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Occupational Medicine Advance Access originally published online on March 19, 2008
Occupational Medicine 2008 58(6):393-399; doi:10.1093/occmed/kqn028
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© The Author 2008. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Epidemiology of occupational injury among cleaners in the healthcare sector

Hasanat Alamgir and Shicheng Yu

Statistics and Evaluation Department, Occupational Health and Safety Agency for Healthcare, Vancouver, British Columbia, Canada

Correspondence to: Hasanat Alamgir, Statistics and Evaluation Department, Occupational Health and Safety Agency for Healthcare, 301-1195 West Broadway, Vancouver, BC, Canada V6H 3X5. Tel: +778 328 8013; fax: +778 328 8002; e-mail: hasanat{at}ohsah.bc.ca


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 
Background The cleaning profession has been associated with multiple ergonomic and chemical hazards which elevate the risk for occupational injury.

Aims This study investigated the epidemiology of occupational injury among cleaners in healthcare work settings in the Canadian province of British Columbia.

Methods Incidents of occupational injury among cleaners, resulting in lost time from work or medical care, over a period of 1 year in two healthcare regions were extracted from a standardized operational database and with person-years obtained from payroll data. Detailed analysis was conducted using Poisson regression modeling.

Results A total of 145 injuries were identified among cleaners, with an annual incidence rate of 32.1 per 100 person-years. After adjustment for age, gender, subsector, facility, experience and employment status, Poisson regression models demonstrated that a significantly higher relative risk (RR) of all injury, musculoskeletal injury and cuts was associated with cleaning work in acute care facilities, compared with long-term care facilities. Female cleaners were at a higher RR of all injuries and contusions than male cleaners. A lower risk of all injury and allergy and irritation incidents among part-time or casual workers was found. Cleaners with >10 years of experience were at significantly lower risk for all injury, contusion and allergy and irritation incidents.

Conclusion Cleaners were found to be at an elevated risk of all injury categories compared with healthcare workers in general.

Keywords      Allergy and irritation; cleaners; musculoskeletal injury; occupational injury


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conflicts of interest
 References
 
The cleaning profession has frequently been associated with multiple ergonomic and chemical hazards, elevating the risk for occupational illness and injury [1–5]. In Norway, the cleaning profession was also characterized by a higher rate of morbidity and a higher level of disability pensioning [6]. Recent research in Australian hospitals found that, while registered nurses (RNs) accounted for 26% of all injury incidents and cleaners accounted for 9%, rates of injury for cleaners were higher than those for RNs and twice the average for all occupations [7]. A cross-sectional study of sharp injuries among hospital support personnel (laundry workers, cleaners, porters and central supply workers) demonstrated that cleaners sustained the majority (66%) of injuries and that inappropriate disposal was associated with 55% of all injuries [8]. The exposure of cleaning personnel to blood and body fluid (BBF) has also been documented in studies [9–15]. The ramifications of injuries to healthcare cleaning personnel include time lost from work, compensation claims and associated costs and an impact on service delivery. Furthermore, the pain, suffering and earnings loss of the injured and their family as consequences of any injury remain important yet difficult to quantify.

Jobs in the cleaning sector often include a number of hazards. Cleaning is a physically demanding job that includes numerous and varied tasks. Cleaners spend a considerable amount of their time standing and lifting or pushing fixtures and equipment. Most of their tasks (e.g. dusting; sweeping and cleaning walls, furniture and bathrooms) require bending, stooping and stretching. Cleaners are also at risk of minor cuts, bruises and burns from machinery, from hand tools and from handling refuse and chemicals. In addition to this, while typically working inside heated, well-lit buildings, cleaners may also work outdoors.

Cleaners working in healthcare facilities are likely to be exposed to additional occupational risks specific to the healthcare sector. Unlike typical office buildings, hospitals are constantly cleaned throughout the 24-h period. During their work, cleaners need to dispose of medical waste, which may by accident contain contaminated needles or sharps. If not disposed of properly, these can transmit life-threatening pathogens. Excreted bodily fluids from patients may also contain these organisms. Healthcare facilities may use cleaning solutions of greater strength and different composition than non-healthcare facilities, thus increasing the level of risk to workers handling such substances.

