- Email: [email protected]
Risk factors associated with reduced work productivity among people with chronic knee pain
Osteoarthritis and Cartilage 21 (2013) 1160e1169
Risk factors associated with reduced work productivity among people with chronic knee pain M. Agaliotis y *, M. Fransen z, L. Bridgett z, L. Nairn y, M. Votrubec x, S. Jan k, R. Heard {, M. Mackey # y Faculty of Health Sciences, University of Sydney, Australia z Physiotherapy, Clinical and Rehabilitation Sciences Research Group, Faculty of Health Sciences, University of Sydney, Australia x Graduate School of Medicine, The University of Notre Dame, Darlinghurst, Australia k The George Institute for Global Health, Sydney, Australia { Behavioural and Social Sciences in Health, Faculty of Health Sciences, University of Sydney, Australia # Physiotherapy, Ageing, Work and Health Research Unit, Faculty of Health Sciences, University of Sydney, Australia
a r t i c l e i n f o
s u m m a r y
Article history: Received 16 February 2013 Accepted 2 July 2013
Objective: To determine the burden and risk factors associated with reduced work productivity among people with chronic knee pain. Method: A longitudinal study, nested within a randomised controlled trial (RCT) evaluating the longterm effects of dietary supplements, was conducted among people with chronic knee pain in paid employment (n ¼ 360). Participants recorded days off work (absenteeism) and reduced productivity while at work (presenteeism) for seven days every two months over a 12-month period in a study specific diary. Examined risk factors included knee pain severity, occupational group, radiographic disease severity, physical activity, body mass index (BMI), health-related quality of life (SF-12) and comorbidity. Results: Over the 12-month follow up period, 50 (14%) participants reported one or more days off work due to knee problems, while 283 (79%) reported reduced productivity while at work (presenteeism <100%). In multivariate analysis, the only significant risk factor for absenteeism was having an SF-12 Mental Component Summary (MCS) score <40 (OR: 2.49 [95% CI: 1.03e5.98]). Significant risk factors for presenteeism included; reporting an; SF-12 Physical Component Summary (PCS) score <50 (OR: 1.99 [95% CI: 1.05e3.76]), semi-manual labour (OR: 2.23 [1.09e4.59]) or manual labour (OR: 6.40 [1.44e28.35]) or a high maximum knee pain (4e6 out of 10) (OR: 2.29 [1.17e4.46]). Conclusions: This longitudinal study found that among this cohort of people with chronic knee pain, the burden of reduced work productivity is mainly attributable to presenteeism rather absenteeism. This study demonstrated that effective strategies to increase work productivity should focus on reducing knee pain or physical disability especially among workers in manual or semi-manual labour. Ó 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
Keywords: Absenteeism Employment Longitudinal studies Knee osteoarthritis Work productivity
Introduction Osteoarthritis of the knee is a common chronic musculoskeletal condition often associated with pain and physical disability1. Chronic knee pain is associated with reduced quality of life2e4. Previous large population-based surveys have shown over 30% of older people have symptomatic knee osteoarthritis with about half also reporting some level of associated disability5e10. With an * Address correspondence and reprint requests to: M. Agaliotis, Cumberland Campus C42, Room 205, O Block, 75 East Street, NSW 1825, Australia. Tel: 61-2-9036-7322; Fax: 61-2-9351-9278. E-mail address: [email protected] (M. Agaliotis).
ageing population, and the growing trend to delay retirement worldwide, the number of people in the workforce affected by painful knee osteoarthritis will increase11,12. Work productivity losses are typically measured in two ways: as days taken off work (absenteeism) or as self-reported reduced productivity, or performance while at work (presenteeism). There is increasing evidence that presenteeism, rather than absenteeism, is the major contributor to loss of work productivity13. However, only a paucity of studies has examined the effects of symptomatic knee osteoarthritis on loss of work productivity. A large population-based cohort study conducted in Sweden found that a diagnosis of knee osteoarthritis was associated with a twofold increased risk of sick leave14. Similar findings were
1063-4584/$ e see front matter Ó 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.joca.2013.07.005
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
reported in a Norwegian population-based survey15. Additionally, in a Finnish survey, 71% of the 227 respondents who reported knee osteoarthritis also reported a reduced working capacity due to health reasons, compared with 24% in the overall cohort16. Similar results were demonstrated in four clinic-based surveys. A French national general practitioner survey of 10,295 patients with osteoarthritis found that among patients with knee osteoarthritis 66% reported occupational limitations compared to 14% reported in the general population17. A Canadian survey examining employment reduction due to osteoarthritis 57 (13%) of 453 people with reported knee ‘arthritis’, had ‘reduced hours’, while 161 (36%) reported ‘total work cessation’18. The VISK study, conducted in The Netherlands, found 20% of 117 working participants, reported taking one or more sick days, while 80% had a ‘hindrance in work’ due to knee symptoms ‘in the last 3 months’19. The Netherlands Cohort Hip and Cohort Knee (CHECK) survey examined the prevalence of sick leave among 493 employed patients with early symptoms of hip or knee osteoarthritis and reported 61 (12%) being on sick leave in the past 12 months because of their knee and/or hip osteoarthritis20. These population and clinic-based surveys had methodological limitations; most were cross sectional studies assessing various measures of absenteeism only and required lengthy recall periods. To date, there has only been one small longitudinal study examining both presenteeism and absenteeism among people with knee osteoarthritis in a prospective manner; the Longitudinal Examination of Arthritis Pain (LEAP) study21. Over the three-month follow-up period, changes in joint pain were highly associated with ‘days missed work’ or ‘days of limited productivity’ among the 47 working participants. However, the sample size was too small to examine risk factors associated with reduced work productivity. The objectives of this study were to determine (1) the burden of reduced work productivity (absenteeism and presenteeism) and (2) risk factors associated with reduced work productivity among people with symptomatic knee osteoarthritis over a 12-month follow-up period. Identifying modifiable risk factors for reduced work productivity may allow the implementation of effective preventive workplace strategies and minimize the economic burden associated with chronic knee pain. Method Design This longitudinal cohort study was conducted among the participants in a randomised controlled clinical trial, the Long-term Evaluation of Glucosamine Sulfate (LEGS) study (NCT00513422). In total, 605 people with chronic knee pain were recruited to the LEGS study through local and state newspaper advertisements and general practitioner clinics from November 2007 to November 2009 in New South Wales, Australia. The LEGS study was approved by the University of Sydney Human Research Ethics Committee and written informed consent was obtained from all participants. LEGS study participants At baseline all participants were aged 45e75 years, reported knee symptoms for more than 6 months, had knee pain or were taking non-steroidal anti-inflammatory drugs or analgesia for knee pain on most days of the past month and rated their knee pain 4 out of 10 for most days of the past week. Potential participants were excluded if they had: unstable diabetes; rheumatoid arthritis or other systemic inflammatory arthritis; lower limb joint surgery within the last 6 months; corticosteroid injection into the symptomatic knee joint in past 3 months; knee replacement in the symptomatic knee, or planning to have knee surgery in the next 12
1161
months. Potential participants were required to have an X-ray of both knees in a semi-flexed weight bearing position according to a specific protocol22. To be eligible, a symptomatically eligible knee needed to demonstrate medial tibiofemoral joint space narrowing but retain more than 2 mm joint space. Follow-up annual assessments were carried out face-to face with participants at one of the four NSW metropolitan radiological centres and bi-monthly LEGS Participant Diaries were mailed to participants from the period of November 2008 to November 2011. To be eligible for this embedded longitudinal cohort study, LEGS participants had to report being in paid employment at the baseline assessment. Outcome measures Bi monthly LEGS Participant Diary (Fig. 2) Participants completed a novel one page, 7-day LEGS Participant Diary, at baseline and then posted with study treatment capsules every 2 months over the 12-month follow-up period (Fig. 2). The LEGS Participant Diary collected data on pain and function, medication intake, physical activity, health service use and work productivity. Work productivity Work productivity was evaluated as: 1) Absenteeism (past 2 months): ‘How many days off did you have due to your knee problems?’ 2) Presenteeism (daily): ‘Your knee problems may affect your ability to work or perform daily activities. Please estimate your capacity for each day from 0% (unable to do usual work/activities) to 100% (fully functioning in usual role).’ Both work productivity questions were derived from the Work Productivity and Activity Impairment Questionnaire: Osteoarthritis of the Knee or Hip V2.0 (WPAI:OA)23,24. Risk factors Baseline clinic assessment included: height and weight without shoes and with pockets emptied to assess body mass index (BMI). Health-related quality of life was evaluated using the Medical Outcomes Study Short Form 12 Health Survey [SF-12]25. The eight health domains are aggregated into two summary measures: the Physical Component Summary (PCS) and the Mental Component Summary (MCS) scores. Both summary scores are population norm-based scores with a mean (sd) of 50 (10). A lower score represents more disability. The SF-12 was further categorized into four groups dependent on final score; 50 or more no disability; 40e 49 mildly disabled; 30e39 moderately disabled and 30 or below severely disabled26. Co-morbidity was reported using the SelfAdministered Co-morbidity Questionnaire (SCQ)27. This questionnaire recorded the presence of 12 current medical conditions: high blood pressure, heart disease, lung disease, diabetes, ulcer or stomach disease, kidney disease, liver disease, anaemia or other blood problems, cancer, depression, back pain, and rheumatoid arthritis. Additional scores are given if the participant reported receiving treatment and if this condition limited activities. The scores range from 0 to 36 points, where a higher score indicates more co-morbidity. The co-morbidity score was further categorized into three levels: 0e1 co-morbidities; 2e3 co-morbidities and 4 or more co-morbidities28. Knee radiographs were graded according to the Kellgren Lawrence (K/L) scale29. Work status classifications included; full-time, part-time, self-employed, unpaid, disabled sick, unemployed, carer, semi-retired or other. Baseline LEGS Participant Diary (Fig. 2).
1162
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Fig. 1. Follow up Participant Diaries (N ¼ 360).
Over 7 days, participants were required to record daily, maximum left and right knee pain (0e10)30; ‘At its worst, how much pain did you experience in your knee today?’, give a patient global assessment (0e4); ‘Considering all the ways your knee arthritis affects you, how would you say your knee(s) are today?’ (0 ¼ Excellent, 1 ¼ Very good, 2 ¼ Good, 3 ¼ Fair and 4 ¼ Poor) and recreational exercise (yes/no); ‘Did you participate in any moderate or vigorous recreational exercise that lasted longer than 20 min today?’ (adequate level: 5e7 days a week, inadequate: 0e4 days a week)31. Patients also stated their current primary occupation. Various methods were employed to encourage completion and timely return of the Participant Diary, including provision of a magnet for attachment of the Diary to the refrigerator, reminder emails or telephone calls, written letters/emails and verbal encouragement during routine bimonthly telephone calls and study newsletters.
