female labor force participation and female mortality in wisconsin 1974–1978

Sot. SC,. Md. Vol. ‘I. No 6. pp. h5.5 h65. IYX.5 Printed m Grear Brl~am All rrghb reserved

0277-9536/X5 53.00 + 0.00 Copyright 4, 1985 Pergamon Press Ltd

FEMALE LABOR FORCE PARTICIPATION AND FEMALE

MORTALITY IN WISCONSIN 1974-1978

MARIAN R. PASSANNANTE and CONSTANCE A. NATHANSON

‘Department of Preventive Medicine and Community Health, University of Medicine and Dentistry of New Jersey, 100 Bergen Street, Newark, NJ 07103 and ‘Department of Population Dynamics, The Johns

Hopkins University. Baltimore. MD 21218. U.S.A.

Abstract-The following research question is addressed in the study: what effect will the entrance of women into the labor force have on female mortality rates for all causes of death combined as well as specific causes relating to occupational stress, behavioral factors and physical hazards associated with occupation? This question is examined through comparisons of age, marital status and occupation-specific death rates for all causes of death combined and for selected causes of death.

Death certificates provided by the Wisconsin Bureau of Health Statistics for the years 19741978 and population data provided by the 1976 Survey of Income and Education were used to construct death rates. The death rates of the white civilian female population of Wisconsin 16-64 years of age were examined using exploratory data analysis techniques (schematic plots and median polish) and standard errors.

In general. the death rates of women in the labor force are substantially lower than those of housewives. These results may indicate that the role of housewife exposes women to health hazards. In addition, the results of this study may suggest some selectivity of healthy women into the labor force or a protective effect of labor force participation.

In a limited number of instances, labor force participants’ mortality rates exceed those of housewives. In the 6&64 year old population, white-collar workers, specifically, sales workers, managers and professionals, experience significantly higher death rates than housewives. In addition, specific groups of labor force participants experience significantly higher death rates than housewives for accidental deaths (i.e. laborers 16-44 and 45-54), deaths due to heart disease (i.e. laborers 45-54 and sales workers 60-64) and deaths due to malignant neoplasms (i.e. white-collar workers 60-64 years of age). The possibility that these instances indicate the direction of future mortality trends should be considered.

INTRODUCTION

The proportion of women in the United States labor force increased from 25.24% in 1949 to 41.7% in 1978. By the middle of 1977, approx. 41% of the country’s entire labor force was female, and 49% of all women 16 and older (40 million women) were members of the labor force [l]. The relationship between the recent increases in the number of women in the U.S. labor force and female mortality has become a popular issue. This relationship is examined in this study.

Few females are members of what traditionally have been considered highly hazardous occupations (e.g. mining, construction, transport and fishing occupations) which entail exposure to serious physical, chemical or biological hazards. However, many industries employing a large percentage of females (e.g. restaurant and hotel industries, food processing industries and hospitals) expose their employees to physical risks [2]. Recent studies also suggest that clerical workers may be exposed to hazardous ozone and methanol levels emanating from copying and duplicating machines [3,4]. Furthermore, many women are employed in manufacturing industries in which workers have a high risk of exposure to carcinogens [5].

In addition, reviews of the literature linking occupational sources of stress to physical and mental disease suggest a number of features of work stress with the potential to affect an individual’s health [6, 71.. The potential sources of stress in the work environment, such as working conditions [8], work

load [9, lo], role in the organization [5, 10, 111, career development [ 12, 131, organizational structure and climate [ 11,6] and the extra-organizational variables [ 14-161 that affect individuals [17] as well as general population phenomenon [ 181, interact and determine both coping and maladaptive behaviors as well as stress-related diseases.

As women enter the workplace they are met with these sources of work stress. However, their status as women may actually serve to increase this stress. For example, aside from role conflict when one’s job demands conflict with the specifications of the job, the additional role of worker as well as wife and mother might induce role strain [19]. In addition, sex discrimination on the job may increase work-related stress. Finally, the coping mechanisms used by females to adjust to stressful.situations may include assuming traditional ‘male behaviors’ associated with high male mortality (e.g. smoking, drinking, driving, suicide, homicide, low levels of health care utilization and little indulgence in the sick role) [20-221.

Of course, participation in the labor force is not necessarily associated with negative health outcomes [23,24]. The advantages of employment may out- weight the disadvantages, and in some cases may even reduce female mortality. Some researchers question the link between role conflict and overload to stress and negative health consequences. They suggest that role accumulation may bring both the direct and indirect benefits of economic gain and increased membership and affiliation to working women. An analysis of suicides in British Columbia suggests that

655

the positive effects of labor force participation out- weigh the negative [25].

