Epidemiologia Trauma Mano

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Epidemiology of occupational acute traumatic

hand injuries: a literature review

G.S. Sorock a,b,c,*, D.A. Lombardi b,c, T.K. Courtney a,b,J.P. Cotnam a,1, M.A. Mittleman b,d

aLiberty Mutual Research Center for Safety and Health, 71 Frankland Road,

Hopkinton, MA 01748, USAbDepartment of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue,

Building I, Boston, MA 02115, USAcDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences,

University of Massachusetts at Amherst, Amherst, MA 01002, USAdDepartment of Epidemiology, Harvard School of Public Health, 665 Huntington Avenue,

Building III, Boston, MA 02115, USA

Abstract

The purpose of this review was to summarize the literature on occupational, acute, trau-

matic hand injury and suggest directions for future research. In 1996, the leading occupational

injury treated in United States' hospital emergency departments was an acute hand injury (e.g.

laceration, crush or fracture). These injuries aected 30% of an estimated 3.3 million injured

workers (990,000). Cuts and lacerations of the ®ngers ranked third after back and leg strains

in the number of lost workday cases in the USA in 1994. The incidence rate of hand injuries

studied in seven manufacturing environments around the world ranged from 4 to 11 per 100

workers per year. Workers aged 24 years or less had the highest risk of hand injury. Men hadhigher rates of severe hand injury than women.

Despite the high frequency and signi®cant amount of lost work time associated with these

injuries, they are poorly understood from an etiological perspective. There is only one case-

control study of occupational hand injury in the literature. That study suggested an important

role for both ®xed (age) and transient risk factors (doing an unusual task) at the time of the

injury. More analytic epidemiological research is needed to identify potentially modi®able risk

or protective factors (e.g. glove use) for acute hand injuries. In this regard, the case-crossover

design, a relatively new epidemiological approach using cases as their own controls, could

Safety Science 38 (2001) 241±256

www.elsevier.com/locate/ssci

0925-7535/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.

P I I : S 0 9 2 5 - 7 5 3 5 ( 0 1 ) 0 0 0 0 4 - 2

* Corresponding author. Tel.: +1-508-435-9061, ext. 223.1 This research was completed during JP Cotnam's tenure as a Researcher at the Liberty Mutual

Research Center. He is now with Atlantic Charter, Boston.

E-mail address: [email protected] (G.S. Sorock).



prove an ecient method for determining transient, modi®able risk factors for acute, occu-

pational hand injury. # 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Occupational; Injury; Hand; Upper extremity; Trauma; Epidemiology

1. Introduction

Acute traumatic occupational hand injury resulting from sudden or instantaneous

events is common yet poorly understood from an etiological perspective. The

National Electronic Injury Surveillance System reported that ®ngers and hands were

the most frequent anatomic sites injured at work (e.g. a laceration or fracture) and

treated in hospital emergency departments in the USA. In 1996, these injuries

occurred to approximately 1 million workers. (Morbidity, Mortality, Weekly

Report, 1998). A recent published analysis of the number of reported US Bureau of

Labor Statistics (BLS) lost-workday cases indicated cuts and lacerations to the ®n-

gers ranked third after back and leg strain cases nationwide in 1994. (Courtney and

Webster, 1999). Despite the obvious frequency of these injuries, there has been only

one published case-control study of acute traumatic injury to the hand in the work

environment (Hertz and Emmett, 1986), leaving large gaps in our understanding

of potential risk factors for hand injuries. This review examines the epidemiology of

acute, occupational, sudden-onset injury to the ®ngers and hand. Directions for

future research in this area are also suggested. For purposes of the review, ®ngers,thumb and hand are considered as one anatomic unit unless otherwise speci®ed.

