american journal of industrial medicine volume 31 issue 5 1997 [doi...

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Mortality Among aCohort of

Electric UtilityWorkers, 19601991

Michael A.Kelsh,MPH,MA, PhD,1* and Jack D.Sahl,MS,MPH, PhD2

Overall mortality trends among an electric utility workforce are examined. The study cohort

(n 5 40,335) included all workers with at least 1 year of work experience from 19601991;

3,753 deaths were observed in this cohort. Standardized mortality ratios (SMRs) and internal

cohort analyses were used to assess mortality trends for the entire cohort and for specific

occupational groups. Most SMRs were #1.0 and were generally lower for noncancer

(cardiovascular, COPD, and injuries) than for cancer mortality. Compared to offce staff, rateratios (RR) were higher for respiratory cancers for field staff [(RR5 2.3, 95% CI, 1.05.0)

linecrew (RR 5 2.2 95% CI, 1.53.1), and power plant occupations (RR 5 2.4, 95% CI,

1.63.6)]. Nonmanagement occupations had rate ratios for motor vehicle injuries and all

types of injuries, within a range of 2.54.7, with all lower CIs.1.0. The healthy worker effect

is an important factor in explaining the difference between SMR and internal cohort analyses

results. The SMR results indicate that this workforce has lower rates for overall mortality,

cardiovascular disease, cancer and nonintentional injury. A consistent finding in the internal

cohort analyses that merits further research was higher mortality rates for respiratory cancer

and injuries among nonoffce staff.Am. J. Ind. Med. 31:534544, 1997. r 1997 Wiley-Liss, Inc.

KEY WORDS: mortality; electric utility workers; cohort; healthy worker effect

INTRODUCTION

Electric utility workers can be exposed to a wide range

of chemical and physical agents. These exposures can

include polychlorinated biphenyls (PCBs), chemical sol-

vents (e.g. benzene, toluene), wood preservatives, pesticides

and herbicides, lead and heavy metals (e.g., chromium and

nickel), asbestos, noise, extremes of environmental heat and

cold, and electromagnetic fields spanning the frequency range of

ionizing radiation, visible light, radio and microwave, and power

frequency fields.This workforcealso shares a range of exposures

from the community in which they live and exposures from their

diet, exercise, and use of alcohol and cigarettes.

Few studies have comprehensively analyzed mortality

trends among an electric utility workforce or among utility

workers in general. Such an analysis is useful in providing a

better understanding of overall mortality trends that should

help identify and prioritize efforts to improve occupational

and public health for this workforce.As part of a comprehen-

sive health research program, mortality data were collected

and linked with personnel and occupational history informa-

tion. Previous analyses of this workforce have focused on

PCB exposures [Sahl et al., 1985], power frequency mag-

netic field exposures [Sahl et al., 1994], power frequency

magnetic field exposure and cancer occurrence [Sahl et al.,

1993], and injury occurrence [Kelsh and Sahl, 1996; Sahl et

al., 1997].

The focus of this report is to provide an overview of the

mortality experience among this workforce. We wanted first

to compare the mortality experience for the electric utility

cohort to that of the general population. Second, we wanted

to compare mortality risk between occupational groups

within our utility worker cohort. The second type of

comparisons provides an assessment for potential life-style

and occupational impacts. Information on the relative mortal

1EcoAnalysis, Inc., Ojai, CA.2Southern California EdisonCompany, Rosemead, CA.

ContractGrantsponsor: Southern California Edison Company, HealthResearch

andEvaluation Division.

*Correspondence to: Dr. Michael A. Kelsh, Environmental Health Strategies,

Inc., 149 Commonwealth Dr., Menlo Park, CA 94025. E-mail: Mkelsh@

envhealth.com

Acceptedfor publication9 October 1996

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 31:534544 (1997)

r 1997 Wiley-Liss, Inc.



ity experience within the cohort will serve as a better guide

for identifying research priorities.

METHODS

CohortandGeneral PopulationMortalityDataDefinitions and Sources

The occupational cohort consisted of all noncontract

personnel who worked for the Southern California Edison

Company (Edison) for at least 1 year between 1960 and

1991. Occupational and demographic information was

abstracted from company personnel records (computer

files, microfilmed records, benefits and personnel folders,

and employment cards). These data were linked with vital

status and cause of death information. Annual age, sex, and

race-specific mortality rates for the Edison workers and the

general population residing in Los Angeles, Orange,

Riverside, and San Bernardino counties were calculatedusing company personnel data, public mortality data, and

U.S. census information.

Vital Status Assignment andCauseof DeathClassification

We submitted record linkage data on personnel who

were retired, terminated, or known deceased to several data

clearance services to determine whether, and in what state,

the employee had died. The data clearance services included

the California Automated Mortality Linkage System

(CAMLIS) [Arrellano, 1986], the National Death Index

[NDI, 1985], and the Social Security Administration (SSA)

beneficiary records files [Aziz et al., 1982]. Death certifi-

cates were obtained based on information provided by

CAMLIS, NDI and SSA records. Edison records also

provided some death certificates that were not provided by

the states or that were unavailable because the employee

died out of the United States. We considered persons to be

alive if they were active workers. Inactive workers were

considered alive if there was no indication of death from

Edison records or CAMLIS, NDI, and SSA data clearance

procedures.

The International Classification of Diseases (ICD) under-

lying and associated causes of death codes were abstractedfrom the death certificate. Only underlying causes of death

were analyzed for comparative purposes with population

mortality data. If the ICD underlying cause of death code

was not available on the death certificate, a nosologist coded

the underlying cause of death into the appropriate ICD

revision (7th, 8th, or 9th). As part of an earlier analysis of

magnetic field exposures and cancer mortality, all death

certificates were also coded into the ICD 9th revision codes.

