Incidence, risk factors, and outcomes of non-fatal work-related injuries among older workers: A review of research from 2010 to 2019

Safety Science 126 (2020) 104668

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Incidence, risk factors, and outcomes of non-fatal work-related injuries among older workers: A review of research from 2010 to 2019

T

Brenda Stoesza, Katherine Chimneyb, Connie Dengc, Harrison Groganb, Verena Menecb, ⁎ Caroline Piotrowskib, Shahin Shooshtarib, Nick Turnerc, a

The Centre for the Advancement of Teaching and Learning, University of Manitoba, Winnipeg, Canada Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada c Organizational Behaviour and Human Resources and Canadian Centre for Advanced Leadership in Business, Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada b

ARTICLE INFO

ABSTRACT

Keywords: Age Aging Occupational injuries Older adults Risk factors Work-related injuries

We reviewed the literature on older workers and work-related injuries published between 2010 and 2019. A review of empirical research during this period yielded 63 original research articles meeting the inclusion criteria. Across these studies, we found differences in work-related injuries among older workers by occupation, and differences in attention paid to modifiable risk factors, non-modifiable risk factors, and outcomes of workrelated injuries among older workers. In general, compared to younger workers, the incidence of work-related injuries was lower among older workers, yet older workers endured more severe and more costly work-related injuries. Taken together, this review highlighted factors for consideration in the prevention of work-related injuries among older workers.

1. Introduction

focused on discrete age ranges along with industry-specific foci, such as nursing (e.g., Phillips and Miltner, 2015; Stichler, 2013), mining (e.g., Kowalski-Trakofler et al., 2005; Margolis, 2010), construction (e.g., Schwatka et al., 2012), and agriculture (e.g., Tonelli et al., 2014). These reviews demonstrated unique challenges and needs for older workers in each specified industry. For example, Phillips and Miltner (2015) reported increased fatigue and loss of functional ability as work-related problems among older nurses. These concerns parallel in research examining the construction industry, which identified how working long hours in draining, high-stress environments took a physical toll on older adults and increased their injury risk (Schwatka et al., 2012). Finally, in a review investigating musculoskeletal (MSK) injuries of agricultural workers, long working hours were linked with increased occupational injury risk for older farmers (Tonelli et al., 2014). Taken together, these reviews suggest that older workers in various industries may be more susceptible to injury due to factors such as long work hours, fatigue, and decreased functional ability. Although useful, these reviews did not provide a comprehensive examination of injury rates, risk factors, and outcomes for older workers across a range of industries. To address these gaps, we conducted the current review on the incidence, risk factors, and outcomes of all types of work-related injuries among older adults across all industries documented in research published in English during the past

As the Canadian population ages, the number of older adults, typically defined as those 65 years of age or older, is increasing. In 2016, 5.9 million older adults in Canada constituted 16% of the population (Statistics Canada, 2016); by 2036, the number of older adults is expected to increase to 10 million or 25% of the Canadian population (Statistics Canada, 2010). Not only are the number and proportion of older adults in the population increasing, they are also healthier, and living and working longer. Accordingly, the labor force participation rate for older adults in Canada has increased significantly over the last decade. In 2003, 16% of adults aged 65–69 years were participating in the labor force; however, this proportion increased to 26% by 2016 and has continued to increase (Employment and Social Development Canada, 2018). According to the 2016 Census, 5.9% of older adults in Canada worked all year on a full-time basis during 2015; this was the highest level since 1981 (Statistics Canada, 2017). These trends of older, healthier adults remaining longer in the working population are also found in other large developed countries (Dobriansky et al., 2007). Given this significant and growing presence in the workforce, the health and safety of older workers is of growing importance (Koukoulaki, 2010; Papadopoulos et al., 2010). Past literature reviews concerning work-related injuries among older workers have often ⁎

Corresponding author. E-mail address: [email protected] (N. Turner).

https://doi.org/10.1016/j.ssci.2020.104668 Received 30 March 2019; Received in revised form 19 December 2019; Accepted 11 February 2020 0925-7535/ Crown Copyright © 2020 Published by Elsevier Ltd. All rights reserved.

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ten years. This broader perspective will enhance our current knowledge regarding this rapidly growing age group of workers in Canada and beyond.

factors for injury, and outcomes of injury.

2. Methods

3.1. Study location and population characteristics

2.1. Search strategy

Thirty of the reviewed articles featured studies conducted in the United States (US), 10 in Canada, 6 in Australia, 4 in Korea, 2 in Sweden, and one each in Egypt, France, Ireland, Japan, the Netherlands, New Zealand, Portugal, Spain, Switzerland, Turkey, and the United Kingdom (UK). These studies investigated work-related injuries experienced by older adults in a large range of sample sizes including small groups of only 9 participants (Caffaro et al., 2018) to as large as 5,104,179 participants (Bande and López-Mourelo, 2015). The average sample size across the 63 articles was 156,479 participants. Forty-nine studies examined injuries in workers aged 45+ years. Six studies included workers aged 45–64 years (Çağlayan and Etiler, 2015; Chen et al., 2017; Mehta and Agnew, 2010; Pliner et al., 2014; Scott et al., 2018b; Welch et al., 2010). Four studies included workers aged 55+ years (Doan et al., 2014; Harrison et al., 2013; Lilley et al., 2018; Wilkie et al., 2011). Three studies restricted their investigation to workers aged 45–54 years (Chau et al., 2014; Sousa and Ramos, 2018; Unruh and Asi, 2018) and one to 65+ years (Caffaro et al., 2018). Thirty-nine studies examined injury information for both women and men, 5 studies focused on men only (Caffaro et al., 2018; Guest et al., 2014a; Kim and Jeong, 2018; Park and Jeong, 2018; Sousa and Ramos, 2018), and 3 focused on women only (Chau et al., 2014; Chen et al., 2017; Harrison et al., 2013). Sixteen studies did not report the sex distribution of their samples.

3. Results

We conducted a systematic literature search in online databases Scopus, and OSHLINE, HSELINE, NIOSHTIC, NIOSHTIC-2, CANADIANA, and CISILO on 17 September 2019. We used the following set of terms and descriptors in the search query: (1) work or occupation; and (2) wound or injury or accident; and (3) older worker or aging or aged worker. We entered these terms and descriptors using Boolean operators (AND, OR), with additional database search tools (e.g., proximity operators, truncation, and filters) as appropriate, and in quotation marks for multiple word phrases to limit excessive irrelevant information. The search query was restricted to peer-reviewed original research articles published in English from 2010 to the date of the search. 2.2. Selection of studies During the screening phase, we included articles for full text review if the titles and abstracts contained the following details: (1) information about the incidence, risk factors, and/or outcomes of work-related injuries; and (2) the study focused on workers aged 40 years and older. Although there is no commonly recognized age to define the older worker, we defined older workers as individuals of at least 40 years of age. Our choice for a lower age to define older workers is supported by several lines of research. For example, research using worker compensation data in the construction industry by Schwatka et al. (2013) revealed that workers’ compensation and medical costs grow with increasing age until 35–44 years, when costs begin to plateau. Moreover, compared to occupations with lower physical strain and higher job control, occupations with high physical demands (e.g., manual jobs) and low job control have an aging effect equivalent to 6–16 months for workers aged 49 years and older who have been in that occupation for at least one year (Ravesteijn et al., 2018). Taking these observations together, we adopted a lower age cut-off to ensure that relevant articles remained in our review. We also included studies for full text review if the abstract was unavailable or if there was uncertainty in making an inclusion judgment based on the title and abstract only. We excluded studies that focused exclusively on occupational diseases, occupational fatalities, or workers under the age of 40 years. We exported the citations and abstracts of 219 records resulting from the database searches. After removing 17 duplicates, we reviewed the titles and abstracts of 202 records to determine their suitability for full-text review: 118 records were excluded because they did not meet our inclusion criteria (i.e., age range < 40 years; not focused on injuries; focused on fatalities; not original research). We retrieved the remaining 84 full-text articles for data extraction. During the data extraction process, we further excluded 34 articles for the reasons listed above. Hand searches of the reference lists of the 50 articles that met our inclusion criteria suggested that 4 articles met our inclusion criteria based on their titles; however, only 2 were retained. Moreover, we reviewed 18 articles from the author’s personal collections and 11 met inclusion criteria. Thus, we extracted and synthesized data from 63 articles for this review. Fig. 1 summarizes the article selection procedure in a PRISMA flow chart.

