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Keywords:

  • Arthritis;
  • Pain exacerbation;
  • Productivity

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Objective

To estimate the prevalence of arthritis and arthritis pain exacerbations in US workers including impact on functioning and lost productive work time (LPT).

Methods

The research was conducted as a nested case-control study of participants in the Caremark American Productivity Audit, a US national random-digit-dial survey of US workers. The sample included 329 workers ages 40–65 years meeting the First National Health and Nutrition Examination Survey criteria for arthritis, and 91 workers not meeting arthritis inclusion criteria. Participants completed a telephone interview to measure the prevalence of arthritis and pain exacerbations, LPT (in hours and dollars), functional disability using the Western Ontario and McMaster Universities Knee and Hip Osteoarthritis Index (WOMAC) and the Australian/Canadian Osteoarthritis Hand Index, and demographics.

Results

The prevalence of arthritis in US workers ages 40–65 years was 14.7% during the 2-week period. Pain exacerbation occurred among 38% of participants with arthritis. Workers with pain exacerbations were significantly more likely to have higher WOMAC scores (38.6 versus 29.6; P = 0.0041) and report arthritis-related LPT (24.4% versus 13.3%; P = 0.0118) than workers without exacerbations. Among those with LPT, average LPT did not differ (4.1 hours per week) between persons with and without exacerbations. The estimated annual LPT cost from arthritis in the US workforce was $7.11 billion, with 65.7% of this cost attributed to the 38% of workers with pain exacerbations.

Conclusion

Workers with arthritis pain exacerbation account for a disproportionate share of the arthritis-related LPT cost. Stratifying workers for appropriate treatment management based on pain exacerbation status could significantly decrease arthritis-related LPT and offer employees and employers an effective return on health care use.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Arthritis affects 15% of US adults (1) and is associated with increased disability (2–4), direct medical care costs (3, 5–9), underemployment (10), earnings losses (5, 6), and lost productive work time (LPT) (11). Arthritis occurs at all ages, increases in prevalence with age, and is common in working adults, especially those 35–64 years of age (1). As arthritis prevalence increases during the next 15 years, it is likely to be a dominant and costly source of LPT, as workers ages 35–64 are at the peak of their earning potential. Employers will face increasing financial challenges from overt medical care costs and even more substantial LPT costs attributable to arthritis. Understanding and defining subgroups of the workforce that account for the greatest share of the LPT costs will facilitate the optimization of stratified and targeted treatment management strategies and will make the most effective use of health care expenditures.

Pain intensity, persistence, chronicity, and exacerbation are key dimensions of variability in the pain experience. Much is known about the independent impact of pain chronicity and intensity (12–15), but not pain exacerbation. Clinically, pain exacerbations or flareups are known to occur independent of pain persistence or chronicity among a minority of individuals with arthritis (16, 17). However, little is known about the individual impact of this dimension of the pain experience. In this study, we examine the relationship between arthritis pain exacerbation and LPT in a random sample of the US workforce.

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The Caremark American Productivity Audit (i.e., audit) is a US national, population-based, random-digit-dial telephone survey that measures the relationship between health and productive work time (18). The arthritis study was designed as a case-control study nested within the audit survey and focused specifically on workers with arthritis. The arthritis study, conducted in the subset of productivity audit respondents interviewed between November 12, 2003 and February 16, 2004, aimed to more accurately estimate LPT costs from arthritis and understand variability in pain experience and associated LPT. The audit and the Caremark Work and Health Interview (questionnaire administered in the audit) are documented elsewhere (18–20) and described briefly below. The Essex Institutional Review Board (Lebanon, NJ) approved the protocol and data collection instrument. Oral informed consent was obtained from each participant before initiating the interview.

Audit and Work and Health Interview.

Audit households were randomly selected from residences with telephones in the 48 contiguous states and the District of Columbia. Residents were eligible if they were 18–65 years of age, a permanent member of the household contacted, and responded affirmatively to the Current Population Survey (CPS) question on current employment status (21). The Caremark Work and Health Interview measures health-related LPT including absenteeism and presenteeism (i.e., reduced performance while at work) in the previous 2 weeks (19, 20). It also captures information on employment status, occupational characteristics, various health conditions (e.g., pain, digestive problems, respiratory conditions, diabetes, heart disease), lifestyle factors (e.g., tobacco use, alcohol consumption), and demographic characteristics including annual salary.

The arthritis study.

