Press operator amputations: Is risk associated with age and gender?

ofSafetyResearch, Vol. 19, PP. 125-133, 1988 0 1988 National Safety Council and Pergamon Press plc

loumol

0022.4375188 $3.00 + .OO Printed in the USA

Press Operator Amputations: Is Risk Associated With Age and Gender? Roger

Jensen

and Edward

Sinkule

A retrospective analysis of injury data was performed to determine if the risk of amputation for press operators is affected by their age or gender. Workers’ compensation data from 28 states were examined for a 3-year period. A total of 628 claims were found for press-related amputations incurred by press operators. Results indicated that risk of amputation was not dependent on gender. Risk was, however, associated with age. The youngest press operators were at greatest risk of amputation. This result may be due, in part, to insufficient training for many young workers who are assigned to operate power presses.

Thousands of working Americans sustain amputations each year. A study by McCaffrey (1981) estimated that 21,000 amputations occurred on the job in 1977. The type of machine most frequently involved in these amputations was the power press. Of the 21,000 amputations, 96.8% occurred to the upper extremities (finger, hand, wrist, or arm). A subsequent study by the Bureau of Labor Statistics (BLS) surveyed workers who incurred a work-related amputation to the upper extremities. Results indicated that power presses were the source of 10% of the amputations (BLS, 1982b). The numerous amputations on power presses indicate a need to strengthen prevenRoger C. Jensen is a senior engineer officer in the U.S. Public Health Service Commi~ion~ Corps, and Edward 1. Sink&e was formerly an epidemiolo&t, Na-

tional Institute for Occupational Safety and-Health, Divisionof Safety Research, 944 Chestnut Ridge Road, Morgantown,

WV 26505.

tion programs. Currently, attempts to prevent amputations emphasize the attachment of safeguarding equipment to comply with applicable regulations. Similarly, research directed at reducing amputations on power presses has focused on the equipment. For example, all of the press safety research conducted or sponsored by the National Institute for Occupations Safety and Health (NIOSH) has concerned equipment used with presses, including radio-frequency sensing devices (Etherton, Concha, & Jensen, 1982), light curtains used for presence sensing device initiation (Salvendy, Shodja, Sharit, & Etherton, 1983), foot switch actuators (Trump & Etherton, 1985, 1986), and the placement of dual palm-button actuators (Pizatella, Etherton, Jensen, & Oppold, 1983; Pizatella & Moll, 1987; also see Collins, Pizatella, Etherton, & Trump, 1986). The equipment approach may be the

most pragmatic from a regulatory perspective, but in the broader sense of injury prevention, consideration of the workers as well as the equipment may lead to more effective programs for preventing amputations on power presses. Some questions about the human component that research might help answer include: When a manufacturer has a job opening for a press operator, what qualifications and/or personal attributes should be considered in selecting among applicants? What kind of training, and how much training should a new press operator get before starting to operate the press without close supervision? When a worker with training and experience on a particular press is assigned to operate a different kind of press, what sort of training is needed to assure competence to operate the press safely? Does the use of piece rate wage systems create an environment that essentially encourages press operators to circumvent safeguarding apparatus? Do press operators who choose not to follow recommended operating procedures do so with full knowledge of the possible consequences or are they lacking basic information needed to evaluate the actual risk? The questions posed in the preceding paragraph cannot be answered by one or two studies. What is really needed is a research program that would include multiple studies, each focusing on particular issues. Due to the limited resources available for occupational safety research, however, it is unrealistic to expect funding for every well-designed research project. For this reason, it appears more realistic to focus research on a small number of particularly important questions. One approach to establishing research priorities is to examine injury data and use injury patterns to help distinguish questions that are especially important from those that have lesser significance for prevention programs. Of particular interest is the identification of groups of press operators who have been experiencing more amputations than other groups of press operators. If operators with certain characteristics are found to have especially large amputation rates, then studies to explain the reasons 126