3.2. Research methods and designs Fifty-seven studies were quantitative and six used mixed methods (i.e., Caffaro et al., 2018; Dimitriadis et al., 2017; Harrison et al., 2013; Lombardi et al., 2011; Muramatsu et al., 2018; Sousa and Ramos, 2018). None of the studies used qualitative methods only. In terms of research designs, 32 studies were identified as longitudinal, 28 as crosssectional, and 3 were experimental (Chen et al., 2017; Mehta and Agnew, 2010; Pliner et al., 2014). 3.3. Industry We classified the reviewed studies according to the industry categories published by Innovation, Science and Economic Development Canada (Government of Canada, 2018). Thirty-three studies did not focus their investigation on any one industry (see Table 1). Of those that examined injuries within a specific industry category, one focused on administrative and support, waste management and remediation services; seven on agriculture, forestry, fishing, and hunting; ten on construction; five on healthcare and social assistance; one on mining, quarrying, and oil and gas extraction; two on public administration; and four on transportation and warehousing (see Table 2). 3.4. Injury types We classified the injuries reported in the studies into ten categories based on previous work addressing injuries across all occupations conducted in Canada (Smith et al., 2013) and the United States (Wuellner et al., 2011); in addition, other categories were added such poisoning, burns, damage to internal organs, and other. Twenty-two of the reviewed studies reported on any/all types of injuries. Thirty-three studies reported on MSK injuries; 12 reported on open wounds (e.g., cuts, bites, bruises); 5 on fractures and breaks; 5 on burns; 2 on intracranial injuries; and three on other types of injuries (e.g. psychological). Seven studies did not report on the types of injuries reported.

2.3. Data extraction The data extracted from the 63 articles included author(s), publication year, country, and size, age ranges, and gender of study population. Additional fields captured information related research methods and designs, industry, injury type, incidence of injury, risk 2

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Fig. 1. Systematic review flow diagram. The PRISMA flow diagram (Moher et al., 2009) for the systematic review details the results of the database searches, the number of subtracts screened, the full texts retrieved, and the final number of articles included in the synthesis of the peer-reviewed original research.

age of 25 years, which dropped to 8.5 per 1000 for those aged 45–55 years. Workers under 25 years of age were at higher risk for all types of injuries, whereas those aged 45–55 years had a higher risk only for same-level falls and falling to a lower floor. Wang et al. (2017) reported an inverted U-shaped pattern such that workers aged 35–44 years and 45–54 years had higher rates of MSK injuries (51.3 and 50.8 per 10,000 full-time equivalent [FTE], respectively) than those aged 65 years and older (14.1 per 10,000 FTE). Although occupational injury rates for older workers have been reported as lower than those among younger workers overall, there were exceptions. For example, Lilley et al. (2018) examined work-related injury incidence rates in workers older than 55 years in New Zealand and presented the rates into 5-year age groups. The rate for 55–59-year-old workers was 8.4 per 1000 FTE; the rate increased linearly with age to 14.1 per 1000 FTE for 70–79-year-olds. Increases in injuries for the oldest workers is more striking in the agriculture, forest, fishing, and mining sectors, followed by mining, construction, and manufacturing sectors. Smith and Berecki-Gisolf (2014) found the claim

3.5. Incidence and risk factors Thirty-nine studies provided information about the incidence of injuries and 61 studies provided information about modifiable (e.g., physical demands, job control, work accommodation) and non-modifiable (e.g., age, gender, physical functioning, occupation) risk factors. When all injuries and industries are considered, the reported injury rates were between 7.54 per 1000 worker years (Berecki-Gisolf et al., 2012) and 22 per 1000 worker years (Fraade-Blanar et al., 2017). An important difference between these studies was that the former included all ages of workers, whereas the latter studied only those workers who were aged 50+ years. In both studies, however, workers older than 55 years of age were less likely than younger workers to be injured. Similar findings that older age was associated with a drop in injury rates were reported in other studies (Chau et al., 2014; Guest et al., 2014b; Konda et al., 2015; Konstantinidis et al., 2011; Mallon and Cherry, 2015; Wang et al., 2017). For example, Chau et al. (2014) found that the peak injury rate was 29.9 for female railway workers under the 3

4

Turkey

US

Ireland

Australia

Chen et al. (2013)

Collins and O’Sullivan (2010)

Dimitriadis et al. (2017)

Australia

Berecki-Gisolf et al. (2012)

Çağlayan and Etiler (2015)

Spain

Bande and LópezMourelo (2015)

Canada

US

Baidwan et al. (2019)

Breslin et al. (2011)

US

Baidwan et al. (2018)

US

Canada

Algarni et al. (2015)

Besen et al. (2016)

Study location

First author (year)

869 (men & women)

332 (men & women)

1,182,400 (men & women) 4431 (men & women) 184,300 (men & women)

361,754 (men & women)

59,525 (NR)

3305 (men & women) 5,104,179 (NR)

7212 (NR)

8003 (NR)

N (gender)

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+ 45–54 55–64

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+ 45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

Age range (years)

Study Population

Longitudinal (3 waves)

Cross-sectional

MSK; psychological

MSK

MSK

Any

Cross-sectional Cross-sectional

Any

Retrospective longitudinal

Any

Any

Retrospective longitudinal Retrospective longitudinal

Any

Any

Any

MSK

Injury type

Retrospective longitudinal

Retrospective longitudinal

Retrospective longitudinal

Cross-sectional

Research Design (data collection waves)

Accidents in last 12 months: 25–44-yrs: 3.0% 45–64-yrs: 2.5% Knee injuries: 5% of all injuries; 13 per 10,000 FTE; 15–19 yrs = 23 (men), 15 (women) ≥50 yrs = 8 lowest prevalence in the youngest group (both genders), followed by marked increases with age. 41–50-yrs women reported higher symptom rates (84%) than men (67%) Percent of claims: 18–24 yrs = 6% 25–34 yrs = 18% 35–44 yrs = 23% 45–54 yrs = 31% 55+ yrs = 21%

NR

NR

Lost time claims: 7.54 per 1000 worker years

Severe injuries: < 39 yrs: 0.04% < 65+ yrs: 0.27%

4.6% experienced work-related injuries during 2008–2014

5% experienced work-related injuries in 2004

NR

Incidence

Table 1 Reviewed Studies Concerning the Incidence, Risk Factors, and/or Outcomes of Work-related Injuries across Various Industries.

(continued on next page)

80% and 90% of claimants no longer receiving wage replacement at 6 and 12 months, respectively.

Women’s mental health decreased linearly with age. For males, the oldest age group experienced the poorest mental health.

age (younger > older); gender (men: job demands vs. women: psychosocial risks); work environment; job content age; job tenure; hours per work week

2% of knee injuries resulted in hospitalization

Older (vs younger) workers' injuries were more likely to be severe or fatal. Number of lost working days due to occupational injury increased with age. Number of workdays compensated increased with age until 50–59 yrs; after age 60 yrs, the number of compensated days declined. Relationship between age and length of disability strengthened until age 70 yrs. Highest predicted length of disability was for the oldest workers with high tenure and shortest for younger workers with the lowest tenure. Consistent decline in the monthly lost-time claim rates during 1991–2007 among 35+ yr-olds. Older workers had lower absenteeism.

65+ yrs less likely to have modified work available or be offered rehabilitation; had more days between injury and assessment. Healthcare cost before assessment was largest for 55–65 yrs. Injured (vs. uninjured) aging workers more likely to experience new functional limitations and to work reduced hours. NR

Outcomes

age (younger > older); gender

no age differences

industry; job tenure

gender (men > women)

age; gender (women > men for 50+ yrs); highest rate was for 45–55-yrs

age; Caucasian; transportation and professional/ technical service industry; full time employment; physically demanding; chronic health condition; depression age; Caucasian/non-Hispanic; US born; blue-collar occupations (men); high vs low demands; high effort-reward imbalance age; certain worker physiological characteristics; seniority/experience

age (older > younger); lower education levels; marital status; working in trades, transport, and related occupations

Risk Factors for Injury

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Japan

Korea

Korea

US

Park et al. (2012)

Park et al. (2017)

Pliner et al. (2014)

US

Konda et al. (2015)

Nakamura et al. (2011)

US

Harrison et al. (2013)

New Zealand

US

Fraade-Blanar et al. (2017)

Lilley et al. (2018)

Australia

Fan et al. (2016)

US

Canada

Doan et al. (2014)

Konstantinidis et al. (2011)

Study location

First author (year)

Table 1 (continued)

5

32 (men & women)

785 (men & women) 30,751 (men & women)

34,217 (NR)

25,455 (men & women)

67,658 (NR)

9200 (men & women)

5586 (men & women) 122 (women)

1044 (men & women) 78,465 (men & women)

N (gender)

45–54 55–64

45–54 55–64 65+ 45–54 55–64 65+ 45–54 55–64 65+

55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+ 55–64 65+

45–54 55–64 65+

55–64 65+

Age range (years)

Study Population

Experimental

Cross-sectional

Cross-sectional

Cross-sectional

Retrospective longitudinal

Retrospective longitudinal

Retrospective longitudinal

Longitudinal (2 to 4 waves)

Longitudinal

Longitudinal

Cross-sectional

Research Design (data collection waves)

