Monitoring of unfavorable reproductive outcome (URO) among occupationally exposed groups

The Science o f the Total Environment, 3 2 ( 1 9 8 4 ) 3 2 1 - - 3 3 4 Elsevier S c i e n c e P u b l i s h e r s B . V . , A m s t e r d a m - - P r i n t e d in T h e N e t h e r l a n d s

321

MONITORING OF UNFAVORABLE REPRODUCTIVE OUTCOME (URO) AMONGOCCUPATIONALLY EXPOSED GROUPS J.R. GOLDSMITH1, Ro ISRAELI2, and J. ELKINS1 1Epidemiology and Health Evaluation Unit, University Center for Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel 2Department of Occupational Health, "Soroka" Medical Center, University Center f o r Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel

ABSTPACT In the Negev Region of I s r a e l , population 300,000, with a centralized health care and health data system, we propose to monitor associations of occupational exposure with the following URO (approximate rates in parenthesis): i n f e r t i l i t y (10%), spontaneous abortion (10%), s t i l l b i r t h (1%), pregnancy complications (5%), specific b i r t h defects (1%), a l l b i r t h defects (5%), low b i r t h weight (5%), neonatal morbidity (5%); a l l URO (25%). C r i t i c a l covariates include smoking, age, contraceptive use, coexisting disease, p a r i t y , spouse exposures, and past reprod u c t i v i t y history° Currently exposed women are estimated to include 150 in hosp i t a l operating rooms, 200 laboratory ~ r s , 75 chemical production workers and 20 in mercury thermometer factory; men include 5000 in chemical production, i000 in a g r i c u l t u r a l chemical use, lOOTn'-chemical laboratories and 200 in u n i v e r s i t y and hospital laboratories. Adjusting for expected turnover rates, we estimate that overall exposures which have risks of increased URO w i l l include about 5000 men and I000 women. Since p r i o r i t y in research resources goes to most feasible detection and prevention con~inations, we define and examine "minimal detectable risk r a t i o s " based on expected populations sizes and i n c i dences f o r a two year cohort study with estimated one "exposed pregnancy" per f i v e person years in t h i s young population. We tabulate these r i s k ratios using a c u t o f f for false p o s i t i v e at p=O.05 and false negative at p=Oolo Sex r a t i o changes represent outcomes r e l a t i v e l y e a s i l y detected. Proposed application of these c r i t e r i a to Negev populations and an example of such applications to published work place exposures to dioxins are shown° INTRODUCTION One of the most important tasks for epidemiology in occupational health is to determine which occupational exposures are having an unfavorable effect on the health of the exposed populations. A serious shortcoming of a number of reports in occupational epidemiology is the interpretation of lack of s t a t i s t i c a l significance as inferring a lack of such unfavorable effects, when with sample sizes available only massively unfavorable changes could have been " s i g n i f i c a n t . " Given that in most studies, the sample size is fixed, that is the epidemiologist may not increase the number of persons exposed in order to conduct a more readily interpretable study, we face a dilemma concerning how to make our studies more

f~f~aR-9~.qTIgAl.~O.q DO

~

1~.g4 Elg~rler

S c i e n c e P u b l i s h e r s B.V_

322

useful f o r i d e n t i f i c a t i o n of hazard in time to protect the workers.

A monitor-

ing strategy which cumulates data over time and across types of unfavorable o u t comes is proposed.

We f i r s t

consider the c r i t e r i a f or d e t e c t a b i l i t y .

D e t e c t a b i l i t y in t h i s paper refers to the a b i l i t y to come to an acceptable i n t e r p r e t a t i o n , on the basis of usual s t a t i s t i c a l c r i t e r i a of the existence of a p o s i t i v e association of a defined occupational exposure to an increased r i s k of unfavorable reproductive outcomes of a couple, one of whom was exposed. D e t e c t a b i l i t y is defined in r e l a t i o n s h i p to a background level of outcomes expected among a non-exposed population, taking i n t o account other relevant v a r i ables and with specified levels of acceptable f als e p o s i t i v e and f a l s e negative rates° In the case o f unfavorable reproductive outcomes as a r e s u l t of exposure of e i t h e r parent, we propose that d e t e c t a b i l i t y in a monitoring programis l i k e l y to be good under two circumstances.