should have a relatively high priority for funding. This investigation was undertaken to determine if press operators with certain characteristics might have been experiencing more amputations than other groups of press operators. The operator characteristics selected for examination were age and gender. These were chosen for two reasons. First, both age and gender might be considered by employers in some countries as a factor in selecting among candidates for a press operator job. Such a practice in the United States would be in violation of Equal Employment Opportunity laws unless there is a clear connection between the selection criteria and the job requirements. Nevertheless, whether age or gender as preemployment selection criteria might be justified from a safety perspective is a question that could best be answered after considering relevant injury data. Second, both age and gender have been found to affect the speed at which press operators can reach from palm-button actuators to the point of operation on a press (Pizatella & Moll, 1987). A faster movement capability implies greater risk of amputation on presses that rely on dual palm-button actuation or light curtain detection as the safeguarding mechanism . Previous epidemiologic studies of occupational amputations involving power presses have been based solely on case data (BLS, 198213; McCaffrey, 1981; Olson & Gerberich, 1986) and do not provide the required data for assessing the possible effect of age or gender on risk of an amputation. Risk comparisons are not possible without including information about exposure, such as hours of exposure or average number of employees exposed. Consequently, no published epidemiologic studies have been found that indicate if the age or gender of press operators affects risk of an amputation. This investigation was undertaken to determine if existing records about amputations and employment indicate that amputation risk among press operators is (a) different for male and female press operators and (b) affected by the age of the press operator. Journal of Safety Research

METHOD

Sample Of all the time periods that might be sampled, calendar years 1979-1981 were selected because of the accurate employment data available from the 1980 Census of the Population. An additional consideration was that data on amputations that occurred during these 3 years were available from BLS’s Supplementary Data System (SDS). The SDS is a federal/state cooperative injury information system based on workers’ compensation claims in the participating states (BLS, 1982a). The states included in this investigation participated in the SDS during all 3 years, coded age and gender of the injured, and also coded occupation according to the Bureau of Census system (Bureau of the Census, 1971). There were 28 states that met these criteria: Alaska, Arizona, Arkansas, California, Colorado, Delaware, Hawaii, Idaho, Indiana, Iowa, Kentucky, Maine, Maryland, Michigan, Minnesota, Missouri, Montana, Nebraska, New Mexico, New York, North Carolina, Oregon, Tennessee, Utah, Vermont, Washington, Wisconsin, and Wyoming. Measure of Risk To assess effects of age and gender, risk was quantified as a proportionate amputation ratio (PAR). This kind of measure has been recommended by the Bureau of Labor Statistics for comparing risks of occupations using similar data (Root & Sebastian, 1981). The PAR measure is simply the percent of amputations incurred by members of a subset of the total study population (% amputations,), divided by the percent of the study population belonging to that subset (% operators,), thus the PAR for group i is PAR, =

% amputations, % press operators, ’

It is equivalent to the proportionate mortality ratio used in fatality studies. A subset at greater risk than the average for the study population will have a PAR value greater then one. A subset with a risk the same as the entire study population will have a PAR Fall 1988Nolume

19Ahmber

3

value of one, and a PAR value less than one indicates that the subset was at lower risk than the overall study population. For example, if press operators in a certain age group accounted for 16% of the amputations, but constituted 8% of all press operators, then the group’s PAR would be (16%)/ (8%) =2.0. Thus, this hypothetical subset of operators was apparently at greater risk of amputation than the average press operator in the study population. Data Percent of amputations. The numerator of the PAR (% amputations) was computed from the number of SDS cases coded to indicate that an employed press operator sustained an amputation on a press during 1979, 1980, or 1981. These cases were identified using a search of SDS data sets for the 28 states included in the study. Because of the way case data were obtained and recorded in the various states, it was also necessary to search records for calendar years subsequent to the year the amputation occurred. For example, amputations that occurred during 1980 may have been processed and coded by compensation agencies during 1980 or during a subsequent calendar year. The approach used for this investigation was to include all available subsequent year records, i.e., through 1984. Most of the cases obtained in this investigation were recorded in the year the amputation occurred or the next year. For example, of the cases that occurred in 1979, 71.7% were recorded in the 1979 computer tapes. The 1980 computer tapes contained records of an additional 16.5%. The remaining computer tapes (1981, 1982, 1983, 1984) contained the following percentages respectively: 6.6%, 3.3%, 1.6%, and 0.3%. Even with this approach, the amputation cases identified from the workers’ compensation records would not constitute 100% of the press operator amputations that occurred in the 28 states during 1979-1981. Because of this, the cases identified were considered a sample of the total population of press operator amputations that occurred during the 3-year period in the 28 states. 127