Cleaners form an important proportion of the total working population, e.g. making up 4% of the working population in Finland [16] and 10% of the female working population in Spain [17]. In the Canadian province of British Columbia (BC), cleaning personnel represent a large and growing occupational group, with numbers rising from 43 650 in 1990 to 56 795 in 2001 [18]. Cleaners working in hospitals and healthcare facilities in Canada represent 30% of those working in the cleaning industry [19].

To date, no previous study has characterized the epidemiology of occupational injury among cleaners in the healthcare sector. This study investigated the risk for various occupational injuries among cleaners working in healthcare in BC. The analysis included injuries in two healthcare regions over a 1-year period.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conflicts of interest
 References
 
The Workplace Health Indicator Tracking and Evaluation (WHITETM) database is a Web-based surveillance system developed by the Occupational Health and Safety Agency for Healthcare in British Columbia (OHSAH) in collaboration with University of British Columbia researchers and the health regions to facilitate the analysis of workplace incidents and injuries (including near-misses), ascertain whether there is a need to develop preventative measures and provide healthcare stakeholders with comparative performance indicators on workplace health and safety. WHITETM data include descriptions of incidents, demographics information, contributory factors related to location and circumstances of the injury, nature and cause of the injury and body part involved. Currently, four of BC's six healthcare regions are tracking incidents using WHITETM.

Incidents are reported by the affected worker to their manager/supervisor. Details of the incident are written onto a triplicate form which is filled out by the supervisor/manager. This form mirrors the questions and fields that are contained in the WHITETM database and the worker is asked to respond to each question. The form is then forwarded to the occupational health and safety department of the appropriate healthcare region where designated staff verify the incident details and complete the document. If an incident requires medical care or loss of time at work, a portion of the form goes to the claims department of the workers' compensation board (WorkSafeBC).

The WHITETM database and its intent were reviewed rigorously by OHSAH's bipartite board of directors consisting of the healthcare employer and union representatives who supported the database and have communicated this to their workforces and membership. The information that is collected is used for health promotion, case management, research and evaluation for the purposes of improving the health of British Columbia's healthcare workforce. The WHITETM database has many layers of security to ensure that information is only available to authorized persons. This is in addition to health authority network security. Data are used for research and analysis purposes by each health authority and OHSAH. Information collected and used by OHSAH maintains the anonymity of individual healthcare workers, through removing or encrypting personal information before any analysis of the data occurs.

The WHITETM database facilitates the merger of incidents of injury with workers' compensation data and payroll data. To increase consistency with existing literature, our analysis includes only those injuries that necessitated medical care or resulted in time lost from work. All such records for cleaning occupation were identified for this study. Our analysis includes injuries among cleaners for two health authorities in BC (Region A: 26 August 2004 to 9 September 2005 and Region B: 5 November 2004 to 8 September 2005). In the other health authorities, cleaning services have been outsourced to private companies or data were unavailable.

This analysis aggregated the standard WHITETM ‘nature of injury’ categories into the following groups: musculoskeletal injury (MSI), contusion (includes bruise), cut (includes cut, scratch, abrasion and laceration), allergy and irritation (includes skin, eye, respiratory irritation, exposure to skin and allergic response) and puncture. Also, for the purposes of this analysis, the ‘cause of injury’ was aggregated into the following groups: ergonomic factors (posture, stress, force, repetition, etc.), hit and caught (hit, struck or cut by equipment; caught in, under or between equipment), slip and fall, chemical exposure, BBF exposure (needlestick, sharps and splash), other exposure (dust, radiation, electricity, latex, temperature, noise, radiation and air quality) and other causes (undetermined and other causes).

The number of injuries and the number of productive hours were used to calculate the incidence rates per 100 person-years (with 1879.2 productive hours equivalent to 1 person-year). The productive hours for cleaners were collected directly from the health authorities' payroll data. These were defined as regular hours worked plus overtime, explicitly excluding sick leave and annual leave taken.

The analyses were conducted using Poisson regression with the occurrence of an occupational injury as the dependent variable, to examine its association with age group, gender, care type, experience and employment status. Because healthcare workers are categorized by facility and health authority, conventional Poisson regression modeling would not be an appropriate statistical technique. Consequently, Poisson regression modeling using generalized estimating equations, with facility and health authority as the clustering variables, was used to examine associations [20]. The adjusted rate ratios were presented along with their 95% confidence intervals. Statistical analysis was carried out using the Statistical Package for Social Sciences (SPSS Version 14.0, 2006) with two-sided significance levels of P ≤ 0.05.