An occupational classification system was developed specifi-

cally for this workforce for health analyses purposes. The

primary objectives of the occupational classification system

were (1) to provide a consistent occupational grouping that

accounts for historical changes in jobs, and (2) to collapse

similar job titles into homogeneous groups with respect to

job tasks and work environments. We further collapsed our

20 broad occupational categories into seven general groups:(1) management and professional; (2) administrative, techni-

cal, and clerical office workers; (3) service, material han-

dlers and drivers; (4) meter readers and field representatives;

(5) linecrew (lineman, groundman, tree trimmers); (6) plant

operators; and (7) plant craft workers (electricians, mechan-

ics, machinists, welders, carpenters, and painters). These

categories represent different work activities and work

environments within this workforce.

We defined an employees usual occupation as the

occupation held for the longest time while employed at

Edison. Usual occupation was treated as a fixed variable in

the analysis, unlike time dependent procedures used for

assigning specific exposure scores. Job titles can represent a

variety of exposures that we have not specified at this time.

We also divided the total cohort into two groups based on

length of service:#15 years and.15 years.

Supplemental Data

Information on personal life-style, such as smoking,

alcohol consumption, and other factors, was not available

for all individuals of the study cohort. However, several

surveys on smoking patterns and alcohol consumption were

conducted as part of ongoing occupational research pro-grams at Edison. As part of a study to evaluate the impacts of

implementing a smoke-free work environment policy, a

smoking prevalence survey was conducted in 1993 through

the use of telephone interviews at the worksite among a

stratified random sample of Edison workers. These survey

data were used to derive estimates of smoking preference by

occupation. Smoking history was categorized as current

smoker,former smoker, or never smoked.

In a separate evaluation project of Nuclear Regulatory

Commission (NRC) and Department of Transportation

(DOT)-mandated substance abuse (drug and alcohol) testing

programs, questionnaire data were collected on typical

alcohol consumption. The survey sample included all DOT

and NRC program participants (those workers involved in

safety-sensitive occupations such as involving nuclear

power or transportation activities) and a stratified random

sample of other Edison employees (stratified by occupation).

This survey was conducted in March 1995. Two types of

alcohol consumption data are presented: (1) the frequency of

consumption, and (2) the frequency of episodes of alcohol

consumption involving five or more drinks (often referred to as

bingedrinking).

535Mortality Among a Cohort of Electric Utility Workers



Statistical Methods

Standardized mortality ratio (SMR) analyses and inter-

nal cohort analyses were applied to the mortality data

[Checkoway et al., 1989, Rothman, 1986]. For the internal

cohort analyses, the administrative, technical, and clericaloccupations were classified as the reference group, based on

their large size and the observation that this group generally

had the lowest SMRs when compared to the general

population. We tabulated follow-up time from January 1,

1960 to the end of study date, December 31, 1991 using a

modification of the Person-Years program [Coleman et

al., 1989]. Using MantelHaenszel procedures for person-

time data [Mantel and Haenszel, 1959; Greenland and

Robins, 1985], we calculated summary rate ratios based on

sex and for 5-year age intervals beginning with the 15- to

19-year age group and ending with 75- to 79-year-old

subjects. Former employees over 80 years old were ex-

cluded from the analysis because the cause of death informa-tion for these age groups is less reliable than for younger age

groups. (When 801-year-olds were included, this did not

change the results reported here.)

Cohort analyses (SMR and internal cohort) included

both male and female workers. We compared the underlying

cause of death for the six occupational groups to the internal

reference group (administrative, technical, and clerical of-

fice staff). SMR analyses were performed for all Edison

workers combined and for the seven occupational sub-

groups. The cohort was also categorized according to the

length of employment with Edison. Two cutpoints were

selected to assess employment duration effects: (1) ,10

years and$10 years, and (2) ,15 years and$15 years. Wealso calculated SMRs and rate ratios for the subgroup of

workers who were active employees as of January 1, 1960

and the subgroup who began employment January 1, 1960 or

later. Mortality rates for the southern California counties

were used as the comparison group in the SMR analysis

because they represented the general population from

which the workforce arose. Ninety-five percent confidence

intervals for the SMRs were obtained using an approxima-

tion procedure that assumes the denominator (the number of

population cases) to be constant and that the observed

number of cases (in the workforce) for a specific cause of

death follows a Poisson distribution [Rothman and Broice,

1979; Checkoway et al., 1989]. Confidence intervals for rate

ratio estimates (internal cohort analyses) were calculated

using GreenlandRobinsmethods [Greenland and Robins,1985].

RESULTS

This cohort includes 40,335 workers for the 32-year

period, 1960 to 1991. Fifty-six percent of this cohort were

not working as of 1991. They had either left the company,

retired or died. Forty-four percent of the cohort were active

workers (Table I). We observed 3,772 deaths among this

workforce. We were unable to obtain death certificates for 19

people (0.1% of the deceased group). Males comprise about

three quarters of the worker cohort. As of 1990, 65% of the

cohort was 50 years old or younger; 10.6% were 5059years old (Table I). The cohort is predominantly white

(75.5%), with Hispanics as the next largest ethnic group

(12.0%), followed by blacks (6.3%). The demographic

profile of the deceased workers is substantially different,

however; 95% were white and 91.4% were male. Because of

the older age profile for whites, who accounted for most of

the deaths in this cohort, and the small number of events

among nonwhite race groups, especially when stratified by

age and occupation, we did not adjust for race in the

mortality analyses. These figures reflect the rapidly chang-

TABLE I. Demographic and Vital Status Summaryof Electric Utility

Cohort, 19601991

Vital Status Characteristics

as of 12/31/91

Total Cohort Deceased Workers

Number Percent Number Percent

Classification

Active worker 17,635 43.8

Out of service (alive) 13,454 33.4

Retired (alive) 5,345 13.3

Deceased(deathcertificateavailable) 3,753 9.3

Deceased(nodeathcertificate) 19 ,.01

Sex

Male 30,450 75.5 3,434 91.5

Female 9,788 24.3 319 8.5

Missing 97 0.2 0 0.0

BirthDecade

187089 2 ,.0005 2 0.1

189099 389 1.0 384 10.2

190009 1,428 3.5 1,085 28.9

191019 2,235 5.5 909 24.2

192029 4,270 10.6 723 19.3

193039 5,761 14.3 288 7.7

194049 11,770 29.2 260 6.9

195059 9,862 24.5 86 2.3

196069 4,334 10.7 16 0.4

197074 194 0.5

Unknown 90 0.2

Race

Black 2,539 6.3 64 1.7

Asian/Pacific Islander 1,612 4.0 18 0.5AmericanIndian 368 0.9 18 0.5

Hispanic 4,856 12.0 57 1.5

White 30,872 76.6 3,593 95.7

Missing/Other 88 0.2 3 0.1

Totals 40,335 100.0 3,753 100.0

536 Kelsh and Sahl



ing ethnic and demographic composition of this workforce.

