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Occupational health disparities in the U.S. hotel industry



Background: Hotel employees have relatively higher rates of occupational injury and sustain more severe injuries than most other service workers. Methods: OSHA log incidents from a sample of 50 unionized hotels drawn from 5 hotel companies for a three-year period were analyzed to calculate injury rates by job, company, race/ethnicity and sex, with a focus on room cleaning work. Injuries were classified as musculoskeletal, acute trauma, or other injuries. Denominators were constructed from the hotel workforce rosters. Multivariate Poisson regression models were used to evaluate the independent effects of demographic factors, job title, and company. Results: A total of 2,865 injuries were identified from OSHA logs for those employed during one or more years during 2003-2005, totaling 55,183 person-years of observation. The overall injury rate was 5.2 injuries per 100 worker-years. The rate was highest for Hispanics (6.4/100), housekeepers (7.9/100), female Hispanic housekeepers (10.6/100) and about double in 3 companies versus 2 others (among the four larger companies, the highest rate was 6.9/100). Acute trauma rates were highest in kitchen workers (4.0/100) and housekeepers (3.9/100); housekeepers also had the highest rate of musculoskeletal disorders (3.2/100). Age, female sex, Hispanic ethnicity, job tenure, job title, and company were all independently associated with injury risk. Conclusion: Sex and ethnicity-based disparities in injury rates were only partially explained by the type of job held and the company in which the work was performed.
Occupational Injury Disparities in the
US Hotel Industry
Susan Buchanan, MD,MPH,
*Pamela Vossenas, MPH,
Niklas Krause, MD,PhD,
Joan Moriarty, MS,
Eric Frumin, MA,
Jo Anna M. Shimek, MS,
Franklin Mirer, PhD,CIH,
Peter Orris, MD,MPH,
and Laura Punnett, ScD
Background Hotel employees have higher rates of occupational injury and sustain more
severe injuries than most other service workers.
Method OSHA log incidents from five unionized hotel companies for a three-year period
were analyzed to estimate injury rates by job, company, and demographic characteristics.
Room cleaning work, known to be physically hazardous, was of particular concern.
Results A total of 2,865 injuries were reported during 55,327 worker-years of observa-
tion. The overall injury rate was 5.2 injuries per 100 worker-years. The rate was highest for
housekeepers (7.9), Hispanic housekeepers (10.6), and about double in three companies
versus two others. Acute trauma rates were highest in kitchen workers (4.0/100) and
housekeepers (3.9/100); housekeepers also had the highest rate of musculoskeletal
disorders (3.2/100). Age, being female or Hispanic, job title, and company were all
independently associated with injury risk.
Conclusion Sex- and ethnicity-based disparities in injury rates were only partially due to
the type of job held and the company in which the work was performed. Am. J. Ind. Med.
2009. 2009 Wiley-Liss, Inc.
KEY WORDS: occupational injury; hotel workers; housekeepers; musculoskeletal
disorders; health disparities
Health disparities between the sexes and between racial/
ethnic groups have been documented for a wide spectrum of
diseases [Satcher and Higginbotham, 2008] but research on
disparities in the rates of injuries and diseases occurring in the
workplace is still emerging. Recent studies have shown that
Hispanic workers have the highest rate of fatal and non-fatal
OSHA-reported injuries in the US, followed by black non-
Hispanic workers [Richardson et al., 2003; USBLS, 2007a].
Among agricultural and hospital workers, a disproportionate
burden of occupational injury is carried by women, African
Americans, and Latinos [McGwin et al., 2000; Simpson and
Severson, 2000; McCurdy et al., 2003]. Elevated risks among
these groups are partially explained by disproportionate
employment in high-risk industries and occupations, but
there may also be disparities within the same industry or
job classification, perhaps resulting from sex, racial, or ethnic
discrimination and other factors.
Accepted 22 May2009
DOI10.1002/ajim.20724.Published online in Wiley InterScience
Contract grantsponsor: UNITEHERE.
*Correspondenceto:SusanBuchanan, MD,MPH,835 S.Wolcott,MC-684,Chicago,IL60612.
Division of Environmental and Occupational Health Sciences, University of Illinois at
Chicago S chool of Public Health, Chicago, Illinois
Occupational S afety and Health Program,UNITE HERE,New York,New York
Division of Occupational a nd Environmental Medicine, University of California San Fran-
cisco, San Franciso, Cali fornia
WorkersUnited/SEIU, New York, NewYork
Division of Environmental and Occupational Health Sciences, University of Illinois at
Chicago S chool of Public Health, Chicago, Illinois
Environmental and Occupational Health Sciences, Urban Public Health Program,Hunter
College School of Health Sciences, New York,New York
Departmentof Occupation al and Environmental Medicine,University of Illinois at Chicago
Medical Center,Chi cago, Illinois
Department of Work Environment, University of Massachusetts Lowell, Lowell, Massa-
Workcon ducted while Joan Moriar ty and Eric Frumin were at UNITEHERE.
2009 Wiley-Liss,Inc.
Within the US hospitality industry, hotels, and motels
employ 1.8 million workers [USBLS, 2007b]. In the United
States, hotel workers are nearly 40% more likely to be injured
on the job than all other service sector workers. Hotel
workers also sustain more severe injuries resulting in
more days off work, more job transfers, and more medically
restricted work compared to other employees in the
hospitality industry [USBLS, 2005].
Approximately 25% of hotel workers are employed in
housekeeping departments [USBLS, 2007b]. Housekeepers
constitute the single largest occupational group in the
hotel industry and include room cleaners (maids or room
attendants) and housemen. Many room attendants are immi-
grant or minority women, with a majority being either Asian,
Latin American, or African American [Wial and Rickert,
2002]. Thus, they belong to several groups that have been
repeatedly identified as having excessive occupational
risks: women [Stellman, 1999; NIOSH, 2002; Kauppinen
et al., 2003; Messing, 2004; Treaster and Burr, 2004],
immigrants [Improving Health and Safety Conditions for
Californias Immigrant Workers, 2002], ethnic/racial minori-
ties [Frumkin et al., 1999], and low-wage workers [Frumkin
and Pransky, 1999]. However, very little is known about
occupational injuries among hotel housekeepers; the US
Bureau of Labor Statistics (BLS) does not provide rates of
occupational injury and illness for single occupations. Among
Las Vegas hotel room cleaners, the prevalence of self-reported
pain associated with work was 75% during the previous year
[Scherzer et al., 2005]; 63% had had severe or very severe low
back pain just in the prior month [Krause et al., 2005].
In 1996, the first National Institute for Occupational
Safety and Health (NIOSH) research agenda (NORA)
called for innovative occupational health research to deter-
mine the extent and severity of disease and injury among
special worker populations [NIOSH, 1996]. Ten years later,
the revised NORA research agenda targeted the service
sector, which accounts for 80% of the US workforce.
Hotel workers have been repeatedly identified as an under
-researched population with significant problems such as
musculoskeletal injuries; even less is known about dish-
washers, cooks, and other food service workers.
This study analyzes the rates of OSHA-reported injury
within the hotel industry for four leading hotel job categories
(hotel housekeepers, cooks/kitchen workers, stewards/
dishwashers, and banquet servers), and examines disparities
in injury risk by race/ethnicity and sex.