The arthritis study comprised workers with arthritis (cases) and a group-matched random sample of workers without arthritis (controls). Both cases and controls could have reported other health conditions in the previous 2 weeks. Participants completed the audit interview and a supplemental interview conducted immediately following the audit interview. Participants selected for this study (Figure 1) were 40–65 years of age, worked for pay or profit in the week before the interview, and screened positive for symptomatic or controlled (i.e., symptoms effectively relieved by medication) arthritis in the previous 2 weeks. Among 3,560 employed participants ages 40–65 years, 648 screened positive for symptomatic (85.3%) or controlled (14.7%) arthritis and completed the supplemental interview. A total of 338 employed audit participants screened negative for arthritis and completed the supplemental interview. The 338 respondents who screened negative comprised 239 individuals who were participating in a concurrent back pain study and a group-matched, stratified (by age, sex, and date of interview), random sample (1:10) of 99 audit participants who screened negative for both arthritis and back pain. The participation rate was 67%.

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Figure 1. Identification and selection of the analytic sample for the arthritis study.

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The supplemental interview included questions from the First National Health and Nutrition Examination Survey (NHANES-I) Pain Screening and Arthritis Supplement sections (22) to establish the presence of clinically meaningful arthritis or joint pain during the recall period, determine lifetime occurrence of pain or aching in any joint lasting at least 1 month, and characterize pain and evaluate pain flareups. It also included the Western Ontario and McMaster Universities Knee and Hip Osteoarthritis Index (WOMAC) version LK3.1 (23) and the Australian/Canadian Osteoarthritis Hand Index (AUSCAN) version LK3.1 (24) to assess functional impairment.

NHANES-I criteria were used to define clinically meaningful arthritis (hereafter, “arthritis”) as arthritis or joint pain on most days for at least 1 month during the previous year. A total of 295 (45.5%) respondents who screened positive for symptomatic or controlled arthritis met NHANES-I criteria for arthritis, as did 34 (10.1%) of the 338 workers who screened negative (Figure 1). These 329 respondents with arthritis comprised the case group for analysis. A comparison group of 91 workers who did not meet criteria for arthritis or back pain was selected as a nonpain comparison group.

Defining pain experience and functional impairment.

Arthritis pain experience was defined by location, frequency and intensity, and occurrence and severity of exacerbations in the previous 2 weeks. Pain exacerbations were defined as a self-reported flare severity rating of at least a 2-point increase over usual pain severity on a 0–10 scale where 0 = “no pain” and 10 = “pain as bad as it could be.” The latter was based on an evaluation of frequency distributions and the correlation between pain flare duration and severity data, sensitivity analyses to determine appropriate cut points based on number and severity of qualifying pain flares, and clinical judgment.

The WOMAC and AUSCAN provide indices of arthritis-specific pain, disability, and joint stiffness on a 5-point scale (where 0 = none and 4 = extreme). Dimension-specific scores were calculated by adding scores for the individual items in each subscale. Total scores were calculated by summing the 3 dimension-specific scores (23, 24). Subscale scores and total scores were normalized to a maximum score of 100.

Statistical analysis.

Analyses were completed to estimate the prevalence of arthritis and arthritis-related LPT costs in the US workforce. Workers with arthritis were categorized by the presence or absence of pain exacerbations as described previously. Prevalence was derived by calculating age- and sex-specific prevalence based on the sample of workers who screened positive and negative for arthritis pain, and by projecting sample estimates to the US workforce 40–65 years of age using a previously described benchmarking procedure (20).

LPT was derived from the Work and Health Interview as described previously (11, 18). Arthritis-related LPT was confined to pain-related LPT specifically due to arthritis or joint pain only. LPT in workers with arthritis and the nonpain comparison group was calculated as total LPT for any health-related reason. Excess LPT attributed to arthritis was defined as the difference in total annual LPT for any health-related reason in workers with arthritis compared with the total annual LPT in the nonpain comparison group. Total LPT in the nonpain comparison group was estimated by applying sex-specific rates of LPT from workers in this group to the corresponding subgroups of individuals with arthritis. Lost labor costs were derived from lost productive hours and self-reported annual income. Hourly wage was calculated by dividing annual income by the self-reported mean number of hours worked per week and multiplying by 52 weeks. Lost dollars were estimated by multiplying lost hours by the hourly wage.

