-up period) or until December 31, 1998 (for those who were still alive after that date).

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2.4. Assessment of covariates A comprehensive baseline examination included self-administered questionnaires and physical examinations using methods of data collection that have been described previously [17,35]. Blood pressure was measured three times, twice by nurses and once by the examining physician. Participants were required to sit quietly for approximately 10 minutes to stabilize blood pressure before the measurements were taken. There were intervals of at least 15 minutes between the three measurements and the mean of the second and third measurements was used in analysis. Triceps skinfold thickness was measured to the nearest millimeter with the participant standing and arms hanging in a relaxed manner using a Lange Skinfold Caliper (Cambridge Scientific Industries, Cambridge, MD). A non-fasting blood sample was taken for measurements of cholesterol, triglyceride, and glucose one hour after participants ingested a 50 gm glucose load. Participants reported the level of education attained. As previously described, a physical activity index was created by multiplying the number of activity hours spent in a 24-hour period (hours were summed across activities) by a weighting factor [8]. The activity levels were basal (e.g., sleeping or reclining), sedentary (e.g., sitting, standing), slight (e.g., casual walking), moderate (e.g., carpentry, gardening), and heavy (lifting, shoveling). The weighting factors were based on the estimated oxygen consumption in liters per minute required to perform the relevant activities and they were 1.0, 1.1, 1.5, 2.4, and 5.0 respectively. Smoking status was categorized as never, former, and current. Alcohol history was recorded as the number of ounces of alcoholic beverages (wine, beer, and liquor) consumed per month. 2.5. Statistical methods Univariate methods were used to compare the baseline characteristics of participants who had died with those who remained alive as at December 31, 1998. Death rates, per 1000 person-years, were calculated for selected causes of death. The total ‘person-years of risk’ accumulated during the follow-up period was 188,970.80 person-years. Analysis of variance models were used to obtain the mean values of covariates across levels of the three primary exposures of interest. The Cox Proportional Hazards model was used to estimate the hazard ratio at each level of the three exposure variables relative to the zero exposure intensity level. In

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L.E. Charles et al. / Occupational exposures and mortality Table 1 Baseline characteristics of participants in 1965–1968 by vital status through 1998, Honolulu Heart Program Characteristics Age, years Systolic blood pressure, mm Hg Diastolic blood pressure, mm Hg Total cholesterol, mg/dL Triglycerides, mg/dL Glucose, mg/dL Body mass index, kg/m2 Triceps skinfold, mm Physical activity index Smoking, pack-years Alcohol, oz/month* Current smoking, % Alcohol intake, % Education >= high school, %

Alive (n = 3055) 51.7 ± 4.0 128.8 ± 17.7 81.0 ± 10.8 218.5 ± 35.2 232.1 ± 187.3 148.9 ± 43.9 24.0 ± 2.8 7.9 ± 3.2 33.0 ± 4.6 31.7 ± 20.9 17.9 ± 23.4 34.9 69.2 55.5

Deceased (n = 4485) 56.1 ± 5.7 137.1 ± 22.0 82.9 ± 12.1 217.5 ± 39.8 239.6 ± 214.4 169.2 ± 64.6 23.7 ± 3.3 7.9 ± 3.5 32.8 ± 4.4 40.3 ± 23.3 24.9 ± 30.1 50.3 67.7 45.1

P-value** < 0.001 < 0.001 < 0.001 0.248 0.119 < 0.001 0.001 0.680 0.114 < 0.001 < 0.001 < 0.001 0.252 < 0.001

Values are means (± SD) or percentages. Pack-years were calculated only for current and past smokers *Alcohol consumption was calculated only for current and past drinkers **p-values were obtained from the t-test (for continuous variables) and χ2 test of independence (for categorical variables).