2. Methods

Large injury and illness registries such as the BLS annual Survey of Occupational

Injury and Illness (SOII) and the National Electronic Injury Surveillance System

(NEISS) were used to estimate the frequency and incidence of hand injuries. Pub-

lished research reports dating back to 1970 were identi®ed through computerized

databases such as PubMed, Grateful Med, NIOSHTIC using the keywords: `òccu-pational'', `ìnjury'', ``hand'', and `ùpper extremity''. The upper extremity was

de®ned as the upper and lower arm, elbow, wrist, hand and ®ngers, excluding the

shoulder and neck.

Epidemiologic studies in the English language of occupational upper extremity

acute trauma were selected for review. Studies were excluded if they described non-

occupational trauma. Case series studies of clinical treatment of small numbers of

upper extremity injured cases were also excluded (Askins et al., 1986). Gradual-

onset injuries such as cumulative trauma disorders were excluded as they have fun-

damentally dierent injury mechanisms from acute trauma which was the focus of

this study (Hagberg et al., 1997). Strains and sprains were excluded due to the di-culty of classifying them as sudden or gradual onset without speci®c clinical infor-

mation. The injury types in this review were restricted to laceration, crush, puncture,

242 G.S. Sorock et al. / Safety Science 38 (2001) 241±256



avulsion, amputation, fracture or contusion. Needlestick injuries (Hanrahan and

Reutter, 1997), animal or human bites, burns or injuries due to falls were excluded

due to their potentially dierent etiological pathways. Lastly, based on ®ndings from

published studies of large national data systems and the initial results of the litera-ture search, the review was subsequently focused on occupational acute trauma to

the hand (including the thumb and ®ngers).

NEISS data are presented ®rst to examine a US national sample of hospital emer-

gency department-treated occupational injuries along with another hospital-based

system, the National Hospital Ambulatory Medical Care Survey (NHAMCS). The

BLS SOII data are discussed next to establish the frequency and severity of

employer-reported upper extremity, and particularly hand, acute trauma. Clinical-

setting studies of patients with hand injuries are then considered.

The next section presents industry-speci®c descriptive studies with a particular

emphasis on rate estimation. In order to develop rate estimates, studies in this sec-

tion had to include the time period of the study, the total count of all injuries and all

hand injuries, and an estimate of the population at risk or the number of worker-

years. To estimate the hand injury rate per 100 worker-years, the total number of

injuries was divided by the estimated average number of employees at risk on an

annual basis multiplied by the total time period of the study, and then further

multiplied by 100. Although the majority of the studies included dynamic work

cohorts, this estimate assumed a ®xed count per year in the denominator. A limiting

assumption is that the number of hours worked per worker is the same. This may

lead to an under or over-estimate of injury rates in some industries (Russer, 1998).An example of this calculation for one study (Nag and Patel, 1998) is as follows:

The estimated annual workforce was 6980 and the study accrued injuries for a time

period of 3 years, thus the denominator in the calculation would be 20,940 person-

years. During this period, a total of 1426 hand/®nger injuries occurred which leads

to an estimated rate of 6.8 hand injuries per 100 worker-years. The industry-speci®c

studies section is followed by an examination of multi-industry descriptive studies of

hand injury. Finally, recommendations are made for approaching future research in

acute hand injury.

3. Descriptive epidemiology

Based on data from a random sample of US hospital emergency departments

from the NEISS, ®ngers and hands were the most common anatomic sites injured

at work and treated in emergency departments in 1996. Hospital coders determined

work-relatedness of these injuries by review of emergency department charts and

admission information. These injuries occurred to 30% of an estimated 3.3 million

injured workers (990,000) (Morbibity Mortality Weekly Report, 1998). Another

clinical-setting-based study in the USA found similar results using the NHAMCS.

(McCraig, et al., 1998) Medical records were reviewed for any indication that injuryoccurred in the course of paid employment. There were an estimated 627,000 visits for

upper extremity laceration among 4.4 million work-related hospital and out-patient

G.S. Sorock et al. / Safety Science 38 (2001) 241±256 243



visits (14%). Fifty percent of hand injuries treated in emergency departments were

lacerations. The largest remaining categories were contusion/abrasion/hematoma

(14%), fracture (8%), sprain/strain (4%), burn (3%), and other types (20%).