A 2-step weighting method accounted for selective participation (i.e., noncoverage and nonresponse) (18). In the first step, a weight was applied to individuals to account for the unequal probability of selecting households. In the second step, a population weighting adjustment accounted for selection bias due to incomplete coverage of the US population and ensured that estimates of certain sample demographic subgroups' totals conformed to the CPS, an external database providing high-quality data on a nationally representative sample of the US workforce. A raking method was used for the population weighting adjustment, benchmarking to 4 variables common to both the productivity audit and the CPS. Benchmarking and weighting variables with missing data (i.e., 13.0%, with 80% of these attributed to missing number of phone lines into the house) were imputed using the age- and sex-specific mode for categorical variables, and the age- and sex-specific median for continuous variables. If 1 of the 5 variables used in the calculation of presenteeism was missing, the mean value of the remaining 4 variables was substituted, reducing the proportion with missing presenteeism estimates from 2.0% to 0.7%. Salary information was missing for 9.7% of all respondents. Regression modeling, which included sex, age, race, education, region of residence, job code, and duration in job, was used to reduce missing salary information to 0.1%. SAS version 8.2 software (SAS Institute, Cary, NC) was used for all analyses. Wesvar version 4 statistical software (Westat, Rockville, MD) was used to perform the raking adjustments. A P value less than 0.05 was used to determine statistical significance.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Arthritis cases and controls did not differ significantly from their counterparts without arthritis by age, sex, race, education, or occupation; however, arthritis cases were significantly more likely than controls to work part time (25.5% versus 15.4%) in a low-demand/high-control job (13.7% versus 3.3%) that paid <$30,000 per year (46.8% versus 27.5%) (Table 1). Most respondents were 50–59 years of age (50.0%), female (69.8%), white (88.6%), educated beyond high school (69.2%), and working in white-collar occupations (68.0%).

Table 1. Distribution of the sample of employed American productivity audit respondents, by selected demographic, health, and employment characteristics*
Characteristic, categoriesArthritis (n = 329)Nonpain controls (n = 91)PPain exacerbation status
Present (n = 124)Absent (n = 205)P
  • *

    Values are the number (percentage) unless otherwise indicated. GED/HS = general education development test/high school.

  • Chi-square statistic (P value) measures the difference between respondents with arthritis and nonpain controls.

  • Chi-square statistic (P value) measures the difference between respondents with and without pain exacerbations.

  • §

    White collar = professional, administrative, or support-type occupations; blue collar = trade or labor occupations (27).

  • Occupations were categorized by job demand and job control characteristics based on Karasek et al (28).