addition, latency analyses were performed to estimate the most etiologically relevant exposure period for the specific outcome [10]. We used the latency intervals of 0-yr, 5-yr, 10-yr, and 15-yr because the lengths of the latency periods for the conditions under study are not known and may vary widely. With 0-year lagging, the entire period of exposure is investigated; with 15-yr lagging, the exposure period excluding the 15 years immediately prior to death is investigated. Only models for the 0-yr and 15-yr lags are shown in the tables. The following variables were included in the model as potential confounders: education, smoking status, triglycerides, physical activity, alcohol intake, and systolic blood pressure. Effect modification was assessed for tricep skinfold thickness and smoking status by stratifying on categories of these variables (< 10 mm vs. > 10 mm and never, former, and current smokers, respectively) and testing interaction terms in the models. Covariates were chosen for the final models based on a priori knowledge and the observed associations with the exposures and outcomes in this study. All analyses were conducted using the SAS system, version 9.1 [27].

sented in Table 1. As expected, men who died during follow-up had a more adverse cardiovascular risk profile at baseline than men who remained alive. In addition, those who died were, on average, older, had higher blood pressure readings and glucose levels, smoked more, consumed more alcohol, and had lower educational levels than those who were alive at the end of the follow-up period. Numbers, rates (per 1000 person-years), and proportion of deaths due to selected conditions are presented in Table 2. Among the 4,485 deaths with ICD codes, 28.3% were due to circulatory diseases and 32.4% were due to cancers. We examined associations between selected demographic and lifestyle characteristics and the measures of occupational exposure (data not shown). Mean age, pack-years of smoking, alcohol consumption, and physical activity increased significantly with increasing levels of exposure to pesticides, metals, and solvents (all trends, p < 0.001). In contrast, the proportion of participants who attained a high school education or higher decreased significantly with increasing levels of exposure to all agents (all trends, p < 0.001).

3. Results

3.2. Exposure intensity scores and mortality

3.1. Participant characteristics and mortality

3.2.1. Pesticide exposure Exposure to pesticides was significantly and positively associated with mortality from all causes, stroke, any cancer, and lung cancer after adjustment for edu-

Descriptive statistics of selected characteristics of the participants at the baseline examination are pre-


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Table 2 All cause and cause-specific mortality, Honolulu Heart Program (1965–1968) Cause of death All causes Circulatory − Coronary heart disease − Stroke All Cancer − Lung cancer Respiratory Diseases (including chronic obstructive lung disease) Diabetes/ Digestive/all other diseases Accidents/violence Undetermined causes

N 4485 1269 595 479 1451 367 357

Mortality rate* 23.7 6.7 3.2 2.5 7.7 1.9 1.9

Proportionate mortality (%)† — 28.3 13.3 10.7 32.4 8.2 8.0

588 173 647

3.1 0.9 3.4

13.1 3.9 14.4

*Mortality rate per 1,000 person-years. †Proportion of deaths due to specific conditions.

cation, smoking status, triglycerides, physical activity, alcohol intake, and systolic blood pressure (Table 3). These associations were significant for all lag intervals, but most associations were strongest at the 15year lag. The other results between pesticide exposure and all-cause mortality after risk-factor adjustment are as follows (from low to high exposure): 5-yr lag, Low Exposure HR = 0.97 (95% CI = 0.81–1.16); Medium Exposure HR = 1.14 (95% CI = 0.98–1.34); High Exposure HR = 1.54 (95% CI = 1.18–2.01); p for trend < 0.001 and 10-yr lag, Low Exposure HR = 1.08 (95% CI = 0.94–1.25); Medium Exposure HR = 1.12 (95% CI = 0.93–1.36); High Exposure HR = 2.18 (95% CI = 1.51–3.14); p for trend < 0.001. For respiratory disease, the sample size in the highest level of pesticide exposure at the 15-yr lag was zero, therefore, the results of the 10-yr lag are also presented here. Respiratory diseases showed the strongest trend with pesticide exposure at the 10-yr lag: Low Exposure HR = 0.99 (95% CI = 0.57–1.73); Medium Exposure HR = 1.40 (95% CI = 0.76–2.56); High Exposure HR = 5.02 (95% CI = 1.86–13.55); p for trend = 0.031.

3.2.3. Solvent exposure Exposure to solvents was significantly and positively associated with mortality from (a) all causes (at the 5yr, 10-yr, and 15-yr lag intervals), (b) all cancers (at all lag intervals), and (c) circulatory and respiratory diseases (at the 15-yr lag interval only) (Table 5). These significant associations were present before and after risk-factor adjustment; associations were strongest at the 15-yr lag interval.