Statistical analysis Absenteeism was calculated as the total number of days participants reported taking off work due to knee problems over the 12 month period while presenteeism was calculated as the average work productivity over the 12 month period. The two measures of reduced work productivity over the 12-month follow-up period showed heavily skewed distributions and so were transformed. Absenteeism was dichotomized: as no days off work vs 1 or more days off work. Presenteeism was less heavily skewed and was trichotomized as: 100%; 90e99%; and <90% presenteeism. This index was later dichotomised as exposed to presenteeism (participants who scored an average of 99.99% and below) vs those not exposed (100%). From the baseline LEGS Participant diary, the maximum knee pain score was defined as the highest score recorded for either left or right knee over each seven-day reporting period. Maximum
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Fig. 2. The LEGS Participant Diary.
1163
1164
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
pain was further categorized into three groups; 0e3: none or mild pain, 4e6: moderate pain, and 7e10: severe pain30. Using the Australian and New Zealand Standard Classification of Occupations (ANZSCO)32, occupation was categorized into seven groups: (1) professionals or managers; (2) clerical or administration; (3) community or personal services; (4) sales; (5) technicians or tradesmen; (6) labourers or (7) machine operators or drivers. To avoid small numbers in some categories, occupation was collapsed into three ordinal groups; non-manual labour (professionals or managers and clerical or administration), semi-manual labour (community or personal services or sales) and manual labour (technicians or tradesmen; labourers or machine operators or drivers). Changes in work over the 12 month period were categorized as: no change, change in occupation, increased hours of work (from part-time to full-time work), reduced hours of work (from full-time to part-time work), retired or unemployed and lost to follow up. Radiographic severity of knee osteoarthritis was determined by selecting for each participant the knee with the highest K/L grade. Descriptive statistics were used to describe the study sample characteristics, including absenteeism and presenteeism. Tests for multicollinearity using simple correlation testing were conducted on all data. Separate logistic regression analyses were performed to determine baseline risk factors for presenteeism and absenteeism over the 12-month follow-up period. Predictor odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated. For the initial selection of multivariate risk factors, univariate risk factors with a P value <0.20 were chosen. For all other comparisons alpha was set at 0.05. Age and gender was included in each model regardless of significance. Comparisons among groups who made changes to their work were performed by the non-parametric KruskaleWallis test for continuous variables. For gender distribution, absenteeism and presenteeism (categorical variables) the chisquare test was used. Any missing data were replaced by the last set of observations (previous bi-monthly Participant Diary)33. All statistical analyses were performed using the Statistical Package for the Social Sciences (IBM-SPSS) Software version 19. Results Among the 360 participants in paid employment at baseline, 37 (10%) withdrew from the study during the 12-month follow-up period (Fig. 1). The main reasons for study withdrawal were: ineffective study treatment (n ¼ 16); family reasons/too busy/general ill health (n ¼ 12) or experiencing an adverse event (n ¼ 9). A total of 289 (80%) completed at least five of the six expected Participant Diaries over the 12-month follow-up period. At baseline the majority of the participants were in full-time work (58%); most participants were in professional or managerial roles (43%) (Table I). The baseline mean SF-12 PCS score was low (43.4 8.9) and more than a third (35%) of this cohort were obese. The most commonly reported co-morbidities were back pain (58%), high blood pressure (29%) and depression (14%). While all participants had medial tibiofemoral joint space narrowing in at least one knee, the majority of knees demonstrated only mild to moderate radiographic disease severity (K/L grade 2 [w90%]). Burden of reduced work productivity Over the 12-month follow-up period, 50 (14%) participants reported 1 or more days off work due to knee problems (Table II). A total of 283 (79%) participants reported some reduced work productivity while at work (<100% presenteeism), with almost half of the cohort (42%) reporting <90% presenteeism due to their knee problems on average over the 12-month follow-up period (Table II). At the 12-month follow-up assessment, 99 (28%) participants had
Table I Baseline characteristics of cohort (N ¼ 360) Baseline characteristics
Mean (sd)
Age 57.5 (7.2) 45e54 years 55e64 years 65 þ years Women SF-12 PCS 43.4 (8.9) SF-12 MCS 52.8 (9.5) 28.9 (5.7) BMI (kg/m2) Normal (<25) Overweight (25 < 30) Obese (30þ) Co-morbidity score mean (sd) 2.9 (2.8) KellgreneLawrence grade (highest grade of left or right knee) KL1 KL2 KL3eKL4 Occupation Professional/Manager Community/Personal Service Administrative/Clerical Technicians/Trade Sales Machinery Operators/Drivers Labourer Type of labour Non-manual Semi-manual Manual Work status Full time Part time Full time carer Self Employed Maximum knee pain (0e10) 4.5 (2.3) Missing 7 (2%) Patient global assessment Excellent/very good/good Fair/poor Missing Adequate exercise (5e7 days a week) Inadequate exercise (0e4 days a week) Missing Absenteeism over past 2 months 1 or more days absent Missing Presenteeism 100% 90e99% <90% Missing
N (%) 133 165 62 196
(37%) (46%) (17%) (54%)
86 (24%) 149 (41%) 125 (35%)
157 (44%) 167 (46%) 36 (10%) 155 82 64 17 19 12 11
(43%) (23%) (18%) (5 %) (5%) (3%) (3%)
219 (61%) 101 (28%) 40 (11%) 208 116 19 17
(58%) (32%) (5%) (5%)
284 68 8 237 116 7
(79%) (19%) (2%) (66%) (32%) (2%)
25 (7%) 7 (2%) 125 86 140 9
(35%) (24%) (38%) (3%)
made at least one change to their work, with the majority changing their occupations (n ¼ 43). A comparable number of participants reported an increase (n ¼ 21) or a decrease (n ¼ 20) in their working hours, while ten retired (seven retiring at 65 years of age or below) and five lost their job (unrelated to knee problems). A Kruskale Wallis test revealed a statistically significant difference in recreational exercise between change in work groups (c2 ¼ 13.45, P ¼ 0.02)5. This effect was only significant because a Bonferroni adjustment was not used. Given the very small effect size (E2 ¼ 0.027) no further adjustments were made for change in work. Risk factors Absenteeism In univariate analyses, age over 64 years, working in semimanual labour, having maximum knee pain between 4 and 6 or having poor health related quality of life (SF-12 PCS or SF-12 MCS <40) at baseline were significant risk factors for one of more days
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
1165
Table II Burden of work disability, N (%) participants
Absenteeism 1 of more days Off work Missing Presenteeism 100% 90e99% <90% Missing
Diary 1
Diary 2
Diary 3
Diary 4
Diary 5
Diary 6
12 months [mean (SD)]
24 (7%) 7 (2%)
22 (6%) 5 (1%)
13 (4%) 5 (1%)
15 (4%) 5 (1%)
17 (5%) 5 (1%)
14 (4%) 5 (1%)
50 (14%) 4 (1%) [1.68 (8.03)]
125 (35%) 86 (24%) 140 (39%) 9 (2%)
132 (37%) 105 (29%) 118 (33%) 5 (1%)
139 (39%) 99 (28%) 117 (33%) 5 (1%)
147 (41%) 99 (28%) 109 (30%) 5 (1%)
153 (43%) 83 (23%) 119 (33%) 5 (1%)
146 (41%) 95 (26%) 114 (32%) 5 (1%)
72 (20%) 131 (37%) 152 (42%) [88.03 (14.05)] 5 (1%)
taken off work (absenteeism) due to knee problems in the 12month follow-up period (Tables III and IV). In multivariate analysis, having an SF-12 MCS <40 at baseline, compared to a score 50 or more, retained statistical significance (OR: 2.49 [95% CI: 1.03e 5.98]) (Table IV). There was also a non-significant trend indicating being over 64 years of age or having an SF-12 PCS <40 would increase the risk of taking one or more days off work. Presenteeism In univariate analyses, statistically significant risk factors for reduced productivity while at work were: being aged 55e64 years; having an SF-12 PCS <50; reporting four or more co-morbidities; working in semi-manual or manual labour; having maximum knee pain 4 out of 10 and having a patient global assessment of ‘fair’ or ‘poor’. Due to high correlation (R ¼ 0.68) between patient global assessment and maximum knee pain, only maximum knee pain was included in the multivariate model. In multivariate analysis, having an SF-12 PCS <50 at baseline (OR: 1.99 [95% CI: 1.05e 3.76]), working in semi-manual (OR: 2.23 [95% CI: 1.09e4.59]) or manual labour (OR: 6.40 [95% CI: 1.44e28.35]) and having a maximum knee pain score between 4 and 6 (OR: 2.29 [95% CI: 1.17e4.46]) remained statistically significant risk factors for reduced work productivity (Table V). Being middle age (55e64 years) or having four or more co-morbidities demonstrated borderline statistical significance in the model. Discussion This longitudinal study found a high burden of reduced productivity while at work among people with chronic knee pain. Only 20% of this cohort of people in paid employment reported 100% work productivity, while 42% reported a marked loss of their ability to fully function in their usual role (<90% presenteeism) due to knee problems over the 12-month follow-up period. This finding
was unanticipated given that most participants had only mild radiographic disease (K/L grade 2). Overall, the results show that absenteeism was related to low mental health related quality of life scores, while presenteeism was based in poor self-reported physical function and the physical demands of the occupation. Our study had comparable findings to previous surveys for absenteeism. We found 14% of participants took one or more days off work in the 12-month follow-up period because of knee problems, while previous surveys examining ‘missed workdays because of osteoarthritis’, or ‘sick leave days in the previous 12 months’ reported absenteeism ranging from 2 to 22%14,15,17,19,20,34e36. Similar to these studies, our study only had a small number of people reporting work absence (n ¼ 50), limiting our ability to detect important risk factors for absenteeism. We found our participants only took an average of one to two days off work in the last 12 months, while other studies have found higher annual estimates ranging from 12 to 87 days14,34e36. However, comparisons between studies of the number of days taken off work should be done with caution due to the differing sick leave attribution, the influences of differing labour markets and social security systems. Our study is the first evaluate psychological wellbeing (SF-12 MCS) concurrently with measure for absenteeism among a cohort of people with chronic knee pain. Similar to other studies, we found the majority of participants reported reduced productivity while at work rather than actually taking days off work16,17,19. Furthermore, our study’s results concur with the findings of the LEAP21 and the VISK studies19 in which high knee pain, physically intensive work or type of labour were found to be associated with reduced productivity while at work among people with knee pain. It is important to note previous studies have used a range of definitions for reduced productivity while at work, including ‘occupational limitations’17, ‘reduced work capacity or change work’16, ‘missed all or part of the day’21, ‘reduced work hours’18 or ‘hindrance
Table III 12 month follow up: change in work (median)
Age Female (%) SF-12 PCS SF-12 MCS BMI (kg/m2) Number of co-morbidities K/L highest Maximum knee pain (0e10) Patient global assessment (0e4) Recreational exercise (0e7 days) Presenteeism <100% Absenteeism (1 or more days) *
Significant differences.