Study Population
Institutional Review Board approval was obtained from
the University of Illinois at Chicago under the exempt
classification. The study population consisted of non-
supervisory hotel workers employed for a minimum of
2 weeks in at least 1 year during the study period of
20032005, at full-service hotels operated by the five
largest hotel companies in the United States. For this study,
full-service hotels are defined as properties with at least 100
guest rooms and with a minimum of 10,000 square feet of
conference space. These criteria were intended to increase
the likelihood that job classifications and workplace expo-
sures to ergonomic and safety hazards would be similar.
Luxury chains were excluded because the design and pace of
work varies significantly at these properties.
The five companies operate several hotel chains that
together make up over 70% of the full-service hotel rooms
nationwide, with each company establishing its own
standards of service. According to information found on
the companiespublic websites in February 2007, these
companies operate 964 hotel properties in the US that meet
the studys definition of full-service hotels. UNITE HERE,
the largest hospitality workers union in North America,
represents workers at many of these hotels.
Hotel Sampling
Upon request from the union, 71 of the hotels with
collectively bargained contracts provided data, which could
be utilized for this study. The two largest companies repre-
sented an unbalanced proportion of the sample, so a random
number generator [Research Randomizer, 19972008] was
used to select 12 hotels from each of these two. All hotels
from the three other companies were included in the data
analysis. This produced a sample of 50 hotels with sufficient
data from 2003 to 2004 and 45 from 2005 (Table I). Study
hotels were dispersed across the country with concentrations
in large urban areas including New York City, Chicago, San
Francisco, Los Angeles, and Honolulu.
Job Classifications
Job titles are numerous within hotel departments andvary
from employer to employer. The authors in collaboration with
TAB L E I. HotelCompany Distributionsof US Full-Service HotelsandHotelsin
the Study Sample
Full-servicehotels Study sample
No.% No.%
Company1 334 35 12 24
Company 2 95 10 12 24
Company 3 10 1 5 10
Company 4 319 33 9 18
Company 5 206 21 12 24
Totals 964 100 50 100
2 Buchanan et al.
experienced union field staff familiar with the specific job
titles, grouped the jobs that share similar tasks and exposures
to workplace hazards (e.g., dishwasherand pot washer,
housekeeping attendantand room attendant). Five key job
categories were createdhousekeepers, banquet servers,
stewards/dishwashers, cooks/kitchen workers, and other.
Housekeepers perform guest room cleaning including
making beds, vacuuming floors, cleaning shower walls and
bathroom fixtures, dusting furniture, and pushing carts.
Banquet servers provide food service such as carrying plated
food from the kitchens to the customers, dispensing drinks,
and supplying food to cafeteria and buffet services. Stewards
retrieve, sort, load/lift, unload, and return dishes, glasses,
pots, utensils and silverware, and provide these items by
pushing carts to cafeteria and buffet lines. In addition,
stewards maintain cleanliness in food preparation areas.
Cooks lift, weigh, measure, mix, cut and grind food ingre-
dients; they cook these ingredients and compose salads and
other food for serving [USBLS Occupational Outlook Hand-
book, 20082009]. All remaining jobs were categorized as
other.Jobs classified as otherwere those that did not
share similar job tasks or exposures with the other four key
job categories. These included lobby attendant, cashier, door
person, host/hostess, among others.
Database Creation
Employee rosters and OSHA 300 log data were provided
to the union by the five hotel companies for the period
20032005. The employee rosters provided employee name,
department, job title, date of birth, date of hire, termination
date, sex, and race/ethnicity. Race/ethnicity was defined by
the employer based on employee self-report as one of
the following five mutually exclusive categories: American
Indian, Asian, Black, Hispanic, and White.
The OSHA 300 logs included employee name, depart-
ment name or location where injury event occurred, job title,
date of injury, injury description, days away from work, and
days on restricted duty. These data were matched to the
employee rosters using employee name and date of birth. The
final dataset included a single record for each employee. Up
to three injury or illness incidents during the 3-year study
period were abstracted for each individual. Employee names
were removed from all datasets before data analysis began. A
record number was assigned to each injury incident and was
subsequently used in all data analyses.
Injury Coding
Nature of injury data was constructed from the injury
description section of OSHA log entries and were grouped by
the authors into four categories: musculoskeletal disorders
(MSDs), acute trauma injuries, other, and not classifiable.
MSDs were coded according to the US BLS definition: an
injury or disorder of the muscles, nerves, tendons, joints,
cartilage, or spinal discs. MSDs do not include disorders
caused by slips, trips, falls, motor vehicle accidents, or
similar accidents[USBLS, 2007c]. Back pain or pain at
other body locations and strain or sprain injuries were coded
as MSDs unless the entry referenced stairs or ladders, or the
employer-reported description of the injury referenced a slip
or fall. Acute traumacases included contusions, fractures,
lacerations, heat burns, and sprain or strain injuries with
evidence of an injury mechanism that involves acute contact
with outside objects (e.g., hit by, struck against) that were not
otherwise categorized as an MSD. Otherincidents includ-
ed chemical exposures, foreign bodies in the eye, and all
other cases. Not classifiableinjuries had insufficient infor-
mation to determine the nature of injury.
Statistical Analysis
All data were analyzed using SAS (SAS v. 9.1, 2007.
SAS Institute, Cary, NC) and Excel (Microsoft Office 2003,
Seattle, Washington). Injury rates and risk ratios were calcu-
lated to compare the injury experience of hotel workers by
sex, race/ethnicity, and job title for the entire study popula-
tion and by company. The denominator for all calculations
was calculated from the number of workers who met the
inclusion criterion of employment for a minimum of 2 weeks
during each year of study. As individual employees may be
counted in more than one study year, the denominators
represent total worker-years of observation. The available
data did not provide information on part-time/full-time
status. The race and ethnicity characterization was left blank
on the employee rosters for <1% of the sample. Therefore,
this race/ethnicity not classifiedgroup was excluded from
all data analyses.
Age was computed by subtracting birth date from the last
day of the year being analyzed (e.g., in 2003, Age ¼12/31/
2003 birth date) divided by 365.25. Only employees aged
1870 years were included in the analysis. A job tenure
variable was similarly created by subtracting termination
date from hiring date.
Risk ratios were calculated using the following referent
groups: males, whites, and otherjob title. For analyses by
hotel company, Company 1 was chosen as the referent group
on the basis of the level of union presence at its hotels,
thereby a measure of labor and managements negotiation of
working conditions.
Because we had injury count data and repeated measures
(multiple years per subject), we performed multivariable
Poisson regression modeling (Loomis et al. 2005) with
generalized estimating equations (GEE) using SAS Proc
Genmod with a Poisson distribution, unstructured correla-
tions and log link to estimate relative risk. Regression
models included age (1827 years, 2837 years, 4857 years,
5870 years), sex, race/ethnicity, job title, job tenure (010
Occupational Injury in Hotel Workers 3
years, 1120 years, 2130 years, 3140 years, 4152 years),
and hotel company as independent variables. In addition,
cross tabulation and regression modeling were perform-
ed within the subset of female housekeepers. Similar
analyses were not conducted within other subsets of other
job classifications; female housekeepers were a particularly
large subset.
There were a total of 55,327 worker-years of observation
in the sample. Fifty-six percent of the sample was male and
44% female (Table II). By job title, 21% of the employees
were housekeepers, 11% were banquet servers, 6% were
stewards/dishwashers, 8% were cooks/kitchen workers, and
54% had other jobs. Most of the workers were non-white
(Black, Asian, Hispanic), comprising 80% of the sample.