NR

Any

NR

NR

Any

Any

Intracranial

MSK, fractures, open wounds, burns

Intracranial, MSK, fracture, open wounds, burns, other Any

MSK, soreness/pain

Injury type

Injury due to accident: < 55 yrs = 1.1% 55+ yrs = 1.4% Soreness/pain: < 55 yrs = 10.3–25.6% 55+ yrs = 16.7–36.2% NR

42.4% of sample had experienced an accident; 57.6% had not

Proportion per age group: 16–35 yrs = 40.1% 36–55 yrs = 44.5% 56–65 yrs = 9.8% 65+ yrs = 5.7% Claim rate per 1000 by age: 55–59 yrs = 8.4 60–64 yrs = 8.7 65–69 yrs = 9.5 70–79 yrs = 14.1 NR

4.3 per 10,000 FTE

105.7 per 10,00 FTE

22 per 1000 person-years

NR

NR

Incidence

age (18–24 and 45–64-yr-olds slipped more than 24–44-yr-olds); constrained foot placement on ladders

age; accident type (60+ yrs had more falls than other accident types; proportions of each accident type is similar for 10–30 yrs) age (30–49-yrs > 50+ yrs > 20–29-yrs); gender (men > women); experience (more job experience associated with more accidents) age; occupation × type of injury

age; gender (males > females); job demands (lifting, carrying); work site conditions (especially for 70–79-yr-olds); presence of animals

age (younger > older, but older > younger for specific injuries); machinery use

age (younger > older); gender (men > women); industry (construction > agriculture, forestry, fishing, and hunting > transportation and warehousing; arts and entertainment)

Annual and point prevalence of discomfort amongst bridge employed adults (Mage = 67 yrs) > fully retired adults (Mage = 71 yrs). age (men: younger > older); injury type (younger workers a higher prevalence of open wounds/ burns, middle age groups had a higher prevalence of chronic MSK. age (middle > older); job demands (lifting, kneeling); industry; working full-time; physical ability age; accumulation of multiple stressors; poor decisions; risky work site

Risk Factors for Injury

NR

NR

(continued on next page)

A greater proportion of older workers are absent from work due to having an accident than younger workers. NR

NR

Several important systemic barriers to treatment and assistance related to poorer outcomes after workplace injury. Critical point in functional limitation, pain, and mental distress signaled end of employment. 10% of injured workers were hospitalized. The overall rate of nonfatal traumatic head injuries increased by an average of 0.21 per 10 000 FTE per year from 1998 through 2007 (p < 0.0001). Severity of injury increased significantly with age.

NR

Older age was associated with greater days of wage replacement. No age differences in severity of injury.

NR

Outcomes

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6

Canada

Australia

US

Smith and BereckiGisolf (2014)

Steege et al. (2014)

Canada

Smith et al. (2013)

Smith et al. (2014c)

Canada

Smith et al. (2012)

Canada

US

Sears et al. (2017)

Smith et al. (2014b)

Canada

Scott et al. (2018b)

Canada

US

Scott et al. (2018a)

Smith et al. (2014a)

Study location

First author (year)

Table 1 (continued)

220,000 (men & women)

118,044 (NR)

373,672 (men & women)

87,968 (men & women)

156,879 (men & women)

389,725 (men & women)

79,114 (men & women)

4,610 (men & women) 67,236 (men & women)

230,000 (men & women)

N (gender)

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64

45–54 55–64 65+

Age range (years)

Study Population

Retrospective longitudinal

Cross-sectional

Retrospective longitudinal

Retrospective Longitudinal

Retrospective Longitudinal

Retrospective longitudinal

Cross-sectional

Retrospective longitudinal

Retrospective longitudinal

Cross-sectional

Research Design (data collection waves)

Any

MSK; non-MSK

Any

MSK

MSK

Any

Any

Any

Any

NR

Injury type

MSK, non-MSK (rate per 1000 FTE) 25–34 yrs: 5.52, 1.06 35–44 yrs: 8.37, 1.39 45–54 yrs: 10.33, 8.08 55+ yrs: 11.00, 11.56 NR

NR

NR

Proportion per age group: 15–24 yrs = 2.2% 25–34 yrs = 3.2% 35–44 yrs = 2.6% 45–54 yrs = 2.3% 55+ yrs = 1.9% Rate/1000 FTE: (men, women) 15–24 yrs = 66.5, 27.7 25–34 yrs = 61.5, 25.6 35–44 yrs = 61.3, 33.8 45–54 yrs = 52.9, 33.5 55+ yrs = 54.0, 35.9 NR

NR

Same-level fall injury rates per 10,000 FTE: 25–34 yrs = 5.7 (manufacturing) 65+ yrs = 39.9 (health care and social assistance); 34.2 (retail trade) N/A

Incidence

gender (men > women); Black; education; foreign-birth; low-wages jobs; industry (Agriculture, forestry, and fishing; mining; transportation and warehousing)

age (older > younger for non-MSK injuries; job demands (especially for 45+ yrs)

age (older > younger); job demands; industry

age; pre-existing chronic condition

depression (women); balancing family responsibilities with rehabilitation (women)

gender (men > women); injury type (older > younger - fractures; younger > older open wounds); industry (i.e., goods-handling); higher physical demands; work environment

age; gender (men > women); presence of chronic conditions

NR

age; job demands (manual tasks)

age; industry; gender (women > men)

Risk Factors for Injury

NR

(continued on next page)

Relationship between age and length of work absence was stronger for men than women. Indirect effects between age and days absent from work. Older age associated with increasing healthcare expenditures. Women: expenditures plateaued at 45–54 years. Men: expenditures were greatest for 55+ yrs. Health care expenditures, days of wage replacement, and % of longterm disability claims were higher for 50+ yrs than < 50 yrs; and higher in medium/heavy strength occupations compared to light/ limited strength occupations. NR

NR

Earlier retirement was more likely as age, injury severity, and job demands increased. Costs associated with (severe) industrial injuries in 65+ yr-olds and women were more likely to be billed to a non-workers' compensation (WC) payer, such as Medicare. NR

NR

Outcomes

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Any Longitudinal (2 waves) 55–64 65+ UK Wilkie et al. (2011)

3004 (men & women)

Age range (years) N (gender)

Notes: FTE = full-time equivalent; FTEWB = full-time week-based equivalents; MSK = Musculoskeletal, NR = not reported.

Work limitations increased over time and with age. Return to work problems were associated with increases in work limitations for those with job lock (retirement prevention strategy); greater increases were associated only with low education in those without job lock. age; education NR

Outcomes Risk Factors for Injury Incidence Injury type Research Design (data collection waves) Study Population

Study location First author (year)

Table 1 (continued)

rates for injuries for workers aged 55+ years was nearly double that of workers aged 25–34 years; although the relationship between occupational demands (classified using the Canadian National Occupational Classification system; specific industries were not reported) and the risk of serious work injury held for all ages, it was strongest for younger workers. Not only are higher job demands associated with particular occupations (i.e., agriculture, forestry, fishing, and hunting; construction; mining, quarrying, and oil and gas extraction; and transportation and warehousing; Baidwan et al., 2018, 2019) and greater risk for occupational injury for older workers, lower physical ability combined with higher job demands contribute to higher rates of occupational injuries (Fraade-Blanar et al., 2017). Increased injuries in older adults may also be the result of specific circumstances leading to specific types of injuries. For example, older workers were at greater risk of slips, trips, and falls than younger workers in several studies (e.g., Chau et al., 2014; Lombardi et al., 2011; Muramatsu et al., 2018; Pliner et al., 2014; Scott et al., 2018a). Chau et al. (2014) reported that female railway workers aged 45–55 years experienced higher injury rates as a result of falls than those under the age of 25 years even though the overall injury rate decreased with age. In a study examining fall incidence rates available in a nationally representative US dataset, injury rates increased with increasing age across all four industries: healthcare and social assistance, manufacturing, retail trade, and transportation and warehousing (Scott et al., 2018a). The rates often more than doubled and differed between men and women. Specifically, the sharpest increases in incidence rates with age occurred for women. For example in the healthcare and social assistance industry, the injury rates for women jumped from 13.9 per 10,000 FTE for ages 25–35 years to 49.9 per 10,000 FTE for 65+ years; however, the injury rate increase for men in the same industry was less dramatic at 7.6 per 10,000 FTE for ages 25–34 years to 18.2 for ages 65+ years. Similar patterns were evident for the other three industries examined. Finally, Nilsson, Pinzke, and Lundqvist (2010) studied the risk of occupational injury for older workers in the agriculture industry and found that older farmers experienced a greater risk of skeletal injuries, more hits and kicks by animals, and had a higher risk of motor vehicle crashes than younger age groups. 3.6. Outcomes Forty-one studies provided information about outcomes as a result of injury, including costs associated with the care of injury, hospitalizations, days absent from work, forced early retirement, and poor rehabilitation. In general, the outcomes of work-related injuries for older workers differed from those of younger workers. For example, costs per injury were higher for older workers. Mallon and Cherry (2015) investigated the relationship between age and median costs of occupational injuries in US Department of Defense employees and found that the likelihood that an individual’s injuries exceeded the median cost increased with increasing age; specifically, the injuries of workers aged 65–70 years were three times more likely to exceed median costs compared to workers aged 18–24 years. Schwatka et al. (2013) found similar results in the construction industry, reporting the lowest mean costs for workers aged 18–24 years at $4,899 per injury with costs increasing in a stepwise fashion with each older age group and finally peaking at $14,253 per injury for workers aged 65+ years. Pre-existing chronic health conditions, such as osteoarthritis and coronary heart disease, exacerbated costs of occupational injuries in older workers (Smith et al., 2014b). Hospitalization data for occupational knee injuries demonstrated that older workers often experience more severe injuries than do their younger counterparts. Chen et al. (2013) used data from emergency services for occupational knee injuries in the US. Among men, the rate of occupational knee injuries did not increase with age; however, for women, the rate increased from 10 per 10,000 for those aged 7