No change (n ¼ 230)
Change in occupation (n ¼ 43)
Change in hours: increased (n ¼ 20)
Change in hours: reduced (n ¼ 21)
Retired or unemployed (n ¼ 15)
Lost to follow up (n ¼ 31)
P
57.00 54.3 45.1 55.1 28.0 2.00 2.00 3.5 2.0 3.3 77.6 14.0
57.00 53.5 43.4 56.6 27.8 2.00 2.00 4.0 2.3 3.2 83.7 18.6
60.00 45.0 48.0 52.2 26.9 3.00 1.50 3.6 1.8 3.9 90.0 20.0
53.00 57.1 40.3 55.9 27.7 2.00 1.00 3.9 1.9 5.0 80.0 0.0
62.00 46.7 42.2 49.1 27.8 3.00 2.00 3.8 2.1 3.2 86.7 20.0
57.00 64.5 45.8 53.4 29.8 2.00 2.00 4.8 2.1 2.0 79.3 10.3
0.29 0.79 0.21 0.35 0.44 0.36 0.99 0.67 0.14 0.02* 0.73 0.37
1166
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Table IV Univariate and multivariate analyses; OR and 95% CI for absenteeism (1 or more days off work) Variable
Total
N (%)
Age group 45e54 years 133 13 (10%) 55e64 years 162 23 (14%) 64 þ years 61 14 (23%) Gender Male 162 17 (11%) Female 194 33 (17%) SF-12 PCS 50 93 7 (8%) 40 < 50 138 18 (13%) <40 125 25 (20%) SF-12 MCS 50 244 32 (13%) 40 < 50 70 7 (10%) <40 42 11 (26%) BMI (kg/m2) Normal 85 14 (17%) Overweight 148 23 (16%) Obese 123 13 (11%) Number of co-morbidities 0 71 7 (10%) 1e3 175 28 (16%) 4 or more 110 15 (14%) KellgreneLawrence score (left knee/right knee) 0e1 155 16 (10%) 2 165 28 (17%) 3e4 36 6 (17%) Type of labour Non-manual 217 23 (11%) Semi-manual 100 21 (21%) Manual 39 6 (15%) Maximum knee pain (0e10) 0e3 140 14 (10%) 4e6 131 24 (18%) 7e10 82 12 (15%) Patient global assessment (0e4) 0 33 4 (12%) 1e2 251 34 (14%) 3e4 68 12 (18%) Recreational exercise (0e7 days) 5e7 days 237 34 (14%) 0e4 days 116 16 (14%) *
Univariate analyses
Multivariate analyses
OR (95% CI)
P
OR (95% CI)
P
1 1.53 (0.74e3.15) 2.75 (1.20e6.29)
0.25 0.02*
1 1.31 (0.61e2.79) 2.38 (0.98e5.78)
0.49 0.05
1 1.75 (0.93e3.27)
0.08
1 1.80 (0.88e3.68)
0.11
1 1.84 (0.74e4.61) 3.07 (1.27e7.45)
0.19 0.01*
1 1.50 (0.57e3.91) 2.51 (0.95e6.61)
0.41 0.06
1 0.74 (0.31e1.75) 2.35 (1.08e5.14)
0.49 0.03*
1 0.79 (0.32e1.96) 2.49 (1.03e5.98)
0.62 0.04*
1 0.93 (0.45e1.93) 0.60 (0.27e1.35)
0.85 0.21
1 1.74 (0.72e4.19) 1.44 (0.56e3.74)
0.22 0.45
1 1.78 (0.92e3.43) 1.74 (0.63e4.81)
0.09 0.29
1 1.72 (0.86e3.43) 2.15 (0.73e6.32)
0.13 0.17
1 2.24 (1.17e4.28) 1.53 (0.58e4.05)
0.01* 0.39
1 1.52 (0.75e3.06) 1.89 (0.64e5.55)
0.25 0.25
1 2.02 (1.00e4.10) 1.54 (0.68e3.52)
0.05* 0.30
1 1.56 (0.73e3.33) 0.81 (0.31e2.11)
0.25 0.67
1 1.14 (0.38e3.43) 1.55 (0.46e5.25)
0.82 0.48
1 0.96 (0.50e1.81)
0.89
Significant P < 0.05.
in work’19. There were also differences regarding whether reduced work productivity was attributed to ‘overall osteoarthritis’17, ‘arthritis’18, for ‘health reasons’16 or was not specified21. In addition, many studies required a lengthy recall period16e18. Our study uniquely used a day-by-day evaluation of lost work productivity specifically related to ‘knee problems’ for 7 days every 2 months over a 12-month follow-up period and is therefore likely to be a more reliable estimate of presenteeism. Our study had some limitations. One limitation was the design of the study, a cohort embedded within a randomised control trial (RCT), limiting generalizability. Another limitation is the small number of semi-manual or manual workers in this cohort, resulting in a wide confidence interval around the mean risk. Further, our method of evaluating physical workload was restricted as we used a crude scale to categorize physical workload based on occupational codes: non-manual, semi-manual, or manual labour. Furthermore, we did not examine the physical, economic and psychological environment of the workplace, factors likely to be associated with reduced work productivity. We also recognize having a small number of participants with severe structural disease (K/L score of 3e4) or lower SF-12 MCS scores could have influenced the findings. To avoid overburdening participants completing the daily diary, we
did not ask participants to include the actual dates or days of work. It is possible on these non-working days participants could have worked less or more than their main working day occupation. However we did take an average of participants’ ability to work during the week for each diary over a 1 year period. We also included carers (5%) and volunteer workers (5%) in our cohort of workers because of their physical and psychosocial commitments were deemed no less than those faced by paid workers. Furthermore, we could not include treatments into the regression models because the results of the randomised controlled trial (RCT) have not been released yet. Conversely, this longitudinal study had many strengths. Compared with previous population or clinic based surveys21,34,35,37, we were able to recruit a large cohort of people with chronic knee pain in paid employment. Importantly, this study collected regular 7 day prospective data on knee pain, patient global assessment and work productivity over a 12-month follow-up period. Additionally, we also asked participants to recall their days taken off work in the last 2 months, rather than in the last year, consecutively over a one year period, reducing recall bias. Although we did not include people without chronic knee pain, reduced work productivity was specifically focused on that attributable to ‘knee problems’, rather than a
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
1167
Table V Univariate and multivariate analyses; OR and 95% CI for presenteeism (<100% work productivity) Variable
Total
N (%)
Univariate analyses OR (95% CI)
Age group 45e54 133 97 (73%) 55e64 161 136 (85%) 64þ 61 50 (83%) Gender Male 162 126 (78%) Female 193 157 (81%) SF-12 PCS 50 93 59 (63%) 40 < 50 137 111 (81%) <40 125 113 (90%) SF-12 MCS 50 244 192 (79%) 40 < 50 70 56 (80%) <40 41 35 (85%) BMI (kg/m2) Normal 85 70 (82%) Overweight 148 113 (76%) Obese 122 100 (82%) Number of co-morbidities 0 71 49 (69%) 1e3 175 137(78%) 4 or more 109 97 (89%) KellgreneLawrence score (left knee/right knee) 0e1 155 123 (79%) 2 165 131 (79%) 3e4 35 29 (83%) Type of labour Non-manual 216 158 (73%) Semi-manual 100 88 (88%) Manual 39 37 (95%) Maximum knee pain (0e10) 0e3 140 96 (68%) 4e6 130 113 (87%) 7e10 82 71 (87%) Patient global assessment (0e4) 0 33 22 (67%) 1e2 251 199 (79%) 3e4 67 58 (87%) Recreational exercise (0e7 days) 5e7 days 236 191 (81%) 0e4 days 116 89 (77%) *
Multivariate analyses P
OR (95% CI)
1 2.02 (1.14e3.58) 1.69 (0.79e3.60)
0.02* 0.18
1 1.25 (0.74e2.09)
0.41
1 2.46 (1.35e4.49) 5.43 (2.62e11.26)
0.01* <0.01*
1 1.08 (0.56e2.10) 1.58 (0.63e3.96)
0.81 0.33
1 0.69 (0.35e1.36) 0.97 (0.47e2.01)
0.28 0.94
1 1.62 (0.87e3.00) 3.63 (1.66e7.94)
0.13 <0.01*
1 1.00 (0.59e1.72) 1.26 (0.48e3.29)
0.99 0.64
1 2.69 (1.37e5.28) 6.79 (1.59e29.08)
0.04* 0.01*
1 3.05 (1.64e5.68) 2.96 (1.43e6.13)
<0.01* 0.01*
1 1.91 (0.87e4.20) 3.22 (1.18e8.83)
0.11 0.02*
1 0.78 (0.45e1.33)
0.36
P
1 1.77 (0.95e3.30) 1.17 (0.50e2.73)
0.07 0.72
1 1.99 (1.05e3.76) 3.44 (1.51e7.81)
0.04* <0.01*
1 1.27 (0.64e2.50) 2.15 (0.91e5.09)
0.50 0.08
1 2.23 (1.09e4.59) 6.40 (1.44e28.35)
0.03* 0.02*
1 2.29 (1.17e4.46) 1.72 (0.75e3.92)
0.02* 0.20
Significant P < 0.05.
broader reference. It is noteworthy that the return rate of completed Participant Diaries was high, with 80% of participants completing at least five of the six Participant Diaries over the 12-month follow-up period. This study also gives some insight into the changing culture of the workforce, where 17% of this cohort consisted of participants who continued to work beyond the usual, but not compulsory, retirement age in Australia of 65 years (Table I). In fact, the Australian labour force participation for males aged 65e74 in 2011 was 24.5% and for females, 12.6%38. Knee osteoarthritis is a complex condition not only affecting quality of life but also the ability to work. Current clinical management of knee osteoarthritis focuses on reducing pain and physical disability but does not usually provide workplace modifications or preventive strategies specifically for people working with knee pain39. Clearly, manual or semi-manual labour are associated with reduced work productivity among people with knee pain. A recent study explored work adaptations among patients with early hip and knee osteoarthritis20. This study found only 67 (14%) of patients made actual work adaptations, while 146 (30%) desired work adaptations. Research in this area remains limited. There has been a growing interest in developing standardized and comprehensive measures of reduced work productivity among people with knee osteoarthritis40. Without accurate
methods of evaluating work productivity we may greatly underestimate the burden of knee pain for the overall community40. In conclusion, we found the majority of participants in this cohort with mostly mild knee osteoarthritis reported reduced productivity while at work rather than actually taking days off work. We demonstrated baseline factors such as type of labour, self-reported physical disability (SF-12 PCS) and knee pain severity were associated with presenteeism. The study examined basic work and health indicators. We need to extend the scope of risk factors to include potential psychosocial and workplace indicators for reduced work productivity such as job demands, job satisfaction and access to workplace adaptations. Once these factors have been evaluated, then can we develop targeted preventative workplace strategies to effectively reduce the burden of lost work productivity among people with chronic knee pain. Authors contributions All the authors were involved in drafting the article or revised the paper for important intellectual content, and all the authors approved the final version to be published. Ms Agaliotis had full access to all of the data in the study and takes full responsibility for the integrity of the data and accuracy of the data analysis.