Since the 1960s, the age profile of the active workforce has

shifted to older age groups, with a larger proportion of 40- to

49-year-old and 50- to 59-year-old workers (data not shown).

Occupational Profile

The occupational profile of the electric utility workforce

by employment years, follow-up years, and number of

employees is presented in Table II. The average length of

service among all employees was 13.1 years, with a standard

deviation of 9.6 years. In terms of the number of employees,

clerical and technical personnel are the largest groups

followed by linecrew personnel. The large proportion of

employment and follow-up time for linecrew and field and

craft workers relative to the number of workers suggests that

these occupations tend to stay in the workforce longer than cler-

ical and technical personnel. We were unable to obtain occupa-

tional information for 6.9% of the cohort which represented

4.3% of the employment years and 9.8% of the follow-up years.

These data are combined with the Other category in Table II.

Smokingand Alcohol

Office staff had the lowest prevalence of smoking,

measured either as a current (11%) or former smoker (30%).

Management staff had similar prevalences for current smok-

ing status, but a higher percentage of former smokers

compared to office staff. Service/labor employees had the

highest prevalence of cigarette smoking (22%), while trade

and craft occupations had a smoking prevalence of 18%. For

all occupational groups there were higher percentages of

former smoking status, within a range of 3040%. The

prevalence of current or former smoking status combined

ranged from 41% for office staff to 62% for service/labor

occupations. The combined smoking prevalence (current

plus former) may be a better reflection of the smoking status

of this cohort during periods of time relevant to disease

outcomes analyzed in this study. The occupational catego-

ries of management, lineman, meter readers, plant operators,

and trade/craft workers all had combined smoking prevalences of

5060%. The response rate for the smoking survey was 91%.

There were similar self-reported alcohol consumption

patterns for the seven electric utility occupational categories

measured either by frequency of consumption (of anyamount) or by episodes of binge drinking (data not

shown). However, service and meter reader occupations had

11% or more workers reporting binge drinking three times or

more per month, compared to an average of 6.4% for the

other occupational groups. Lineman and management had

the highest percentage of drinkers with 13% and 12%

reporting five or more drinking occasions per week. The

response rate for this survey was 30%.

UnderlyingCauseof DeathDistributionbySexAmongElectricUtilityWorkers

Cardiovascular diseases were the leading cause of deathamong male employees. For female employees, cancer (all

types) was the leading cause of death (Table III). Among

male workers, respiratory cancers were the most common

type of cancer. Other more common cancers were digestive,

prostate, and colon cancers. Lymphoma and leukemia ac-

counted for 1.9% and 1.4%, respectively, of all deaths

among male employees. There were no male breast cancers

observed in the cohort. Chronic obstructive pulmonary

disease (COPD), suicide, and influenza each accounted for

at least 2% of the deaths among males. All other specific

TABLE II. Occupational Profile of Electric UtilityWorkers, 19601991

Occupational Group

Employment

yearsa % of total

Follow-up

yearsb % of total

Usual

occupationc % of total

Management/Specialist/Supervisor 53987.7 9.6 61639.3 9.6 3526 8.7

Administrative/Technical/Clerical 163096.7 29.0 211924.7 32.9 14672 36.4

Service/Labord 30516.1 5.4 33869.5 5.3 2719 6.7

Meter readers/Field service 17570.6 3.1 19899.8 3.1 1747 4.3

Linemen/Service appliance 103449.9 18.4 111189.2 17.3 5718 14.2

Trade/Craft 80229.6 14.3 94948.5 14.8 6222 15.4

Plantoperatorse 46154.5 8.2 46941.5 7.3 2958 7.3

Other and missing 67306.5 12.0 63011.9 9.8 2773 6.9

Totals 562311.6 100.0 643424.2 100.0 40335 100.0

aEmploymentyears include workhistory fromfirst in-service date (includingpriorto1960)todate of retirement or termination.bFollow-up yearsinclude studyfollow-up time byusual occupational categoryuntil end of studydate(12/31/91) ordateof death.cNumberof workers. Usual occupationdefined as theoccupationheldfor thelongesttime whileemployedatEdison.dService occupationsinclude securitystaff, janitors, porters, foodservice, andlandscaping/gardeningoccupations.e

Plantoperators include control roomoperators, plant equipmentoperators, andsubstation operators.




causes of death accounted for less than 1% of the deaths

among male workers (Table III). Breast cancer was the most

common cancer among female workers followed by respira-

tory cancers. After cancer and heart disease, injuries were

the third most common cause of death. Both males andfemales had similar proportions of deaths due to injuries

(7.6% and 7.7%). The totals for the underlying cause of

death include all individuals in the cohort.

SMRAnalysis for SelectedCauses of Death

Standardized mortality ratios were calculated excluding

801-year-olds and individuals who were missing demo-

graphic or in-service information. Twenty-nine records

(deaths) were excluded because of missing demographic or

in-service data, and 513 deaths were excluded because their

age was$80 years. This reduced the total number of deaths

from 3,753 to 3,211 for the SMR analysis. Among the entireEdison cohort, consistently low SMRs (,1.0) were ob-

served for all selected causes of death except prostate cancer

and leukemia (Table IV). The SMRs for prostate cancer and

leukemia were 1.04 and 1.07, respectively. The SMRs were

generally lower for noncancer outcomes (COPD, cardiovas-

cular disease, injuries and suicide) than for cancer outcomes.