The f i r s t

is to choose a c r i t e r i o n of un-

favorable outcome which has a r e l a t i v e l y great frequency among the unexposed population.

The second is to pool comparable data from several studies of

several d i f f e r e n t outcomes.

We show t h a t , by applying well established s t a t i s -

t i c a l c r i t e r i a to the r e l a t i o n s h i p between sample size and r e l a t i v e r i s k , det e c t a b i l i t y of unfavorable reactions is more l i k e l y f o r r e l a t i v e l y frequent conditions l i k e spontaneous abortion rates or a l t e r a t i o n s of sex r a t i o o f o f f spring than f o r r e l a t i v e l y more uncommon outcomes such as f e t a l d e a t h ( s t i l l b i r t h s ) or congenital anomalies ( b i r t h defects}° (ref.

Since as B u f f l e r and Aase

i ) have shown in t h e i r recent review, many agents and most mechanisms of

unfavorable reproductive outcome have m u l t i p l e possible manifestations depending on (a) the time of exposure, (b) which parent is exposed and (c) dose, we often can select e i t h e r an outcome of r e l a t i v e l y good p o t e n t i a l d e t e c t a b i l i t y ( t h a t is r e l a t i v e l y high prevalence) or combine several outcomes to improve detectability°

These p r i n c i p l e s are applied to several recent problems.

CLASSIFICATION OF UNFAVORABLEREPRODUCTIVEOUTCOMES (URO} C l a s s i f i c a t i o n may be based on which parent is exposed, the time and dosage o f exposure with respect to reproductive events, and the general b i o l o g i c a l processes affected by exposures° ( r e f o l } the f i r s t

Following the c l a s s i f i c a t i o n of B u f f l e r and Aase

two may be combined simply into preconception exposures of

the f a t h e r, (for which the exposures in the months or weeks p r i o r to conception are most c r i t i c a l ) ,

preconception exposures of the mother (which have t h e i r

greatest impacts beginning with the prepubertal ages of the mother); exposures of the mother from conception onward f or which teratogenic effects are more l i k e l y when exposure is e a r l y in pregnancy, while more general biochemical or " n u t r i t i o n a l " effects are more l i k e l y l a t e r in pregnancy ( a f t e r the f i r s t t r i mester).

323

TABLE 1 Spectrum of reproductive outcomes noted in association with parental exposures to environmental agents Exposures I n f e r - Spont. Sex Fetal Neo- Low B i r t h Devel.Child Child t i l i t y Abort. Ratio Death Natal B i r t h Defct.Abnor-Malia- Death Chng. Late ~eath Weight mal nancy Maternal,preconception Oral ContraX X ceptives Irradiation,lo Maternal, post conception Ovulation stimulants Sex Hormones DES X Anticonvulsant Antimetabolite X Tranquilizers X Oral Anticoag. X X X Diabetes X X Alcohol X X X X X Irradiation,hi X X X X I r r a d i a t i o n , lo X X Anesthet. gas X Mercury X Lead X X X X Smoking c i g a r t . X Paternal Anticonvulsant Antineoplastic X Irradiation,hi X Irradiation,lo Anesthet. gas X Vinyl Chloride X Hydrocarbons Chloroprene X Kepone X X DBCP X X Dioxin ~ummary includes a l l p o s i t i v e associations from human population studies, withoutsystematic evaluation of the more than 200 studies as to study design sample size, strength of association, and handling of confounding variables. Lo and hi r e f e r to low dose and high dose r a d i a t i o n r e s p e c t i v e l y ; DES is d i e t h y l s t i l l b e s t r o l , DBCP is dibromochloro propane. Source: B u f f l e r & Aase ( r e f . 1) Table 1 indicates t h i s p a t t e r n . Among these four classes, male preconception ( I ) , early postconception ( I I I ) ,

female preconception ( I I ) ,

and l a t e r post-conception ( I V ) , the f o l l o w i n g types

of outcomes depending on dose and duration of exposures are relevant:

324

PROPOSED CLASSIFICATION OF UNFAVORABLEREPRODUCTIVEOUTCOMES(URO) Class

Parent Exposed

Time of Exposure

URO

I

Male

Preconception weeks

I n f e r t i l i t y , Spontaneous Abortion, A l t e r a ation in Sex Ratio, Birth Defects (mutational),Low B i r t h Weight