1168
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Study concept and design: Fransen, Jan, Agaliotis, Votrubec, Nairn. Acquisition of data: Agaliotis, Bridgett, Nairn, Votrubec, Fransen. Analysis and interpretation of data: Agaliotis, Bridgett, Heard, Fransen, Jan, Mackey. Drafting or revising critically for important intellectual content: Agaliotis, Bridgett, Fransen, Heard, Jan, Mackey, Nairn, Votrubec. Final approval of version to be submitted: Agaliotis, Bridgett, Fransen, Heard, Jan, Mackey, Nairn, Votrubec. Role of funding source The Long-term Evaluation of Glucosamine Sulfate (LEGS) study was funded by the National Health and Medical Research Council (NHMRC) of Australia, with some supplementary funding provided by Sanofi-Aventis Consumer Healthcare Pty Ltd. The study funders had no involvement in study design, collection, analysis and interpretation of the data; the writing of the manuscript or in the decision to submit the manuscript for publication.
11.
12. 13.
14.
15.
16.
Competing interests None of the authors have competing interests to declare. 17. Acknowledgements We thank the LEGS participants for their contributions to our research. We would also like to thank Dr Federica Barzi for her suggestions with the statistical analysis. This work was supported by Arthritis Australia (The Kevin R James Grant) awarded to Ms Maria Agaliotis. References 1. Busija L, Bridgett L, Williams SRM, Osborne RH, Buchbinder R, March L, et al. Osteoarthritis. Baillieres Best Pract Res Clin Rheumatol 2010;24:757e68. 2. Bookwala J, Harralson TL, Parmelee PA. Effects of pain on functioning and well-being in older adults with osteoarthritis of the knee. Psychol Aging 2003;18:844e50. 3. Hopman-Rock M, Kraaimaat FW, Bijlsma JW. Quality of life in elderly subjects with pain in the hip or knee. Qual Life Res 1997;6:67e76. 4. Muraki S, Akune T, Oka H, Mabuchi A, En-Yo Y, Yoshida M, et al. Association of occupational activity with radiographic knee osteoarthritis and lumbar spondylosis in elderly patients of population-based cohorts: a large-scale population-based study. Arthritis Rheum 2009;61:779e86. 5. Davis MA, Ettinger WH, Neuhaus JM, Mallon KP. Knee osteoarthritis and physical functioning: evidence from the NHANES I epidemiologic followup study. J Rheumatol 1991;18:591e8. 6. Guccione AA, Felson DT, Anderson JJ, Anthony JM, Zhang Y, Wilson PW, et al. The effects of specific medical conditions on the functional limitations of elders in the Framingham Study. Am J Public Health 1994;84:351e8. 7. McAlindon TE, Cooper C, Kirwan JR, Dieppe PA. Determinants of disability in osteoarthritis of the knee. Ann Rheum Dis 1993;52:258e62. 8. Peat G, McCarney R, Croft P. Knee pain and osteoarthritis in older adults: a review of community burden and current use of primary health care. Ann Rheum Dis 2001;60:91e7. 9. Anderson JJ, Felson DT. Factors associated with osteoarthritis of the knee in the first national Health and Nutrition Examination Survey (HANES I). Evidence for an association with overweight, race, and physical demands of work. Am J Epidemiol 1988;128:179e89. 10. Pincus T, Mitchell JM, Burkhauser RV. Substantial work disability and earnings losses in individuals less than age 65
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
with osteoarthritis: comparisons with rheumatoid arthritis. J Clin Epidemiol 1989;42:449e57. Zheltoukhova K, Bevan S, Reichi A. Fit for Work? Musculoskeletal Disorders and the Australian Labour Market. London, United Kingdom: The Work Foundation; 20121e85. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ 2003;81:646e56. Schultz AB, Edington DW, Schultz AB, Edington DW. Employee health and presenteeism: a systematic review. J Occup Rehabil 2007;17:547e79. Hubertsson J, Petersson IF, Thorstensson CA, Englund M. Risk of sick leave and disability pension in working-age women and men with knee osteoarthritis. Ann Rheum Dis 2013;72:401e5. Grotle M, Hagen KB, Natvig B, Dahl FA, Kvien TK. Prevalence and burden of osteoarthritis: results from a population survey in Norway. J Rheumatol 2008;35:677e84. Makela M, Heliovaara M, Sievers K, Knekt P, Maatela J, Aromaa A. Musculoskeletal disorders as determinants of disability in Finns aged 30 years or more. J Clin Epidemiol 1993;46:549e59. Fautrel B, Hilliquin P, Rozenberg S, Allaert FA, Coste P, Leclerc A, et al. Impact of osteoarthritis: results of a nationwide survey of 10,000 patients consulting for OA. Joint Bone Spine Revue du Rhumatisme 2005;72:235e40. Sayre EC, Li LC, Kopec JA, Esdaile JM, Bar S, Cibere J. The effect of disease site (knee, hip, hand, foot, lower back or neck) on employment reduction due to osteoarthritis. PLoS ONE 2010;5: e10470, http://dx.doi.org/10.1371/journal.pone.0010470. Accessed 05.12.12. Hermans J, Koopmanschap MA, Bierma-Zeinstra SMA, van Linge JH, Verhaar JAN, Reijman M, et al. Productivity costs and medical costs among working patients with knee osteoarthritis. Arthritis Care Res 2012;64:853e61. Bieleman HJ, Oosterveld FG, Oostveen JC, Reneman MF, Groothoff JW. Work participation and health status in early osteoarthritis of the hip and/or knee: a comparison between the Cohort Hip and Cohort Knee and the Osteoarthritis Initiative. Arthritis Care Res 2010;62:683e9. Hutchings A, Calloway M, Choy E, Hooper M, Hunter DJ, Jordan JM, et al. The Longitudinal Examination of Arthritis Pain (LEAP) study: relationships between weekly fluctuations in patient-rated joint pain and other health outcomes. J Rheumatol 2007;34:2291e300. Buckland-Wright JC, Wolfe F, Ward RJ, Flowers N, Hayne C. Substantial superiority of semiflexed (MTP) views in knee osteoarthritis: a comparative radiographic study, without fluoroscopy, of standing extended, semiflexed (MTP), and schuss views. J Rheumatol 1999;26:2664e74. Lin C-WC, March L, Crosbie J, Crawford R, Graves S, Naylor J, et al. Maximum recovery after knee replacementethe MARKER study rationale and protocol. BMC Musculoskelet Disord 2009;10:69. Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics 1993;4:353e65. Sanderson K, Andrews G. The SF-12 in the Australian population: cross-validation of item selection. Aust New Zealand J Public Health 2002;26:343e5. Andrews G. A brief integer scorer for the SF-12: validity of the brief scorer in Australian community and clinic settings. Aust New Zealand J Public Health 2002;26:508e10. Sangha O, Stucki G, Liang MH, Fossel AH, Katz JN. The SelfAdministered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum 2003;49:156e63.
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
28. Reichmann WM, Katz JN, Kessler CL, Jordan JM, Losina E. Determinants of self-reported health status in a populationbased sample of persons with radiographic knee osteoarthritis. Arthritis Rheum 2009;61:1046e53. 29. Kellgren JH, Lawrence JS. Radiological assessment of osteoarthrosis. Ann Rheum Dis 1957;16:494e502. 30. Lequesne M. Indices of severity and disease activity for osteoarthritis. Semin Arthritis Rheum 1991;20:48e54. 31. Armstrong TBA, Davies J. Physical Activity Patterns of Australian Adults. Results of the 1999 National Physical Activity Survey. Canberra, Australia: Australian Institute of Health and Welfare; 20001e68. 32. ANZSCO e Australian and New Zealand Standard Classification of Occupations. First edn. Revision 1. Canberra: Australian Bureau of Statistics (ABS); 2009. Available at: http://www.abs. gov.au/ausstats/[email protected]/mf/1220.0. 33. Auleley GR, Giraudeau B, Baron G, Maillefert JF, Dougados M, Ravaud P, et al. The methods for handling missing data in clinical trials influence sample size requirements. J Clin Epidemiol 2004;57:447e53. 34. Leardini G, Salaffi F, Caporali R, Canesi B, Rovati L, Montanelli R, et al. Direct and indirect costs of osteoarthritis of the knee. Clin Exp Rheumatol 2004;22:699e706.
1169
35. Woo J, Lau E, Lau CS, Lee P, Zhang J, Kwok T, et al. Socioeconomic impact of osteoarthritis in Hong Kong: utilization of health and social services, and direct and indirect costs. Arthritis Rheum 2003;49:526e34. 36. Merx H, Dreinhofer KE, Gunther KP. Socioeconomic relevance of osteoarthritis in Germany. Z Orthopadie Unfallchirurgie 2007;145:421e9. 37. Gupta S, Hawker GA, Laporte A, Croxford R, Coyte PC. The economic burden of disabling hip and knee osteoarthritis (OA) from the perspective of individuals living with this condition. Rheumatology 2005;44:1531e7. 38. Australian Bureau of Statistics (ABS). Gender Indicators, Australia; Jan 2013. Catalogue No: 4125.0. Available at: http:// www.abs.gov.au/ausstats/[email protected]/mf/4125.0. 39. Zhang W, Nuki G, Moskowitz RW, Abramson S, Altman RD, Arden NK, et al. OARSI recommendations for the management of hip and knee osteoarthritis: part III: changes in evidence following systematic cumulative update of research published through January 2009. Osteoarthritis Cartilage 2010;18:476e99. 40. Beaton D, Bombardier C, Escorpizo R, Zhang W, Lacaille D, Boonen A, et al. Measuring worker productivity: frameworks and measures. J Rheumatol 2009;36:2100e9.
