upper extremity in poultry proc
TRANSCRIPT
AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 51:24–36 (2008)
Upper Extremity Musculoskeletal Symptoms andDisorders Among a Cohort of Women Employed in
Poultry Processing
Hester Lipscomb,� Kristen Kucera, Carol Epling, and John Dement
Background We evaluated musculoskeletal problems amongwomen employed in poultryprocessing in rural northeastern North Carolina. Poultry processing is the largest singleemployer of women in this economically depressed region with a black majoritypopulation.Methods Data were collected from a cohort of 291 women through interviews andphysical exams conducted at 6-month intervals over 3 years. An index of cumulativeexposure, based on departmental rankings and work history, was the primary exposurevariable. Other variables of interest included work organization factors, other medicalconditions, depressive symptoms, children in the home, and hand intensive home activities.Poisson regression with generalized estimating equations was used to evaluate factorsassociated with occurrences of upper extremity symptoms and incidence of disorders atfollow-up.Results Symptoms making it difficult to maintain work speed or quality and depressivesymptoms at baseline were associated with symptoms at follow-up; age, being overweight,and job insecurity at baseline were associated with incident disorders. After consideringthese factors, the exposure response pattern was J-shaped with risk decreasing inthe second quartile of cumulative exposure and then going steadily up; the effect wasstronger for disorders.Conclusions The pattern of risk is consistentwith onset of earlymusculoskeletal problemsamong women new to the industry followed by a later increase with continued exposure.Among this highly exposed population, the effects of depressive symptoms and workorganization factors were diminished when cumulative exposure was considered,illustrating the contextual nature of the complex relationships between physical workexposures and psychosocial factors. Am. J. Ind. Med. 51:24–36, 2008.� 2007 Wiley-Liss, Inc.
KEY WORDS: cohort study; poultry processing; musculoskeletal disorders; women’shealth; work-related
BACKGROUND
As early as the 18th Century, musculoskeletal problems
were clinically described in terms of work-relatedness, and a
number of disorders—bricklayer’s shoulder, stitcher’s wrist,
gamekeeper’s thumb, carpet-layer’s, and housemaid’s knee—
have been named for the occupational groups in which they
were identified [Hales and Bernard, 1996]. Besides this history
� 2007Wiley-Liss, Inc.
Duke University Medical Center, Durham, North CarolinaContract grant sponsor: National Institute of Environmental Health Sciences; Contract
grant sponsor: National Institute of Arthritis Musculoskeletal and Skin Diseases; Contractgrant number: R01ES10939.
*Correspondence to: Hester Lipscomb, Box 3834, DUMC, Durham, NC 27710.E-mail: [email protected]
Accepted10 September 2007DOI10.1002/ajim.20527. Published online inWiley InterScience
(www.interscience.wiley.com)
of clinical observation, there is a body of more recent
epidemiologic literature linking musculoskeletal disorders
(MSDs) with occupational exposures, such as repetitiveness
of work, force requirements, posture, vibration, lifting, and
combinations of these factors [NIOSH, 1997]. Despite
established clinical labels and epidemiologic literature,
attribution of work-relatedness to musculoskeletal problems
has been an area of contention in occupational health.
The lack of full acceptance may result, in part, from
limitations in the existing scientific work. The vast majority
of epidemiologic studies of MSDs in industry have been
cross-sectional. In addition, there is a limited understanding
of the exact roles that psychosocial factors play in develop-
ment, expression, care seeking and disability related to these
disorders [Westgaard and Bjorkland, 1987]. Monotonous
work, time pressures, and perceived high work load have all
been described as being associated with work-related MSDs;
however, the findings are not consistent across studies, and
the reported associations could be attributed to physical work
factors associated with these variables [Bongers et al., 1993].
Worker capacity and skill, as well as work environment and
organization may influence the development and/or expres-
sion of MSDs [Hagberg, 1992]. Complicating interpretation,
psychosocial and physical demands may also be highly
correlated in some situations [Bernard et al., 1993].
Unfortunately, attention to psychosocial dimensions of the
problem may contribute to perceptions that workers who
report musculoskeletal symptoms are ‘‘malcontents’’ or
more likely to complain for reasons independent of physical
pathology [Hadler, 2003].
We responded to a request from women in rural
northeastern of North Carolina to evaluate health effects of
their employment in poultry processing, the largest single
employer of women in this economically depressed rural
area. The study counties are among the poorest in the state
with black majorities [U.S. Census Bureau, 2004]. The
poultry plant, which provides yearly salaries of about US
$17,000, is among the higher paying jobs of women in
the area. In 1989, N.C. Occupational Safety and Health
Administration (OSHA) inspectors cited the plants in the
area for serious upper extremity repetitive motion problems,
[NC Dept of Labor, 1989] and the National Institute for
Occupational Safety and Health (NIOSH) confirmed the risk
in a subsequent Health Hazard Evaluation (HHE) [Kiken
et al., 1990]. Primary community concerns continued to
center on upper extremity musculoskeletal disorders as well
as quality of life issues.
METHODS
Study Design
We conducted a longitudinal study of women employed
in this industry to explore the relationships among health
outcomes, tenure in the plant, exposure differences, and
coping strategies. We hypothesized that the development of
symptoms and disorders would be associated with the
physical work exposures/demands. We were also interested
in evaluating relative contributions of work organization
factors in this fast-paced upper extremity intensive work. In
this poor economic region, we were concerned that economic
depravity might influence women to remain in jobs that might
be harmful to their health due to lack of alternative
employment.
Based on community concerns and the history of the
industry’s poor labor relationships, locally as well as
nationally [NC Dept of Labor, 1989; Kiken et al., 1990;
Griffith, 1993; Human Rights Watch, 2000; Fink, 2003], we
conducted the study in a manner that did not require the
cooperation of the employer. This decision influenced the
research methods and necessitated community involvement.
The project background and details of the community-based
study design have been previously described [Lipscomb
et al., 2005]; key elements are presented briefly here.