Thus, for this study, the percentage distribution of cases among age and gender groups determined from this sample was treated as representative of the corresponding percentage distributions within the total population of work-related amputations in the 28 states during the period 1979-1981, The set of cases retrieved from the SDS records of the 28 states were those that satisfied the following specifications’: 1. Reference year- 1979 through 1984; 2. Year of occurrence-1979, 1980, or 1981; 3. Nature of injury - amputation; 4. Occupation-press operator; 5. Source-press (excluding printing presses) ; 6. Industry - all except domestic work and self employed. of press operators. The denominator of the PAR (% press operators) was based on census data. The 1980 census was conducted during one week in May 1980. It has been assumed that this one-week sample from the 156 weeks in the 1979-1981 period provided a representative picture of the percentage of press operators who were male and female, as well as the percentage of press operators in each age category. To obtain the values required to compute the denominator of the PAR, census records were searched to determine the number of press operators employed during the week of the census who would have been eligible for workers’ compensation in one of the 28 states if they incurred an amputation in the course of employment. These values were obtained from computer tapes called Public-Use Microdata Samples, which consist of a 5% sample of each state’s 1980 census returns (Bureau of the Census, 1983). The strategy for searching these records was to start by selecting all nonmilitary press operators employed in the 28 SDS states and then exclude those with certain employment characteristics. Excluded were: (a) employees clearly not covered by state workers’ compensation, i.e., federal Percent

IA more complete description of these coding categories is provided elsewhere (Jensen, 1987b).

128

employees, unpaid family workers, longshore and harbor workers, and railroad workers; and (b) individuals who may or may not have been covered by a state workers’ compensation plan, i.e., self-employed individuals, employees of their own corporation, and domestic workers. To ensure proper matching of numerator and denominator data, amputations involving these employment categories were not included in the numerator data file either. The values resulting from this selection process were used to determine the percentage of press operators in subsets defined by age and/or gender. Data Analysis There were very few press operators age 16 and 17. Consequently, these were combined with the 18 year olds to form one age category. Similarly, press operators age 64 and older were combined into one group. The first statistical analysis was to determine if gender had a significant effect on PAR. For this analysis, the possibly confounding effect of age was controlled by using age as a blocking variable. A nonparametric sign test, also known as Fisher’s sign test, was used to test the hypothesis of no difference in the PAR values of men and women against the two-sided alternative that the males had a different PAR value than the females (Hollander & Wolfe, 1973). The second analysis was to determine if age was associated with PAR. The PAR values for each age group were plotted to facilitate visual identification of any pattern between PAR and age. Two nonparametric statistical tests were performed, the oneway chi-square test and the rank order correlation procedure for association (Conover, 1980).

RESULTS

PAR values were used to test for possible gender-based differences in amputation experience. The PAR values of male and female press operators are listed in Table 1 by age group. The right column shows the difference between the PAR values of the men and women (male PAR minus female PAR). journal

of Safety Research

TABLE 1 PAR VALUES FOR MALE AND FEMALE PRESS OPERATORS IN 28 STATES BY AGE

16-18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 & older

Male PAR

F-1 e PAR

3.42 2.48 2.56 1.46 1.96

10.42 3.27 1.67 2.79 0.70 1.44 1.18 0.66 0.61 2.23 0.71 0.72 0.88 0.44 1.23 0.94 0.49 1.48 1.95 0.72 0.47 0.82 0.50 0.36 1.28 0.65 0.92 0.71 1.09 0.53 0.27 0.61 1.22 0.00 0.00 0.65 1.94 0.77 0.66 0.98 0.68 0.68 0.82 1.84 0.00 3.06 0.00