Risk factors associated with reduced work productivity among people with chronic knee pain M. Agaliotis y *, M. Fransen z, L. Bridgett z, L. Nairn y, M. Votrubec x, S. Jan k, R. Heard {, M. Mackey # y Faculty of Health Sciences, University of Sydney, Australia z Physiotherapy, Clinical and Rehabilitation Sciences Research Group, Faculty of Health Sciences, University of Sydney, Australia x Graduate School of Medicine, The University of Notre Dame, Darlinghurst, Australia k The George Institute for Global Health, Sydney, Australia { Behavioural and Social Sciences in Health, Faculty of Health Sciences, University of Sydney, Australia # Physiotherapy, Ageing, Work and Health Research Unit, Faculty of Health Sciences, University of Sydney, Australia
a r t i c l e i n f o
s u m m a r y
Article history: Received 16 February 2013 Accepted 2 July 2013
Objective: To determine the burden and risk factors associated with reduced work productivity among people with chronic knee pain. Method: A longitudinal study, nested within a randomised controlled trial (RCT) evaluating the longterm effects of dietary supplements, was conducted among people with chronic knee pain in paid employment (n ¼ 360). Participants recorded days off work (absenteeism) and reduced productivity while at work (presenteeism) for seven days every two months over a 12-month period in a study specific diary. Examined risk factors included knee pain severity, occupational group, radiographic disease severity, physical activity, body mass index (BMI), health-related quality of life (SF-12) and comorbidity. Results: Over the 12-month follow up period, 50 (14%) participants reported one or more days off work due to knee problems, while 283 (79%) reported reduced productivity while at work (presenteeism <100%). In multivariate analysis, the only significant risk factor for absenteeism was having an SF-12 Mental Component Summary (MCS) score <40 (OR: 2.49 [95% CI: 1.03e5.98]). Significant risk factors for presenteeism included; reporting an; SF-12 Physical Component Summary (PCS) score <50 (OR: 1.99 [95% CI: 1.05e3.76]), semi-manual labour (OR: 2.23 [1.09e4.59]) or manual labour (OR: 6.40 [1.44e28.35]) or a high maximum knee pain (4e6 out of 10) (OR: 2.29 [1.17e4.46]). Conclusions: This longitudinal study found that among this cohort of people with chronic knee pain, the burden of reduced work productivity is mainly attributable to presenteeism rather absenteeism. This study demonstrated that effective strategies to increase work productivity should focus on reducing knee pain or physical disability especially among workers in manual or semi-manual labour. Ó 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
Keywords: Absenteeism Employment Longitudinal studies Knee osteoarthritis Work productivity
Introduction Osteoarthritis of the knee is a common chronic musculoskeletal condition often associated with pain and physical disability1. Chronic knee pain is associated with reduced quality of life2e4. Previous large population-based surveys have shown over 30% of older people have symptomatic knee osteoarthritis with about half also reporting some level of associated disability5e10. With an * Address correspondence and reprint requests to: M. Agaliotis, Cumberland Campus C42, Room 205, O Block, 75 East Street, NSW 1825, Australia. Tel: 61-2-9036-7322; Fax: 61-2-9351-9278. E-mail address: [email protected] (M. Agaliotis).
ageing population, and the growing trend to delay retirement worldwide, the number of people in the workforce affected by painful knee osteoarthritis will increase11,12. Work productivity losses are typically measured in two ways: as days taken off work (absenteeism) or as self-reported reduced productivity, or performance while at work (presenteeism). There is increasing evidence that presenteeism, rather than absenteeism, is the major contributor to loss of work productivity13. However, only a paucity of studies has examined the effects of symptomatic knee osteoarthritis on loss of work productivity. A large population-based cohort study conducted in Sweden found that a diagnosis of knee osteoarthritis was associated with a twofold increased risk of sick leave14. Similar findings were
1063-4584/$ e see front matter Ó 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.joca.2013.07.005
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
reported in a Norwegian population-based survey15. Additionally, in a Finnish survey, 71% of the 227 respondents who reported knee osteoarthritis also reported a reduced working capacity due to health reasons, compared with 24% in the overall cohort16. Similar results were demonstrated in four clinic-based surveys. A French national general practitioner survey of 10,295 patients with osteoarthritis found that among patients with knee osteoarthritis 66% reported occupational limitations compared to 14% reported in the general population17. A Canadian survey examining employment reduction due to osteoarthritis 57 (13%) of 453 people with reported knee ‘arthritis’, had ‘reduced hours’, while 161 (36%) reported ‘total work cessation’18. The VISK study, conducted in The Netherlands, found 20% of 117 working participants, reported taking one or more sick days, while 80% had a ‘hindrance in work’ due to knee symptoms ‘in the last 3 months’19. The Netherlands Cohort Hip and Cohort Knee (CHECK) survey examined the prevalence of sick leave among 493 employed patients with early symptoms of hip or knee osteoarthritis and reported 61 (12%) being on sick leave in the past 12 months because of their knee and/or hip osteoarthritis20. These population and clinic-based surveys had methodological limitations; most were cross sectional studies assessing various measures of absenteeism only and required lengthy recall periods. To date, there has only been one small longitudinal study examining both presenteeism and absenteeism among people with knee osteoarthritis in a prospective manner; the Longitudinal Examination of Arthritis Pain (LEAP) study21. Over the three-month follow-up period, changes in joint pain were highly associated with ‘days missed work’ or ‘days of limited productivity’ among the 47 working participants. However, the sample size was too small to examine risk factors associated with reduced work productivity. The objectives of this study were to determine (1) the burden of reduced work productivity (absenteeism and presenteeism) and (2) risk factors associated with reduced work productivity among people with symptomatic knee osteoarthritis over a 12-month follow-up period. Identifying modifiable risk factors for reduced work productivity may allow the implementation of effective preventive workplace strategies and minimize the economic burden associated with chronic knee pain. Method Design This longitudinal cohort study was conducted among the participants in a randomised controlled clinical trial, the Long-term Evaluation of Glucosamine Sulfate (LEGS) study (NCT00513422). In total, 605 people with chronic knee pain were recruited to the LEGS study through local and state newspaper advertisements and general practitioner clinics from November 2007 to November 2009 in New South Wales, Australia. The LEGS study was approved by the University of Sydney Human Research Ethics Committee and written informed consent was obtained from all participants. LEGS study participants At baseline all participants were aged 45e75 years, reported knee symptoms for more than 6 months, had knee pain or were taking non-steroidal anti-inflammatory drugs or analgesia for knee pain on most days of the past month and rated their knee pain 4 out of 10 for most days of the past week. Potential participants were excluded if they had: unstable diabetes; rheumatoid arthritis or other systemic inflammatory arthritis; lower limb joint surgery within the last 6 months; corticosteroid injection into the symptomatic knee joint in past 3 months; knee replacement in the symptomatic knee, or planning to have knee surgery in the next 12
1161
months. Potential participants were required to have an X-ray of both knees in a semi-flexed weight bearing position according to a specific protocol22. To be eligible, a symptomatically eligible knee needed to demonstrate medial tibiofemoral joint space narrowing but retain more than 2 mm joint space. Follow-up annual assessments were carried out face-to face with participants at one of the four NSW metropolitan radiological centres and bi-monthly LEGS Participant Diaries were mailed to participants from the period of November 2008 to November 2011. To be eligible for this embedded longitudinal cohort study, LEGS participants had to report being in paid employment at the baseline assessment. Outcome measures Bi monthly LEGS Participant Diary (Fig. 2) Participants completed a novel one page, 7-day LEGS Participant Diary, at baseline and then posted with study treatment capsules every 2 months over the 12-month follow-up period (Fig. 2). The LEGS Participant Diary collected data on pain and function, medication intake, physical activity, health service use and work productivity. Work productivity Work productivity was evaluated as: 1) Absenteeism (past 2 months): ‘How many days off did you have due to your knee problems?’ 2) Presenteeism (daily): ‘Your knee problems may affect your ability to work or perform daily activities. Please estimate your capacity for each day from 0% (unable to do usual work/activities) to 100% (fully functioning in usual role).’ Both work productivity questions were derived from the Work Productivity and Activity Impairment Questionnaire: Osteoarthritis of the Knee or Hip V2.0 (WPAI:OA)23,24. Risk factors Baseline clinic assessment included: height and weight without shoes and with pockets emptied to assess body mass index (BMI). Health-related quality of life was evaluated using the Medical Outcomes Study Short Form 12 Health Survey [SF-12]25. The eight health domains are aggregated into two summary measures: the Physical Component Summary (PCS) and the Mental Component Summary (MCS) scores. Both summary scores are population norm-based scores with a mean (sd) of 50 (10). A lower score represents more disability. The SF-12 was further categorized into four groups dependent on final score; 50 or more no disability; 40e 49 mildly disabled; 30e39 moderately disabled and 30 or below severely disabled26. Co-morbidity was reported using the SelfAdministered Co-morbidity Questionnaire (SCQ)27. This questionnaire recorded the presence of 12 current medical conditions: high blood pressure, heart disease, lung disease, diabetes, ulcer or stomach disease, kidney disease, liver disease, anaemia or other blood problems, cancer, depression, back pain, and rheumatoid arthritis. Additional scores are given if the participant reported receiving treatment and if this condition limited activities. The scores range from 0 to 36 points, where a higher score indicates more co-morbidity. The co-morbidity score was further categorized into three levels: 0e1 co-morbidities; 2e3 co-morbidities and 4 or more co-morbidities28. Knee radiographs were graded according to the Kellgren Lawrence (K/L) scale29. Work status classifications included; full-time, part-time, self-employed, unpaid, disabled sick, unemployed, carer, semi-retired or other. Baseline LEGS Participant Diary (Fig. 2).
1162
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Fig. 1. Follow up Participant Diaries (N ¼ 360).
Over 7 days, participants were required to record daily, maximum left and right knee pain (0e10)30; ‘At its worst, how much pain did you experience in your knee today?’, give a patient global assessment (0e4); ‘Considering all the ways your knee arthritis affects you, how would you say your knee(s) are today?’ (0 ¼ Excellent, 1 ¼ Very good, 2 ¼ Good, 3 ¼ Fair and 4 ¼ Poor) and recreational exercise (yes/no); ‘Did you participate in any moderate or vigorous recreational exercise that lasted longer than 20 min today?’ (adequate level: 5e7 days a week, inadequate: 0e4 days a week)31. Patients also stated their current primary occupation. Various methods were employed to encourage completion and timely return of the Participant Diary, including provision of a magnet for attachment of the Diary to the refrigerator, reminder emails or telephone calls, written letters/emails and verbal encouragement during routine bimonthly telephone calls and study newsletters.