Between May 2002 and March 2004 community-based
staff recruited women employed in poultry processing in
northeastern North Carolina to participate in the longitudinal
study. Women were enrolled largely through social networks
without regard for their current symptoms or prior medical
history. Initial recruitment was limited to individuals who
were relatively new hires (9 months or less) to the industry
intentionally over-sampling women who were new to the
industry.
This cohort participated in interviews and physical
exams conducted in a community-based office at 6 month
intervals over a maximum of 3 years. Questionnaires were
administered by the community-based staff; this allowed
collection of data from individuals who might lack necessary
reading skills to complete the detailed tool on their own.
Trained study nurses performed standardized physical exams
based on the protocol developed for the Washington State
Department of Labor and Industries Safety and Health
Assessment and Research Program (SHARP) upper extrem-
ity musculoskeletal study [Viikari-Juntura, 2000]. Informa-
tion on work exposure in each department and changes in
work processes was collected through 39 key informant
interviews with current and past poultry workers represent-
ing each department in the plant.
Participants received $40 for each interview/exam
encounter or qualitative interview. All procedures were
approved by the Duke University Medical Center Institu-
tional Review Board.
Upper extremity outcomes
Participants were asked about current musculoskeletal
symptoms and symptoms they had since their last follow-up
(in the last 12 months at baseline) using items adapted from
Musculoskeletal Disorders in Poultry Processing 25
the questionnaire developed by the NIOSH Research
Program for the prevention of work-related musculoskeletal
disorders [NIOSH, 2000]. Participants with hand symptoms
were asked to complete a hand diagram, documenting areas
of pain or paresthesias. The diagrams were rated by one
occupational medicine physician (CE) for probable or classic
carpal tunnel syndrome (CTS) as described by Katz et al.,
[1990] as well as for pain in the radial, flexor, or extensor
wrist, and numbness or pain in the ulnar nerve distribution.
We separately evaluated the presence of symptoms and
musculoskeletal disorders at follow-up. Women with all
three of the following criteria were considered symptomatic:
(1) upper extremity or neck symptoms (pain, aching, stiff-
ness, burning, numbness, or tingling) that lasted a week or
longer or that occurred more than three times since their last
follow-up, (2) onset of symptoms after beginning work at the
plant, and (3) no prior acute trauma to the painful region such
as a fracture or sports injury. To be defined as having a
musculoskeletal disorder a woman had to have the above
symptom threshold and positive physical exam findings in
the same body region as her reported pain consistent with a
musculoskeletal disorder (tendonitis, tenosynovitis, nerve
compression syndromes). The disorder definitions were
based on reported criteria for defining musculoskeletal
disorders in epidemiologic studies [Palmer et al., 2000;
Sluiter et al., 2001]. The exact criteria for the case definitions
are provided in the attached Appendix. In both cases, we
combined all upper extremity conditions (disorders or
symptoms) involving the hand/wrist, forearm/elbow, and
shoulder due to limited statistical power to evaluate them
separately.
Exposure assignment
Our primary exposure of interest was an index of cumu-
lative exposure. This index was created by assigning a rank of
high, medium, or low exposure to each department in the
poultry plant based on assignment at the time of the NIOSH
HHE. The exposure assignments were based on exposure to
repetitive and forceful movements and/or extreme, awkward
upper extremity postures observed in walk-through assess-
ments [Kiken et al., 1990]. High exposure rank was assigned
to evisceration (gutting of birds), grade and rehang (birds are
assigned a grade based on quality of meat and rehung on
shackles to move through the plant), deboning (deboning of
white meat fillets and packaging), and cut-up (cutting and
packaging of chicken pieces); low exposure was assigned to
inspection (US Department of Agriculture meat inspection
helper), giblets (packaging of livers and gizzards), sanitation
(clean-up), and other jobs including clerical work. We
assigned a medium grade of exposure to women working in
overwrap (packaging) and whole bird bagging. The rank
(3¼High, 2¼Medium, 1¼Low) was then multiplied
by time in the department for each person based on their
reported work history. For example, a woman working one
full-time year (always assigned 2,000 hr per year) in
evisceration (H¼ 3) and two fulltime years (4,000 hr) in
overwrap (M¼ 2) had a cumulative exposure assignment of
(3� 2,000)þ (2� 4,000)¼ 14,000 rank-hours. Values for
individuals who had worked in more than one department
were summed at the baseline evaluation. Additional
cumulative exposure was assigned at each follow-up period
based on self-report of job changes.
Risk factors or possible confoundersfor upper extremity disorders
Individuals were queried about prior medical history
including musculoskeletal problems, injuries or surgery, as
well as history of diabetes, sickle cell, thyroid disease, lupus,
kidney failure, trauma, pregnancies, and smoking history.
Specific questions were included on hormonal therapies as
well as a report of use of any other regular medications.
Because of the possible relationships between depres-
sion and pain complaints, we included the Center for
Epidemiologic Studies Depression Scale (CES-D) as a
measure of depressive symptoms [Radloff, 1977]. This 20-
item self-report tool has been used to assess depressive
symptoms in varied population groups including African-
American populations and women [Miller et al., 2004;
Nguyen et al., 2004]. Values over 16 represent evidence of
depressive symptoms.
Levels of psychological demand and control (latitude),
or job strain, were measured using the Job Content
Questionnaire (JCQ) developed by Karasek [Karasek et al.,
1998]; high strain was defined among individuals with high
psychological demands and low decision latitude with cut
points at the median for the study population. The JCQ
includes scales to assess social support, physical job
demands, isometric load (sustained awkward work postures),
job insecurity and dissatisfaction; these scales were dicho-
tomized at the population median.
Because of interest in how socioeconomic disadvantage
might influence development of, or impairment from,
musculoskeletal symptoms by limiting the ability of women
to leave jobs that might adversely affect their health,
participants were asked how long they could be out of work
without pay before loss of their income would be a major
problem. They were also asked about children in the home, the
availability of another adult to help with household responsi-
bilities, and weekly frequency of hand and arm intensive
activities such as needlework, keyboard use, or braiding hair.