Study location

N

Age range (years)

Study Population

Research Design

8

Canada

US

Switzerland

Australia

Construction Chen et al. (2017)

Choi (2015)

Frickmann et al. (2012)

Guest et al. (2014b)

Egypt

US

Weigel and Armijos (2010)

Zytoon and Basahel (2017)

US

Tonozzi and Layne (2016)

US

Sweden

Nilsson et al. (2010)

Weigel et al. (2014)

US

Heaton et al. (2010)

782 (men & women) 709 (NR)

24 (women) 143 (NR)

686 (NR)

177 (men & women)

19,377 (men & women) 141 (men & women)

756 (men & women) 5062 (men & women)

Agriculture, Forestry, Fishing, and Hunting Caffaro et al. (2018) Sweden 9

45–54 55–64 45–54 55–64 65+ 45–54 55–64 65+ 45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+ 45–54 55–64 65+

45–54 55–64 65+ 45–54 55–64 65+

65+

Retrospective longitudinal

Longitudinal

Retrospective longitudinal

Experimental

Cross-sectional

Cross-sectional

Retrospective longitudinal (2 waves) Cross-sectional

Cross-sectional

Cross-sectional

Cross-sectional

Administrative and Support, Waste Management and Remediation Services Kim and Jeong (2018) Korea 831 45–54 Cross-sectional (men) 55–64 65+

First author (year)

MSK, open wounds, burns

Any

MSK

MSK

MSK, fractures, open wounds, burns

MSK

MSK, fractures, open wounds MSK, fractures, open wounds

MSK, open wounds

Cuts, burns, MSK

MSK

MSK

Injury type

Claim rates per 100 person-yrs (2001–2004): < 30 yrs = 4.8 30–39 yrs = 4.5 40–49 yrs = 3.1 50+ yrs = 3.2

NR

NR

NR

NR

81% of sample

Injury frequency: < 49 yrs = 4% 50–59 yrs = 5% 60+ yrs = 4% 1999, 2002–2004 = 4.3/100 per FTEWB 2008–2010 = 2.9/100 per FTEWB Knee and back injuries most common (40–50% of sample).

11.1% of sample

67% of sample

60–69 yrs accounted for 62% of all injuries; 70+ yrs accounted for 25% of all injuries

Incidence

Table 2 Reviewed Studies Concerning the Incidence, Risk Factors, and/or Outcomes of Work-related Injuries by Industry.

age (younger > older)

age; foreign workers (more cases in each age group)

age; maximum acceptable weight of life (i.e., liftmax was 23.8% lower for older than younger workers) age; trade/occupation (i.e., laborers, carpenters, iron workers, and operators)

age (younger > older > middle); experience; sea sickness; weather conditions; accident type; job stress (younger > older)

age (middle-aged and elderly > younger); gender (men > women); job demands (e.g., heavy lifting tasks; prolonged bending, stooping, and other awkward postures) age; sex; job demands; presence of diabetes

age (older > younger): experience; pesticide handling; job demands

working with animals (older > younger); moving vehicles and machines; falling/flying or sharp objects

risky tasks; poor visual conditions; extreme fatigue; using equipment designed for other tasks; age (as related to slower reaction times, lower attention thresholds, underestimation of risks) number of workdays; gender (men > women); arthritis/rheumatism; sleep apnea; sleepiness

action, perceptual, and cognitive errors; facility or tools failure, third-party violence, and vehicle accidents; work environment; shift work

Risk Factors for Injury

NR

(continued on next page)

Severity of injury greatest in workers aged 60+ yrs

NR

NR

Average of 2.9 ± 2.3 different injury events resulting in pain lasting 5–8 weeks, depending on injury. Fewer than 25% of injured workers received medical treatment. NR

Persistent pain, functional impairment, disability, poor quality of life.

79% sought medical help. 60+ yrs took more days off work. Workers aged 60+ yrs did not apply for sick benefits due to ineligibility related to age. In period II, 85% of the injuries required treatment.

NR

NR

NR

Outcomes

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Netherlands

US

US

US

US

Hoonakker and Van Duivenbooden (2010)

Mehta and Agnew (2010)

Schwatka et al. (2013)

Wang et al. (2017)

Welch et al. (2010)

9

US

US

Ranzenberger et al. (2016)

Unruh and Asi (2018)

11,204 (men & women) 414 (men)

741 (NR)

263 (men & women)

979 (NR)

22 (men & women) 107,064 (men & women) 328,620 (NR)

288,140 (NR)

N

US

Korea

Public Administration Mallon and Cherry (2015)

Park and Jeong (2018)

432 (men)

142,115 (men & women) 45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64 65+ 45–54

45–54 55–64 65+

45–54 55–64 65+

45–54 55–64

45–54 55–64 65+ 45–54 55–64 65+

45–54 55–64

45–54 55–64 65+

Age range (years)

Study Population

Mining, Quarrying, and Oil and Gas Extraction Margolis (2010) US 10,345 (NR)

US

Muramatsu et al. (2018)

Health Care and Social Assistance Dropkin et al. (2019) US

Study location

First author (year)

Table 2 (continued)

Cross-sectional

Cross-sectional

Retrospective longitudinal

Cross-sectional

Cross-sectional

Cross-sectional

Cross-sectional

Longitudinal (2 waves)

Retrospective longitudinal

Retrospective longitudinal

Experimental

Cross-sectional (6 waves)

Research Design

MSK, open wounds

All

NR

MSK, open wounds

All

MSK

MSK

MSK

MSK

MSK, open wounds

MSK

MSK

Injury type

88.7% of all injuries occurred in workers 60+ yrs

Overall rate: 286 per 10,000 defense workers; highest number in 50–54-yrs, lowest in 70+ yrs

NR

verbal violence (70%), open wounds (49%), MSK (40%)

NR

NR

64.6% had at least one workrelated injury requiring medical care

Rate per 10,000 FTE: 35–44 yrs = 51.3 45–54 yrs = 50.8 65+ yrs 14.1 35.9% had an MSK disorder; 30.8% had an MSK disorder and medical condition

NR

Percent of age group with workrelated injury: < 20 yrs: 6.2% 20–24-yrs: 6.1% 25–29 yrs: 5.1% 30–34 yrs: 54.4% 35–44 yrs: 4.8% 45–54 yrs: 4.5% 55+ yrs: 4.3% NR

Incidence

work environment, weather (slips, trips, falls)

age (younger > older); gender (males > females)

NR

age (needlesticks: older > younger; other open wounds: older < younger); gender (men < women); African American; education; experience; job demands

age (younger < older); gender (women > men); patient care (direct > indirect)

age [older vs younger workers had 9% greater likelihood of injury (PR = 1.09, 95% CI = 0.92–1.29)];experience (working < 5 yrs was protective); vehicle crashes; perception that fitness testing was unimportant Risk of trips, slips, falls: age (younger < older); working conditions (ice, clutter); workload; fatigue; education/training

Predictors of premature departure from workforce: age; lower physical functioning; work limitations; absenteeism

age (younger < older, until 55 yrs, then declined); occupation

age × fatigue (younger > older); gender × fatigue × age (younger men > younger women > older) age (younger > older); gender (men > women)

age (older < younger); awkward postures

Risk Factors for Injury

(continued on next page)

Cost per claim for all ages = $654; 18–24yr-olds had lowest median cost ($286), which increased by $69 for each 5-year age group. NR

Age and experience influenced the severity of injury and days absent from work following injury.

NR

EMS personnel with greater than moderate pain severity had a 50% higher prevalence of lost workdays than those with mild to moderate pain severity (PR = 1.50, 95%CI = 1.10–2.06). While serious falls were rare, older HCAs in particular reported exacerbation of underlying arthritis and subsequent fear of falling. NR

Among the 78 roofers who left roofing, 60% reported they did so for healthrelated reasons.