3.2.2. Metal exposure Results for the association between metal exposure and mortality are presented in Table 4. Exposure to metals was significantly and positively associated with mortality from all causes and cancer at the 15-year lag (p for trend < 0.001). Risk-factor adjustment did not change the strength of the association. In addition, increasing exposure to metals was significantly associated with increased mortality from respiratory diseases at the 10-yr and 15-yr lag intervals (but not at 0-yr or 5-yr lag intervals), with the trend at the 15-yr interval being slightly stronger (adjusted p for trend = 0.007).

The results of this prospective study showed that exposure to pesticides, metals, and solvents during middle age was significantly associated with mortality years later from all causes, circulatory diseases, stroke, any cancers, and lung cancer. Of the three occupational agents investigated, exposure to pesticides was most strongly associated with increased risk of mortality. The association between occupational exposure to pesticides and mortality reported in other studies has been mixed [2,3,5,15,36,28]. However, there is some biological evidence supporting a causal relationship between pesticide exposure and cancer. Workers em-

3.3. Effect modification We assessed effect modification for the associations of the three exposures with mortality from all causes and cancer by tricep skinfold thickness and smoking status. Neither triceps skinfold thickness (< 10 mm and > 10 mm) nor smoking status (never, former and current smoking) modified any of the associations between exposure and mortality; all interaction p-values were > 0.20.

4. Discussion

0 1-39 40-79 > 80

Lung cancer 1.00 1.19 1.05 1.80 0.093 1.00 0.75 1.35 1.55 0.074

326 5 16 9

1.00 1.00 1.07 1.39 0.043

334 8 13 11

1334 27 53 34

1.00 0.79 1.33 1.93 0.006

436 7 21 15

0.31, 1.82 0.82, 2.24 0.80, 2.99

0.59, 2.40 0.60, 1.83 0.99, 3.29

0.68, 1.46 0.82, 1.41 0.99, 1.96

0.37, 1.66 0.86, 2.06 1.15, 3.23

0.75, 2.16 0.80, 1.82 0.61, 2.02

0.68, 1.53 0.95, 1.65 1.04, 2.12

1.00 0.65 1.33 1.56 0.089

1.00 1.31 1.24 1.99 0.018

1.00 1.03 1.13 1.38 0.028

1.00 0.61 1.21 1.73 0.050

1.00 1.23 1.18 1.06 0.463

1.00 0.87 1.19 1.36 0.061

HR 1.00 0.85 1.18 1.29 0.002

0.24, 1.75 0.79, 2.24 0.80, 3.04

0.65, 2.66 0.71, 2.17 1.09, 3.64

0.70, 1.51 0.85, 1.49 0.98, 1.94

0.27, 1.37 0.76, 1.91 1.03, 2.91

0.72, 2.09 0.78, 1.80 0.58, 1.93

0.57, 1.32 0.90, 1.59 0.95, 1.95

0.68, 1.08 1.01, 1.37 1.06, 1.57

Adjusted* 95% CI

1.00 1.11 1.93 3.37 0.037 1.00 1.76 1.02 — 0.019

339 16 10 1 327 24 5 0

1.00 1.19 1.50 1.65 0.004

1.00 1.08 1.65 5.26 0.005

446 20 11 2 1347 68 31 2

1.00 1.11 1.06 2.02 0.511

1.00 1.07 1.34 2.89 0.011

HR 1.00 1.20 1.33 2.22 < 0.001

557 26 9 1

1187 53 24 3

Deaths 4174 210 84 8

1.17, 2.67 0.42, 2.48 —

0.67, 1.89 1.03, 3.62 0.48, 23.93

0.93, 1.52 1.05, 2.14 0.41, 6.61

0.69, 1.69 0.91, 3.01 1.31, 21.10

0.75, 1.65 0.55, 2.05 0.29, 14.37

0.81, 1.41 0.89, 2.01 0.93, 8.97

1.05, 1.38 1.07, 1.65 1.11, 4.43

15-yr lag Unadjusted 95% CI

HR = Hazard ratio; CI = confidence intervals; CHD = Coronary heart disease. P-values for trend obtained from regression models. *Adjusted for education, smoking status, triglycerides, physical activity, alcohol intake, and systolic blood pressure. Number of participants at risk in pesticide exposure intensity score categories (0, 1–39, 40–79, and > 80) were 6964, 140, 271, and 147 respectively. †No. of deaths for all cause mortality do not add up to 4485 because of missing information for exposure intensity scores.