Analyses
Descriptive statistics were calculated by baseline
demographics and work history variables. Because of the
26 Lipscomb et al.
non-specific nature of many musculoskeletal symptoms and
our interest in their dynamic nature, we evaluated the
occurrence of upper extremity musculoskeletal symptoms,
as opposed to incidence in which the individual would be
censored after first development of symptoms. This approach
allowed us to look at prior symptoms and their severity as
predictors of later symptoms. Individuals with disorders at
baseline were excluded from the symptom analyses because
we did not know when in their exposure history they had
developed their problem. However they did remain at risk for
development of a different disorder. In follow-up, individuals
identified with a given disorder were not at risk for the same
disorder until they had at least one follow-up without that
disorder.
Days at risk were calculated from days between follow-
up assessments. Incidence and occurrence rates and rate
ratios (RR) were modeled using Poisson regression with the
log of person-days included as an offset term [Nizim, 2000].
Generalized estimating equations (GEE) [Liang and Zeger,
1986] were used to control for the statistical dependence
between multiple assessments per worker. Separate models
were created allowing us to compare risk factors associated
with (1) occurrence of symptoms and (2) incidence of
disorders at follow-up.
Covariates were included in the initial models if the
crude RR was greater than 1.2 (or less than 0.85). A step-wise
backwards elimination strategy was used. Variables inde-
pendently associated with the outcome based on likelihood
ratio statistics were retained as were covariates whose
removal resulted in more than a 15% change from the crude
to adjusted risk ratios. No variables were removed from the
models with a P-value of less than 0.10.
RESULTS
Two hundred ninety-one women completed baseline
interviews and physical exams. They were relatively young
(mean age 31.4 years; median 28 years) and predominantly
black (98.3%) (Table I). Few of these working women
reported other non-musculoskeletal chronic medical con-
ditions (kidney disease (0.34%), sickle cell disease or trait
(4.8%), diabetes (3.1%), thyroid disease (2.8%), Raynauds
(0.34%). With the exception of diabetes, none of these
conditions were significant in multivariate analyses and they
are not discussed further. The cohort was markedly obese;
only 16.5% (n¼ 48) were at normal body weight based on
body mass index (BMI). BMI values ranged from 16.4 to
64.4, with a mean of 33.4. At baseline, 47.8% (n¼ 139) had
CES-D scores of 16 or higher indicative of significant
depressive symptoms. Almost all worked fulltime exclu-
sively at the poultry processing plant and about half reported
job rotation most work days (Table II). Most (86%) worked
currently in high exposure departments.
TABLE I. Characteristics of Female PoultryWorkers (n¼ 291),Northeastern North Carolina, 2002^2004
Age 18^61;mean 31.4; median 28Black 286 (98.3)Marital statusSingle 192 (66.0)Married 61 (21.0)Divorced/separated/widowed 38 (13.1)
Numberof people in home 1^13; mean 3.7; median 4Number employed
One 140 (48.1)Two 113 (38.8)Three ormore 38 (13.1)
Number children in homeNone 57 (19.6)One 84 (28.9)Two 85 (29.2)Three ormore 65 (22.3)
Another adult in home to help 175 (60.1)Education<High school 70 (24.1)High school 199 (68.4)>High school 22 (7.6)
Hourly wages $6^$14; mean $8.18; median $8.35Loss of incomemajor problem in1week or less 181 (62.2)2^3weeks 78 (26.8)�1month 32 (11.0)
TABLE II. Work Characteristics of Female PoultryWorkers (n¼ 291),Northeastern North Carolina, 2002^2004
Timeworked in plant at baseline 1^418months;mean 53.8months;median 7months
Work fulltime in poultry plant 273 (93.8%)Job rotationmost days 135 (46.4%)Primary department in plantEvisceration (H) 28 (9.6%)Inspection (L) 2 (0.69%)Grade and rehang (H) 10 (3.4%)Giblets (L) 2 (0.69%)Cut-up (H) 79 (27.2%)Deboning (H) 133 (45.7%)Whole bird bagging (M) 7 (2.4%)Overwrap (M) 13 (4.5%Sanitation (L) 9 (3.1%)Other (L) 8 (2.8%)
Second job away fromplant 18 (6.2%)
H¼ high exposure department; M¼medium exposure department; L¼ low expo-sure department.
Musculoskeletal Disorders in Poultry Processing 27
One hundred fifty (n¼ 150) women were still actively
employed study participants at the close of follow-up.
Fourteen percent (n¼ 41) were lost to follow-up. The
remaining women no longer worked in the plant but their
reasons for leaving were known and most often included:
quitting for another job (n¼ 55), having been fired or laid off
(n¼ 26), moving from the area (n¼ 8), and family reasons
(n¼ 7). More uncommon reasons included pregnancy,
having returned to school, having been jailed, and one death.
Five women reported that they quit or lost their job because of
upper extremity problems.
Because recruitment of participants occurred over
23 months with initial participants limited to new hires,
participants had variable tenure in the plant and follow-
up time. New hires had from one to six visits (mean and
median 3) and longer-term workers had between one and four
(mean 3; median 4). A total of 696 interviews and exams were
conducted representing 130,737 person-days or 358 person-
years, of follow-up time. Excluding individuals with dis-
orders at baseline, there were 517 visits representing 107,290
person-days or 301 person-years.
It was not unusual for women to have pain in more than
one area of the upper extremity as well as more than one
disorder at a given follow-up visit. Excluding women with
disorders at baseline, a total of 135 occurrences of upper
extremity musculoskeletal symptoms (defined as symptoms
since last visit on more than three occasions or lasting a week
or more) were reported among 78 different women. Twenty-
four (30.8%) had reported work-related symptoms at base-
line. A total of 74 new upper extremity disorders, based on
defined constellations of symptoms and signs from the
physical exam, were identified among 47 women. These
represent a symptom occurrence rate of 44.8 per 100 person-
years (or 25.9 persons with symptoms per 100 person-years)
and disorder incidence rates of 20.7 per 100 person-years of
follow-up (or 13.1 individuals with new disorders per 100
person-years).