Estimated wage loss due to injury was as much as $46 million in 2014.

Costs associated with an injury generally increased with increasing age until 35 yrs

NR

Absenteeism of older (vs. younger) workers due to injury is significantly lower.

Outcomes

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53% of accidents resulted in 10 absent days from work; 7% resulted in > than 100 days absent.

25–34 years to 15 per 10,000 for those aged 50–54 years. Injury Severity Scores (ISS), a scoring system based on severity of injuries in six body systems (ranging from 1 to 75), also show that older workers experience more severe injuries than younger workers (Frickmann et al., 2012; Konstantinidis et al., 2011). An investigation on severe injuries (i.e., contusions, fractures, sprains, cuts) in the construction industry in Switzerland revealed that the median ISS was 4 for all workers below 60 years of age, but 9 for workers older than 60 years (Frickmann et al., 2012). Using data from the US National Trauma Databank, Konstantinidis et al. (2011) calculated mean ISS scores for occupational injuries, which showed an increasing trend with age. Specifically, mean ISS scores were 8.9 for workers aged 16–35 years, 9.4 for workers aged 36–55 years, 10.4 for workers aged 56–65 years, and 11 for workers aged 65+ years. The authors also reported that workers aged 65 years and older were more likely to sustain intracranial injuries requiring craniotomies or craniectomies, and experiencing rib fractures, and internal organ and spinal injuries. In contrast, Fan et al. (2016) did not find age differences in severity of injuries (as determined through two administrative outcomes: requiring in-patient hospital care and amount of health care expenditure), and suggested that longer return to work durations may be due to factors related to differences in the healing process across age groups. The articles we reviewed did not examine the healing process after a work-related injury directly, however, several reported the mean number of lost working days or compensated days per age group, which generally increased with increasing age. Berecki-Gisolf et al. (2012) found that Australian workers younger than 50 years were compensated for an average of 55 lost work days, whereas those aged 50 years or older were compensated for an average of 74 lost work days. In a Spanish study, workers aged 16–24 years had an average of 17.3 nonworking days due to injuries compared to an average of 36.6 nonworking days for workers aged 65 years and older (Bande and LópezMourelo, 2015). Besen et al. (2016) found similar results in the US, with an average length of 32.3 days post-injury disability for 18-year-olds compared to 50.9 days for 80-year-olds. These results suggest then injuries become more severe and/or require more healing time with increasing age. Older workers may also have fewer opportunities for treatment and rehabilitation after experiencing work-related injuries. Algarni et al. (2015) found that older workers were less likely to receive rehabilitation after an injury assessment compared to their younger counterparts. In that study, 18% of injured workers aged 25–54 years did not receive rehabilitation, whereas 28% of the population of injured workers aged 65+ years did not receive rehabilitation. Further examination of the profile of these older workers revealed that they were more likely to be over retirement age, have lower education levels, and to receive wage replacement benefits, but were less likely to be currently working or have modified work available, and reported poorer physical functioning. Slower recovery due to lack of treatment may have additional consequences. For example, Scott et al. (2018b) examined early retirement after a permanent impairment; they found that the proportion of workers who retired compared to those who did not retire after permanent impairment increased with increasing age.

US

Portugal

Heaton et al. (2017)

Sousa and Ramos (2018)

23 (men & women) 16 (men)

Australia Guest et al. (2014a)

Notes: FTE = full-time equivalent; FTEWB = full-time week-based equivalents; MSK = Musculoskeletal, NR = not reported.

working conditions (physical, organizational, psychosocial) MSK, open wounds Cross-sectional

NR NR Cross-sectional

Traumatisms (32.2%), bruises (26.9%)

NR

NR

Risk for crashes: age (younger > older); vehicles type (rigid > articulated) Predicters of visual processing speed and fatigue: age; frequency of loading/unloading freight NR

45–54 55–64 65+ 45–54 55–64 65+ 45–54 12,501 (men)

Longitudinal

45–54 22,952 (women)

Longitudinal Age range (years) N

Transportation and Warehousing Chau et al. (2014) France

First author (year)

Table 2 (continued)

Study location

Study Population

Research Design

All

Injury type

Incidence

Rate per 1,000 person-years over 3 years: Overall: 11.9 < 25 yrs: 29.9 25–34 yrs: 16.5 35–44 yrs: 7.9 45–55 yrs: 8.5 NR

Risk Factors for Injury

age (younger > older overall, but older for fall injuries); experience (up to 4 yrs); task (manual tasks, risky physical environment)

NR

Outcomes

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4. Discussion Our review of studies published between 2010 and 2019 revealed that the incidence of work-related injuries was lower among older workers compared to younger workers. The consequences of work-related injuries, however, were often more severe for older than younger workers (Frickmann et al., 2012; Konstantinidis et al., 2011) and older workers on average experienced certain types of injuries (e.g., slips, trips, and falls) more often than younger workers (Chau et al., 2014; Lombardi et al., 2011; Muramatsu et al., 2018; Pliner et al., 2014; Scott et al., 2018a). Several studies also found that injuries were more costly on average for older than younger workers (Mallon and Cherry, 2015; 10

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Schwatka et al., 2013). As the population of Canada and the world is aging (Statistics Canada, 2016), the findings from the current review underscore the importance of preventing occupational injuries in older workers to reduce direct impact on older workers and the associated healthcare costs and burden on support systems. The industries in which older workers were at the greatest risk for injury included agriculture, forestry, fishing, and hunting; construction; mining, quarrying, and oil and gas extraction; and transportation and warehousing (Baidwan et al., 2018, 2019). Injuries that occurred in these occupations were likely due to a mismatch of physical ability in older workers and occupational job demands. As occupational demands increase and the physical ability of older workers decrease, occupational injury rates increase (Berecki-Gisolf et al., 2012). To reduce injury rates for older workers in these industries, modifiable risk factors should be identified and tasks should be adapted or modified to align with the physical abilities of the older worker. Moreover, older workers may require additional supports and/or re-training to work safely in the working conditions that increase their risk for injury. Ergonomic interventions (e.g., increased illumination at the workplace or reduced lifting required by older workers) had been found to be useful in creating a suitable environment for older workers (see Truxillo et al., 2015 for a review). Further research is needed to design, implement, and evaluate the effectiveness of workplace interventions designed to reduce injuries among older workers specifically. Slips, trips, and falls were also a primary concern for older workers. Whereas most injury types decreased with age, injuries because of falls often remained stable or increased with age (e.g., Chau et al., 2014; Lombardi et al., 2011; Muramatsu et al., 2018; Pliner et al., 2014; Scott et al., 2018a). Falls and injuries resulting from falls could be prevented by ensuring that workplace environment and job duties are modified and match the workers’ physical ability. This may be achieved by examining individual level risk factors for potential injury, modifying the workplace for their needs, and retraining older workers. Environmental interventions (e.g., improving lighting, removing physical obstacles, safety reminders) could reduce injury risk and improve outcomes (Scott et al., 2018a).

4.2. Limitations An important limitation of our review was that we did not formally examine the quality of the studies that we reviewed. This is an important next step to ascertain the relative strengths of the inferences that can be derived from the literature over the last ten years. Another limitation was that we did not expand our search prior to 2010 for practical reasons; however, it would be interesting to examine the trends in injury rates, risk factors, and outcomes over a longer time frame to determine if general increases or decreases are apparent. One might expect that injury rates (overall) in older worker would have increased given that more individuals in older age ranges are working now compared to 40 years ago. Most (86%) of the studies included in this review also did not explore the impact of work status (i.e., fulltime, part-time, seasonal, contract) or schedule (e.g., daytime, evening, night, or rotating) on occupation injury rates, making describing injury trends by specific employment information difficult. This is an important area for future research as certain types of seasonal work, for example, may increase the risk of injury for aging workers, particularly for migrant workers who may not have access to conventional medical treatment (e.g., Weigel and Armijos, 2012; Weigel et al., 2014). Another important limitation of this review was that the definitions of older worker often varied by study, depended on the country in which the study originated, as well as the research teams and organizations conducting the studies. For example, the Bureau of Labor Statistics in the United States defined older workers as those aged 55 years and older (Toossi and Torpey, 2017), as does the International Labour Organization (Ernst, 2015), whereas the United Nations currently uses age 60 years and over to identify older workers (United Nations, 2017). An agreed upon definition or specific age ranges would facilitate comparisons across industries, injuries, risk factors, and outcomes. Finally, our review was not limited to articles that used a certain type of data; indeed, various data sources were used to estimate workrelated injuries among older workers across studies and jurisdiction. For example, of the Canadian studies reviewed, six relied on worker compensation claims data as their primary data source (Algarni et al., 2015; Breslin et al., 2011; Sbarra et al., 2012; Scott et al., 2018; Smith et al., 2013, 2014). Although worker compensation data are valuable for determining estimates of incidence rates of occupational injuries, claims that are not accepted as compensable injuries by the worker compensation boards are not included in the dataset. Moreover, using these databases can lead to the overestimation of medical costs because the more severe injuries are most likely to be reported (Kim et al., 2013). Thus, it is highly probable that many more injuries than what can be calculated from these datasets have occurred, resulting in underestimations of occupational injury rates. Underreporting would vary by jurisdiction depending on the type of data collected. The use of representative survey data may help to close a gap in this regard. National surveys could be used to determine if there are older workers who were injured at work but did not report their injuries to their employer or their injuries were not accepted by claims boards. For example, the Canadian Longitudinal Study on Aging (n.d.), initiated in 2010, collects data from over 50,000 Canadian men and women, ages 45–85 years at the time of their first survey in 2011. This longitudinal study based on data from a national sample provides an opportunity to examine rates, risk factors (i.e., modifiable: health-related behaviours, mental health problems, factors related to social support; and nonmodifiable: occupation), and health outcomes of work-related injuries in Canadians aged 45–85 years by age group, sex, and residency location (e.g., provincial, urban/rural settings). Survey data can also be collected from workers who have experienced injuries at work that occurred over long periods (e.g., MSK injuries) and associations between the injuries and the occupational demands could be investigated. Surveys could also be used as parts of studies of mixed methods design, in which data are collected from workers whose claims were denied by