While the earliest studies of occupational mortality concentrated on males [29. 301. the issues of female occupational mortality has recently received much attention. These recent occupational mortality studies present conflicting findings. In Framingham. Massachusetts, the study of 45-6.5 year old housewives, working women and men presented results which suggest a lack of association between employment status and coronary heart disease (CHD) in women. However, a higher incidence of CHD did appear among women with clerical jobs than among housewives [3 I].

In an analysis of the Wisconsin labor force, women in the professional and technical occupations had higher mortality than men in these occupations (ages 1664). Furthermore, females in the higher income occupations (e.g. professionals and managers) appeared to experience higher mortality than females in lower income occupations (e.g. salespersons) [32].

In a study of American physicians who died during the years 1969-1973, female physicians enjoyed greater longevity than females in the general population. However, the age-specific death rates for female physicians 3&34 and 40-44 were greater than the age-specific death rates for their male counterparts. While higher female physician age-specific death rates are explained as aberrations of the data (due to the small number of females in the age groups), when examined in the light of findings of other studies, the results seem worthy of further investigation [33, 341.

Finally, in a study of suicide among male and female physicians, female physicians experienced an excess of suicides in comparison with the general female population and an excess of suicides over male physicians (under 35 years of age) [35].

When interpreting the results of these occupational mortality studies, a number of factors such as the selection, marital status and socioeconomic status of the study population must be considered. Two longitudinal studies recently showed that the health of women has a significant effect on labor force participation in the United States [26]. That is, women who reported poor health or limited activity due to a health problem were more likely to leave the labor force. Furthermore, these same women were less likely to join the labor force. These results suggest that there is a selection of healthy women into the labor force. This selection, known as the ‘healthy worker effect’, makes the exploration of the labor force participation and mortality relationship rather difficult because the population in the labor force and those who stay home may not be equally likely to die from a particular disease. However, if female labor force participants’ death rates do exceed those of housewives in studies of occupational mortality, then the impact of labor force participation would

*The death certificate records used in the analysis were provided by the Bureau of Health Statistics of the Wisconsin Department of Health and Social Services. Any analyses. interpretations or conclusions reached using these data should be attributed to the authors and not to the providers of the data tape.

have to be sufficiently !arge to overcome this healthy worker phenomenon. Simrlarly. since the marital [27] and socioeconomic status [28] of labor force participants may differ from those of housewives and these factors independently affect mortality. these variables should be controlled for when exploring the possible impact of labor force participation on women’s mortality.

While the findings of recent studies are not conclu- sive. they suggest that mortality may be related to labor force status. A number of these studies even suggest that women in the highest income occupations may experience the highest mortality levels. sometimes approaching male mortality levels. These results clearly suggest the need for further research. Therefore, the following research question was addressed in this study: What <fleet will the entrance of women into the labor force hate on .femule

mortality rates for all causes qf death as well us spectjic causes relating to occupational.stress, behar - ioral factors and physical hazards associated with

occupation?

DATA

Data from the State of Wisconsin was used to examine the relatiohship between labor force participation and mortality. The decision to utilize Wis- consin data was based on the availability, quality, completeness and accuracy of the source of mortality data-death certificate records [36, 32. 371.

Mortality data *

The study population was limited to Wisconsin civilian residents, so that when death rates were calculated the numerators would be proper subsets of the denominators, That is, since only civilian state residents were enumerated in the 1976 intercensal population survey, and this information was used for the denominators of the death rates, the inclusion of non-residents and members of the military living on a base in the numerators would inflate the death rates. The study population was limited to the white population in Wisconsin because the small number of non-whites in Wisconsin (approx. 3%), makes sepa- rate detailed statistical analysis of this group very difficult. Furthermore, the inclusion of all races in the analysis might confound the results due to the substantial mortality differences between races. Finally, individuals 65 and over were eliminated from the analysis to avoid inaccuracies which appear when examining the occupation information from the death certificates of retired persons [29].

Data dejiciencies

Mortality data are collected using a standard death certificate issued by the United States Public Health Service. While some states modify the format of the certificate, the Wisconsin certificate closely conforms to the standard. Entries on the death certificate are filled in by funeral directors, physicians and medical examiners. A number of studies have attempted to assess the accuracy of vital registration data by matching census records with death certificate data [38,39]. These studies indicate that there are some

Female labor force participation

q is the survival rate and N is the total number of observations (i.e. the denominator of the death rate). The average p value or p is equal to the sum of the p values for each S-year period divided by 5:

d, d, _+‘+-+-+_

n, n4 1 = Zdi i5ti.