The distribution of symptoms among individuals with-
out disorders at baseline included: hand/wrist (n¼ 106),
forearm (n¼ 5), shoulder (n¼ 40), and neck (n¼ 12). The
types of disorders identified included: painful flexor nodules
(n¼ 4), ulnar nerve compression at the wrist (n¼ 12), wrist
flexor tendonitis (n¼ 12), wrist extensor tendonitis (n¼ 8),
Dequervain’s tenosynovitis (n¼ 7), lateral epicondylitis
(n¼ 2), shoulder capsulitis (n¼ 8), and rotator cuff tendo-
nitis (n¼ 21). Neither symptoms nor disorders were mutually
exclusive, therefore the total is greater than overall
occurrences. While we identified no new cases of CTS, it is
noteworthy that 40 women reported a prior diagnosis of CTS
at their baseline evaluation. At baseline two women were
identified with CTS and four with ulnar nerve compression at
the wrist.
Crude rates of symptoms and disorders increased with
increasing age (Table III). However, the rates among women
over 40 represent less than 10% of the cases among this
young cohort. The report of UE symptoms that interfered
with work speed or quality at baseline was a stronger
predictor than symptoms at the prior visit. Women who
reported significant depressive symptoms at baseline were at
greater risk of musculoskeletal problems. Women with
diabetes had higher rates of disorders, while those who were
currently pregnant, on hormonal therapies (not shown) or
smokers had lower rates of musculoskeletal problems.
Overall risk estimates tended to be stronger for disorders.
Cut-points for the cumulative exposure indices were
made at the quartiles of cumulative exposure of cases which
ranged from 1,432 to 151,300 rank-hours (mean 31,865;
median 9,446) for symptoms and 2,040 to 151,300 rank-
hours (mean 46,168; median 36,225) for disorders. The
cumulative exposure-response patterns were J-shaped with
risk decreasing in the second quartile of cumulative exposure
and then steadily increasing; the effect was stronger for
disorders (Table IV).
A number of baseline work organization factors were
also associated with symptoms and disorders but the
magnitude of the associations varied with the case definition.
Individuals with job rotation were less likely to have
musculoskeletal problems, while women with second jobs
were more likely to have symptoms.
In the multivariate models, the J-shaped exposure-
response patterns remained after adjustment for other risk
factors (Table V). The mean number of disorders identified
per woman at the quartiles of dose followed this same pattern
(1.7 at the 1st quartile, 1.3 at the 2nd and 3rd, and 2.5 at 4th).
Similarly, the proportion of women with more than one
diagnosis at follow-up varied by levels of cumulative
exposure (41.7% at 1st, 16.7% at 2nd, 25% at 3rd, and 82%
at 4th). Age remained an important risk factor for disorders,
but not for symptoms. Age and the cumulative exposure
index were correlated (correlation coefficient¼ 0.57;
P< 0.0001); consequently, our inclusion of age may over-
adjust for our exposure measure. Dropping age from the
model results in a similar exposure-response pattern with
higher estimates for the top two quartiles of exposure (3rd
quartile RR¼ 1.08 (0.45, 2.59); 4th quartile RR¼ 2.77 (1.14,
6.73). Women who reported difficulty maintaining work
speed or quality at baseline had higher rates of symptoms in
follow-up but not of disorders. Being overweight, having
depressive symptoms and job insecurity were associated with
the occurrence of disorders. No differences in risk were ob-
served for being overweight (BMI 25–< 30) or being obese
(BMI> 30), and they were combined in the presentation.
DISCUSSION
In these longitudinal analyses we were interested in the
potentially dynamic nature of musculoskeletal problems
among workers; consequently, we evaluated occurrences of
28 Lipscomb et al.
TABLE
III.
DistributionofFollow
-UpTime,FrequencyofSym
rptomsatFollow
-up,CrudeO
ccurrenceR
ates,and
RateRatiosbyP
ersonalCovariates*
Follow-uptim
ea
Symptom
sat
follow-up
(n¼135cases)
Cruderateb
(95%
CI)
Cruderateratio
(95%
CI)
Follow-uptime
Disordersa
tfollow-up
(n¼47
cases)
Cruderateb
(95%
CI)
Cruderateratio
(95%
CI)
Age <30
94,829
106
1.12(0.90,1.41)
110,020
280.25
(0.16,0.38)
130^<40
9,747
212.27
(1.55,3.34)
1.84(1.16,2.93)
17,270
150.91
(0.55,1.49)
3.73
(1.83,7.63)
40þ
2,714
83.66
(2.45,5.48)
3.86
(1.98,7.51)
3,447
41.15(0.53,2.51)
5.87
(2.58,13.37)
Children
None
20,306