Sex  0.1573  0.9141
 Male94 (28.57)33 (36.26) 35 (28.23)59 (28.78) 
 Female235 (71.43)58 (63.74) 89 (71.77)146 (71.22) 
Age, years  0.6134  0.2004
 40–49112 (34.04)36 (39.56) 46 (37.10)66 (32.20)
 50–59168 (51.07)42 (46.15) 65 (52.42)103 (50.24)
 60–6549 (14.89)13 (14.29) 13 (10.48)36 (17.56) 
Sex and age, years  0.5276  0.1990
 Male, 40–4925 (7.60)12 (13.19) 12 (9.68)13 (6.34) 
 Male, 50–5954 (16.41)15 (16.48) 17 (13.71)37 (18.05) 
 Male, 60–6515 (4.56)6 (6.59) 6 (4.84)9 (4.39) 
 Female, 40–4987 (26.44)24 (26.37) 34 (27.42)53 (25.85) 
 Female, 50–59114 (34.66)27 (29.68) 48 (38.70)66 (32.20) 
 Female, 60–6534 (10.33)7 (7.69) 7 (5.65)27 (13.17) 
Race  0.2974  0.3795
 White292 (88.75)73 (80.22) 109 (87.90)183 (89.27) 
 African American22 (6.69)9 (9.89) 11 (8.87)11 (5.37) 
 Other11 (3.34)5 (5.49) 3 (2.42)8 (3.90) 
 Not stated4 (1.22)4 (4.40) 1 (0.81)3 (1.46) 
Formal education  0.0679  0.0917
 <12th grade25 (7.60)2 (2.20) 9 (7.26)16 (7.80) 
 GED/HS graduate85 (25.83)17 (18.68) 35 (28.23)50 (24.40) 
 Some college83 (25.23)21 (23.08) 39 (31.44)44 (21.46) 
 Associate degree25 (7.60)5 (5.49) 11 (8.87)14 (6.83) 
 College degree63 (19.15)27 (29.67) 18 (14.52)45 (21.95) 
 Graduate degree48 (14.59)18 (19.78) 12 (9.68)36 (17.56) 
 Not stated0 (0.00)1 (1.10) 0 (0.00)0 (0.00) 
Annual salary  0.0228  0.8881
 <$10,00039 (11.85)6 (6.59) 12 (9.68)27 (13.17) 
 $10,000–$19,99959 (17.93)6 (6.59) 23 (18.55)36 (17.56) 
 $20,000–$29,99956 (17.02)13 (14.29) 22 (17.74)34 (16.59) 
 $30,000–$39,99948 (14.59)14 (15.38) 20 (16.13)28 (13.66) 
 $40,000–$49,99934 (10.33)16 (17.58) 14 (11.29)20 (9.76) 
 ≥$50,00089 (27.06)32 (35.17) 31 (25.00)58 (28.28) 
 Not stated4 (1.22)4 (4.40) 2 (1.61)2 (0.98) 
Employment status  0.0428  0.0823
 Full time245 (74.47)77 (84.62) 99 (79.84)146 (71.22) 
 Part time84 (25.53)14 (15.38) 25 (20.16)59 (28.78) 
Type of occupation§  0.0638  0.0818
 White collar213 (64.74)67 (73.62) 73 (58.87)140 (68.30) 
 Blue collar111 (33.74)21 (23.08) 49 (39.52)62 (30.24) 
 Not stated5 (1.52)3 (3.30) 2 (1.61)3 (1.46) 
Job demand/control  0.0253  0.0148
 High/high139 (42.25)37 (40.66) 65 (52.42)74 (36.10) 
 High/low111 (33.74)41 (45.05) 33 (26.61)78 (38.04) 
 Low/high45 (13.68)3 (3.30) 18 (14.52)27 (13.17) 
 Low/low33 (10.03)9 (9.89) 8 (6.45)25 (12.20) 
 Not stated1 (0.30)1 (1.10) 0 (0.00)1 (0.49) 

Respondents with and without arthritis pain exacerbations differed only by job demand/control, where jobs designated as high demand/high control were more common among those with exacerbations (52.4%) (Table 1).

Prevalence of arthritis.

The prevalence of arthritis in US workers 40–65 years of age was 14.7% during the 2-week period (Table 2), and 37.9% had exacerbating pain. Arthritis was significantly more prevalent in women than men (18.8% versus 11.0%), in workers ages 50–59 years (18.9%), and in those with less formal education and lower annual salary. Prevalence was 2 times higher in workers with a high school education or less compared with those with a college degree, and in workers earning <$20,000 per year compared with those earning ≥$20,000 per year. Arthritis was significantly more prevalent in adults working part time than those working full time (23.5% versus 13.1%) and in adults in low-demand/high-control jobs (32.4%) compared with workers in the other 3 job demand/control categories. Arthritis with pain exacerbation was significantly more prevalent in women than in men (7.3% versus 4.1%) and in workers in low-demand/high-control occupations compared with the 3 other job demand/control categories (11.4% versus ≤6.8%).

Table 2. Prevalence of arthritis and arthritis pain exacerbations in the US workforce 40–65 years of age (67.7 million individuals), by selected demographic and employment characteristics*
Characteristic, categoriesAll arthritisArthritis with pain exacerbations
% (95% CI)P% (95% CI)P
  • *

    Estimates benchmarked to the US workforce using an iterative proportional fitting procedure described in the Methods section. 95% CI = 95% confidence interval; GED/HS = general education development test/high school.

  • Chi-square statistic (P value) measures the difference between characteristic categories.

  • Chi-square statistic (P value) measures the difference in prevalence estimates among categories by pain exacerbation status.

  • §

    White collar = professional, administrative, or support-type occupations; blue collar = trade or labor occupations (27).

  • Occupations were categorized by job demand and job control characteristics based on Karasek et al (28).

