Work‐related injury burden, workers' compensation claim filing, and barriers: Results from a statewide survey of janitors

1 INTRODUCTION

Janitors in the United States comprise a large, ethnically and linguistically diverse occupational group of low-wage, low-status workers facing a high burden of occupational injury and illness.1-4 In Washington State, Janitors are one of the largest occupational groups (ranked 12th in the state, an estimated 40,586 in 2021),5 and nationally, janitors are among the top 10 occupations projected to have the highest number of new jobs from 2018 to 2028.6 The average annual wage for janitors in WA is around $30,000,7, 8 which is significantly less than the state average for all industries ($69,615)7 though higher than janitors nationally.8

Janitors have a high burden of occupational injury and illness due to the wide range of physical demands and chemical exposures experienced on the job.1-3, 9-18 These include, but are not limited to: work-related asthma and respiratory disorders,19-22 musculoskeletal issues,12, 13, 18, 23, 24 and dermal and ocular irritation.11, 17 Janitorial work may also be associated with increased risk of birth defects and poor pregnancy outcomes,25-27 as well as certain cancers.28-30

The U.S. Bureau of Labor Statistics Occupational Injuries/Illnesses and Fatal Injuries Profiles data for the United States (private industry, 2019) shows an incidence rate for the “Janitorial Services” industry (North American Industry Classification System (NAICS) 561720) of nonfatal occupational injuries and illness involving days away from work of 107.5 per 10,000 full-time workers, higher than the rate for private industry as a whole (86.9 per 10,000 full-time workers).31 By occupation, using Standard Occupational Classification (SOC) codes for “Janitors and cleaners, except maids and housekeeping cleaners” (SOC 372011) the incidence rate for injuries and illnesses involving days away from work was 157.4 per 10,000 full-time workers in 2019, nearly twice the rate of 86.9 per 10,000 workers for “all occupations.”32 When looking at selected events or exposures leading to injury or illness by occupation, “Janitors and cleaners, except maids and housekeeping cleaners” (SOC 372011) had higher rates per 10,000 full-time workers than “all occupations” in events such as “Struck by object or equipment” (20.4 vs. 13.2), “Falls, slips, trips” (55.9 vs. 23.9), “Overexertion and bodily reaction” (47.1 vs. 27.0), and “Exposure to harmful substances or environments” (6.4 vs. 3.6).33

Workplace injuries for janitors come at sizeable costs to the worker and to society, with an estimated 4.1 billion dollars in medical and productivity costs, annually in the United States, the 2nd highest cost total of the low-wage occupations studied.34 These costs include both direct (e.g., medical care) and indirect (e.g., productivity) losses.34 Janitors were ranked among the occupations at highest risk for a variety of occupational injuries, illnesses, and fatalities when compared with other occupations in an analysis of workers' compensation (WC) data,35 and another study found “Services to Buildings” (Standard Industrial Classification Code 734, which includes janitorial services) was ranked 33rd highest out of 313 industries for total costs for fatal and nonfatal injuries and illnesses.36 In WA, “Services to Buildings and Dwellings” (NAICS industry group 5617) was ranked at highest risk overall by prevention index (a metric averaging injury count and rate to prioritize industries or occupations for prevention and intervention) from 2002 to 2010, consistently ranking in the top 25 industry groups across seven common injury types.2

The majority of commercial cleaning work is performed by workers employed by specialized janitorial services firms that contract either directly with clients, or with a building management firm that provides a range of building management services to clients. The firm that controls the worksite and determines the scope of the work—the client—is distinct from the firm that employs and supervises the janitors. This organizational structure, termed “fissured” or “outsourced,” became widespread in the late 20th century as part of a broad set of organizational changes that saw large, multifunctional firms shed many “non-core” activities that had been performed in-house by the firm's own employees. The aim of this shift was to allow the firm to reduce labor costs for ongoing, noncore activities. The source of labor cost reduction is that janitorial workers who are directly employed in a large multifunctional firm had both higher wages and benefits than did their counterparts working for small, specialized contract cleaning firms. By shedding these activities, lead firms could exclude some workers from participation in such benefits programs and convert a compensation and supervision issue into a transaction to be settled by contracting with a vendor in a competitive market.37, 38 Empirical estimates of the wage reduction realized by firms that outsource such noncore activities range from 4%–7%39 to 15%–17%40 and these studies found that outsourced janitorial workers were much less likely to receive employer-sponsored health insurance coverage.