271.42(0.97,2.10)
125,999
130.51
(0.29,0.88)
1Oneortwo
62,501
801.22(0.93,1.60)
0.89
(0.51,1.55)
76,916
210.26
(0.16,0.45)
0.58
(0.25,1.33)
>Two
24,483
281.22(0.80,1.87)
0.92
(0.46,1.82)
25,822
130.48
(0.28,0.82)
1.06(0.47,2.4)
Timelive
withoutwages
1monthþ
12,816
171.33(1.05,1.70)
115,862
50.33
(0.15,0.72)
1<1m
onth
24,949
280.96
(0.62,1.48)
0.70
(0.30,1.61)
30,613
110.32
(0.17,0.63)
0.79
(0.24,2.57)
<1w
eek
69,525
901.35(0.75,2.43)
1.05(0.48,2.29)
82,974
310.38
(0.25,0.56)
1.22(0.46,3.24)
Smokes
No85,354
114
1.30(1.03,1.62)
1102,968
400.38
(0.27,0.54)
1Yes
21,936
211.06(0.69,1.64)
0.78
(0.45,1.34)
26,481
70.27
(0.14,0.55)
0.82
(0.37,1.82)
Weight
Overweight
90,754
121
1.32(1.10,1.62)
119,502
450.41
(0.29,0.59)
1Normal
16,536
140.80
(0.38,1.67)
0.69
(0.30,1.59)
79,551
20.09
(0.03,0.35)
0.14(0.02,0.98)
Diabetes
No102,970
130
1.25(1.02,1.53)
1124,782
440.35
(0.26,0.49)
1Yes
3,758
30.9
9(0.51,1.92)
1.09(0.54,2.21)
4,667
20.43
(0.07,2.6)
1.81(0.30,10.7)
Currentlypregnant
No101,135
131
1.28(1.04,1.56)
1122,621
47Yes
6,155
40.76
(0.33,1.74)
0.78
(0.33,1.86)
6,828
0�
�Depressivesym
ptom
sCES-D
<16
60,846
711.00(0.73,1.37)
170,376
300.24
(0.15,0.39)
116þ
46,444
641.59(1.24,2.04)
1.73(1.09,2.74)
60,361
170.49
(0.33,0.75)
2.08
(1.06,4.09)
Symptom
sinterferedwithwork
No90,122
971.06(0.84,1.34)
195,108
260.27
(0.18,0.40)
1Yes
17,168
382.66
(1.70,4.17)
2.66
(1.70,4.17)
35,629
210.67
(0.41,1.07)
2.47
(1.25,4.89)
Symptom
satpriorvisit
No77,217
691.06(0.84,1.34)
184,801
200.25
(0.16,0.39)
1Yes
30,073
661.66(1.28,2.17)
1.53(0.98,2.41)
45,936
270.56
(0.37,0.85)
2.25
(1.16,4.36)
Homehandactivity
<4hr/week
81,138
102
1.35(0.90,2.01)
198,071
320.33
(0.25,0.47)
14þ
hr/week
26,152
331.23(0.98,1.55)
0.90
(0.51,1.60)
32,666
150.48
(0.26,0.87)
1.53(0.68,3.44)
*Based
onbaselinereports
exceptpregnancyanddiabeteswhichwereallowed
tovaryateachfollow-up.
a Follow-uptim
eforsym
ptom
sexcludedthosewith
anydisordersatbaseline.
b Ratesper1,000
person-daysoffollow-up,cruderatesandrateratioscalculated
wGEE.
29
TABLE
IV.DistributionofFollow
-upTime,FrequencyofSym
ptom
satFollow
-up,CrudeO
ccurrenceR
ates,and
RateRatiosbyW
orkV
ariables*
Follow-uptimea
Symptom
satfollow-up
(n¼135cases)
Cruderateb
(95%
CI)
Cruderateratio
(95%
CI)
Follow-uptim
eDisordersa
tfollow-up
(n¼47
cases)
Cruderateb
(95%
CI)
Cruderateratiob
(95%
CI)
Cumulativeexposureindex
c
Low
31,527
331.08(0.78,1.50)
136,232
120.34
(0.17,0.66)
1Mod-low
28,846
351.01(0.77,1.60)
0.92
(0.57,1.50)
62,976
120.19(0.11,0.32)
0.48
(0.20,1.15)
Mod-high
25,197
331.40(0.97,2.01)
1.28(0.702.33)
22,424
120.54
(0.32,0.92)
1.57(0.64,3.80)
High
21,720
341.55(1.03,2.33)
1.45(0.82,2.57)
9,105
111.23(0.68,2.21)
3.51
(1.38,8.95)
Non-poultry
job
No101,332
127
1.24(1.01,1.53)
1123,023
440.37
(0.27,0.50)
1Yes
5,959
81.25(0.68,2.27)
1.16(0.53,2.53)
7,714
30.35
(0.11,1.2)
0.98
(0.28,3.5)
Jobrotation
Yes
53,810
671.22(0.91,1.62)
161,489
170.4
4(0.30,0.65)
1No
53,480
681.27(0.96,1.68)
0.94
(0.53,2.53)
69,248
300.28
(0.17,0.46)
0.65
(0.34,1.4)
JobContentQuestionnaireScales
Jobstrain
Low
15,611
281.17(0.93,1.47)
1102,328
350.45
(0.22,0.92)
1High
88,682
105
1.65(1.10,2.47)
1.42(0.80,2.5)
18,983
110.33
(0.22,0.48)
1.72(0.83,3.6)
Socialsupport
High
62,430
691.05(0.79,1.39)
167,872
250.35
(0.22,0.55)
1Low
42,010
641.59(1.17,2.03)
1.42(0.90,2.25)
53,439
200.35
(0.22,0.55)
1.0(0.51,2.0)
Isom
etricload
Low
45,956
490.97
(0.69,1.36)
147,051
130.23
(0.10,0.53)
1High
60,794
861.45(1.13,1.85)
1.37(0.86,2.19)
74,260
340.42
(0.29,0.60)
1.78(0.74,4.3)
Jobinsecurity
Low
45,114
521.12(0.81,1.55)
147,963
110.21
(0.09,0.50)
1High
60,361
801.34(1.04,1.72)
1.26(0.79,2.01)
73,348
350.43
(0.31,0.62)
2.04
(0.81,5.17)
Jobdissatisfaction
Low
48,778
561.08(0.78,1.48)
148,848
190.35
(0.21,0.58)
1High
58,512
791.04(0.77,1.41)
1.23(0.78,1.93)
72,463
270.34
(0.21,0.54)
0.98
(0.50,1.92)
Jobhazard
Low
66,135
661.03(0.77,1.37)
170,003
210.31
(0.20,0.52)
1High
40,622
671.61(1.23,2.09)
1.50(0.95,2.36)
51,308
250.38
(0.24,0.61)
1.16(0.59,2.3)
Physicaldemand
Low
15,269
211.24(1.00,1.53)
116,340
30.18(0.04,0.71)
1High
91,640
114
1.30(0.75,2.24)
1.00(0.55,1.83)
104,971
440.37
(0.26,0.53)
2.06
(0.49,8.6)
*Based
onbaselinereports
exceptcumulativeexposurewhich
increasedoverfollow-up.
a Follow-uptim
eforsym
ptom
sexcludedthosewith
anydisordersatbaseline.
b Rates(per100person-daysoffollow-up)andrateratiosareGEEadjusted.
c Cut-pointsatquartilesofexposuredistributionofcases.