4.1. Future research Future research needs to emphasize potential modifiable risk factors for older workers, and our review identified several gaps in the literature. First, although a few studies did discuss alcohol use and occupational injuries, these studies were either older than our 2010–2019 review period or focused on younger workers, or both, which led to exclusion from our review (e.g., Chau et al., 2009). Second, only a few of the reviewed studies provided information about the influence of mental health problems such as depression, anxiety, traumatic stress, or post-traumatic stress disorder on occupational injury rates, risk factors, or outcomes (Baidwan et al., 2018; Smith et al., 2014), but details about how age interacts with mental health problems and injuries were relatively sparse. Smith et al., 2014a reported that age and healthcare expenditures following injury were positively associated but that depression mediated the relationship for women up to age 54 years. In addition, the examination of linkages between health-related behaviors, such as level of physical activity and nutrition, and psychosocial factors, including social support and family violence, and work-related injuries might be a fruitful avenue for future research as these factors could potentially improve the outcomes for older workers. We recommend that future studies of longitudinal design estimate the incidence of work-related injuries as people age and examine the relationships among modifiable risk factors, such as smoking, drinking, physical activity, eating behavior, and social support with work-related injuries among workers in various age groups. In addition, future studies should examine the work trajectories of individuals as they age, including how they manage work demands as their abilities change and related impacts on their finances. 11

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workers compensation boards. The survey data could be analyzed to determine claim denial trends, while also reporting national aggregate estimates of work-related injuries.

Chau, N., Dehaene, D., Benamghar, L., Bourgkard, E., Mur, J.M., Touron, C., Wild, P., 2014. Roles of age, length of service and job in work-related injury: A prospective study of 63,620 person-years in female workers. Am. J. Ind. Med. 57 (2), 172–183. https://doi.org/10.1002/ajim.22259. Chen, J.A., Dickerson, C.R., Wells, R.P., Laing, A.C., 2017. Older females in the workforce–the effects of age on psychophysical estimates of maximum acceptable lifting loads. Ergonomics 60 (12), 1708–1717. https://doi.org/10.1080/00140139.2017. 1335883. Chen, Z., Chakrabarty, S., Levine, R.S., Aliyu, M.H., Ding, T., Jackson, L.L., 2013. Workrelated knee injuries treated in emergency departments in the United States. J. Occup. Environ. Med. 55 (9), 1091–1099. https://doi.org/10.1097/JOM. 0b013e31829b27bf. Choi, S.D., 2015. Aging workers and trade-related injuries in the US construction industry. Safety Health Work 6 (2), 151–155. https://doi.org/10.1016/j.shaw.2015.02. 002. Collins, J., O’Sullivan, L., 2010. Psychosocial risk exposures and musculoskeletal disorders across working-age males and females. Human Factors Ergon. Manuf. 20 (4), 272–286. https://doi.org/10.1002/hfm.20220. Dimitriadis, C., Lamontagne, A.D., Lilley, R., Hogg-Johnson, S., Sim, M., Smith, P., 2017. Cohort profile: Workers’ compensation in a changing Australian labour market: The return to work (RTW) study. BMJ Open 7 (11), 1–9. https://doi.org/10.1136/ bmjopen-2017-016366. Doan, J.B., Copeland, J.L., Brown, L.A., Newman, J.T., Hudson, D.S., 2014. Work activities and musculoskeletal discomforts amongst active older Albertans on alternative employment trajectories. Work 47 (1), 55–62. https://doi.org/10.3233/WOR131685. Dobriansky, P.J., Suzman, R.M., Hodes, R.J. (2007). Why population aging matters - A global perspective (Report No. 07-6134). Retrieved from https://www.nia.nih.gov/ sites/default/files/2017-06/WPAM.pdf. Dropkin, J., Power, P., Rasul, R., Moline, J., Kim, H., 2019. Effect of resiliency and age on musculoskeletal injuries and lost workdays in emergency medical service personnel. Int. J. Ind. Ergon. 69, 184–193. https://doi.org/10.1016/j.ergon.2018.11.008. Employment and Social Development Canada. (2018). Promoting the labour force participation of older Canadians: Promising Initaitives. Retrieved from https://www. canada.ca/en/employment-social-development/corporate/seniors/forum/labourforce-participation.html#h2.4-3.2. Ernst, E. (speaker). (2015). What age means for the labour force [Audio podcast]. Retrieved from https://www.ilo.org/global/about-the-ilo/multimedia/audio/ WCMS_358943/lang–en/index.htm. Fan, J.K., Black, O., Smith, P.M., 2016. Examining age differences in duration of wage replacement by injury characteristics. Occup. Med. 66 (9), 698–705. https://doi.org/ 10.1093/occmed/kqw168. Fraade-Blanar, L.A., Sears, J.M., Chan, K.C.G., Thompson, H.J., Crane, P.K., Ebel, B.E., 2017. Relating older workers’ injuries to the mismatch between physical ability and job demands. J. Occup. Environ. Med. 59 (2), 212–221. https://doi.org/10.1097/ JOM.0000000000000941. Frickmann, F., Wurm, B., Jeger, V., Lehmann, B., Zimmermann, H., Exadaktylos, A.K., 2012. 782 Consecutive construction work accidents: Who is at risk? A 10-year analysis from a Swiss university hospital trauma unit. Swiss Medical Weekly 142. https://doi.org/10.4414/smw.2012.13674. Government of Canada. (2018). Canadian Industry Statistics. Retrieved December 6, 2019, from https://www.ic.gc.ca/app/scr/app/cis/search-recherche?lang=eng. Guest, M., Boggess, M.M., Duke, J.M., 2014a. Age related annual crash incidence rate ratios in professional drivers of heavy goods vehicles. Transport. Res. Part A: Policy Practice 65, 1–8. https://doi.org/10.1016/j.tra.2014.04.003. Guest, M., Boggess, M.M., Viljoen, D.A., Duke, J.M., Culvern, C.N., 2014b. Age-related injury and compensation claim rates in heavy industry. Occup. Med. 64 (2), 95–103. https://doi.org/10.1093/occmed/kqt166. Harrison, T., LeGarde, B., Kim, S.H., Walker, J., Blozis, S., Umberson, D., 2013. Work related injury among aging women. Policy Politics Nurs. Pract. 14 (1), 16–25. https://doi.org/10.1177/1527154413476095. Heaton, K., Azuero, A., Reed, D., 2010. Obstructive sleep apnea indicators and injury in older farmers. J. Agromed. 15 (2), 148–156. https://doi.org/10.1080/ 10599241003636020. Heaton, K., McManus, B.J., Mumbower, R., Vance, D.E., 2017. A pilot study of sleep, work practices, visual processing speed, and 5-year motor vehicle crash risk among truck drivers. Workplace Health Safety 65 (12), 572–579. https://doi.org/10.1177/ 2165079917704448. Hoonakker, P., Van Duivenbooden, C., 2010. Monitoring working conditions and health of older workers in dutch construction industry. Am. J. Ind. Med. 53 (6), 641–653. https://doi.org/10.1002/ajim.20838. Kim, H., Moline, J., Dropkin, J., 2013. Aging, sex, and cost of medical treatment. J. Occup. Environ. Med. 55 (5), 572–578. https://doi.org/10.1097/JOM. 0b013e318289eeda. Kim, J.S., Jeong, B.Y., 2018. Occupational accidents and human errors in apartment custodians’ work. Work 60 (4), 587–595. https://doi.org/10.3233/WOR-182766. Konda, S., Reichard, A., Tiesman, H.M., Hendricks, S., 2015. Non-fatal work-related traumatic brain injuries treated in US hospital emergency departments, 1998–2007. Injury Prevention 21 (2), 115–120. https://doi.org/10.1136/injuryprev-2014041323. Konstantinidis, A., Talving, P., Kobayashi, L., Barmparas, G., Plurad, D., Lam, L., Demetriades, D., 2011. Work-related injuries: Injury characteristics, survival, and age effect. Am. Surg. 77 (6), 702–707. Koukoulaki, T., 2010. New trends in work environment - New effects on safety. Saf. Sci. 48 (8), 936–942. https://doi.org/10.1016/j.ssci.2009.04.003. Kowalski-Trakofler, K.M., Steiner, L.J., Schwerha, D.J., 2005. Safety considerations for