1.24 0.75 0.84 0.78 1.13 1.67 0.91 0.56 0.53 0.77 0.54 0.86 0.56 0.68 0.32 0.41 1.14 0.59 0.91 0.77 0.60 0.26 0.16 0.17 1.00 0.53 0.25 1.64 1.13 0.28 0.73 1.09 0.70 0.77 0.68 1.10 1.11 0.99 0.00 0.61 0.72 1.69

Note. Values are rounded to the nearest

Difference

-6.99 -0.78 0.89 -1.33 1.26 -0.20 -0.43 0.18 0.17 -1.10 0.96 0.19 -0.32 0.09 -0.46 -0.41 0.37 -0.92 -1.27 -0.40 -0.06 0.32 0.09 0.55 -0.51 -0.05 -0.66 -0.55 -0.92 0.47 0.27 -0.37 0.42 1.13 0.28 0.08 -0.85 -0.07 0.11 -0.30 0.42 0.43 0.18 -1.84 0.61 -2.34 1.69

tenth.

The greatest difference in PAR value (-6.99) was found among press operators age 18 or younger. Other age groups had Fall 1988Nolume

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3

much smaller differences than the 18 year olds. It is not at all clear why the 18-yearold female press operators had a PAR so much larger than their l&year-old male counterparts. If being young was the explanation, a similar pattern would be expected for the 19 and 20 years olds, but this was not the case. The difference in PAR values for the 19 year olds was -0.78, and for the 20 year olds it was 0.89. These values are similar to those found in the other age groups. Thus, these data should not be interpreted as indicating that young female press operators tend to be more at risk of amputation than young male press operators. Some other possible explanations for the large gender difference in PAR among the 18-year-old press operators might be differences in knowledge, skill, after-reach speed, or willingness to accept risk. It is also possible that this 3-year sample from SDS files just happened to include a larger number of amputation cases among the l&year-old women than would have been found if some other 3year period had been selected. From the data available in the SDS and census records it is not possible to adequately explore these possibilities. Across all age groups the mean PAR difference value was -0.254. The difference values did not follow a normal distribution according to the Kolmogorov-SmirnovLilliefors Test (Conover, 1980); consequently, parametric statistical procedures were not used to examine the significance of this difference. Instead, a nonparametric test that does not assume a normal distribution was used. The Fisher sign test is a nonparametric procedure based on the expectation that, under the null hypothesis of no gender difference in PAR, about half the PAR difference values should be positive, and half negative (Hollander & Wolfe, 1973). The data in Table 1 were consistent with the null hypothesis of no gender difference in PAR. Specifically, of the 47 difference values, 23 were positive and 24 were negative. Thus, it was concluded that the risk of amputation was not significantly different between men and women press operators. Once it was determined that gender was not a significant factor, the male and female data were combined to examine the .possible effect of age on PAR. Figure 1 shows these 129

FIGURE PAR AMONG

1

ALL PRESS OPERATORS

ACCORDING

TO AGE

5.5 5.0 0 $ cr

4.5.

d

3.0

0

5 W

0

2.5

0

0

&

1.5

l

i? i

I .o

0

00

0 0

0

0

0

0

0

l 00

0

0

0

.-

0.5 0.0 L

1

I

I

I‘

IS

I

81

1

I1

I1

I

I

I

I

a

I

I

I1

18 2022242628303234363840424446485052545658606264 AGE

PAR values plotted against age. The youngest age group (18 or younger) had the largest PAR value (5.0), indicating that the likelihood of a young press operator experiencing an amputation was five times greater than that of the average press operator in the study population. The second and third youngest age groups (19 and 20) had the second and third largest values (2.6 and 2.3) of PAR, respectively, those values being about half as large as the 18 year old group. The fourth and fifth youngest age groups (21 and 22) had the fourth and fifth largest values (1.7 and 1.6) of PAR respectively. From age 23 up, the PAR values fluctuated between 0.19 and 1.50 with no apparent pattern. The chi-square test compared the observed frequency of amputations in each age category (oJ with the expected frequency (e,) under the null hypothesis that every age group category had the same incidence ratio (IR). This IR was determined from the ratio 130