The injury outcome in respect to compensation was also reported. The detailed descriptions of incidents were available in the incident database. These were examined to compile a list of commonly reported occupational hazards for cleaners.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Conflicts of interest
 References
 
A total of 145 reported injuries were identified among cleaners. Of these reported injuries, 87 (62%) resulted in time lost from work. Table 1 presents the proportion of injuries that resulted in time loss and/or medical aid by nature of injury. Of the reported MSIs, 83% resulted in time loss, while 63% of contusions, 14% of allergy and irritation incidents and 13% of puncture injuries required time loss.


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  		Table 1. Injury outcome by time loss and medical care

 
MSIs were the most prevalent nature of injury for cleaners, representing 59% of all injuries. This was followed by contusions 13%, allergy and irritations 10%, cuts 9% and punctures 6%. The majority of injuries reported involved cleaners who were female (90%), age 40–49 years (47%), full-time employees (47%), worked in acute care (86%) and had 1–5 years experience (35%).

The annual incidence rate of injury among cleaners was found to be 32.1 per 100 person-years with the highest rate for MSI of 19 per 100 person-years (Table 2). Compared with all healthcare workers, cleaners had a two to three times higher risk for almost every injury category. With the exception of punctures and allergy and irritations, female workers had higher rates of all other injury categories. Cleaners employed in acute care facilities had a higher rate of all injury categories than those working in long-term care settings. Part-time workers were at a higher risk of all injuries, MSIs and contusions. With respect to experience, workers with >10 years experience generally had less risk of all injury and MSI than those employees with 1–10 years experience. No clear relationship of injury risk with respect to age was apparent.


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  		Table 2. Injury numbers and rates in cleaners by age, gender, subsector, employment status and experience

 
Table 3 shows the relative risk (RR) of injury obtained from Poisson regression models after adjusting for age, gender, subsector, facility, experience and employment status. Some of the variables from Table 2 (age, experience, subsector and employment status) were collapsed to have sufficient numbers in the cells to fit the model in Table 3. A significantly higher RR of all injuries, MSIs and cuts was associated with cleaning work in acute care facilities compared with long-term care facilities (P < 0.05). Female cleaners were at higher RR of all injury and contusion than male cleaners (P < 0.05). Adjusted Poisson regression models also showed a lower risk of all injuries and allergy and irritation incidents among part-time or casual workers, compared with their full-time counterparts (P < 0.05). Cleaners with >10 years of experience were at significantly lower risk for all injuries, contusions and allergies and irritation incidents (P < 0.05). The slight differences in risk between age groups were not significant.


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  		Table 3. Association of occupational injury for selected variables: age, gender, subsector, employment status and experience among cleaners (multivariate models)

 
Figure 1 provides a cross-tabulation of the causes of different injury categories by their nature. Ergonomic factors and slip and fall accounted for 90% of the MSI incidents. Slip and fall, and hit and caught were responsible for 85% of the contusion incidents. BBF incidents (needlestick, splash and sharps) accounted for 90% of the puncture incidents. For allergy and irritation, chemical exposure was responsible for 43% incidents. For cuts, 31% resulted from being caught or hit by equipment.


Figure 1
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  		Figure 1. Injuries and its causes among cleaners.

 
Table 4 provides a summary of the commonly reported occupational hazards found in our study among cleaners. Repetitive tasks, lifting heavy objects and pushing and pulling of objects were noted as the principal reasons for MSI events. Garbage handling was the cause of most of the puncture and cut incidents. The most common cleaning solutions mentioned in injury incidents contained chlorine, hydrogen peroxide, n-alkyl dimethyl benzyl ammonium chloride and didecyl dimethyl ammonium chloride.


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  		Table 4. Occupational hazards for cleaners in healthcare settings

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conflicts of interest
 References
 
The current study suggests that cleaning staff in the healthcare setting are at a very high risk of injury at work. Compared with other healthcare workers, the overall injury rate for cleaners was 32.1 per 100 person-years compared with 13.0 per 100 person-years. Our study also found that among cleaners in the healthcare sector, inexperienced workers, female workers and those working in acute care facilities were at the highest risk of injury. MSI was the most common injury reported among cleaners and ergonomic factors were predominately responsible for this. In terms of severity, the data suggest that the bulk of injury incidents among cleaners result in time lost from work (particularly incidents of MSI and contusion).