5. Conclusion Our literature review highlighted that older workers experience a lower rate of occupational injury than do younger workers for some types of occupational injuries and that such injuries are more likely to be severe. But these results were not straightforward. The contradictory findings of younger or older workers experiencing more or fewer injuries across studies described in this review were likely due to the collapsing of findings across varying and broad age ranges and/or complex interactions between the types of injuries sustained, and modifiable (e.g., occupational demands) and non-modifiable (e.g., gender, occupation, employment tenure, physical ability) risk factors. Future research must address which factors are associated with increased or decreased risk of work-related injuries in older workers, including work-related injuries that result in death. Results of such studies may inform the design of programs and initiatives aimed to reduce the frequency and severity of work-related injuries among older workers. Industries with a higher risk for injury, such as agriculture and transportation, may need to lead the way to safer working conditions for older workers. Assessing if job demands align sufficiently with physical capabilities of older workers would be a positive first step, as would appropriately modifying duties to help reduce the injury risk. The use of the longitudinal and representative data is encouraged to address some of the existing gaps in the literature with the aim of preventing work-related injuries among older workers. Author notes Authors are listed alphabetically after Stoesz and Chimney. Funding for this research was provided by Workplace NL, the Canadian Centre for Advanced Leadership in Business, and University of Manitoba Undergraduate Research Award. References Algarni, F.S., Gross, D.P., Senthilselvan, A., Battié, M.C., 2015. Ageing workers with work-related musculoskeletal injuries. Occup. Med. 65 (3), 229–237. https://doi.org/ 10.1093/occmed/kqu213. Baidwan, N.K., Gerberich, S.G., Kim, H., Ryan, A.D., Church, T.R., Capistrant, B., 2018. A longitudinal study of work-related injuries: comparisons of health and work-related consequences between injured and uninjured aging United States adults. Injury Epidemiol. 5 (1). https://doi.org/10.1186/s40621-018-0166-7. Baidwan, N.K., Gerberich, S.G., Kim, H., Ryan, A., Church, T., Capistrant, B., 2019. A longitudinal study of work-related psychosocial factors and injuries: Implications for the aging United States workforce. Am. J. Ind. Med. 62 (3), 212–221. https://doi.org/ 10.1002/ajim.22945. Bande, R., López-Mourelo, E., 2015. The impact of worker’s age on the consequences of occupational accidents: empirical evidence using spanish data. J. Labor Res. 36 (2), 129–174. https://doi.org/10.1007/s12122-015-9199-7. Berecki-Gisolf, J., Clay, F.J., Collie, A., McClure, R.J., 2012. The impact of aging on work disability and return to work: insights from workers’ compensation claim records. J. Occup. Environ. Med. 54 (3), 318–327. https://doi.org/10.1097/JOM. 0b013e31823fdf9d. Besen, E., Young, A.E., Gaines, B., Pransky, G., 2016. Relationship between age, tenure, and disability duration in persons with compensated work-related conditions. J. Occup. Environ. Med. 58 (2), 140–147. https://doi.org/10.1097/JOM. 0000000000000623. Breslin, F.C., Smith, P.M., Moore, I., 2011. Examining the decline in lost-time claim rates across age groups in Ontario between 1991 and 2007. Occup. Environ. Med. 68 (11), 813–817. https://doi.org/10.1136/oem.2010.062562. Caffaro, F., Lundqvist, P., Micheletti Cremasco, M., Nilsson, K., Pinzke, S., Cavallo, E., 2018. Machinery-related perceived risks and safety attitudes in senior Swedish farmers. J. Agromed. 23 (1), 78–91. https://doi.org/10.1080/1059924X.2017. 1384420. Çağlayan, Ç., Etiler, N., 2015. Health of older workers in Turkey: A further analysis of a national sample. Turkish J. Geriatrics 18 (4), 285–292. Canadian Longitudinal Study on Aging. (n.d.). Retrieved from https://www.clsa-elcv.ca/. Chau, N., Bhattacherjee, A., Kunar, B.M., 2009. Relationship between job, lifestyle, age and occupational injuries. Occup. Med. 59 (2), 114–119. https://doi.org/10.1093/ occmed/kqp002.

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Smith, P.M., Bielecky, A., Ibrahim, S., Mustard, C., Saunders, R., Beaton, D., HoggJohnson, S., 2014a. Impact of pre-existing chronic conditions on age differences in sickness absence after a musculoskeletal work injury: a path analysis approach. Scand. J. Work Environ. Health 40 (3), 167–175. https://doi.org/10.5271/sjweh. 3408. Smith, P.M., Bielecky, A., Ibrahim, S., Mustard, C., Scott-Marshall, H., Saunders, R., Beaton, D., 2014b. How much do preexisting chronic conditions contribute to age differences in health care expenditures after a work-related musculoskeletal injury? Med. Care 52 (1), 71–77. https://doi.org/10.1097/MLR.0000000000000017. Smith, P.M., Bielecky, A., Koehoorn, M., Beaton, D., Ibrahim, S., Mustard, C., ScottMarshall, H., 2014c. Are age-related differences in the consequence of work injury greater when occupational physical demands are high? Am. J. Ind. Med. 57 (4), 438–444. https://doi.org/10.1002/ajim.22303. Smith, P.M., Bielecky, A., Mustard, C., 2012. The relationship between chronic conditions and work-related injuries and repetitive strain injuries in Canada. J. Occup. Environ. Med. 54 (7), 841–846. https://doi.org/10.1097/JOM.0b013e31824e11f7. Smith, P.M., Bielecky, A., Mustard, C., Beaton, D., Hogg-Johnson, S., Ibrahim, S., ScottMarshall, H., 2013. The relationship between age and work injury in British Columbia: Examining differences across time and nature of injury. J. Occupat. Health 55 (2), 98–107. https://doi.org/10.1539/joh.12-0219-OA. Sousa, I.C., Ramos, S., 2018. Working conditions, health and retirement intentions: a case study of truck drivers. Int. J. Workplace Health Manage. 11 (3), 114–129. https://doi. org/10.1108/IJWHM-02-2018-0019. Statistics Canada. (2010). Population projections for Canada, Provinces and Territories: 2009 to 2036 (Catalogue No. 91-5520-X). Retrieved from https://www150.statcan. gc.ca/n1/pub/91-520-x/91-520-x2010001-eng.pdf. Statistics Canada. (2016). Population by sex and age group. Retrieved May 13, 2017, from http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/demo10a-eng.htm. Statistics Canada. (2017). Labour in Canada: Key results from the 2016 census. Retrieved from https://www150.statcan.gc.ca/n1/daily-quotidien/171129/dq171129b-eng. htm. Steege, A.L., Baron, S.L., Marsh, S.M., Menéndez, C.C., Myers, J.R., 2014. Examining occupational health and safety disparities using national data: A cause for continuing concern. Am. J. Ind. Med. 57 (5), 527–538. https://doi.org/10.1002/ajim.22297. Stichler, J.F., 2013. Healthy work environments for the ageing nursing workforce. J. Nurs. Manage. 21 (7), 956–963. https://doi.org/10.1111/jonm.12174. Tonelli, S., Culp, K., Donham, K., 2014. Work-related musculoskeletal disorders in senior farmers: Safety and health considerations. Workplace Health Safety 62 (8), 333–341. https://doi.org/10.3928/21650799-20140708-04. Tonozzi, T.R., Layne, L.A., 2016. Hired crop worker injuries on farms in the United States: A comparison of two survey periods from the National Agricultural Workers Survey. Am. J. Ind. Med. 59 (5), 408–423. https://doi.org/10.1002/ajim.22578. Toossi, M., Torpey, E. (2017). Older workers: Labor force trends and career options. Retrieved from https://www.bls.gov/careeroutlook/2017/article/older-workers. htm. Truxillo, D.M., Cadiz, D.M., Hammer, L.B., 2015. Supporting the aging workforce: A review and recommendations for workplace intervention research. Annual Rev. Organizat. Psychol. Organizat. Behav. 2, 351–381. https://doi.org/10.1146/annurevorgpsych-032414-111435. United Nations (2017). World population ageing 2017 – Highlights. Retrieved from http://www.un.org/en/development/desa/population/publications/pdf/ageing/ WPA2017_Highlights.pdf. Unruh, L., Asi, Y., 2018. Determinants of workplace injuries and violence among newly licensed RNs. Workplace Health Safety 66 (10), 482–492. https://doi.org/10.1177/ 2165079918756909. Wang, X., Dong, X.S., Choi, S.D., Dement, J., 2017. Work-related musculoskeletal disorders among construction workers in the United States from 1992 to 2014. Occup. Environ. Med. 74 (5), 374–380. https://doi.org/10.1136/oemed-2016-103943. Weigel, M.M., Armijos, R.X., 2012. Exploratory study of the occupational health and health-seeking of migrant and seasonal farmworkers on the U.S.-mexico border. J. Immigr. Minor. Health 14 (4), 648–656. https://doi.org/10.1007/s10903-0119503-4. Weigel, M.M., Armijos, R.X., Beltran, O., 2014. Musculoskeletal injury, functional disability, and health-related quality of life in aging Mexican immigrant farmworkers. J. Immigr. Minor. Health 16 (5), 904–913. https://doi.org/10.1007/s10903-0139788-6. Welch, L.S., Haile, E., Boden, L.I., Hunting, K.L., 2010. Impact of musculoskeletal and medical conditions on disability retirement – A longitudinal study among construction roofers. Am. J. Ind. Med. 53 (6), 552–560. https://doi.org/10.1002/ajim.20794. Wilkie, R., Cifuentes, M., Pransky, G., 2011. Exploring extensions to working life: Job lock and predictors of decreasing work function in older workers. Disabil. Rehabil. 33 (19–20), 1719–1727. https://doi.org/10.3109/09638288.2010.544835. Wuellner, S.E., Walters, J.K., Leinenkugel, K., Rogers, P.F., Lefkowitz, D., Davis, L.K., Castillo, D.N., 2011. Nonfatal occupational injuries and illnesses among older workers –- United States, 2009. Morb. Mortal. Wkly Rep. 60 (16), 503–508. Zytoon, M.A., Basahel, A.M., 2017. Occupational safety and health conditions aboard small- and medium-size fishing vessels: Differences among age groups. Int. J. Environ. Res. Public Health 14 (3), 229. https://doi.org/10.3390/ijerph14030229.