Ptrend

Respiratory Diseases

Ptrend

Ptrend

0 1-39 40-79 > 80

0 1-39 40-79 > 80

Any cancer

Ptrend

0 1-39 40-79 > 80

1.00 1.27 1.21 1.11 0.305

1.00 1.02 1.25 1.48 0.007

0.73, 1.15 1.02, 1.38 1.12, 1.66


HR 1.00 0.92 1.19 1.36 < 0.001

544 14 24 11

1159 24 53 31

0 1-39 40-79 > 80

0 1-39 40-79 > 80

Deaths 4119 77 179 101

Exposure Intensity Levels 0 1-39 40-79 > 80

Stroke

Ptrend

CHD

Ptrend

Circulatory diseases

Ptrend

Cause All causes†

Table 3

1.00 1.79 1.02 — 0.018

1.00 1.27 2.09 3.38 0.010

1.00 1.23 1.48 1.51 0.005

1.00 0.92 1.48 3.70 0.038

1.00 1.06 1.01 1.38 0.752

1.00 0.97 1.23 1.97 0.081

1.17, 2.75 0.42, 2.48 —

0.77, 2.10 1.11, 3.93 0.47, 24.23

0.96, 1.57 1.03, 2.11 0.38, 6.04

0.58, 1.49 0.81, 2.70 0.92, 14.96

0.71, 1.58 0.52, 1.96 1.93, 9.83

0.73, 1.30 0.82, 1.86 0.63, 6.12

Adjusted* HR 95% CI 1.00 1.01, 1.34 1.16 1.02, 1.58 1.27 0.87, 3.47 1.73 < 0.001

Associations of pesticide exposure intensity scores at baseline with all cause and cause-specific mortality by latency, Honolulu Heart Program, 1965–1998

210 L.E. Charles et al. / Occupational exposures and mortality

None Low Med High

None Low Med High

None Low Med High

None Low Med High

None Low Med High

None Low Med High

Exposure Intensity Levels None Low Med High

1.00 0.73 0.99 1.07 0.631 1.00 0.92 1.15 1.12 0.585 1.00 1.02 1.19 1.54 0.002 1.00 0.89 1.57 1.27 0.070

377 138 60 18

219 82 40 16

209 92 53 12

820 414 157 57

1.00 0.74 1.14 1.66 0.280

1.00 0.81 1.08 1.13 0.922

779 314 135 39

283 130 52 14

HR 1.00 0.86 1.05 1.36 0.075

Deaths 2694 1163 456 163

0.57, 0.95 0.81, 1.59 1.00, 2.76

0.69, 1.13 1.16, 2.12 0.71, 2.27

0.90, 1.14 1.00, 1.41 1.17, 2.01

0.74, 1.13 0.85, 1.54 0.66, 1.92

0.60, 0.89 0.75, 1.30 0.67, 1.72

0.71, 0.92 0.90, 1.29 0.82, 1.56

0.81, 0.93 0.95, 1.16 1.16, 1.59


1.00 0.72 1.15 1.69 0.188

1.00 0.75 0.89 1.03 0.531 1.00 0.92 1.01 1.08 0.885 1.00 0.98 1.13 1.45 0.029 1.00 0.89 1.54 1.15 0.179

1.00 0.83 0.95 1.08 0.722

HR 1.00 0.85 0.97 1.27 0.497

0.54, 0.95 0.80, 1.64 1.00, 2.83

0.68, 1.16 1.11, 2.13 0.62, 2.12

0.86, 1.11 0.94, 1.36 1.10, 1.91

0.74, 1.15 0.73, 1.39 0.63, 1.86

0.61, 0.93 0.66, 1.19 0.63, 1.69

0.72, 0.95 0.78, 1.16 0.78, 1.51

0.79, 0.92 0.87, 1.08 1.08, 1.49

Adjusted* 95% CI

232 106 14 4

230 121 14 1

895 490 57 6

1.00 0.91 1.50 4.94 0.013

1.00 0.74 1.24 1.95 0.808 1.00 1.00 1.46 0.92 0.082 1.00 1.10 1.53 1.75 < 0.001 1.00 1.05 1.46 1.12 0.044