30
symptoms and incidence of disorders. In doing so, we
identified differences in the specific factors associated with
these outcomes and the magnitude of risk. In both cases, after
adjusting for other independent risk factors there was a
decline in the rate of events in the second quartile of
cumulative exposure followed by a steady increase with
increasing exposure to poultry processing work. The stronger
exposure-response relationship observed for incidence of
disorders may reflect that we were modeling non-specific
occurrences of symptoms and more precisely defined
incidence of disorders. We believe that the J-shaped response
curves are consistent with the early development of
musculoskeletal problems in this fast-paced upper extremity
intensive work; consequently, some women may leave the
workforce, others may adapt, and some later develop
additional problems with continued exposures. The lower
levels of disease in the second quartile of cumulative
exposure could represent a latency period for later diseases
different from those developed in the early follow-up period.
It is interesting however that we see the same pattern for
symptoms. Considering that we were not studying an
inception cohort, limited to new hires to the industry, and
that our greatest lost to follow-up occurred early in follow-up,
this pattern could also reflect, in part, a healthy worker effect
[Checkoway et al., 2004].
More specifically, these findings add to a body of work
that raises serious concern about the health and safety of
black women employed in this particular poultry processing
plant in rural North Carolina. We have previously described
prevalence of symptoms and disorders very similar to that
found in a HHE conducted by the NIOSH [Kiken et al., 1990]
over 15 years ago [Lipscomb et al., 2007a]. We have also
documented higher prevalence of upper extremity symptoms
[Lipscomb et al., 2007b] and higher prevalence of depression
among the poultry workers than among other women in low-
wage jobs in their same community [Lipscomb et al., 2007c].
In the early planning of this project, women from the
community raised concerns that their work-related problems
were often dismissed by management and medical providers
as being related to child-care responsibilities, mental health
concerns, and other health problems such as obesity. Child-
care responsibilities were not significant predictors of the
onset of disorders or the occurrence of symptoms in our
multivariate analyses. Longitudinally, the incidence of
disorders was associated with being overweight. However,
the BMI risk estimates are imprecise and do not explain the
TABLE V. Adjusted Rate Ratios (PoissonModelsWith GEE) forMusculoskeletal Symptoms andMusculoskeletal Disorders
Occurrence of symptomsadjusted rate ratio (95%CI)
Incidence of disordersadjusted rate ratiob (95%CI)
Cumulative exposure indexa
Low 1 1Mod-low 0.83 (0.55,1.27) 0.34 (0.15, 0.76)Mod-high 1.24 (0.70, 2.19) 0.72 (0.28,1.86)High 1.39 (0.79, 2.42) 1.75 (0.71, 4.28)
Age<30 � 130^<40 2.79 (1.36, 5.73)<40 6.30 (2.54,45.62
BMIOverweight � 1Normal 0.12 (0.02, 0.83)
Job insecurityLow � 1High 1.86 (0.80,4.31)
Depressive symptomsCES-D<16 1 �CESDGE16 1.67 (1.02, 2.61)
Symptoms interferedwith workNo 1Yes 2.50 (1.64, 3.83) �
aCut-points at quartiles of distribution of events.bAlso adjusted for diabetes (lower among diabetics) and children in home. Children was not a significant risk factor but removalchanged exposure estimate>15%.
Musculoskeletal Disorders in Poultry Processing 31
population variability among these women. There was
marked lack of variability in the weight distribution of this
population of women; only 15% were of normal body weight
based on BMI measures. Depression was a risk factor for
symptoms but not onset of disorders. When considering these
other risk factors, cumulative work exposure predicted the
presence of symptoms and disorders at follow-up. Although
the high levels of obesity and depression among these women
are of great concern, they do not explain their musculo-
skeletal problems independent of physical pathology or
increasing work exposure.
Interestingly, even when considering symptoms at
baseline, women with high job insecurity at baseline were
more likely to have a disorder at a follow-up visit. We do not
know the precise mechanism behind this association, but
hypothesize this may reflect that individuals who are insecure
about their job continue working with symptoms—perhaps
without seeking treatment or accommodation and thus may
be more likely to develop disorders. This association is
consistent with qualitative data from women in the
community and our knowledge of participants refusing
medical referrals because of fear for their jobs [Lipscomb
et al., 2007a]. This was the only work organization factor
associated with either symptoms or disorders in multivariate
longitudinal analyses even though a number were crudely
associated.
Limitations and Strengths
We have described several limitations to this work in
previous reports [Lipscomb et al., 2005, 2007a,b,c]. First, we
had no direct exposure measures, but utilized the relative
department rankings that NIOSH investigators assigned in
walk-through assessments of the plant at the time of the HHE
in 1989. We recognize that changes have been made in the
plant processes and work conditions since the NIOSH
evaluation. However, the ranks are consistent with recent
qualitative data from key informant interviews, and we
believe that the relative ranking by department is still
appropriate. This approach likely underestimates the expo-
sures for very long-term workers who were in the plant before
changes were instituted. Because of our lack of direct
exposure measures, we cannot discern what specific aspects,
or combinations, of the physical work contribute to these
problems. Because our analyses were limited by small
numbers, we evaluated all upper extremity symptoms and
disorders together making it more difficult to identify
relationships that are not common to all symptoms and/or
disorders we are studying—and likely muting the effect of
our cumulative exposure measure. We did not evaluate the
effect of temperature on the musculoskeletal problems of
these women. Most were exposed to cold conditions; after the
birds are eviscerated they are chilled, and remain so, as they
are moved through the processing plant.