II

Female

Preconception I n f e r t i l i t y , Spontaneous Abortion, Alt er ayears or months in Sex Ratio, Birth Defects (mutational) Pregnancy Complications, S t i l l b i r t h , Low Birth Weight, Infant M o r t a l i t y

III

Female

Early Pregnancy

Spontaneous Abortion, Bir t h Defects (mutat i o n a l or teratogenic) S t i l l b i r t h , Infant M o r t a l i t y , Infant Morbidity

IV

Female

Late Pregnancy

S t i l l b i r t h , Pregnancy Complications, Low B i rt h Weight, Infant M o r t a l i t y , Infant Morbidity

Within these classes, i t is possible to distinguish t o x i c i t y due to a l t e r a tions in c e l l d i v i s i o n processes, which we could designate "nuclear t o x i c i t y " and impairment of somatic functions which sustain the health o f the fetus and i n f a n t , which we could designate "somatic t o x i c i t y . " first

For some effects in the

two classes we may say that there is "gametotoxicity" without specifying

whether i t is nuclear or somatic t o x i c i t y .

We shall leave f o r another context

the question of the c r i t e r i a of d e t e c t a b i l i t y of human mutation, as well as the possible r e l a t i o n s h i p of URO to risk o f carcinogenesis.

Neither do we deal with

impotence or mental health aspects of these expsoures and e f f e c t s . The major purpose of t h i s c l a s s i f i c a t i o n is to indicate that m u l t i p l e types of possible URO are associated with most types of occupational exposure which we shall wish to evaluate°

Many reports deal with a s in g le , usually infrequent

type of outcome (such as b i r t h defects), and as a r e s u l t , some of these reports come to a conclusion that the exposures do not have a detectable effect°

Others

base negative conclusions on sperm count or morphology, rather than outcomes. This paper examines the hypothesis that these types of monitoring may be biol o g i c a l l y erroneous, and can be traced to choice of an infrequent type of outcome or of a v a r i a b l e r e f l e c t i n g a single mechanism, which with l i m i t e d populations at risk are ! i k e l y to r e s u l t in s t a t i s t i c a l l y

n o n - s i g n i f i c a n t conclusions.

The

a l t e r n a t i v e p o s s i b i l i t i e s of examining URO w i t h i n the same class which have a greater expected prevalence, or examining the combined prevalence o f several poss i b l e URO or the combined results of several studies can be shown to be more l i k e l y to lead to s t a t i s t i c a l l y s i g n i f i c a n t results with the same level of Risk Ratio, or proportion of increased r i s k , when a true e f f e c t e x i s t s .

325

METHODS We have, with the help of Mrs. Saskia Beeser, used an i n t e r a c t i v e computer program representing the r e l a t i o n s h i p s between underlying prevalence in the nonexposed populations, sample size, and Minimal Detectable Relative Risk (MDRR), given a decision as to : Consider a Case-Control or Cohort Study Use a one-sided or two-sided test of s i g n i f i c a n c e Which level of s t a t i s t i c a l r i s k f o r Type I e r r o r ( f a l s e p o s i t i v e } is to be considered acceptable Which level of s t a t i s t i c a l risk f o r Type I I e r r o r (false negative) is to be considered acceptable. In order to more c l e a r l y r e f l e c t the r e l a t i o n s h i p of underlying, sample size and minimal detectable Relative Risk, we f i r s t

standardized the four c r i -

t e r i a l i s t e d above tn analysis nf: Cohort Studies One-sided tests Type I e r r o r deemed acceptable = 0.05 Type I I e r r o r deemed acceptable = 0.I0o To i l l u s t r a t e the r e s u l t s , we i n i t i a l l y

assume that a prevalence of O.Ol (1%)

applies to such effects (outcomes) as selected obvious b i r t h defects, or s t i l l b i r t h s ; that a prevalence of 0 . i 0 ( i e 10%) applies to such outcomes as spontaneous a b o r t i o n, i n f e r t i l i t y ,

serious pregnancy complications, or low b i r t h weight;

a prevalence of 0.25 may be chosen i n i t i a l l y a l l other URO taken together.

as r e f l e c t i n g i n f a n t morbidity or

We assume i n i t i a l l y

that other relevant variables

have s i m i l a r e f fe c ts in both exposed and unexposed populations.