American Indians and male housekeepers were very few in
number. Hispanics comprised the largest proportion of three
job titles: housekeepers, stewards, and cooks. The mean age
of the study population was 44.5 years (SD 13.5). The mean
job tenure was 9.61 years (SD 8.8).
There were 2,865 injuries recorded on the OSHA
300 logs in 20032005 (Table III), for an injury rate of
5.2 injuries per 100 worker-years. Acute trauma accounted
for 52% of the injuries, 39% were musculoskeletal injuries,
and 9% were otheror not classifiable.Women workers
had a higher overall injury rate (6.3) than men (4.3).
Housekeepers had the highest overall injury rate and the
highest rate of MSDs, at 7.9 and 3.2 per 100 workers,
respectively. Acute trauma rates were highest in cooks/
kitchen workers and housekeepers. Banquet servers had the
lowest injury rates. Excluding the six injuries among
American Indians, among housekeepers (Table IV), Hispanic
workers had the highest overall injury rate at 10.6, the highest
rate of MSDs (4.4), and the highest rate of acute traumas
(4.9). Among cooks (not shown), Asians had the highest rate:
8.4% for all injuries, with 7.9% among males and 10.1%
among females.
In each job title of interest (housekeepers, etc.), injuries
of the upper extremity were the most common, followed by
back injuries and lower extremity injuries. By nature of
injury, over 40% of MSDs involved the back, 22% distal
upper extremities, and 13% the shoulder. In contrast, 44% of
acute traumatic incidents were to the upper extremity,
especially the hand.
Women workers overall and Asian and Hispanic men
were about 1.5 times more likely to have been injured than
their referent groups (Table V). Female American Indians
fared the worst, although the number of injuries were so few
that the confidence intervals are relatively wide. Hispanic
women had almost double the risk of injury than their white
female counterparts. Within job categories, non-white
female cooks/kitchen workers fared poorly compared to their
white counterparts as did non-white male banquet servers.
Female housekeepers had about three times the risk of injury
than male housekeepers, and Hispanic housekeepers were
70% more likely to be injured than white female
When analyzed by hotel company, the overall injury
rates differed markedly by company, with companies 2, 3,
and 4 in particular having almost twice the rate of Company
1 (Table VI). Company 2 had the highest rate of injury for
housekeepers (10.4). This overall effect was consistent in
analysis by injury type, with the lowest rates for both MSDs
and acute trauma injuries in Company 1. These same patterns
by company were also evident for key demographic groups
within the four key jobs. Of the 15 job/race/sex groups with
sufficient cases for comparison, Companies 2 and 3 had the
highest injury rates for five of them and Company 4 had
almost as many. Company 1 had only one such group, and
Company 5 had none.
TAB L E I I. Demographic Breakdown of Hotel Workers* Employed 20032005 in 50 Unionized Full-Service Hotels(n ¼55,327)
Total Housekeeper Banquetserver Steward/dishwasher Cook/kitchenworker Other jobs
Male 31,135 56.4 269 2.3 3,406 66.8 2,948 85.1 3,269 72.0 20,280 69.2
Female 24,048 43.6 11,320 97.7 1,693 33.2 518 14.9 1,271 28.0 9,008 30.8
White 11,187 20.3 982 8.4 2,137 36.8 286 8.1 882 19.3 6,898 23.3
Asian 13,352 24.2 3,109 26.7 909 15.6 594 16.9 1,202 26.3 7,538 25.4
Black 12,252 22.2 3,439 29.5 712 12.3 962 27.3 872 19.0 6,267 21.1
Hispanic 18,392 33.3 4,118 35.3 2,047 35.3 1,678 47.7 1,622 35.4 8,927 30.1
14 4 <112<132<17<110<183<1
Total (%)
55,327 100.0 11,660 21.1 5,837 10.5 3,527 6.4 4,588 8.3 29,713 53.7
Total person-years observed, not total employees.
Total excludes race not specified(<1%of total).
4 Buchanan et al.
The regression analyses of all hotel workers (Table VII)
confirmed the higher injury risk for housekeepers and His-
panic workers, and the lower risk in Company 1, after
adjusting for demographic characteristics. Comparison of
univariable and multivariable models showed that some of
the apparent excess risk in Black, Hispanic, and Asian
workers was reduced after adjustment for job title and hotel
company. This was consistent with the fact that Blacks
were most likely (30%), and Whites least likely (8%), to be
employed as housekeepers rather than in other jobs, and that
Company 1 had fewer Black and Asian employees. Job
tenure had a slight inverted-U effect (risk was highest for
2130 years of seniority and then decreased) but it was
dropped from the multivariable models because the coeffi-
cient was very small, the confidence intervals wide, and the
type 3 (GEE) score statistics indicated that the variable did
not contribute any explanatory power. Among female house-
keepers, the predictors of injury were quite similar to those
for all hotel workers, with increased risk for being Hispanic
or employment at Companies 2, 3, and 4.
Several studies have shown that cleaning tasks in various
industries demand a high level of physical effort, including
high aerobic strain and repetitive movements [Hagner and
Hagberg, 1989]; high static muscular loads [Milburn and
Barrett, 1999]; high frequency of unsatisfactory postures
such as stooping and crouching [Woods et al., 1999]; and
subjective experience of strenuous work [Sogaard et al.,
1996; Seifert and Messing, 2006]. In hotel workers specifi-
cally, guest room cleaning work is marked by time pressure,
low job control, low wages, increasing use of contingent
employees without job security, and few opportunities for
career advancement [Parker, 1999; Lee and Krause, 2002;
Wial and Rickert, 2002; Bernhardt et al., 2003; Krause et al.,
2005]. The present study is one of the first to quantify the
incidence, rates, and risk of injury among hotel workers.
We found that women were more often injured than men
and that housekeepers in general suffered the highest injury
rate among the four job titles of interest. Moreover, our
results show an alarming injury rate among housekeepers
in general and Hispanic housekeepers in particular. While
close to half of the total workers here are women, they were
heavily grouped in the housekeeping category, a set of jobs
with very high physical demands. This study strengthens the
evidence that job gender stereotyping within the American
economy remains a potent defining factor for the workforce
and potentially a substantial risk factor for injury [Mergler,
1995; Messing et al., 1998, 2003; Punnett and Herbert, 2000].
Socioeconomic status (SES) in general, and income
inequality, education, and job-specific occupational hazards
in particular, have all been proposed as possible explanations
for racial/ethnic as well as gender health disparities. There is
TABLE III. Injury Incidencean d Rates*for the Hotel Worker Study Population,by Sex and JobTitle, 20032005
Total Male Fema le Hou sekee per Banqu et ser ver Ste ward/dis hwasher Cook /kitche n worker Oth er jobs
Inj no. R ate Inj no. Rate In j no. Rate Inj no . Rate Inj no. Rat e Inj no. Rate Inj n o. Rate Inj no. Rat e
MSDs 1,117 2.02 525 1.68 592 2.46 368 3.16 63 1.08 70 1.99 80 1.74 536 1.82
1,497 2.71 709 2.28 788 3.28 456 3.91 94 1.62 116 3.30 182 3.98 649 2.19
Otherinjuries 251 0.45 110 0.35 141 0.59 93 0.80 7 0.12 24 0.68 12 0.26 115 3.88
Total injuries 2,865 5.19 1,344 4.32 1,521 6.32 917 7.87 164 2.82 210 5.97 274 5.99 1,300 4.92
Injury rate is number of cases per 100 person-years.