Statistical analysis Absenteeism was calculated as the total number of days participants reported taking off work due to knee problems over the 12 month period while presenteeism was calculated as the average work productivity over the 12 month period. The two measures of reduced work productivity over the 12-month follow-up period showed heavily skewed distributions and so were transformed. Absenteeism was dichotomized: as no days off work vs 1 or more days off work. Presenteeism was less heavily skewed and was trichotomized as: 100%; 90e99%; and <90% presenteeism. This index was later dichotomised as exposed to presenteeism (participants who scored an average of 99.99% and below) vs those not exposed (100%). From the baseline LEGS Participant diary, the maximum knee pain score was defined as the highest score recorded for either left or right knee over each seven-day reporting period. Maximum
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Fig. 2. The LEGS Participant Diary.
1163
1164
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
pain was further categorized into three groups; 0e3: none or mild pain, 4e6: moderate pain, and 7e10: severe pain30. Using the Australian and New Zealand Standard Classification of Occupations (ANZSCO)32, occupation was categorized into seven groups: (1) professionals or managers; (2) clerical or administration; (3) community or personal services; (4) sales; (5) technicians or tradesmen; (6) labourers or (7) machine operators or drivers. To avoid small numbers in some categories, occupation was collapsed into three ordinal groups; non-manual labour (professionals or managers and clerical or administration), semi-manual labour (community or personal services or sales) and manual labour (technicians or tradesmen; labourers or machine operators or drivers). Changes in work over the 12 month period were categorized as: no change, change in occupation, increased hours of work (from part-time to full-time work), reduced hours of work (from full-time to part-time work), retired or unemployed and lost to follow up. Radiographic severity of knee osteoarthritis was determined by selecting for each participant the knee with the highest K/L grade. Descriptive statistics were used to describe the study sample characteristics, including absenteeism and presenteeism. Tests for multicollinearity using simple correlation testing were conducted on all data. Separate logistic regression analyses were performed to determine baseline risk factors for presenteeism and absenteeism over the 12-month follow-up period. Predictor odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated. For the initial selection of multivariate risk factors, univariate risk factors with a P value <0.20 were chosen. For all other comparisons alpha was set at 0.05. Age and gender was included in each model regardless of significance. Comparisons among groups who made changes to their work were performed by the non-parametric KruskaleWallis test for continuous variables. For gender distribution, absenteeism and presenteeism (categorical variables) the chisquare test was used. Any missing data were replaced by the last set of observations (previous bi-monthly Participant Diary)33. All statistical analyses were performed using the Statistical Package for the Social Sciences (IBM-SPSS) Software version 19. Results Among the 360 participants in paid employment at baseline, 37 (10%) withdrew from the study during the 12-month follow-up period (Fig. 1). The main reasons for study withdrawal were: ineffective study treatment (n ¼ 16); family reasons/too busy/general ill health (n ¼ 12) or experiencing an adverse event (n ¼ 9). A total of 289 (80%) completed at least five of the six expected Participant Diaries over the 12-month follow-up period. At baseline the majority of the participants were in full-time work (58%); most participants were in professional or managerial roles (43%) (Table I). The baseline mean SF-12 PCS score was low (43.4 8.9) and more than a third (35%) of this cohort were obese. The most commonly reported co-morbidities were back pain (58%), high blood pressure (29%) and depression (14%). While all participants had medial tibiofemoral joint space narrowing in at least one knee, the majority of knees demonstrated only mild to moderate radiographic disease severity (K/L grade 2 [w90%]). Burden of reduced work productivity Over the 12-month follow-up period, 50 (14%) participants reported 1 or more days off work due to knee problems (Table II). A total of 283 (79%) participants reported some reduced work productivity while at work (<100% presenteeism), with almost half of the cohort (42%) reporting <90% presenteeism due to their knee problems on average over the 12-month follow-up period (Table II). At the 12-month follow-up assessment, 99 (28%) participants had
Table I Baseline characteristics of cohort (N ¼ 360) Baseline characteristics
Mean (sd)
Age 57.5 (7.2) 45e54 years 55e64 years 65 þ years Women SF-12 PCS 43.4 (8.9) SF-12 MCS 52.8 (9.5) 28.9 (5.7) BMI (kg/m2) Normal (<25) Overweight (25 < 30) Obese (30þ) Co-morbidity score mean (sd) 2.9 (2.8) KellgreneLawrence grade (highest grade of left or right knee) KL1 KL2 KL3eKL4 Occupation Professional/Manager Community/Personal Service Administrative/Clerical Technicians/Trade Sales Machinery Operators/Drivers Labourer Type of labour Non-manual Semi-manual Manual Work status Full time Part time Full time carer Self Employed Maximum knee pain (0e10) 4.5 (2.3) Missing 7 (2%) Patient global assessment Excellent/very good/good Fair/poor Missing Adequate exercise (5e7 days a week) Inadequate exercise (0e4 days a week) Missing Absenteeism over past 2 months 1 or more days absent Missing Presenteeism 100% 90e99% <90% Missing
N (%) 133 165 62 196
(37%) (46%) (17%) (54%)
86 (24%) 149 (41%) 125 (35%)
157 (44%) 167 (46%) 36 (10%) 155 82 64 17 19 12 11
(43%) (23%) (18%) (5 %) (5%) (3%) (3%)
219 (61%) 101 (28%) 40 (11%) 208 116 19 17
(58%) (32%) (5%) (5%)
284 68 8 237 116 7
(79%) (19%) (2%) (66%) (32%) (2%)
25 (7%) 7 (2%) 125 86 140 9
(35%) (24%) (38%) (3%)
made at least one change to their work, with the majority changing their occupations (n ¼ 43). A comparable number of participants reported an increase (n ¼ 21) or a decrease (n ¼ 20) in their working hours, while ten retired (seven retiring at 65 years of age or below) and five lost their job (unrelated to knee problems). A Kruskale Wallis test revealed a statistically significant difference in recreational exercise between change in work groups (c2 ¼ 13.45, P ¼ 0.02)5. This effect was only significant because a Bonferroni adjustment was not used. Given the very small effect size (E2 ¼ 0.027) no further adjustments were made for change in work. Risk factors Absenteeism In univariate analyses, age over 64 years, working in semimanual labour, having maximum knee pain between 4 and 6 or having poor health related quality of life (SF-12 PCS or SF-12 MCS <40) at baseline were significant risk factors for one of more days
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
1165
Table II Burden of work disability, N (%) participants
Absenteeism 1 of more days Off work Missing Presenteeism 100% 90e99% <90% Missing
Diary 1
Diary 2
Diary 3
Diary 4
Diary 5
Diary 6
12 months [mean (SD)]
24 (7%) 7 (2%)
22 (6%) 5 (1%)
13 (4%) 5 (1%)
15 (4%) 5 (1%)
17 (5%) 5 (1%)
14 (4%) 5 (1%)
50 (14%) 4 (1%) [1.68 (8.03)]
125 (35%) 86 (24%) 140 (39%) 9 (2%)
132 (37%) 105 (29%) 118 (33%) 5 (1%)
139 (39%) 99 (28%) 117 (33%) 5 (1%)
147 (41%) 99 (28%) 109 (30%) 5 (1%)
153 (43%) 83 (23%) 119 (33%) 5 (1%)
146 (41%) 95 (26%) 114 (32%) 5 (1%)
72 (20%) 131 (37%) 152 (42%) [88.03 (14.05)] 5 (1%)
taken off work (absenteeism) due to knee problems in the 12month follow-up period (Tables III and IV). In multivariate analysis, having an SF-12 MCS <40 at baseline, compared to a score 50 or more, retained statistical significance (OR: 2.49 [95% CI: 1.03e 5.98]) (Table IV). There was also a non-significant trend indicating being over 64 years of age or having an SF-12 PCS <40 would increase the risk of taking one or more days off work. Presenteeism In univariate analyses, statistically significant risk factors for reduced productivity while at work were: being aged 55e64 years; having an SF-12 PCS <50; reporting four or more co-morbidities; working in semi-manual or manual labour; having maximum knee pain 4 out of 10 and having a patient global assessment of ‘fair’ or ‘poor’. Due to high correlation (R ¼ 0.68) between patient global assessment and maximum knee pain, only maximum knee pain was included in the multivariate model. In multivariate analysis, having an SF-12 PCS <50 at baseline (OR: 1.99 [95% CI: 1.05e 3.76]), working in semi-manual (OR: 2.23 [95% CI: 1.09e4.59]) or manual labour (OR: 6.40 [95% CI: 1.44e28.35]) and having a maximum knee pain score between 4 and 6 (OR: 2.29 [95% CI: 1.17e4.46]) remained statistically significant risk factors for reduced work productivity (Table V). Being middle age (55e64 years) or having four or more co-morbidities demonstrated borderline statistical significance in the model. Discussion This longitudinal study found a high burden of reduced productivity while at work among people with chronic knee pain. Only 20% of this cohort of people in paid employment reported 100% work productivity, while 42% reported a marked loss of their ability to fully function in their usual role (<90% presenteeism) due to knee problems over the 12-month follow-up period. This finding
was unanticipated given that most participants had only mild radiographic disease (K/L grade 2). Overall, the results show that absenteeism was related to low mental health related quality of life scores, while presenteeism was based in poor self-reported physical function and the physical demands of the occupation. Our study had comparable findings to previous surveys for absenteeism. We found 14% of participants took one or more days off work in the 12-month follow-up period because of knee problems, while previous surveys examining ‘missed workdays because of osteoarthritis’, or ‘sick leave days in the previous 12 months’ reported absenteeism ranging from 2 to 22%14,15,17,19,20,34e36. Similar to these studies, our study only had a small number of people reporting work absence (n ¼ 50), limiting our ability to detect important risk factors for absenteeism. We found our participants only took an average of one to two days off work in the last 12 months, while other studies have found higher annual estimates ranging from 12 to 87 days14,34e36. However, comparisons between studies of the number of days taken off work should be done with caution due to the differing sick leave attribution, the influences of differing labour markets and social security systems. Our study is the first evaluate psychological wellbeing (SF-12 MCS) concurrently with measure for absenteeism among a cohort of people with chronic knee pain. Similar to other studies, we found the majority of participants reported reduced productivity while at work rather than actually taking days off work16,17,19. Furthermore, our study’s results concur with the findings of the LEAP21 and the VISK studies19 in which high knee pain, physically intensive work or type of labour were found to be associated with reduced productivity while at work among people with knee pain. It is important to note previous studies have used a range of definitions for reduced productivity while at work, including ‘occupational limitations’17, ‘reduced work capacity or change work’16, ‘missed all or part of the day’21, ‘reduced work hours’18 or ‘hindrance
Table III 12 month follow up: change in work (median)
Age Female (%) SF-12 PCS SF-12 MCS BMI (kg/m2) Number of co-morbidities K/L highest Maximum knee pain (0e10) Patient global assessment (0e4) Recreational exercise (0e7 days) Presenteeism <100% Absenteeism (1 or more days) *
Significant differences.