We define "min-

imal detectable r e l a t i v e risks" as the lowest risk r a t i o which would be associated with a s i g n i f i c a n t l y p o s i t i v e r e s u l t , based on these standard assumptions and given sample sizes. RESULTS Tables 2, 3, and 4 show the r e l a t i o n s h i p s of sample size and Minimal Detectable Relative Risk f o r these three i l l u s t r a t i v e prevalence rates.

For conveni-

ence o f i n t e r p r e t a t i o n , we also tabulate in these tables the minimal detectable prevalence in the exposed group under these assumptions°

The sample size given

is based on the assumption that both an exposed and an unexposed cohort of t h i s size were followed through an "exposed" pregnancy.

The usual circumstanceis

that many more unexposed persons are p o t e n t i a l l y a v a i l a b l e f or inclusion in cohort studies.

When t h i s occurs, i t is usually f e a s i b l e to e i t h e r use the data

f o r unexposed persons as a basis f o r more accurately estimating the prevalence expected among the exposed and various subsets; or we can adjust, match or use

326

other methods based on the exact sample sizes f or the two populations. TABLE 2 Minimal Detectable Risk Ratios and prevalence in exposed group With underlying prevalence = 1% (0.01) ( i . e . Birth defects) Type I error = 0.05, Type I I = 0 . i 0 Sample Size 30 50 100 300 500 1000 3000 5000 *

Relative Risk

Prevalence in Exposed

26.0 17.7 10.5 5.O8 3.83 2°78 1o90 1.67

26% 17.7 10.5 5.O8 3.83 2.78 1o90 1o67

Sample size fo r both exposed and unexposed cohort° Twice t h i s number would be needed for comparisons.

TABLE 3 Minimal Detectable Risk Ratios and prevalence in exposed group With underlying prevalence = 10% (0o10) ( i . e . Spontaneous abortion) Type I e r r o r = 0°05, Type I I = 0.10 Sample Size 10 30 5O 100 300 500 I000 3000 5000

Relative Risk 6.82 4.21 3.37 2.57 1.83 1.62 1o43 1.24 1.18

Prevalence in Exposed % 68.2 42ol 33.7 25.7 18.3 16o2 14.3 12.8 11.8

In general, the minimal needed number of observations on both exposed and unexposed would be twice the sample size tabulated in Tables 2,3, and 4. Comparisons across such tables makes c lear that with a given Relative Risk, say 2.0, which is equivalent of a doubling of the underlying prevalence, the req u i s i t e sample size with an underlying prevalence of 0oi (10%) would only require between i00 and 300, and with an underlying prevalence of 0 . I (10%) would

327

only require between 100 and 300, and with an underlying prevalence o f 0.25 (25%} i t would require s l i g h t l y more than 50 persons in each group.

TABLE 4 Minimal Detectable Risk Ratios and prevalence in exposed groups With underlying prevalence = 0.25 (25%) (ioe. a l l URO) Type I e r r o r = 0.05, Type I I = 0o10

Sample Size

Relative Risk

6 10 30 50 100 300 500 I000 3000 50UO I0000

3.84 3.38 2.45 2o12 1.78 1.44 1.34 1.24 1.13 1o10 1o073

Prevalence in Exposed % 96.1 84°5 61o2 53.0 44°5 36°0 33°4 30.9 28.4 27.6 26.8

The exact numbers of persons in each group required under these conditions and stanHer~ assumntinns, (Cohort study, one-sided t e s t , Type I error=Oo05, Type I I error=Ool): TABLE 5 Underlying Prevalence Sample Size Minimal Detectable Relative Risk

0.01 2,517 2.0

0.05 471 2.0

0.10 216 2.0

0.15 131 2.0

0.25 63 2.0

DETECTABILITY OF CHANGES IN SEX RATIO Approximate odds f o r the b i r t h of e i t h e r a g i r l or boy as a r e s u l t of a given pregnancy are 0.5.

In fact s l i g h t l y more boys than g i r l s are born; the

most recent I s r a e l i figures are 51.45% boys, or 48.55% g i r l s . We have i d e n t i f i e d a preponderance of females among 12 children born to DBCP workers, a r e s u l t possibly related to an e f f e c t on the Y chromosome o Potashnik G, Goldsmith JR and I n s l e r V. "Dibromochloropropane-induced a l t e r a t i o n of the s e x - r a t i o in man" - submitted to Andrologia.