The BLS SOII provides estimates of injury characteristics for employer-reportedinjuries resulting in at least 1-day-away-from work (DAW). Table 1 presents the

leading acute traumatic injuries to the upper extremity in 1994 ranked by frequency

(Courtney and Webster, 1999). Laceration of the ®ngers and hand had the highest

frequency and incidence rates followed by fractured ®nger (with a median of nine

lost work days). Seven of the 10 most frequently injured upper extremity body parts

among these DAW cases involved the ®ngers or hand.

3.1. Injury severity (lost work days) at the national level

Though the high frequency of hand injuries among USA workers is readily

established, the impact of such injuries is less well known. Courtney and Websters'

study of the BLS data further indicated that cuts and lacerations to the ®ngers and

hand accounted for medians of 3 and 4 DAW per case, respectively, whereas frac-

tures and amputations of the ®nger accounted for medians of 9 and 22 DAW,

respectively (Courtney and Webster, 1999; see Table 1). Fractures of the arm and

wrist had medians of 23 and 27 days lost, respectively. By contrast, sprains or strains

of the wrist were reported to have a median of 5 DAW, and wrist disorders of the

peripheral nervous system to have a median of 30 DAW (data not shown) (Courtney

and Webster, 1999). More severe traumatic injuries including wrist fracture, tendonlacerations and amputations have been reported elsewhere in the literature to be

associated with signi®cant disability (1±6 months; Skov et al., 1999, Van Der Molen,

1999). Beyond the physical injury, other studies suggest psychological symptoms

Table 1

Leading upper extremity traumatic injury cases with days-away-from work reported to BLS in 1994a

Rank Body part Nature of injury Number Incidence

ratebMedian

days away

1 Finger Laceration 81,837 10.1 3

2 Hand Laceration 27,360 3.4 4

3 Finger Fracture 23,185 2.9 9

4 Finger Non-spec. injury 17,373 2.2 5

5 Arm Bruise/Contusion 13,362 1.7 3

6 Hand Bruise/Contusion 12,673 1.6 3

7 Wrist Fracture 12,646 1.6 27

8 Arm Fracture 12,370 1.5 23

9 Finger Amputation 11,658 1.4 22

10 Finger Bruise/Contusion 11,321 1.4 2

Total 223,785a Developed from: Courtney and Webster (1999), Table 4.b Incidence rate is number of new cases per 10,000 full-time workers per year (1994).




associated with post traumatic stress disorders can persist up to 18 months after the

date of severe occupational hand injury (amputation, crush, nerve lacerations) and

can eect return to work (Grunert et al., 1992). In summary, hand injuries are

common and in the aggregate result in large amounts of lost work time. Hand injuryincidence rates may suggest how many such cases can be expected in a clinical set-

ting and in what sorts of industrial settings.

3.2. Incidence of hand injuries treated in clinical settings

Table 2 (Mathur and Sharma, 1988; Oleske and Hahn, 1992; Angermann and

Lohman, 1993; Sorock et al., 1993; Skov, 1994; Boyle et al., 2000) summarizes three

USA and three international studies that include information on rates of hand

injury per 100 person-years from inpatient, outpatient or combined settings. The

incidence of occupational hand injury treated in hospital emergency departments

was 1.6 (Angermann and Lohman, 1993) to 1.7 (Skov, 1994) per 100 worker-years.

In another study of cases treated in an orthopedics unit of one large hospital in

India, the rate was lower (0.4 per 100 worker-years). In the latter study, 44% of

the cases were amputations, or fractures (Mathur and Sharma, 1988). In one of the

largest studies of hand and wrist injuries treated in hospital emergency depart-

ments, 72% of occupational hand injuries were to the ®ngers, 21% to the hand and

6% to the wrist (Angermann and Lehman, 1993). In this same study, 2% of all

hand injuries, regardless of injury location, were hospitalized. Sorock et al. (1993)

reported that the rate of hospitalized occupational ®nger amputations was 1/10,000worker-years, which is consistent with Table 1 data for ®nger amputation incidence

(1.4/10,000 worker-years). More recently, Boyle et al. (2000) reported a rate of 4/

10,000 worker-years for ®nger (95%) and hand (5%) amputations. The large dis-

crepancy in rates (by two orders of magnitude) in Table 2 are a re¯ection of the

lower incidence of amputations in the employed populations compared with less

severe injuries.