No change (n ¼ 230)
Change in occupation (n ¼ 43)
Change in hours: increased (n ¼ 20)
Change in hours: reduced (n ¼ 21)
Retired or unemployed (n ¼ 15)
Lost to follow up (n ¼ 31)
P
57.00 54.3 45.1 55.1 28.0 2.00 2.00 3.5 2.0 3.3 77.6 14.0
57.00 53.5 43.4 56.6 27.8 2.00 2.00 4.0 2.3 3.2 83.7 18.6
60.00 45.0 48.0 52.2 26.9 3.00 1.50 3.6 1.8 3.9 90.0 20.0
53.00 57.1 40.3 55.9 27.7 2.00 1.00 3.9 1.9 5.0 80.0 0.0
62.00 46.7 42.2 49.1 27.8 3.00 2.00 3.8 2.1 3.2 86.7 20.0
57.00 64.5 45.8 53.4 29.8 2.00 2.00 4.8 2.1 2.0 79.3 10.3
0.29 0.79 0.21 0.35 0.44 0.36 0.99 0.67 0.14 0.02* 0.73 0.37
1166
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Table IV Univariate and multivariate analyses; OR and 95% CI for absenteeism (1 or more days off work) Variable
Total
N (%)
Age group 45e54 years 133 13 (10%) 55e64 years 162 23 (14%) 64 þ years 61 14 (23%) Gender Male 162 17 (11%) Female 194 33 (17%) SF-12 PCS 50 93 7 (8%) 40 < 50 138 18 (13%) <40 125 25 (20%) SF-12 MCS 50 244 32 (13%) 40 < 50 70 7 (10%) <40 42 11 (26%) BMI (kg/m2) Normal 85 14 (17%) Overweight 148 23 (16%) Obese 123 13 (11%) Number of co-morbidities 0 71 7 (10%) 1e3 175 28 (16%) 4 or more 110 15 (14%) KellgreneLawrence score (left knee/right knee) 0e1 155 16 (10%) 2 165 28 (17%) 3e4 36 6 (17%) Type of labour Non-manual 217 23 (11%) Semi-manual 100 21 (21%) Manual 39 6 (15%) Maximum knee pain (0e10) 0e3 140 14 (10%) 4e6 131 24 (18%) 7e10 82 12 (15%) Patient global assessment (0e4) 0 33 4 (12%) 1e2 251 34 (14%) 3e4 68 12 (18%) Recreational exercise (0e7 days) 5e7 days 237 34 (14%) 0e4 days 116 16 (14%) *
Univariate analyses
Multivariate analyses
OR (95% CI)
P
OR (95% CI)
P
1 1.53 (0.74e3.15) 2.75 (1.20e6.29)
0.25 0.02*
1 1.31 (0.61e2.79) 2.38 (0.98e5.78)
0.49 0.05
1 1.75 (0.93e3.27)
0.08
1 1.80 (0.88e3.68)
0.11
1 1.84 (0.74e4.61) 3.07 (1.27e7.45)
0.19 0.01*
1 1.50 (0.57e3.91) 2.51 (0.95e6.61)
0.41 0.06
1 0.74 (0.31e1.75) 2.35 (1.08e5.14)
0.49 0.03*
1 0.79 (0.32e1.96) 2.49 (1.03e5.98)
0.62 0.04*
1 0.93 (0.45e1.93) 0.60 (0.27e1.35)
0.85 0.21
1 1.74 (0.72e4.19) 1.44 (0.56e3.74)
0.22 0.45
1 1.78 (0.92e3.43) 1.74 (0.63e4.81)
0.09 0.29
1 1.72 (0.86e3.43) 2.15 (0.73e6.32)
0.13 0.17
1 2.24 (1.17e4.28) 1.53 (0.58e4.05)
0.01* 0.39
1 1.52 (0.75e3.06) 1.89 (0.64e5.55)
0.25 0.25
1 2.02 (1.00e4.10) 1.54 (0.68e3.52)
0.05* 0.30
1 1.56 (0.73e3.33) 0.81 (0.31e2.11)
0.25 0.67
1 1.14 (0.38e3.43) 1.55 (0.46e5.25)
0.82 0.48
1 0.96 (0.50e1.81)
0.89
Significant P < 0.05.
in work’19. There were also differences regarding whether reduced work productivity was attributed to ‘overall osteoarthritis’17, ‘arthritis’18, for ‘health reasons’16 or was not specified21. In addition, many studies required a lengthy recall period16e18. Our study uniquely used a day-by-day evaluation of lost work productivity specifically related to ‘knee problems’ for 7 days every 2 months over a 12-month follow-up period and is therefore likely to be a more reliable estimate of presenteeism. Our study had some limitations. One limitation was the design of the study, a cohort embedded within a randomised control trial (RCT), limiting generalizability. Another limitation is the small number of semi-manual or manual workers in this cohort, resulting in a wide confidence interval around the mean risk. Further, our method of evaluating physical workload was restricted as we used a crude scale to categorize physical workload based on occupational codes: non-manual, semi-manual, or manual labour. Furthermore, we did not examine the physical, economic and psychological environment of the workplace, factors likely to be associated with reduced work productivity. We also recognize having a small number of participants with severe structural disease (K/L score of 3e4) or lower SF-12 MCS scores could have influenced the findings. To avoid overburdening participants completing the daily diary, we
did not ask participants to include the actual dates or days of work. It is possible on these non-working days participants could have worked less or more than their main working day occupation. However we did take an average of participants’ ability to work during the week for each diary over a 1 year period. We also included carers (5%) and volunteer workers (5%) in our cohort of workers because of their physical and psychosocial commitments were deemed no less than those faced by paid workers. Furthermore, we could not include treatments into the regression models because the results of the randomised controlled trial (RCT) have not been released yet. Conversely, this longitudinal study had many strengths. Compared with previous population or clinic based surveys21,34,35,37, we were able to recruit a large cohort of people with chronic knee pain in paid employment. Importantly, this study collected regular 7 day prospective data on knee pain, patient global assessment and work productivity over a 12-month follow-up period. Additionally, we also asked participants to recall their days taken off work in the last 2 months, rather than in the last year, consecutively over a one year period, reducing recall bias. Although we did not include people without chronic knee pain, reduced work productivity was specifically focused on that attributable to ‘knee problems’, rather than a
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
1167
Table V Univariate and multivariate analyses; OR and 95% CI for presenteeism (<100% work productivity) Variable
Total
N (%)
Univariate analyses OR (95% CI)
Age group 45e54 133 97 (73%) 55e64 161 136 (85%) 64þ 61 50 (83%) Gender Male 162 126 (78%) Female 193 157 (81%) SF-12 PCS 50 93 59 (63%) 40 < 50 137 111 (81%) <40 125 113 (90%) SF-12 MCS 50 244 192 (79%) 40 < 50 70 56 (80%) <40 41 35 (85%) BMI (kg/m2) Normal 85 70 (82%) Overweight 148 113 (76%) Obese 122 100 (82%) Number of co-morbidities 0 71 49 (69%) 1e3 175 137(78%) 4 or more 109 97 (89%) KellgreneLawrence score (left knee/right knee) 0e1 155 123 (79%) 2 165 131 (79%) 3e4 35 29 (83%) Type of labour Non-manual 216 158 (73%) Semi-manual 100 88 (88%) Manual 39 37 (95%) Maximum knee pain (0e10) 0e3 140 96 (68%) 4e6 130 113 (87%) 7e10 82 71 (87%) Patient global assessment (0e4) 0 33 22 (67%) 1e2 251 199 (79%) 3e4 67 58 (87%) Recreational exercise (0e7 days) 5e7 days 236 191 (81%) 0e4 days 116 89 (77%) *
Multivariate analyses P
OR (95% CI)
1 2.02 (1.14e3.58) 1.69 (0.79e3.60)
0.02* 0.18
1 1.25 (0.74e2.09)
0.41
1 2.46 (1.35e4.49) 5.43 (2.62e11.26)
0.01* <0.01*
1 1.08 (0.56e2.10) 1.58 (0.63e3.96)
0.81 0.33
1 0.69 (0.35e1.36) 0.97 (0.47e2.01)
0.28 0.94
1 1.62 (0.87e3.00) 3.63 (1.66e7.94)
0.13 <0.01*
1 1.00 (0.59e1.72) 1.26 (0.48e3.29)
0.99 0.64
1 2.69 (1.37e5.28) 6.79 (1.59e29.08)
0.04* 0.01*
1 3.05 (1.64e5.68) 2.96 (1.43e6.13)
<0.01* 0.01*
1 1.91 (0.87e4.20) 3.22 (1.18e8.83)
0.11 0.02*
1 0.78 (0.45e1.33)
0.36
P
1 1.77 (0.95e3.30) 1.17 (0.50e2.73)
0.07 0.72
1 1.99 (1.05e3.76) 3.44 (1.51e7.81)
0.04* <0.01*
1 1.27 (0.64e2.50) 2.15 (0.91e5.09)
0.50 0.08
1 2.23 (1.09e4.59) 6.40 (1.44e28.35)
0.03* 0.02*
1 2.29 (1.17e4.46) 1.72 (0.75e3.92)
0.02* 0.20
Significant P < 0.05.
broader reference. It is noteworthy that the return rate of completed Participant Diaries was high, with 80% of participants completing at least five of the six Participant Diaries over the 12-month follow-up period. This study also gives some insight into the changing culture of the workforce, where 17% of this cohort consisted of participants who continued to work beyond the usual, but not compulsory, retirement age in Australia of 65 years (Table I). In fact, the Australian labour force participation for males aged 65e74 in 2011 was 24.5% and for females, 12.6%38. Knee osteoarthritis is a complex condition not only affecting quality of life but also the ability to work. Current clinical management of knee osteoarthritis focuses on reducing pain and physical disability but does not usually provide workplace modifications or preventive strategies specifically for people working with knee pain39. Clearly, manual or semi-manual labour are associated with reduced work productivity among people with knee pain. A recent study explored work adaptations among patients with early hip and knee osteoarthritis20. This study found only 67 (14%) of patients made actual work adaptations, while 146 (30%) desired work adaptations. Research in this area remains limited. There has been a growing interest in developing standardized and comprehensive measures of reduced work productivity among people with knee osteoarthritis40. Without accurate
methods of evaluating work productivity we may greatly underestimate the burden of knee pain for the overall community40. In conclusion, we found the majority of participants in this cohort with mostly mild knee osteoarthritis reported reduced productivity while at work rather than actually taking days off work. We demonstrated baseline factors such as type of labour, self-reported physical disability (SF-12 PCS) and knee pain severity were associated with presenteeism. The study examined basic work and health indicators. We need to extend the scope of risk factors to include potential psychosocial and workplace indicators for reduced work productivity such as job demands, job satisfaction and access to workplace adaptations. Once these factors have been evaluated, then can we develop targeted preventative workplace strategies to effectively reduce the burden of lost work productivity among people with chronic knee pain. Authors contributions All the authors were involved in drafting the article or revised the paper for important intellectual content, and all the authors approved the final version to be published. Ms Agaliotis had full access to all of the data in the study and takes full responsibility for the integrity of the data and accuracy of the data analysis.