328

Other exposures, i . e . births.

X - r a y s , tend to lead to a h i g h e r p r o p o r t i o n o f male

This i s what is meant by a change in sex r a t i o .

In terms o f the calcu.

l a t i o n s used above, the u n d e r l y i n g prevalence f o r a female b i r t h a p p r o x i m a t e l y 0.5.

is 0°4855, or

Since we have seen t h a t as the u n d e r l y i n g prevalence i n -

creases, the sample s i z e r e q u i r e d f o r a given minimal d e t e c t a b l e r i s k r a t i o d i m i n i s h e s , we may c o n s i d e r limits

t o t h i s process.

to exact probabilities lity

t h a t change in sex r a t i o

i s about the u l t i m a t e in

A simple a p p l i c a t i o n o f the binomial theorem can lead f o r s p e c i f i e d numbers o f female b i r t h s .

(This p r o b a b i -

is e q u i v a l e n t t o t a k i n g account only o f the Type I e r r o r used a b o v e . ) .

An example o f the a p p l i c a t i o n s o f binomial p r o b a b i l i t y

f o r s p e c i f i c small num-

bers o f b i r t h s are shown in Table 6 ( f o r which p=0.4855i.

Since we are i n

TABLE 6 Binomial p r o b a b i l i t i e s

o f having a t l e a s t a s p e c i f i e d number of female

c h i l d r e n f o r a sample o f N b i r t h s when p = 0.4855

5 6 7 8 9 10 12 14 18 20 25

N-1

0.027 0o013 0.006 0.003 0°001 -#

0.170" 0°096 0°054 0.029 0.016 0.008 0.002 -

* #

S p e c i f i e d number o f females i n N b i r t h s N-2 N-3 N-4 N-5 N-7 N-9

N

+ 0o317 0.204 0.126 0.076 0.045 0.015 0.005 -

+ + + + 0.226 0.104 0°060 0.022 0.003 -

+ + + + + 0.167 0.073 0.011 0.004 -

+ + + + + 0.181 0.037 O.UI5 0.001

+ ÷ 0.203 0.106 0.012

÷ + + 0.085

N-tO

+ + 0.169

Once p r o b a b i l i t i e s exceed 0.1, r a t h e r than t a b u l a t e them they are shown + A p r o b a b i l i t y less than 0.001 is shown by -

search o f c o n d i t i o n s which produce s t a t i s t i c a l l y show~ nnly the f i r s t shown as ( + ) .

probability

Probabilities

exceeding 0 . I ;

significant

results,

higher probabilities

the t a b l e being

o f less than 0o001 c o r r e s p o n d i n g l y are shown as

(-). As an example as t o how the t a b l e could be read, f o r 8 b i r t h s e i g h t c h i l d r e n were g i r l s , 0.003.

the p r o b a b i l i t y

I f 7, ( N - I ) , b i r t h s were g i r l s ,

i n c l u d i n g 8) would be 0°029°

the p r o b a b i l i t y

The p r o b a b i l i t y

o f t h i s o r more ( i . e o

of 6, 7, o r 8 b i r t h s being g i r l s

0o126 but f o r a s m a l l e r number o f b i r t h s being g i r l s , h i g h e r , and the r e s u l t s not l i k e l y

(N-8) i f a l l

o f t h i s being due t o chance would be

the p r o b a b i l i t i e s

are

to be considered s i g n i f i c a n t .

I n c l u s i o n of Type I I e r r o r is h a r d l y r e l e v a n t in such a case since there i s

329

no p a r t i c u l a r r i s k associated with a false negative r e s u l t , as the word " r i s k " is usually used° That is to say, i t may be b i o l o g i c a l l y i n t e r e s t i n g to be able to say there is a greater than random p r o b a b i l i t y o f having a g i r l baby, but the l i t e r a l

risk is not of public health or personal relevance, compared to say,

having an abortion or complications of pregnancy or a baby with a b i r t h defect° For such an outcome, therefore, i t is not so important to include avoidance o f Type I I e r r o r , and therefore the binomial estimate o f p r o b a b i l i t y is suitable° SOME APPLICATIONS Townsend et al have reported a retrospective study of the reproductive events of wives of workers exposed to c hlor inat ed dioxins ~ref. 7}. covered a period of 1939 to 1975.