3.3. Incidence of hand injury in industry-speci®c studies

Table 3 summarizes four national and eight international industry-speci®c studiesof hand injury (Bennett and Passmore, 1986; Jensen, 1987; Ong et al., 1987; Norrish

and Cryer, 1990; Nikoli and Mavric, 1994; Nordstrom et al., 1995; Pickett et al.,

1995; Wohl et al., 1995; La¯amme, 1996; La¯amme and Blank, 1996; Laing et

al., 1997; Nag and Patel, 1998). For comparison purposes, three studies report on

upper extremity injuries, where we assume 70±80% of the injuries involve the hand.

A total of 11 industries are represented in the table including ®shing, textile, steel,

tractor, petro-chemical, food products, automobile manufacturing, farming (two

studies), automobile assembly, iron ore and coal mining. The design for all but one

of the studies was retrospective (Wohl et al., 1995), and there was variation by study

in the body part included, the total number of subjects, the duration of thestudy periods (from 1 to 14 years) and the estimated rates (range 0.33±11.0 per 100

worker-years). The source data for these studies also varied and included company




Table 2Summary of six studies of hand injury cases treated in hospitals or clinics

Author Country (study period) Treatment site Case de®nition Persons

injured

Angermann (1993) Denmark (1990±1991) 5 hospital accident/emergency

departments

Hand and wrist injury 12,950

Boyle et al. (1999a) Minnesota, USA

(1994±1995)

Hospital-treated or hospitalized Finger/thumb

amputation (95%)

Other amputation (5%)

601

Mathur and

Sharma (1988)

India (1983±1986) Employees state insurance

hospital orthopedics unit

Hand Injuries: 44%

amputation or fractures56% less severe

661

Oleske (1992) Illinois, USA (1988) 5 occupational health clinics Hand/®nger only 59%

laceration 21% contusion

8% fractures 5% sprain/

strain 8% other

4120

Skov (1994) Denmark (1991) University hospital ED

6 months surveillance

Hand Injury±Severeb

vs. Minor

824

Sorock et al. (1993) New Jersery, USA

(1985±1986)

105 acute care hospitals

discharge abstracts

(Hospitalized cases)

Finger amputation only

609

a Estimated 60% of total population was employed in 1990±1991 (x2)=677,570Â.6Â2.b

Severe injury is de®ned as laceration, fracture or tendon or nerve damage.



Table 3

Summary of 12 industry-based studies of occupational upper extremity trauma (UET)

Reference (year) Industry Country Source data Body

part(s)

Includeda

Total

employees

or Subjects

Tim

per

(ye

Norrish and Cryer

(1990)

Commercial ®shing New Zealand Industry-wide compensation

claims

H, F 3200 1

Nag and Patel (1998) Textile industry India Selected group of companies,

records and questionnaire

H, F Est. annual 6980 3

Laing et al. (1997) Food products

manufacturing

New Zealand Industry-wide from National

sources, hospitalizations

H, A 1979±88 29,481±

25,585

10

La¯amme (1996) Automobile assembly

workers

Sweden Industry-wide from Swedish

National data sources

H, F, W Est. annual 3619

(females)

6

La¯amme and

Blank (1996)

Iron ore miners Sweden Single mine, from Swedish

National sources

H, F, W Est. annual 1100 14

Pickett et al. (1995) Farming Canada(Ontario) Mail survey questionnaireto a sample of farmers UE 3752 1

Nordstrom et al.