Injuries that were not classifiablewere collapsed into otherjobs.
Occupational Injury in Hotel Workers 5
consistent epidemiologic evidence that low status jobs
are associated with a high burden of disease, injury, and
disability [Robinson, 1989; Krause et al., 1997, 2001; Amick
et al., 1998; Borg and Kristensen, 2000; Pransky et al., 2000;
Berkman and Kawachi, 2002; dErrico et al., 2007]. This
burden falls disproportionately on workers who are multiply
disadvantaged in society and who have been under-repre-
sented and under-served in occupational health research.
Female immigrant cleaners are a typical example of a
minority population at the low end of the well-established
SES gradient.
As yet, there has been no evaluation of the causes of
differential injury rates by race/ethnicity within job title in
this industry. One must question whether discrimination in
the treatment of such workersin the form of dispropor-
tionate assignment to high-risk jobs, refusal to fix unsafe
conditions, or workersdisempowermentresulting in
unwillingness to speak up about such conditions, is at fault.
As Murray [2003] noted, previous studies have observed
informal systems of work assignments to non-white workers
resulting in greater exposures to the hazards therein. More-
over, US BLS has already found that disproportionate em-
ployment of Hispanics in specific jobs is not associated with
increased risk of injury after controlling for such employ-
ment patterns [Richardson et al., 2003]. In essence, race/
ethnicity itself is not an indicator of increased risk.
The injury rate for the workers in this sample was
5.19 per 100 workers. For 2004, the US BLS reported a rate
of 5.8 per 100 FTEs in hotel workers and 4.2 per 100 FTEs in
the service sector overall. The lower overall injury rate
reported in our sample may be due to the inability to identify
the proportion of part time workers in this sample or that
unionized employees work under conditions defined by
collective bargaining agreements, which are intended to
improve workplace safety. The study sample included only
unionized workers, whereas the majority of US hotel
employees do not belong to unions. Since unions function
as the bargaining agent between the employer and the
employee, it is likely that non-unionized hotels, in which
workers do not have a formal means to gain better working
conditions, would have even higher injury rates than those
reported in this study. Further, it is possible that hotels not
providing data were those at which workplace safety is less of
a priority and which have higher injury rates than those
reported here.
These results also need to be seen in the context of the
tendency of many workers not to report their injuries, espe-
cially if they are non-unionized, immigrants, or otherwise
politically vulnerable [Azaroff et al., 2002, 2004; Brown
et al., 2002; Scherzer et al., 2005]. Non-reporting of injuries
may be due to language barriers, fear of retaliation, or lack of
understanding of legal rights under Workers Compensation
laws and OSHA standards. Although our data represent
unionized workers who reported their injuries, the results
may still represent an under-estimation of the true injury risk.
Other possible limitations to this study include quality
of the data, coding, and job grouping errors. Injury data
obtained from OSHA 300 logs may have contained inaccu-
racies. The individual responsible for completing these logs
varies by workplace and is not always well trained in
correct recording procedures. There may well be systematic
differential approaches to OSHA 300 log completion by
different hotel companies. Nevertheless, we saw no evidence
of frequent recording errors or systemic bias in recording
through regular quality control checks as well as consulta-
tions with experts on the coding and grouping criteria.
Although the high rate of acute injuries in housekeepers
may suggest coding errors, the OSHA logs frequently
included event/exposure data such as contact with
furniture, tripping over sheets, slips in bathtubs, etc. Further-
more, coding error is possible since some acute injuries in
housekeeping may have been MSDs. However, the patterns
of injury we found are also seen in US BLS data.
The hotels in this study sample were included based on
number of rooms and size of meeting space in order to ensure
similarity in job task burden among workers in the sample.
Working conditions in full-service hotels are determined and
standardized in major part by corporate-level policies such as
TAB L E I V. Injury Incidence and Rates* for Housekeepers by Race/Ethnicit y, 20032005
All injuries MSDs Acute trauma Other/not classifiable
Inj no. Rate Inj no. Rate Inj no. Rate Inj no. Rate
Asian 228 7.33 102 3.28 106 3.41 20 0.64
Black 189 5.50 58 1.69 113 3.29 18 0.52
Hispanic 435 10.56 183 4.44 203 4.93 49 1.19
White 62 6.31 24 2.44 32 3.26 6 0.61
American Indian 6 50.00 1 8.33 5 41.67 None
920 7.89 368 3.16 459 3.94 93 0.80
Injury rate is number of cases per100 person-years.
Total excludes race not specified(<1%of total).
6 Buchanan et al.
TAB L E V I. Injury Incidence Rate*, and Rate Ratio for the Hotel Worker Study Population,by JobTitle and Hotel Company, 20032005
Job titles
Company 2 Company 3 Company 4 Company 5
# Inj Rate # Inj Rate RR (95 % CI) # Inj Rat e RR (95% CI) # Inj Rate RR (95% CI ) # Inj Rate RR (95 % CI)
Housekeeper 211 5.47 276 10.36 1.93 (1.592.34) 86 9.67 1.78 (1. 372.32) 211 9.44 1.74 (1.412.13) 135 6.18 1.13 (0.89 1.43)
Banquet Server 5 n.a. 56 3.69 n.a. 14 3.97 n.a. 69 4.33 n.a. 20 4.25 n.a.
51 4.63 60 7.15 1.55 (1.042 . 31 ) 3 2 11.19 2.48 (1.48 4.14) 4 5 9.15 1.99 (1.293.08) 22 2 .60 0.56 (0.34.93)
47 3.90 88 7.48 1.94 (1.35 2.79) 26 12.32 3.29 (2.015.40) 59 6.54 1.68 (1.15 2.46) 56 4.94 1.27 (0.861.8 9 )
Other workers 258 2.72 317 5.72 2.10 (1.772.50) 140 6.23 2.31 (1.8 4 2.89) 354 5.54 2.04 (1.722.42) 232 3.72 1.3 7 (1.131.6 5 )
All jobs 572 3.26 797 6.79 2.10(1.872.36) 298 7.48 2.33 (1.992.72) 738 6.36 1.95 (1.742.20) 465 4.28 1.31(1. 15 1.49)
n.a., insufficient data.
Injury rate is the number of injuries per100 person-years.
Company 1is the referent group for all other companies.
Statistically significant results are shown in bold.
TAB L E V. Injury Rate Ratios* for the Hotel Worker StudyPopulation by JobTitle, Sex, and Race/Ethnicit y, 20032005
Males Females
All females American Indian Asian Black Hispanic American Indian Asian Black Hispanic
Job t itle RR(9 5% CI) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI)
All hotel workers 1.46 (1.351. 57 ) 0 .4 1 (0 .0 6 2.87) 1.52 (1.281.8 2) 1.07 (0. 871.3 2 ) 1.54 (1.301. 8 2 ) 2.19 (1.084.46) 1.39 (1.151.6 7 ) 1. 14 ( 0 . 9 4 1.3 8 ) 1.91 (1. 6 2.27)
Housekeepers 3.19 (1.536.64) n.a. n.a. n.a. n.a. 4.00 (1.659.67) 1.19 ( 0.871.62) 0.87 (0.631.2 0 ) 1.70 (1.262.29)
Banquet servers 1.38 (1.001.89) n.a. 1.65 (n.a.) 1.87 (n.a.) 2.02 (n.a.) n.a. 0.66 (n.a.) 1.20 (n.a.) 1.14(n.a.)