Total US workforce14.65 (12.04–17.26)5.56 (4.15–6.96)0.1293
Sex 0.0006 0.0289
 Male11.02 (7.69–14.35) 4.06 (2.39–5.72) 
 Female18.76 (14.15–23.36) 7.25 (4.81–9.70) 
Age, years 0.0150 0.4773
 40–4911.73 (8.39–15.07) 4.81 (2.72–6.90) 
 50–5918.91 (14.49–23.33) 6.76 (4.64–8.88) 
 60–6515.04 (5.57–24.51) 5.37 (1.18–9.56) 
Sex and age, years 0.0005 0.1785
 Male, 40–496.68 (3.29–10.07) 3.11 (0.94–5.27) 
 Male, 50–5917.19 (9.29–25.08) 4.80 (1.64–7.95) 
 Male, 60–6512.94 (4.00–21.88) 5.99 (0.54–11.43) 
 Female, 40–4917.78 (11.33–24.23) 6.86 (3.22–10.49) 
 Female, 50–5920.75 (14.60–26.89) 8.85 (5.51–12.18) 
 Female, 60–6517.28 (3.02–31.53) 4.71 (0.00–10.37) 
Race 0.2328 0.4696
 White15.61 (12.33–18.89) 6.03 (4.21–7.85) 
 African American9.49 (1.55–17.42) 4.49 (0.38–8.59) 
 Other12.02 (1.65–22.39) 2.43 (0.00–6.22) 
Formal education 0.0381 0.0640
 <12th grade26.59 (5.06–48.12) 8.28 (0.00–17.31) 
 GED/HS graduate17.00 (10.20–23.81) 7.47 (3.24–11.70) 
 Some college15.54 (9.79–21.29) 6.78 (3.15–10.41) 
 Associate degree20.21 (5.05–35.36) 10.45 (2.10–18.80) 
 College degree10.44 (5.00–15.87) 2.51 (0.52–4.49) 
 Graduate degree12.15 (5.56–18.73) 3.77 (0.97–6.58) 
Annual salary 0.0013 0.2679
 <$10,00025.63 (11.75–39.51) 9.41 (0.68–18.14) 
 $10,000–$19,99924.61 (2.69–46.53) 9.32 (0.00–19.33) 
 $20,000–$29,99912.73 (5.96–19.50) 4.94 (1.73–8.16) 
 $30,000–$39,99913.80 (5.08–22.52) 5.16 (2.02–8.31) 
 $40,000–$49,99912.84 (6.73–18.94) 5.59 (2.30–8.87) 
 ≥$50,00011.23 (7.51–14.95) 4.17 (1.99–6.35) 
Employment status 0.0009 0.3408
 Full time13.06 (10.74–15.37) 5.26 (3.87–6.65) 
 Part time23.50 (11.91–35.09) 7.19 (2.73–11.66) 
Type of occupation§ 0.1843 0.0830
 White collar13.57 (10.23–16.91) 4.63 (3.26–6.00)
 Blue collar16.70 (12.37–21.04) 7.29 (4.49–10.09) 
Job demand/control 0.0001 0.0215
 High/high13.36 (9.26–17.47) 6.84 (4.20–9.48) 
 High/low12.13 (7.75–16.51) 3.24 (1.85–4.64) 
 Low/high32.35 (21.15–43.55) 11.38 (5.00–17.76) 
 Low/low18.99 (9.85–28.13) 4.55 (0.00–10.09) 

Pain experience.

The hip or knee (88.5%) and hand (23.4%) were the most commonly reported sites of arthritis pain. Almost 60% reported having arthritis pain every day in the previous 2 weeks, and 37.9% reported pain exacerbation in the previous 2 weeks. Workers with and without arthritis pain exacerbations did not differ significantly by pain frequency. Workers with arthritis exacerbations reported an average of 4.8 pain flares (95% confidence interval [95% CI] 3.6–6.1) per 2-week period lasting 2.8 days (95% CI 1.6–4.1). Among this group, mean pain severity in the absence of a pain flare was 2.9 (95% CI 2.4–3.4) on a 0–10 scale (where 0 = no pain and 10 = pain as bad as it could be) and with pain exacerbation, the pain was 6.4 (95% CI 5.9–6.9). Those without pain exacerbations reported a mean arthritis severity of 4.1 (95% CI 3.7–4.5).

Functional impairment.

The normalized mean total WOMAC score of workers with hip or knee arthritis was 34.3; the normalized mean total AUSCAN score for those with hand arthritis was 41.0 (Table 3). Scores indicated that workers with arthritis experienced moderate pain and physical dysfunction, on average. Workers with hand arthritis reported more pain, on average, than workers with hip or knee arthritis (Table 3). Workers with hip or knee pain exacerbations reported significantly more pain (42.2 versus 33.7), stiffness (48.7 versus 38.8), and impaired physical functioning (38.6 versus 29.0) than workers without pain exacerbations. No such relationship was found in workers with hand arthritis (Table 3).