(1995)

Farming USA

(Wisconsin)

Clinic and hospital records

of three rural counties

UE 978 2

Nikoli and Mavric

(1994)

Tractor

manufacturing

Yugoslavia Factory medical records F, P Est. annual 3058 5

Jensen (1987) Petro-chemical

manufacturing

USA (Texas) Single large-facility from

®rst-aid records

F Est. annual 3000 5

Ong et al. (1987) Steel manufacturing Singapore Company medical records H Est. annual 664 5

Bennett and

Passmore (1986)

Coal miners USA Industry-wide from National

sources (DOL)

H, F Est. annuale

240,399

9

Wohl et al. (1995) Aircraft

manufacturing

USA

(California)

Company medical, personnel,

and insurance records

UE 156 cases 312

controls (females)

1

a Body Part: UE=all upper extremities, H=hand, F=®nger, W=wrist, P=palm, A=arm.b For the crude UET rate, the person-year denominator was estimated by multiplying the total number of employees or subjects by t

by the author, the cohort is assumed to be an approximation of the average work force at risk per year.c The rate for farm residents was presented as 38.3 per 10,000 farm resident person-years.d Approximately 27% of the total events were caused by contact with hot substances or exposures to high temperature.e Data source: Mine Safety and Health Administration.



medical and ®rst-aid records, national-level industry records, clinic and hospital

records, and mail survey questionnaires. Other factors in¯uencing the variability of

these rates include the number of body parts studied, the method of injury ascertain-

ment (data source), and dierences between countries in work methods, safety andreporting procedures. For example, the estimated rate for steel manufacturing utilized

company in-house medical records included many cases requiring minimal medical

intervention (Ong et al., 1987), while the rate for food products manufacturing was

low because it was based on hospitalized cases Ð the most severe subset of hand

injury (Laing et al., 1997). This ®nding was in contrast to a Swedish study of DAW

cases of hand injuries in which butchers and meat-preparers had the highest rates of

injuries (13.3 per 100/year) (Carlsson, 1984). Injured workers in this industry may

have to stay home for more minor injuries for food safety reasons. In the ®shing

industry, more than one-third of upper extremity lacerations became infected, which

demonstrates the post-injury risk of infection by contaminated food products (Fer-

guson and Sapelli, 1992). The industry-speci®c incidence rates in Table 3 are, in

general, higher than the clinically-based incidence rates presented in Table 2.

In summary, hand injury incidence rates will clearly vary depending on industry

and clinical setting, which is a re¯ection of the lower frequency of more severe

injuries presenting for treatment. Ultimately, prevention of these injuries is depen-

dent on what is known about risk factors for their occurrence.

3.4. Multi-industry descriptive studies of hand injuries

Two large scale special surveys by the BLS, when examined together, suggest the

circumstances related to less severe hand injuries may be similar to more severe hand

injuries (Bureau of Labor Statistics, 1982). One study examined hand injuries (cuts,

fractures, scratches or burns) resulting in one or more days away from work. The

other was limited to amputations of the arm, hand or ®nger. The hand injury survey

of lacerations, punctures, cuts and fractures included 944 cases; 653 of the cases

(69%) had lacerations, punctures and cuts, 245 (26%) of the cases had fractures.

The remaining 46 (5%) of cases had burns or abrasions. The amputation survey

included 862 cases, 99% of which were to the ®ngers. Seventy-two percent of the

amputations occurred to the ®nger tip or distal phalange. Where possible, both setsof data were also compared to an earlier BLS survey of 8602 amputations