The data

A t o t a l of 930 men w~th p o t e n t i a l exposures

to dioxins were i d e n t i f i e d , along with a set of men not exposed who were matched by date o f h i r e .

Data were collected from wives of 370 out of 586 e l i g i b l e

women f o r the exposed group and 345 out of 559 e l i g i b l e wives in the comparison cohort.

Since some of the pregnancies in the exposed men's wives occurred

p r i o r to exposure, the data r e f l e c t e d 2031 unexposed conceptions and 737 exposed conceptions°

Data were tabulated f o r numbers of miscarriages, s t i l l -

b i r t h s , congenital malformations, i n f a n t deaths, other health defects among l i v e b i r t h s , and t o t a l unfavorable outcomes f o r a l l conceptions and f o r a l l live births.

No data on sex of the o f f s p r i n g are presented.

maternal covariates were considered:

Nine types of

age at conception, b i r t h control used,

complications during labor and d e l i v e r y (not here considered as an outcome), health problem o f mother during pregnancy, medication or treatment of mother during pregnancy, g r a v i d i t y , use of alcohol or tobacco during pregnancy, and whether or not mothers had "high r i s k " work during the pregnancy.

In the ex-

posed group, there were p r o p o r t i o n a l l y more older and multigravida mothers, and medication use and i l l n e s s e s were p r o p o r t i o n a t e l y more common among unexposed mothers.

Analyses were done by using Mantel-Haenszel and r e l a t e d methods°

None o f the o v e r a l l odds r a t i o s , crude or adjusted were said to be s t a t i s t i c a l l y significant.

Excerpted crude data are shown f o r i n t e r e s t i n g exclusive categor-

ies in Table 7.

Among c o - v a r i a b l e s p e c i f i c sub-tables, s i g n i f i c a n t l y elevated

odds r a t i o s were found f o r a group o f nine TCDD exposed conceptions which cont r l b u t e d three spontaneous abortions and s ix l i v e b i r t h s to mothers of 18-30 years of age and gravida 4+.

Since the analysis used overlapping categories,

t h i s set of deviant outcomes produced a number of " s i g n i f i c a n t " results among subtableso

There is no mention of any subtables with s i g n i f i c a n t l y elevated

congenital malformation rates. Table 7 shows some a t t r i b u t e s which appear surprisingo

The two highest re-

l a t i v e risks are f o r miscarriages among the "Other Dioxin" Subgroup with i year or more of exposure (R=1.611) and the congenital malformation rate f o r the TCDD

33O TABLE 7 Pregnancy outcome data f o r exposed and non-exposed cohorts of chemical workers, 1939-1975 Dow-Midland

Not Exposed Conceptions Miscarriages Rate

Stillbirths Rate

TCDD Only
Other Dioxins+TCDD A l l <1 y r 1 yr+

Exposed

2031 213

187 18

231 25

177 18

142 24

737 85

0.105

0.096

0.108

0~102

0.169

0.115

33

3

4

5

3

15

0.019

0.016

0o017

0°028

0.021

0.020

Live B i r t h s Congenital Malformations

1784 87

166 14

202 7

lb4 5

115 5

637 31

Rate*

0°049

0.084

0.035

0°033

0.044

0.049

Infant Mortality Rate*

A l l Unfavorable Outcomes Rate

*

39 0.022

372 0.184

Rates are per b i r t h .

Source:

4 0.024

39 0.209

2

3

0.010

0.020

38

31

0.164

0o175

1

10

0.009

0.016

33

141

0.213

0.191

A l l other rates are based on number of conceptions

Reference 7

only with less than 1 year of exposure (R=1.731),

Because the underlying pre-

valence in the unexposed is l a r g e r f o r miscarriages, a smaller p r o b a b i l i t y of t h i s d e v i a t i o n being due to chance is found than f o r the congenital malformation r a t e , which has a l a r g e r r e l a t i v e r i s k .