Using the SE formula (pqln)’ ’ substituting ,?J for p and 55 for n the formula will be

It should be noted that this formula is not strictly appropriate for the calculation of the standard error of a central death rate because the central death rate is not an ordinary binomial proportion. However, a comparison of standard errors based on the formula described above and based on a formula which more accurately accounts for the distribution of deaths in the interval sugggests that when the death rate is low. the difference between the standard errors which result from each formula is small [46]. Since the more accurate standard error formula requires a complicated set of calculations and the difference between the results based on each formula is minimal, the simpler formula was employed in this study.

Additional studies suggest that cause of death information gathered from death certificates may suffer from serious inaccuracies [40-42]. While these problems cannot be resolved in this analysis, the use of major cause of death categories rather than detailed cause of death listings, may lessen the impact of these inaccuracies on the results presented.

Finally, the accuracy of the reported occupation on the death certificate is of particular importance in this study of occupational mortality. The accuracy of reported occupation has been examined by matching death certificate and census records [29]. The results of this comparison suggest that the use of major occupational groupings rather than detailed categories provides a more accurate match between death certificate and census data occupational listings [29]. Therefore, major occupational groupings* were used to measure occupational affiliation in this analysis.

Other measures have been taken to lessen the impact of possible inaccuracies in the recording of the usualt occupation of an individual on death certificates. For example, the problems involved in the use of occupational listings from death certificates of retired individuals are diminished in this analysis by limiting the study population to women of pre- retirement age (under 65 years of age).

Population data

Information on the female population during the study period was needed in order to calculate death rates for this study. Detailed cross-tabulations of the population by age, sex, race, marital status, labor force status and occupation were not readily avail- able. Therefore, a sample of the 1976 Survey of Income and Education was used to provide the necessary population data for the analysis.

The Survey of Income and Education [43] included approx. 158,500 households from the 50 states and the District of Columbia. The Census Bureau conducted interviews (45 min in length) with the members of the households in the months of April and July of 1976. The Survey contains a large amount of information on the family and the individuals in the family. The variables used in this study were: age, sex, race, marital status, employment status and occupation of Wisconsin residents.

METHODOLOGY

The major unit of analysis in this study was the occupation-specific death rate. This death rate was calculated by dividing the number of individuals who died during the study period whose usual occupation was i, by the number of people in the population during that time period whose usual occupation was i. In addition to occupation, death rates were calculated specific for age, marital status and cause of death.

The death rates were calculated using death certificate data for the 5year period 1974-1978. Tabulations based on the 1976 Survey of Income and Education provided the mid-period population for this S-year period. Standard errors were calculated for all death rates:. Death rates were compared with

658 MARIAN R. PASSANNANTE and CWSTANCE A. NATHANSOV

one another by examining the difference between the two rates and the standard error of the difference.*

RESULTS

The central death rates were examined using box Examination of the age-specitic death rates of plots [44,45], an exploratory death analysis tech- housewives and female labor force participants Indi- nique. Box plots are simple and compact graphic cates that housewives experience a mortality disad- presentations of the distributions of comparison vantage when compared with women in the labor force, groupst. A more detailed examination of the popu- For the first three age groups (16-44, 45-54 and lation is possible using another exploratory data 55-59), death rates for housewives are approximately analysis technique-median polish [44]. This pro- twice as high as those of labor force participants. How- cedure allows one to examine batches of data in ever, in the oldest age group (60-64). there is verb relation to more than one variable and assess the little difference between the death rates of housewives relative importance of each variable:. and that of women in the labor force (see Table I ).

Exploratory data analysis techniques, developed by John Tukey, were used to analyze these death rates rather than more traditional confirmatory techniques. Both box plots and median polish procedures examine medians rather than means in order to avoid distortion due to outlier observations. Due to the questionable accuracy of female occupational death rates based on information from their death certificates, it was decided by the researchers to explore the data, rather than attempt to present results based on a confirmatory technique, such as analysis of variance [44,48].

When labor force participants’ death rates are examined by occupation category. housewives con- tinue to have much higher death rates than women in

the labor force at the first three age groups. However. at age 6&64, white-collar and blue-collar females experience higher death rates than housewives. and service workers experience a death rate which is onI> slightly lower than that of housewives. The convergence of the death rates of housewives and female labor force participants in the oldest age group ma) indicate an interesting mortality pattern that needs to be explored further. This convergence is illustrated in

Fig. I. The box plots in Fig. I show that, for the first three age groups, housewives’ death rates are outlier observations, while among 60-64 year olds. housewives experience the median death rate value.

*The difference between two rates and the standard error of the difference were compared using the following formula:

Dxa - Dxb

(SE’s + SE%)’ z

where Dxa and Dxh are death rates for each comparison group and SEcr and SEh are standard errors for the respective rates. When the test statistic is large (i.e. > 2). then the difference between the two rates was considered to be significant (i.e. greater than would have occurred by chance) [47].

tBoxes represent the middle 50% of the values in the distributions with the lower and upper boundaries representing the lower and upper quartiles of the distributions. The distance between the quartiles is known as Ihe spread: the asterisk inside the boxes represents the median value of the distribution. The vertical lines which emanate from either end of the boxes mark the values which are farthest from the boxes but within one midspread distance. Any values outside of these points are known as outliers and are identified by the symbol ‘0’. unless they are more than I.5 times the midspread distance away from the quartiles, in which case they are identified by the symbol ‘0’.