(McCaery, 1981). The industry and occupation of subjects with both lacera-

tions and amputations were similar (Table 4; McCaery, 1981; Bureau of Labor

Statistics, 1982). The highest numbers and rates of hand and ®nger injuries were in

manufacturing. Construction and retail were the second and third most involved

industries, respectively (McCaery, 1981). These ®ndings are consistent with more

recent research (Olson and Gerberich, 1986; Boyle et al., 2000). Hand and ®nger

injuries most often occurred to machinery maintenance workers, (US Department of

Labor, 1981) machine operators and tenders, craft and kindred operators, followed

by manual materials handlers and food preparers.The leading ®ve conditions that contributed to an injury were similar for both

classes of injury: being in a hurry, not realizing the hand was in a hazardous area,




misjudging time and distance to avoid an injury, shifting work materials or tools,

and attention not fully on task (Table 5; Bureau of Labor Statistics, 1993). A

similar conclusion was reached when comparing the activities prior to 11,322

injury-producing incidents (83% OSHA-recordable, 13% ®rst-aid only) in a large

petrochemical manufacturing complex. The percent distribution of four dierent

activities prior to OSHA recordable or ®rst-aid-only injuries were similar (Laughery

and Vaubel, 1993). The most frequent injury type was a laceration, burn or contu-

sion to the ®ngers or arm. These studies suggest that the etiology may be some-what similar for more and less severe injuries, apart from the role that machinery

plays in the most severe injuries Ð amputations. Protection against less severe hand

Table 4

Percent distribution of industry/occupation and demographic factors among UE injured workers

1981a Hand injury

(n=944; %)

1981a UE

Amputation

(n=862; %)

1977b UE

Amputation

(n=8602; %)

Leading industries

Manufacturing 60 62 60

Construction 13 10 9

Retail trade 8 6 ±

Leading occupations

Operatives excluding transport 45 41 46

Craft and kindred workers 35 31 28

Laborers excluding farm 14 15 18

Leading sources of injury

Machines 37 65 54

Metal items 19 8 12

Hand tools non-powered 16 ± c 4

Hand tools powered 5 ± 5

Gender

Male 86 87 ±

Female 14 13 ±

Age (years)16±19 7 6 ±

20±24 26 17 ±

25±34 29 26 ±

35±44 15 17 ±

45±54 10 13 ±

55±65 10 14 ±

65+ 1 2 ±

a BLS, USDOL (Bureau of Labor Statistics, 1982).b McCarey (1987).c ±, unavailable.




injuries may also protect against the more severe injuries. This hypothesis needs tobe adequately tested.

3.4.1. Age and gender

Young workers 24 years of age or younger have the highest risk of occupational

hand and ®nger trauma (Olson and Gerberich, 1986; Skov, 1994; La¯amme and

Blank, 1996; Boyle et al., 2000). These ®ndings may re¯ect the length of job experi-

ence, and hazardous work conditions present at the time of the injury. Clinical stu-

dies have reported dierent rates of hand injury for men and women. Skov (1994)

reported a rate of 2.4 for men and 1.0 for women in one large Danish hospital. For

emergency-department-treated occupational ®nger injuries in the USA, the reportedrates per 100 worker-years were 1.0 for men and 0.6 for women (Pizatella and Moll,

1987). Similarly, Sorock et al. (1993) reported that the rate of hospitalized ®nger

Table 5

Distribution of Circumstances for UE injuries

1981a Hand

injury (n=944; %)

1981a UE

Amputation

(n=862; %)

Activity at time of injury:

Working with/on machinery 44 66

Lifting/carrying/handling objects 23 15

Non-powered hand tool (e.g. knife) 19 2

Powered hand tool (e.g. portable saw) 7 5

How did injury occur?

Flying/falling/swinging object hit hand 36 15

Caught in/between machinery/objects 17 34

Struck by moving machine part 16 25UE hit against moving machine part 14 24

Conditions which led to injury

In a hurry 29 25

Did not realize UE was in hazardous area 26 29

Misjudged time/distance to avoid injury 20 16

Work material shifted position or broke 19 17

Tool/machinery shifted position/slipped 17 10

Hand slipped 17 8

Attention not fully on task 11 11

Not looking at hand 10 9

Tool/equipment in bad condition 9 12No safeguard on machinery/tool 9 17

Co-worker did something to cause injury 7 13

Tool or machinery accidentally activated 6 13

a Source: BLS 1982 (Bureau of Labor Statistics, 1982); Percentages will exceed 100 where more than

one prior condition was indicated; percentages less than 100 are a result of selecting the leading four

categories.