As the authors say, n e i t h e r r e s u l t is

less l i k e l y than p=O.05 usually used as the c r i t e r i o n f o r s t a t i s t i c a l

signifi-

cance IType I e r r o r ) . Although no dose or time trend data are presented, the authors did look f o r e f f e c t s of exposure i n t e n s i t y and r e p o r t t h a t no s t a t i s t i c a l l y

significant dif-

ferences were found. In the categories which were presented, the p o s s i b i l i t y is apparent t h a t the e a r l i e s t and possibly heaviest exposures could have had e f f e c t s which were d i l u ted by l a t e r and presumably lesser exposures°

Such gradients are worth looking

f o r , but a paradox then occurs in t h a t the sample size becomes smaller and even i f the r e l a t i v e r i s k is higher in such subsets, i t s s i g n i f i c a n c e cannot r e a d i l y be established ( i o e o , i t s d e t e c t a b i l i t y is poor)°

No trend based on duration of

exposures can be discerned from Table 7 f o r the data from which i t was excerpted)o One subset of exposures, we know, was s u f f i c i e n t to produce chloracneo

We

are not t o l d whether the wives of t h i s set of exposed men had any unusual preg-

331

nancy outcomes w i t h i n t h i s data set, other than being t o l d that "high p o t e n t i a l TCDD" exposure was assigned to the jobs involved in the process area at the time when chloracne occurred°

One is permitted to suppose that this represents the

11 moderate to high TCDD exposure subset of pregnancies (with no abnormalities) in t h e i r Table 50 Thus in t h i s large and apparently careful study, conscientious e f f o r t s were made f o r detection of possibly unfavorable outcomes w i t h i n the a v a i l a b l e populat i o n , and no convincing evidence of such outcome was found.

Although no data

are presented f o r low b i r t h weight, or pregnancy complications, these URO are u n l i k e l y with study of male exposures; while no data on sex r a t i o changes are presented, there are no experimental data suggesting effects of dioxins on spermatogenesis or sperm count, which might be associated with a l t e r a t i o n s in sex ratio°

These omissions are therefore not serious with respect to the i n t e r p r e -

t a t i o n of no detectable e f f e c t ° I t would have been desirable to v a l i d a t e a sample, at l e a s t , of reproductive records with hospitals or midical records° I t is important to r e c a l l that a l l o f the sources of variance considered in the s t a t i s t i c a l tests considered so f a r are sampling variances, and we assume that the determination of both numerator and denominator are made without e r r o r . or bias; that is there is no measurement e r r o r assumed°

I f any be present then

i t too must be included in the d e t e c t a b i l i t y r e l a t i o n s h i p , and w i l l i n v a r i a b l y impair d e t e c t a b i l i t y . A s a t i s f a c t o r y monitoring program might have involved pooling data from other exposed populations.

Kline and Stein (refo2) as well as 13uffler and Aase (refo

I) both point out the advantages of examining abortuses f o r chromosomal abnormalities. lities

The l a t t e r c i t e Boue and Boue as f i n d i n g 61.5% chromosomal abnorma-

among spontaneous abortions averaging 11.5 mean gestational weeks.

In-

duced abortions show 17o25% (at a mean of 7°6 gestational weeks), whereas l i v e births show rates of 5.15%o Unfortunately each of these estimates was from a d i f f e r e n t source°

Early f e t a l loss would also be useful as a sentinel of repro-

ductive t o x i c i t y , but very e a r l y f e t a l loss is d i f f i c u l t fidence.

to detect with much con-

We know of no occupational cohort study which has used these a t t r a c -

t i v e suggestions; each of these procedures poses problems of v a l i d i t y and the study of chromosomal abnormalities in abortuses is also a tedious and exacting laboratory t e s t .

332

APPLICATIONS TO POPULATIONSLIKELY TO BE EXPOSED IN THE NEGEV Because the health care system and health data system is u n i f i e d in the Negev Region of Israel (population about 300,0001, we have unusual opportunities to monitor both from records and interviews, associations of URO with occupational exposures to heat stress, mercury, chemical production, a g r i c u l t u r a l chemical use, u n i v e r s i t y l a b o r a t o r i e s , hospital operating rooms, and hospital laboratories.

From chemical industry rosters, f o r example, we i d e n t i f i e d 1422 persons,

including 1199 males from 20-60 years and 223 females 20-50, with about 50% and 7% respectively in production work.