:Median polish assumes an additive row-plus-column fit:

J(i. j) = I + r(i) + c(j) + 2(i. j)

where i.j refers to the row and column respectively. The equation states that the response in the ith row and the jth column is equal lo the typical value plus the ith row effect plus the j th column effect plus the residual in the ith row and the jth column. In this study,,

DEATH RATE = typical + age effect + occupation death effect

rate + residual effect

The median polish procedure produces a listing which describes how well the model fits the data. i.e. what percent of the variation of the data is accounted for by the row-plus-column model, as well as the relative importance of variables in the model (e.g. age and occupation).

When the labor force is broken down into eleven occupation groups, the death rates of a number of occupation groups exceed those of housewives. In the 16-44 age group, laborers’ death rate exceeds that of housewives. Laborers and crafts workers 45-54 years of age experience significantly higher death rates than housewives. Among 55-59 year olds, crafts workers’ death rate slightly exceeds that of housewives. In addition, in the 6@-64 age group, housewives experience a death rate which is only slightly higher than the median death rate value. In the oldest age group. the death rates of five occupation groups exceed that of housewives-sales workers, professionals, managers, operatives and laborers. And the death rates belonging to members of the oldest white-collar occupation groups (i.e. sales workers, professionals and managers) are significantly higher than that of housewives (see Table 3).

A comparison of housewives with members of the eleven major occupational groups by age and marital status yields some interesting results (see Fig. 2). Divorced housewives experience the highest death rates for each age group, with the exception of 55-59 year old clerical and service workers. In general, married housewives experience higher death rates than members of the eleven occupation groups. How- ever, there are a few exceptions to this high married housewife mortality trend; death rates for married housewives are exceeded by laborers and crafts workers 16-44 and 45-54, by laborers 55-59 and by sales workers and managers 60-64 years of age. In the single population, housewives experience very low death rates, due to the fact that the number of deaths to single housewives during this period is so small (I 7 deaths). Perhaps this finding can be explained as a result of the ambiguous marital status-occupation combination of single housewives. Yet, it is interesting to note that among labor force participants,

Female labor force participation and mortality 659

Table I. Age-specific death rates (per 1000) of housewives and the female exnerienced labor force in Wisconsin. 19741978

Age

Housewives Labor force

N Rate SE N Rate SE

16-44 225.550 1.15 0.03 654.660 0.51 0.01 45m 54 82.718 5.44 0.1 I 159.212 2.33 0.05 55-59 49.955 8.44 0.18 68.967 4.73 0.12 60-64 57.718 10.96 0.19 44.323 10.12 0.21

Note: the differences between the death rates for housewives and for female labor force partrcrpants are statistically significant at the 0.05 level at all ages.

Table 2. Age-specific death rates (per 1000) of housewives and the female experienced labor force by occupation category ITI Wisconsm. 1974-1978

White-cdlar Blue-collar Farm workers Service workers Housewives

Age N Rate SE N Rate SE N Rate SE N Rate SE N Raw SE

1644 365.293 0.53 0.02 94.596 0.66 0.04 22.371 0.04 0.02 166.772 0.44 0.02 25.549 I.15 0.03 45-54 90.001 2.58 0.08 25.363 3.01 0.15 9714 0.12 0.05 3 I.280 I .99 0.1 I 82.7 I7 5.44 0.1 I 55-59 32,667 5.75 0.19 17. I05 4.26 0.22 3355 0.54 0.18 14.580 4.36 0.24 49,955 8.44 0.18 60-64 21.279 12.06 0.33 8383 II.26 0.52 2102 0.76 0.27 10,503 9.10 0.41 57,718 10.96 0.19

Note: differences between housewives’ and labor force participants’ age-specific death rates are significant at all ages except for 60-64 year old blue-collar workers

the single population experiences relatively high death rates; specifically, single clericals, professionals and operatives experience high death rate values. Lastly. widowed housewives have higher death rates than members of the eleven occupation groups in the 45-54 and 55-59 year age groups. However, for widowed females 16-44 and 60-64, the death rates for a number of occupation groups exceed those of housewives.

The results of the preceding analysis suggest that housewives usually experience higher mortality rates than labor force participants, even when controlling for age and marital status. The only strong exception to this pattern is among single housewives. However, because there are only a small number of single housewives and the classification is questionable, a comparison involving this group may not be very useful. Further exceptions to higher housewife mortality are generally accounted for by blue-collar, white-collar and service workers in the oldest age groups.