415 154 21 3 307 153 18 1

1.00 0.86 1.36 1.29 0.116

HR 1.00 0.95 1.40 1.79 < 0.001

850 366 47 4

Deaths 2911 1380 166 19

0.72, 1.15 0.87, 2.57 1.84, 13.27

0.85, 1.31 0.85, 2.51 0.16, 7.95

0.98, 1.22 1.17, 2.00 0.79, 3.91

0.82, 1.21 0.91, 2.35 0.13, 6.57

0.62, 0.90 0.80, 1.93 0.63, 6.08

0.76, 0.98 1.02, 1.83 0.49, 3.46

0.89, 1.01 1.20, 1.64 1.14, 2.81


HR = Hazard ratio; CI = confidence intervals; CHD = Coronary heart disease. P-values for trend obtained from regression models. *Adjusted for education, smoking status, triglycerides, physical activity, alcohol intake, and systolic blood pressure. Metal exposure intensity score levels are 0, 1-39, 40-79, >=80 for None, Low, Medium and High respectively. Number of participants at risk in metal exposure intensity score categories (None, Low, Medium, and High) were 4461, 2103, 738, and 223 respectively. †No. of deaths for all cause mortality do not add up to 4485 because of missing information for exposure intensity scores.

Ptrend


Ptrend

Ptrend Lung cancer

Ptrend Any cancer

Ptrend Stroke

CHD

Ptrend


Ptrend

Cause All causes†

Table 4

1.00 0.93 1.52 4.93 0.007

1.00 0.74 1.12 1.45 0.960 1.00 0.98 1.28 0.95 0.214 1.00 1.06 1.39 1.78 < 0.001 1.00 1.07 1.21 1.22 0.099

1.00 0.86 1.18 1.03 0.314

0.72, 1.19 0.88, 2.63 1.82, 13.23

0.84, 1.36 0.67, 2.18 0.17, 8.73

0.94, 1.20 1.05, 1.83 0.80, 3.98

0.80, 1.21 0.79, 2.08 0.13, 6.75

0.61, 0.91 0.72, 1.75 0.36, 5.83

0.76, 0.99 0.88, 1.60 0.33, 3.20

Adjusted* HR 95% CI 1.00 0.93 0.87, 1.00 1.23 1.05, 1.45 1.70 1.07, 2.70 < 0.001

Associations of metal exposure intensity scores at baseline with all cause and cause-specific mortality by latency, Honolulu Heart Program, 1965–1998

L.E. Charles et al. / Occupational exposures and mortality 211

None Low Med High

None Low Med High

None Low Med High

None Low Med High

None Low Med High

None Low Med High

Exposure Intensity Levels None Low Med High

1.00 0.78 0.82 1.11 0.927 1.00 0.86 1.13 1.29 0.157 1.00 0.95 1.17 1.37 < 0.001 1.00 0.89 1.21 1.48 0.044

311 165 74 43

175 104 49 28

171 103 60 32

672 431 229 116

1.00 0.88 0.96 1.29 0.228

1.00 0.78 0.98 1.14 0.264

646 344 185 92

231 135 76 37

HR 1.00 0.87 1.00 1.23 0.002

Deaths 2203 1296 639 338

0.69, 1.12 0.70, 1.32 0.87, 1.93

0.70, 1.14 0.90, 1.62 1.02, 2.16

0.84, 1.07 1.01, 1.36 1.12, 1.66

0.69, 1.06 0.87, 1.47 0.91, 1.83

0.65, 0.94 0.63, 1.05 0.80, 1.52

0.69, 0.89 0.84, 1.16 0.92, 1.42

0.81, 0.93 0.91, 1.09 1.10, 1.38


1.00 0.86 0.89 1.23 0.305

1.00 0.83 0.81 1.06 0.959 1.00 0.89 1.11 1.15 0.394 1.00 0.91 1.12 1.26 0.015 1.00 0.90 1.20 1.35 0.151