Previously, high injury rates have also been shown among hotel cleaners, 29.6 per 100 full time equivalent (FTE) using self-reported data [2]. Past research, in accordance with the results of this study, has recognized MSIs to be major concern for cleaners. Unge et al. [21] determined that hospital cleaners had a high prevalence of neck and upper limb disorders that coincided with high physical workloads [21]. According to published statistics by WorkSafeBC, for light duty cleaners (including cleaners at healthcare facilities and many different industries) from 1997 to 2004, there were 9197 compensated time-loss injuries in BC [22]. Among these, the largest injury categories were overexertion in lifting (11%), overexertion in pulling or pushing objects (8%), other overexertion (14%), fall on same level to floor or other surface (11%), bending, climbing, crawling, reaching twist (6%) and struck against stationary object (5%) [22]. The detailed listing of hazards presented in this study identifies similar hazards. It seems that the physical demands of the job put cleaners at risk of occupational injuries.

This investigation identifies vulnerable groups among cleaners who could be targeted for prioritized interventions. Preventative efforts to protect inexperienced workers could be undertaken. Higher injury rates among these workers may relate to a poor understanding of work processes, a lower awareness of the potential hazards or simply being assigned to do more hazardous jobs. Experience has been shown to correspond with lower injury risk in other healthcare workers. For example, nurses with >5 years experience showed a decreased risk for needlestick injuries [23]. In the present study, a decrease in overall injury risk was observed for workers with >10 years experience. The lower injury rate among experienced workers might also be explained by the healthy worker effect, i.e. workers with a history of frequent or severe injury may stop working in this occupation or sector with only healthy workers remaining in the workforce. This is a potential source of bias of this study.

Our finding of a higher risk of injury among female workers concurs with the recent evidence that suggests that gender segregation occurs at work, with women often performing the more repetitive and routine work (even within in the same job category) [24]. Another possible explanation of this is that women often have a heavy domestic workload which may contribute to injury rates (i.e. having less opportunity to relax and exercise outside of work) [25].

Cleaners in acute care facilities had a higher risk of all injury categories when compared with cleaners in the non-acute setting. Acute facilities tend to have a faster paced environment with greater workload, heavier loads and stricter time lines. Although acute facilities are larger and therefore are thought to have structured and safer work environments, this is not reflected in this analysis.

There are several limitations to this study. The analysis was limited to two healthcare regions, consisting of ~10% of the healthcare workforce of the province. Thus, there may be differences in demographic characteristics that limit the ability to generalize our findings. In addition, the study population included workers directly employed by the health regions, excluding workers whose cleaning services were contracted by outside providers. This study further excluded some healthcare facilities that operate outside any healthcare region's jurisdiction in BC. The statistical analysis was limited by small subgroup populations in certain categories—males, workers <30 years old and those working in non-acute care facilities. Aggregation of a few of these groups reduced the ability to determine more precise differences across characteristics. Also, the data collected did not include information on many other contributing factors, such as workplace culture, training, multiple jobs, etc. The 1-year data collection period restricted the identification of long-term trends. Finally, this investigation accounted only for reported events and underreporting is an issue, especially when cleaners assume that such injuries are part of their job or that reporting would not reduce future hazard exposure. Therefore, it is likely that our study underestimated injury rates.

Occupational hazards for cleaners in healthcare settings have so far received little attention in the scientific community. This study contributes to the knowledge base in this area. It is important to build upon this research in order to help develop preventative policies to reduce the hazards in the workplace and promote safer work practices for cleaners.


Key points
  • Cleaners in the healthcare sector were found to be at an elevated risk of occupational injury compared with other healthcare workers. MSI was the most prevalent nature of injury for cleaners.
  • Cleaners in acute care facilities, female cleaners, full-time cleaners and inexperienced cleaners were at the highest risk of occupational injury.
  • Preventative policies should be developed to reduce the hazards in the workplace and promote safer work practices for cleaners working in healthcare facilities.

 


   Conflicts of interest
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
References
 
None declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 

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