1168
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
Study concept and design: Fransen, Jan, Agaliotis, Votrubec, Nairn. Acquisition of data: Agaliotis, Bridgett, Nairn, Votrubec, Fransen. Analysis and interpretation of data: Agaliotis, Bridgett, Heard, Fransen, Jan, Mackey. Drafting or revising critically for important intellectual content: Agaliotis, Bridgett, Fransen, Heard, Jan, Mackey, Nairn, Votrubec. Final approval of version to be submitted: Agaliotis, Bridgett, Fransen, Heard, Jan, Mackey, Nairn, Votrubec. Role of funding source The Long-term Evaluation of Glucosamine Sulfate (LEGS) study was funded by the National Health and Medical Research Council (NHMRC) of Australia, with some supplementary funding provided by Sanofi-Aventis Consumer Healthcare Pty Ltd. The study funders had no involvement in study design, collection, analysis and interpretation of the data; the writing of the manuscript or in the decision to submit the manuscript for publication.
11.
12. 13.
14.
15.
16.
Competing interests None of the authors have competing interests to declare. 17. Acknowledgements We thank the LEGS participants for their contributions to our research. We would also like to thank Dr Federica Barzi for her suggestions with the statistical analysis. This work was supported by Arthritis Australia (The Kevin R James Grant) awarded to Ms Maria Agaliotis. References 1. Busija L, Bridgett L, Williams SRM, Osborne RH, Buchbinder R, March L, et al. Osteoarthritis. Baillieres Best Pract Res Clin Rheumatol 2010;24:757e68. 2. Bookwala J, Harralson TL, Parmelee PA. Effects of pain on functioning and well-being in older adults with osteoarthritis of the knee. Psychol Aging 2003;18:844e50. 3. Hopman-Rock M, Kraaimaat FW, Bijlsma JW. Quality of life in elderly subjects with pain in the hip or knee. Qual Life Res 1997;6:67e76. 4. Muraki S, Akune T, Oka H, Mabuchi A, En-Yo Y, Yoshida M, et al. Association of occupational activity with radiographic knee osteoarthritis and lumbar spondylosis in elderly patients of population-based cohorts: a large-scale population-based study. Arthritis Rheum 2009;61:779e86. 5. Davis MA, Ettinger WH, Neuhaus JM, Mallon KP. Knee osteoarthritis and physical functioning: evidence from the NHANES I epidemiologic followup study. J Rheumatol 1991;18:591e8. 6. Guccione AA, Felson DT, Anderson JJ, Anthony JM, Zhang Y, Wilson PW, et al. The effects of specific medical conditions on the functional limitations of elders in the Framingham Study. Am J Public Health 1994;84:351e8. 7. McAlindon TE, Cooper C, Kirwan JR, Dieppe PA. Determinants of disability in osteoarthritis of the knee. Ann Rheum Dis 1993;52:258e62. 8. Peat G, McCarney R, Croft P. Knee pain and osteoarthritis in older adults: a review of community burden and current use of primary health care. Ann Rheum Dis 2001;60:91e7. 9. Anderson JJ, Felson DT. Factors associated with osteoarthritis of the knee in the first national Health and Nutrition Examination Survey (HANES I). Evidence for an association with overweight, race, and physical demands of work. Am J Epidemiol 1988;128:179e89. 10. Pincus T, Mitchell JM, Burkhauser RV. Substantial work disability and earnings losses in individuals less than age 65
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
with osteoarthritis: comparisons with rheumatoid arthritis. J Clin Epidemiol 1989;42:449e57. Zheltoukhova K, Bevan S, Reichi A. Fit for Work? Musculoskeletal Disorders and the Australian Labour Market. London, United Kingdom: The Work Foundation; 20121e85. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ 2003;81:646e56. Schultz AB, Edington DW, Schultz AB, Edington DW. Employee health and presenteeism: a systematic review. J Occup Rehabil 2007;17:547e79. Hubertsson J, Petersson IF, Thorstensson CA, Englund M. Risk of sick leave and disability pension in working-age women and men with knee osteoarthritis. Ann Rheum Dis 2013;72:401e5. Grotle M, Hagen KB, Natvig B, Dahl FA, Kvien TK. Prevalence and burden of osteoarthritis: results from a population survey in Norway. J Rheumatol 2008;35:677e84. Makela M, Heliovaara M, Sievers K, Knekt P, Maatela J, Aromaa A. Musculoskeletal disorders as determinants of disability in Finns aged 30 years or more. J Clin Epidemiol 1993;46:549e59. Fautrel B, Hilliquin P, Rozenberg S, Allaert FA, Coste P, Leclerc A, et al. Impact of osteoarthritis: results of a nationwide survey of 10,000 patients consulting for OA. Joint Bone Spine Revue du Rhumatisme 2005;72:235e40. Sayre EC, Li LC, Kopec JA, Esdaile JM, Bar S, Cibere J. The effect of disease site (knee, hip, hand, foot, lower back or neck) on employment reduction due to osteoarthritis. PLoS ONE 2010;5: e10470, http://dx.doi.org/10.1371/journal.pone.0010470. Accessed 05.12.12. Hermans J, Koopmanschap MA, Bierma-Zeinstra SMA, van Linge JH, Verhaar JAN, Reijman M, et al. Productivity costs and medical costs among working patients with knee osteoarthritis. Arthritis Care Res 2012;64:853e61. Bieleman HJ, Oosterveld FG, Oostveen JC, Reneman MF, Groothoff JW. Work participation and health status in early osteoarthritis of the hip and/or knee: a comparison between the Cohort Hip and Cohort Knee and the Osteoarthritis Initiative. Arthritis Care Res 2010;62:683e9. Hutchings A, Calloway M, Choy E, Hooper M, Hunter DJ, Jordan JM, et al. The Longitudinal Examination of Arthritis Pain (LEAP) study: relationships between weekly fluctuations in patient-rated joint pain and other health outcomes. J Rheumatol 2007;34:2291e300. Buckland-Wright JC, Wolfe F, Ward RJ, Flowers N, Hayne C. Substantial superiority of semiflexed (MTP) views in knee osteoarthritis: a comparative radiographic study, without fluoroscopy, of standing extended, semiflexed (MTP), and schuss views. J Rheumatol 1999;26:2664e74. Lin C-WC, March L, Crosbie J, Crawford R, Graves S, Naylor J, et al. Maximum recovery after knee replacementethe MARKER study rationale and protocol. BMC Musculoskelet Disord 2009;10:69. Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics 1993;4:353e65. Sanderson K, Andrews G. The SF-12 in the Australian population: cross-validation of item selection. Aust New Zealand J Public Health 2002;26:343e5. Andrews G. A brief integer scorer for the SF-12: validity of the brief scorer in Australian community and clinic settings. Aust New Zealand J Public Health 2002;26:508e10. Sangha O, Stucki G, Liang MH, Fossel AH, Katz JN. The SelfAdministered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum 2003;49:156e63.
M. Agaliotis et al. / Osteoarthritis and Cartilage 21 (2013) 1160e1169
28. Reichmann WM, Katz JN, Kessler CL, Jordan JM, Losina E. Determinants of self-reported health status in a populationbased sample of persons with radiographic knee osteoarthritis. Arthritis Rheum 2009;61:1046e53. 29. Kellgren JH, Lawrence JS. Radiological assessment of osteoarthrosis. Ann Rheum Dis 1957;16:494e502. 30. Lequesne M. Indices of severity and disease activity for osteoarthritis. Semin Arthritis Rheum 1991;20:48e54. 31. Armstrong TBA, Davies J. Physical Activity Patterns of Australian Adults. Results of the 1999 National Physical Activity Survey. Canberra, Australia: Australian Institute of Health and Welfare; 20001e68. 32. ANZSCO e Australian and New Zealand Standard Classification of Occupations. First edn. Revision 1. Canberra: Australian Bureau of Statistics (ABS); 2009. Available at: http://www.abs. gov.au/ausstats/[email protected]/mf/1220.0. 33. Auleley GR, Giraudeau B, Baron G, Maillefert JF, Dougados M, Ravaud P, et al. The methods for handling missing data in clinical trials influence sample size requirements. J Clin Epidemiol 2004;57:447e53. 34. Leardini G, Salaffi F, Caporali R, Canesi B, Rovati L, Montanelli R, et al. Direct and indirect costs of osteoarthritis of the knee. Clin Exp Rheumatol 2004;22:699e706.
1169
35. Woo J, Lau E, Lau CS, Lee P, Zhang J, Kwok T, et al. Socioeconomic impact of osteoarthritis in Hong Kong: utilization of health and social services, and direct and indirect costs. Arthritis Rheum 2003;49:526e34. 36. Merx H, Dreinhofer KE, Gunther KP. Socioeconomic relevance of osteoarthritis in Germany. Z Orthopadie Unfallchirurgie 2007;145:421e9. 37. Gupta S, Hawker GA, Laporte A, Croxford R, Coyte PC. The economic burden of disabling hip and knee osteoarthritis (OA) from the perspective of individuals living with this condition. Rheumatology 2005;44:1531e7. 38. Australian Bureau of Statistics (ABS). Gender Indicators, Australia; Jan 2013. Catalogue No: 4125.0. Available at: http:// www.abs.gov.au/ausstats/[email protected]/mf/4125.0. 39. Zhang W, Nuki G, Moskowitz RW, Abramson S, Altman RD, Arden NK, et al. OARSI recommendations for the management of hip and knee osteoarthritis: part III: changes in evidence following systematic cumulative update of research published through January 2009. Osteoarthritis Cartilage 2010;18:476e99. 40. Beaton D, Bombardier C, Escorpizo R, Zhang W, Lacaille D, Boonen A, et al. Measuring worker productivity: frameworks and measures. J Rheumatol 2009;36:2100e9.