Another way to look at these data is to apply an analytical tool that allows one to examine these death

Scale .

Maximum ;a.ow

I x -*-

I K)UScwxVts

I . -+-

I I -.- I I -+-

I*! ; baustllws --- 0

i ‘i’ . .

. 1 ,*-.4 41-11 ss-I. W-M

Minimum ‘0.040

Fig. 1. Box plots of age-specific death rates of housewives and the experienced female labor force by occupation

category in Wisconsin. 1974-1978.

rates in relation to a number of variables. The examination of the age-specific death rates of women by occupation category suggests that the row-plus- column model fits relatively well. By applying Tukey’s median polish procedure to these death rates about 75% of the spread or variation in the data is accounted for by the row-plus-column model.

Table 4 presents the typical death rate value, age effects, occupation effects and residuals left after the median polish procedure is completed. The average age group and occupation category values can be obtained by adding the typical death rate value to the appropriate row or column effect value. For example, the average death rate value for housewives is 3.96 + 1.87. These values indicate that the average occupation death rate value for housewives is greater than the average values for members of the four occupation categories (i.e. white-collar, blue-collar, farm workers and service workers). Furthermore, among the members of the experienced labor force, white-collar workers experience the highest average death rate value.

An examination of the residuals produced by the procedure suggests that there are two occupation categories where the row-plus-column model does not fit well (i.e. residuals which are greater than or equal to twice the average residual size). The residuals for 16-44 and 60-64 year old farm workers are exceptionally large. However, the small number of deaths in each group over the 5-year period (5 and 8 deaths, respectively), probably account for the lack of fit. The residual for 60-64 year old white-collar females is also large, although less than twice the average ,residual size. Since the number of deaths of members of this group is sizable, the large residual may indicate that some factor other than age and occupation is affecting the mortality of this group. Therefore, white-collar females should be examined more closely.

An examination of white-collar females by marital status suggests that the model does not fit well for 60-64 year olds. in this particular age group the residuals which correspond to divorced, single and

660 MARIAN R. PASSANNANTE and CCINSTANCE A. NATHASSOL

Table 3. Age-specific death rates (per 1000) of housewives snd the female experienced labor force b> occupation group m W~szona~n. 197&197X

Age

16-44 45-54 55-59 6&64

Age

l&44 45-54 55-59 60-64

Age

16-44 45-54 55-59 60-64

Professionals Managers Clencdls

.V Rate SE ‘V Rate SE .\ Rate SE

99.109 0.64 0.04 19.407 0.57 0.08 205.961 0 49 0 02 22.95 I 2.86 0.16 13.328 2.07 0.18 46.507 1.4-l 0 IO

9252 4.84 0.32 5004 5 28 0 46 13.341 6.60 0 31 4888 14.16 0.76 3299 12.06 0.85 10.68 I IO.26 0.4-i

Sales Crafts Operawes

N Rate SE N Rate SE V Rate SE

40,824 0.44 0.05 I I .786 0.36 0.08 70.310 0.60 0.04 7217 3.57 0.31 844 8.71 1.43 23.28 I 2.43 0 I3 5069 5.64 0.47 808 8.91 1.48 14.629 3.72 0 23 2411 15.76 I.13 I229 8.79 I.19 5885 I I.83 0 6.:

La borers Farm managers Farm laborers

N Rate SE N Rate SE .V Rate SE

12.502 1.30 0.14 4285 0.14 0.08 18.085 0.02 0.01 I238 10.02 I .27 2505 0.32 0.16 7209 0.06 0.04 I668 6.72 0.89 427 3.75 1.32 2928 0.07 0.07 1269 11.03 I.31 417 3.36 1.27 I684 0.12 0. I ?

Age

Private household Service workers workers Housewves

N Rate SE N Rate SE N Rate SE

16-44 150,649 0.48 0.03 16,124 0.10 0.04 225,549 I.15 0.03 4554 30.861 I .95 0.1 I 419 5.25 I .58 82,717 5.44 0.1 I 55-59 Il.232 5.50 0.3 I 3348 0.54 0.18 49.955 8 44 0.18 60-64 8884 10.20 0.48 1620 3.09 0.62 57.718 10.96 0.19

Maxlnum

Scale 0lMKL0

?’

Minimum 0 O.arO

Scale

Maximum yao

I I I I

I ,,-.. .a-,. ¶I-en ewe4

Minimum b.ooo

Seal e

Maximum

Minlmum

Maximum

Minimum

LAlrl)S / i ;‘;

. . . 1.1 !.I

?cl ,030

I

SEWICE .

-.- -.-

I,-..

o.ooo

Fig. 2. Box plots of age-specific death rates of housewives and the experienced female labor force by occupation group and marital status in Wisconsin, 19761978.