1. 4 2 ( 1. 0 0 1.97) n.a. 1.29 (n.a.) 1.46 (n.a.) 1.78 (n.a.) n.a. n.a. 0.42(n.a.) 0.45 (n.a.)
Cook/kitchen worker 1. 34 (1.0 41.72) n.a. 1.42 (n.a.) 0.51(n.a.) 0.89 (n.a.) n.a. 2.77 (n.a.) 2.20 (n.a.) 1.94 (n.a.)
Other workers 1.05 (0.931.19 ) 0. 7 5 ( 0 .11 5.21) 1.39 (1.121. 7 3 ) 0. 9 5 ( 0 . 7 4 1.2 2 ) 1.48 (1.211. 8 1 ) 1. 8 8 ( 0 . 7 0 5.09) 1.11 (0.821.5 0 ) 1. 0 0 ( 0 . 7 3 1.3 7 ) 1. 44 (1.081. 9 3 )
n.a., insufficient data.
Referent groups:Males are referent group for females; white males are referent groupfor American Indian, Asian, Black, and Hispanic males; white females are the referent groupfor American Indian, Asian, Black, and Hispanic females.
Statistically significant results are shown in bold.
job task lists and the use of branded products such as luxury
beds. Hotels with fewer than 100 rooms would be less likely
to have standardized room quotas, which might affect work-
load pressure and therefore injury risk among housekeepers.
Thus, we believe that the inter- and intra-hotel variations in
work tasks among job title groups are likely to be minimal in
our sample of properties.
There were substantial and consistent differences in
injury rates among the five companies. These differences
persisted for all injuries, for injuries by job title, and by
demographic groups. As this study sought to standardize job
tasks between companies, this differential suggests the
influence of management policies and practices, meaning
that workplace intervention has a significant ability to modify
the risks identified in this study. These marked differences
between companies demonstrate the potential for sharp
improvement by individual companies in injury rates. They
also underscore the need for companies with high rates to
investigate whether discriminatory workplace practices
contribute to these disparitiesin order to remedy the dis-
crimination and reduce the injury risk accordingly.
Injury rates for hotel workers are higher than those in the
service sector as a whole. Characteristics that increased the
injury risk among the workers in our study included female
sex, Hispanic ethnicity, housekeeper job title, and hotel
company. Hispanic banquet servers had the highest risk
amongst men, and American Indian housekeepers had the
highest risk among women. Hispanic female housekeepers
suffered more injuries than other female room cleaners.
Immediate action is needed with respect to the control of
hazards to housekeepers, especially those stressing the upper
extremities, and to food service workers with respect to
acute trauma. The ethnic, gender, and employer differentials
deserve further exploration to adequately understand the
interaction of social forces with ergonomic and safety
hazards in the workplace. Large differences of injury rates
between employers indicate a substantial potential for injury
prevention in the hotel sector.
Financial support for the data analysis was provided by
UNITE HERE. The following individuals contributed to this
study: Christopher E. Mason, PhD, employee hiring list data
preparation; Emily Perry, BA, research on full service hotel
sector; and John M. Halpin, MD, MPH, housekeeper injury
analysis of earlier version of dataset. We are grateful to
Rebecca Gore, PhD for statistical advice.
TAB L E V I I. Regression Modelsof Injuries Per Year* to US Unionized Hotel workers, 20032005: RiskRatios and 95% Confidence Intervals
(all ho tel wor kers)
Multivariable model
(all ho tel wor kers)
Multivariable model
(all ho tel wor kers)
Multivariable model
(female housekeepers)
Odds ratio 95% CI Odds ratio 95% CI Odds ratio 95% CI Odds ratio 95% CI
Age 1.07 1.041.0 9 1. 0 8 1. 0 51. 11 1. 0 9 1. 0 6 1.12 1. 10 1.0 3 1.18
Job tenure 1.08 1.041. 12
Female 1.46 1.351. 5 8 1. 2 4 1.12 1. 3 7 1. 2 1 1. 0 9 1.3 4
American Indian 1.35 0.672.72 1.33 0.682 . 61 1.15 0 .6 0 2.22 2.54 1.056.13
Asian 1.46 1.291.6 7 1. 2 5 1. 10 1.4 2 1. 11 0 . 9 7 1.26 0.97 0.711. 3 3
Black 1.15 1.001.32 0.97 0.841.11 0.85 0.740.98 0.75 0.541. 0 3
Hispanic 1.70 1.501.9 2 1. 5 0 1. 3 3 1. 7 0 1. 4 2 1. 2 6 1.6 1 1. 5 0 1.11 2.02
Housekeeper 1.80 1.651. 97 1. 5 0 1. 3 4 1.6 8 1. 5 2 1. 3 6 1.7 0
Banquet server 0.64 0.540.77 0.60 0.500.72 0.56 0.470.67
1. 3 7 1.1 7 1.6 1 1. 3 0 1. 11 1. 5 3 1. 3 1 1. 12 1.5 4
1. 3 8 1. 2 0 1. 5 8 1. 3 4 1. 17 1. 5 4 1. 3 1 1.15 1. 51
Company 2 2.10 1.872.36 2.17 1.942.44 1.94 1.592.35
Company 3 2.33 1.992.72 2.41 2.072.81 1.84 1.412.39
Company 4 1.95 1.742.20 2.06 1.832.32 1.74 1.412.14
Company 5 1.31 1.151. 50 1. 3 7 1. 2 0 1.5 6 1. 19 0 .9 4 1. 5 0
Male is the referent groupfor female; White is the referentgroup for Black, Hispanic, Asian, and American Indian; Other jobsis the referent groupfor housekeeper, banquet server,
steward, and cook/kitchen worker; Company 1 is the referent group.
Up to three injuries per year per employee; denominators ¼55,311person-years of observation for all hotel workers an d 11,375 person-years for female housekeepers.
8 Buchanan et al.
Amick BC III, Kawachi I, Coakley EH, Lerner D, Levine S, Colditz GA.
1998. Relationship of job strain and iso-strain to health status in a cohort
of women in the United States. Scand J Work Environ Health 24(1):
Azaroff L, Levenstein C, Wegman DH. 2002. Occupational injury and
illness surveillance: Conceptual filters explain underreporting. Am
J Public Health 92:14211429.
Azaroff LS, Lax MB, Levenstein C, Wegman DH. 2004. Wounding
the messenger: The new economy makes occupational health
indicators too good to be true. Int J Health Serv 2004. 34:271
Berkman SF, Kawachi I. editors. 2002. Social epidemiology.New York:
Oxford University Press.
Bernhardt A, Dresser L, Hatton E. 2003. The coffee pot wars: Unions
and firm restructuring in the hotel industry. In: Appelbaum E, Bernhardt
A, Murnane RJ, editors. Low-wage America: How employers are
reshaping opportunity in the workplace. New York: Russell Sage
Foundation, p 3376.
Borg V, Kristensen TS. 2000. Social class and self-rated health: Can the
gradient be explained by differences in life style or work environment?
Soc Sci Med 51(7):10191030.