Table 3. Mean functional impairment due to arthritis in the US workforce as measured by the WOMAC and the AUSCAN*
ScalePain exacerbation statusAll arthritis/joint pain
PresentAbsentP
  • *

    Values are the mean (95% confidence interval) unless otherwise indicated. WOMAC = Western Ontario and McMaster Universities Knee and Hip Osteoarthritis Index; AUSCAN = Australian/Canadian Osteoarthritis Hand Index.

  • t statistic (P value) measures the difference between workers with and without pain exacerbations.

  • Arthritis pain in the knee or hip; raw scores normalized to a maximum score of 100.

  • §

    Arthritis pain in the hand; raw scores normalized to a maximum score of 100; estimates of WOMAC and AUSCAN scores were benchmarked to the US workforce using an iterative proportional fitting procedure described in the Subjects and Methods section.

WOMAC    
 Pain42.20 (38.20–46.20)33.72 (29.70–37.73)0.009836.87 (34.06–39.68)
 Stiffness48.73 (43.02–54.43)38.84 (34.82–42.87)0.016942.52 (39.52–45.52)
 Physical function38.58 (34.68–42.48)28.97 (24.49–33.45)0.005232.55 (29.36–35.73)
 Total40.18 (36.47–43.90)30.78 (26.67–34.89)0.004134.28 (31.37–37.18)
AUSCAN§    
 Pain50.61 (44.08–57.14)46.16 (39.56–52.75)0.388748.07 (43.96–52.18)
 Stiffness43.94 (34.38–53.50)44.94 (37.50–52.39)0.864244.51 (38.65–50.37)
 Physical function35.19 (27.60–42.77)37.75 (30.94–44.56)0.654836.65 (32.55–40.75)
 Total40.91 (34.54–47.28)41.03 (34.63–47.44)0.981240.98 (37.42–44.54)

Lost productive time and national cost estimates.

Overall, 17.5% of participants with arthritis lost productive work time due to arthritis (Table 4). Most LPT occurred at work (mean 3.48 hours per worker per week) rather than as time absent from work (mean 0.57 hours per worker per week). Workers with arthritis pain exacerbations were significantly more likely to lose productive time due to arthritis than workers without exacerbations (24.4% versus 13.3%) (Table 4). Workers with arthritis-related LPT lost an average of 4.1 hours per week with 85.9% attributed to reduced performance (Table 4). The presence of pain exacerbations was unrelated to average LPT per week (Table 4). LPT due to arthritis costs US employers an estimated $7.11 billion per year, with 71.9% ($5.11 billion) explained by reduced performance while at work (Table 4). Almost two-thirds of the total arthritis-specific LPT cost ($4.67 billion) occurs among workers with pain exacerbations (Table 4).

Table 4. Percent with lost productive work time (LPT), mean hours lost per week, and cost of LPT due to arthritis in the previous 2 weeks in the US workforce 40–65 years of age with arthritis*
Type of LPTAll arthritisPain exacerbation status
PresentAbsentP
  • *

    Estimates benchmarked to the US workforce using an iterative proportional fitting procedure described in the Methods section. 95% CI = 95% confidence interval.

  • Chi-square statistic (P value) measures the difference in prevalence between workers with and without pain exacerbations; t-test statistic (P value) measures the difference in means between workers with and without pain exacerbations.

  • Means only include workers with > 0 LPT due to arthritis or joint pain.

Total LPT    
 >0 total LPT, % (95% CI)17.48 (11.56–23.41)24.39 (13.74–35.05)13.34 (6.26–20.43)0.0118
 Hours lost, mean (95% CI) hours/worker/week4.05 (2.65–5.46)4.04 (1.91–6.17)4.07 (1.87–6.26)0.9846
 Cost, mean (95% CI) dollars/worker/week82.03 (14.85–149.22)104.65 (0.00–234.67)57.96 (22.00–93.93)0.4817
 Total cost (95% CI), $billions/year7.11 (1.77–12.44)4.67 (0.00–10.05)2.43 (0.57–4.29)
Absenteeism    
 >0 absenteeism, % (95% CI)1.15 (0.00–2.32)1.72 (0.00–3.64)0.79 (0.00–2.46)0.4443
 Hours lost, mean (95% CI) hours/worker/week0.57 (0.00–1.15)0.55 (0.00–1.21)0.59 (0.00–1.77)0.9375
 Cost, mean (95% CI) dollars/worker/week23.00 (0.00–54.66)36.20 (0.00–99.54)8.97 (0.00–24.03)0.4122
 Total cost (95% CI), $billions/year1.99 (0.00–4.59)1.62 (0.00–4.30)0.38 (0.00–0.99)
Presenteeism    
 >0 presenteeism, % (95% CI)16.82 (10.92–22.71)22.88 (12.51–33.25)13.11 (6.08–20.14)0.0171
 Hours lost, mean (95% CI) hours/worker/week3.48 (2.28–4.69)3.49 (1.79–5.20)3.47 (1.64–5.30)0.9843
 Cost, mean (95% CI) dollars/worker/week59.03 (22.00–96.06)68.46 (1.31–135.60)49.00 (19.55–78.44)0.5782
 Total cost (95% CI), $billions/year5.11 (2.16–8.07)3.06 (0.32–5.79)2.06 (0.47–3.64)