Small janitorial services firms contracting with clients in a competitive market with low barriers to entry for new start-ups are under significant pressure to keep costs low. Such constraints may result in a focus on production at the expense of attention to compliance with standards for occupational safety and health. The expansion in commercial office space in WA has outpaced the growth of the workforce and may increase work demands.41 Janitors have recently reported increasing workloads42-44 which may put them at increased risk of work-related injuries.

Janitors face what is described by the National Institute for Occupational Safety and Health (NIOSH) as “overlapping vulnerabilities.”45 This refers to a situation where, in addition to occupational hazards, a variety of factors may combine to affect work and health experiences and increase risk of work-related injury and illness (WRII). For janitors, these factors include being low-wage and low-status,46 often women,1, 12-14, 16 being older age workers (often over 40),12, 13, 16 with a large proportion of immigrants,10, 14 and facing language barriers.13

The janitorial workforce is also racially and ethnically diverse, and many of these workers have historically faced discrimination in health diagnoses and health care quality which may increase their proportion of comorbidities and compound risk of and difficulty in recovering from, WRII.47-52 The combination of limited knowledge of and access to training, healthcare and other workplace rights and benefits,10 as well as lower bargaining power to demand safe work,46 places janitors at high risk of occupational injury. Both California and Oregon have passed legislation regarding training and protections for janitors.53, 54

In WA, analyses of WC claims and the state's Behavioral Risk Factor Surveillance System (BRFSS) data by occupation have consistently identified janitors as a profession at high risk for WRII compared to other workers across a wide range of injury types, and in need of further attention to reduce this burden.1-3, 55 In 2018, the Washington State Legislature funded the creation of the Washington State Janitorial Workload Study (JWS) to address the high injury rates for janitors.56 The specific aims of the JWS were to: quantify the physical demands of common janitorial tasks, assess the safety and health needs of janitors, identify potential risk factors associated with increased risk of injury, and measure workload strain. The JWS statewide survey was created to help fulfill these aims (along with other study components, such as in-person physical exposure assessments, an employer survey, and focus groups).

2 MATERIALS AND METHODS 2.1 Population

A statewide survey of janitors was conducted from November 4, 2019, through February 4, 2020, for all eligible janitors in WA. Eligible survey respondents were those currently employed as commercial janitors or custodians, or had been so employed in the past year, and were 18 years of age or older. A professional survey research firm administered the survey through mail, phone, and web modes. The survey was available in English, Spanish, Vietnamese, Somali, Traditional Chinese, Simplified Chinese, Russian, and Amharic.

2.2 Data sources and linking

The janitorial workforce is difficult to survey because janitors work across industries, in a variety of employment arrangements, and with varying work organization, tenure, and employer sizes. Additionally, records on employment are limited as there are no state licensing requirements, registries, certifications, associations, or other publicly accessible lists of janitors with necessary contact information. As a result, a novel data linkage procedure combining WA Employment Security/Unemployment Insurance data (ESD), WA WC claims data, union enrollment data, and WA driver's licensing data was created to capture a broad sample of janitors across WA (Table 1). Relying on a single source would have limited the sample in size and generalizability (e.g., only injured janitors from WC, only union janitors from union membership rolls).

Table 1. Washington state janitorial workload study, 2019–2020 statewide survey sample information Data source Employment security department (ESD) data Department of licensing (DOL) data WA workers' compensation claims Union membership rolls (1) Total raw sample (2) After data cleaning (3) 1st sample (4) 2nd sample % of total raw sample (1) 74% Not applicable//matching only 5% 21% 20,129a 16,664b 12,847 1263 Identification processc Identified workers employed by janitorial firms within NAICS code 561720, Janitorial Services ESD data matched to WA drivers' license holders by name Workers compensation claims data for janitors, identified by risk class 6602, specifically 6602-03 and 6602-05 Janitors represented by the union Variables used, strengths and limitations Employee names. No individual contact information. Limited to workers employed by Janitorial Services firms (industry based)—does not identify janitors directly employed by other types of companies Name and contact information. Limited to those with a valid drivers' license. Many out-of-date addresses. Does not include employment information, can only be used to provide contact information via name matching Name and contact information. Not limited to industry coding (NAICS)- this allows us to identify janitors who work outside of 'Janitorial Services—NAICS 561720' (e.g., janitors directly employed by other companies). May include language preference. Limited to injured workers who filed a claim Employment, name, and contact information. Language preference. Unions represent only a small percentage of janitors. Union members may differ from other janitors in working conditions, wages, demographics, work organization, and other factors

The multisource linking process yielded many potential janitors, but was limited by the available data, and likely did not include certain groups of janitors such as self-employed owners of cleaning businesses without other employees or employing only family members (e.g., franchisees), janitors employed directly by nonjanitorial-service firms (outside of those included in WC), and janitors employed in the underground economy.