Table 4. Median polish of age-specific death rates* of housewives and the female labor force by occupation category in Wisconsin, 19X-1978

Aee Housewives White-collar

Occupation category Median age-group value

Residuals (typical value I age Blue-collar Farm workers Service workers Age efTect effect)

16-44 - 1.38 -0.48 0.00 3.01 0.34 - 3.30 0.66 45-54 0.56 -0.78 0.00 0.74 -0.47 -0.95 3.01 55-59 I .66 0.48 -0.68 -0.74 0.00 0.95 4.91 60-64 -0.56 2.05 I.61 - 5.26 0.00 5.69 9.66

Occupation elTect 1.87

Median occupation value 5.83 (typical value + occupation efffect)

0.35 0.00

4.3 I 3.96

Typical value: - 3.83 -0.56 3 96

0.13 3.41

Goodness of fit: 68.39$, = (the sum of the magnitudes of the data after their median has been subtracted - the sum of the magmtudes of the residuals after the final polish)/the sum of the magnitudes of the data after their median has been subtracted; 80.45?, = (spread of rates - spread of the residuals)/spread of the rates (n.b. spread = upper quartile - lower quartile.).

‘The death rates used in this median polish appear in Table 2. Note: death rates can by constructed from this table by adding the typical value to the appropriate age effect. occupation effect and residual.

Table 5. Median polish of age-specific death rates of white-collar females by marital status in Wisconsin. 19761978

Aee Divorced Married

Residuals

Single Widowed Age

eflect

Median age group

value

1644 45-54 55-59 60-64

Occupation effect

Median

0.39 I .57 -1.35 -0.39 -0.39 -0.60 I .35 0.39 -0.93 0.60 9.13 -0.58

7.32 -0.52 -6.32 5.21

-0.50 -2.39 0.69 0.05

-4.76 I .07 -0.84 4.99

0.84 6.67 10.94 16.77

Typical value: 5.83

Goodness of fit occupation value 5.78 3.45 6.52 5.88 49.16x-74.99%

widowed women are quite large (see Table 5). Further inspection of this table reveals an extremely large residual for 55-59 year old single women. Next, an examination of more detailed occupation groupings for divorced and single white-collar workers is justified in order to identify the groups that do not fit the row-plus-column model.

White-collar workers include four major occupational groups: professional workers, managers, clerical workers and sales workers. Among divorced white-collar workers, the largest residual is for clerical workers 60-64 years of age (see Table 6). The residual for 45-54 year old clericals is also large, but it has a negative value (i.e. representing a low death rate). In addition, for single white-collar workers the residuals are largest for professionals 60-64 years old and for 55-59 year old clerical workers (see Table 7). In the three instances with large positive residuals, these residuals correspond to high death rate values.

The results of the analysis using the median polish technique support the findings described previously: housewives experience the highest average death rate values. In addition, the median polish analysis identifies occupation categories (i.e. farm workers and white-collar workers) for whom the model does not fit well. Further examination of these categories identifies a number of subgroups (i.e. divorced and single clericals and single profession&) with high death rate values which do not conform to the row-plus-column model. This suggests that for these subgroups, some factor not yet considered may be affecting their mortality. An examination of these groups by cause of death may suggest some explanation for these results.

Of the eleven selected causes of death examined in this study, a number have obvious behavioral components (i.e. accidental deaths, homicides and suicides) which could be affected by an increase in

Table 6. Median polish of age-specific death rates of divorced white-collar females in Wisconsin, 1974-1978

Ane

Residuals Median Clerical Sales Age age group

Professionals Managers workers workers effect value

1644 -1.11 45-54 6.40 55-59 I.11 60-64 -4.62

Occupation effect 0.37

Median occupation value 5.37

I .43 -7.15 1.15 -2.25 - I I .62 2.56

.- 1.43 7.15 - I.15 4.23 12.62 -3.92

- 3.03 5.90 -0.33

1.91 10.90 4.67

-2.56 2.48 3.65 8.65 0.75 5.75

-0.75 4.25 Typical value:

5.00 Goodness of fit:

9.03%-16.87X

662 MARIAN R. PASSANNANTE and CONSTANCE A. NATHAN~N

Table 7. Median polish of age-spec&c death rates of smgle white-collar females in Wisconsin, 1974-197x

Aae Professionals

Residuals Clertcal

Managers workers Sales Age

workers effect

Median age group

value

16-44 - 1.44 45-54 - 5.96 55-59 1.44 6G-64 IO.17

Occupation effect 1.57

Median occupation value 8.75

1.37 - 6.79 7.05 -6.69 0.50 0.94 3.44 -0.94 0.94 8.13

- 2.75 20.00 - I .50 1.50 8.69 - 0.94 -3.44 0.94 -0.94 6.24

Typtcal value: - 1.50 6.63 -7.19 7.19

Goodness of fit: 5.69 13.81 0.00 32.90”,-55.29””