In estimating cumulative exposure we assigned each
woman reporting fulltime work 2,000 hr of exposure per year,
although women working partial years were proportionately
assigned hours based on the number of months they reported
working, These women have little vacation time (typically
5 days) and do not receive paid sick leave, but they are
eligible for Family Medical Leave Act (FMLA) benefits.
However, we did not ask for a recall of days away from work
each year, for illness, pregnancy, etc. and there may have
been some over-estimation of exposure for some women
because of this. [This over-estimation of exposure is non-
differential with respect to the outcome and is unlikely to bias
our estimates.]
The design we chose, which recruited and followed
employed women in one industry, does not have an
unexposed group. This highly exposed cohort constitutes
neither a full enumeration of potential workers nor a random
sample of the population at risk. The over-recruitment of new
hires to the industry was intentional in the design of the
longitudinal work, and while we do have representation from
a number of departments in the plant, the majority of our
cohort came from areas considered to have high exposure.
While not ruling out selection bias or a healthy worker effect,
these problems are of less concern in a design using internal
comparisons of longitudinal data with reasonable follow-up
over time, such as this one. However, the ratio results should
be viewed with the knowledge of the relatively high exposure
of all workers and the potential over adjustment of
cumulative dose because of its correlation with age.
In addition to the longitudinal design, the work has other
strengths. Although we lacked precise exposure measure-
ments, we were able to estimate a cumulative index of
exposure using work histories that account for time worked in
different departments, qualitative information, and prior
information on relative departmental exposures. We were
able to evaluate contributions of work organization and
psychosocial factors in multivariate analyses with this
cumulative exposure index. Among this highly exposed
population, the effects of depressive symptoms at baseline
and work organization factors were diminished when
cumulative exposure was considered, illustrating the highly
contextual nature of the complex relationships between the
physical work exposures and social factors [Hagberg, 1992].
Because we had physical examination data we were
able to evaluate, not just symptom reports, but also likely
disorders based on clusters of symptoms and findings
recommended for use in epidemiologic studies [Palmer
et al., 2000; Sluiter et al., 2001]. As others have reported
[Miranda et al., 2005], risk differed by outcome definition
demonstrating the utility of differentiating symptoms and
disorders.
Participants were recruited by women in their commun-
ity largely using social networks without consideration
of disease or symptoms. We do not believe that a more
32 Lipscomb et al.
traditional approach involving random selection of workers
through industry cooperation would have been successful
under the circumstances. The community-based approach
allowed the collection of a tremendous amount of informa-
tion from a hard to reach population under circumstances that
made the conduct of the work inherently challenging and all
the more important.
CONCLUSIONS
While these data add to evidence from multiple
investigators that work in poultry processing contributes to
upper extremity musculoskeletal problems, unfortunately,
we are not documenting new problems. Concerns about this
industry have been for decades, and continue to be, the
subject of researchers, journalists, and workers [Armstrong
et al., 1982; Hall, 1989; Anthan, 1991; Yassi et al., 1996;
Campbell, 1999; Nowell, 2000; Quandt et al., 2006]. We
acknowledge that changes have taken place in the plant we
studied since the time of the OSHA citations in 1989. For
example, a number of women reported job rotations.
However, they were often assigned to other high exposure
work areas, which may explain our failure to identify rotation
as a protective factor in our multivariate analyses. Some
processes are now automated that were not at that time of the
OSHA violations. Biomechanical evaluations demonstrate
that mechanical deboning efforts moderately reduce peak
forces, but muscular activity remains high with higher levels
of acceleration and repetition rates [Juul-Kristensen et al.,
2002]. In light of this and the relative paucity of low exposure
work in the industry, it would be prudent to slow the speed of
the lines while working to reduce postural load and force.
This is consistent with the desires of the workforce, and
would help to address some of the negativework organization
issues reported by these women.
In the absence of an enforced ergonomic standard for
this industry in the US, maximal line speeds continue to be set
without regard for worker safety by the Department of
Agriculture, the agency responsible for ensuring food safety.
Since it began setting line speeds in 1968, work pace has
increased from less than 20 birds per minute to the current
maximum of 91 birds per minute [USDA, 2006]. There are
significant challenges to reducing the work exposures of
these women in the present US political climate, focused on
voluntary compliance with occupational safety and health
guidelines.
The citing of poultry processing plants with their
associated work risks, largely in depressed, disadvantaged
areas of the rural southern US, with the employment of large
numbers of workers of color—often African-Americans or
Latinos—illustrates how work can contribute to disparities in
health that might otherwise be attributed to characteristics of
the population. This happens while helping producers keep
their costs low [Griffith, 1993; Nowell, 2000; Fink, 2003].
‘‘The pain and suffering due to work-relatedMSDs. . . are frequently, or perhaps even typically,not captured or recorded by the marketplace.These costs are not reflected in wages or passedon to consumers because poultry oligopoliesbenefit from a seemingly inexhaustible ruralreservoir of atomized unskilled workers with fewalternatives, and are well positioned to extractlabor without having to indemnify their employ-ees for impairments of the value of their laborpower’’ [Linder, 1995, p. 115].
In low-wage, high turnover industries it is difficult to
adequately assess health and safety of the workforce. An
inception cohort is hard, if not impossible, to recruit and
follow, as are random samples of workers. Consideration of
these issues led to our decision to conduct this work outside
of industry. Just as the health effects of precarious work
situations have been the subject of much discussion world-
wide [Quinlan et al., 2001] these women also perceive
precarious employment, which makes research into their
problems more difficult with traditional academically driven
epidemiologic methods. Given the social context, these
findings also illustrate how the health of workers is
influenced not just by their personal characteristics and
direct work exposures, but also by government policy, racial
history, longstanding patterns of exploitation, and economic
opportunity, or lack thereof [Lipscomb et al., 2006].