the aging workforce. Saf. Sci. 43, 779–793. https://doi.org/10.1016/j.ssci.2005.08. 014. Lilley, R., Jaye, C., Davie, G., Keeling, S., Waters, D., Egan, R., 2018. Age-related patterns in work-related injury claims from older New Zealanders, 2009–2013: Implications of injury for an aging workforce. Accid. Anal. Prev. 110, 86–92. https://doi.org/10. 1016/j.aap.2017.10.022. Lombardi, D.A., Smith, G.S., Courtney, T.K., Brennan, M.J., Kim, J.Y., Perry, M.J., 2011. Work-related falls from ladders - a follow-back study of US emergency department cases. Scand. J. Work Environ. Health 37 (6), 525–532. https://doi.org/10.5271/ sjweh.3174. Mallon, T., Cherry, S., 2015. Investigating the relationship between worker demographics and nature of injury on federal department of defense workers’ compensation injury rates and costs from 2000 to 2008. J. Occupat. Environ. Med. 57, S27–S30. https:// doi.org/10.1097/JOM.0000000000000416. Margolis, K.A., 2010. Underground coal mining injury: A look at how age and experience relate to days lost from work following an injury. Saf. Sci. 48 (4), 417–421. https:// doi.org/10.1016/j.ssci.2009.12.015. Mehta, R.K., Agnew, M.J., 2010. Analysis of individual and occupational risk factors on task performance and biomechanical demands for a simulated drilling task. Int. J. Ind. Ergon. 40 (5), 584–591. https://doi.org/10.1016/j.ergon.2010.06.003. Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Phys. Ther. 89 (9), 873–880. https://doi.org/10.1136/bmj.b2535. Muramatsu, N., Sokas, R.K., Chakraborty, A., Zanoni, J.P., Lipscomb, J., 2018. Slips, trips, and falls among home care aides a mixed-methods study. J. Occup. Environ. Med. 60 (9), 796–803. https://doi.org/10.1097/JOM.0000000000001355. Nakamura, T., Takagi, M., Usui, S., 2011. Changes in labor accident risk with aging. J. Disaster Res. 6 (2), 253–257. https://doi.org/10.20965/jdr.2011.p0253. Nilsson, K., Pinzke, S., Lundqvist, P., 2010. Occupational injuries to senior farmers in Sweden. J. Agric. Safety Health 16 (1), 19–29. https://doi.org/10.13031/2013. 29246. Papadopoulos, G., Georgiadou, P., Papazoglou, C., Michaliou, K., 2010. Occupational and public health and safety in a changing work environment: an integrated approach for risk assessment and prevention. Saf. Sci. 48, 943–949. https://doi.org/10.1016/j.ssci. 2009.11.002. Park, J., Kim, S.G., Park, J., Shik, Han, B., Kim, K.B., Kim, Y., 2017. Hazards and health problems in occupations dominated by aged workers in South Korea. Annals Occupat. Environ. Med. 29 (1), 1–10. https://doi.org/10.1186/s40557-017-0177-9. Park, M.H., Jeong, B.Y., 2018. Occupational injuries and risk assessment of apartment guards work. Human Factors Ergon. Manuf. 28 (4), 220–226. https://doi.org/10. 1002/hfm.20737. Park, S.H., Yang, D.J., Shin, J. Il, Park, S.J., Oh, H.W., Choi, E.M., Yang, Y.A., 2012. Workplace accident prevention and improvement of work ability in an aging society. J. Phys. Ther. Sci. 24 (1), 143–148. https://doi.org/10.1589/jpts.24.143. Phillips, J.A., Miltner, R., 2015. Work hazards for an aging nursing workforce. J. Nurs. Manage. 23 (6), 803–812. https://doi.org/10.1111/jonm.12217. Pliner, E.M., Campbell-Kyureghyan, N.H., Beschorner, K.E., 2014. Effects of foot placement, hand positioning, age and climbing biodynamics on ladder slip outcomes. Ergonomics 57 (11), 1739–1749. https://doi.org/10.1080/00140139.2014.943681. Ranzenberger, K., Bunn, T.L., Slavova, S., 2016. Healthcare industry injuries by patient contact status in Kentucky, 2012–2014. South. Med. J. 109 (10), 599–605. https:// doi.org/10.14423/SMJ.0000000000000544. Ravesteijn, B., Kippersluis, H.V., Doorslaer, E.V., 2018. The wear and tear on health: What is the role of occupation? Health Econ. 27 (2), e69–e86. https://doi.org/10.1002/ hec.3563. Sbarra, D.A., Smith, H.L., Mehl, M.R., 2012. When leaving your ex, love yourself: observational ratings of self-compassion predict the course of emotional recovery following marital separation. Psychol. Sci. 23 (3), 261–269. https://doi.org/10.1177/ 0956797611429466. Schwatka, N.V., Butler, L.M., Rosecrance, J.R., 2012. An aging workforce and injury in the construction industry. Epidemiol. Rev. 34 (1), 156–167. https://doi.org/10. 1093/epirev/mxr020. Schwatka, N.V., Butler, L.M., Rosecrance, J.C., 2013. Age in relation to worker compensation costs in the construction industry. Am. J. Ind. Med. 56 (3), 356–366. https://doi.org/10.1002/ajim.22093. Scott, K.A., Fisher, G.G., Barón, A.E., Tompa, E., Stallones, L., DiGuiseppi, C., 2018a. Same-level fall injuries in US workplaces by age group, gender, and industry. Am. J. Ind. Med. 61 (2), 111–119. https://doi.org/10.1002/ajim.22796. Scott, K.A., Liao, Q., Fisher, G.G., Stallones, L., DiGuiseppi, C., Tompa, E., 2018b. Early labor force exit subsequent to permanently impairing occupational injury or illness among workers 50–64 years of age. Am. J. Ind. Med. 61 (4), 317–325. https://doi. org/10.1002/ajim.22817. Sears, J.M., Bowman, S.M., Blanar, L., Hogg-Johnson, S., 2017. Industrial injury hospitalizations billed to payers other than workers’ compensation: characteristics and trends by state. Health Serv. Res. 52 (2), 763–785. https://doi.org/10.1111/14756773.12500. Smith, P.M., Berecki-Gisolf, J., 2014. Age, occupational demands and the risk of serious work injury. Occupat. Med. (Oxford, England) 64 (8), 571–576. https://doi.org/10. 1093/occmed/kqu125.

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