Due to limitations and missing data elements in each of the data sources used (Table 1), the linkage process was necessary to compile a usable sample of janitors. Data from ESD (74% of the initial raw sample, Table 1) identified janitorial firms and janitors within NAICS code 561720—Janitorial Services, but did not include contact or demographic information about individuals, nor occupation or risk class information to better identify janitors within this or other industry classifications. This data was linked to the Department of Licensing name and contact information for WA residents with valid drivers' licenses, which could be matched to the names of janitors identified by the ESD data. This provided data only for those with a valid license, and this information is not always up-to-date.

For janitors who are not employed by Janitorial Services (NAICS 561720) firms, data from sources other than ESD were needed. To capture janitors directly employed by other types of businesses (e.g., janitors employed in a manufacturing company, janitors employed in agricultural warehouses), we used risk class information from WA WC data. Risk class is a WA-specific classification system that combines industry and occupation information to group workplaces by similar risk level for industrial insurance purposes. For example, a janitor directly employed by a manufacturing company would have the same NAICS code (industry) as any other employee working for the same firm regardless of occupation, but they would be assigned different risk classes, and the employer would pay WC premiums based on their risk classes. ESD data does not include occupational information, so it cannot be used to differentiate between janitors and those doing non-janitorial work at the same firm. However, this WC information is only available for injured janitors. Employers pay premiums based on the number of employees by risk class, but the employer account database does not include names or contact information for individual workers. When a worker is injured and files a claim, this information becomes available. We identified janitors from the WC data by risk class 6602—Janitorial Services and Pest Control, specifically sub-classes 6602-03—Janitorial Cleaning Services, Not Otherwise Classified (N.O.C.), and 6602-05—Janitors, N.O.C. This excludes other workers in the risk class such as contract window washing services, residential janitors, pest control, portable cleaning and washing, and street and building decoration workers. The WA WC system is a rich data source and provides name and contact information, as well as language preference data when available. Approximately 5% of the total raw sample data (Table 1) sent to the survey research firm were from WC data (before the addition of union membership rolls, and before data cleaning and sample selection).

The final data source included was membership data from a labor union that represents property service workers (including janitors). A data sharing agreement was established between the union and the survey research firm; name, contact information, and language preference information were sent directly to the survey research firm.

2.3 Sampling

The survey research firm that was contracted worked with an Institutional Review Board trained and approved staff member who was not involved in the JWS to compile the data for sampling. An initial survey sample pool of 20,129 potential janitors (Table 1) was created, and after removal of duplicates and janitors without usable contact information, the sample was reduced to 16,664 potential janitors. The authors were not privy to the methods used to select janitors. The first sample of 12,847 potential janitors was selected, which was followed about a month later by the drawing of a second sample of 1263 respondents from the remaining previously uncontacted pool of potential janitors to increase the total number of responses.

2.4 Survey administration

Potential respondents were contacted by mail (by the survey research company) with prenotification letters and informed consent information, including information on how to opt-out if they did not wish to be contacted further. Following this initial contact, potential respondents were sent survey packets with information on how to take the survey in multiple languages. Janitors were provided with unique personal identification numbers (pins) so that only those identified by the sample as verifiable janitors or custodians had access. Additional janitors who found out about the survey through other means and wanted to participate were able to take it by contacting the research team and having their name and employment verified, and upon confirmation, they were given pin numbers for access. Several weeks after the full questionnaire packet mailings, if the potential janitors had not opted out, nor mailed in a reply, and if there was a valid phone number, the survey research company had interviewers call to attempt to interview potential janitors by phone. Janitors who participated were asked if they were currently employed as janitors (or had been in the last year), as part of the screening process, along with confirming they were over age 18.

Respondents could participate in the survey by returning the printed questionnaire in an included postage-paid envelope, by filling it out online, or by calling the provided telephone numbers. While the paper survey form was only mailed in English, as no available data source could predict language preference for the entire sample, information on how to take the survey was provided in each of the supported languages. The online method was available in English and Spanish, while phone numbers were available for all others. The languages supported were chosen based on prior analyses of WC claims by janitors (the initial WC form at claim initiation allows workers to select a preferred language to communicate with the agency, though it is optional), and by consultation with a labor organization that represents janitors in WA.

2.5 Questionnaire

The survey instrument covered a wide range of topics about janitorial workload, work organization, job demands and control, physical load assessments, employment situation, health and safety concerns (including work-related injury, depression, and physical and chemical exposures), safety climate/culture, training, employer policies, discrimination, and demographics. The final questionnaire was developed in consultation with the entire JWS team of multidisciplinary researchers. The survey topics were designed to identify hazards and characterize outcomes and working conditions, and to supplement the workload assessment component of the study, which includes in-person data collection. Before the survey, we conducted exploratory focus groups (in English and Spanish) with janitors across the state to help inform survey development and identify topic areas.