of all claims by press operators for amputations on presses that occurred during 19791981 to the average number of employed press operators in the 28 states during this period according to the census. This S-year incidence ratio was calculated as follows: IR=

total amputations in 3 years employed press operators

628 amputations = 76,960 operators = 0.00816

amputations

per operator

Values for the expected amputation frequency in each age category were determined by multiplying the number of press operators in the age group (n,) by the overall IR, thus ei=IR(ni). The chi-square statistic was computed from these values and compared with tabled chi-square values to de-

Journal

of Safety

Research

termine significance level (Snedecor & Cochran, 1980). Table 2 lists the observed cases, expected cases, and the difference (0,-e,) for each age. Results of the chi-square analysis indicated that the distribution of observed cases among the age groups was significantly different from that expected if the incidence ratio was the same for all age groups (x2=254; df=45; CY<.OOl). The chi-square procedure, however, does not indicate anything about the nature of the differences. To explore this further, a correlation procedure was used. Parametric correlation procedures were considered initially, but due to the skewed distribution of the PAR statistic (mean = 1, theoretical range from 0 to infinity), it was questionable whether the assumptions for parametric correlation would be met. Consequently, the nonparametric rank-order correlation procedure of Spearman was used (Conover, 1980). The Spearman Correlation Coefficient (- .344) indicated a significant negative correlation between rank of the PAR values and rank of the ages (N=47; 01< .05).

TABLE OBSERVED AMONG

AND

Dbsened

14

27

24

28

24

29

18

30

11 8 16 11 12 14 13 7 6 14 8 9 10 6 5 4 6 9 5 5 15 10 2 7 14 8 7 8 10 10 8 3 2 4 8

628

628.0

38

20

45

21

34

22

34

23

29

24

19

25

18

31 32 33 34 35 36 37 38 39 40 41 43 44

This assessment of workers’ compensation data was undertaken to determine if age and gender are factors associated with risk of amputation among press operators in order to determine if more in-depth research on these factors would be justified. Because gender was not significantly associated with the risk measure (PAR), it appears that little would be gained by allocating resources for a study to search for some unlikely connection between gender and the risk of amputation among press operators. In contrast, since age was significantly associated with PAR, studies appear justified to explain the reasons for this association. In particular, additional studies are needed to determine why young press operators had the largest PAR values. Several possible explanations may be put on the table for further discussion and research. One possibility is a difference in after-reach speed. Pizatella and Moll (1987) found that the age of their sample of 60 press operators signifiFall 1988Nolume

1 S/iVumber 3

Expected

26

36

19

45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 I older

Total

Note.

Values

are

rounded

BY AGE

Mutations

7.2 14.5 19.4 20.1 21.1 22.5 22.4 22.7 18.9 17.8 16.8 20.9 16.5 16.0 18.0 17.3 15.7 17.1 12.4 14.9 13.9 13.7 14.5 11.6 10.4 9.8 10.9 10.6 10.4 10.8 11.3 13.1 10.0 11.4 10.4 10.0 10.4 11.1 9.8 10.0 10.8 10.1 8.5 7.2 4.4 3.4 7.5

16-18

42

DISCUSSION

AMPUTATIONS

PRESS OPERATORS

kputatims Av

2

EXPECTED

to the nearest

Difference

28.8 23.5 25.6 13.9 12.9 6.5 -3.4 -4.7 -4.9 6.2 7.2 -2.9 -5.5 -8.0 -2.0 -6.3 -3.7 -3.1 0.6 -7.9 -7.9 0.3 -6.5 -2.6 -0.4 -3.8 -5.9 -6.6 -4.4 -1.8 -6.3 -8.1 5.0 -1.4 -8.4 -3.0 3.6 -3.1 -2.8 -2.0 -0.8 -0.1 -0.5 -4.2 -2.4 0.6 0.5

tenth.