1.00 0.83 0.97 1.05 0.526

HR 1.00 0.86 0.95 1.12 0.089

0.66, 1.12 0.63, 1.26 0.81, 1.88

0.69, 1.17 0.87, 1.64 0.89, 2.03

0.80, 1.04 0.95, 1.31 1.02, 1.55

0.71, 1.13 0.84, 1.46 0.80, 1.67

0.68, 1.02 0.61, 1.06 0.75, 1.48

0.72, 0.95 0.81, 1.15 0.83, 1.32

0.80, 0.93 0.87, 1.04 1.00, 1.27

Adjusted* 95% CI

198 132 16 10

204 132 27 3

781 556 94 17

1.00 0.97 0.91 5.99 0.014

1.00 0.76 1.21 2.46 0.249 1.00 0.98 1.31 1.32 0.011 1.00 1.04 1.33 2.32 < 0.001 1.00 0.95 1.46 1.55 0.028

360 186 39 8 266 179 31 3

1.00 0.85 1.22 1.98 0.006

HR 1.00 0.94 1.25 2.42 < 0.001

742 431 81 13

Deaths 2522 1619 281 54

0.78, 1.21 0.55, 1.51 3.16, 11.33

0.76, 1.18 0.98, 2.18 0.50, 4.84

0.94, 1.16 1.07, 1.65 1.44, 3.75

0.81, 1.19 0.91, 1.91 0.42, 4.12

0.63, 0.90 0.87, 1.69 1.22, 4.97

0.75, 0.96 0.97, 1.54 1.14, 3.43

0.88, 1.00 1.10, 1.41 1.84, 3.16


HR = Hazard ratio; CI = confidence intervals; CHD = Coronary heart disease. P-values for trend obtained from regression models. *Adjusted for education, smoking status, triglycerides, physical activity, alcohol intake, and systolic blood pressure. Solvent exposure intensity score levels are 0, 1-39, 40-79, >=80 for None, Low, Medium and High respectively. Number of participants at risk in solvent exposure intensity score categories (None, Low, Medium, and High) were 3640, 2332, 1053, and 497 respectively. †No. of deaths for all cause mortality do not add up to 4485 because of missing information for exposure intensity scores.

Ptrend


Ptrend

Ptrend Lung cancer

Ptrend Any cancer

Ptrend Stroke

CHD

Ptrend


Ptrend

Cause All causes†

Table 5

1.00 0.96 0.92 5.66 0.022

1.00 0.79 1.15 2.27 0.333 1.00 1.01 1.12 1.18 0.083 1.00 1.02 1.23 1.97 < 0.001 1.00 0.95 1.33 1.10 0.113

1.00 0.88 1.09 1.76 0.052

0.75, 1.22 0.55, 1.55 2.95, 10.86

0.75, 1.21 0.87, 2.04 0.27, 4.48

0.90, 1.14 0.99, 1.54 1.18, 3.30

0.82, 1.23 0.76, 1.67 0.38, 3.71

0.65, 0.96 0.81, 1.62 1.07, 4.84

0.77, 1.00 0.86, 1.39 0.99, 3.12

Adjusted* HR 95% CI 1.00 0.94 0.88, 1.00 1.13 0.99, 1.28 2.15 1.63, 2.85 < 0.001

Associations of solvent exposure intensity scores at baseline with all cause and cause-specific mortality by latency, Honolulu Heart Program, 1965–1998