amputation for men was seven times higher than for women per 100,000 worker-

years (14.7 versus 1.9) among workers in New Jersey. The BLS (Bureau of Labor

Statistics, 1982) found that hand injury severity distributions by gender were similar

(Table 4), suggesting that gender may not statistically signi®cantly in¯uence the riskof hand injury provided the task demands, job experience and age are held constant

between men and women. In future studies, adjustment for occupation, age and

length of employment would be useful to assess potential dierences in injury risk by

gender (Payne and Waller, 1989; Powell et al., 2000).

4. Analytic epidemiology

The only published case-control study of risk factors for hand injury in the lit-

erature was published by Hertz and Emmett (1986). This study included 124

municipal government employees who sustained a hand injury at work. Each case

employee was individually matched to a control employee who was at work during

the time of the case's injury. Cases and controls were also matched on gender and

job. All interviews were completed within 8 days of the index date of the injury via

a telephone questionnaire. Exposures on or near the index time of the injury for

each case were asked of all case-control pairs. Cuts and lacerations (48%) and

sprains (45%) accounted for the largest percentage of cases. The risk (odds ratio,

95% con®dence interval) of a hand injury was signi®cantly elevated while using

defective materials (O.R.=30.0, 5.0± I

), performing a non-typical task (O.R.=23.0, 3.7± I), and being less than 25 years of age (O.R.=3.0, 1.0±10.6). Not

using gloves at the time of the injury also increased the hand injury risk: (O.R.=

2.6, 1.1±6.9)

One major limitation of all observational research including case-control studies is

the presence of between-person confounders. For example, injured persons may

dier from uninjured persons according to hand speed (Punnett, 1994), perceptual-

motor skills, risk-taking behavior, injury history, or job experience. Moreover,

matching on job does not answer the question of which tasks within a job are high

risk. In addition, cases who seek medical care may be dierent from controls who

have not (selection bias), especially for less severe occupational traumatic injury(Saari, 1997). Further, transient risk factors that are present immediately prior to

the injury (e.g. being rushed, distracted, or doing a task in an unusual fashion) are

typically not evaluated as in the above study. Controlled studies of occupational

injury (not limited to upper extremity trauma) may oer additional insights into

potential injury mechanisms. One shop ¯oor study of 2367 injuries in manufacturing

suggested that controls for injured workers are dicult to select because people

doing the same task perform it dierently (Boyle et al., 2000). This suggests that

injured workers may best serve as their own controls. Additionally, machines

that appear to be the same may operate quite dierently depending on age, wear and

settings. Two other controlled studies suggest that limited experience in manu-facturing environments increases the risk of an injury two to eight fold (Hanecke et

al., 1998; Harma et al., 1998).




5. Directions for future epidemiological research

Descriptive studies have suggested that in addition to workplace and worker

characteristics, transient work practices (e.g. uncommon work tasks, work methods,or tools), unusual conditions of work equipment (e.g. malfunctioning tools or

equipment), and individual and work organization-related factors (e.g. fatigue,

rushing, distractions) may be potential risk factors (Bureau of Labor Statistics,

1982; Kelsh and Sahl, 1996; Nag and Patel, 1998). Boyle (Morbidity Mortality

Weekly Report, 1982, 1983) reported that working an unusual job may increase

the risk of amputation and the severity of the amputations which occur. A study

of the textile industry in India reported that the two main risk factors which

increased the risk of injury were the start up of the working period and `accumulated

fatigue' (Nag and Patel, 1998). A large database study of 1.2 million injuries

reported on the potential time-related fatigue eects on occupational accident risk

occurring in the German working population (Kelsh and Sahl, 1996). Other studies

have suggested that shift work may also in¯uence injury incidence due to dierences

in the quality of sleep and sleep patterns for both shift and non-shift workers (Jensen

and Sinkule, 1988). Fatigue and other transient factors at work may be a useful

focus of future etiological research on hand injury.