Comparing normalized total WOMAC scores of workers with >0 arthritis-related LPT with those of workers with no arthritis-related LPT in the previous 2 weeks, workers with >0 LPT were significantly more functionally impaired than their counterparts without LPT (WOMAC = 40.2, 95% CI 37.7–42.7 versus WOMAC = 25.8, 95% CI 21.5–30.1; P < 0.0001). The same pattern was also observed for the normalized WOMAC component-specific scores.

A total of 53.3% of workers with arthritis lost productive time for any health-related reason compared with 19.1% of controls (Table 5). Workers with arthritis were also more likely to miss work (14.7% versus 3.9%) and report reduced performance while at work (50.7% versus 18.9%) than controls (Table 5). Workers with arthritis were absent from work 3 times more, on average, than controls (1.7 hours per week versus 0.6 hours per week), and they lost ∼2 times more productive time, on average, than controls (5.4 hours per week versus 2.8 hours per week) (Table 5). Overall, workers with arthritis cost US employers an estimated $22.8 billion per year in health-related LPT, an excess of $15.96 billion per year when compared with workers with neither arthritis nor back pain (Table 5).

Table 5. Percent with lost productive work time (LPT), mean hours lost per week, and cost of LPT for any health-related reason in the previous 2 weeks in the US workforce 40–65 years of age with arthritis and a nonpain comparison group*
Type of LPTAll arthritisNonpain comparison groupP
  • *

    Estimates benchmarked to the US workforce using an iterative proportional fitting procedure described in the Subjects and Methods section. 95% CI = 95% confidence interval.

  • Chi-square statistic (P value) measures the difference in prevalence between workers with arthritis and the nonpain comparison group; t-test statistic (P value) measures the difference in means between workers with arthritis and the nonpain comparison group.

  • Means only include respondents with >0 LPT due to any health-related reason.

  • §

    Total cost for the nonpain comparison group was adjusted to reflect a population equivalent to arthritis cases in size and sex distribution.

  • Unable to estimate variance due to adjustment to reflect a population equivalent to arthritis cases in size and sex distribution.

Total LPT   
 >0 total LPT, % (95% CI)53.27 (43.88–62.66)19.10 (10.17–28.03)< 0.00001
 Hours lost, mean (95% CI) hours/worker/week5.35 (4.41–6.29)2.78 (0.42–5.15)0.0536
 Cost, mean (95% CI) dollars/worker/week83.49 (60.17–106.80)61.89 (4.51–119.26)0.4986
 Total cost (95% CI), $billions/year§22.82 (15.89–29.76)6.86
Absenteeism   
 >0 absenteeism, % (95% CI)14.67 (10.05–19.30)3.89 (0.00–7.94)0.0002
 Hours lost, mean (95% CI) hours/worker/week1.74 (1.28–2.19)0.57 (0.00–1.23)0.0108
 Cost, mean (95% CI) dollars/worker/week30.34 (16.65–44.03)12.31 (0.00–27.17)0.1114
 Total cost (95% CI), $billions/year§8.29 (4.34–12.25)1.42
Presenteeism   
 >0 presenteeism, % (95% CI)50.70 (41.53–59.87)18.89 (9.90–27.89)< 0.00001
 Hours lost, mean (95% CI) hours/worker/week3.62 (2.84–4.40)2.21 (0.23–4.20)0.2050
 Cost, mean (95% CI) dollars/worker/week53.15 (38.62–67.68)49.57 (0.87–98.28)0.8895
 Total cost (95% CI), $billions/year§14.53 (10.36–18.70)5.44