Validated, existing measures or existing questions were used or adapted where freely available and relevant, including but not limited to: the San Diego Labor Trafficking Survey Questionnaire,57 the NIOSH Quality of Worklife Module, General Social Survey 2010, Section D,58 the NIOSH Generic Job Stress Questionnaire,59, 60 the Job Content Questionnaire,61 and the Everyday Discrimination Scale.62 The work-related injury or illness question (WRII) was adapted from a BRFSS Worker Health Module.63 The question asked: “In the past 12 months, have you been injured while performing work as a janitor, or has a doctor or other medical professional told you that you have a work-related illness?” The questions about WC claim filing were also from the BRFSS Worker Health module.63 Other questions adapted from the BRFSS include those on sleep and self-reported general health.64 Questions on specific geographic origins were adapted from the U.S. Census Bureau's American Community Survey.65 The questionnaire is available upon request.

The questionnaire was pre- and pilot-tested on selected staff, janitors, and finally by interviewers from the survey research company. Pre- and pilot-testing were done with a small group of volunteers running through the questionnaire in-person and over the phone. This iterative process tested the questionnaire's length and question comprehension and answerability. Questions were kept, edited, or discarded based on how they performed in the testing phase and input from the pilot-testers. Both pre- and pilot-testing were done in multiple languages, with edits made for timing, clarity, and cultural sensitivity. The final versions of the questionnaire for use by phone, web, and mailing were approved by the Washington State Institutional Review Board. All staff and interviewers from the survey research firm who had access to personally identifying information were trained and certified on human subjects protection, as well as completing confidentiality, privacy, and nondisclosure training and a project specific briefing.

2.6 Participation and incentive

Completed interviews took a mean length of 62 min (all methods), and median time to complete was 46 min. Telephone mean and median completion times were both around 50 min, but time for completion of the online version of the questionnaire was more varied (77 and 37 min mean and median, respectively). Two response rates and four cooperation rates were calculated, following American Association of Public Opinion Research (AAPOR) standards.66 The response rates were 4.2%–4.5%, primarily due to the influence of cases of unknown eligibility (e.g., line busy, no response to mailing and no phone number, no answer, mailed but no response; n = 11,880 for this category). However, the cooperation rates (which exclude those of unknown eligibility), ranged from 38.9% to 48.6%.

To encourage participation and compensate janitors for the time spent taking the survey, a $15 incentive (in the form of a preloaded Visa card), was provided to participating janitors regardless of how much of the survey they completed. Janitors who wanted to receive the incentive provided their information directly to the survey company, whose staff handled distributing incentives. The authors and JWS staff did not have access to the participants' contact information, which was destroyed after mailing the incentive, or to be destroyed within 1 year of the survey if the respondents gave consent to be contacted again within that time frame.

All participants received informed consent information (available in all languages) and all research activities (questionnaires, incentives, consent documents, scripts, and advertising) were approved by the Washington State Institutional Review Board.

2.7 Data analysis

Throughout this analysis, the results of questions with less than 10 responses are suppressed and analysis was restricted to complete response files only (n = 620; an additional 39 were excluded as partials, and 1 was removed for ineligibility, overall n = 660). Respondents could specify other gender options, but analysis was restricted to male or female because of the small number of other responses. We present the data stratified by gender binary to explore possible differences in WRII and risk factors, as female janitors in WA have been previously shown to have significantly higher injury rates.1 A mutually exclusive race/ethnicity variable (White, American Indian/Alaskan Native, Asian/Pacific Islander, Black, Latino, and More than one race) was used in analysis and was created by combining answers to several questions on race and ethnicity. “Latino” took precedence over racial categories specified when in combinations (e.g., Latino for ethnicity and White for race would be counted as Latino).

Where open text fields were provided for respondents, verbatim responses were collected for coding by the research staff as applicable (e.g., grouping chemicals and cleaning products, common themes for why not filed a WC claim if injured). Body mass index (BMI) was calculated from self-report fields for height and weight (BMI = [kg/m2]), according to the Centers for Disease Control and Prevention (CDC) categories. The Patient Health Questionnaire-267 (PHQ-2) set of screening questions was used to indicate possible depression when the combined score was three or higher.