The upper confidence limits for all causes, all cancers

combined, respiratory cancers, digestive system cancers,

cardiovascular disease, COPD, injuries, and suicide were all

TABLE III. UnderlyingCauseof DeathDistributionbySexAmong Electric UtilityWorkers

Underlying cause of death (ICD-9 Codes)

M ales Females Totals

# males % of males % of total # females % of females % of total Total number Percent of total

All Causes (00009999) 3434 100 91.5 319 100 8.5 3753 100

Cardiovascular (39004489) 1466 42.7 39.1 95 29.8 2.5 1561 41.6

Ischemic Heart Disease(41004149) 969 28.2 25.8 51 16.0 1.4 1020 27.2

OtherCardiovascular (39004489)

(excluding41004149 &43004389) 321 9.3 8.6 25 7.8 0.7 346 9.2

Cerebrovascular (43004389) 176 5.1 4.7 19 6.0 0.5 195 5.2

Cancers (14002089) 958 27.9 25.5 130 40.8 3.5 1088 29.0

Respiratory(16001659) 360 10.5 9.6 19 6.0 0.5 379 10.1

Digestive (15001599) (excluding colon, 15301539) 117 3.4 3.1 17 5.3 0.5 134 3.6

Prostate(18501859) 95 2.8 2.5 0 0 0 95 2.5

Lymphoma(20002039) 65 1.9 1.7 5 1.6 0.1 70 1.9

Leukemia(20402089) 48 1.4 1.3 3 0.9 0.1 51 1.4

Breast (17401759) 0 0 0 34 10.7 0.9 34 0.9

Brain(19101919) 25 0.7 0.7 5 1.6 0.1 30 0.8

Colon(15301539)* 98 2.9 2.6 15 4.7 0.4 113 3.0

Other (in 14002089) (not in anyof the ranges listed above) 150 4.4 4.0 32 10.0 0.9 182 4.8

Injuries (80009499) 268 7.8 7.1 24 7.5 0.6 292 7.8

Motor VehicleInjuries (81008259) 128 3.7 3.4 15 4.7 0.4 143 3.8

Other Accidents (in 80009499) (not in 81008259) 140 4.1 3.7 9 2.8 0.2 149 4

Chronic Obstructive

PulmonaryDisease(COPD)(49004969) 129 3.8 3.4 9 2.8 0.2 138 3.7

Suicide(95009599) 96 2.8 2.6 9 2.8 0.2 105 2.8

Influenza/Pneumonia(48004879) 74 2.2 2.0 4 1.3 0.1 78 2.1

Diabetes (25002509) 29 0.8 0.8 3 0.9 0.1 32 0.9

Homicide(96009599) 28 0.8 0.8 6 1.9 0.2 34 0.9

Infectious Disease (00011399, not in 04200449) 29 0.8 0.8 1 0.3 ,0.1 30 0.8AIDS (04200449) 17 0.5 0.5 1 0.3 ,0.1 18 0.5

Alzheimers Disease(3310) 11 0.3 0.3 2 0.6 0.1 13 0.3

Parkinsons Disease(332) 9 0.3 0.2 3 0.9 0.1 12 0.3

Other 318 9.3 8.5 31 9.7 0.8 349 9.3

Unknown(0000) 2 0.1 0.1 1 0.3 ,0.1 3 0.1

538 Kelsh and Sahl



,1.0. The SMRs for the higher categories of length of

employment (.10 years and .15 years) were very similar

to the findings presented for the entire cohort (data not

shown). Workers with $10 years of employment had

slightly higher SMRs than those with,10 years. The results

were the same for the 15-year dichotomization of the cohort

data. Because of the relative stability of the workforce and

the fact that the average length of employment was 13 years,

the SMR findings for the total cohort reflect nearly the same

SMRs as that for the longer-term workers. Age adjustment

procedures for the SMR calculations also account for length

of employment because of the high correlation between age

and employment duration in this cohort.

Administrative/technical and management personnel

generally had lower SMRs than other occupational groups,

except for colon and prostate cancers, where the SMRs were

slightly above 1.0 (although neither SMR was statistically

significant) (Table V). Among field, service, linecrew, and

power station workers, the results follow the same pattern as

the entire cohort. Most SMRs were ,1.0 (Tables V, VI). For

craft workers the SMRs for leukemias, lymphomas, andprostate cancers were slightly.1.0. Meter readers and Field

services representatives (FSRs) had elevated SMRs for brain

cancer and colon cancer; however, both observations were

based on three observed cases and therefore had wide

confidence intervals (Table V). SMR analyses that focus on

specific occupations (Tables V, VI) include 2,593 of the

3,211 included in the companywide SMR analysis. Occupa-

tions labeled as other or missing (Table II) were not

included in the occupation-specific SMR analysis.

Internal CohortAnalysisfor Selected Causes of Death

Among mortality outcomes, the most consistently ele-

vated rate ratios were for nonintentional injuries (all injury

types and motor vehicle injuries) and suicide among field,

linecrew, and craft occupations. Another consistent finding

was that relative to the reference group, nearly all other

occupational groups had elevated rate ratios for respiratory

cancers. Management staff had ratios near 1.2 (CI, 0.71.9),

whereas service, field staff, linecrew, and power plant

occupations had respiratory cancer rate ratios within a range

of 1.92.5 with 95% confidence intervals ranging from 1.0

(lower) to 5.0 (upper) (Table VII). All occupational groups,

except management, had elevated rate ratios for all causes of

death combined (range 1.321.78). These rates were driven

primarily by higher rates for cardiovascular disease. All

occupational groups except management and trade/craft

workers, had higher rates for all cancers combined, with rate

ratios within a range of 1.341.44 and all lower 95%

confidence limits exceeding 1.0 for service, lineman, meterreaders, and plant operations occupational categories (TableVII).