Brown MP, Domenzain A, Villoria-Siegert N. 2002. Californias im-
migrant workers speak up about health and safety in the workplace. Los
Angeles, California: University of California Los Angeles Labor
Occupational Safety and Health Program Health and Safety Policy
dErrico A, Punnett L, Cifuentes M, Boyer J, Tessler J, Gore R, Scollin P,
Slatin C. 2007. Hospital injury rates in relation to socioeconomic status
and working conditions. Occup Environ Med 64(5):325333.
Frumkin H, Pransky G. 1999. Special populations in occupational
health. Occup Med 14(3):479484.
Frumkin H, Walker ED, Friedman-Jimenez G. 1999. Minority workers
and communities. Occup Med 14(3):495517.
Hagner IM, Hagberg M. 1989. Evaluation of two floor-mopping work
methods by measurement of load. Ergonomics 32(4):401408.
Improving Health and Safety Conditions for Californias Immigrant
Workers. Report and Recommendations of the California Working
Immigrant Safety and Health Coalition. November 2002. Berkeley,
Kauppinen K, Kumpulainen R, Copsey S. 2003. Gender issues in safety
and health at workA review. Finland: European Agency for Safety
and Health at Work.
Krause N, Lynch J, Kaplan GA, Cohen RD, Goldberg DE, Salonen JT.
1997. Predictors of disability retirement. Scand J Work Environ Health
Krause N, Frank JW, Dasinger LK, Sullivan TJ, Sinclair SJ. 2001.
Determinants of duration of disability and return-to-work after work-
related injury and illness: Challenges for future research. Am J Ind Med
Krause N, Scherzer T, Rugulies R. 2005. Physical workload, work
intensification, and prevalence of pain in low wage workers: Results
from a participatory research project with hotel room cleaners in Las
Vegas. Am J Ind Med 48:326337.
Lee PT,Krause N. 2002. The impact of a worker health study on working
conditions. J Public Health Policy 23(3):268285.
Loomis D, Richardson DB, Elliott L. 2005. Poisson regression analysis
of ungrouped data. Occup Environ Med 62:325329.
McCurdy SA, Samuels SJ, Carroll DJ, Beaumont JJ, Morrin LA. 2003.
Agricultural injury in California migrant Hispanic farm workers. Am
J Ind Med 44(3):225235.
McGwin G, Jr., Enochs R, Roseman JM. 2000. Increased risk of
agricultural injury among African-American farm workers from Ala-
bama and Mississippi. Am J Epidemiol 152(7):640650.
Mergler D. 1995. Adjusting for gender differences in occupational
health studies. In: Messing K, Neis B, Dumais L, editors. Invisible:
Issues in womens occupational health/La sant
e des travailleuses.
Charlottetown, P.E.I., Canada: Gynergy Books. p 236251.
Messing K. 2004. Physical exposures in work commonly done by
women. Can J Appl Physiol 29(5):639656.
Messing K, Tissot F, Saurel-Cubizolles M, Kaminski M, Bourgine M.
1998. Sex as a variable can be a surrogate for some working conditions.
J Occup Environ Med 40:250260.
Messing K, Punnett L, Bond MA, Alexanderson K, Pyle JL, Stock SR,
Wegman DH, Zahm S, Stock SR, de Grosbois S. 2003. Be the fairest of
them all: Challenges and recommendations for the treatment of gender
in occupational health research. Am J Ind Med 43:618629.
Milburn PD, Barrett RS. 1999. Lumbosacral loads in bedmaking. Appl
Ergon 30(3):263273.
Murray LR. 2003. Sick and tired of being sick and tired: Scientific
evidence, methods, and research implications for racial and ethnic
disparities in occupational health. Am J Public Health 93:221226.
National Institute for Occupational Safety and Health. 1996. National
Occupational Research Agenda: Special Populations at Risk. Cincin-
nati, OH: DHHS (NIOSH) Publication No. 96-115.
National Institute for Occupational Safety and Health. 2002. The
changing organization of work and the safety and health of working
people. Cincinnati, OH: DHHS (NIOSH) Publication No. 2002-
Parker E. 1999. Job quality in the hospitality industry: Findings from the
San Francisco housekeeping study. Report to the Rockefeller
Foundation. University of Wisconsin-Madison and University of
California-Berkeley: Madison, Wisconsin, and Berkeley, California.
p 23.
Pransky G, Benjamin K, Hill-Fotouhi C, Fletcher KE, Himmelstein J,
Karz J. 2000. Work-related outcomes in occupational low back pain: A
multidimensional analysis. Am J Ind Med 37(4):400409.
Punnett L, Herbert R. 2000. Work-related musculoskeletal disorders: Is
there a gender differential, and if so, what does it mean? In: Goldman
MB, Hatch MC, editors. Women and health. San Diego, CA: Academic
Press. p 474492.
Research Randomizer. Social Psychology Network. Copyright
Ó19972008 by Geoffrey C. Urbaniak and Scott Plous. http:// Accessed April 10, 2007.
Richardson S, Ruser J, Suarez P. 2003. Hispanic workers in the United
States: An analysis of employment distributions, fatal occupational
injuries, and non-fatal occupational injuries and illnesses in Safety is
Seguridad. National Research Council of the National Academies,
Washington, DC.
Robinson JC. 1989. Exposure to occupational hazards among Hispa-
nics, blacks and non-Hispanic whites in California. Am J Public Health
Satcher D, Higginbotham EJ. 2008. The public health approach to
eliminating disparities in health. Am J Public Health 98(9 Suppl):
Scherzer T, Rugulies R, Krause N. 2005. Work-related pain, injury, and
barriers to workerscompensation among Las Vegas hotel room clea-
ners. Am J Public Health 95(3):478488.
Occupational Injury in Hotel Workers 9
Seifert AM, Messing K. 2006. Cleaning up after globalization: An
ergonomic analysis of work activity of hotel cleaners. Antipode
Simpson CL, Severson RK. 2000. Risk of injury in African American
hospital workers. J Occup Environ Med 42(10):10351040.
Sogaard K, Fallentin N, Nielsen J. 1996. Work load during floor
cleaning. The effect of cleaning methods and work technique. Eur
J Appl Physiol Occup Physiol 73(12):7381.
Stellman JM. 1999. Women workers: The social construction of a
special population. Occup Med 14(3):559580.
Treaster DE, Burr D. 2004. Gender differences in prevalence of
upper extremity musculoskeletal disorders. Ergonomics 47(5):495
Wial H, Rickert J. 2002. U.S. Hotels and their workers: Room for
improvement, in the state of U.S. Industries. AFL-CIO Working for
America Institute.
Woods V, Buckle P, Haisman M. 1999. Musculoskeletal Health of
Cleaners. Robens Centre for Health Ergonomics, European
Institute for Health and Medical Sciences, University of Surrey, Eng-
land: p 112.
10 Buchanan et al.
... While the occupational experiences of cleaners exists in literature, the experience of temporary women factory workers engaged in informal work is largely unknown. Occupational health studies conducted among women household service workers identified deleterious health effects ranging from burning in the eyes and throat, watery red eyes, breathing difficulty, skin burns and irritation due to chemical exposures; back injury, lack of vitality and fatigue from their intensely physically demanding jobs; and stress, sleep deprivation and depression from psychosocial stressors [12,[20][21][22][23][24][25][26]. Research also shows that the probability of not receiving Workers' Compensation coverage was higher among women, new immigrants, and part-time or temporary workers [27][28]. ...