The current state of knowledge of the etiology of occupational injuries is almost

entirely limited to descriptive studies of injured cases (Kraus, 1985; Veazie et al.,

1994). Without proper controls, person-time denominators of work exposure, and

the identi®cation and control of potential confounders, few advances in injury pre-vention can be expected. Advances in understanding potential causes of hand injury

may require dierent research questions. For example, how can we eectively con-

trol for age, length of experience and task demands when assessing gender dier-

ences in injury risk? Why does a hand injury occur at one point in time and not at

other times, given that work tasks are often done repeatedly? What is unusual about

the work environment or dierent within the individual at the time an injury occurs?

A methodology is needed for identifying variations in changes in the work environ-

ment that may be part of the causal pathway of the `accident' (Lepalt and Rasmus-

sen, 1984).

Some suggestions for addressing these questions and for future research are listedbelow.

1. Planning etiological studies of occupational hand injuries might begin with

unstructured interviews with hand-injured workers. This might be speci®c to

one company, or one injury scenario, such as knife-related or machinery-related

lacerations (Drury and Brill, 1983). Such descriptions may increase the range of

potential risk factors for study in a more structured interview (Cheng, 1997).

2. New epidemiological methods used to study triggering events for acute myo-

cardial infarction can be applied to the study of transient factors associated with

hand injury in the work environment (Mittleman et al., 1997). Speci®cally, thecase-crossover design which uses cases as their own controls, has been shown to

be useful for studying the role of transient risk factors in occupational hand




injuries (Sorock et al., 2001). This design assesses the etiologic role of transient

factors close to the time of the injury. One of its main strengths is the ability to

perfectly control for between-individual confounders (such as age, gender and

occupation). Control information comes from each case regarding their usualfrequency of exposure to transient factors such as glove use, malfunctioning

equipment, or feeling ill at work. This methodology has limitations associated

with retrospective research including potential recall bias (Redelmeier and

Tibshirani, 1997).

3. Manufacturing plants might collaborate with researchers as study locations to

participate in multiple ongoing surveillance and controlled studies of hand

injury (case-control and case-crossover). These same sites would be potential

locations for intervention eorts to reduce exposure to risk factors for injuries.

Surveillance and controlled investigations would then monitor not only change

in hand injury incidence, but change in exposures as well. Repeated case-

crossover studies could examine the exposure-injury relationship over time.

4. Dierences in outcome de®nition between studies included in this review often

made comparisons dicult. Future studies should make every eort to clearly

de®ne the nature of injury and upper extremity part of body aected and cross-

tabulate these two variables where possible. In addition, studies should include

reporting based on at least one reasonably universal outcome categorization

related to disability such as injuries resulting in 1 day of absence from work or

more.

5. The Hand Injury Severity Score (HISS) could prove useful for rating injuryseverity (Campbell and Kray, 1996). The HISS is a method of rating in-

jury severity in the skeletal, motor and neural domains for each ®nger sepa-

rately. Each ®nger's score is multiplied by a weighting factor and added to the

scores of other ®ngers for a total injury score. The HISS scale needs further

testing for applicability with less severe hand injuries.

In summary, the descriptive epidemiological and related literature on acute hand

injury at work indicates high-risk industries and occupations. Dierences in risk by

age and gender may still be confounded by work exposure and length of job

experience. Further progress in hand injury prevention will require analytic studiesto identify modi®able risk factors for these injuries, e.g. glove use, fatigue or use of

an unusual tool. In this regard, case-crossover studies appear to be one promising

approach to improving our understanding of why these injuries may occur (Sorock

et al., 2001).

Acknowledgements

We are grateful to our colleagues Larry Layne, Barbara Webster, Edward Clancy

and David Parker for their helpful comments on earlier versions of the manuscript.Patricia Boelsen carefully prepared the manuscript for submission. This work was

supported in part by NIOSH grant R01 OH-03763-01.




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