Table 8. Age-specific death rates (per 1000) of housewives and laborers for accidental deaths in Wisconsin. 1974-1978

Housewives Laborers

Age N Rate SE N kate SE

1644 225.550 0.19 0.04 12,502 0.45 0.08 45-54 82.718 0.20 0.02 1238 1.29 0.46 55-59 49,995 0.25 0.03 I668 0.24 0.17 6&64 57.718 0.23 0.03 I269 0.32 0.22

risk-taking behaviors. Increased alcohol intake could affect deaths due to cirrhosis of the liver. Increased cigarette smoking could affect deaths due to ischemic heart diseases (which constitute 88% of all heart disease deaths in the U.S.), bronchitis, emphysema and asthma, and malignant neoplasms (e.g. lung cancer). In addition, hazardous chemical or biological exposure in the work place as well as cigarettes could be linked with deaths due to bronchitis, emphysema and asthma, influenza and pneumonia and malignant neoplasms. The remaining three causes of death (i.e. cerebrovascular diseases, diabetes mellitus and arteriosclerosis), though they have behavioral components, are not as easily linked with stress, health hazards and behaviors associated with occupational affiliation.

Examination of occupation category-specific death rates by age and cause of death supports the results of the previous analysis. This is, housewives generally experienced higher death rates than women in the experience labor force. However, there are a number of instances in which housewives do not experience the maximum death rate value. For the first three age groups, in each instance when housewives rates are exceeded by the death rates of labor force participants, it is the death rate of blue-collar workers that is higher. Among 16-44 year olds, blue-collar workers experience the highest death rate values for accidental and homicide deaths, and for 45-54 year olds, blue-collar workers experience the highest death rate value for deaths due to homicide. In addition, among 60-64 year olds, white-collar workers experience maximum death rate values for deaths due to accidents, suicides, heart diseases, influenza and ma-

lignant neoplasms, while blue-collar workers experience the maximum death rate value for deaths due to cirrhosis of the liver. In each instance when housewives’ death rates are exceeded by those of members of the labor force among 60-64 year olds, deaths are due to one of the eight causes of death presumably associated with occupational affiliation. In general, the instances of labor force participant excess mortality, among the younger age groups are due to deaths to blue-collar workers, while white-collar workers experience excess mortality in the oldest age group.

Perhaps the most interesting findings in this analysis are those where female labor force participants experience significantly higher death rates than housewives. The death rates of laborers 16-44 and 45-54 for accidental deaths are significantly larger than those of housewives (see Table 8). Similarly, Table 9 illustrates that laborers 45-54 and sales workers 60-64 experience significantly higher death rates than their counterparts in the home for deaths due to heart diseases. Finally, the comparison of housewives and female labor force participants for deaths due to malignant neoplasms presents the following results: white-collar workers 60-64 years old, specifically professionals, managers and sales workers, experience significantly higher death rates than housewives 60-64 years of age (see Table 10). Despite these interesting findings, it should be re- membered that, in general, housewives experience higher death rates than labor force participants for each of the eleven selected causes of death.

DISCUSSION

The results of the preceding data analysis suggest that death rates for women in the labor force, as a group, are not higher than the death rates of housewives when controlling for age and marital status (excluding the single population). In fact, for most age and marital status categories, housewives’ death rates are significantly larger than those of women in the labor force.

Table 9. Age-specllic death rates (per 1000) of housewives, laborers and sales workers for deaths due to heart diseases in Wisconsin. 1974-1978

Housewives Laborers Sales workers

Are N Rate SE N Rate SE N Rate SE

16-44 225.550 0.12 0.03 12.502 0.02 0.02 40,824 0.03 0.01 45-54 82.718 0.97 0.05 1238 2.26 0.60 7211 0.80 0.15 55-59 49,995 2.19 0.09 I668 I .68 0.45 5069 1.58 0.25 60-64 57.718 3.28 0.1 I I269 2.84 0.67 2411 4.73 0.62


However, the specific instances where labor force participants’ mortality rates exceed those of housewives (e.g. among 60-64 year olds)-may indicate the direction of future mortality trends. In the 6@-64 year old population, white-collar workers experienced significantly higher death rates than housewives, while the members of the other three occupation categories did not (see Table 2). In addition, sales workers, managers and professionals (three white- collar occupation groups) experienced the highest death rates among female labor force participants. While operatives and laborers also experienced death rates which were higher than those of housewives, only the members of the white-collar occupation groups experienced death rates which were significantly higher than that of ‘housewives (see Table 3). These findings support the results of an earlier study which suggest that women in higher income occupations may experience higher mortality rates than those in lower income occupations [32].