... Other research focusing on precarious occupations and temporary workers shows poor working conditions replete with exposures to vibration; excessive and loud noise and the repetitive performance of defined tasks. These jobs are often associated with fatigue, back pain and musculoskeletal injury [20][21]. Precarious jobs have also been associated with increased rates of injury and chronic disease from exposure to a variety of chemical hazards as well as from long work hours and few breaks [28]. ...
... Another cleaner said that, "I breathe those bad fumes all day through my nose, I can smell the stuff all day long." This kind of cleaning is quite different from a weekly cleaning and exposure to chemicals once or twice a week in a household; instead these women have repeated exposure to these chemicals throughout the day, which some studies have shown to be harmful [20][21][22][23][24][25][26]. ...
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This study explores the organization of work and occupational health risk as elicited from recently immigrated women (n = 8) who have been in the US for less than three years and employed in informal work sectors such as cleaning and factory work in the greater Boston area in Massachusetts. Additional interviews (n = 8) with Community Key Informants with knowledge of this sector and representatives of temporary employment agencies in the area provides further context to the interviews conducted with recent immigrant women. These results were also compared with our immigrant occupational health survey, a large project that spawned this study. Responses from the study participants suggest health outcomes consistent with being a day-laborer scholarship, new immigrant women are especially at higher risk within these low wage informal work sectors. A difference in health experiences based on ethnicity and occupation was also observed. Low skilled temporary jobs are fashioned around meeting the job performance expectations of the employer; the worker's needs are hardly addressed, resulting in low work standards, little worker protection and poor health outcomes. The rising prevalence of non-standard employment or informal labor sector requires that policies or labor market legislation be revised to meet the needs presented by these marginalized workers.
... Hotel housekeeping is a high stress job with characteristics that increase the risk for hypertension [Hunter Powell and Watson, 2006;Rugulies et al., 2008;Krause et al., 2009;Lee and Krause, 2002]. As the largest occupational group of the 1.8 million workers in the hospitality industry [Bureau of Labor Statistics, 2012a,b], hotel housekeepers experience irregular work schedules, time pressure, repetitive routines, hazardous physical conditions, and lack of autonomy over their tasks [Buchanan et al., 2010;DaRos, 2011; Department of Health and Human Services: National Institute of Occupational Safety and Health, 2012; Soltani and Wilkinson, 2010a,b]. Moreover, the fact that hotel housekeepers are predominantly women and immigrants puts them at further risks for poor management of the disease. ...
... The current literature on hotel housekeepers has mainly focused on their workload, avenues for personal and professional growth, and the growth of the industry [Hunter Powell and Watson, 2006, Kandampully andSuhartanto, 2000]. Additionally, there are studies about psychological outcomes such as stress, emotional distress, and feelings of burnout [Erkal and Şahin, 2012] and physical health outcomes of musculoskeletal problems such as back pain and injuries [Buchanan et al., 2010;Krause et al., 2005;Scherzer et al., 2005]. This study shows that research about the health and safety of hotel housekeepers must account for their ability to take care of their chronic diseases, both within and outside of the workplace. ...
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Background Characteristics of hotel housekeeping work increase the risk for hypertension development. Little is known about the influences of such work on hypertension management. Methods For this qualitative study, 27 Haitian immigrant hotel housekeepers from Miami-Dade County, FL were interviewed. Interview transcripts were analyzed with the assistance of the Atlas.ti software for code and theme identification. ResultsInfluences of hotel housekeeping work on hypertension management arose both at the individual and system levels. Factors at the individual level included co-worker dynamics and maintenance of transmigrant life. Factors at the system level included supervisory support, workload, work pace, and work hiring practices. No positive influences were reported for workload and hiring practices. Conclusions Workplace interventions may be beneficial for effective hypertension management among hotel housekeepers. These work influences must be considered when determining effective methods for hypertension management among hotel housekeepers. Am. J. Ind. Med. 56:1402-1413. (c) 2013 Wiley Periodicals, Inc.
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Background: Utilizing a psychosocial stress approach, we report psychosocial stressors that Latina/o immigrant day laborers in Baltimore report as workplace hazards and the contextual factors that shape these stressors. Methods: Through a community–academic partnership, we conducted focus groups (n = 18) and key informant interviews (n = 9) using instruments developed between academics and the community partner to inquire Latina/o immigrants’ jobs, hazard awareness, occupational illnesses and injuries, and reporting behaviors. We conducted a transcript-based thematic analysis. results: The psychosocial stressors that Latina/o day laborers report as dangers at work are anxiety beating the deadline and fear from wage theft, sudden termination and immigration enforcement. Discussion: More attention needs to be given to Latina/o immigrant day laborers’ occupational psychosocial risks. Policies should be made to lower barriers for Latina/o immigrants to report grievances to state agencies.
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Background The Services Sector, as defined by the National Occupational Research Agenda (NORA), is comprised of a diverse industry mix and its workers face a variety of occupational exposures and hazards. The objective of this study was to identify high-risk industry groups within the Services Sector for prevention targeting. Methods Compensable Washington State workers’ compensation claims from the Services Sector from 2002 through 2010 were analyzed. A “prevention index” (PI), the average of the rank orders of claim count and claim incidence rate, was used to rank 87 Services Sector industry groups by seven injury types: Work- Related Musculoskeletal Disorders (WMSDs), Fall to Lower Level, Fall on Same Level, Struck By/Against, Caught In/Under/Between, Motor Vehicle, and Overexertion. In the PI rankings, industry groups with high injury burdens appear higher ranked than industry groups with low counts or low rates of injury, indicating a need for prioritizing injury prevention efforts in these groups. Results In the Services Sector, these 7 injury types account for 84% of compensable claims in WA. The industry groups highest ranked by PI across the injury types included: Services to Buildings and Dwellings; Executive, Legislative, and Other General Government Support; and Waste Collection. WMSDs had the highest compensable claims rates. Conclusions Services is a large sector of the economy, and the substantial number, rate, and cost of occupational injuries within this sector should be addressed. Several Services Sector industry groups are at high risk for a variety of occupational injuries. Using a PI to rank industry groups based on their injury risk provides information with which to guide prevention efforts.
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Background: The occurrence of specific low back pain (LBP) due to workplace factors has not been well described among kitchen industry workers. This study would claim various risk factors that contributing LBP among kitchen workers. Objective: The purpose of the study was to examine the risk factors and the prevalence of LBP among the male commercial kitchen workers at catering industry. Methods: The study population comprised of 114 male kitchen workers from nine hostel kitchens in a college campus in South India. The reported musculoskeletal symptoms during past 12 months were determined with the help of standardized Nordic Musculoskeletal Questionnaire (NMQ) survey and by direct observations. Results: The statistical analyses were carried out and the highest prevalence of LBP among subjects was reported as 65.8%. Among different work categories, the Chief cooks were reported highest prevalence of LBP (79.2%) than Assistant Cooks (71.4%) and Kitchen Aids (30.0%). Similarly the upper age group (⩾ 41 years) workers had experienced the highest discomfort in low back as 92.9% than other age groups. Conclusions: Results suggest that to undertake further studies on different preventive measures and ergonomics intervention to reduce the risks of LBP among kitchen workers.