We estimate that the f ollow ing numbers of

males and females are c u r r e n t l y occupationally exposed in the Negev to agents which could produce URO: Males Operating room and Anesthesla Hospital Laboratories Chemical Production Mercury A g r i c u l t u r a l Chemical Applications Chemical Research Laboratories

Females

50 200 5000

150 200 75 20

I000

-

100

50

From our knowledge of usual work force turnover rates, we estimate the number o f persons with recent exposures to be some m u l t i p l e of these figures.

Such

multiples range from 1.1 f o r male chemical production workers to 4.0 f o r women working with mercury thermometers. Applying these multiples and summing, we estimate 9050 men worked in jobs with possible exposures to agents which may produce URO and 1230 women with such exposures.

We believe t~at many men in chemical production would probably not

be meaningfully exposed to agents with a p o t e n t i a l to cause URO. Thus o v er all we expect about 5000 males and 1000 females to be or to have been at r i s k . With an estimated pregnancy rate of one per f i v e person-years of exposure, the most relevant minlmal sample sizes f o r "exposed" pregnancies would be f o r women's groups, 6, 30, and 100 f o r men 30, i00, 5000, and 3000.

The minimal de-

tectable r e l a t i v e risks f o r the range of useful prevalence rates and these sample sizes are:

333

Using Schlesselman r e l a t i o n s h i p , cut o f f f o r false p o s i t i v e at p=O.05 and false negative p=O.l. Expected Prevalence

Minimal Detectable RR for "Exposed Pregnancies" N=

6

30

1% ( s t i l l b i r t h , specific birth defects, i n f a n t m o r t a l i t y )

Not Detectable

10% (Spontaneous abortion infertility)

Not Detectable

25% ( a l l URO)

3.8

100

500

3000

10.5

3.8

1.9

4.Z1

2.6

1.6

1.3

2.5

1.8

1.3

1.1

For example, with 6 "exposed" pregnancies and Expected Incidence of 25% the minimal detectable RR of 3.8 x 6 = 5.8 would only be reached i f a l l 6 had URO. With 30 "Exposed" pregnancies and 10% incidence, 30 x 0 . i x 4.2 = 12.6; 13 observed would reach s i g n i f i c a n c e . We believe that such approaches as these are preferable to the isolated study of decreased sperm count (refs 5 and 4) or the comparisons of overall f e r t i l i t y rates ( r e f . 3 ) .

ACKNOWLEDGEMENT The authors have pleasure in acknowledging the assistance of Ms. Saskia Beeser who prepared the computer programs f o r sample size evaluations.

Her

research is supported by a grant from the United S t a t i s - l s r a e l Binational Science Foundation {BSF), Jerusalem, I s r a e l .

Dr. L i l y Neumann assisted us

in i n t e r p r e t i n g the binomial estimates of sex r a t i o .

334

REFERENCES 1 P.A. B u f f l e r and J.M. Aase, Genetic Risks and Environmental Surveillance: Epidemiological Aspects of Monitoring I n d u s t r i a l Populations for Environmental Mutagens. J. Occ. Med., 24 (1982) 305-314. 2 J. Kline, Z. Stein, B. Strobine et a l , Surveillance of Spontaneous Abortions: Power in Environmental Monitoring. Am. J. Epidemiol., 106 (1977)345-350. 3 R.J. Levine, M.J. Symons, S.A. Balogh, D.M. Arndt, N.T. Kaswandik and J.W. Gentile, A Method f o r Monitoring the F e r t i l i t y of Workers: Method and P i l o t Studies. J. Occ. Med., 22 (1980) 781-791. 4 C.R. Meyer, Semen Quality in Workers Exposed to Carbon D i s u l f i d e Compared to a Control Group from the Same Plant. J. Occ. Med., 23 (1981 435-439. 5 T. Milby and D. Whorton, Epidemiologic Assessment of Occupationally Related and chemically induced sperm count suppression. J. Occup. Med.,22(1980) 77-82. 6 J.J. Schlesselman, Sample Size Requirements in Cohort and Case-Control Studies of Disease. Am. J. Epidemiol., 99 (1974) 381-384. 7 J.C. Townsend, K.M. Bedner, P.F.D. Peenen, R.D. Olsen and R.R. Cook, Survey of Reproductive Events of Wives of Employees Exposed to Chlorinated Dioxinso Am. J. Epidemiology, 115 (1982} 695-713.