Management personnel had elevated rate ratios for

leukemias, brain cancers, and digestive cancers [1.9 (95%

CI, 0.75.4), 1.7 (95% CI, 0.46.7), and 1.8 (95% CI,

0.93.5), respectively], although all lower confidence inter-

vals were below 1.0. Most other specific cause of death

ratios for this group were below or near 1.0. The highest rate

ratios for lineman occupations were for all injuries and

motor vehicle injuries [4.2 (95% CI 2.96.2) and 3.4 (95%

TABLE IV. Standardized MortalityRatios (SMRs)Among Electric UtilityWorkers for Selected Causes of Death

Underlying cause of death (ICD-9 codes)

M ales Females Totals

OBS SM R 95% CI OBS SMR 95% CI OBS SMR 95% CI

Cardiovascular (3900 4489) 1211 0.63 0.59 0.66 66 0.51 0.40 0.65 1277 0.62 0.59 0.65

Cancers (14002089) 869 0.86 0.800.92 113 0.84 0.691.01 982 0.86 0.800.91

Respiratory (1600 1659) 328 0.92 0.82 1.03 18 0.73 0.43 1.16 346 0.91 0.821.01

Digestive(15001599)(excludingcolon, 15301539) 109 0.60 0.490.72 13 0.82 0.441.41 122 0.62 0.510.74

Prostate(18501859) 68 1.04 0.811.32 0 68 1.04 0.811.32

Lymphoma (20002039) 66 1.04 0.811.32 5 0.72 0.231.69 71 1.01 0.791.27

Leukemia (20402089) 45 1.13 0.821.51 3 0.58 0.121.71 48 1.07 0.791.41

Breast (17401759) 0 0.00 26 0.80 0.521.17 26 0.77 0.501.13

Brain(19101919) 25 0.81 0.521.19 4 1.13 0.302.90 29 0.84 0.561.21

Colon(15301539) 80 0.97 0.771.21 13 1.28 0.682.20 93 1.00 0.811.23

Injuries (80009499) 263 0.76 0.670.85 22 0.75 0.471.14 285 0.76 0.670.85

MotorVehicleInjuries(81008259) 130 0.80 0.670.95 14 0.94 0.521.58 144 0.82 0.690.96

Chronic ObstructivePulmonaryDisease(COPD)(49004969) 91 0.62 0.500.76 8 0.70 0.301.38 99 0.62 0.510.76

Suicide (95009599) 95 0.62 0.500.75 9 0.53 0.241.01 104 0.61 0.500.74




TABLE V. Age- and Sex-AdjustedSMR Analysis for Selected Causes of DeathbyOccupational Category: Administrative,

Management, andService Occupations

Cause of deatha

Administrative/ Technical Management/ Professional Service/ Labor

Observed SMR 95% CI Observed SMR 95% CI Observed SM R 95% CI

All causes 598 0.51 0.470.55 229 0.50 0.440.57 226 0.75 0.650.85

Major cardiovascular 223 0.5 0.440.57 103 0.53 0.430.64 82 0.64 0.510.80

All cancers 206 0.71 0.620.81 79 0.72 0.570.90 72 1.01 0.791.27

Respiratory cancer 51 0.58 0.430.76 23 0.62 0.390.93 34 1.34 0.931.87

Digestivecancerb 22 0.48 0.300.72 14 0.74 0.401.24 6 0.47 0.171.03

Prostate cancer 15 1.19 0.671.97 8 1.28 0.552.51 3 0.70 0.142.05

Lymphomas 14 0.81 0.441.35 6 0.90 0.331.96 4 0.93 0.252.39

Leukemia 8 0.69 0.301.37 6 1.43 0.523.12 3 1.12 0.233.28

Breast cancer c 13 0.62 0.331.06 0 0.00 0.001.36 2 3.03 0.3410.94

Brain cancer 5 0.55 0.181.29 3 0.90 0.182.64 2 0.94 0.113.41

Colon cancer 30 1.33 0.901.90 6 0.67 0.251.47 3 0.52 0.101.52

Injuries 36 0.37 0.260.51 5 0.16 0.050.36 18 0.83 0.491.31

Motor vehicle injury 18 0.39 0.230.62 1 0.07 0.000.38 8 0.78 0.341.54

COPD 24 0.67 0.431.00 3 0.20 0.040.58 7 0.71 0.281.47

Suicide 18 0.39 0.230.62 5 0.33 0.110.78 8 0.81 0.351.60

aExcludes death thatoccurredamongindividualswho wereclassifiedas other ormissing. N5 618.bExcludes coloncancers.cAll femalebreastcancers, 0 male breastcancers.

TABLE VI. Age- andSex-AdjustedSMRAnalysis forSelectedCauses ofDeathbyOccupational Category: Field, Linecrew, andPowerStationWorkers

Cause of deatha

Linem en/ Service appliance M eter reader/ Field service Plant operations Trade/ craft

Observed SMRa 9 5% CI Ob se rved SM Ra 9 5% CI Observed SM Ra 9 5% CI Ob se rve d SM Ra 95% CI

All causes 627 0.68 0.63 0.74 74 0.73 0.57 0.92 333 0.72 0.64 0.80 506 0.60 0.55 0.65

Majorcardiovascular 217 0.58 0.500.66 25 0.73 0.471.08 130 0.65 0.540.77 216 0.60 0.520.68

All cancers 195 0.96 0.831.11 18 0.92 0.551.46 103 0.98 0.801.19 144 0.74 0.630.87

Respiratorycancer 76 1.07 0.841.33 7 1.14 0.462.35 44 1.21 0.881.62 53 0.77 0.571.00

Digestivecancerb 25 0.70 0.451.03 2 0.61 0.072.22 12 0.64 0.331.13 18 0.52 0.31 0.82

Prostate cancer 18 1.49 0.88 2.35 0 0.00 0.00 3.82 4 0.57 0.15 1.47 13 1.06 0.571.82