212 L.E. Charles et al. / Occupational exposures and mortality


ployed in a pesticide manufacturing factory were studied by Grover and colleagues (2003) who reported a significant increase in DNA damage caused by occupational exposure to a mixture of pesticides [13]. As discussed by Petrovitch and colleagues (2002), a number of the HHP study participants were employed on large sugarcane and pineapple plantations where large amounts of insecticides and herbicides were used [23]. The insecticides most frequently used in the pineapple industry were the organochlorines dichlorodiphenyltrichloroethane (DDR), heptachlor, lindane, and chlordane and the organophosphates malathion and diazinon [14]. Herbicides were the primary type of pesticides (> 90%) used on sugarcane, but constituted only 32% of all pesticides used in Hawaii. Synthetic herbicides used during 1945–1965 included pentachlorophenol, diuron, dalapon, sodium trichloroacetate, and the triazines-trazine and ametryn. Plantation workers were also exposed to other substances in the dusty work environment such as manganese which is known to be at high levels in the Hawaiian soil [11]. Exposure to metals and solvents was also associated with an increased risk of mortality from all causes, cancers, and respiratory diseases. Using data from the NHANES II and the NHANES II Mortality Follow-up Study (NH2MS), Wu and colleagues (2003) showed that individuals with the highest level (top 10th percentile) of serum iron or copper at baseline had a high risk of dying from cancer [34]. Another investigation which used data from the National Longitudinal Mortality Study found greater mortality rates, although not statistically significant, for brain cancer among individuals in jobs potentially involving lead exposure [30]. A nested case-control study using civilian workers employed at a naval shipyard reported that solvent exposure (including benzene and carbon tetrachloride) was significantly associated with leukemia mortality after adjusting for risk factors [19]. In contrast, the risk of mortality among painters, processing operators/assistants, electroplaters, and other workers who were routinely exposed to various solvents was not significantly increased for total cancer or specific cancers [7]. Several metals are known to have cytotoxic, neurotoxic, or mutagenic effects, and exposure to the vaporized metal fumes during the welding process has been shown to increase inflammatory cytokines in the lungs and cause respiratory illnesses [4,26]. Solvents are also known to damage DNA resulting in cancer and other health disorders [12,29].

213

Latency analysis is appropriate for studies of occupational exposures and chronic diseases because the true intervals between the exposures and outcomes are usually not known [10]. We conducted analyses for 0-year (full exposure), 5-year, 10-year, and 15-year latency intervals. With the exception of a few mortality outcomes, the strongest exposure-response linear trends were seen with exposure to pesticides, metals, and solvents approximately 15 years prior to death. We assessed effect modification by tricep skinfold thickness and smoking status. No significant interaction was seen for either of these variables. It has been suggested that pesticide levels might be higher in participants who were more obese [20], yet associations were similar in those with smaller and larger skinfold thickness. Tobacco consumption appears to increase the risk of toxicity due to certain pesticides [21], but our results did not show stronger associations among smokers. Our outcome was mortality, yet there are some advantages to studying outcomes of incidence rather than mortality. Mortality is influenced not only by etiologic factors but also by factors that affect prognosis such as access to health care, type of health care, etc. Major strengths of the study include the prospective design, adjudication of underlying cause of death by an expert physician committee using standardized criteria, and expert assessment of the occupational exposure information. In addition, mortality data were obtained from multiple sources and the ascertainment of vital status was high given very minimal out-migration from the state. Also, because the cohort was geographically stable, no persons were lost to follow-up. We excluded persons with prevalent CHD, stroke and cancer from the study population. The large sample size is another strength of the study, allowing sufficient numbers at each level of exposure and enabling stratification. Finally, we were able to estimate latency effects, adjust for several confounding factors, and assess the presence or absence of effect modification. In summary, occupational exposure to pesticides, metals, and solvents obtained during middle age was independently associated with increased mortality from all causes, cancer, and in specific cases, circulatory diseases. Exposures occurring approximately 15 years prior to death appear to be etiologically important in these associations. It is possible that decreased exposure through use of personal protective equipment or engineering controls could reduce the mortality burden on workers who regularly use these agents. Future studies should continue to investigate the relationship between these occupational exposures and mortality with assessment for latency effects.

214


Acknowledgements This study was supported by a grant from the U.S. Department of the Army (DAMD17-98-1-8621), by the National Institutes of Health (National Institute on Aging contract N01-AG-4-2149 and grant 1-R01AG17155-01A1, National Heart, Lung, and Blood Institute contract N01-HC-05102, and a National Institute of Neurological Disorders and Stroke grant 1-R01NS41265-01), by the National Institute for Occupational Safety and Health (Contract HELD0080060), and by the Medical Research Service Office of Research and Development, Department of Veterans Affairs. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health or the other Government agencies, and no official endorsement should be inferred. The authors have no conflict of interests.

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