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Arthritis, often perceived as a condition of older adults who are not employed, leads to substantial covert costs to employers. In a previous study, we estimated that arthritis resulted in annual LPT costs of $10.3 billion, an estimate that included all age groups and levels of arthritis severity (11). In the current study of workers ages 40–65 years, NHANES-I criteria were used to improve the validity of arthritis case status and focus on more frequent and persistent pain. Our data suggest that this restricted subgroup accounts for a major share (i.e., $7.11 billion per year) of arthritis-related LPT, even without consideration of unemployment or underemployment. Individuals with arthritis are more likely to work part time and hold jobs characterized by low demand and high control.

Our arthritis prevalence estimate of 14.7% in workers 40–65 years of age is consistent with the National Arthritis Data Workgroup's 1995 estimate of ∼30% in all US adults 45–64 years of age (1) and reflects the difference in prevalence in an employed population compared with the general population. In the US workforce, there appears to be a selective loss of workers with arthritis with age, as we observed the prevalence of arthritis decrease from 18.9% in workers 50–59 years of age to 15.0% in workers 60–65 years of age. Based on results from the 1989–1991 US National Health Interview Survey (NHIS) conducted in the general US population, we expected the prevalence of arthritis to increase with age (25). Our observed higher prevalence of arthritis in women than in men was expected and is supported by NHIS survey results (25).

WOMAC scores were significantly higher in workers with arthritis pain exacerbations compared with workers without pain exacerbations, but AUSCAN scores were not. One possible reason for this is that pain was reported more commonly in the hip and/or knee than in the hand, and pain exacerbations would be more common in the former than the latter group. A second reason might be that the AUSCAN is less sensitive in detecting exacerbations of pain confined to the hand compared with the WOMAC relative to the hip or knee. Both of these instruments were originally developed for use as outcome measures in clinical trials and have not been used previously in this type of research setting. Hence, their clinometric properties might not be optimal for these purposes.

Arthritis pain exacerbation is common and accounts for a disproportionate share of LPT and LPT costs due to arthritis. Our data suggest that the impact is mediated by the greater proportion of workers with arthritis who lose work time, not by the average amount of productive time lost per worker. In chronic or persistent arthritis pain, exacerbating pain might occur in the natural course of the condition, might result from suboptimal clinical management, or might be attributed to other causes. The data from this study suggest that efforts directed to detecting individuals with exacerbating pain and reducing the frequency or severity of flareups could have a marked positive effect on the productivity of affected workers. Women, in particular, may benefit from these targeted efforts because they are more likely than men to experience arthritis pain exacerbation. Additional research is needed, however, to devise simple, valid, and reliable methods of detecting exacerbating pain and stratifying patients for appropriate treatment management.

This study does not offer a full account of the labor costs associated with arthritis. In particular, we have limited information on the risk of underemployment and unemployment associated with arthritis because questions to ascertain arthritis case status were administered only to individuals who reported working in the previous 7 days. Our study only offers a 2-week snapshot of the actively employed US workforce. However, even this limited view indicates that arthritis is associated with a greater likelihood of part-time work. We do not know when or how this occurs in the natural history of the condition, how long individuals have been in part-time status, or who is at greatest risk. It is also likely that arthritis is associated with an increased risk of unemployment. Longitudinal studies are better suited to quantify the risk and cost of underemployment and unemployment associated with arthritis.

This research has several limitations. First, although valid NHANES-I criteria were used to identify workers with arthritis in this study, our case definition was based on self-reported symptoms of arthritis and joint pain. Second, our LPT estimates did not take into consideration other costs such as the hiring and training of replacement workers, impact of coworkers' productivity, and employees' potentially forfeited leisure time (26). Finally, although participants were strategically selected as a population-based national random sample of the US workforce, the sample size from which all estimates were derived was modest. Inherent in the sample size for this study are the uncertainties associated with statistical confidence around all of our nationally projected estimates for arthritis pain and arthritis pain with and without exacerbations.

Arthritis is common in workers 40–65 years of age. Arthritis pain exacerbations occur frequently and have a substantial impact on work productivity. Workers with pain exacerbation account for a disproportionate share of the LPT cost from arthritis pain. Appropriate treatment of pain exacerbations could have a significant positive impact on the productivity of US workers.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The authors thank Thomas Sarosky, Bernita Williams, and Amy Lorandeau at Caremark for their contributions to this research.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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