Lymphomas 18 1.37 0.812.17 1 0.71 0.013.97 9 1.40 0.642.66 8 0.66 0.291.31

Leukemia 9 1.08 0.492.06 1 1.14 0.016.32 3 0.74 0.152.16 10 1.34 0.642.47

Breast cancerc 1 3.57 0.05 19.87 0 0.00 0.0011.46 0 0.00 0.005.56 0 0.00 0.00 10.79

Brain cancer 4 0.60 0.161.53 3 4.23 0.8512.35 3 0.99 0.202.89 4 0.66 0.181.70

Colon cancer 12 0.74 0.381.30 3 2.01 0.40 5.88 16 1.86 1.07 3.03 16 1.02 0.581.65

Injuries 90 1.09 0.871.34 12 0.87 0.451.52 37 1.08 0.761.49 43 0.68 0.490.92

Motorvehicleinjury 35 0.89 0.621.24 8 1.17 0.502.30 21 1.32 0.822.02 29 0.99 0.661.42

COPD 22 0.79 0.491.20 1 0.41 0.012.28 9 0.57 0.261.08 16 0.58 0.330.94

Suicide 22 0.61 0.380.92 3 0.55 0.111.59 13 0.85 0.451.46 19 0.66 0.401.03

aExcludes deathsthat occurredamong individuals whowereclassifiedas otheror missing. N5 618.bExcludes coloncancers.cAll femalebreastcancers, 0 male breastcancers.

540 Kelsh and Sahl



CI 1.95.9), respectively]. In addition to respiratory cancers,

among lineman occupations, specific cancers that had rate

ratios .1.5 included lymphomas, prostate, digestive, and

leukemia. Meter reader and field services occupations had

higher ratios for brain cancer and leukemia. Plant operator

occupations had elevated rate ratios for lymphomas and

digestive cancers. In addition to respiratory cancer, trade and

craft occupations had elevated leukemia rates; however,

most other cancer rate ratios were near 1.0.

For each of the seven occupational categories, we

divided the workers into two groups: those active as of

January 1, 1960 (the start date of our cohort definitions) and

those active after January 1, 1960. We then calculated rate

ratios relative to the administrative/technical classification.

The rationale for these analyses was that the survivorcohort as of 1960 may be different than the workers starting

after 1960. We present data for selected occupational

categories (service/labor, linemen, and trade/craft) where we

had sufficient numbers of workers and death events to

conduct these analyses (Table VIII). For the most part, the

overall results are closer to the subcohort who were active

workers as of January 1, 1960. This is because most of the

death events occurred among these workers. In comparing

rate ratios between the active as of 1960 subcohorts and the

active after 1960 subcohorts, we generally observed higher

rate ratios in the latter group, although none of these

differences is statistically significant.

DISCUSSION

These SMR findings emphasize the improved health

status among a stable, financially secure worker population

with adequate access to health care. When comparing the

entire electric utility cohort or specific occupational groups

to the general population, the SMRs were #1.0 for nearly all

mortality outcomes. This result has four components to

consider. First, there is some degree of organizational and

self-selection into the cohort. Second, continued member-

ship in the workforce may be differential by underlying

health status. Taken together, these represent the healthyworker effect [Howe et al., 1988; Arrigi and Hertz-

Picciotto, 1994; Wen and Tsai, 1982; Wilcosky and Wing,

1987]. As a measure of the strength of the healthy worker

effect, COPD mortality can be used as an indicator of

selection for good health status [Park et al., 1991]. For this

electric utility cohort, the SMRs for COPD and cardiovascu-

lar disease for all workers and all occupational groups were

low, indicating a strong healthy worker effect. Third, the

cohort may have different personal exposures than the

general population in areas like diet, exercise, alcohol

TABLE VII. Internal Cohort Analysis for Selected Causes of Death byOccupational Category, 19601991

Mortality

outcome

Management/

Professional Service/ Labor Linem en

Meter reader/

Fie ld se rvic e Pla nt o pe ra tion s Tr ad e/ cr af t

mRRa,b,c 9 5% CI m RRa,b,c 9 5% CI m RRa,b,c 9 5% CI m RRa,b,c 9 5% CI m RRa,b,c 9 5% CI m RRa,b,c 95% CI

All causes 1.02 0.881.19 1.59 1.371.86 1.57 1.411.76 1.78 1.392.28 1.58 1.391.81 1.32 1.171.49

Major cardiovascular 1.19 0.941.50 1.48 1.151.91 1.42 1.181.71 1.71 1.132.58 1.56 1.261.94 1.44 1.191.73

All cancers 1.01 0.781.31 1.44 1.101.89 1.41 1.161.71 1.34 0.822.18 1.40 1.111.78 1.07 0.861.32

Respiratory cancer 1.17 0.711.91 2.64 1.714.07 2.19 1.543.12 2.25 1.015.00 2.39 1.603.58 1.55 1.052.28

Digestivecancerd 1.76 0.893.46 1.21 0.483.04 1.73 0.973.07 1.25 0.295.36 1.63 0.823.26 1.28 0.682.43

Prostatecancer 1.25 0.532.96 0.77 0.222.66 1.67 0.843.31 0.60 0.201.81 1.18 0.562.48

Lymphomas 1.22 0.463.23 1.28 0.423.94 1.96 0.973.99 0.96 0.118.51 2.12 0.914.90 0.95 0.392.30

Leukemia 1.89 0.665.41 1.55 0.435.61 1.66 0.654.24 1.93 0.2515.05 0.98 0.263.66 1.83 0.724.62

Breast cancere 0.65 0.142.92 0.13 0.020.89

Braincancer 1.66 0.416.66 1.60 0.327.98 1.26 0.354.50 10.19 2.3144.96 1.78 0.437.32 1.36 0.404.59

Coloncancer 0.52 0.221.24 0.40 0.121.32 0.59 0.301.14 1.53 0.455.21 1.38 0.742.56 0.81 0.451.48