131

cantly affected after-reach speeds. Another possibility is that many of the young press operators might have lacked an adequate understanding of the press they were assigned to operate. Other possible explanations include differences in skill for performing press operations and willingness to take risks by circumventing standard operating procedures or equipment intended for safe operation. It could, of course, be a combination of two or more of these factors. The relative contribution of each factor, if any, cannot be determined from available data. In using PAR to compare groups of workers, a bias would be present if the comparison were between one group of workers who were primarily full-time employees to another group of workers that included many part-time workers. For such a comparison, it would be appropriate to use a measure of risk with a denominator that has total person-hours of employment for each group. Because PAR is ‘based on a count of employees in each group, rather than a summation of person-time units of exposure, the PAR measure is only appropriate for comparisons between groups with equivalent average time of exposure per employee during the study period. For example, it would be alright to compare two groups that each had an average of 39 hours of work per week per employee, but there would be a bias if one &TOUP averaged 39 hours and the other group averaged 25 hours per week. Consequently, for the comparisons reported, it has been assumed that the groups of press operators defined by age and/or gender were equivalent in terms of average exposure time per employee. The values for PAR used in this investigation were based on the best available data; however, this does not mean the PAR values are perfectly accurate or free of bias. Inaccurate values for case and/or employment data may have led to PAR values that either over- or underestimated the true PAR values. There is no reason to suspect, however, that bias would be inconsistent between groups of different age or gender. Thus, even if there is some bias in the PAR values, conclusions about differences in PAR due to age or gender should still be valid. Some comments on the use of workers’ 132

compensation data may be helpful to other investigators considering the use of such data. Perhaps the richest source of information about methods and measures is found in articles that report analyses of workers’ compensation data. Some reports describe analyses of claim data without using employment or exposure data (McCaffrey, 1981; Olson & Gerberich, 1986; Seligman, Halperin, Mullan, & Frazier, 1986; StoutWiegand, 1987). Other studies have utilized employment data to calculate risk quantities (e.g., injury rates, injury ratios) for comparing the injury experiences of different groups of workers according to such factors as age, gender, occupation, and industry of employment (Abenhaim & Suissa, 1987; Broberg, 1984; Jensen, 1983; Jensen, 1987a; Jensen, Klein, & Sanderson, 1983; Klein, Jensen, & Sanderson, 1984; Sinks, Mathias, Halperin, Timbrook, & Newman, 1987). One study used logistic regression to determine what factors contribute to the probability that over a one-year period a worker will start receiving workers’ compensation payments for an injury or illness (Leigh, 1986). Workers’ compensation claim data have been criticized because many work-related illnesses are not compensable and, therefore, not included in compensation record systems (Ashford & Andrews, 1983). This is a legitimate concern for many occupational diseases, but not for amputations. Unlike occupational diseases, amputations clearly fit within the traditional workers’ compensation definition of an “accident.” Also in contrast to occupational diseases, the relatedness to work is usually much easier to establish for amputations than it is for most diseases. Additionally, amputations are “scheduled” injuries, meaning that they automatically qualify for compensation without any showing of medical expenses or lost workdays. Although the results of this investigation do not indicate the reasons why the youngest press operators experienced more than their share of amputations, there is certainly a possibility that many young, newly hired workers are assigned to operate power presses after receiving very minimal training. It is, therefore, recommended that emJournal of Safety Research

ployers with power press operations make an effort to improve the training provided for workers assigned to operate presses. Along with employee training should be an assessment of the equipment. Checklists for mechanical power presses actuated with palm buttons or foot controls have been published by NIOSH (1987).

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