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Prior research has shown increased risk of injury for female employees compared to male employees after controlling for job and tasks, but have not explored whether this increased risk might be moderated by manager gender. The gender of one's manager could in theory affect injury rates among male and female employees through their managers' response to an employee's psychosocial stress or through how employees differentially report injuries. Other explanations for the gender disparity in injury experience, such as ergonomic factors or differential training, are unlikely to be impacted by supervisor gender. This study seeks to explore whether an employee's manager's gender modifies the effect of employee gender with regards to risk of acute injury. A cohort of employees and managers were identified using human resources and injury management data between January 1, 2002 and December 31, 2007 for six facilities of a large US aluminum manufacturing company. Cox proportional hazards models were employed to examine the interaction between employee gender and whether the employee had female only manager(s), male only manager(s), or both male and female managers on injury risk. Manager gender category was included as a time varying covariate and reassessed for each employee at the midpoint of each year. The percentage of departments with both female and male managers increased dramatically during the study period due to corporate efforts to increase female representation in management. After adjustment for fixed effects at the facility level and shared frailty by department, manager gender category does not appear to moderate the effect of employee gender (p = 0.717). Manager category was not a significant predictor (p = 0.093) of time to first acute injury. Similarly, having at least one female manager did not modify the hazard of injury for female employees compared to males (p = 0.899) and was not a significant predictor of time to first acute injury (p = 0.601). Prior findings suggest that female manufacturing employees are at higher risk for acute injury compared to males; this analysis suggests that this relationship is not affected by the gender of the employee's manager(s).
Background: Acute work-related trauma is a leading cause of death and disability for U.S. workers but it is difficult to obtain information about injured workers not covered by workers' compensation (WC). This study aimed to: (1) describe trends in expected payer and linkage to WC claims, (2) compare characteristics of injured workers who did and did not have a linked WC claim, and (3) describe variation in expected payer and linkage to WC claims by ethnicity and injury severity. Methods: Data for injuries occurring from 1998 through 2008 were obtained from the Washington State Trauma Registry and linked to WC claims. Results: We found that 27% of work-related traumatic injuries did not have WC listed as a payer, while 37% did not link to a WC claim. Among those with WC listed as a payer, the odds of having a linked WC claim were 57% lower for workers with other non-WC insurance compared with the otherwise uninsured. Latinos were more likely to have a linked WC claim compared with non-Latinos, but there was no significant difference after partially controlling for WC-covered employment and other insurance. Conclusions: This study demonstrated the importance of considering differential access to other insurance coverage and adaptation by health care settings to financial pressures when assessing trends in occupational injury incidence and reporting, especially when using WC as a proxy for work-relatedness. The addition of occupation, industry, and work status to trauma registries and hospital discharge databases would improve surveillance, research, policy and prevention efforts.
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Brazilian immigration to Massachusetts and other states in the US grew significantly in the last two decades. There is a lack of data about the working conditions and health and safety hazards faced by Brazilian immigrant workers. We surveyed over 500 workers in Eastern Massachusetts through a community-based participatory research project to explore occupational and immigration factors that may represent a risk to the health of Brazilian immigrant workers, who mostly work in the construction, housecleaning, and food services segments of the state labor force. Our pilot study suggests that Brazilian immigrant workers are exposed to chemical, ergonomic, physical, and psychosocial job hazards and have experienced a variety of health symptoms that may be associated with these work environment exposures. Since most Brazilian workers have not received proper training to recognize the hazards, there is an urgent need for the implementation of culturally adequate training programs and enforcement of safety and health regulations to prevent occupational injuries and fatalities.
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Background The purpose of this review was to identify critical data and research needs in addressing the following question: What are the primary factors that affect the time lost from work, return-to-work (RTW), subsequent unemployment, and changes in occupation after disabling illness or injury?Methods Review of the literature to identify research challenges originating from the multitude of disciplines, data sources, outcome measures, and methodological and analytical problems.ResultsAbout 100 different determinants of RTW outcomes were identified. Their impact varies across different phases of the disablement process. Recommendations are provided for addressing five selected research challenges.Conclusion Interdisciplinary research needs to develop a comprehensive conceptual framework. Priority should be given to studies on specific domains of risk factors meeting five selection criteria: amenability to change; relevance to users of research; generalizability across health conditions, disability phases, and settings; “degree of promise” as derived from qualitative exploratory studies; and capacity to improve measurement instruments. Combining qualitative and quantitative research methods is necessary to bridge existing knowledge gaps. Am. J. Ind. Med. 40:464–484, 2001. © 2001 Wiley-Liss, Inc.
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Achieving gender equality in all aspects of employment is now a key European priority. It is a matter of rights, but it is also a matter of sound economic policy — especially considering the human and economic costs of injuries and ill health caused or made worse by work. The report highlights the dual importance of considering gender in risk prevention and including occupational safety and health in gender equality employment activities. Cooperation between these two policy areas is crucial, from the European level, down to the workplace, to promote improved workplace risk prevention for both women and men. Available in: [Deutsch] [English] [Español] [Français] [Italiano] [Polski]
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Relative risks of exposure to each of six types of occupational injuries and illnesses for Hispanic and Black workers compared to Whites who are not Hispanic were calculated using 1986 California data. Among males, Hispanics faced relative risks of exposure to all hazards adjusted for education and years of work experience of 1.33 (95% CI 1.22, 1.45), while Blacks faced relative risks of 1.17 (1.0, 1.37). Among females, adjusted relative risks were 1.19 (1.09, 1.29) for Hispanics and 1.31 (1.15, 1.50) for Blacks.
Hotels and hotel chains are responding to globalization and increased competition through new marketing initiatives, employment practices, and restructuring decisions that are intensifying the work of cleaners. In this paper, we report on how such work intensification at two hotels in Montréal, Canada, is changing the nature of cleaners’ jobs. Specifically, we found that the numbers of operations to be completed, the numbers and weights of items to be cleaned, and the effort involved have all increased. “Flexible” employment relationships and outsourcing have also worsened cleaners’ workloads. In response to our research, the labour union representing cleaners has negotiated a lower number of room assignments per cleaner, as well as an improved way of taking into account the variability of work when determining the quota of rooms to be cleaned. Despite this, new marketing strategies continue to intensify work. We conclude that standards and regulation on a governmental level are a necessary complement to union actions.
The North American work force is still highly sex-segregated, with most members of each sex in jobs composed primarily of workers of the same sex. This division is accentuated when jobs involve physical demands. Women have traditionally been assigned to tasks whose physical demands are considered to be light. Nevertheless, these tasks can have biological effects, sometimes serious. Phenomena related to physical demands of women's work can be considered in three categories: (a) musculoskeletal and cardiovascular demands of tasks often assigned to women in factories and service work; (b) sex- and gender-specific effects of toxic substances found in the workplace; and (c) interactions between work and the domestic responsibilities of many women. These phenomena are described, using examples recently gathered from workplaces. Effects of biological sex are distinguished, as far as possible, from effects of gender (social roles).
More than twice as many workdays are lost to illness than for personal or family reasons. We examine possible workplace determinants of sickness absence among French workers in the food processing industry. These workers are exposed to a variety of environmental and organizational constraints: cold, uncomfortable postures, assembly-line work, and irregular schedules. In 1987-1988, a medical examination and questionnaire were administered to 558 men and 790 women as part of a study of 17 poultry slaughterhouses and 6 canning factories. Women's and men's working conditions were very different, and their sickness absences for musculoskeletal and respiratory illnesses were related to some of their specific working conditions: cold exposure, ill-adapted work stations, and problems with their supervisors and co-workers. If male and female workers were combined into a single analysis that adjusted for sex, many of the associations operant for a single sex could no longer be seen.