Injuries 0.46 0.181.22 2.76 1.574.83 4.24 2.896.22 3.49 1.806.76 3.91 2.486.16 2.48 1.603.83

Motor vehicleinjury 0.21 0.031.62 2.63 1.136.09 3.36 1.905.94 4.26 1.849.85 4.68 2.478.89 3.55 1.976.39

COPD 0.31 0.091.02 1.20 0.522.77 1.28 0.722.30 0.59 0.084.23 0.91 0.431.95 0.97 0.521.82

Suicide 0.91 0.332.47 2.23 0.965.20 2.03 1.093.76 2.01 0.567.14 2.65 1.265.54 1.98 1.033.82

aExcludes 801 year olds.bMantel Haenszel summaryrateratios (age- andsex-adjusted).cReferencegroupadministrative/technical/clerical occupations(see TableIV for number of events in each occupational group).dExcludes coloncancers.eFemalesonly, nomale breastcancersobserved.




consumption, or cigarette smoking. Fourth, with respect to

occupational exposures in this industry, there may be few

exposure effects on health. It is possible that for disease

outcomes where the SMRs are near 1.0, there may be some

exposure health effects that are masked by the healthy

worker selection biases.

Internal cohort analyses provide an alternative reference

group instead of the general population that reduces differ-

ences in employment status and the provision of health care.

Accounting for both of these factors helps to reduce the

potential bias due to the healthy worker effect [Park et al.,

1991; Wen and Tsai, 1982; Wilcosky and Wing, 1987]. We

used the occupational group with the lowest SMRs (adminis-

trative/technical personnel) as the reference group in the

internal cohort analyses. This created numerous elevated

rate ratio estimates among the other occupational groups.

Our internal cohort analyses revealed substantial varia-tion in mortality risk between occupational groups. These

variations may be attributable to three components. First,

there are likely selection factors that influence the composi-

tion of these occupational groups. This is synonymous to the

healthy worker effect when comparing our working cohort

to the general population. Our findings for the separate

analyses of workers active as of 1960 versus workers active

after 1960 suggest a healthy survivor effect occurring in this

cohort, because the early subcohorts had, in general, lower

rate ratios than the latter group. However, these analyses are

limited by small numbers. Second, life-style choices and

social, economic, and cultural influences are likely to vary

by occupational group. Third, work-related exposures will

also be different. Consistently higher respiratory cancer

among nonoffice employees highlights the need for addi-

tional research on the occurrence of cigarette smoking and

workplace exposures potentially associated with these type

of cancers (e.g., asbestos, airborne solvent exposures, dust

and particulate exposures, and other workplace exposures).

Although we observed consistent elevated rate ratios for

respiratory cancer, the exposures across these groups can

vary widely. In addition, when we compared smoking

history between occupations, we observed some variation.

However, we did not observe excess mortality due to COPD,

which has been used as a proxy for smoking history. The rate

ratios for leukemia, which has been associated with benzene,

solvent, ionizing radiation and magnetic field exposures,were inconsistent (Gilbert and Marks, 1979; Theriault et al.,

1994). They were higher among occupations with low

exposure levels to these agents (managers and meter read-

ers) and lower among plant operations occupations, who

probably have higher exposures to these agents. Lineman

and trade/craft occupations had moderately higher rate ratios

for leukemias. For lymphomas, a cancer also associated with

many of these agents, there were higher rate ratios (near 2.0)

for lineman and plant operations occupations, yet a low ratio

among trade/craft occupations.

TABLE VIII. Cohort Analyses for Selected Occupational Groups byWorkStatus as of 1960

Cause of deatha

Service/ Labor Linemen Trade/ Craft

Act ive before 1960 Act ive af ter 1960 Act ive before 1960 Act ive af ter 1960 Act ive before 1960 Act ive af ter 1960

RR 95% CI RR 95% CI RR 95% CI RR 95% CI RR 95% CI RR 95% CI

All causes 1.58 1.311.91 1.80 1.372.34 1.37 1.201.55 2.00 1.542.58 1.23 1.061.41 1.48 1.161.87

Major cardiovascular 1.44 1.071.94 2.00 1.183.39 1.28 1.041.56 0.52 0.191.39 1.36 1.111.66 1.28 0.752.17

All cancers 1.30 0.911.86 1.71 1.112.63 1.33 1.061.67 1.63 1.012.60 1.06 0.821.35 1.05 0.681.62

Respiratorycancer 2.34 1.364.02 3.92 1.788.62 1.82 1.222.70 4.22 1.5911.20 1.40 0.912.15 1.95 0.814.72

Digestivecancerb 0.67 0.153.00 2.08 0.518.37 1.78 0.883.58 1.30 0.414.13 1.45 0.693.03 0.82 0.223.05

Prostatecancer 0.30 0.042.37 4.68 0.4251.64 1.50 0.753.02 0 0.87 0.391.97 8.39 0.9673.60

Lymphomas 1.10 0.235.13 2.00 0.3611.10 1.98 0.894.41 0.55 0.064.94 1.03 0.382.75 0.48 0.054.14

Leukemia 0.74 0.096.04 3.70 0.6122.50 1.28 0.423.87 3.81 0.3640.60 1.85 0.665.22 1.22 0.1212.0

Breast cancerc 0.98 0.118.28 0.40 0.043.61 0 0.47 0.054.37 0 0

Braincancer 1.58 0.1615.40 1.57 0.1813.40 0.99 0.195.17 2.99 0.1368.90 0.90 0.165.18 2.51 0.3716.91

Coloncancer 0.54 0.161.82 0 0.39 0.180.85 3.13 0.8212.00 0.61 0.311.22 1.97 0.527.48

Injuries 3.34 1.388.12 2.57 1.112.63 3.02 1.555.89 5.19 3.158.56 0.88 0.362.15 3.83 2.286.43

Motor vehicleinjury 5.44 1.0827.40 2.00 0.755.31 4.32 1.2215.30 3.49 1.766.92 1.77 0.388.18 4.40 2.328.34

COPD 1.10 0.42 2.90 2.82 0.44 17.92 1.27 0.69 2.32 0 0.94 0.48 1.82 0.71 0.07 7.19

Suicide 1.44 0.316.82 2.94 0.998.76 1.50 0.573.97 2.43 1.005.90 2.26 0.895.77 1.63 0.634.19

aExcludes 801 year olds.bExcludes coloncancers.cFemalesonly, nomale breastcancersobserved.