Descriptive statistical analyses were conducted and are presented to characterize the respondents, work organization factors, and safety and health issues. Exact binomial proportions and 95% confidence intervals (CIs) are presented for these factors by gender binary. Post-hoc analyses of categorical variables were performed using Chi-square tests. Continuous variables (age, BMI, PHQ-2 score, days) were analyzed by means (with 95% CIs) and t tests.

Comparison data for janitors' demographic information were gathered via the NIOSH Employed Labor Force (ELF) query tool using Current Population Survey (CPS) estimates68 for Janitors and Building Cleaners (Bureau of Census (BOC) occupation code: 4220); and the U.S. Census Bureau's Quarterly Workforce Indicators (QWI) tool69 for workers employed in NAICS 5617 Services to Buildings and Dwellings (which includes janitors). While providing useful estimates for comparison, the data in these systems differ in scope from our sample. NAICS-based data (QWI) include other occupations in the same industry, and CPS data include types of workers (e.g., government employees), that our sample would likely not capture. Public-sector janitors included in the CPS may have better wages and protections than workers in contract janitorial firms, such as the majority of those in our sample.

Survey questions selected for this analysis were chosen to provide an overview of major questionnaire topics, to provide items for inclusion in modelling which factors impact WRII risk in this population, and to suggest further analyses. Binary variables were created for WRII (in the past 12 months, as diagnosed by a healthcare professional), gender, annual household income (≥/<$50,000), union membership, having multiple jobs, whether their shifts change, belief that the quality of their tools negatively impacted their job, amount of sleep (greater than or equal to/less than 7 h in a 24-h period), and Patient Health Questionnaire-2 (PHQ-2) score (≥3, or <3). The remaining variables tested in the model were categorical variables (age category, race and ethnicity, marital status, education, tenure, hours worked). Poisson regression with robust variance was used to estimate the relative risk of WRII for janitors, with 95% CIs. Statistical analysis was conducted with SAS 9.4 (SAS Institute Inc.).

3 RESULTS

There were 620 complete response files from Washington State janitors available for analysis. We characterized respondents and explored potential factors involved in WRII risk. Table 2 presents survey information and demographic characteristics of respondents. Of the WA janitors surveyed, over half were female (57%), had worked as a janitor for less than 5 years overall (54%), and made less than $50,000 in annual household income (83%) (Table 2). Almost half (43%) of Janitors were nonwhite (Table 2), and janitors came from at least 30 countries and sovereign Indigenous nations (data not shown).

Table 2. Survey administration and demographic characteristics, Washington state janitors, 2019–2020 Gendera Total Female Male n %, 95% CI n %, 95% CI n %, 95% CI Respondents 620 100 348 57.1 (53.0–61.0) 262 43.0 (39.0–47.0) Survey typeb Mail 388 62.6 (58.6–66.4) 219 62.9 (57.6–68.0) 163 62.2 (56.0–68.1) Phone 142 22.9 (19.7–26.4) 78 22.4 (18.1–27.2) 62 23.7 (18.6–29.2) Web 90 14.5 (11.8–17.5) 51 14.7 (11.1–18.8) 37 14.1 (10.1–18.3) Language administered English 532 85.8 (85.1–90.4) 291 83.6 (79.3–87.4) 232 88.6 (84.1–92.1) Spanish 41 6.6 (4.9–9.1) - 9.8 (7.1–13.8) ≤10 - Vietnamese 32 5.2 (3.7–7.4) 13 3.7 (2.1–6.5) 19 7.3 (4.5–11.3) Somali ≤10 - ≤10 - ≤10 - Chinese-traditional ≤10 - ≤10 - ≤10 - Chinese-simplified ≤10 - ≤10 - ≤10 - Amharic ≤10 - ≤10 - ≤10 - Gender Female 348 56.5 (52.5–60.5) - - - - Male 262 42.5 (38.6–46.6) - - - - Transgender, other, or gender nonconforming ≤10 - - - - - Age categories 18–29 96 17.8 (14.7–21.3) 56 18.3 (14.1–23.1) 40 17.3 (12.7–22.8) 30–39 122 22.6 (19.2–26.4) 80 26.1 (21.3–31.5) 41 17.8 (13.1–23.3) 40–49 95 17.6 (14.5–21.1) 64 20.9 (16.5–25.9) 30 13.0 (8.9–18.0) 50–59 106 19.7 (16.4–23.3) 62 20.3 (15.9–25.2) 44 19.1 (14.2–24.7) 60+ 120 22.3 (18.8–26.0) 44 14.4 (10.7–18.8) 76 32.9 (26.9–39.4) Mean years (95% CI) 45 (43.8–46.3) 42.8 (41.3–44.2) 48.1 (46.1–50.1)

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