ACKNOWLEDGMENTS
The questionnaire used to collect musculoskeletal
symptom data was adapted from the questionnaire developed
by the NIOSH Research Program for the prevention of work-
related musculoskeletal disorders. The physical exam
protocol is based in large part on the protocol developed by
Professor Eira Viikari-Juntura for the Washington State Dept
of Labor and Industries SHARP upper extremity muscu-
loskeletal study.
We acknowledge Kristie Wicker for her many efforts
coordinating the project and for her assistance in preparing
the manuscript. We acknowledge the contributions of Steve
Wing and Dana Loomis to the early development of the
project and Robin Argue for project management. We thank
Belinda Lee and Andie Whitehead for their roles performing
the physical exams on study participants; particularly we
acknowledge their flexibility in scheduling that facilitated
participation. Lastly, we acknowledge the essential contri-
butions of the community-based staff including Emma
Pender, Rita Perry, Christal Rankins, and Chaniqua Rodgers
who recruited participants, collected the interview data, and
managed the community project office. Lola Williams is
acknowledged posthumously. She was the inspiration behind
Musculoskeletal Disorders in Poultry Processing 33
this project, seeking academic partners to address issues of
health disparities in her community. Of note, the study
population is referred to as black, as opposed to African-
American, throughout the manuscript based on the prefer-
ence of the community-based staff. The authors have no
competing financial interests.
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APPENDIX
Criteria used for Definitions of UpperExtremity/Neck Disorders
Disorders are based on symptoms in a given body
region. Possible work-related cases must have had onset
after having begun working at the plant, but worker did
not have to attribute onset to the workplace. The individual
must not have reported previous trauma to that body
region.
Symptom and Sign-based Disorders
Hand/wrist disorders
All include:
. Hand/wrist symptoms > 3 times or lasting at least
a week in the last 12 months at baseline or last
6 months at follow-up
Dequervain’s tenosynovitis
Scandinavian definition1
. Pain, radial side of wrist from hand diagram,
AND
. Positive Finkelstein’s (>0), OR
. Pain on resisted thumb extension, OR
. Pain on resisted thumb abduction
Wrist flexor tendonitis [included individuals meeting
either case definition]
Scandinavian definition
. Pain over flexor tendons (ventral aspect of wrist)
from hand diagram, AND
. Pain provocation on resisted wrist flexion, OR
. Crepitus under symptom area, OR
. Visible swelling of affected region
Southhampton definition2
. Pain with wrist flexion, OR
. Pain with resisted wrist flexion, OR
. Pain with resisted flexion 2–5
Wrist extensor tendonitis [included individuals meeting
either case definition]
Scandinavian definition
. Pain over extensor tendons (dorsal aspect of wrist)
from hand diagram, AND
. Pain provocation on resisted wrist extension, OR
. Crepitus under symptom area, OR
. Visible swelling of affected region
South Hampton definition
. Pain with wrist extension, OR
. Pain with resisted wrist extension, OR
. Pain with resisted extension 2–5
Carpal tunnel syndrome
Scandianavian definition
. Paresthesia/pain in median nerve distribution
(classic or probable CTS per Katz) from hand
diagram
. Positive flexion/compression test, OR
. Positive carpal compression test, OR
. Positive tinel’s sign, OR
. Atrophy of abductor pollicis brevis
Ulnar nerve compression at the wrist
. Probable case based on symptoms, AND
. Weakness or atrophy, ulnar innervated hand
intrinsic muscles, OR
. Positive Tinel’s at Guyon canal
Possible osteoarthropathy hand/wrist
. Swollen/deformed joints (note: we do not differ-
entiate swollen and deformed in our exam
reports), AND
1 This definition is based on Sluiter JK, Rest KM, Frings-Dresen MH.2001. Criteria document for evaluating the work-relatedness of upper-extremity musculoskeletal disorders. Scand WorkEnviron Health27(1):1–102.
2 Palmer K, Walker-Bone K, Linaker C, Reading I, Kellingray S,Coggon DD, Cooper C. 2000. The Southampton examinationschedule for the diagnosis of musculoskeletal disorders of the upperlimb. Ann Rheum Dis 59(1):5–11.
Musculoskeletal Disorders in Poultry Processing 35
. Limited ROM, OR
. Pain with ROM, OR
. Triggering
Painful hand flexor nodules
. Based on physical exam finding of painful nodules
Triggering of any finger with or without pain
Elbow/forearm disorders
All include:
. Elbow/forearm symptoms >3 times or lasting at
least a week in the last 12 months at baseline or last
6 months at follow-up
Cubital tunnel syndrome
. Probable case by symptom definition, AND
. Positive combined pressure/flexion of ulnar nerve
proximal to cubital tunnel; positive must include
pain and/or paresthesia in ulnar forearm, ring or
little finger
Epicondylitis, lateral
. Local pain on resisted wrist extension
Epicondylitis, medial
. Local pain on resisted wrist flexion
Shoulder disorders
All include:
. Shoulder symptoms >3 times or lasting at least a
week in the last 12 months at baseline or last
6 months at follow-up
Rotator cuff syndrome [included individuals meeting
either case definition]
Scandinavian definition
. Pain on resisted abduction, OR
. Pain on resisted internal rotation, OR
. Pain with resisted elbow flexion, OR
. Painful arc test on upper arm elevation,
Southhampton also includes, OR
. Pain on external rotation, OR
. Pain on internal rotation
Shoulder capsulitis
. Unilateral limitation of ROM and pain
Neck disorders
All include:
. Neck symptoms >3 times or lasting at least a
week in the last 12 months at baseline or last
6 months at follow-up
Radiating neck syndrome
. Pain in UE with active or passive cervical
rotation
Tension neck syndrome
. Abnormal neck ROM, AND
. Pain on palpation of the trapezius, OR
. Pain in neck/trap with passive rotation, OR
. Other pain w ROM
36 Lipscomb et al.