542 Kelsh and Sahl



A consistent association was found between mortality

outcomes and occupation for nonintentional injuries, particu-

larly motor vehicle injuries. Nonoffice occupations had rate

ratios within a range of 2.64.7 for motor vehicle injuries.

Fatal motor vehicle injuries while performing company

duties are rare and do not account for these differences. TheSMRs for injuries indicate lower risk than for the general

population, and this has been the finding among most

mortality analyses of occupational cohorts. However, few

studies have examined within-cohort variation for the risk of

fatal injuries. A recently completed study among Canadian

utility workers found elevated rate ratios for mortality due to

nonintentional injury and violence among those workers

with higher exposures to electric fields [Baris et al., 1996a].

This classification of Canadian workers includes several of

the nonoffice occupations in the Edison cohort; however,

our analyses are not based on electric or magnetic field

exposure classification, but rather on job titles (usual occu-

pation).Factors associated with some of these occupations such

as shiftwork, overtime work, and fatigue may contribute to

the increased risk of nonwork fatal injuries. However,

preliminary analysis of work-related injury data has not

suggested increased injury risk for shift workers or work

during time of disaster response (unpublished data). Other

personal factors such as increased recreational driving for

certain occupational groups or different alcohol consump-

tion patterns may also explain these differences.

Self-reported alcohol consumption data, obtained from

a sample of the current workforce, did not vary across

occupational groups in a pattern similar to the injury

mortality rates. These survey data although useful, are

limited by low response, the fact that they are group

(ecological) rather than individual data and represent behav-

iors by the current workforce, not necessarily the historical

cohort. Alcohol consumption self-reporting may also vary

by occupation, with certain groups more likely to underre-

port their consumption patterns.

Our mortality findings may also be driven by an

unusually low injury fatality rate among the comparison

group, administrative/technical office workers. These factors

should be evaluated in future case-control studies. Another

noncancer outcome that was consistently associated with

nonoffice occupations was suicide. Risk factors for suicideinclude marital status, age, sex, and depression. In a study

that evaluated the relationship between magnetic fields and

depression, Savitz and colleagues found that the prevalence

of depression among electrical workers was not elevated

when compared to nonelectrical workers, although there was

a suggestion of increased prevalence among one subgroup,

electricians [Savitz et al., 1994]. Among Canadian utility

workers, there was an increase risk of suicide observed in

relation to electric field exposures; however most exposure

indices did not suggest an association. Also, the dose-

response trends were not consistent and the study was

limited by a small sample size [Baris et al., 1996b].

We have previously reported results for all cancers

combined, leukemias, lymphomas, and brain cancers and

their relation to power frequency magnetic fields [Sahl et al.,

1993]. The findings presented in this analysis are some-what different due to several factors. First, we have ex-

panded the cohort to include three additional years of

follow-up. Second, we used a revised occupational classifi-

cation system; and third, our reference group in the latest

analyses was defined as administrative, technical and cleri-

cal staff without any regard to magnetic field exposures. In

our magnetic field exposure and cancer analyses, the refer-

ence group included service/labor and meter reader occupa-

tional groups, which have higher rate ratios for several

cancer and noncancer mortality outcomes. The lower mor-

tality rate in the current reference group compared to

our first reference group produced higher relative ratio

results.The limitations of the study include the use of job titles

instead of developing a series of specific job exposure

matrices. In addition, we have only selected the usual

occupation to represent the workers occupational history.

All these job title/cancer outcome associations are also

limited by low study power and potential exposure misclas-

sification. Future analyses will focus on specific exposures,

and cumulative exposure scores will be developed using job

exposure matrices and the workers complete occupational

history. Although we provide some information on smoking

patterns and alcohol consumption in the current workforce,

direct individual information and other confounding informa-

tion was not available. The mortality experience of this

electric utility cohort may be unique and not represent the

experience of other electric utility groups. We did not

observe an excess of breast cancer as previously reported

(Loomis et al., 1994). However, these findings are consistent

with the SMR results of a cohort of 138,905 male electric

utility workers selected from five U.S. electric utility

companies [Savitz and Loomis, 1995] and 21,744 male

Canadian electric utility workers [Baris et al., 1996a] and

with cancer mortality among Scandinavian utility workers

[Tornquist et al., 1986].

The main purposes of this overall mortality analysis

were (1) to assess whether any major health hazards werepresent in this cohort of workers, and (2) to use the mortality

findings as a guide in developing more targeted research that

focuses on the potential relationships of mortality outcomes

and specific exposures in community, personal, and work

environments. Despite the limitations in this design and

analysis, our findings suggest that relative to the general

Southern California population, this workforce has lower

overall mortality, less cardiovascular disease and cancer, and

lower mortality rates due to nonintentional injury. These

findings are consistent with many occupational studies that




compare their workers mortality experience to that of the

general population. Our findings highlight the substantial

variation in mortality risk across different occupational

groups within the same industry. The higher rates of

respiratory cancer, nonintentional injuries, and suicide among

nonoffice occupational groups merit further research on bothoccupational and nonoccupational factors. If these associa-

tions persist across different studies, further research of

specific exposures in these groups is warranted.

ACKNOWLEDGMENTS

The authors acknowledge the valuable contributions of

Delia Garnes, Rick Sands, Karen Haines, Dena Sherick, and

Carolyn Watkins for their work in project administration,

data programming, manuscript preparation, and data coding.

Funding was provided by the Southern California Edison

Company, Health Research and Evaluation Division.

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