Another interesting study result appeared in the comparison of housewives and labor force participants by age and occupation group. Labor force participants experiencing significantly higher death rates than those of housewives in the youngest age groups were usually blue-collar workers, while white- collar workers experienced significantly higher death rates in the 60-64 year age group. This age-occupation mortality differential may be accounted for by the amount and type of exposure to occupational health hazards (i.e. immediate or cum- mulative) associated with particular occupations. The results of the cause of death analysis further illustrates this finding.

Death rates of laborers exceeded those of housewives for accidents in the 16-44 and 45-54 year age groups (see Table 8). It could be argued that these results suggest that the risk-taking behavior or hazardous job conditions of young female laborers may negatively affect their mortality. In addition, for deaths due to heart disease, laborers 45-54 and sales workers 60-64 experienced higher death rates that housewives. Furthermore, death rates for malignant neoplasms among professionals, managers and sales workers exceeded that of housewives among 60-64 year olds (see Table 10). These results may argue that stress or behavior (e.g. cigarette smoking) affect these high mortality rates. One might expect these factors to be related to deaths among older workers because the negative effects of both stress and cigarette smoking may be cumulative.

There is another possible explanation for the results of the comparison of 60-64 year olds. The ‘suggestive’ findings that appear in the oldest age group (60-64 year olds) may be a function of the data sources and definitions used to distinguish the population. For example, death certificates classify individuals according to their usual occupation throughout their working lives, while the population survey classifies individuals according to current occupation. Therefore, in the oldest age group, where the largest number of retired workers appear, retired women who describe themselves as housewives would be placed in the denominators, while deaths to these women would appear in the numerators of the death rates of the experienced labor force. Thus, the death

664 MARIAN R. PASSANNANTE and CONSTANCE A. NATHANSOY

rates for women in the experienced labor force would be inflated. This set of circumstances could result in findings similar to those which have previously been described as ‘suggestive’ of future mortality trends for the female labor force.

Alternative explanations for the study findings should be considered. The negative health outcomes traditionally associated with the male occupational role may not affect females as a group until sufficient numbers enter and remain in the labor force for extended periods of time. Furthermore, any change in female mortality might be dependent on the entranve of substantial numbers of females into traditionally male-dominated occupations. Obviously, further exploration of these factors would be dependent on major changes in the duration of female labor force participation and the sex structure of the present labor force.

Another reason for the study results might be that employment has a positive effect on individual health [21,22]. It is possible that, for females, the positive effects of labor force participation may simply out- weigh the negative effects [23,24]. For example, when women enter the labor force, they may decrease their exposure time to household health hazards, such as cleaning agents or accidents in the home. It is also possible that increased role accumulation (i.e. assuming the work role as well as the role of spouse and parent) may bring the direct and indirect benefits of economic gain, and increased membership and affiliation. These circumstances might decrease deaths for housewives due to suicide or cirrhosis of the liver, related to stress caused by social isolaton.

Of cause, the high mortality of housewives could be caused by some selectivity. This is, women who enter the labor force might be more healthy than the population of women who remain in the home. This could be explained by the fact that women who work outside of the home must, by necessity, be healthy enough to maintain their jobs. In addition, less healthy women who are unable to hold jobs outside of the home may simply describe themselves as housewives. Therefore, the study results might be described as generally supportive of the ‘healthy worker’ effect. The results of Waldron’s [26] longitudinal studies support this explanation.

However, there may also be some selection by marital status which would work against and perhaps cancel out the healthy worker effect. For example, if less healthy women remain single and therefore must rely upon themselves for financial support, then less healthy single females would be forced to enter and remain in the labor force. The results of this analysis, where single labor force participants experienced unusually high death rates support this view.

In order to distinguish between these alternative explanations, further studies should be pursued. Some of the issues raised in this examination will be easier to pursue in the years ahead, when the mortality experience of the large number of women who have entered the labor force in the past 10 years can be followed.

Yet, in order to be more confident about the results of any subsequent study, the system of coding of occupation on the death certificate needs to be im- proved. As has been noted previously [36], at present

few states code occupation information in their certificate files. This coding system should be adopted in other states so that comparative studies can be conducted. Furthermore, given the limited amount of information on death certificates as well as the problems associated with the use of occupation responses. alternative sources of information should be considered.

One possible source of data, which would allow further study of the relationship between female labor force participation and mortality, would be detailed occupation and health histories. These detailed histories could provide information on the duration of employment, specific occupations held. job hazards encountered at the work site and specific health problems encountered throughout one’s working life. Additional information. such as the occupation of spouse or family income, would allow researchers to control for the socioeconomic status of comparison groups in future studies.

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